[{"intvolume":"        21","related_material":{"link":[{"url":"https://github.com/tuoping/alchemicalFES","relation":"software"}]},"doi":"10.1021/acs.jctc.5c01248","scopus_import":"1","date_created":"2025-11-30T23:02:06Z","citation":{"ama":"Tuo P, Zeng Z, Chen J, Cheng B. Scalable multitemperature free energy sampling of classical Ising spin states. <i>Journal of Chemical Theory and Computation</i>. 2025;21(22):11427-11435. doi:<a href=\"https://doi.org/10.1021/acs.jctc.5c01248\">10.1021/acs.jctc.5c01248</a>","ieee":"P. Tuo, Z. Zeng, J. Chen, and B. Cheng, “Scalable multitemperature free energy sampling of classical Ising spin states,” <i>Journal of Chemical Theory and Computation</i>, vol. 21, no. 22. American Chemical Society, pp. 11427–11435, 2025.","short":"P. Tuo, Z. Zeng, J. Chen, B. Cheng, Journal of Chemical Theory and Computation 21 (2025) 11427–11435.","mla":"Tuo, Ping, et al. “Scalable Multitemperature Free Energy Sampling of Classical Ising Spin States.” <i>Journal of Chemical Theory and Computation</i>, vol. 21, no. 22, American Chemical Society, 2025, pp. 11427–35, doi:<a href=\"https://doi.org/10.1021/acs.jctc.5c01248\">10.1021/acs.jctc.5c01248</a>.","chicago":"Tuo, Ping, Zezhu Zeng, Jiale Chen, and Bingqing Cheng. “Scalable Multitemperature Free Energy Sampling of Classical Ising Spin States.” <i>Journal of Chemical Theory and Computation</i>. American Chemical Society, 2025. <a href=\"https://doi.org/10.1021/acs.jctc.5c01248\">https://doi.org/10.1021/acs.jctc.5c01248</a>.","apa":"Tuo, P., Zeng, Z., Chen, J., &#38; Cheng, B. (2025). Scalable multitemperature free energy sampling of classical Ising spin states. <i>Journal of Chemical Theory and Computation</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.jctc.5c01248\">https://doi.org/10.1021/acs.jctc.5c01248</a>","ista":"Tuo P, Zeng Z, Chen J, Cheng B. 2025. Scalable multitemperature free energy sampling of classical Ising spin states. Journal of Chemical Theory and Computation. 21(22), 11427–11435."},"quality_controlled":"1","day":"31","corr_author":"1","article_processing_charge":"No","abstract":[{"lang":"eng","text":"Generative models have advanced significantly in sampling material systems with continuous variables, such as atomistic structures. However, their application to discrete variables, like atom types or spin states, remains underexplored. In this work, we introduce a discrete flow matching model, tailored for systems with discrete phase-space coordinates (e.g., the Ising model or a multicomponent system on a lattice). This approach enables a single model to sample free energy surfaces over a wide temperature range with minimal training overhead, and the model generation is scalable to larger lattice sizes than those in the training set. We demonstrate our approach on the 2D Ising model, showing efficient and reliable free energy sampling. These results highlight the potential of flow matching for low-cost, scalable free energy sampling in discrete systems and suggest promising extensions to alchemical degrees of freedom in crystalline materials. The codebase developed for this work is openly available at https://github.com/tuoping/alchemicalFES."