--- OA_place: publisher OA_type: hybrid _id: '18952' abstract: - lang: eng text: 'A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern. The use of CSP in the prediction of likely cocrystal stoichiometry was also explored, demonstrating multiple possible approaches. Crystallographic disorder emerged as an important theme throughout the test as both a challenge for analysis and a major achievement where two groups blindly predicted the existence of disorder for the first time. Additionally, large-scale comparisons of the sets of predicted crystal structures also showed that some methods yield sets that largely contain the same crystal structures.' acknowledgement: "The CCDC Blind Test Team. The CCDC organizers (L. M. Hunnisett, J. Nyman, N. Francia, I. Sugden, G. Sadiq, and J. C. Cole) gratefully acknowledge numerous CCDC colleagues for\r\ntheir helpful feedback and suggestions on the manuscript (P. McCabe, E. Pidcock, P. Martinez-Bulit, C. Kingsbury), providing useful python knowledge (A. Moldovan), providing and maintaining internal compute resources (K. Taylor, M. Burling, J. Swift, L. Wallis), monitoring and depositing structures in the CSD (S. Ward, K. Orzechowska, V. Menon), support in organization of the blind test meeting (E. Clarke),and improvements to the Crystal Packing Similarity tool (M.\r\nRead). Data analysis was performed using resources provided by the Cambridge Service for Data Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/T022159/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk). N. Francia thanks M. Salvalaglio for advice on the metadynamics simulations and the University College London for providing access to the Kathleen High Performance Computing Facility Kathleen@UCL) on which simulations were performed. N. Francia also thanks V. Kurlin and D. E. Widdowson for counselling on crystal structure similarity. I. Sugden and N. Francia participated in the blind test as members of Groups 1 and 24, respectively. They were involved in the analysis of the results.\r\nand in writing this paper only after all results were made\r\navailable to participants." article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Lily M. full_name: Hunnisett, Lily M. last_name: Hunnisett - first_name: Jonas full_name: Nyman, Jonas last_name: Nyman - first_name: Nicholas full_name: Francia, Nicholas last_name: Francia - first_name: Nathan S. full_name: Abraham, Nathan S. last_name: Abraham - first_name: Claire S. full_name: Adjiman, Claire S. last_name: Adjiman - first_name: Srinivasulu full_name: Aitipamula, Srinivasulu last_name: Aitipamula - first_name: Tamador full_name: Alkhidir, Tamador last_name: Alkhidir - first_name: Mubarak full_name: Almehairbi, Mubarak last_name: Almehairbi - first_name: Andrea full_name: Anelli, Andrea last_name: Anelli - first_name: Dylan M. full_name: Anstine, Dylan M. last_name: Anstine - first_name: John E. full_name: Anthony, John E. last_name: Anthony - first_name: Joseph E. full_name: Arnold, Joseph E. last_name: Arnold - first_name: Faezeh full_name: Bahrami, Faezeh last_name: Bahrami - first_name: Michael A. full_name: Bellucci, Michael A. last_name: Bellucci - first_name: Rajni M. full_name: Bhardwaj, Rajni M. last_name: Bhardwaj - first_name: Imanuel full_name: Bier, Imanuel last_name: Bier - first_name: Joanna A. full_name: Bis, Joanna A. last_name: Bis - first_name: A. Daniel full_name: Boese, A. Daniel last_name: Boese - first_name: David H. full_name: Bowskill, David H. last_name: Bowskill - first_name: James full_name: Bramley, James last_name: Bramley - first_name: Jan Gerit full_name: Brandenburg, Jan Gerit last_name: Brandenburg - first_name: Doris E. full_name: Braun, Doris E. last_name: Braun - first_name: Patrick W. V. full_name: Butler, Patrick W. V. last_name: Butler - first_name: Joseph full_name: Cadden, Joseph last_name: Cadden - first_name: Stephen full_name: Carino, Stephen last_name: Carino - first_name: Eric J. full_name: Chan, Eric J. last_name: Chan - first_name: Chao full_name: Chang, Chao last_name: Chang - first_name: Bingqing full_name: Cheng, Bingqing id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9 last_name: Cheng orcid: 0000-0002-3584-9632 - first_name: Sarah M. full_name: Clarke, Sarah M. last_name: Clarke - first_name: Simon J. full_name: Coles, Simon J. last_name: Coles - first_name: Richard I. full_name: Cooper, Richard I. last_name: Cooper - first_name: Ricky full_name: Couch, Ricky last_name: Couch - first_name: Ramon full_name: Cuadrado, Ramon last_name: Cuadrado - first_name: Tom full_name: Darden, Tom last_name: Darden - first_name: Graeme M. full_name: Day, Graeme M. last_name: Day - first_name: Hanno full_name: Dietrich, Hanno last_name: Dietrich - first_name: Yiming full_name: Ding, Yiming last_name: Ding - first_name: Antonio full_name: DiPasquale, Antonio last_name: DiPasquale - first_name: Bhausaheb full_name: Dhokale, Bhausaheb last_name: Dhokale - first_name: Bouke P. full_name: van Eijck, Bouke P. last_name: van Eijck - first_name: Mark R. J. full_name: Elsegood, Mark R. J. last_name: Elsegood - first_name: Dzmitry full_name: Firaha, Dzmitry last_name: Firaha - first_name: Wenbo full_name: Fu, Wenbo last_name: Fu - first_name: Kaori full_name: Fukuzawa, Kaori last_name: Fukuzawa - first_name: Joseph full_name: Glover, Joseph last_name: Glover - first_name: Hitoshi full_name: Goto, Hitoshi last_name: Goto - first_name: Chandler full_name: Greenwell, Chandler last_name: Greenwell - first_name: Rui full_name: Guo, Rui last_name: Guo - first_name: Jürgen full_name: Harter, Jürgen last_name: Harter - first_name: Julian full_name: Helfferich, Julian last_name: Helfferich - first_name: Detlef W. M. full_name: Hofmann, Detlef W. M. last_name: Hofmann - first_name: Johannes full_name: Hoja, Johannes last_name: Hoja - first_name: John full_name: Hone, John last_name: Hone - first_name: Richard full_name: Hong, Richard last_name: Hong - first_name: Geoffrey full_name: Hutchison, Geoffrey last_name: Hutchison - first_name: Yasuhiro full_name: Ikabata, Yasuhiro last_name: Ikabata - first_name: Olexandr full_name: Isayev, Olexandr last_name: Isayev - first_name: Ommair full_name: Ishaque, Ommair last_name: Ishaque - first_name: Varsha full_name: Jain, Varsha last_name: Jain - first_name: Yingdi full_name: Jin, Yingdi last_name: Jin - first_name: Aling full_name: Jing, Aling last_name: Jing - first_name: Erin R. full_name: Johnson, Erin R. last_name: Johnson - first_name: Ian full_name: Jones, Ian last_name: Jones - first_name: K. V. Jovan full_name: Jose, K. V. Jovan last_name: Jose - first_name: Elena A. full_name: Kabova, Elena A. last_name: Kabova - first_name: Adam full_name: Keates, Adam last_name: Keates - first_name: Paul F. full_name: Kelly, Paul F. last_name: Kelly - first_name: Dmitry full_name: Khakimov, Dmitry last_name: Khakimov - first_name: Stefanos full_name: Konstantinopoulos, Stefanos last_name: Konstantinopoulos - first_name: Liudmila N. full_name: Kuleshova, Liudmila N. last_name: Kuleshova - first_name: He full_name: Li, He last_name: Li - first_name: Xiaolu full_name: Lin, Xiaolu last_name: Lin - first_name: Alexander full_name: List, Alexander last_name: List - first_name: Congcong full_name: Liu, Congcong last_name: Liu - first_name: Yifei Michelle full_name: Liu, Yifei Michelle last_name: Liu - first_name: Zenghui full_name: Liu, Zenghui last_name: Liu - first_name: Zhi-Pan full_name: Liu, Zhi-Pan last_name: Liu - first_name: Joseph W. full_name: Lubach, Joseph W. last_name: Lubach - first_name: Noa full_name: Marom, Noa last_name: Marom - first_name: Alexander A. full_name: Maryewski, Alexander A. last_name: Maryewski - first_name: Hiroyuki full_name: Matsui, Hiroyuki last_name: Matsui - first_name: Alessandra full_name: Mattei, Alessandra last_name: Mattei - first_name: R. Alex full_name: Mayo, R. Alex last_name: Mayo - first_name: John W. full_name: Melkumov, John W. last_name: Melkumov - first_name: Sharmarke full_name: Mohamed, Sharmarke last_name: Mohamed - first_name: Zahrasadat full_name: Momenzadeh Abardeh, Zahrasadat last_name: Momenzadeh Abardeh - first_name: Hari S. full_name: Muddana, Hari S. last_name: Muddana - first_name: Naofumi full_name: Nakayama, Naofumi last_name: Nakayama - first_name: Kamal Singh full_name: Nayal, Kamal Singh last_name: Nayal - first_name: Marcus A. full_name: Neumann, Marcus A. last_name: Neumann - first_name: Rahul full_name: Nikhar, Rahul last_name: Nikhar - first_name: Shigeaki full_name: Obata, Shigeaki last_name: Obata - first_name: Dana full_name: O'Connor, Dana last_name: O'Connor - first_name: Artem R. full_name: Oganov, Artem R. last_name: Oganov - first_name: Koji full_name: Okuwaki, Koji last_name: Okuwaki - first_name: Alberto full_name: Otero-de-la-Roza, Alberto last_name: Otero-de-la-Roza - first_name: Constantinos C. full_name: Pantelides, Constantinos C. last_name: Pantelides - first_name: Sean full_name: Parkin, Sean last_name: Parkin - first_name: Chris J. full_name: Pickard, Chris J. last_name: Pickard - first_name: Luca full_name: Pilia, Luca last_name: Pilia - first_name: Tatyana full_name: Pivina, Tatyana last_name: Pivina - first_name: Rafał full_name: Podeszwa, Rafał last_name: Podeszwa - first_name: Alastair J. A. full_name: Price, Alastair J. A. last_name: Price - first_name: Louise S. full_name: Price, Louise S. last_name: Price - first_name: Sarah L. full_name: Price, Sarah L. last_name: Price - first_name: Michael R. full_name: Probert, Michael R. last_name: Probert - first_name: Angeles full_name: Pulido, Angeles last_name: Pulido - first_name: Gunjan Rajendra full_name: Ramteke, Gunjan Rajendra last_name: Ramteke - first_name: Atta Ur full_name: Rehman, Atta Ur last_name: Rehman - first_name: Susan M. full_name: Reutzel-Edens, Susan M. last_name: Reutzel-Edens - first_name: Jutta full_name: Rogal, Jutta last_name: Rogal - first_name: Marta J. full_name: Ross, Marta J. last_name: Ross - first_name: Adrian F. full_name: Rumson, Adrian F. last_name: Rumson - first_name: Ghazala full_name: Sadiq, Ghazala last_name: Sadiq - first_name: Zeinab M. full_name: Saeed, Zeinab M. last_name: Saeed - first_name: Alireza full_name: Salimi, Alireza last_name: Salimi - first_name: Matteo full_name: Salvalaglio, Matteo last_name: Salvalaglio - first_name: Leticia full_name: Sanders de Almada, Leticia last_name: Sanders de Almada - first_name: Kiran full_name: Sasikumar, Kiran last_name: Sasikumar - first_name: Sivakumar full_name: Sekharan, Sivakumar last_name: Sekharan - first_name: Cheng full_name: Shang, Cheng last_name: Shang - first_name: Kenneth full_name: Shankland, Kenneth last_name: Shankland - first_name: Kotaro full_name: Shinohara, Kotaro last_name: Shinohara - first_name: Baimei full_name: Shi, Baimei last_name: Shi - first_name: Xuekun full_name: Shi, Xuekun last_name: Shi - first_name: A. Geoffrey full_name: Skillman, A. Geoffrey last_name: Skillman - first_name: Hongxing full_name: Song, Hongxing last_name: Song - first_name: Nina full_name: Strasser, Nina last_name: Strasser - first_name: Jacco full_name: van de Streek, Jacco last_name: van de Streek - first_name: Isaac J. full_name: Sugden, Isaac J. last_name: Sugden - first_name: Guangxu full_name: Sun, Guangxu last_name: Sun - first_name: Krzysztof full_name: Szalewicz, Krzysztof last_name: Szalewicz - first_name: Benjamin I. full_name: Tan, Benjamin I. last_name: Tan - first_name: Lu full_name: Tan, Lu last_name: Tan - first_name: Frank full_name: Tarczynski, Frank last_name: Tarczynski - first_name: Christopher R. full_name: Taylor, Christopher R. last_name: Taylor - first_name: Alexandre full_name: Tkatchenko, Alexandre last_name: Tkatchenko - first_name: Rithwik full_name: Tom, Rithwik last_name: Tom - first_name: Mark E. full_name: Tuckerman, Mark E. last_name: Tuckerman - first_name: Yohei full_name: Utsumi, Yohei last_name: Utsumi - first_name: Leslie full_name: Vogt-Maranto, Leslie last_name: Vogt-Maranto - first_name: Jake full_name: Weatherston, Jake last_name: Weatherston - first_name: Luke J. full_name: Wilkinson, Luke J. last_name: Wilkinson - first_name: Robert D. full_name: Willacy, Robert D. last_name: Willacy - first_name: Lukasz full_name: Wojtas, Lukasz last_name: Wojtas - first_name: Grahame R. full_name: Woollam, Grahame R. last_name: Woollam - first_name: Zhuocen full_name: Yang, Zhuocen last_name: Yang - first_name: Etsuo full_name: Yonemochi, Etsuo last_name: Yonemochi - first_name: Xin full_name: Yue, Xin last_name: Yue - first_name: Qun full_name: Zeng, Qun last_name: Zeng - first_name: Yizu full_name: Zhang, Yizu last_name: Zhang - first_name: Tian full_name: Zhou, Tian last_name: Zhou - first_name: Yunfei full_name: Zhou, Yunfei last_name: Zhou - first_name: Roman full_name: Zubatyuk, Roman last_name: Zubatyuk - first_name: Jason C. full_name: Cole, Jason C. last_name: Cole citation: ama: 'Hunnisett LM, Nyman J, Francia N, et al. The seventh blind test of crystal structure prediction: Structure generation methods. Acta Crystallographica Section B. 2024;80(6):517-547. doi:10.1107/s2052520624007492' apa: 'Hunnisett, L. M., Nyman, J., Francia, N., Abraham, N. S., Adjiman, C. S., Aitipamula, S., … Cole, J. C. (2024). The seventh blind test of crystal structure prediction: Structure generation methods. Acta Crystallographica Section B. International Union of Crystallography. https://doi.org/10.1107/s2052520624007492' chicago: 'Hunnisett, Lily M., Jonas Nyman, Nicholas Francia, Nathan S. Abraham, Claire S. Adjiman, Srinivasulu Aitipamula, Tamador Alkhidir, et al. “The Seventh Blind Test of Crystal Structure Prediction: Structure Generation Methods.” Acta Crystallographica Section B. International Union of Crystallography, 2024. https://doi.org/10.1107/s2052520624007492.' ieee: 'L. M. Hunnisett et al., “The seventh blind test of crystal structure prediction: Structure generation methods,” Acta Crystallographica Section B, vol. 80, no. 6. International Union of Crystallography, pp. 517–547, 2024.' ista: 'Hunnisett LM et al. 2024. The seventh blind test of crystal structure prediction: Structure generation methods. Acta Crystallographica Section B. 80(6), 517–547.' mla: 'Hunnisett, Lily M., et al. “The Seventh Blind Test of Crystal Structure Prediction: Structure Generation Methods.” Acta Crystallographica Section B, vol. 80, no. 6, International Union of Crystallography, 2024, pp. 517–47, doi:10.1107/s2052520624007492.' short: L.M. Hunnisett, J. Nyman, N. Francia, N.S. Abraham, C.S. Adjiman, S. Aitipamula, T. Alkhidir, M. Almehairbi, A. Anelli, D.M. Anstine, J.E. Anthony, J.E. Arnold, F. Bahrami, M.A. Bellucci, R.M. Bhardwaj, I. Bier, J.A. Bis, A.D. Boese, D.H. Bowskill, J. Bramley, J.G. Brandenburg, D.E. Braun, P.W.V. Butler, J. Cadden, S. Carino, E.J. Chan, C. Chang, B. Cheng, S.M. Clarke, S.J. Coles, R.I. Cooper, R. Couch, R. Cuadrado, T. Darden, G.M. Day, H. Dietrich, Y. Ding, A. DiPasquale, B. Dhokale, B.P. van Eijck, M.R.J. Elsegood, D. Firaha, W. Fu, K. Fukuzawa, J. Glover, H. Goto, C. Greenwell, R. Guo, J. Harter, J. Helfferich, D.W.M. Hofmann, J. Hoja, J. Hone, R. Hong, G. Hutchison, Y. Ikabata, O. Isayev, O. Ishaque, V. Jain, Y. Jin, A. Jing, E.R. Johnson, I. Jones, K.V.J. Jose, E.A. Kabova, A. Keates, P.F. Kelly, D. Khakimov, S. Konstantinopoulos, L.N. Kuleshova, H. Li, X. Lin, A. List, C. Liu, Y.M. Liu, Z. Liu, Z.