[{"month":"12","status":"public","publication":"Nano Letters","issue":"1","intvolume":"        21","language":[{"iso":"eng"}],"OA_type":"closed access","publisher":"American Chemical Society","date_created":"2024-09-09T06:48:30Z","pmid":1,"abstract":[{"lang":"eng","text":"Probing structural changes of a molecule induced by charge transfer is important for understanding the physicochemical properties of molecules and developing new electronic devices. Here, we interrogate the structural changes of a single diketopyrrolopyrrole (DPP) molecule induced by charge transport at a high bias using scanning tunneling microscope break junction (STM-BJ) techniques. Specifically, we demonstrate that application of a high bias increases the average nonresonant conductance of single Au–DPP–Au junctions. We infer from the increased conductance that resonant charge transport induces planarization of the molecular backbone. We further show that this conformational planarization is assisted by thermally activated junction reorganization. The planarization only occurs under specific electronic conditions, which we rationalize by ab initio calculations. These results emphasize the need for a comprehensive view of single-molecule junctions which includes both the electronic properties and structure of the molecules and the electrodes when designing electrically driven single-molecule motors."}],"date_published":"2020-12-18T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"published","article_processing_charge":"No","year":"2020","type":"journal_article","page":"673-679","quality_controlled":"1","oa_version":"None","_id":"17902","extern":"1","doi":"10.1021/acs.nanolett.0c04260","citation":{"short":"Y. Zang, E.-D. Fung, T. Fu, S. Ray, M.H. Garner, A. Borges, M.L. Steigerwald, S. Patil, G. Solomon, L. Venkataraman, Nano Letters 21 (2020) 673–679.","chicago":"Zang, Yaping, E-Dean Fung, Tianren Fu, Suman Ray, Marc H. Garner, Anders Borges, Michael L. Steigerwald, Satish Patil, Gemma Solomon, and Latha Venkataraman. “Voltage-Induced Single-Molecule Junction Planarization.” <i>Nano Letters</i>. American Chemical Society, 2020. <a href=\"https://doi.org/10.1021/acs.nanolett.0c04260\">https://doi.org/10.1021/acs.nanolett.0c04260</a>.","apa":"Zang, Y., Fung, E.-D., Fu, T., Ray, S., Garner, M. H., Borges, A., … Venkataraman, L. (2020). Voltage-induced single-molecule junction planarization. <i>Nano Letters</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.nanolett.0c04260\">https://doi.org/10.1021/acs.nanolett.0c04260</a>","ama":"Zang Y, Fung E-D, Fu T, et al. Voltage-induced single-molecule junction planarization. <i>Nano Letters</i>. 2020;21(1):673-679. doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c04260\">10.1021/acs.nanolett.0c04260</a>","ista":"Zang Y, Fung E-D, Fu T, Ray S, Garner MH, Borges A, Steigerwald ML, Patil S, Solomon G, Venkataraman L. 2020. Voltage-induced single-molecule junction planarization. Nano Letters. 21(1), 673–679.","mla":"Zang, Yaping, et al. “Voltage-Induced Single-Molecule Junction Planarization.” <i>Nano Letters</i>, vol. 21, no. 1, American Chemical Society, 2020, pp. 673–79, doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c04260\">10.1021/acs.nanolett.0c04260</a>.","ieee":"Y. Zang <i>et al.</i>, “Voltage-induced single-molecule junction planarization,” <i>Nano Letters</i>, vol. 21, no. 1. American Chemical Society, pp. 673–679, 2020."},"volume":21,"scopus_import":"1","title":"Voltage-induced single-molecule junction planarization","date_updated":"2024-12-10T10:26:22Z","author":[{"full_name":"Zang, Yaping","first_name":"Yaping","last_name":"Zang"},{"first_name":"E-Dean","last_name":"Fung","full_name":"Fung, E-Dean"},{"full_name":"Fu, Tianren","first_name":"Tianren","last_name":"Fu"},{"full_name":"Ray, Suman","last_name":"Ray","first_name":"Suman"},{"full_name":"Garner, Marc H.","first_name":"Marc H.","last_name":"Garner"},{"first_name":"Anders","last_name":"Borges","full_name":"Borges, Anders"},{"full_name":"Steigerwald, Michael L.","first_name":"Michael L.","last_name":"Steigerwald"},{"first_name":"Satish","last_name":"Patil","full_name":"Patil, Satish"},{"last_name":"Solomon","first_name":"Gemma","full_name":"Solomon, Gemma"},{"first_name":"Latha","orcid":"0000-0002-6957-6089","last_name":"Venkataraman","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","full_name":"Venkataraman, Latha"}],"external_id":{"pmid":["33337876"]},"day":"18","article_type":"letter_note","publication_identifier":{"eissn":["1530-6992"],"issn":["1530-6984"]}},{"extern":"1","_id":"17903","quality_controlled":"1","oa_version":"None","scopus_import":"1","volume":20,"doi":"10.1021/acs.nanolett.0c03994","citation":{"ieee":"E.-D. Fung and L. Venkataraman, “Too cool for blackbody radiation: Overbias photon emission in ambient STM due to multielectron processes,” <i>Nano Letters</i>, vol. 20, no. 12. American Chemical Society, pp. 8912–8918, 2020.","mla":"Fung, E. Dean, and Latha Venkataraman. “Too Cool for Blackbody Radiation: Overbias Photon Emission in Ambient STM Due to Multielectron Processes.” <i>Nano Letters</i>, vol. 20, no. 12, American Chemical Society, 2020, pp. 8912–18, doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c03994\">10.1021/acs.nanolett.0c03994</a>.","ista":"Fung E-D, Venkataraman L. 2020. Too cool for blackbody radiation: Overbias photon emission in ambient STM due to multielectron processes. Nano Letters. 20(12), 8912–8918.","ama":"Fung E-D, Venkataraman L. Too cool for blackbody radiation: Overbias photon emission in ambient STM due to multielectron processes. <i>Nano Letters</i>. 2020;20(12):8912-8918. doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c03994\">10.1021/acs.nanolett.0c03994</a>","apa":"Fung, E.-D., &#38; Venkataraman, L. (2020). Too cool for blackbody radiation: Overbias photon emission in ambient STM due to multielectron processes. <i>Nano Letters</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.nanolett.0c03994\">https://doi.org/10.1021/acs.nanolett.0c03994</a>","chicago":"Fung, E-Dean, and Latha Venkataraman. “Too Cool for Blackbody Radiation: Overbias Photon Emission in Ambient STM Due to Multielectron Processes.” <i>Nano Letters</i>. American Chemical Society, 2020. <a href=\"https://doi.org/10.1021/acs.nanolett.0c03994\">https://doi.org/10.1021/acs.nanolett.0c03994</a>.","short":"E.-D. Fung, L. Venkataraman, Nano Letters 20 (2020) 8912–8918."},"author":[{"full_name":"Fung, E-Dean","last_name":"Fung","first_name":"E-Dean"},{"last_name":"Venkataraman","orcid":"0000-0002-6957-6089","first_name":"Latha","full_name":"Venkataraman, Latha","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf"}],"title":"Too cool for blackbody radiation: Overbias photon emission in ambient STM due to multielectron processes","date_updated":"2024-12-10T10:28:52Z","day":"18","article_type":"letter_note","publication_identifier":{"eissn":["1530-6992"],"issn":["1530-6984"]},"external_id":{"pmid":["33206534"]},"issue":"12","month":"11","status":"public","publication":"Nano Letters","pmid":1,"date_created":"2024-09-09T07:12:19Z","abstract":[{"text":"Light emission from tunnel junctions are a potential photon source for nanophotonic applications. Surprisingly, the photons emitted can have energies exceeding the energy supplied to the electrons by the bias. Three mechanisms for generating these so-called overbias photons have been proposed, but the relationship between these mechanisms has not been clarified. In this work, we argue that multielectron processes provide the best framework for understanding overbias light emission in tunnel junctions. Experimentally, we demonstrate for the first time that the superlinear dependence of emission on conductance predicted by this theory is robust