}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2025-10-31T00:00:00Z","author":[{"full_name":"Tuo, Ping","id":"6e5644c0-c180-11ed-a2da-facc4c9f4f09","last_name":"Tuo","first_name":"Ping"},{"first_name":"Zezhu","orcid":"0000-0001-5126-4928","full_name":"Zeng, Zezhu","last_name":"Zeng","id":"54a2c730-803f-11ed-ab7e-95b29d2680e7"},{"last_name":"Chen","id":"4d0a9064-1ff6-11ee-9fa6-ec046c604785","full_name":"Chen, Jiale","orcid":"0000-0001-5337-5875","first_name":"Jiale"},{"last_name":"Cheng","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","full_name":"Cheng, Bingqing","orcid":"0000-0002-3584-9632","first_name":"Bingqing"}],"external_id":{"pmid":["41172130"],"isi":["001605927900001"]},"volume":21,"status":"public","acknowledgement":"P.T. acknowledges funding from FFG MAGNIFICO and the BIDMaP Postdoctoral Fellowship. Z.Z. acknowledges funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 101034413. The authors acknowledge the research computing facilities provided by the Institute of Science and Technology Austria (ISTA), and resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy Office of Science User Facility using NERSC award DOEERCAP0031751 ’GenAI@NERSC’. P.T. acknowledges valued discussions with Dr. Daniel King, Dr. Lei Wang, and Dr. Fuzhi Dai.","year":"2025","page":"11427-11435","publication":"Journal of Chemical Theory and Computation","language":[{"iso":"eng"}],"issue":"22","ec_funded":1,"_id":"20704","pmid":1,"isi":1,"acknowledged_ssus":[{"_id":"ScienComp"}],"publication_identifier":{"issn":["1549-9618"],"eissn":["1549-9626"]},"date_updated":"2025-12-01T15:40:27Z","title":"Scalable multitemperature free energy sampling of classical Ising spin states","department":[{"_id":"BiCh"},{"_id":"DaAl"}],"project":[{"_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","name":"IST-BRIDGE: International postdoctoral program","call_identifier":"H2020","grant_number":"101034413"}],"month":"10","article_type":"original","OA_type":"closed access","type":"journal_article","publisher":"American Chemical Society","publication_status":"published","oa_version":"None"},{"publisher":"American Chemical Society","publication_status":"published","type":"journal_article","oa_version":"Preprint","arxiv":1,"month":"12","article_type":"original","OA_type":"green","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2507.14302"}],"date_updated":"2026-01-05T11:34:21Z","department":[{"_id":"GradSch"},{"_id":"BiCh"}],"title":"A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials","_id":"20926","pmid":1,"OA_place":"repository","publication_identifier":{"eissn":["1549-9626"],"issn":["1549-9618"]},"year":"2025","publication":"Journal of Chemical Theory and Computation","page":"12709-12724","language":[{"iso":"eng"}],"issue":"24","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2025-12-10T00:00:00Z","external_id":{"pmid":["41368735 "],"arxiv":["2507.14302"]},"author":[{"last_name":"Kim","full_name":"Kim, Dongjin","first_name":"Dongjin"},{"first_name":"Xiaoyu","full_name":"Wang, Xiaoyu","last_name":"Wang","id":"8dff9c62-32b0-11ee-9fa8-fc73025e10f3"},{"last_name":"Vargas","full_name":"Vargas, Santiago","first_name":"Santiago"},{"last_name":"Zhong","full_name":"Zhong, Peichen","first_name":"Peichen"},{"first_name":"Daniel S.","last_name":"King","full_name":"King, Daniel S."},{"last_name":"Inizan","full_name":"Inizan, Theo Jaffrelot","first_name":"Theo Jaffrelot"},{"first_name":"Bingqing","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","last_name":"Cheng","orcid":"0000-0002-3584-9632","full_name":"Cheng, Bingqing"}],"volume":21,"status":"public","acknowledgement":"Research reported in this publication was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number R35GM159986. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. D.K. and B.C. acknowledge funding from Toyota Research Institute Synthesis Advanced Research Challenge. T.J.I., D.S.K. and P.Z. acknowledge funding from BIDMaP Postdoctoral Fellowship. T.J.I. used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy Office of Science User Facility using NERSC award DOEERCAP0031751 ′GenAI@NERSC’. The authors thank Bowen Deng for valuable discussions on MatGL implementation, and thank Gabor Csanyi for stimulating discussions.","article_processing_charge":"No","abstract":[{"lang":"eng","text":"Most current machine learning interatomic potentials (MLIPs) rely on short-range approximations, without explicit treatment of long-range electrostatics. To address this, we recently developed the Latent Ewald Summation (LES) method, which infers electrostatic interactions, polarization, and Born effective charges (BECs), just by learning from energy and force training data. Here, we present LES as a standalone library, compatible with any short-range MLIP, and demonstrate its integration with methods such as MACE, NequIP, Allegro, CACE, CHGNet, and UMA. We benchmark LES-enhanced models on distinct systems, including bulk water, polar dipeptides, and gold dimer adsorption on defective substrates, and show that LES not only captures correct electrostatics but also improves accuracy. Additionally, we scale LES to large and chemically diverse data by training MACELES-OFF on the SPICE set containing molecules and clusters, making a universal MLIP with electrostatics for organic systems, including biomolecules. MACELES-OFF is more accurate than its short-range counterpart (MACE-OFF) trained on the same data set, predicts dipoles and BECs reliably, and has better descriptions of bulk liquids. By enabling efficient long-range electrostatics without directly training on electrical properties, LES paves the way for electrostatic foundation MLIPs."}],"oa":1,"intvolume":"        21","doi":"10.1021/acs.jctc.5c01400","scopus_import":"1","date_created":"2026-01-04T23:01:33Z","quality_controlled":"1","citation":{"chicago":"Kim, Dongjin, Xiaoyu Wang, Santiago Vargas, Peichen Zhong, Daniel S. King, Theo Jaffrelot Inizan, and Bingqing Cheng. “A Universal Augmentation Framework for Long-Range Electrostatics in Machine Learning Interatomic Potentials.” <i>Journal of Chemical Theory and Computation</i>. American Chemical Society, 2025. <a href=\"https://doi.org/10.1021/acs.jctc.5c01400\">https://doi.org/10.1021/acs.jctc.5c01400</a>.","apa":"Kim, D., Wang, X., Vargas, S., Zhong, P., King, D. S., Inizan, T. J., &#38; Cheng, B. (2025). A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials. <i>Journal of Chemical Theory and Computation</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.jctc.5c01400\">https://doi.org/10.1021/acs.jctc.5c01400</a>","mla":"Kim, Dongjin, et al. “A Universal Augmentation Framework for Long-Range Electrostatics in Machine Learning Interatomic Potentials.” <i>Journal of Chemical Theory and Computation</i>, vol. 21, no. 24, American Chemical Society, 2025, pp. 12709–24, doi:<a href=\"https://doi.org/10.1021/acs.jctc.5c01400\">10.1021/acs.jctc.5c01400</a>.","ista":"Kim D, Wang X, Vargas S, Zhong P, King DS, Inizan TJ, Cheng B. 2025. A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials. Journal of Chemical Theory and Computation. 21(24), 12709–12724.","ama":"Kim D, Wang X, Vargas S, et al. A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials. <i>Journal of Chemical Theory and Computation</i>. 2025;21(24):12709-12724. doi:<a href=\"https://doi.org/10.1021/acs.jctc.5c01400\">10.1021/acs.jctc.5c01400</a>","short":"D. Kim, X. Wang, S. Vargas, P. Zhong, D.S. King, T.J. Inizan, B. Cheng, Journal of Chemical Theory and Computation 21 (2025) 12709–12724.","ieee":"D. Kim <i>et al.</i>, “A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials,” <i>Journal of Chemical Theory and Computation</i>, vol. 21, no. 24. American Chemical Society, pp. 12709–12724, 2025."