-P. Liu, J.W. Lubach, N. Marom, A.A. Maryewski, H. Matsui, A. Mattei, R.A. Mayo, J.W. Melkumov, S. Mohamed, Z. Momenzadeh Abardeh, H.S. Muddana, N. Nakayama, K.S. Nayal, M.A. Neumann, R. Nikhar, S. Obata, D. O’Connor, A.R. Oganov, K. Okuwaki, A. Otero-de-la-Roza, C.C. Pantelides, S. Parkin, C.J. Pickard, L. Pilia, T. Pivina, R. Podeszwa, A.J.A. Price, L.S. Price, S.L. Price, M.R. Probert, A. Pulido, G.R. Ramteke, A.U. Rehman, S.M. Reutzel-Edens, J. Rogal, M.J. Ross, A.F. Rumson, G. Sadiq, Z.M. Saeed, A. Salimi, M. Salvalaglio, L. Sanders de Almada, K. Sasikumar, S. Sekharan, C. Shang, K. Shankland, K. Shinohara, B. Shi, X. Shi, A.G. Skillman, H. Song, N. Strasser, J. van de Streek, I.J. Sugden, G. Sun, K. Szalewicz, B.I. Tan, L. Tan, F. Tarczynski, C.R. Taylor, A. Tkatchenko, R. Tom, M.E. Tuckerman, Y. Utsumi, L. Vogt-Maranto, J. Weatherston, L.J. Wilkinson, R.D. Willacy, L. Wojtas, G.R. Woollam, Z. Yang, E. Yonemochi, X. Yue, Q. Zeng, Y. Zhang, T. Zhou, Y. Zhou, R. Zubatyuk, J.C. Cole, Acta Crystallographica Section B 80 (2024) 517–547. das_tickbox: '0' date_created: 2025-01-29T11:07:36Z date_published: 2024-12-01T00:00:00Z date_updated: 2026-08-07T10:46:53Z day: '01' ddc: - '540' department: - _id: BiCh doi: 10.1107/s2052520624007492 external_id: isi: - '001388840500003' pmid: - '39405196' file: - access_level: open_access checksum: 33b8083e76564cc918182b0b0b2cc023 content_type: application/pdf creator: dernst date_created: 2025-01-29T11:09:48Z date_updated: 2025-01-29T11:09:48Z file_id: '18954' file_name: 2024_ActaCrystallographicaB_Hunnisett.pdf file_size: 10061037 relation: main_file success: 1 file_date_updated: 2025-01-29T11:09:48Z has_accepted_license: '1' intvolume: ' 80' isi: 1 issue: '6' language: - iso: eng month: '12' oa: 1 oa_version: Published Version page: 517-547 pmid: 1 publication: Acta Crystallographica Section B publication_identifier: issn: - 2052-5206 publication_status: published publisher: International Union of Crystallography quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: 'The seventh blind test of crystal structure prediction: Structure generation methods' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 80 year: '2024' ... --- _id: '15359' abstract: - lang: eng text: Molecular dynamics (MD) simulations play an important role in understanding and engineering heat transport properties of complex materials. An essential requirement for reliably predicting heat transport properties is the use of accurate and efficient interatomic potentials. Recently, machine-learned potentials (MLPs) have shown great promise in providing the required accuracy for a broad range of materials. In this mini-review and tutorial, we delve into the fundamentals of heat transport, explore pertinent MD simulation methods, and survey the applications of MLPs in MD simulations of heat transport. Furthermore, we provide a step-by-step tutorial on developing MLPs for highly efficient and predictive heat transport simulations, utilizing the neuroevolution potentials as implemented in the GPUMD package. Our aim with this mini-review and tutorial is to empower researchers with valuable insights into cutting-edge methodologies that can significantly enhance the accuracy and efficiency of MD simulations for heat transport studies. acknowledgement: H.D. is supported by the Science Foundation from the Education Department of Liaoning Province (No. JYTMS20231613) and the Doctoral start-up Fund of Bohai University (No. 0523bs008). P.Y. is supported by the Israel Academy of Sciences and Humanities & Council for Higher Education Excellence Fellowship Program for International Postdoctoral Researchers. K.X. and T.L. acknowledge support from the National Key R&D Project from Ministry of Science and Technology of China (No. 2022YFA1203100), the Research Grants Council of Hong Kong (No. AoE/P-701/20), and RGC GRF (No. 14220022). Z.Z. acknowledges the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101034413. S.X. acknowledges financial support from the National Natural Science Foundation of China (NNSFC) (Grant No. 12174276). article_number: '161101' article_processing_charge: Yes (in subscription journal) article_type: review arxiv: 1 author: - first_name: Haikuan full_name: Dong, Haikuan last_name: Dong - first_name: Yongbo full_name: Shi, Yongbo last_name: Shi - first_name: Penghua full_name: Ying, Penghua last_name: Ying - first_name: Ke full_name: Xu, Ke last_name: Xu - first_name: Ting full_name: Liang, Ting last_name: Liang - first_name: Yanzhou full_name: Wang, Yanzhou last_name: Wang - first_name: Zezhu full_name: Zeng, Zezhu id: 54a2c730-803f-11ed-ab7e-95b29d2680e7 last_name: Zeng orcid: 0000-0001-5126-4928 - first_name: Xin full_name: Wu, Xin last_name: Wu - first_name: Wenjiang full_name: Zhou, Wenjiang last_name: Zhou - first_name: Shiyun full_name: Xiong, Shiyun last_name: Xiong - first_name: Shunda full_name: Chen, Shunda last_name: Chen - first_name: Zheyong full_name: Fan, Zheyong last_name: Fan citation: ama: 'Dong H, Shi Y, Ying P, et al. Molecular dynamics simulations of heat transport using machine-learned potentials: A mini-review and tutorial on GPUMD with neuroevolution potentials. Journal of Applied Physics. 2024;135(16). doi:10.1063/5.0200833' apa: 'Dong, H., Shi, Y., Ying, P., Xu, K., Liang, T., Wang, Y., … Fan, Z. (2024). Molecular dynamics simulations of heat transport using machine-learned potentials: A mini-review and tutorial on GPUMD with neuroevolution potentials. Journal of Applied Physics. AIP Publishing. https://doi.org/10.1063/5.0200833' chicago: 'Dong, Haikuan, Yongbo Shi, Penghua Ying, Ke Xu, Ting Liang, Yanzhou Wang, Zezhu Zeng, et al. “Molecular Dynamics Simulations of Heat Transport Using Machine-Learned Potentials: A Mini-Review and Tutorial on GPUMD with Neuroevolution Potentials.” Journal of Applied Physics. AIP Publishing, 2024. https://doi.org/10.1063/5.0200833.' ieee: 'H. Dong et al., “Molecular dynamics simulations of heat transport using machine-learned potentials: A mini-review and tutorial on GPUMD with neuroevolution potentials,” Journal of Applied Physics, vol. 135, no. 16. AIP Publishing, 2024.' ista: 'Dong H, Shi Y, Ying P, Xu K, Liang T, Wang Y, Zeng Z, Wu X, Zhou W, Xiong S, Chen S, Fan Z. 2024. Molecular dynamics simulations of heat transport using machine-learned potentials: A mini-review and tutorial on GPUMD with neuroevolution potentials. Journal of Applied Physics. 135(16), 161101.' mla: 'Dong, Haikuan, et al. “Molecular Dynamics Simulations of Heat Transport Using Machine-Learned Potentials: A Mini-Review and Tutorial on GPUMD with Neuroevolution Potentials.” Journal of Applied Physics, vol. 135, no. 16, 161101, AIP Publishing, 2024, doi:10.1063/5.0200833.' short: H. Dong, Y. Shi, P. Ying, K. Xu, T. Liang, Y. Wang, Z. Zeng, X. Wu, W. Zhou, S. Xiong, S. Chen, Z. Fan, Journal of Applied Physics 135 (2024). das_tickbox: '1' dataavailabilitystatement: All the training and test datasets and the trained NEP models for crystalline silicon are freely available at https://gitlab.com/brucefan1983/nep-data. The training datasets, trained NEP, DP, and MTP models for graphene and MD input files for reproducing Fig. 3 are freely available at https://github.com/hityingph/supporting-info/tree/main/Dong_GPUMD_Tutorial_2024. date_created: 2024-05-05T22:01:03Z date_published: 2024-04-28T00:00:00Z date_updated: 2026-08-07T10:35:13Z day: '28' ddc: - '530' department: - _id: BiCh doi: 10.1063/5.0200833 ec_funded: 1 external_id: arxiv: - '2401.16249' isi: - '001215967400009' file: - access_level: open_access checksum: 4d6abb3ebe058ce8eebf4fc7e9cdda0d content_type: application/pdf creator: dernst date_created: 2024-05-13T08:07:44Z date_updated: 2024-05-13T08:07:44Z file_id: '15382' file_name: 2024_JourApplPhysics_Dong.pdf file_size: 3240613 relation: main_file success: 1 file_date_updated: 2024-05-13T08:07:44Z has_accepted_license: '1' intvolume: ' 135' isi: 1 issue: '16' language: - iso: eng month: '04' oa: 1 oa_version: Preprint project: - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' publication: Journal of Applied Physics publication_identifier: eissn: - 1089-7550 issn: - 0021-8979 publication_status: published publisher: AIP Publishing quality_controlled: '1' related_material: link: - relation: software url: https://gitlab.com/brucefan1983/nep-data researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: 'Molecular dynamics simulations of heat transport using machine-learned potentials: A mini-review and tutorial on GPUMD with neuroevolution potentials' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 135 year: '2024' ... --- OA_place: publisher OA_type: hybrid _id: '18452' abstract: - lang: eng text: 'Diffusion models have recently emerged as powerful tools for the generation of new molecular and material structures. The key insight is that the noise in these models is related to the response of the atoms to displacement, and the denoising step is thus analogous to the geometry relaxation of atomistic systems starting from a random structure. Building on this, we present a generative method called Response Matching (RM), which leverages the fact that each stable material or molecule exists at the minimum of its potential energy surface. Any perturbation induces a response in energy and stress, driving the structure back to equilibrium. Matching this response is closely related to score matching in diffusion models. Another important aspect of state-of-the-art diffusion models is the incorporation of physical symmetries such as translation, rotation, and periodicity. RM employs a machine learning interatomic potential and random structure search as the denoising model, inherently respecting these symmetries and exploiting the locality of atomic interactions. RM handles both molecules and bulk materials under the same framework. Its efficiency and generalization are demonstrated on three systems: a small organic molecular data set, stable crystals from the Materials Project, and one-shot learning on a single diamond configuration.' acknowledgement: B.C. thanks Chris Pickard for enlightening discussions. article_processing_charge: Yes (in subscription journal) article_type: original arxiv: 1 author: - first_name: Bingqing full_name: Cheng, Bingqing id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9 last_name: Cheng orcid: 0000-0002-3584-9632 citation: ama: Cheng B. Response matching for generating materials and molecules. Journal of Chemical Theory and Computation. 2024;20(20):9259-9266. doi:10.1021/acs.jctc.4c00998 apa: Cheng, B. (2024). Response matching for generating materials and molecules. Journal of Chemical Theory and Computation. American Chemical Society. https://doi.org/10.1021/acs.jctc.4c00998 chicago: Cheng, Bingqing. “Response Matching for Generating Materials and Molecules.” Journal of Chemical Theory and Computation. American Chemical Society, 2024. https://doi.org/10.1021/acs.jctc.4c00998. ieee: B. Cheng, “Response matching for generating materials and molecules,” Journal of Chemical Theory and Computation, vol. 20, no. 20. American Chemical Society, pp. 9259–9266, 2024. ista: Cheng B. 2024. Response matching for generating materials and molecules. Journal of Chemical Theory and Computation. 