to the temperature of the tunnel junction, indicating that tunnel junctions are a promising candidate for electrically driven broadband photon sources.","lang":"eng"}],"publisher":"American Chemical Society","OA_type":"closed access","language":[{"iso":"eng"}],"intvolume":"        20","publication_status":"published","article_processing_charge":"No","year":"2020","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2020-11-18T00:00:00Z","page":"8912-8918","type":"journal_article"},{"issue":"47","publication":"Journal of the American Chemical Society","status":"public","month":"11","abstract":[{"text":"The creation of stable molecular monolayers on metallic surfaces is a fundamental challenge of surface chemistry. N-Heterocyclic carbenes (NHCs) were recently shown to form self-assembled monolayers that are significantly more stable than the traditional thiols on Au system. Here we theoretically and experimentally demonstrate that the smallest cyclic carbene, cyclopropenylidene, binds even more strongly than NHCs to Au surfaces without altering the surface structure. We deposit bis(diisopropylamino)cyclopropenylidene (BAC) on Au(111) using the molecular adduct BAC–CO2 as a precursor and determine the structure, geometry, and behavior of the surface-bound molecules through high-resolution X-ray photoelectron spectroscopy, atomic force microscopy, and scanning tunneling microscopy. Our experiments are supported by density functional theory calculations of the molecular binding energy of BAC on Au(111) and its electronic structure. Our work is the first demonstration of surface modification with a stable carbene other than NHC; more broadly, it drives further exploration of various carbenes on metal surfaces.","lang":"eng"}],"pmid":1,"date_created":"2024-09-09T07:13:45Z","publisher":"American Chemical Society","language":[{"iso":"eng"}],"OA_type":"closed access","intvolume":"       142","publication_status":"published","article_processing_charge":"No","year":"2020","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2020-11-11T00:00:00Z","page":"19902-19906","type":"journal_article","extern":"1","_id":"17904","quality_controlled":"1","oa_version":"None","scopus_import":"1","volume":142,"doi":"10.1021/jacs.0c10743","citation":{"ista":"Doud EA, Starr RL, Kladnik G, Voevodin A, Montes E, Arasu NP, Zang Y, Zahl P, Morgante A, Venkataraman L, Vázquez H, Cvetko D, Roy X. 2020. Cyclopropenylidenes as strong carbene anchoring groups on Au surfaces. Journal of the American Chemical Society. 142(47), 19902–19906.","ama":"Doud EA, Starr RL, Kladnik G, et al. Cyclopropenylidenes as strong carbene anchoring groups on Au surfaces. <i>Journal of the American Chemical Society</i>. 2020;142(47):19902-19906. doi:<a href=\"https://doi.org/10.1021/jacs.0c10743\">10.1021/jacs.0c10743</a>","apa":"Doud, E. A., Starr, R. L., Kladnik, G., Voevodin, A., Montes, E., Arasu, N. P., … Roy, X. (2020). Cyclopropenylidenes as strong carbene anchoring groups on Au surfaces. <i>Journal of the American Chemical Society</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/jacs.0c10743\">https://doi.org/10.1021/jacs.0c10743</a>","ieee":"E. A. Doud <i>et al.</i>, “Cyclopropenylidenes as strong carbene anchoring groups on Au surfaces,” <i>Journal of the American Chemical Society</i>, vol. 142, no. 47. American Chemical Society, pp. 19902–19906, 2020.","mla":"Doud, Evan A., et al. “Cyclopropenylidenes as Strong Carbene Anchoring Groups on Au Surfaces.” <i>Journal of the American Chemical Society</i>, vol. 142, no. 47, American Chemical Society, 2020, pp. 19902–06, doi:<a href=\"https://doi.org/10.1021/jacs.0c10743\">10.1021/jacs.0c10743</a>.","short":"E.A. Doud, R.L. Starr, G. Kladnik, A. Voevodin, E. Montes, N.P. Arasu, Y. Zang, P. Zahl, A. Morgante, L. Venkataraman, H. Vázquez, D. Cvetko, X. Roy, Journal of the American Chemical Society 142 (2020) 19902–19906.","chicago":"Doud, Evan A., Rachel L. Starr, Gregor Kladnik, Anastasia Voevodin, Enrique Montes, Narendra P. Arasu, Yaping Zang, et al. “Cyclopropenylidenes as Strong Carbene Anchoring Groups on Au Surfaces.” <i>Journal of the American Chemical Society</i>. American Chemical Society, 2020. <a href=\"https://doi.org/10.1021/jacs.0c10743\">https://doi.org/10.1021/jacs.0c10743</a>."},"author":[{"full_name":"Doud, Evan A.","last_name":"Doud","first_name":"Evan A."},{"first_name":"Rachel L.","last_name":"Starr","full_name":"Starr, Rachel L."},{"last_name":"Kladnik","first_name":"Gregor","full_name":"Kladnik, Gregor"},{"full_name":"Voevodin, Anastasia","last_name":"Voevodin","first_name":"Anastasia"},{"full_name":"Montes, Enrique","first_name":"Enrique","last_name":"Montes"},{"full_name":"Arasu, Narendra P.","first_name":"Narendra P.","last_name":"Arasu"},{"first_name":"Yaping","last_name":"Zang","full_name":"Zang, Yaping"},{"full_name":"Zahl, Percy","first_name":"Percy","last_name":"Zahl"},{"last_name":"Morgante","first_name":"Alberto","full_name":"Morgante, Alberto"},{"id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","full_name":"Venkataraman, Latha","first_name":"Latha","orcid":"0000-0002-6957-6089","last_name":"Venkataraman"},{"last_name":"Vázquez","first_name":"Héctor","full_name":"Vázquez, Héctor"},{"full_name":"Cvetko, Dean","last_name":"Cvetko","first_name":"Dean"},{"full_name":"Roy, Xavier","first_name":"Xavier","last_name":"Roy"}],"title":"Cyclopropenylidenes as strong carbene anchoring groups on Au surfaces","date_updated":"2024-12-10T10:34:58Z","day":"11","publication_identifier":{"issn":["0002-7863"],"eissn":["1520-5126"]},"article_type":"letter_note","external_id":{"pmid":["33175526"]}},{"doi":"10.1039/d0ra08220a","tmp":{"name":"Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc/3.0/legalcode","short":"CC BY-NC (3.0)","image":"/images/cc_by_nc.png"},"citation":{"mla":"Guijarro, Fernando G., et al. “Synthesis and Electronic Properties of Pyridine End-Capped Cyclopentadithiophene-Vinylene Oligomers.” <i>RSC Advances</i>, vol. 10, no. 68, Royal Society of Chemistry, 2020, pp. 41264–71, doi:<a href=\"https://doi.org/10.1039/d0ra08220a\">10.1039/d0ra08220a</a>.","ieee":"F. G. Guijarro <i>et al.</i>, “Synthesis and electronic properties of pyridine end-capped cyclopentadithiophene-vinylene oligomers,” <i>RSC Advances</i>, vol. 10, no. 68. Royal Society of Chemistry, pp. 41264–41271, 2020.","apa":"Guijarro, F. G., Medina Rivero, S., Gunasekaran, S., Arretxea, I., Ponce Ortiz, R., Caballero, R., … Casado, J. (2020). Synthesis and electronic properties of pyridine end-capped cyclopentadithiophene-vinylene oligomers. <i>RSC Advances</i>. Royal Society of Chemistry. <a href=\"https://doi.org/10.1039/d0ra08220a\">https://doi.org/10.1039/d0ra08220a</a>","ista":"Guijarro FG, Medina Rivero S, Gunasekaran S, Arretxea I, Ponce Ortiz R, Caballero R, Cruz P de la, Langa F, Venkataraman L, Casado J. 2020. Synthesis and electronic properties of pyridine end-capped cyclopentadithiophene-vinylene oligomers. RSC Advances. 10(68), 41264–41271.","ama":"Guijarro FG, Medina Rivero S, Gunasekaran S, et al. Synthesis and electronic properties of pyridine end-capped cyclopentadithiophene-vinylene oligomers. <i>RSC Advances</i>. 2020;10(68):41264-41271. doi:<a href=\"https://doi.org/10.1039/d0ra08220a\">10.1039/d0ra08220a</a>","chicago":"Guijarro, Fernando G., Samara Medina Rivero, Suman Gunasekaran, Iratxe Arretxea, Rocío Ponce Ortiz, Rubén Caballero, Pilar de la Cruz, Fernando Langa, Latha Venkataraman, and Juan Casado. “Synthesis and Electronic Properties of Pyridine End-Capped Cyclopentadithiophene-Vinylene Oligomers.” <i>RSC Advances</i>. Royal Society of Chemistry, 2020. <a href=\"https://doi.org/10.1039/d0ra08220a\">https://doi.org/10.1039/d0ra08220a</a>.","short":"F.G. Guijarro, S. Medina Rivero, S. Gunasekaran, I. Arretxea, R. Ponce Ortiz, R. Caballero, P. de la Cruz, F. Langa, L. Venkataraman, J. Casado, RSC Advances 10 (2020) 41264–41271."