},"corr_author":"1","day":"10"},{"volume":20,"author":[{"orcid":"0000-0002-3584-9632","full_name":"Cheng, Bingqing","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","last_name":"Cheng","first_name":"Bingqing"}],"external_id":{"arxiv":["2405.09057"],"isi":["001330001500001"],"pmid":["39365029"]},"file":[{"access_level":"open_access","content_type":"application/pdf","date_created":"2025-01-13T09:11:09Z","checksum":"aca0011bba4846140809b5af583daa9a","file_size":4758251,"success":1,"file_name":"2024_JCTC_Cheng.pdf","relation":"main_file","creator":"dernst","file_id":"18832","date_updated":"2025-01-13T09:11:09Z"}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","date_published":"2024-10-22T00:00:00Z","status":"public","acknowledgement":"B.C. thanks Chris Pickard for enlightening discussions.","year":"2024","issue":"20","publication":"Journal of Chemical Theory and Computation","page":"9259-9266","language":[{"iso":"eng"}],"doi":"10.1021/acs.jctc.4c00998","related_material":{"link":[{"relation":"software","url":"https://github.com/BingqingCheng/cace"}]},"intvolume":"        20","corr_author":"1","day":"22","quality_controlled":"1","citation":{"apa":"Cheng, B. (2024). Response matching for generating materials and molecules. <i>Journal of Chemical Theory and Computation</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.jctc.4c00998\">https://doi.org/10.1021/acs.jctc.4c00998</a>","mla":"Cheng, Bingqing. “Response Matching for Generating Materials and Molecules.” <i>Journal of Chemical Theory and Computation</i>, vol. 20, no. 20, American Chemical Society, 2024, pp. 9259–66, doi:<a href=\"https://doi.org/10.1021/acs.jctc.4c00998\">10.1021/acs.jctc.4c00998</a>.","chicago":"Cheng, Bingqing. “Response Matching for Generating Materials and Molecules.” <i>Journal of Chemical Theory and Computation</i>. American Chemical Society, 2024. <a href=\"https://doi.org/10.1021/acs.jctc.4c00998\">https://doi.org/10.1021/acs.jctc.4c00998</a>.","ista":"Cheng B. 2024. Response matching for generating materials and molecules. Journal of Chemical Theory and Computation. 20(20), 9259–9266.","short":"B. Cheng, Journal of Chemical Theory and Computation 20 (2024) 9259–9266.","ieee":"B. Cheng, “Response matching for generating materials and molecules,” <i>Journal of Chemical Theory and Computation</i>, vol. 20, no. 20. American Chemical Society, pp. 9259–9266, 2024.","ama":"Cheng B. Response matching for generating materials and molecules. <i>Journal of Chemical Theory and Computation</i>. 2024;20(20):9259-9266. doi:<a href=\"https://doi.org/10.1021/acs.jctc.4c00998\">10.1021/acs.jctc.4c00998</a>"},"date_created":"2024-10-20T22:02:07Z","scopus_import":"1","has_accepted_license":"1","article_processing_charge":"Yes (in subscription journal)","oa":1,"file_date_updated":"2025-01-13T09:11:09Z","ddc":["540"],"abstract":[{"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.","lang":"eng"}],"article_type":"original","month":"10","OA_type":"hybrid","oa_version":"Published Version","publication_status":"published","type":"journal_article","publisher":"American Chemical Society","arxiv":1,"pmid":1,"_id":"18452","publication_identifier":{"issn":["1549-9618"],"eissn":["1549-9626"]},"OA_place":"publisher","isi":1,"date_updated":"2025-09-08T14:21:30Z","tmp":{"image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","short":"CC BY-NC-ND (4.0)"},"department":[{"_id":"BiCh"}],"title":"Response matching for generating materials and molecules"},{"publication_identifier":{"issn":["1549-9618"],"eissn":["1549-9626"]},"_id":"9680","pmid":1,"title":"Iterative unbiasing of quasi-equilibrium sampling","date_updated":"2021-08-09T12:37:37Z","main_file_link":[{"url":"https://arxiv.org/abs/1911.01140","open_access":"1"}],"month":"01","article_type":"original","arxiv":1,"type":"journal_article","publisher":"American