20(20), 9259–9266. mla: Cheng, Bingqing. “Response Matching for Generating Materials and Molecules.” Journal of Chemical Theory and Computation, vol. 20, no. 20, American Chemical Society, 2024, pp. 9259–66, doi:10.1021/acs.jctc.4c00998. short: B. Cheng, Journal of Chemical Theory and Computation 20 (2024) 9259–9266. corr_author: '1' das_tickbox: '1' dataavailabilitystatement: The training scripts, trained models, and training data are available at https://github.com/BingqingCheng/cace-rm. date_created: 2024-10-20T22:02:07Z date_published: 2024-10-22T00:00:00Z date_updated: 2026-08-07T10:36:38Z day: '22' ddc: - '540' department: - _id: BiCh doi: 10.1021/acs.jctc.4c00998 external_id: arxiv: - '2405.09057' isi: - '001330001500001' pmid: - '39365029' file: - access_level: open_access checksum: aca0011bba4846140809b5af583daa9a content_type: application/pdf creator: dernst date_created: 2025-01-13T09:11:09Z date_updated: 2025-01-13T09:11:09Z file_id: '18832' file_name: 2024_JCTC_Cheng.pdf file_size: 4758251 relation: main_file success: 1 file_date_updated: 2025-01-13T09:11:09Z has_accepted_license: '1' intvolume: ' 20' isi: 1 issue: '20' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '10' oa: 1 oa_version: Published Version page: 9259-9266 pmid: 1 publication: Journal of Chemical Theory and Computation publication_identifier: eissn: - 1549-9626 issn: - 1549-9618 publication_status: published publisher: American Chemical Society quality_controlled: '1' related_material: link: - relation: software url: https://github.com/BingqingCheng/cace researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: Response matching for generating materials and molecules tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 20 year: '2024' ... --- DOAJ_listed: '1' OA_place: publisher OA_type: gold _id: '17322' abstract: - lang: eng text: Machine learning interatomic potentials are revolutionizing large-scale, accurate atomistic modeling in material science and chemistry. Many potentials use atomic cluster expansion or equivariant message-passing frameworks. Such frameworks typically use spherical harmonics as angular basis functions, followed by Clebsch-Gordan contraction to maintain rotational symmetry. We propose a mathematically equivalent and simple alternative that performs all operations in the Cartesian coordinates. This approach provides a complete set of polynormially independent features of atomic environments while maintaining interaction body orders. Additionally, we integrate low-dimensional embeddings of various chemical elements, trainable radial channel coupling, and inter-atomic message passing. The resulting potential, named Cartesian Atomic Cluster Expansion (CACE), exhibits good accuracy, stability, and generalizability. We validate its performance in diverse systems, including bulk water, small molecules, and 25-element high-entropy alloys. acknowledgement: B.C. thanks Ralf Drautz and Ngoc Cuong Nguyen for illuminating discussions. article_number: '157' article_processing_charge: Yes article_type: original arxiv: 1 author: - first_name: Bingqing full_name: Cheng, Bingqing id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9 last_name: Cheng orcid: 0000-0002-3584-9632 citation: ama: Cheng B. Cartesian atomic cluster expansion for machine learning interatomic potentials. npj Computational Materials. 2024;10. doi:10.1038/s41524-024-01332-4 apa: Cheng, B. (2024). Cartesian atomic cluster expansion for machine learning interatomic potentials. Npj Computational Materials. Springer Nature. https://doi.org/10.1038/s41524-024-01332-4 chicago: Cheng, Bingqing. “Cartesian Atomic Cluster Expansion for Machine Learning Interatomic Potentials.” Npj Computational Materials. Springer Nature, 2024. https://doi.org/10.1038/s41524-024-01332-4. ieee: B. Cheng, “Cartesian atomic cluster expansion for machine learning interatomic potentials,” npj Computational Materials, vol. 10. Springer Nature, 2024. ista: Cheng B. 2024. Cartesian atomic cluster expansion for machine learning interatomic potentials. npj Computational Materials. 10, 157. mla: Cheng, Bingqing. “Cartesian Atomic Cluster Expansion for Machine Learning Interatomic Potentials.” Npj Computational Materials, vol. 10, 157, Springer Nature, 2024, doi:10.1038/s41524-024-01332-4. short: B. Cheng, Npj Computational Materials 10 (2024). corr_author: '1' das_tickbox: '1' dataavailabilitystatement: The water dataset is from https://github.com/BingqingCheng/ab-initio-thermodynamics-of-water. MD17-ethanol is from http://www.sgdml.org/#datasets. BPA is from ref. 43, downloaded from https://github.com/davkovacs/BOTNet-datasets. The HEA25 dataset is from ref. 45, downloaded from https://archive.materialscloud.org/record/2023.57. The training scripts, trained CACE potentials, and MD input files are available at https://github.com/BingqingCheng/cacefit. date_created: 2024-07-28T22:01:08Z date_published: 2024-07-18T00:00:00Z date_updated: 2026-08-07T10:41:14Z day: '18' ddc: - '000' department: - _id: BiCh doi: 10.1038/s41524-024-01332-4 external_id: arxiv: - '2402.07472' isi: - '001271730700001' file: - access_level: open_access checksum: e6b4d1a45a9ef1e9be35b313d96ebd6f content_type: application/pdf creator: dernst date_created: 2025-01-09T12:36:48Z date_updated: 2025-01-09T12:36:48Z file_id: '18813' file_name: 2024_npjComputationalMaterials_Cheng.pdf file_size: 1659509 relation: main_file success: 1 file_date_updated: 2025-01-09T12:36:48Z has_accepted_license: '1' intvolume: ' 10' isi: 1 language: - iso: eng month: '07' oa: 1 oa_version: Published Version publication: npj Computational Materials publication_identifier: eissn: - 2057-3960 publication_status: published publisher: Springer Nature quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: Cartesian atomic cluster expansion for machine learning interatomic potentials tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 10 year: '2024' ... --- _id: '17278' abstract: - lang: eng text: An azeotrope is a constant boiling point mixture, and its behavior is important for fluid separation processes. Predicting azeotropes from atomistic simulations is difficult due to the complexities and convergence problems of Monte Carlo and free-energy perturbation techniques. Here, we present a methodology for predicting the azeotropes of binary mixtures, which computes the compositional dependence of chemical potentials from molecular dynamics simulations using the S0 method and employs experimental boiling point and vaporization enthalpy data. Using this methodology, we reproduce the azeotropes, or lack thereof, in five case studies, including ethanol/water, ethanol/isooctane, methanol/water, hydrazine/water, and acetone/chloroform mixtures. We find that it is crucial to use the experimental boiling point and vaporization enthalpy for reliable azeotrope predictions, as empirical force fields are not accurate enough for these quantities. Finally, we use regular solution models to rationalize the azeotropes and reveal that they tend to form when the mixture components have similar boiling points and strong interactions. acknowledgement: B.C. thanks Alessandro Laio, who introduced the phenomenon of azeotrope and suggested using the S0 method to compute it. B.C. and X.W. thank Felix Wodaczek for the insightful comments and suggestions on the manuscript. B.C. and X.W. acknowledge the resources provided by the Cambridge Tier-2 system operated by the University of Cambridge Research Computing Service, funded by EPSRC Tier-2 capital (Grant No. EP/P020259/1). article_number: '034111' article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Xiaoyu full_name: Wang, Xiaoyu id: 8dff9c62-32b0-11ee-9fa8-fc73025e10f3 last_name: Wang - first_name: Bingqing full_name: Cheng, Bingqing id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9 last_name: Cheng orcid: 0000-0002-3584-9632 citation: ama: Wang X, Cheng B. Integrating molecular dynamics simulations and experimental data for azeotrope predictions in binary mixtures. Journal of Chemical Physics. 2024;161(3). doi:10.1063/5.0217232 apa: Wang, X., & Cheng, B. (2024). Integrating molecular dynamics simulations and experimental data for azeotrope predictions in binary mixtures. Journal of Chemical Physics. AIP Publishing. https://doi.org/10.1063/5.0217232 chicago: Wang, Xiaoyu, and Bingqing Cheng. “Integrating Molecular Dynamics Simulations and Experimental Data for Azeotrope Predictions in Binary Mixtures.” Journal of Chemical Physics. AIP Publishing, 2024. https://doi.org/10.1063/5.0217232. ieee: X. Wang and B. Cheng, “Integrating molecular dynamics simulations and experimental data for azeotrope predictions in binary mixtures,” Journal of Chemical Physics, vol. 161, no. 3. AIP Publishing, 2024. ista: Wang X, Cheng B. 2024. Integrating molecular dynamics simulations and experimental data for azeotrope predictions in binary mixtures. Journal of Chemical Physics. 161(3), 034111. mla: Wang, Xiaoyu, and Bingqing Cheng. “Integrating Molecular Dynamics Simulations and Experimental Data for Azeotrope Predictions in Binary Mixtures.” Journal of Chemical Physics, vol. 161, no. 3, 034111, AIP Publishing, 2024, doi:10.1063/5.0217232. short: X. Wang, B. Cheng, Journal of Chemical Physics 161 (2024). corr_author: '1' das_tickbox: '1' dataavailabilitystatement: All simulation setups, analysis scripts, and raw data in the study are available in the SI repository https://github.com/Xiaoyu-Wang-Stone/Azeotrope_S0. date_created: 2024-07-21T22:01:00Z date_published: 2024-07-14T00:00:00Z date_updated: 2026-08-07T10:38:59Z day: '14' department: - _id: BiCh - _id: GradSch doi: 10.1063/5.0217232 external_id: arxiv: - '2405.02216' isi: - '001281819100016' pmid: - '39007379' intvolume: ' 161' isi: 1 issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2405.02216 month: '07' oa: 1 oa_version: Preprint pmid: 1 publication: Journal of Chemical Physics publication_identifier: eissn: - 1089-7690 issn: - 0021-9606 publication_status: published publisher: AIP Publishing quality_controlled: '1' related_material: link: - relation: software url: https://github.com/Xiaoyu-Wang-Stone/Azeotrope_S0 researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: Integrating molecular dynamics simulations and experimental data for azeotrope predictions in binary mixtures type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 161 year: '2024' ... --- APC_amount: 3062,93 EUR OA_place: publisher OA_type: hybrid _id: '18525' abstract: - lang: eng text: As their statistical power grows, genome-wide association studies (GWAS) have identified an increasing number of loci underlying quantitative traits of interest. These loci are scattered throughout the genome and are individually responsible only for small fractions of the total heritable trait variance. The recently proposed omnigenic model provides a conceptual framework to explain these observations by postulating that numerous distant loci contribute to each complex trait via effect propagation through intracellular regulatory networks. We formalize this conceptual framework by proposing the “quantitative omnigenic model” (QOM), a statistical model that combines prior knowledge of the regulatory network topology with genomic data. By applying our model to gene expression traits in yeast, we demonstrate that QOM achieves similar gene expression prediction performance to traditional GWAS with hundreds of times less parameters, while simultaneously extracting candidate causal and quantitative chains of effect propagation through the regulatory network for every individual gene. We estimate the fraction of heritable trait variance in cis- and in trans-, break the latter down by effect propagation order, assess the trans- variance not attributable to transcriptional regulation, and show that QOM correctly accounts for the low-dimensional structure of gene expression covariance. We furthermore demonstrate the relevance of QOM for systems biology, by employing it as a statistical test for the quality of regulatory network reconstructions, and linking it to the propagation of nontranscriptional (including environmental) effects. acknowledgement: N.R.acknowledges the support of the Austrian Academy of Sciences through the Doctoral Fellowship Programme (DOC) of the Austrian Academy of Sciences 26917. M.H. and G.T. were supported in part by the Human Frontiers Science Program Grant RGP0034/2018. We thank Nicholas H. Barton, Fyodor Kondrashov, and Matthew R. Robinson for fruitful discussions. article_number: e2402340121 article_processing_charge: Yes article_type: original author: - first_name: Natalia full_name: Ruzickova, Natalia id: D2761128-D73D-11E9-A1BF-BA0DE6697425 last_name: Ruzickova - first_name: Michal full_name: Hledik, Michal id: 4171253A-F248-11E8-B48F-1D18A9856A87 last_name: Hledik - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Ruzickova N, Hledik M, Tkačik G. Quantitative omnigenic model discovers interpretable genome-wide associations. Proceedings of the National Academy of Sciences of the United States of America. 2024;121(44). doi:10.1073/pnas.2402340121 apa: Ruzickova, N., Hledik, M., & Tkačik, G. (2024). Quantitative omnigenic model discovers interpretable genome-wide associations. Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences. https://doi.org/10.1073/pnas.2402340121 chicago: Ruzickova, Natalia, Michal Hledik, and Gašper Tkačik. “Quantitative Omnigenic Model Discovers Interpretable Genome-Wide Associations.” Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences, 2024. https://doi.org/10.1073/pnas.2402340121. ieee: N. Ruzickova, M. Hledik, and G. Tkačik, “Quantitative omnigenic model discovers interpretable genome-wide associations,” Proceedings of the National Academy of Sciences of the United States of America, vol. 121, no. 44. National Academy of Sciences, 2024. ista: Ruzickova N, Hledik M, Tkačik G. 2024. Quantitative omnigenic model discovers interpretable genome-wide associations. Proceedings of the National Academy of Sciences of the United States of America. 121(44), e2402340121. mla: Ruzickova, Natalia, et al. “Quantitative Omnigenic Model Discovers Interpretable Genome-Wide Associations.” Proceedings of the National Academy of Sciences of the United States of America, vol. 121, no. 44, e2402340121, National Academy of Sciences, 2024, doi:10.1073/pnas.2402340121. short: N. Ruzickova, M. Hledik, G. Tkačik, Proceedings of the National Academy of Sciences of the United States of America 121 (2024). corr_author: '1' date_created: 2024-11-10T23:01:59Z date_published: 2024-10-29T00:00:00Z date_updated: 2026-08-10T07:47:55Z day: '29' ddc: - '570' department: - _id: GaTk - _id: NiBa doi: 10.1073/pnas.2402340121 external_id: isi: - '001349462600001' pmid: - '39441639' file: - access_level: open_access checksum: d930e2ccf9ec900c7d7509a78cfb3564 content_type: application/pdf creator: dernst date_created: 2024-11-11T09:31:00Z date_updated: 2024-11-11T09:31:00Z file_id: '18536' file_name: 2024_PNAS_Ruzickova.pdf file_size: 25529709 relation: main_file success: 1 file_date_updated: 2024-11-11T09:31:00Z has_accepted_license: '1' intvolume: ' 121' isi: 1 issue: '44' language: - iso: eng month: '10' oa: 1 oa_version: Published Version pmid: 1 project: - _id: 7bec9174-9f16-11ee-852c-ded9fe5f810e name: Collective behaviour of cells in pancreatic Islets of Langerhans - _id: 2665AAFE-B435-11E9-9278-68D0E5697425 grant_number: RGP0034/2018 name: Can evolution minimize spurious signaling crosstalk to reach optimal performance? publication: Proceedings of the National Academy of Sciences of the United States of America publication_identifier: eissn: - 1091-6490 issn: - 0027-8424 publication_status: published publisher: National Academy of Sciences quality_controlled: '1' related_material: record: - id: '20357' relation: dissertation_contains status: public scopus_import: '1' status: public title: Quantitative omnigenic model discovers interpretable genome-wide associations tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 121 year: '2024' ... --- OA_place: publisher OA_type: hybrid _id: '17052' abstract: - lang: eng text: Production of thermoelectric materials from solution-processed particles involves the synthesis of particles, their purification and densification into pelletized material. Chemical changes that occur during each one of these steps render them performance determining. Particularly the purification steps, bypassed in conventional solid-state synthesis, are the cause for large discrepancies among similar solution-processed materials. In present work, the investigation focuses on a water-based surfactant free solution synthesis of SnSe, a highly relevant thermoelectric material. We show and rationalize that the number of leaching steps, purification solvent, annealing, and annealing atmosphere have significant influence on the Sn : Se ratio and impurity content in the powder. Such compositional changes that are undetectable by conventional characterization techniques lead to distinct consolidated materials with different types and concentration of defects. Additionally, the profound effect on their transport properties is demonstrated. We emphasize that understanding the chemistry and identifying key chemical species and their role throughout the process is paramount for optimizing material performance. Furthermore, we aim to demonstrate the necessity of comprehensive reporting of these steps as a standard practice to ensure material reproducibility. acknowledged_ssus: - _id: EM-Fac - _id: NMR - _id: LifeSc acknowledgement: ISTA and the Werner Siemens Foundation financially supported this work. The Scientific Service Units (SSU) of ISTA supported this research through resources provided by the Electron Microscopy Facility (EMF), NMR Facility and the Lab Support Facility (LSF). Dr. Krishnendu Maji at ISTA aided in this work through XRD analysis of the crystal phase of SnSe. Y.L. acknowledges funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 754411, the National Natural Science Foundation of China (NSFC) (Grants No. 22209034). M.C. received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 665385. article_number: e202402628 article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Christine full_name: Fiedler, Christine id: bd3fceba-dc74-11ea-a0a7-c17f71817366 last_name: Fiedler - first_name: Mariano full_name: Calcabrini, Mariano id: 45D7531A-F248-11E8-B48F-1D18A9856A87 last_name: Calcabrini orcid: 0000-0003-4566-5877 - first_name: Yu full_name: Liu, Yu id: 2A70014E-F248-11E8-B48F-1D18A9856A87 last_name: Liu orcid: 0000-0001-7313-6740 - first_name: Maria full_name: Ibáñez, Maria id: 43C61214-F248-11E8-B48F-1D18A9856A87 last_name: Ibáñez orcid: 0000-0001-5013-2843 citation: ama: Fiedler C, Calcabrini M, Liu Y, Ibáñez M. Unveiling crucial chemical processing parameters influencing the performance of solution-processed inorganic thermoelectric materials. Angewandte Chemie International Edition. 2024;63(25). doi:10.1002/anie.202402628 apa: Fiedler, C., Calcabrini, M., Liu, Y., & Ibáñez, M. (2024). Unveiling crucial chemical processing parameters influencing the performance of solution-processed inorganic thermoelectric materials. Angewandte Chemie International Edition. Wiley. https://doi.org/10.1002/anie.202402628 chicago: Fiedler, Christine, Mariano Calcabrini, Yu Liu, and Maria Ibáñez. “Unveiling Crucial Chemical Processing Parameters Influencing the Performance of Solution-Processed Inorganic Thermoelectric Materials.” Angewandte Chemie International Edition. Wiley, 2024. https://doi.org/10.1002/anie.202402628. ieee: C. Fiedler, M. Calcabrini, Y. Liu, and M. Ibáñez, “Unveiling crucial chemical processing parameters influencing the performance of solution-processed inorganic thermoelectric materials,” Angewandte Chemie International Edition, vol. 63, no. 25. Wiley, 2024. ista: Fiedler C, Calcabrini M, Liu Y, Ibáñez M. 2024. Unveiling crucial chemical processing parameters influencing the performance of solution-processed inorganic thermoelectric materials. Angewandte Chemie International Edition. 63(25), e202402628. mla: Fiedler, Christine, et al. “Unveiling Crucial Chemical Processing Parameters Influencing the Performance of Solution-Processed Inorganic Thermoelectric Materials.” Angewandte Chemie International Edition, vol. 63, no. 25, e202402628, Wiley, 2024, doi:10.1002/anie.202402628. short: C. Fiedler, M. Calcabrini, Y. Liu, M. Ibáñez, Angewandte Chemie International Edition 63 (2024). corr_author: '1' das_tickbox: '1' date_created: 2024-05-26T22:00:58Z date_published: 2024-06-17T00:00:00Z date_updated: 2026-08-11T12:39:15Z day: '17' ddc: - '540' department: - _id: MaIb doi: 10.1002/anie.202402628 ec_funded: 1 external_id: isi: - '001223768400001' pmid: - '38623865' file: - access_level: open_access checksum: 1572a0f4d2df55751761efeb2d11c7fc content_type: application/pdf creator: dernst date_created: 2025-01-09T09:12:07Z date_updated: 2025-01-09T09:12:07Z file_id: '18797' file_name: 2024_AngewChemieIntern_Fiedler.pdf file_size: 16347226 relation: main_file success: 1 file_date_updated: 2025-01-09T09:12:07Z has_accepted_license: '1' intvolume: ' 63' isi: 1 issue: '25' language: - iso: eng month: '06' oa: 1 oa_version: Published Version pmid: 1 project: - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program - _id: 9B8F7476-BA93-11EA-9121-9846C619BF3A name: 'HighTE: The Werner Siemens Laboratory for the High Throughput Discovery of Semiconductors for Waste Heat Recovery' publication: Angewandte Chemie International Edition publication_identifier: eissn: - 1521-3773 issn: - 1433-7851 publication_status: published publisher: Wiley quality_controlled: '1' related_material: record: - id: '22626' relation: dissertation_contains status: public scopus_import: '1' status: public title: Unveiling crucial chemical processing parameters influencing the performance of solution-processed inorganic thermoelectric materials tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 63 year: '2024' ... --- APC_amount: 4394,84 EUR OA_place: publisher OA_type: hybrid _id: '17124' abstract: - lang: eng text: 'In recent years, solution processes have gained considerable traction as a cost-effective and scalable method to produce high-performance thermoelectric materials. The process entails a series of critical steps: synthesis, purification, thermal treatments, and consolidation, each playing a pivotal role in determining performance, stability, and reproducibility. We have noticed a need for more comprehensive details for each of the described steps in most published works. Recognizing the significance of detailed synthetic protocols, we describe here the approach used to synthesize and characterize one of the highest-performing polycrystalline p-type SnSe. In particular, we report the synthesis of SnSe particles in water and the subsequent surface treatment with CdSe molecular complexes that yields CdSe-SnSe nanocomposites upon consolidation. Moreover, the surface treatment inhibits grain growth through Zenner pinning of secondary phase CdSe nanoparticles and enhances defect formation at different length scales. The enhanced complexity in the CdSe-SnSe nanocomposite microstructure with respect to SnSe promotes phonon scattering and thereby significantly reduces the thermal conductivity. Such surface engineering provides opportunities in solution processing for introducing and controlling defects, making it possible to optimize the transport properties and attain a high thermoelectric figure of merit.' acknowledged_ssus: - _id: EM-Fac - _id: LifeSc acknowledgement: The Scientific Service Units (SSU) of ISTA supported this research through resources provided by the Electron Microscopy Facility (EMF) and the Lab Support Facility (LSF). This work was financially supported by the Institute of Science and Technology Austria and the Werner Siemens Foundation. article_number: e66278 article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Christine full_name: Fiedler, Christine id: bd3fceba-dc74-11ea-a0a7-c17f71817366 last_name: Fiedler - first_name: Yu full_name: Liu, Yu id: 2A70014E-F248-11E8-B48F-1D18A9856A87 last_name: Liu orcid: 0000-0001-7313-6740 - first_name: Maria full_name: Ibáñez, Maria id: 43C61214-F248-11E8-B48F-1D18A9856A87 last_name: Ibáñez orcid: 0000-0001-5013-2843 citation: ama: Fiedler C, Liu Y, Ibáñez M. Solution-processed, surface-engineered, polycrystalline CdSe-SnSe exhibiting low thermal conductivity. Journal of Visualized Experiments. 2024;2024(207). doi:10.3791/66278 apa: Fiedler, C., Liu, Y., & Ibáñez, M. (2024). Solution-processed, surface-engineered, polycrystalline CdSe-SnSe exhibiting low thermal conductivity. Journal of Visualized Experiments. MyJove Corporation. https://doi.org/10.3791/66278 chicago: Fiedler, Christine, Yu Liu, and Maria Ibáñez. “Solution-Processed, Surface-Engineered, Polycrystalline CdSe-SnSe Exhibiting Low Thermal Conductivity.” Journal of Visualized Experiments. MyJove Corporation, 2024. https://doi.org/10.3791/66278. ieee: C. Fiedler, Y. Liu, and M. Ibáñez, “Solution-processed, surface-engineered, polycrystalline CdSe-SnSe exhibiting low thermal conductivity,” Journal of Visualized Experiments, vol. 2024, no. 207. MyJove Corporation, 2024. ista: Fiedler C, Liu Y, Ibáñez M. 2024. Solution-processed, surface-engineered, polycrystalline CdSe-SnSe exhibiting low thermal conductivity. Journal of Visualized Experiments. 