},"scopus_import":"1","volume":10,"extern":"1","_id":"17905","oa_version":"Published Version","quality_controlled":"1","OA_place":"publisher","license":"https://creativecommons.org/licenses/by-nc/3.0/","external_id":{"pmid":["35516533"]},"day":"11","article_type":"original","publication_identifier":{"issn":["2046-2069"]},"DOAJ_listed":"1","title":"Synthesis and electronic properties of pyridine end-capped cyclopentadithiophene-vinylene oligomers","date_updated":"2024-12-10T10:38:07Z","author":[{"full_name":"Guijarro, Fernando G.","last_name":"Guijarro","first_name":"Fernando G."},{"last_name":"Medina Rivero","first_name":"Samara","full_name":"Medina Rivero, Samara"},{"last_name":"Gunasekaran","first_name":"Suman","full_name":"Gunasekaran, Suman"},{"full_name":"Arretxea, Iratxe","first_name":"Iratxe","last_name":"Arretxea"},{"first_name":"Rocío","last_name":"Ponce Ortiz","full_name":"Ponce Ortiz, Rocío"},{"last_name":"Caballero","first_name":"Rubén","full_name":"Caballero, Rubén"},{"full_name":"Cruz, Pilar de la","last_name":"Cruz","first_name":"Pilar de la"},{"last_name":"Langa","first_name":"Fernando","full_name":"Langa, Fernando"},{"last_name":"Venkataraman","orcid":"0000-0002-6957-6089","first_name":"Latha","full_name":"Venkataraman, Latha","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf"},{"first_name":"Juan","last_name":"Casado","full_name":"Casado, Juan"}],"language":[{"iso":"eng"}],"OA_type":"gold","intvolume":"        10","pmid":1,"date_created":"2024-09-09T07:14:34Z","abstract":[{"text":"A series of four oligomers of cyclopentadithiophene-vinylenes end capped with pyridine groups was prepared and their optical and electronic properties studied. Treatment with trifluoroacetic acid (TFA) leads to the bisprotonation of the nitrogens of the pyridine, which has an important impact on the optical properties. Excess treatment with TFA provokes the oxidation of the conjugated core, generating radical cations and dications. The ease of the TFA treatment in solution was extended to protonation in the solid-state where further characterization of the neutral and TFA-treated samples was carried out in electrically active substrates in organic field-effect transistors. Finally, the new molecules were found to be excellent conductors in single-molecule junctions thanks to strong electron delocalization and resonance orbital mediated transport. These studies show the opening of a spectrum of possibilities by suitable terminal substitution of π-cores.","lang":"eng"}],"publisher":"Royal Society of Chemistry","status":"public","month":"11","publication":"RSC Advances","issue":"68","type":"journal_article","page":"41264-41271","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2020-11-11T00:00:00Z","publication_status":"published","year":"2020","article_processing_charge":"Yes"},{"abstract":[{"lang":"eng","text":"One-dimensional sp-hybridized carbon wires, including cumulenes and polyynes, can be regarded as finite versions of carbynes. They are likely to be good candidates for molecular-scale conducting wires as they are predicted to have a high-conductance. In this study, we first characterize the single-molecule conductance of a series of cumulenes and polyynes with a backbone ranging in length from 4 to 8 carbon atoms, including [7]cumulene, the longest cumulenic carbon wire studied to date for molecular electronics. We observe different length dependence of conductance when comparing these two forms of carbon wires. Polyynes exhibit conductance decays with increasing molecular length, while cumulenes show a conductance increase with increasing molecular length. Their distinct conducting behaviors are attributed to their different bond length alternation, which is supported by theoretical calculations. This study confirms the long-standing theoretical predictions on sp-hybridized carbon wires and demonstrates that cumulenes can form highly conducting molecular wires."}],"date_created":"2024-09-09T07:16:20Z","pmid":1,"publisher":"American Chemical Society","language":[{"iso":"eng"}],"OA_type":"closed access","intvolume":"        20","issue":"11","publication":"Nano Letters","status":"public","month":"10","page":"8415-8419","type":"journal_article","year":"2020","article_processing_charge":"No","publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2020-10-23T00:00:00Z","scopus_import":"1","volume":20,"doi":"10.1021/acs.nanolett.0c03794","citation":{"ieee":"Y. Zang <i>et al.</i>, “Cumulene wires display increasing conductance with increasing length,” <i>Nano Letters</i>, vol. 20, no. 11. American Chemical Society, pp. 8415–8419, 2020.","mla":"Zang, Yaping, et al. “Cumulene Wires Display Increasing Conductance with Increasing Length.” <i>Nano Letters</i>, vol. 20, no. 11, American Chemical Society, 2020, pp. 8415–19, doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c03794\">10.1021/acs.nanolett.0c03794</a>.","apa":"Zang, Y., Fu, T., Zou, Q., Ng, F., Li, H., Steigerwald, M. L., … Venkataraman, L. (2020). Cumulene wires display increasing conductance with increasing length. <i>Nano Letters</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.nanolett.0c03794\">https://doi.org/10.1021/acs.nanolett.0c03794</a>","ama":"Zang Y, Fu T, Zou Q, et al. Cumulene wires display increasing conductance with increasing length. <i>Nano Letters</i>. 2020;20(11):8415-8419. doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c03794\">10.1021/acs.nanolett.0c03794</a>","ista":"Zang Y, Fu T, Zou Q, Ng F, Li H, Steigerwald ML, Nuckolls C, Venkataraman L. 2020. Cumulene wires display increasing conductance with increasing length. Nano Letters. 20(11), 8415–8419.","chicago":"Zang, Yaping, Tianren Fu, Qi Zou, Fay Ng, Hexing Li, Michael L. Steigerwald, Colin Nuckolls, and Latha Venkataraman. “Cumulene Wires Display Increasing Conductance with Increasing Length.” <i>Nano Letters</i>. American Chemical Society, 2020. <a href=\"https://doi.org/10.1021/acs.nanolett.0c03794\">https://doi.org/10.1021/acs.nanolett.0c03794</a>.","short":"Y. Zang, T. Fu, Q. Zou, F. Ng, H. Li, M.L. Steigerwald, C. Nuckolls, L. Venkataraman, Nano Letters 20 (2020) 8415–8419."},"extern":"1","_id":"17906","quality_controlled":"1","oa_version":"None","publication_identifier":{"issn":["1530-6984"],"eissn":["1530-6992"]},"article_type":"letter_note","day":"23","external_id":{"pmid":["33095021"]},"author":[{"first_name":"Yaping","last_name":"Zang","full_name":"Zang, Yaping"},{"last_name":"Fu","first_name":"Tianren","full_name":"Fu, Tianren"},{"last_name":"Zou","first_name":"Qi","full_name":"Zou, Qi"},{"full_name":"Ng, Fay","first_name":"Fay","last_name":"Ng"},{"first_name":"Hexing","last_name":"Li","full_name":"Li, Hexing"},{"first_name":"Michael L.","last_name":"Steigerwald","full_name":"Steigerwald, Michael L."