Chemical Society","publication_status":"published","oa_version":"Preprint","scopus_import":"1","citation":{"short":"F. Giberti, B. Cheng, G.A. Tribello, M. Ceriotti, Journal of Chemical Theory and Computation 16 (2019) 100–107.","ieee":"F. Giberti, B. Cheng, G. A. Tribello, and M. Ceriotti, “Iterative unbiasing of quasi-equilibrium sampling,” <i>Journal of Chemical Theory and Computation</i>, vol. 16, no. 1. American Chemical Society, pp. 100–107, 2019.","ama":"Giberti F, Cheng B, Tribello GA, Ceriotti M. Iterative unbiasing of quasi-equilibrium sampling. <i>Journal of Chemical Theory and Computation</i>. 2019;16(1):100-107. doi:<a href=\"https://doi.org/10.1021/acs.jctc.9b00907\">10.1021/acs.jctc.9b00907</a>","apa":"Giberti, F., Cheng, B., Tribello, G. A., &#38; Ceriotti, M. (2019). Iterative unbiasing of quasi-equilibrium sampling. <i>Journal of Chemical Theory and Computation</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.jctc.9b00907\">https://doi.org/10.1021/acs.jctc.9b00907</a>","chicago":"Giberti, F., Bingqing Cheng, G. A. Tribello, and M. Ceriotti. “Iterative Unbiasing of Quasi-Equilibrium Sampling.” <i>Journal of Chemical Theory and Computation</i>. American Chemical Society, 2019. <a href=\"https://doi.org/10.1021/acs.jctc.9b00907\">https://doi.org/10.1021/acs.jctc.9b00907</a>.","mla":"Giberti, F., et al. “Iterative Unbiasing of Quasi-Equilibrium Sampling.” <i>Journal of Chemical Theory and Computation</i>, vol. 16, no. 1, American Chemical Society, 2019, pp. 100–07, doi:<a href=\"https://doi.org/10.1021/acs.jctc.9b00907\">10.1021/acs.jctc.9b00907</a>.","ista":"Giberti F, Cheng B, Tribello GA, Ceriotti M. 2019. Iterative unbiasing of quasi-equilibrium sampling. Journal of Chemical Theory and Computation. 16(1), 100–107."},"quality_controlled":"1","date_created":"2021-07-19T06:56:45Z","day":"14","intvolume":"        16","doi":"10.1021/acs.jctc.9b00907","abstract":[{"text":"Atomistic modeling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an appropriately chosen set of collective variables can significantly accelerate the exploration of phase space, albeit at the price of distorting the distribution of microstates. Efficient reweighting to recover the unbiased distribution can be nontrivial when employing adaptive sampling techniques such as metadynamics, variationally enhanced sampling, or parallel bias metadynamics, in which the system evolves in a quasi-equilibrium manner under a time-dependent bias. We introduce an iterative unbiasing scheme that makes efficient use of all the trajectory data and that does not require the distribution to be evaluated on a grid. The method can thus be used even when the bias has a high dimensionality. We benchmark this approach against some of the existing schemes on model systems with different complexity and dimensionality.","lang":"eng"}],"oa":1,"article_processing_charge":"No","status":"public","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","date_published":"2019-01-14T00:00:00Z","external_id":{"pmid":["31743021"],"arxiv":["1911.01140"]},"author":[{"first_name":"F.","full_name":"Giberti, F.","last_name":"Giberti"},{"first_name":"Bingqing","last_name":"Cheng","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","orcid":"0000-0002-3584-9632","full_name":"Cheng, Bingqing"},{"last_name":"Tribello","full_name":"Tribello, G. A.","first_name":"G. A."},{"first_name":"M.","last_name":"Ceriotti","full_name":"Ceriotti, M."