2024(207), e66278. mla: Fiedler, Christine, et al. “Solution-Processed, Surface-Engineered, Polycrystalline CdSe-SnSe Exhibiting Low Thermal Conductivity.” Journal of Visualized Experiments, vol. 2024, no. 207, e66278, MyJove Corporation, 2024, doi:10.3791/66278. short: C. Fiedler, Y. Liu, M. Ibáñez, Journal of Visualized Experiments 2024 (2024). corr_author: '1' date_created: 2024-06-09T22:01:02Z date_published: 2024-05-01T00:00:00Z date_updated: 2026-08-11T12:39:14Z day: '01' ddc: - '530' department: - _id: MaIb doi: 10.3791/66278 external_id: isi: - '001281657200005' pmid: - '38829127' file: - access_level: open_access checksum: ddb41f1ce2333484ab5cd109ac2941c0 content_type: application/pdf creator: dernst date_created: 2025-02-17T15:08:55Z date_updated: 2025-02-17T15:08:55Z file_id: '19047' file_name: 2024_JoVE_Fiedler.pdf file_size: 1371995 relation: main_file success: 1 file_date_updated: 2025-02-17T15:08:55Z has_accepted_license: '1' intvolume: ' 2024' isi: 1 issue: '207' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/3.0/ month: '05' oa: 1 oa_version: Published Version pmid: 1 project: - _id: 9B8F7476-BA93-11EA-9121-9846C619BF3A name: 'HighTE: The Werner Siemens Laboratory for the High Throughput Discovery of Semiconductors for Waste Heat Recovery' publication: Journal of Visualized Experiments publication_identifier: issn: - 1940-087X publication_status: published publisher: MyJove Corporation quality_controlled: '1' related_material: record: - id: '22626' relation: dissertation_contains status: public scopus_import: '1' status: public title: Solution-processed, surface-engineered, polycrystalline CdSe-SnSe exhibiting low thermal conductivity tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 2024 year: '2024' ... --- _id: '15298' abstract: - lang: eng text: Mountains are important suppliers of freshwater to downstream areas, affecting large populations in particular in High Mountain Asia (HMA). Yet, the propagation of water from HMA headwaters to downstream areas is not fully understood, as interactions in the mountain water cycle between the cryo-, hydro- and biosphere remain elusive. We review the definition of blue and green water fluxes as liquid water that contributes to runoff at the outlet of the selected domain (blue) and water lost to the atmosphere through vapor fluxes, that is evaporation from water, ground, and interception plus transpiration (green) and propose to add the term white water to account for the (often neglected) evaporation and sublimation from snow and ice. We provide an assessment of models that can simulate the cryo-hydro-biosphere continuum and the interactions between spheres in high mountain catchments, going beyond disciplinary separations. Land surface models are uniquely able to account for such complexity, since they solve the coupled fluxes of water, energy, and carbon between the land surface and atmosphere. Due to the mechanistic nature of such models, specific variables can be compared systematically to independent remote sensing observations – providing vital insights into model accuracy and enabling the understanding of the complex watersheds of HMA. We discuss recent developments in spaceborne earth observation products that have the potential to support catchment modeling in high mountain regions. We then present a pilot study application of the mechanistic land surface model Tethys & Chloris to a glacierized watershed in the Nepalese Himalayas and discuss the use of high-resolution earth observation data to constrain the meteorological forcing uncertainty and validate model results. We use these insights to highlight the remaining challenges and future opportunities that remote sensing data presents for land surface modeling in HMA. acknowledgement: 'This work was supported by the ESA and NRSCC Dragon 5 cooperation project “Cryosphere-hydrosphere interactions of the Asian water towers: using remote sensing to drive hyper-resolution ecohydrological modelling” [Grant no. 59199]. PB and FP acknowledge funding from the SNSF (High-elevation precipitation in High Mountain Asia, HOPE)) [Grant no. 183633]. ESM, MK, SFu and FP acknowledge funding from the ERC under the European Union’s Horizon 2020 research and innovation program (Rapid mass losses of debris-covered glaciers in High Mountain Asia, RAVEN) [Grant no. 772751]. LJ, CZ and MMe acknowledge the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) [grant no. 2019QZKK010308, no. 2019QZKK0206], the National Natural Science Foundation of China projects (Grant no. 42171039, no. 91737205), the Chinese Academy of Sciences President’s International Fellowship Initiative [Grant no. 2020VTA0001], and the MOST High-Level Foreign Expert Program [Grant no. G2022055010L].' article_processing_charge: Yes article_type: original author: - first_name: Pascal full_name: Buri, Pascal last_name: Buri - first_name: Simone full_name: Fatichi, Simone id: cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6 last_name: Fatichi - first_name: Thomas full_name: Shaw, Thomas id: 3caa3f91-1f03-11ee-96ce-e0e553054d6e last_name: Shaw orcid: 0000-0001-7640-6152 - first_name: Catriona Louise full_name: Fyffe, Catriona Louise id: 001b0422-8d15-11ed-bc51-cab6c037a228 last_name: Fyffe - first_name: Evan S. full_name: Miles, Evan S. last_name: Miles - first_name: Michael full_name: Mccarthy, Michael id: 22a2674a-61ce-11ee-94b5-d18813baf16f last_name: Mccarthy - first_name: Marin full_name: Kneib, Marin last_name: Kneib - first_name: Shaoting full_name: Ren, Shaoting last_name: Ren - first_name: Achille full_name: Jouberton, Achille last_name: Jouberton - first_name: Stefan full_name: Fugger, Stefan last_name: Fugger - first_name: Li full_name: Jia, Li last_name: Jia - first_name: Jing full_name: Zhang, Jing last_name: Zhang - first_name: Cong full_name: Shen, Cong last_name: Shen - first_name: Chaolei full_name: Zheng, Chaolei last_name: Zheng - first_name: Massimo full_name: Menenti, Massimo last_name: Menenti - first_name: Francesca full_name: Pellicciotti, Francesca id: b28f055a-81ea-11ed-b70c-a9fe7f7b0e70 last_name: Pellicciotti orcid: 0000-0002-5554-8087 citation: ama: 'Buri P, Fatichi S, Shaw T, et al. Land surface modeling informed by earth observation data: Toward understanding blue–green–white water fluxes in High Mountain Asia. Geo-Spatial Information Science. 2024;27(3):703-727. doi:10.1080/10095020.2024.2330546' apa: 'Buri, P., Fatichi, S., Shaw, T., Fyffe, C. L., Miles, E. S., McCarthy, M., … Pellicciotti, F. (2024). Land surface modeling informed by earth observation data: Toward understanding blue–green–white water fluxes in High Mountain Asia. Geo-Spatial Information Science. Taylor & Francis. https://doi.org/10.1080/10095020.2024.2330546' chicago: 'Buri, Pascal, Simone Fatichi, Thomas Shaw, Catriona Louise Fyffe, Evan S. Miles, Michael McCarthy, Marin Kneib, et al. “Land Surface Modeling Informed by Earth Observation Data: Toward Understanding Blue–Green–White Water Fluxes in High Mountain Asia.” Geo-Spatial Information Science. Taylor & Francis, 2024. https://doi.org/10.1080/10095020.2024.2330546.' ieee: 'P. Buri et al., “Land surface modeling informed by earth observation data: Toward understanding blue–green–white water fluxes in High Mountain Asia,” Geo-Spatial Information Science, vol. 27, no. 3. Taylor & Francis, pp. 703–727, 2024.' ista: 'Buri P, Fatichi S, Shaw T, Fyffe CL, Miles ES, McCarthy M, Kneib M, Ren S, Jouberton A, Fugger S, Jia L, Zhang J, Shen C, Zheng C, Menenti M, Pellicciotti F. 2024. Land surface modeling informed by earth observation data: Toward understanding blue–green–white water fluxes in High Mountain Asia. Geo-Spatial Information Science. 27(3), 703–727.' mla: 'Buri, Pascal, et al. “Land Surface Modeling Informed by Earth Observation Data: Toward Understanding Blue–Green–White Water Fluxes in High Mountain Asia.” Geo-Spatial Information Science, vol. 27, no. 3, Taylor & Francis, 2024, pp. 703–27, doi:10.1080/10095020.2024.2330546.' short: P. Buri, S. Fatichi, T. Shaw, C.L. Fyffe, E.S. Miles, M. McCarthy, M. Kneib, S. Ren, A. Jouberton, S. Fugger, L. Jia, J. Zhang, C. Shen, C. Zheng, M. Menenti, F. Pellicciotti, Geo-Spatial Information Science 27 (2024) 703–727. date_created: 2024-04-07T22:00:56Z date_published: 2024-03-22T00:00:00Z date_updated: 2026-08-12T05:38:30Z day: '22' ddc: - '550' department: - _id: FrPe doi: 10.1080/10095020.2024.2330546 external_id: isi: - '001189470100001' file: - access_level: open_access checksum: afbfc4e9f1bf2a00711efc30ad667c40 content_type: application/pdf creator: dernst date_created: 2024-07-29T11:34:54Z date_updated: 2024-07-29T11:34:54Z file_id: '17342' file_name: 2024_GeoSpatialInfo_Buri.pdf file_size: 15678450 relation: main_file success: 1 file_date_updated: 2024-07-29T11:34:54Z has_accepted_license: '1' intvolume: ' 27' isi: 1 issue: '3' language: - iso: eng month: '03' oa: 1 oa_version: Published Version page: 703-727 publication: Geo-Spatial Information Science publication_identifier: issn: - 1009-5020 publication_status: published publisher: Taylor & Francis quality_controlled: '1' scopus_import: '1' status: public title: 'Land surface modeling informed by earth observation data: Toward understanding blue–green–white water fluxes in High Mountain Asia' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 27 year: '2024' ... --- OA_type: free access _id: '17231' abstract: - lang: eng text: In the class of projective billiards, which contains the usual billiards, we exhibit counter-examples to Ivrii's conjecture, which states that in any planar billiard with smooth boundary the set of periodic orbits has zero measure. The counter-examples are polygons admitting a 2-parameters family of n-periodic orbits, with n being either 3 or any even integer greater than 4. article_processing_charge: No article_type: original author: - first_name: Corentin full_name: Fiorebe, Corentin id: 06619f18-9070-11eb-847d-d1ee780bd88b last_name: Fiorebe citation: ama: Fiorebe C. Examples of projective billiards with open sets of periodic orbits. Discrete and Continuous Dynamical Systems- Series A. 2024;44(11):3287-3301. doi:10.3934/dcds.2024059 apa: Fiorebe, C. (2024). Examples of projective billiards with open sets of periodic orbits. Discrete and Continuous Dynamical Systems- Series A. AIMS. https://doi.org/10.3934/dcds.2024059 chicago: Fiorebe, Corentin. “Examples of Projective Billiards with Open Sets of Periodic Orbits.” Discrete and Continuous Dynamical Systems- Series A. AIMS, 2024. https://doi.org/10.3934/dcds.2024059. ieee: C. Fiorebe, “Examples of projective billiards with open sets of periodic orbits,” Discrete and Continuous Dynamical Systems- Series A, vol. 44, no. 11. AIMS, pp. 3287–3301, 2024. ista: Fiorebe C. 2024. Examples of projective billiards with open sets of periodic orbits. Discrete and Continuous Dynamical Systems- Series A. 44(11), 3287–3301. mla: Fiorebe, Corentin. “Examples of Projective Billiards with Open Sets of Periodic Orbits.” Discrete and Continuous Dynamical Systems- Series A, vol. 44, no. 11, AIMS, 2024, pp. 3287–301, doi:10.3934/dcds.2024059. short: C. Fiorebe, Discrete and Continuous Dynamical Systems- Series A 44 (2024) 3287–3301. corr_author: '1' date_created: 2024-07-14T22:01:10Z date_published: 2024-11-01T00:00:00Z date_updated: 2026-08-12T06:19:26Z day: '01' ddc: - '500' department: - _id: VaKa doi: 10.3934/dcds.2024059 external_id: isi: - '001230091000001' intvolume: ' 44' isi: 1 issue: '11' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.3934/dcds.2024059 month: '11' oa: 1 oa_version: Published Version page: 3287-3301 publication: Discrete and Continuous Dynamical Systems- Series A publication_identifier: eissn: - 1553-5231 issn: - 1078-0947 publication_status: published publisher: AIMS quality_controlled: '1' scopus_import: '1' status: public title: Examples of projective billiards with open sets of periodic orbits type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 44 year: '2024' ... --- OA_place: repository _id: '15091' abstract: - lang: eng text: "Motivated by applications in the medical sciences, we study finite chromatic\r\nsets in Euclidean space from a topological perspective. Based on the persistent\r\nhomology for images, kernels and cokernels, we design provably stable\r\nhomological quantifiers that describe the geometric micro- and macro-structure\r\nof how the color classes mingle. These can be efficiently computed using\r\nchromatic variants of Delaunay and alpha complexes, and code that does these\r\ncomputations is provided." article_number: '2212.03128' article_processing_charge: No arxiv: 1 author: - first_name: Sebastiano full_name: Cultrera di Montesano, Sebastiano id: 34D2A09C-F248-11E8-B48F-1D18A9856A87 last_name: Cultrera di Montesano orcid: 0000-0001-6249-0832 - first_name: Ondrej full_name: Draganov, Ondrej id: 2B23F01E-F248-11E8-B48F-1D18A9856A87 last_name: Draganov orcid: 0000-0003-0464-3823 - first_name: Herbert full_name: Edelsbrunner, Herbert id: 3FB178DA-F248-11E8-B48F-1D18A9856A87 last_name: Edelsbrunner orcid: 0000-0002-9823-6833 - first_name: Morteza full_name: Saghafian, Morteza id: f86f7148-b140-11ec-9577-95435b8df824 last_name: Saghafian citation: ama: Cultrera di Montesano S, Draganov O, Edelsbrunner H, Saghafian M. Chromatic alpha complexes. arXiv. doi:10.48550/arXiv.2212.03128 apa: Cultrera di Montesano, S., Draganov, O., Edelsbrunner, H., & Saghafian, M. (n.d.). Chromatic alpha complexes. arXiv. https://doi.org/10.48550/arXiv.2212.03128 chicago: Cultrera di Montesano, Sebastiano, Ondrej Draganov, Herbert Edelsbrunner, and Morteza Saghafian. “Chromatic Alpha Complexes.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2212.03128. ieee: S. Cultrera di Montesano, O. Draganov, H. Edelsbrunner, and M. Saghafian, “Chromatic alpha complexes,” arXiv. . ista: Cultrera di Montesano S, Draganov O, Edelsbrunner H, Saghafian M. Chromatic alpha complexes. arXiv, 2212.03128. mla: Cultrera di Montesano, Sebastiano, et al. “Chromatic Alpha Complexes.” ArXiv, 2212.03128, doi:10.48550/arXiv.2212.03128. short: S. Cultrera di Montesano, O. Draganov, H. Edelsbrunner, M. Saghafian, ArXiv (n.d.). corr_author: '1' date_created: 2024-03-08T10:13:59Z date_published: 2024-02-07T00:00:00Z date_updated: 2026-08-12T06:19:48Z day: '07' department: - _id: HeEd doi: 10.48550/arXiv.2212.03128 external_id: arxiv: - '2212.03128' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2212.03128 month: '02' oa: 1 oa_version: Preprint publication: arXiv publication_status: draft related_material: record: - id: '18979' relation: dissertation_contains status: public - id: '15094' relation: dissertation_contains status: public - id: '20585' relation: later_version status: public status: public title: Chromatic alpha complexes tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2024' ... --- _id: '17898' abstract: - lang: eng text: 'There is an ever-growing zoo of modern neural network models that can efficiently learn end-to-end control from visual observations. These advanced deep models, ranging from convolutional to Vision Transformers, from small to gigantic networks, have been extensively tested on offline image classification tasks. In this paper, we study these vision models with respect to the open-loop training to closed-loop generalization abilities, i.e., deployment realizes a causal feedback loop that is not present during training. This causality gap typically emerges in robotics applications such as autonomous driving, where a network is trained to imitate the control commands of a human. In this setting, two situations arise: 1) Closed-loop testing in-distribution, where the test environment shares properties with those of offline training data. 2) Closed-loop testing under distribution shifts and out-of-distribution. Contrary to recently reported results, we show that under proper training guidelines, all vision architectures perform indistinguishably well on in-distribution deployment, resolving the causality gap. In situation 2, We observe that scale is the strongest factor in improving closed-loop generalization regardless of the choice of the model architecture. Our results predict the trend that in the future we will see larger and larger models being used in offline-training-online-deployment imitation learning tasks in robotic applications.' acknowledgement: This work was partially supported in parts by the ERC-2020-AdG 101020093. Additionally, it was partially sponsored by the United States Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under Cooperative Agreement Number FA8750-19-2-1000. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein. This work was further supported by The Boeing Company and the Office of Naval Research (ONR) Grant N00014-18-1-2830. article_processing_charge: No author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Alexander full_name: Amini, Alexander last_name: Amini - first_name: Tsun Hsuan full_name: Wang, Tsun Hsuan last_name: Wang - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Daniela full_name: Rus, Daniela last_name: Rus citation: ama: 'Lechner M, Hasani R, Amini A, Wang TH, Henzinger TA, Rus D. Overparametrization helps offline-to-online generalization of closed-loop control from pixels. In: Proceedings of the 2024 IEEE International Conference on Robotics and Automation. IEEE; 2024:2774-2782. doi:10.1109/ICRA57147.2024.10610284' apa: 'Lechner, M., Hasani, R., Amini, A., Wang, T. H., Henzinger, T. A., & Rus, D. (2024). Overparametrization helps offline-to-online generalization of closed-loop control from pixels. In Proceedings of the 2024 IEEE International Conference on Robotics and Automation (pp. 2774–2782). Yokohama, Japan: IEEE. https://doi.org/10.1109/ICRA57147.2024.10610284' chicago: Lechner, Mathias, Ramin Hasani, Alexander Amini, Tsun Hsuan Wang, Thomas A Henzinger, and Daniela Rus. “Overparametrization Helps Offline-to-Online Generalization of Closed-Loop Control from Pixels.” In Proceedings of the 2024 IEEE International Conference on Robotics and Automation, 2774–82. IEEE, 2024. https://doi.org/10.1109/ICRA57147.2024.10610284. ieee: M. Lechner, R. Hasani, A. Amini, T. H. Wang, T. A. Henzinger, and D. Rus, “Overparametrization helps offline-to-online generalization of closed-loop control from pixels,” in Proceedings of the 2024 IEEE International Conference on Robotics and Automation, Yokohama, Japan, 2024, pp. 2774–2782. ista: 'Lechner M, Hasani R, Amini A, Wang TH, Henzinger TA, Rus D. 2024. Overparametrization helps offline-to-online generalization of closed-loop control from pixels. Proceedings of the 2024 IEEE International Conference on Robotics and Automation. ICRA: International Conference on Robotics and Automation, 2774–2782.' mla: Lechner, Mathias, et al. “Overparametrization Helps Offline-to-Online Generalization of Closed-Loop Control from Pixels.” Proceedings of the 2024 IEEE International Conference on Robotics and Automation, IEEE, 2024, pp. 2774–82, doi:10.1109/ICRA57147.2024.10610284. short: M. Lechner, R. Hasani, A. Amini, T.H. Wang, T.A. Henzinger, D. Rus, in:, Proceedings of the 2024 IEEE International Conference on Robotics and Automation, IEEE, 2024, pp. 2774–2782. conference: end_date: 2024-05-17 location: Yokohama, Japan name: 'ICRA: International Conference on Robotics and Automation' start_date: 2024-05-13 date_created: 2024-09-08T22:01:13Z date_published: 2024-08-08T00:00:00Z date_updated: 2026-08-12T06:35:50Z day: '08' department: - _id: ToHe doi: 10.1109/ICRA57147.2024.10610284 ec_funded: 1 external_id: isi: - '001294576202044' isi: 1 language: - iso: eng month: '08' oa_version: None page: 2774-2782 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: Proceedings of the 2024 IEEE International Conference on Robotics and Automation publication_identifier: isbn: - '9798350384574' issn: - 1050-4729 publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Overparametrization helps offline-to-online generalization of closed-loop control from pixels type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2024' ... --- _id: '17893' abstract: - lang: eng text: Strong data processing inequalities (SDPI) are an important object of study in Information Theory and have been well studied for f -divergences. Universal upper and lower bounds have been provided along with several applications, connecting them to impossibility (converse) results, concentration of measure, hypercontractivity, and so on. In this paper, we study Renyi divergence and the corresponding SDPI constant whose behavior seems to deviate from that of ordinary <1>-divergences. In particular, one can find examples showing that the universal upper bound relating its SDPI constant to the one of Total Variation does not hold in general. In this work, we prove, however, that the universal lower bound involving the SDPI constant of the Chi-square divergence does indeed hold. Furthermore, we also provide a characterization of the distribution that achieves the supremum when is equal to 2 and consequently compute the SDPI constant for Renyi divergence of the general binary channel. acknowledgement: "The work in this paper was supported in part by the Swiss National Science Foundation under Grant 200364.\r\n" article_processing_charge: No arxiv: 1 author: - first_name: Lifu full_name: Jin, Lifu last_name: Jin - first_name: Amedeo Roberto full_name: Esposito, Amedeo Roberto id: 9583e921-e1ad-11ec-9862-cef099626dc9 last_name: Esposito - first_name: Michael full_name: Gastpar, Michael last_name: Gastpar citation: ama: 'Jin L, Esposito AR, Gastpar M. Properties of the strong data processing constant for Rényi divergence. In: Proceedings of the 2024 IEEE International Symposium on Information Theory. IEEE; 2024:3178-3183. doi:10.1109/ISIT57864.2024.10619367' apa: 'Jin, L., Esposito, A. R., & Gastpar, M. (2024). Properties of the strong data processing constant for Rényi divergence. In Proceedings of the 2024 IEEE International Symposium on Information Theory (pp. 3178–3183). Athens, Greece: IEEE. https://doi.org/10.1109/ISIT57864.2024.10619367' chicago: Jin, Lifu, Amedeo Roberto Esposito, and Michael Gastpar. “Properties of the Strong Data Processing Constant for Rényi Divergence.” In Proceedings of the 2024 IEEE International Symposium on Information Theory, 3178–83. IEEE, 2024. https://doi.org/10.1109/ISIT57864.2024.10619367. ieee: L. Jin, A. R. Esposito, and M. Gastpar, “Properties of the strong data processing constant for Rényi divergence,” in Proceedings of the 2024 IEEE International Symposium on Information Theory, Athens, Greece, 2024, pp. 3178–3183. ista: 'Jin L, Esposito AR, Gastpar M. 2024. Properties of the strong data processing constant for Rényi divergence. Proceedings of the 2024 IEEE International Symposium on Information Theory. ISIT: International Symposium on Information Theory, 3178–3183.' mla: Jin, Lifu, et al. “Properties of the Strong Data Processing Constant for Rényi Divergence.” Proceedings of the 2024 IEEE International Symposium on Information Theory, IEEE, 2024, pp. 3178–83, doi:10.1109/ISIT57864.2024.10619367. short: L. Jin, A.R. Esposito, M. Gastpar, in:, Proceedings of the 2024 IEEE International Symposium on Information Theory, IEEE, 2024, pp. 3178–3183. conference: end_date: 2024-07-12 location: Athens, Greece name: 'ISIT: International Symposium on Information Theory' start_date: 2024-07-07 corr_author: '1' date_created: 2024-09-08T22:01:12Z date_published: 2024-08-19T00:00:00Z date_updated: 2026-08-12T06:38:02Z day: '19' department: - _id: MaMo doi: 10.1109/ISIT57864.2024.10619367 external_id: arxiv: - '2403.10656' isi: - '001304426903055' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: 'https://doi.org/10.48550/arXiv.2403.10656 ' month: '08' oa: 1 oa_version: Preprint page: 3178-3183 publication: Proceedings of the 2024 IEEE International Symposium on Information Theory publication_identifier: isbn: - '9798350382846' issn: - 2157-8095 publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Properties of the strong data processing constant for Rényi divergence type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2024' ... --- _id: '17895' abstract: - lang: eng text: We propose a concatenated code construction for a class of discrete-alphabet oblivious arbitrarily varying channels (AVCs) with cost constraints. The code has time and space complexity polynomial in the blocklength n . It uses a Reed-Solomon outer code, logarithmic blocklength random inner codes, and stochastic encoding by permuting the codeword before transmission. When the channel satisfies a condition called strong DS-nonsymmetrizability (a modified version of nonsymmetrizability originally due to Dobrushin and Stambler), we show that the code achieves a rate that for a variety of oblivious AVCs (such as classically studied error/erasure channels) match the known capacities. acknowledgement: "The work of M. Langberg and A. D. Sarwate was supported in part by the US NSF under awards CCF-1909451 and CCF1909468. B. K. Dey was supported in part by the Bharti Centre\r\nfor Communication in IIT Bombay. " article_processing_charge: No author: - first_name: B. K. full_name: Dey, B. K. last_name: Dey - first_name: S. full_name: Jaggi, S. last_name: Jaggi - first_name: M. full_name: Langberg, M. last_name: Langberg - first_name: A. D. full_name: Sarwate, A. D. last_name: Sarwate - first_name: Yihan full_name: Zhang, Yihan id: 2ce5da42-b2ea-11eb-bba5-9f264e9d002c last_name: Zhang orcid: 0000-0002-6465-6258 citation: ama: 'Dey BK, Jaggi S, Langberg M, Sarwate AD, Zhang Y. Computationally efficient codes for strongly Dobrushin-Stambler nonsymmetrizable oblivious AVCs. In: Proceedings of the 2024 IEEE International Symposium on Information Theory . IEEE; 2024:1586-1591. doi:10.1109/ISIT57864.2024.10619362' apa: 'Dey, B. K., Jaggi, S., Langberg, M., Sarwate, A. D., & Zhang, Y. (2024). Computationally efficient codes for strongly Dobrushin-Stambler nonsymmetrizable oblivious AVCs. In Proceedings of the 2024 IEEE International Symposium on Information Theory (pp. 1586–1591). Athens, Greece: IEEE. https://doi.org/10.1109/ISIT57864.2024.10619362' chicago: Dey, B. K., S. Jaggi, M. Langberg, A. D. Sarwate, and Yihan Zhang. “Computationally Efficient Codes for Strongly Dobrushin-Stambler Nonsymmetrizable Oblivious AVCs.” In Proceedings of the 2024 IEEE International Symposium on Information Theory , 1586–91. IEEE, 2024. https://doi.org/10.1109/ISIT57864.2024.10619362. ieee: B. K. Dey, S. Jaggi, M. Langberg, A. D. Sarwate, and Y. Zhang, “Computationally efficient codes for strongly Dobrushin-Stambler nonsymmetrizable oblivious AVCs,” in Proceedings of the 2024 IEEE International Symposium on Information Theory , Athens, Greece, 2024, pp. 1586–1591. ista: 'Dey BK, Jaggi S, Langberg M, Sarwate AD, Zhang Y. 2024. Computationally efficient codes for strongly Dobrushin-Stambler nonsymmetrizable oblivious AVCs. Proceedings of the 2024 IEEE International Symposium on Information Theory . ISIT: International Symposium on Information Theory, 1586–1591.' mla: Dey, B. K., et al. “Computationally Efficient Codes for Strongly Dobrushin-Stambler Nonsymmetrizable Oblivious AVCs.” Proceedings of the 2024 IEEE International Symposium on Information Theory , IEEE, 2024, pp. 1586–91, doi:10.1109/ISIT57864.2024.10619362. short: B.K. Dey, S. Jaggi, M. Langberg, A.D. Sarwate, Y. Zhang, in:, Proceedings of the 2024 IEEE International Symposium on Information Theory , IEEE, 2024, pp. 1586–1591. conference: end_date: 2024-07-12 location: Athens, Greece name: 'ISIT: International Symposium on Information Theory' start_date: 2024-07-07 date_created: 2024-09-08T22:01:12Z date_published: 2024-08-19T00:00:00Z date_updated: 2026-08-12T06:37:45Z day: '19' department: - _id: MaMo doi: 10.1109/ISIT57864.2024.10619362 external_id: isi: - '001304426901091' isi: 1 language: - iso: eng month: '08' oa_version: None page: 1586-1591 publication: 'Proceedings of the 2024 IEEE International Symposium on Information Theory ' publication_identifier: isbn: - '9798350382846' issn: - 2157-8095 publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Computationally efficient codes for strongly Dobrushin-Stambler nonsymmetrizable oblivious AVCs type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2024' ... --- _id: '17894' abstract: - lang: eng text: 'Sibson''s α -mutual information has received renewed attention recently in several contexts: concentration of measure under dependence, statistical learning, hypothesis testing, and estimation theory. In this work, we introduce several variational representations of Sibson''s α -mutual