},{"full_name":"Nuckolls, Colin","first_name":"Colin","last_name":"Nuckolls"},{"id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","full_name":"Venkataraman, Latha","first_name":"Latha","orcid":"0000-0002-6957-6089","last_name":"Venkataraman"}],"date_updated":"2024-12-10T10:41:40Z","title":"Cumulene wires display increasing conductance with increasing length"},{"type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_number":"124304 ","date_published":"2020-09-28T00:00:00Z","year":"2020","article_processing_charge":"No","publication_status":"published","language":[{"iso":"eng"}],"OA_type":"closed access","intvolume":"       153","abstract":[{"text":"Carbyne is a linear allotrope of carbon that is composed of a chain of sp-hybridized carbon atoms. Through appropriate engineering of the chain termination, carbyne can harbor helical states where the π-electron delocalization twists along the axis of the chain. Herein, we present a comprehensive analysis of these helical states at the tight-binding level. We demonstrate that, in general, the molecular orbital coefficients of the helical states trace out an ellipse, in analogy to elliptically polarized light. Helical states can be realized in a model, inspired by the structure of cumulene, which considers a chain terminated by sp2-hybridized atoms oriented at a nontrivial dihedral angle. We provide a complete analytic solution for this model. Additionally, we present a variation of the model that yields perfect helical states that trace out a circle as opposed to an ellipse. Our results provide a deeper understanding of helical states and lay a foundation for more advanced levels of theory.","lang":"eng"}],"pmid":1,"date_created":"2024-09-09T07:17:20Z","publisher":"AIP Publishing","month":"09","publication":"The Journal of Chemical Physics","status":"public","issue":"12","external_id":{"pmid":["33003709"]},"publication_identifier":{"eissn":["1089-7690"],"issn":["0021-9606"]},"article_type":"original","day":"28","date_updated":"2024-12-10T10:46:25Z","title":"Tight-binding analysis of helical states in carbyne","author":[{"full_name":"Gunasekaran, Suman","last_name":"Gunasekaran","first_name":"Suman"},{"id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","full_name":"Venkataraman, Latha","first_name":"Latha","orcid":"0000-0002-6957-6089","last_name":"Venkataraman"}],"citation":{"chicago":"Gunasekaran, Suman, and Latha Venkataraman. “Tight-Binding Analysis of Helical States in Carbyne.” <i>The Journal of Chemical Physics</i>. AIP Publishing, 2020. <a href=\"https://doi.org/10.1063/5.0021146\">https://doi.org/10.1063/5.0021146</a>.","short":"S. Gunasekaran, L. Venkataraman, The Journal of Chemical Physics 153 (2020).","ieee":"S. Gunasekaran and L. Venkataraman, “Tight-binding analysis of helical states in carbyne,” <i>The Journal of Chemical Physics</i>, vol. 153, no. 12. AIP Publishing, 2020.","mla":"Gunasekaran, Suman, and Latha Venkataraman. “Tight-Binding Analysis of Helical States in Carbyne.” <i>The Journal of Chemical Physics</i>, vol. 153, no. 12, 124304, AIP Publishing, 2020, doi:<a href=\"https://doi.org/10.1063/5.0021146\">10.1063/5.0021146</a>.","ama":"Gunasekaran S, Venkataraman L. Tight-binding analysis of helical states in carbyne. <i>The Journal of Chemical Physics</i>. 2020;153(12). doi:<a href=\"https://doi.org/10.1063/5.0021146\">10.1063/5.0021146</a>","ista":"Gunasekaran S, Venkataraman L. 2020. Tight-binding analysis of helical states in carbyne. The Journal of Chemical Physics. 153(12), 124304.","apa":"Gunasekaran, S., &#38; Venkataraman, L. (2020). Tight-binding analysis of helical states in carbyne. <i>The Journal of Chemical Physics</i>. AIP Publishing. <a href=\"https://doi.org/10.1063/5.0021146\">https://doi.org/10.1063/5.0021146</a>"},"doi":"10.1063/5.0021146","scopus_import":"1","volume":153,"extern":"1","_id":"17907","quality_controlled":"1","oa_version":"None"},{"citation":{"apa":"Camarasa-Gómez, M., Hernangómez-Pérez, D., Inkpen, M. S., Lovat, G., Fung, E.-D., Roy, X., … Evers, F. (2020). Mechanically tunable quantum interference in ferrocene-based single-molecule junctions. <i>Nano Letters</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.nanolett.0c01956\">https://doi.org/10.1021/acs.nanolett.0c01956</a>","ista":"Camarasa-Gómez M, Hernangómez-Pérez D, Inkpen MS, Lovat G, Fung E-D, Roy X, Venkataraman L, Evers F. 2020. Mechanically tunable quantum interference in ferrocene-based single-molecule junctions. Nano Letters. 20(9), 6381–6386.","ama":"Camarasa-Gómez M, Hernangómez-Pérez D, Inkpen MS, et al. Mechanically tunable quantum interference in ferrocene-based single-molecule junctions. <i>Nano Letters</i>. 2020;20(9):6381-6386. doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c01956\">10.1021/acs.nanolett.0c01956</a>","mla":"Camarasa-Gómez, María, et al. “Mechanically Tunable Quantum Interference in Ferrocene-Based Single-Molecule Junctions.” <i>Nano Letters</i>, vol. 20, no. 9, American Chemical Society, 2020, pp. 6381–86, doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c01956\">10.1021/acs.nanolett.0c01956</a>.","ieee":"M. Camarasa-Gómez <i>et al.</i>, “Mechanically tunable quantum interference in ferrocene-based single-molecule junctions,” <i>Nano Letters</i>, vol. 20, no. 9. American Chemical Society, pp. 6381–6386, 2020.","short":"M. Camarasa-Gómez, D. Hernangómez-Pérez, M.S. Inkpen, G. Lovat, E.-D. Fung, X. Roy, L. Venkataraman, F. Evers, Nano Letters 20 (2020) 6381–6386.","chicago":"Camarasa-Gómez, María, Daniel Hernangómez-Pérez, Michael S. Inkpen, Giacomo Lovat, E-Dean Fung, Xavier Roy, Latha Venkataraman, and Ferdinand Evers. “Mechanically Tunable Quantum Interference in Ferrocene-Based Single-Molecule Junctions.” <i>Nano Letters</i>. American Chemical Society, 2020. <a href=\"https://doi.org/10.1021/acs.nanolett.0c01956\">https://doi.org/10.1021/acs.nanolett.0c01956</a>."},"doi":"10.1021/acs.nanolett.0c01956","volume":20,"scopus_import":"1","quality_controlled":"1","oa_version":"Preprint","main_file_link":[{"open_access":"1","url":"https://doi.org/10.26434/chemrxiv.12252059.v1"}],"_id":"17908","extern":"1","external_id":{"pmid":["32787164"]},"OA_place":"repository","day":"03","publication_identifier":{"eissn":["1530-6992"],"issn":["1530-6984"]},"article_type":"letter_note","title":"Mechanically tunable quantum interference in ferrocene-based single-molecule junctions","date_updated":"2024-12-10T10:49:18Z","author":[{"first_name":"María","last_name":"Camarasa-Gómez","full_name":"Camarasa-Gómez, María"},{"full_name":"Hernangómez-Pérez, Daniel","last_name":"Hernangómez-Pérez","first_name":"Daniel"},{"full_name":"Inkpen, Michael S.","last_name":"Inkpen","first_name":"Michael S."},{"full_name":"Lovat, Giacomo","first_name":"Giacomo","last_name":"Lovat"},{"full_name":"Fung, E-Dean","last_name":"Fung","first_name":"E-Dean"},{"full_name":"Roy, Xavier","first_name":"Xavier","last_name":"Roy"},{"orcid":"0000-0002-6957-6089","last_name":"Venkataraman","first_name":"Latha","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","full_name":"Venkataraman, Latha"},{"full_name":"Evers, Ferdinand","first_name":"Ferdinand","last_name":"Evers"}],"intvolume":"        20","OA_type":"green","language":[{"iso":"eng"}],"publisher":"American Chemical Society","date_created":"2024-09-09T07:18:19Z","abstract":[{"lang":"eng","text":"Ferrocenes are ubiquitous organometallic building blocks that comprise a Fe atom sandwiched between two cyclopentadienyl (Cp) rings that rotate freely at room temperature. Of widespread interest in fundamental studies and real-world applications, they have also attracted some interest as functional elements of molecular-scale devices. Here we investigate the impact of the configurational degrees of freedom of a ferrocene derivative on its single-molecule junction conductance. Measurements indicate that the conductance of the ferrocene derivative, which is suppressed by 2 orders of magnitude as compared to a fully conjugated analogue, can be modulated by altering the junction configuration. Ab initio transport calculations show that the low conductance is a consequence of destructive quantum interference effects of the Fano type that arise from the hybridization of localized metal-based d-orbitals and the delocalized ligand-based π-system. By rotation of the Cp rings, the hybridization, and thus the quantum interference, can be mechanically controlled, resulting in a conductance modulation that is seen experimentally."