}],"extern":"1","volume":16,"page":"100-107","publication":"Journal of Chemical Theory and Computation","language":[{"iso":"eng"}],"issue":"1","year":"2019"},{"abstract":[{"text":"Polysaccharides (carbohydrates) are key regulators of a large number of cell biological processes. However, precise biochemical or genetic manipulation of these often complex structures is laborious and hampers experimental structure–function studies. Molecular Dynamics (MD) simulations provide a valuable alternative tool to generate and test hypotheses on saccharide function. Yet, currently used MD force fields often overestimate the aggregation propensity of polysaccharides, affecting the usability of those simulations. Here we tested MARTINI, a popular coarse-grained (CG) force field for biological macromolecules, for its ability to accurately represent molecular forces between saccharides. To this end, we calculated a thermodynamic solution property, the second virial coefficient of the osmotic pressure (B22). Comparison with light scattering experiments revealed a nonphysical aggregation of a prototypical polysaccharide in MARTINI, pointing at an imbalance of the nonbonded solute–solute, solute–water, and water–water interactions. This finding also applies to smaller oligosaccharides which were all found to aggregate in simulations even at moderate concentrations, well below their solubility limit. Finally, we explored the influence of the Lennard-Jones (LJ) interaction between saccharide molecules and propose a simple scaling of the LJ interaction strength that makes MARTINI more reliable for the simulation of saccharides.","lang":"eng"}],"oa":1,"article_processing_charge":"No","citation":{"ista":"Schmalhorst PS, Deluweit F, Scherrers R, Heisenberg C-PJ, Sikora MK. 2017. Overcoming the limitations of the MARTINI force field in simulations of polysaccharides. Journal of Chemical Theory and Computation. 13(10), 5039–5053.","apa":"Schmalhorst, P. S., Deluweit, F., Scherrers, R., Heisenberg, C.-P. J., &#38; Sikora, M. K. (2017). Overcoming the limitations of the MARTINI force field in simulations of polysaccharides. <i>Journal of Chemical Theory and Computation</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.jctc.7b00374\">https://doi.org/10.1021/acs.jctc.7b00374</a>","mla":"Schmalhorst, Philipp S., et al. “Overcoming the Limitations of the MARTINI Force Field in Simulations of Polysaccharides.” <i>Journal of Chemical Theory and Computation</i>, vol. 13, no. 10, American Chemical Society, 2017, pp. 5039–53, doi:<a href=\"https://doi.org/10.1021/acs.jctc.7b00374\">10.1021/acs.jctc.7b00374</a>.","chicago":"Schmalhorst, Philipp S, Felix Deluweit, Roger Scherrers, Carl-Philipp J Heisenberg, and Mateusz K Sikora. “Overcoming the Limitations of the MARTINI Force Field in Simulations of Polysaccharides.” <i>Journal of Chemical Theory and Computation</i>. American Chemical Society, 2017. <a href=\"https://doi.org/10.1021/acs.jctc.7b00374\">https://doi.org/10.1021/acs.jctc.7b00374</a>.","ieee":"P. S. Schmalhorst, F. Deluweit, R. Scherrers, C.-P. J. Heisenberg, and M. K. Sikora, “Overcoming the limitations of the MARTINI force field in simulations of polysaccharides,” <i>Journal of Chemical Theory and Computation</i>, vol. 13, no. 10. American Chemical Society, pp. 5039–5053, 2017.","short":"P.S. Schmalhorst, F. Deluweit, R. Scherrers, C.-P.J. Heisenberg, M.K. Sikora, Journal of Chemical Theory and Computation 13 (2017) 5039–5053.","ama":"Schmalhorst PS, Deluweit F, Scherrers R, Heisenberg C-PJ, Sikora MK. Overcoming the limitations of the MARTINI force field in simulations of polysaccharides. <i>Journal of Chemical Theory and Computation</i>. 