information: 1) as a supremum over joint distributions of (a combination of) KL divergences; and 2) as a supremum over functions of opportune expected values. Leveraging them, we produce a variety of novel and known results, including a generalization of transportation-cost inequalities and Fano''s inequality.' acknowledgement: The work in this paper was supported in part by the Swiss National Science Foundation under Grant 200364. article_processing_charge: No author: - first_name: Amedeo Roberto full_name: Esposito, Amedeo Roberto id: 9583e921-e1ad-11ec-9862-cef099626dc9 last_name: Esposito - first_name: Michael full_name: Gastpar, Michael last_name: Gastpar - first_name: Ibrahim full_name: Issa, Ibrahim last_name: Issa citation: ama: 'Esposito AR, Gastpar M, Issa I. Variational characterizations of Sibson’s α-mutual information. In: Proceedings of the 2024 IEEE International Symposium on Information Theory . IEEE; 2024:2110-2115. doi:10.1109/ISIT57864.2024.10619378' apa: 'Esposito, A. R., Gastpar, M., & Issa, I. (2024). Variational characterizations of Sibson’s α-mutual information. In Proceedings of the 2024 IEEE International Symposium on Information Theory (pp. 2110–2115). Athens, Greece: IEEE. https://doi.org/10.1109/ISIT57864.2024.10619378' chicago: Esposito, Amedeo Roberto, Michael Gastpar, and Ibrahim Issa. “Variational Characterizations of Sibson’s α-Mutual Information.” In Proceedings of the 2024 IEEE International Symposium on Information Theory , 2110–15. IEEE, 2024. https://doi.org/10.1109/ISIT57864.2024.10619378. ieee: A. R. Esposito, M. Gastpar, and I. Issa, “Variational characterizations of Sibson’s α-mutual information,” in Proceedings of the 2024 IEEE International Symposium on Information Theory , Athens, Greece, 2024, pp. 2110–2115. ista: 'Esposito AR, Gastpar M, Issa I. 2024. Variational characterizations of Sibson’s α-mutual information. Proceedings of the 2024 IEEE International Symposium on Information Theory . ISIT: International Symposium on Information Theory, 2110–2115.' mla: Esposito, Amedeo Roberto, et al. “Variational Characterizations of Sibson’s α-Mutual Information.” Proceedings of the 2024 IEEE International Symposium on Information Theory , IEEE, 2024, pp. 2110–15, doi:10.1109/ISIT57864.2024.10619378. short: A.R. Esposito, M. Gastpar, I. Issa, in:, Proceedings of the 2024 IEEE International Symposium on Information Theory , IEEE, 2024, pp. 2110–2115. conference: end_date: 2024-07-12 location: Athens, Greece name: 'ISIT: International Symposium on Information Theory' start_date: 2024-07-07 corr_author: '1' date_created: 2024-09-08T22:01:12Z date_published: 2024-08-19T00:00:00Z date_updated: 2026-08-12T06:38:18Z day: '19' department: - _id: MaMo doi: 10.1109/ISIT57864.2024.10619378 external_id: isi: - '001304426902023' isi: 1 language: - iso: eng month: '08' oa_version: None page: 2110-2115 publication: 'Proceedings of the 2024 IEEE International Symposium on Information Theory ' publication_identifier: isbn: - '9798350382846' issn: - 2157-8095 publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Variational characterizations of Sibson's α-mutual information type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2024' ... --- DOAJ_listed: '1' OA_place: publisher OA_type: gold _id: '18630' abstract: - lang: eng text: 'Markov chains are the de facto finite-state model for stochastic dynamical systems, and Markov decision processes (MDPs) extend Markov chains by incorporating non-deterministic behaviors. Given an MDP and rewards on states, a classical optimization criterion is the maximal expected total reward where the MDP stops after T steps, which can be computed by a simple dynamic programming algorithm. We consider a natural generalization of the problem where the stopping times can be chosen according to a probability distribution, such that the expected stopping time is T, to optimize the expected total reward. Quite surprisingly we establish inter-reducibility of the expected stopping-time problem for Markov chains with the Positivity problem (which is related to the well-known Skolem problem), for which establishing either decidability or undecidability would be a major breakthrough. Given the hardness of the exact problem, we consider the approximate version of the problem: we show that it can be solved in exponential time for Markov chains and in exponential space for MDPs.' acknowledgement: The authors are grateful to the anonymous reviewers of LICS 2021 and of a previous version of this paper for insightful comments that helped improving the presentation. The research presented in this paper was partially supported by the grant ERC CoG 863818 (ForM-SMArt). alternative_title: - LMCS article_processing_charge: Yes article_type: original arxiv: 1 author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Laurent full_name: Doyen, Laurent last_name: Doyen citation: ama: Chatterjee K, Doyen L. Stochastic processes with expected stopping time. Logical Methods in Computer Science. 2024;20(4):11:1-11:34. doi:10.46298/lmcs-20(4:11)2024 apa: Chatterjee, K., & Doyen, L. (2024). Stochastic processes with expected stopping time. Logical Methods in Computer Science. EPI Sciences. https://doi.org/10.46298/lmcs-20(4:11)2024 chicago: Chatterjee, Krishnendu, and Laurent Doyen. “Stochastic Processes with Expected Stopping Time.” Logical Methods in Computer Science. EPI Sciences, 2024. https://doi.org/10.46298/lmcs-20(4:11)2024. ieee: K. Chatterjee and L. Doyen, “Stochastic processes with expected stopping time,” Logical Methods in Computer Science, vol. 20, no. 4. EPI Sciences, p. 11:1-11:34, 2024. ista: Chatterjee K, Doyen L. 2024. Stochastic processes with expected stopping time. Logical Methods in Computer Science. 20(4), 11:1-11:34. mla: Chatterjee, Krishnendu, and Laurent Doyen. “Stochastic Processes with Expected Stopping Time.” Logical Methods in Computer Science, vol. 20, no. 4, EPI Sciences, 2024, p. 11:1-11:34, doi:10.46298/lmcs-20(4:11)2024. short: K. Chatterjee, L. Doyen, Logical Methods in Computer Science 20 (2024) 11:1-11:34. corr_author: '1' date_created: 2024-12-08T23:01:56Z date_published: 2024-11-12T00:00:00Z date_updated: 2026-08-12T06:39:26Z day: '12' ddc: - '000' department: - _id: KrCh doi: 10.46298/lmcs-20(4:11)2024 ec_funded: 1 external_id: arxiv: - '2104.07278' isi: - '001367316400002' file: - access_level: open_access checksum: b3315c74ce18ce0a30ed33d8c9972992 content_type: application/pdf creator: dernst date_created: 2024-12-09T08:38:48Z date_updated: 2024-12-09T08:38:48Z file_id: '18633' file_name: 2024_LMCS_Chatterjee.pdf file_size: 416814 relation: main_file success: 1 file_date_updated: 2024-12-09T08:38:48Z has_accepted_license: '1' intvolume: ' 20' isi: 1 issue: '4' language: - iso: eng month: '11' oa: 1 oa_version: Published Version page: 11:1-11:34 project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' publication: Logical Methods in Computer Science publication_identifier: eissn: - 1860-5974 publication_status: published publisher: EPI Sciences quality_controlled: '1' related_material: record: - id: '10004' relation: earlier_version status: public scopus_import: '1' status: public title: Stochastic processes with expected stopping time tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 20 year: '2024' ... --- OA_place: publisher OA_type: hybrid _id: '18923' abstract: - lang: eng text: 'Combinatorial optimization is a challenging problem applicable in a wide range of fields from logistics to finance. Recently, quantum computing has been used to attempt to solve these problems using a range of algorithms, including parameterized quantum circuits, adiabatic protocols, and quantum annealing. These solutions typically have several challenges: 1) there is little to no performance gain over classical methods; 2) not all constraints and objectives may be efficiently encoded in the quantum ansatz; and 3) the solution domain of the objective function may not be the same as the bit strings of measurement outcomes. This work presents “nonnative hybrid algorithms”: a framework to overcome these challenges by integrating quantum and classical resources with a hybrid approach. By designing nonnative quantum variational anosatzes that inherit some but not all problem structure, measurement outcomes from the quantum computer can act as a resource to be used by classical routines to indirectly compute optimal solutions, partially overcoming the challenges of contemporary quantum optimization approaches. These methods are demonstrated using a publicly available neutral-atom quantum computer on two simple problems of Max k-Cut and maximum independent set. We find improvements in solution quality when comparing the hybrid algorithm to its “no quantum” version, a demonstration of a “comparative advantage.”' acknowledgement: "The authors would like to thank Alexander Keesling, Maddie Cain, Nate Gemelke, and Phillip Weinberg for helpful discussions and Danylo Lykov who had early contributions to this work.\r\n10.13039/100000185-Defense Advanced Research Projects Agency Noisy Intermediate-Scale Quantum Devices (Grant Number: W911NF2010021), DARPA Small Business Technology Transfer program (Grant Number: 140D0422C0035)." article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Jonathan full_name: Wurtz, Jonathan last_name: Wurtz - first_name: Stefan full_name: Sack, Stefan id: dd622248-f6e0-11ea-865d-ce382a1c81a5 last_name: Sack orcid: 0000-0001-5400-8508 - first_name: Sheng-Tao full_name: Wang, Sheng-Tao last_name: Wang citation: ama: Wurtz J, Sack S, Wang S-T. Solving nonnative combinatorial optimization problems using hybrid quantum–classical algorithms. IEEE Transactions on Quantum Engineering. 2024;5:1-14. doi:10.1109/tqe.2024.3443660 apa: Wurtz, J., Sack, S., & Wang, S.-T. (2024). Solving nonnative combinatorial optimization problems using hybrid quantum–classical algorithms. IEEE Transactions on Quantum Engineering. IEEE. https://doi.org/10.1109/tqe.2024.3443660 chicago: Wurtz, Jonathan, Stefan Sack, and Sheng-Tao Wang. “Solving Nonnative Combinatorial Optimization Problems Using Hybrid Quantum–Classical Algorithms.” IEEE Transactions on Quantum Engineering. IEEE, 2024. https://doi.org/10.1109/tqe.2024.3443660. ieee: J. Wurtz, S. Sack, and S.-T. Wang, “Solving nonnative combinatorial optimization problems using hybrid quantum–classical algorithms,” IEEE Transactions on Quantum Engineering, vol. 5. IEEE, pp. 1–14, 2024. ista: Wurtz J, Sack S, Wang S-T. 2024. Solving nonnative combinatorial optimization problems using hybrid quantum–classical algorithms. IEEE Transactions on Quantum Engineering. 5, 1–14. mla: Wurtz, Jonathan, et al. “Solving Nonnative Combinatorial Optimization Problems Using Hybrid Quantum–Classical Algorithms.” IEEE Transactions on Quantum Engineering, vol. 5, IEEE, 2024, pp. 1–14, doi:10.1109/tqe.2024.3443660. short: J. Wurtz, S. Sack, S.-T. Wang, IEEE Transactions on Quantum Engineering 5 (2024) 1–14. das_tickbox: '1' date_created: 2025-01-27T15:00:44Z date_published: 2024-08-14T00:00:00Z date_updated: 2026-08-12T06:42:26Z day: '14' ddc: - '530' department: - _id: MaSe doi: 10.1109/tqe.2024.3443660 file: - access_level: open_access checksum: 19b84e35cba05bde72bfe7e0b54c3e6c content_type: application/pdf creator: dernst date_created: 2025-01-27T15:03:09Z date_updated: 2025-01-27T15:03:09Z file_id: '18924' file_name: 2024_IEEEQuantumComputing_Wurtz.pdf file_size: 1753095 relation: main_file success: 1 file_date_updated: 2025-01-27T15:03:09Z has_accepted_license: '1' intvolume: ' 5' language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: 1-14 publication: IEEE Transactions on Quantum Engineering publication_identifier: issn: - 2689-1808 publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Solving nonnative combinatorial optimization problems using hybrid quantum–classical algorithms tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 5 year: '2024' ... --- _id: '17481' abstract: - lang: eng text: "Phase-field models such as the Allen–Cahn equation may give rise to the formation and evolution of geometric shapes, a phenomenon that may be analyzed rigorously in suitable scaling regimes. In its sharp-interface limit, the vectorial Allen–Cahn equation with a potential with N≥3 distinct minima has been conjectured to describe the evolution of branched interfaces by multiphase mean curvature flow. In the present work, we give a rigorous proof for this statement in two and three ambient dimensions and for a suitable class of potentials: as long as a strong solution to multiphase mean curvature flow exists, solutions to the vectorial Allen–Cahn equation with well-prepared initial data converge towards multiphase mean curvature flow in the limit of vanishing interface width parameter ε↘0. We even establish the rate of convergence O(ε \r\n1/2\r\n ). Our approach is based on the gradient-flow structure of the Allen–Cahn equation and its limiting motion: building on the recent concept of “gradient-flow calibrations” for multiphase mean curvature flow, we introduce a notion of relative entropy for the vectorial Allen–Cahn equation with multi-well potential. This enables us to overcome the limitations of other approaches, e.g. avoiding the need for a stability analysis of the Allen–Cahn operator or additional convergence hypotheses for the energy at positive times." acknowledgement: "The authors thank Sebastian Hensel for useful and helpful commentson the first draft of this work.