}],"pmid":1,"status":"public","publication":"Nano Letters","month":"08","issue":"9","oa":1,"type":"journal_article","page":"6381-6386","date_published":"2020-08-03T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"published","article_processing_charge":"No","year":"2020"},{"title":"Single-electron currents in designer single-cluster devices","date_updated":"2024-12-10T12:04:31Z","author":[{"last_name":"Gunasekaran","first_name":"Suman","full_name":"Gunasekaran, Suman"},{"full_name":"Reed, Douglas A.","first_name":"Douglas A.","last_name":"Reed"},{"first_name":"Daniel W.","last_name":"Paley","full_name":"Paley, Daniel W."},{"full_name":"Bartholomew, Amymarie K.","last_name":"Bartholomew","first_name":"Amymarie K."},{"id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","full_name":"Venkataraman, Latha","first_name":"Latha","orcid":"0000-0002-6957-6089","last_name":"Venkataraman"},{"full_name":"Steigerwald, Michael L.","last_name":"Steigerwald","first_name":"Michael L."},{"first_name":"Xavier","last_name":"Roy","full_name":"Roy, Xavier"},{"last_name":"Nuckolls","first_name":"Colin","full_name":"Nuckolls, Colin"}],"external_id":{"pmid":["32809814"]},"day":"18","article_type":"original","publication_identifier":{"issn":["0002-7863"],"eissn":["1520-5126"]},"oa_version":"None","quality_controlled":"1","_id":"17909","extern":"1","citation":{"short":"S. Gunasekaran, D.A. Reed, D.W. Paley, A.K. Bartholomew, L. Venkataraman, M.L. Steigerwald, X. Roy, C. Nuckolls, Journal of the American Chemical Society 142 (2020) 14924–14932.","chicago":"Gunasekaran, Suman, Douglas A. Reed, Daniel W. Paley, Amymarie K. Bartholomew, Latha Venkataraman, Michael L. Steigerwald, Xavier Roy, and Colin Nuckolls. “Single-Electron Currents in Designer Single-Cluster Devices.” <i>Journal of the American Chemical Society</i>. American Chemical Society, 2020. <a href=\"https://doi.org/10.1021/jacs.0c04970\">https://doi.org/10.1021/jacs.0c04970</a>.","ama":"Gunasekaran S, Reed DA, Paley DW, et al. Single-electron currents in designer single-cluster devices. <i>Journal of the American Chemical Society</i>. 2020;142(35):14924-14932. doi:<a href=\"https://doi.org/10.1021/jacs.0c04970\">10.1021/jacs.0c04970</a>","ista":"Gunasekaran S, Reed DA, Paley DW, Bartholomew AK, Venkataraman L, Steigerwald ML, Roy X, Nuckolls C. 2020. Single-electron currents in designer single-cluster devices. Journal of the American Chemical Society. 142(35), 14924–14932.","apa":"Gunasekaran, S., Reed, D. A., Paley, D. W., Bartholomew, A. K., Venkataraman, L., Steigerwald, M. L., … Nuckolls, C. (2020). Single-electron currents in designer single-cluster devices. <i>Journal of the American Chemical Society</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/jacs.0c04970\">https://doi.org/10.1021/jacs.0c04970</a>","mla":"Gunasekaran, Suman, et al. “Single-Electron Currents in Designer Single-Cluster Devices.” <i>Journal of the American Chemical Society</i>, vol. 142, no. 35, American Chemical Society, 2020, pp. 14924–32, doi:<a href=\"https://doi.org/10.1021/jacs.0c04970\">10.1021/jacs.0c04970</a>.","ieee":"S. Gunasekaran <i>et al.</i>, “Single-electron currents in designer single-cluster devices,” <i>Journal of the American Chemical Society</i>, vol. 142, no. 35. American Chemical Society, pp. 14924–14932, 2020."},"doi":"10.1021/jacs.0c04970","volume":142,"scopus_import":"1","date_published":"2020-08-18T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"published","year":"2020","article_processing_charge":"No","type":"journal_article","page":"14924-14932","month":"08","publication":"Journal of the American Chemical Society","status":"public","issue":"35","intvolume":"       142","language":[{"iso":"eng"}],"OA_type":"closed access","publisher":"American Chemical Society","date_created":"2024-09-09T07:19:56Z","pmid":1,"abstract":[{"lang":"eng","text":"Atomically precise clusters can be used to create single-electron devices wherein a single redox-active cluster is connected to two macroscopic electrodes via anchoring ligands. Unlike single-electron devices comprising nanocrystals, these cluster-based devices can be fabricated with atomic precision. This affords an unprecedented level of control over the device properties. Herein, we design a series of cobalt chalcogenide clusters with varying ligand geometries and core nuclearities to control their current–voltage (I–V) characteristics in a scanning tunneling microscope-based break junction (STM-BJ) device. First, the device geometry is modified by precisely positioning junction-anchoring ligands on the surface of the cluster. We show that the I–V characteristics are independent of ligand placement, confirming a sequential, single-electron tunneling mechanism. Next, we chemically fuse two clusters to realize a larger cluster dimer that behaves as a single electronic unit, possessing a smaller reorganization energy and more accessible redox states than the monomeric analogues. As a result, dimer-based devices exhibit significantly higher currents and can even be pushed to current saturation at high bias. Owing to these controllable properties, single-cluster junctions serve as an excellent platform for exploring incoherent charge transport processes at the nanoscale. With this understanding, as well as properties such as nonlinear I–V characteristics and rectification, these molecular clusters may function as conductive inorganic nodes in new devices and materials."}]},{"type":"journal_article","page":"3320-3325","date_published":"2020-04-03T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"published","article_processing_charge":"No","year":"2020","intvolume":"        20","language":[{"iso":"eng"}],"publisher":"American Chemical Society","pmid":1,"date_created":"2024-09-09T07:20:52Z","abstract":[{"text":"The scanning tunneling microscope-based break junction (STM-BJ) is used widely to create and characterize single metal-molecule-metal junctions. In this technique, conductance is continuously recorded as a metal point contact is broken in a solution of molecules. Conductance plateaus are seen when stable molecular junctions are formed. Typically, thousands of junctions are created and measured, yielding thousands of distinct conductance versus extension traces. However, such traces are rarely analyzed individually to recognize the types of junctions formed. Here, we present a deep learning-based method to identify molecular junctions and show that it performs better than several commonly used and recently reported techniques. We demonstrate molecular junction identification from mixed solution measurements with accuracies as high as 97%. We also apply this model to an in situ electric field-driven isomerization reaction of a [3]cumulene to follow the reaction over time. Furthermore, we demonstrate that our model can remain accurate even when a key parameter, the average junction conductance, is eliminated from the analysis, showing that our model goes beyond conventional analysis in existing methods.","lang":"eng"}],"publication":"Nano Letters","month":"04","status":"public","issue":"5","external_id":{"pmid":["32242671"]},"day":"03","article_type":"letter_note","publication_identifier":{"eissn":["1530-6992"],"issn":["1530-6984"]},"title":"Using deep learning to identify molecular junction characteristics","date_updated":"2024-12-10T12:08:53Z","author":[{"last_name":"Fu","first_name":"Tianren","full_name":"Fu, Tianren"},{"first_name":"Yaping","last_name":"Zang","full_name":"Zang, Yaping"},{"full_name":"Zou, Qi","first_name":"Qi","last_name":"Zou"},{"first_name":"Colin","last_name":"Nuckolls","full_name":"Nuckolls, Colin"},{"full_name":"Venkataraman, Latha","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","last_name":"Venkataraman","orcid":"0000-0002-6957-6089","first_name":"Latha"}],"citation":{"apa":"Fu, T., Zang, Y., Zou, Q., Nuckolls, C., &#38; Venkataraman, L. (2020). Using deep learning to identify molecular junction characteristics. <i>Nano Letters</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.nanolett.0c00198\">https://doi.org/10.1021/acs.nanolett.0c00198</a>","ista":"Fu T, Zang Y, Zou Q, Nuckolls C, Venkataraman L. 2020. Using deep learning to identify molecular junction characteristics. Nano Letters. 