2017;13(10):5039-5053. doi:<a href=\"https://doi.org/10.1021/acs.jctc.7b00374\">10.1021/acs.jctc.7b00374</a>"},"date_created":"2018-12-11T11:48:35Z","quality_controlled":"1","scopus_import":"1","day":"10","corr_author":"1","intvolume":"        13","doi":"10.1021/acs.jctc.7b00374","language":[{"iso":"eng"}],"page":"5039 - 5053","publication":"Journal of Chemical Theory and Computation","issue":"10","year":"2017","status":"public","acknowledgement":"P.S.S. was supported by research fellowship 2811/1-1 from the German Research Foundation (DFG), and M.S. was supported by EMBO Long Term Fellowship ALTF 187-2013 and Grant GC65-32 from the  Interdisciplinary Centre for Mathematical and Computational Modelling (ICM), University of Warsaw, Poland. The authors thank Antje Potthast, Marek Cieplak, Tomasz Włodarski, and Damien Thompson for fruitful discussions and the IST Austria Scientific Computing Facility for support.","date_published":"2017-10-10T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","volume":13,"publist_id":"6847","author":[{"orcid":"0000-0002-5795-0133","full_name":"Schmalhorst, Philipp S","last_name":"Schmalhorst","id":"309D50DA-F248-11E8-B48F-1D18A9856A87","first_name":"Philipp S"},{"first_name":"Felix","last_name":"Deluweit","full_name":"Deluweit, Felix"},{"last_name":"Scherrers","full_name":"Scherrers, Roger","first_name":"Roger"},{"last_name":"Heisenberg","id":"39427864-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-0912-4566","full_name":"Heisenberg, Carl-Philipp J","first_name":"Carl-Philipp J"},{"first_name":"Mateusz K","full_name":"Sikora, Mateusz K","id":"2F74BCDE-F248-11E8-B48F-1D18A9856A87","last_name":"Sikora"}],"external_id":{"isi":["000412965700036"],"arxiv":["1704.03773"]},"title":"Overcoming the limitations of the MARTINI force field in simulations of polysaccharides","department":[{"_id":"CaHe"}],"date_updated":"2025-06-04T09:49:02Z","isi":1,"acknowledged_ssus":[{"_id":"ScienComp"}],"publication_identifier":{"issn":["1549-9618"]},"_id":"804","arxiv":1,"publication_status":"published","publisher":"American Chemical Society","type":"journal_article","oa_version":"Submitted Version","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1704.03773"}],"month":"10"},{"title":"Computational design of intrinsic molecular rectifiers based on asymmetric functionalization of N-Phenylbenzamide","date_updated":"2024-12-18T10:33:40Z","publication_identifier":{"issn":["1549-9618"],"eissn":["1549-9626"]},"pmid":1,"_id":"17967","oa_version":"None","publication_status":"published","type":"journal_article","publisher":"American Chemical Society","OA_type":"closed access","article_type":"original","month":"11","abstract":[{"text":"We report a systematic computational search of molecular frameworks for intrinsic rectification of electron transport. The screening of molecular rectifiers includes 52 molecules and conformers spanning over 9 series of structural motifs. N-Phenylbenzamide is found to be a promising framework with both suitable conductance and rectification properties. A targeted screening performed on 30 additional derivatives and conformers of N-phenylbenzamide yielded enhanced rectification based on asymmetric functionalization. We demonstrate that electron-donating substituent groups that maintain an asymmetric distribution of charge in the dominant transport channel (e.g., HOMO) enhance rectification by raising the channel closer to the Fermi level. These findings are particularly valuable for the design of molecular assemblies that could ensure directionality of electron transport in a wide range of applications, from molecular electronics to catalytic reactions.","lang":"eng"}],"article_processing_charge":"No","day":"03","citation":{"apa":"Ding, W., Koepf, M., Koenigsmann, C., Batra, A., Venkataraman, L., Negre, C. F. A., … Batista, V. S. (2015). Computational