\r\nThis project has received funding from the European Research Council (ERC)\r\nunder the European Union’s Horizon 2020 research and innovation programme (grant\r\nagreement no. 948819." article_processing_charge: Yes article_type: original author: - first_name: Julian L full_name: Fischer, Julian L id: 2C12A0B0-F248-11E8-B48F-1D18A9856A87 last_name: Fischer orcid: 0000-0002-0479-558X - first_name: Alice full_name: Marveggio, Alice id: 25647992-AA84-11E9-9D75-8427E6697425 last_name: Marveggio citation: ama: Fischer JL, Marveggio A. Quantitative convergence of the vectorial Allen–Cahn equation towards multiphase mean curvature flow. Annales de l’Institut Henri Poincaré C. 2024;41(5):1117-1178. doi:10.4171/AIHPC/109 apa: Fischer, J. L., & Marveggio, A. (2024). Quantitative convergence of the vectorial Allen–Cahn equation towards multiphase mean curvature flow. Annales de l’Institut Henri Poincaré C. EMS Press. https://doi.org/10.4171/AIHPC/109 chicago: Fischer, Julian L, and Alice Marveggio. “Quantitative Convergence of the Vectorial Allen–Cahn Equation towards Multiphase Mean Curvature Flow.” Annales de l’Institut Henri Poincaré C. EMS Press, 2024. https://doi.org/10.4171/AIHPC/109. ieee: J. L. Fischer and A. Marveggio, “Quantitative convergence of the vectorial Allen–Cahn equation towards multiphase mean curvature flow,” Annales de l’Institut Henri Poincaré C, vol. 41, no. 5. EMS Press, pp. 1117–1178, 2024. ista: Fischer JL, Marveggio A. 2024. Quantitative convergence of the vectorial Allen–Cahn equation towards multiphase mean curvature flow. Annales de l’Institut Henri Poincaré C. 41(5), 1117–1178. mla: Fischer, Julian L., and Alice Marveggio. “Quantitative Convergence of the Vectorial Allen–Cahn Equation towards Multiphase Mean Curvature Flow.” Annales de l’Institut Henri Poincaré C, vol. 41, no. 5, EMS Press, 2024, pp. 1117–78, doi:10.4171/AIHPC/109. short: J.L. Fischer, A. Marveggio, Annales de l’Institut Henri Poincaré C 41 (2024) 1117–1178. corr_author: '1' date_created: 2024-09-01T22:01:09Z date_published: 2024-01-24T00:00:00Z date_updated: 2026-08-12T09:15:49Z day: '24' ddc: - '510' department: - _id: JuFi doi: 10.4171/AIHPC/109 ec_funded: 1 external_id: isi: - '001293853900003' file: - access_level: open_access checksum: b5ad02d9abd5b4701269cd1ad0a1cc8f content_type: application/pdf creator: dernst date_created: 2024-09-09T07:46:42Z date_updated: 2024-09-09T07:46:42Z file_id: '17923' file_name: 2024_AnnInstHPoincare_Fischer.pdf file_size: 1348896 relation: main_file success: 1 file_date_updated: 2024-09-09T07:46:42Z has_accepted_license: '1' intvolume: ' 41' isi: 1 issue: '5' language: - iso: eng month: '01' oa: 1 oa_version: Published Version page: 1117-1178 project: - _id: 0aa76401-070f-11eb-9043-b5bb049fa26d call_identifier: H2020 grant_number: '948819' name: Bridging Scales in Random Materials publication: Annales de l'Institut Henri Poincaré C publication_identifier: eissn: - 1873-1430 issn: - 0294-1449 publication_status: published publisher: EMS Press quality_controlled: '1' related_material: record: - id: '14597' relation: earlier_version status: public scopus_import: '1' status: public title: Quantitative convergence of the vectorial Allen–Cahn equation towards multiphase mean curvature flow tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 41 year: '2024' ... --- _id: '15048' abstract: - lang: eng text: Embryogenesis results from the coordinated activities of different signaling pathways controlling cell fate specification and morphogenesis. In vertebrate gastrulation, both Nodal and BMP signaling play key roles in germ layer specification and morphogenesis, yet their interplay to coordinate embryo patterning with morphogenesis is still insufficiently understood. Here, we took a reductionist approach using zebrafish embryonic explants to study the coordination of Nodal and BMP signaling for embryo patterning and morphogenesis. We show that Nodal signaling triggers explant elongation by inducing mesendodermal progenitors but also suppressing BMP signaling activity at the site of mesendoderm induction. Consistent with this, ectopic BMP signaling in the mesendoderm blocks cell alignment and oriented mesendoderm intercalations, key processes during explant elongation. Translating these ex vivo observations to the intact embryo showed that, similar to explants, Nodal signaling suppresses the effect of BMP signaling on cell intercalations in the dorsal domain, thus allowing robust embryonic axis elongation. These findings suggest a dual function of Nodal signaling in embryonic axis elongation by both inducing mesendoderm and suppressing BMP effects in the dorsal portion of the mesendoderm. acknowledged_ssus: - _id: Bio - _id: LifeSc acknowledgement: "We thank Patrick Müller for sharing the chordintt250 mutant zebrafish line as well as the plasmid for chrd-GFP, Katherine Rogers for sharing the bmp2b plasmid and Andrea Pauli for sharing the draculin plasmid. Diana Pinheiro generated the MZlefty1,2;Tg(sebox::EGFP) line. We are grateful to Patrick Müller, Diana Pinheiro and Katherine Rogers and members of the Heisenberg lab for discussions, technical advice and feedback on the manuscript. We also thank Anna Kicheva and Edouard Hannezo for discussions. We thank the Imaging and Optics Facility as well as the Life Science facility at IST Austria for support with microscopy and fish maintenance.\r\nThis work was supported by a European Research Council Advanced Grant\r\n(MECSPEC 742573 to C.-P.H.). A.S. is a recipient of a DOC Fellowship of the Austrian\r\nAcademy of Sciences at IST Austria. Open Access funding provided by Institute of\r\nScience and Technology Austria. " article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Alexandra full_name: Schauer, Alexandra id: 30A536BA-F248-11E8-B48F-1D18A9856A87 last_name: Schauer orcid: 0000-0001-7659-9142 - first_name: Kornelija full_name: Pranjic-Ferscha, Kornelija id: 4362B3C2-F248-11E8-B48F-1D18A9856A87 last_name: Pranjic-Ferscha - first_name: Robert full_name: Hauschild, Robert id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87 last_name: Hauschild orcid: 0000-0001-9843-3522 - first_name: Carl-Philipp J full_name: Heisenberg, Carl-Philipp J id: 39427864-F248-11E8-B48F-1D18A9856A87 last_name: Heisenberg orcid: 0000-0002-0912-4566 citation: ama: Schauer A, Pranjic-Ferscha K, Hauschild R, Heisenberg C-PJ. Robust axis elongation by Nodal-dependent restriction of BMP signaling. Development. 2024;151(4):1-18. doi:10.1242/dev.202316 apa: Schauer, A., Pranjic-Ferscha, K., Hauschild, R., & Heisenberg, C.-P. J. (2024). Robust axis elongation by Nodal-dependent restriction of BMP signaling. Development. Company of Biologists. https://doi.org/10.1242/dev.202316 chicago: Schauer, Alexandra, Kornelija Pranjic-Ferscha, Robert Hauschild, and Carl-Philipp J Heisenberg. “Robust Axis Elongation by Nodal-Dependent Restriction of BMP Signaling.” Development. Company of Biologists, 2024. https://doi.org/10.1242/dev.202316. ieee: A. Schauer, K. Pranjic-Ferscha, R. Hauschild, and C.-P. J. Heisenberg, “Robust axis elongation by Nodal-dependent restriction of BMP signaling,” Development, vol. 151, no. 4. Company of Biologists, pp. 1–18, 2024. ista: Schauer A, Pranjic-Ferscha K, Hauschild R, Heisenberg C-PJ. 2024. Robust axis elongation by Nodal-dependent restriction of BMP signaling. Development. 151(4), 1–18. mla: Schauer, Alexandra, et al. “Robust Axis Elongation by Nodal-Dependent Restriction of BMP Signaling.” Development, vol. 151, no. 4, Company of Biologists, 2024, pp. 1–18, doi:10.1242/dev.202316. short: A. Schauer, K. Pranjic-Ferscha, R. Hauschild, C.-P.J. Heisenberg, Development 151 (2024) 1–18. corr_author: '1' date_created: 2024-03-03T23:00:50Z date_published: 2024-02-01T00:00:00Z date_updated: 2026-08-12T10:00:14Z day: '01' ddc: - '570' department: - _id: CaHe - _id: Bio doi: 10.1242/dev.202316 ec_funded: 1 external_id: isi: - '001170580200001' pmid: - '38372390' file: - access_level: open_access checksum: 6961ea10012bf0d266681f9628bb8f13 content_type: application/pdf creator: dernst date_created: 2024-03-04T07:24:43Z date_updated: 2024-03-04T07:24:43Z file_id: '15050' file_name: 2024_Development_Schauer.pdf file_size: 14839986 relation: main_file success: 1 file_date_updated: 2024-03-04T07:24:43Z has_accepted_license: '1' intvolume: ' 151' isi: 1 issue: '4' language: - iso: eng month: '02' oa: 1 oa_version: Published Version page: 1-18 pmid: 1 project: - _id: 260F1432-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '742573' name: Interaction and feedback between cell mechanics and fate specification in vertebrate gastrulation - _id: 26B1E39C-B435-11E9-9278-68D0E5697425 grant_number: '25239' name: 'Mesendoderm specification in zebrafish: The role of extraembryonic tissues' publication: Development publication_identifier: eissn: - 1477-9129 issn: - 0950-1991 publication_status: published publisher: Company of Biologists quality_controlled: '1' related_material: record: - id: '14926' relation: research_data status: public scopus_import: '1' status: public title: Robust axis elongation by Nodal-dependent restriction of BMP signaling tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 151 year: '2024' ... --- _id: '17458' abstract: - lang: eng text: Changes in gene dosage can have tremendous evolutionary potential (e.g. whole-genome duplications), but without compensatory mechanisms, they can also lead to gene dysregulation and pathologies. Sex chromosomes are a paradigmatic example of naturally occurring gene dosage differences and their compensation. In species with chromosome-based sex determination, individuals within the same population necessarily show ‘natural’ differences in gene dosage for the sex chromosomes. In this Review, we focus on the mammalian X chromosome and discuss recent new insights into the dosage-compensation mechanisms that evolved along with the emergence of sex chromosomes, namely X-inactivation and X-upregulation. We also discuss the evolution of the genetic loci and molecular players involved, as well as the regulatory diversity and potentially different requirements for dosage compensation across mammalian species. acknowledgement: We thank Estelle Nicolas for critical feedback on the manuscript and Ikuhiro Okamoto for critical feedback on the figures. We apologise to authors whose work we overlooked or did not discuss or cite due to limits in the number of references. We thank the anonymous reviewers for pointing us to additional literature and for their constructive feedback. Figures were prepared with BioRender.com. D.C. is supported by a fellowship from Ligue Contre le Cancer (LNCC_TAJT25850) and R.G. holds a tenured research position from the Centre National de la Recherche Scientifique (France). Research in the Galupa lab is supported by a grant from the Fondation pour la Recherche Médicale (AJE202305017142). Open Access funding provided by Fondation pour la Recherche Médicale. Deposited in PMC for immediate release. article_number: dev202891 article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Daniela full_name: Cecalev, Daniela last_name: Cecalev - first_name: Beatriz full_name: Vicoso, Beatriz id: 49E1C5C6-F248-11E8-B48F-1D18A9856A87 last_name: Vicoso orcid: 0000-0002-4579-8306 - first_name: Rafael full_name: Galupa, Rafael last_name: Galupa citation: ama: Cecalev D, Vicoso B, Galupa R. Compensation of gene dosage on the mammalian X. Development. 2024;151(15). doi:10.1242/dev.202891 apa: Cecalev, D., Vicoso, B., & Galupa, R. (2024). Compensation of gene dosage on the mammalian X. Development. Company of Biologists. https://doi.org/10.1242/dev.202891 chicago: Cecalev, Daniela, Beatriz Vicoso, and Rafael Galupa. “Compensation of Gene Dosage on the Mammalian X.” Development. Company of Biologists, 2024. https://doi.org/10.1242/dev.202891. ieee: D. Cecalev, B. Vicoso, and R. Galupa, “Compensation of gene dosage on the mammalian X,” Development, vol. 151, no. 15. Company of Biologists, 2024. ista: Cecalev D, Vicoso B, Galupa R. 2024. Compensation of gene dosage on the mammalian X. Development. 151(15), dev202891. mla: Cecalev, Daniela, et al. “Compensation of Gene Dosage on the Mammalian X.” Development, vol. 151, no. 15, dev202891, Company of Biologists, 2024, doi:10.1242/dev.202891. short: D. Cecalev, B. Vicoso, R. Galupa, Development 151 (2024). date_created: 2024-08-25T22:01:07Z date_published: 2024-08-14T00:00:00Z date_updated: 2026-08-12T10:01:13Z day: '14' ddc: - '599' department: - _id: BeVi doi: 10.1242/dev.202891 external_id: isi: - '001292608800003' pmid: - '39140247' file: - access_level: open_access checksum: 5e428bda0440d3f957c694b315a8f2a9 content_type: application/pdf creator: cchlebak date_created: 2024-08-28T10:32:16Z date_updated: 2024-08-28T10:32:16Z file_id: '17464' file_name: 2024_Development_Cecalev.pdf file_size: 2085135 relation: main_file success: 1 file_date_updated: 2024-08-28T10:32:16Z has_accepted_license: '1' intvolume: ' 151' isi: 1 issue: '15' language: - iso: eng month: '08' oa: 1 oa_version: Published Version pmid: 1 publication: Development publication_identifier: eissn: - 1477-9129 issn: - 0950-1991 publication_status: published publisher: Company of Biologists quality_controlled: '1' scopus_import: '1' status: public title: Compensation of gene dosage on the mammalian X tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 151 year: '2024' ...