20(5), 3320–3325.","ama":"Fu T, Zang Y, Zou Q, Nuckolls C, Venkataraman L. Using deep learning to identify molecular junction characteristics. <i>Nano Letters</i>. 2020;20(5):3320-3325. doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c00198\">10.1021/acs.nanolett.0c00198</a>","ieee":"T. Fu, Y. Zang, Q. Zou, C. Nuckolls, and L. Venkataraman, “Using deep learning to identify molecular junction characteristics,” <i>Nano Letters</i>, vol. 20, no. 5. American Chemical Society, pp. 3320–3325, 2020.","mla":"Fu, Tianren, et al. “Using Deep Learning to Identify Molecular Junction Characteristics.” <i>Nano Letters</i>, vol. 20, no. 5, American Chemical Society, 2020, pp. 3320–25, doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c00198\">10.1021/acs.nanolett.0c00198</a>.","short":"T. Fu, Y. Zang, Q. Zou, C. Nuckolls, L. Venkataraman, Nano Letters 20 (2020) 3320–3325.","chicago":"Fu, Tianren, Yaping Zang, Qi Zou, Colin Nuckolls, and Latha Venkataraman. “Using Deep Learning to Identify Molecular Junction Characteristics.” <i>Nano Letters</i>. American Chemical Society, 2020. <a href=\"https://doi.org/10.1021/acs.nanolett.0c00198\">https://doi.org/10.1021/acs.nanolett.0c00198</a>."},"doi":"10.1021/acs.nanolett.0c00198","volume":20,"scopus_import":"1","oa_version":"None","quality_controlled":"1","_id":"17910","extern":"1"},{"volume":12,"scopus_import":"1","tmp":{"name":"Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc/3.0/legalcode","short":"CC BY-NC (3.0)","image":"/images/cc_by_nc.png"},"doi":"10.1039/d0nr00467g","citation":{"chicago":"Magyarkuti, András, Nóra Balogh, Zoltán Balogh, Latha Venkataraman, and András Halbritter. “Unsupervised Feature Recognition in Single-Molecule Break Junction Data.” <i>Nanoscale</i>. Royal Society of Chemistry, 2020. <a href=\"https://doi.org/10.1039/d0nr00467g\">https://doi.org/10.1039/d0nr00467g</a>.","short":"A. Magyarkuti, N. Balogh, Z. Balogh, L. Venkataraman, A. Halbritter, Nanoscale 12 (2020) 8355–8363.","mla":"Magyarkuti, András, et al. “Unsupervised Feature Recognition in Single-Molecule Break Junction Data.” <i>Nanoscale</i>, vol. 12, no. 15, Royal Society of Chemistry, 2020, pp. 8355–63, doi:<a href=\"https://doi.org/10.1039/d0nr00467g\">10.1039/d0nr00467g</a>.","ieee":"A. Magyarkuti, N. Balogh, Z. Balogh, L. Venkataraman, and A. Halbritter, “Unsupervised feature recognition in single-molecule break junction data,” <i>Nanoscale</i>, vol. 12, no. 15. Royal Society of Chemistry, pp. 8355–8363, 2020.","apa":"Magyarkuti, A., Balogh, N., Balogh, Z., Venkataraman, L., &#38; Halbritter, A. (2020). Unsupervised feature recognition in single-molecule break junction data. <i>Nanoscale</i>. Royal Society of Chemistry. <a href=\"https://doi.org/10.1039/d0nr00467g\">https://doi.org/10.1039/d0nr00467g</a>","ama":"Magyarkuti A, Balogh N, Balogh Z, Venkataraman L, Halbritter A. Unsupervised feature recognition in single-molecule break junction data. <i>Nanoscale</i>. 2020;12(15):8355-8363. doi:<a href=\"https://doi.org/10.1039/d0nr00467g\">10.1039/d0nr00467g</a>","ista":"Magyarkuti A, Balogh N, Balogh Z, Venkataraman L, Halbritter A. 2020. Unsupervised feature recognition in single-molecule break junction data. Nanoscale. 12(15), 8355–8363."},"quality_controlled":"1","oa_version":"Published Version","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1039/D0NR00467G"}],"extern":"1","_id":"17911","arxiv":1,"day":"25","article_type":"original","publication_identifier":{"eissn":["2040-3372"],"issn":["2040-3364"]},"external_id":{"arxiv":["2001.03006"]},"OA_place":"publisher","author":[{"last_name":"Magyarkuti","first_name":"András","full_name":"Magyarkuti, András"},{"last_name":"Balogh","first_name":"Nóra","full_name":"Balogh, Nóra"},{"full_name":"Balogh, Zoltán","last_name":"Balogh","first_name":"Zoltán"},{"first_name":"Latha","orcid":"0000-0002-6957-6089","last_name":"Venkataraman","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","full_name":"Venkataraman, Latha"},{"full_name":"Halbritter, András","first_name":"András","last_name":"Halbritter"}],"title":"Unsupervised feature recognition in single-molecule break junction data","date_updated":"2024-12-10T12:13:16Z","publisher":"Royal Society of Chemistry","abstract":[{"text":"Single-molecule break junction measurements deliver a huge number of conductance vs. electrode separation traces. During such measurements, the target molecules may bind to the electrodes in different geometries, and the evolution and rupture of the single-molecule junction may also follow distinct trajectories. The unraveling of the various typical trace classes is a prerequisite to the proper physical interpretation of the data. Here we exploit the efficient feature recognition properties of neural networks to automatically find the relevant trace classes. To eliminate the need for manually labeled training data we apply a combined method, which automatically selects training traces according to the extreme values of principal component projections or some auxiliary measured quantities. Then the network captures the features of these characteristic traces and generalizes its inference to the entire dataset. The use of a simple neural network structure also enables a direct insight into the decision-making mechanism. We demonstrate that this combined machine learning method is efficient in the unsupervised recognition of unobvious, but highly relevant trace classes within low and room temperature gold–4,4′ bipyridine–gold single-molecule break junction data.","lang":"eng"}],"date_created":"2024-09-09T07:21:34Z","intvolume":"        12","OA_type":"hybrid","language":[{"iso":"eng"}],"issue":"15","publication":"Nanoscale","month":"03","status":"public","page":"8355-8363","oa":1,"type":"journal_article","publication_status":"published","article_processing_charge":"Yes","year":"2020","date_published":"2020-03-25T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87"},{"publication_status":"published","article_processing_charge":"No","year":"2020","date_published":"2020-03-26T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"7128-7133","type":"journal_article","issue":"15","status":"public","month":"03","publication":"Journal of the American Chemical Society","publisher":"American Chemical Society","abstract":[{"text":"Aryl halides are ubiquitous functional groups in organic chemistry, yet despite their obvious appeal as surface-binding linkers and as precursors for controlled graphene nanoribbon synthesis, they have seldom been used as such in molecular electronics. The confusion regarding the bonding of aryl iodides to Au electrodes is a case in point, with ambiguous reports of both dative Au–I and covalent Au–C contacts. Here we form single-molecule junctions with a series of oligophenylene molecular wires terminated asymmetrically with iodine and thiomethyl to show that the dative Au–I contact has a lower conductance than the covalent Au–C interaction, which we propose occurs via an in situ oxidative addition reaction at the Au surface. Furthermore, we confirm the formation of the Au–C bond by measuring an analogous series of molecules prepared ex situ with the complex AuI(PPh3) in place of the iodide. Density functional theory-based transport calculations support our experimental observations that Au–C linkages have higher conductance than Au–I linkages. Finally, we demonstrate selective promotion of the Au–C bond formation by controlling the bias applied across the junction. In addition to establishing the different binding modes of aryl iodides, our results chart a path to actively controlling oxidative addition on an Au surface using an applied bias.","lang":"eng"}],"date_created":"2024-09-09T07:22:26Z","pmid":1,"intvolume":"       142","language":[{"iso":"eng"}],"OA_type":"closed access","author":[{"full_name":"Starr, Rachel L.","last_name":"Starr","first_name":"Rachel L."