design of intrinsic molecular rectifiers based on asymmetric functionalization of N-Phenylbenzamide. <i>Journal of Chemical Theory and Computation</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.jctc.5b00823\">https://doi.org/10.1021/acs.jctc.5b00823</a>","mla":"Ding, Wendu, et al. “Computational Design of Intrinsic Molecular Rectifiers Based on Asymmetric Functionalization of N-Phenylbenzamide.” <i>Journal of Chemical Theory and Computation</i>, vol. 11, no. 12, American Chemical Society, 2015, pp. 5888–96, doi:<a href=\"https://doi.org/10.1021/acs.jctc.5b00823\">10.1021/acs.jctc.5b00823</a>.","chicago":"Ding, Wendu, Matthieu Koepf, Christopher Koenigsmann, Arunabh Batra, Latha Venkataraman, Christian F. A. Negre, Gary W. Brudvig, Robert H. Crabtree, Charles A. Schmuttenmaer, and Victor S. Batista. “Computational Design of Intrinsic Molecular Rectifiers Based on Asymmetric Functionalization of N-Phenylbenzamide.” <i>Journal of Chemical Theory and Computation</i>. American Chemical Society, 2015. <a href=\"https://doi.org/10.1021/acs.jctc.5b00823\">https://doi.org/10.1021/acs.jctc.5b00823</a>.","ista":"Ding W, Koepf M, Koenigsmann C, Batra A, Venkataraman L, Negre CFA, Brudvig GW, Crabtree RH, Schmuttenmaer CA, Batista VS. 2015. Computational design of intrinsic molecular rectifiers based on asymmetric functionalization of N-Phenylbenzamide. Journal of Chemical Theory and Computation. 11(12), 5888–5896.","ama":"Ding W, Koepf M, Koenigsmann C, et al. Computational design of intrinsic molecular rectifiers based on asymmetric functionalization of N-Phenylbenzamide. <i>Journal of Chemical Theory and Computation</i>. 2015;11(12):5888-5896. doi:<a href=\"https://doi.org/10.1021/acs.jctc.5b00823\">10.1021/acs.jctc.5b00823</a>","ieee":"W. Ding <i>et al.</i>, “Computational design of intrinsic molecular rectifiers based on asymmetric functionalization of N-Phenylbenzamide,” <i>Journal of Chemical Theory and Computation</i>, vol. 11, no. 12. American Chemical Society, pp. 5888–5896, 2015.","short":"W. Ding, M. Koepf, C. Koenigsmann, A. Batra, L. Venkataraman, C.F.A. Negre, G.W. Brudvig, R.H. Crabtree, C.A. Schmuttenmaer, V.S. Batista, Journal of Chemical Theory and Computation 11 (2015) 5888–5896."},"date_created":"2024-09-09T09:42:20Z","quality_controlled":"1","scopus_import":"1","doi":"10.1021/acs.jctc.5b00823","intvolume":"        11","issue":"12","page":"5888-5896","publication":"Journal of Chemical Theory and Computation","language":[{"iso":"eng"}],"year":"2015","status":"public","extern":"1","volume":11,"external_id":{"pmid":["26642992"]},"author":[{"full_name":"Ding, Wendu","last_name":"Ding","first_name":"Wendu"},{"full_name":"Koepf, Matthieu","last_name":"Koepf","first_name":"Matthieu"},{"first_name":"Christopher","last_name":"Koenigsmann","full_name":"Koenigsmann, Christopher"},{"first_name":"Arunabh","last_name":"Batra","full_name":"Batra, Arunabh"},{"id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","last_name":"Venkataraman","full_name":"Venkataraman, Latha","orcid":"0000-0002-6957-6089","first_name":"Latha"},{"first_name":"Christian F. A.","last_name":"Negre","full_name":"Negre, Christian F. A."},{"first_name":"Gary W.","last_name":"Brudvig","full_name":"Brudvig, Gary W."},{"full_name":"Crabtree, Robert H.","last_name":"Crabtree","first_name":"Robert H."},{"first_name":"Charles A.","full_name":"Schmuttenmaer, Charles A.","last_name":"Schmuttenmaer"},{"last_name":"Batista","full_name":"Batista, Victor S.","first_name":"Victor S."}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2015-11-03T00:00:00Z"}]