},{"full_name":"Fu, Tianren","first_name":"Tianren","last_name":"Fu"},{"full_name":"Doud, Evan A.","last_name":"Doud","first_name":"Evan A."},{"full_name":"Stone, Ilana","first_name":"Ilana","last_name":"Stone"},{"last_name":"Roy","first_name":"Xavier","full_name":"Roy, Xavier"},{"full_name":"Venkataraman, Latha","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","last_name":"Venkataraman","orcid":"0000-0002-6957-6089","first_name":"Latha"}],"title":"Gold–carbon contacts from oxidative addition of aryl iodides","date_updated":"2024-12-10T12:20:47Z","day":"26","article_type":"original","publication_identifier":{"issn":["0002-7863"],"eissn":["1520-5126"]},"external_id":{"pmid":["32212683"]},"quality_controlled":"1","oa_version":"None","extern":"1","_id":"17912","volume":142,"scopus_import":"1","citation":{"chicago":"Starr, Rachel L., Tianren Fu, Evan A. Doud, Ilana Stone, Xavier Roy, and Latha Venkataraman. “Gold–Carbon Contacts from Oxidative Addition of Aryl Iodides.” <i>Journal of the American Chemical Society</i>. American Chemical Society, 2020. <a href=\"https://doi.org/10.1021/jacs.0c01466\">https://doi.org/10.1021/jacs.0c01466</a>.","short":"R.L. Starr, T. Fu, E.A. Doud, I. Stone, X. Roy, L. Venkataraman, Journal of the American Chemical Society 142 (2020) 7128–7133.","ieee":"R. L. Starr, T. Fu, E. A. Doud, I. Stone, X. Roy, and L. Venkataraman, “Gold–carbon contacts from oxidative addition of aryl iodides,” <i>Journal of the American Chemical Society</i>, vol. 142, no. 15. American Chemical Society, pp. 7128–7133, 2020.","mla":"Starr, Rachel L., et al. “Gold–Carbon Contacts from Oxidative Addition of Aryl Iodides.” <i>Journal of the American Chemical Society</i>, vol. 142, no. 15, American Chemical Society, 2020, pp. 7128–33, doi:<a href=\"https://doi.org/10.1021/jacs.0c01466\">10.1021/jacs.0c01466</a>.","apa":"Starr, R. L., Fu, T., Doud, E. A., Stone, I., Roy, X., &#38; Venkataraman, L. (2020). Gold–carbon contacts from oxidative addition of aryl iodides. <i>Journal of the American Chemical Society</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/jacs.0c01466\">https://doi.org/10.1021/jacs.0c01466</a>","ista":"Starr RL, Fu T, Doud EA, Stone I, Roy X, Venkataraman L. 2020. Gold–carbon contacts from oxidative addition of aryl iodides. Journal of the American Chemical Society. 142(15), 7128–7133.","ama":"Starr RL, Fu T, Doud EA, Stone I, Roy X, Venkataraman L. Gold–carbon contacts from oxidative addition of aryl iodides. <i>Journal of the American Chemical Society</i>. 2020;142(15):7128-7133. doi:<a href=\"https://doi.org/10.1021/jacs.0c01466\">10.1021/jacs.0c01466</a>"},"doi":"10.1021/jacs.0c01466"},{"type":"journal_article","page":"2843-2848","date_published":"2020-03-06T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","year":"2020","publication_status":"published","intvolume":"        20","language":[{"iso":"eng"}],"OA_type":"closed access","publisher":"American Chemical Society","date_created":"2024-09-09T07:36:41Z","abstract":[{"text":"Electron transport across a molecular junction is characterized by an energy-dependent transmission function. The transmission function accounts for electrons tunneling through multiple molecular orbitals (MOs) with different phases, which gives rise to quantum interference (QI) effects. Because the transmission function comprises both interfering and noninterfering effects, individual interferences between MOs cannot be deduced from the transmission function directly. Herein, we demonstrate how the transmission function can be deconstructed into its constituent interfering and noninterfering contributions for any model molecular junction. These contributions are arranged in a matrix and displayed pictorially as a QI map, which allows one to easily identify individual QI effects. Importantly, we show that exponential conductance decay with increasing oligomer length is primarily due to an increase in destructive QI. With an ability to “see” QI effects using the QI map, we find that QI is vital to all molecular-scale electron transport.","lang":"eng"}],"pmid":1,"month":"03","status":"public","publication":"Nano Letters","issue":"4","external_id":{"pmid":["32142291"]},"publication_identifier":{"eissn":["1530-6992"],"issn":["1530-6984"]},"article_type":"letter_note","day":"06","date_updated":"2024-12-10T12:24:13Z","title":"Visualizing quantum interference in molecular junctions","author":[{"first_name":"Suman","last_name":"Gunasekaran","full_name":"Gunasekaran, Suman"},{"full_name":"Greenwald, Julia E.","first_name":"Julia E.","last_name":"Greenwald"},{"id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","full_name":"Venkataraman, Latha","first_name":"Latha","orcid":"0000-0002-6957-6089","last_name":"Venkataraman"}],"citation":{"short":"S. Gunasekaran, J.E. Greenwald, L. Venkataraman, Nano Letters 20 (2020) 2843–2848.","chicago":"Gunasekaran, Suman, Julia E. Greenwald, and Latha Venkataraman. “Visualizing Quantum Interference in Molecular Junctions.” <i>Nano Letters</i>. American Chemical Society, 2020. <a href=\"https://doi.org/10.1021/acs.nanolett.0c00605\">https://doi.org/10.1021/acs.nanolett.0c00605</a>.","apa":"Gunasekaran, S., Greenwald, J. E., &#38; Venkataraman, L. (2020). Visualizing quantum interference in molecular junctions. <i>Nano Letters</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.nanolett.0c00605\">https://doi.org/10.1021/acs.nanolett.0c00605</a>","ista":"Gunasekaran S, Greenwald JE, Venkataraman L. 2020. Visualizing quantum interference in molecular junctions. Nano Letters. 20(4), 2843–2848.","ama":"Gunasekaran S, Greenwald JE, Venkataraman L. Visualizing quantum interference in molecular junctions. <i>Nano Letters</i>. 2020;20(4):2843-2848. doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c00605\">10.1021/acs.nanolett.0c00605</a>","mla":"Gunasekaran, Suman, et al. “Visualizing Quantum Interference in Molecular Junctions.” <i>Nano Letters</i>, vol. 20, no. 4, American Chemical Society, 2020, pp. 2843–48, doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c00605\">10.1021/acs.nanolett.0c00605</a>.","ieee":"S. Gunasekaran, J. E. Greenwald, and L. Venkataraman, “Visualizing quantum interference in molecular junctions,” <i>Nano Letters</i>, vol. 20, no. 4. American Chemical Society, pp. 2843–2848, 2020."},"doi":"10.1021/acs.nanolett.0c00605","volume":20,"scopus_import":"1","quality_controlled":"1","oa_version":"None","_id":"17913","extern":"1"},{"doi":"10.1021/acs.nanolett.0c00136","citation":{"short":"D. Hernangómez-Pérez, S. Gunasekaran, L. Venkataraman, F. Evers, Nano Letters 20 (2020) 2615–2619.","chicago":"Hernangómez-Pérez, Daniel, Suman Gunasekaran, Latha Venkataraman, and Ferdinand Evers. “Solitonics with Polyacetylenes.” <i>Nano Letters</i>. American Chemical Society, 2020. <a href=\"https://doi.org/10.1021/acs.nanolett.0c00136\">https://doi.org/10.1021/acs.nanolett.0c00136</a>.","ama":"Hernangómez-Pérez D, Gunasekaran S, Venkataraman L, Evers F. Solitonics with polyacetylenes. <i>Nano Letters</i>. 2020;20(4):2615-2619. doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c00136\">10.1021/acs.nanolett.0c00136</a>","ista":"Hernangómez-Pérez D, Gunasekaran S, Venkataraman L, Evers F. 2020. Solitonics with polyacetylenes. Nano Letters. 20(4), 2615–2619.","apa":"Hernangómez-Pérez, D., Gunasekaran, S., Venkataraman, L., &#38; Evers, F. (2020). Solitonics with polyacetylenes. <i>Nano Letters</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.nanolett.0c00136\">https://doi.org/10.1021/acs.nanolett.0c00136</a>","mla":"Hernangómez-Pérez, Daniel, et al. “Solitonics with Polyacetylenes.” <i>Nano Letters</i>, vol. 20, no. 4, American Chemical Society, 2020, pp. 2615–19, doi:<a href=\"https://doi.org/10.1021/acs.nanolett.0c00136\">10.1021/acs.nanolett.0c00136</a>.","ieee":"D. Hernangómez-Pérez, S. Gunasekaran, L. Venkataraman, and F. Evers, “Solitonics with polyacetylenes,” <i>Nano Letters</i>, vol. 20, no. 4. American Chemical Society, pp. 2615–2619, 2020."},"scopus_import":"1","volume":20,"extern":"1","_id":"17914","oa_version":"None","quality_controlled":"1","external_id":{"pmid":["32125870"]},"publication_identifier":{"issn":["1530-6984"],"eissn":["1530-6992"]},"article_type":"letter_note","day":"03","date_updated":"2024-12-10T12:26:43Z","title":"Solitonics with polyacetylenes","author":[{"full_name":"Hernangómez-Pérez, Daniel","last_name":"Hernangómez-Pérez","first_name":"Daniel"},{"first_name":"Suman","last_name":"Gunasekaran","full_name":"Gunasekaran, Suman"},{"first_name":"Latha","orcid":"0000-0002-6957-6089","last_name":"Venkataraman","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","full_name":"Venkataraman, Latha"},{"first_name":"Ferdinand","last_name":"Evers","full_name":"Evers, Ferdinand"}],"language":[{"iso":"eng"}],"OA_type":"closed access","intvolume":"        20","pmid":1,"date_created":"2024-09-09T07:38:36Z","abstract":[{"text":"Polyacetylene molecular wires have attracted a long-standing interest for the past 40 years. From a fundamental perspective, there are two main reasons for the interest. First, polyacetylenes are a prime realization of a one-dimensional topological insulator. Second, long molecules support freely propagating topological domain-wall states, so-called “solitons,” which provide an early paradigm for spin-charge separation. Because of recent experimental developments, individual polyacetylene chains can now be synthesized on substrates. Motivated by this breakthrough, we here propose a novel way for chemically supported soliton design in these systems. We demonstrate how to control the soliton position and how to read it out via external means. Also, we show how extra soliton–antisoliton pairs arise when applying a moderate static electric field. We thus make a step toward functionality of electronic devices based on soliton manipulation, that is, “solitonics”.","lang":"eng"}],"publisher":"American Chemical Society","month":"03","status":"public","publication":"Nano Letters","issue":"4","type":"journal_article","page":"2615-2619","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2020-03-03T00:00:00Z","article_processing_charge":"No","year":"2020","publication_status":"published"},{"external_id":{"arxiv":["2005.09689"]},"arxiv":1,"publication_identifier":{"eissn":["2469-9934"],"issn":["2469-9926"]},"article_type":"original","day":"14","date_updated":"2024-10-08T09:51:57Z","title":"Fractional Chern insulators of few bosons in a box: Hall plateaus from center-of-mass drifts and density profiles","author":[{"last_name":"Repellin","first_name":"C.","full_name":"Repellin, C."},{"first_name":"Julian","last_name":"Leonard","full_name":"Leonard, Julian","id":"b75b3f45-7995-11ef-9bfd-9a9cd02c3577"},{"full_name":"Goldman, N.","last_name":"Goldman","first_name":"N."}],"doi":"10.1103/physreva.102.063316","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"citation":{"chicago":"Repellin, C., Julian Leonard, and N. Goldman. “Fractional Chern Insulators of Few Bosons in a Box: Hall Plateaus from Center-of-Mass Drifts and Density Profiles.” <i>Physical Review A</i>. American Physical Society, 2020. <a href=\"https://doi.org/10.1103/physreva.102.063316\">https://doi.org/10.1103/physreva.102.063316</a>.","short":"C. Repellin, J. Leonard, N. Goldman, Physical Review A 102 (2020).","ieee":"C. Repellin, J. Leonard, and N. Goldman, “Fractional Chern insulators of few bosons in a box: Hall plateaus from center-of-mass drifts and density profiles,” <i>Physical Review A</i>, vol. 102, no. 6. American Physical Society, 2020.","mla":"Repellin, C., et al. “Fractional Chern Insulators of Few Bosons in a Box: Hall Plateaus from Center-of-Mass Drifts and Density Profiles.” <i>Physical Review A</i>, vol. 102, no. 6, 063316, American Physical Society, 2020, doi:<a href=\"https://doi.org/10.1103/physreva.102.063316\">10.1103/physreva.102.063316</a>.","ama":"Repellin C, Leonard J, Goldman N. Fractional Chern insulators of few bosons in a box: Hall plateaus from center-of-mass drifts and density profiles. <i>Physical Review A</i>. 2020;102(6). doi:<a href=\"https://doi.org/10.1103/physreva.102.063316\">10.1103/physreva.102.063316</a>","ista":"Repellin C, Leonard J, Goldman N. 2020. Fractional Chern insulators of few bosons in a box: Hall plateaus from center-of-mass drifts and density profiles. Physical Review A. 102(6), 063316.","apa":"Repellin, C., Leonard, J., &#38; Goldman, N. (2020). Fractional Chern insulators of few bosons in a box: Hall plateaus from center-of-mass drifts and density profiles. <i>Physical Review A</i>. American Physical Society. <a href=\"https://doi.org/10.1103/physreva.102.063316\">https://doi.org/10.1103/physreva.102.063316</a>"},"volume":102,"scopus_import":"1","main_file_link":[{"url":"https://doi.org/10.1103/PhysRevA.102.063316","open_access":"1"}],"oa_version":"Published Version","quality_controlled":"1","extern":"1","_id":"18194","oa":1,"type":"journal_article","article_number":"063316","date_published":"2020-12-14T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"Yes (in subscription journal)","year":"2020","publication_status":"published","intvolume":"       102","language":[{"iso":"eng"}],"publisher":"American Physical Society","abstract":[{"text":"Realizing strongly correlated topological phases of ultracold gases is a central goal for ongoing experiments. While fractional quantum Hall states could soon be implemented in small atomic ensembles, detecting their signatures in few-particle settings remains a fundamental challenge. In this work, we numerically analyze the center-of-mass Hall drift of a small ensemble of hardcore bosons, initially prepared in the ground state of the Harper-Hofstadter-Hubbard model in a box potential. By monitoring the Hall drift upon release, for a wide range of magnetic flux values, we identify an emergent Hall plateau compatible with a fractional Chern insulator state: The extracted Hall conductivity approaches a fractional value determined by the many-body Chern number, while the width of the plateau agrees with the spectral and topological properties of the prepared ground state. Besides, a direct application of Streda's formula indicates that such Hall plateaus can also be directly obtained from static density-profile measurements. Our calculations suggest that fractional Chern insulators can be detected in cold-atom experiments, using available detection methods.","lang":"eng"}],"date_created":"2024-10-07T11:48:07Z","has_accepted_license":"1","status":"public","publication":"Physical Review A","ddc":["530"],"month":"12","issue":"6"},{"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.1909.06397","open_access":"1"}],"oa_version":"Preprint","quality_controlled":"1","_id":"18228","extern":"1","doi":"10.1109/tpami.2020.2994507","citation":{"chicago":"Sommer, Stefan, and Alex M. Bronstein. “Horizontal Flows and Manifold Stochastics in Geometric Deep Learning.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. Institute of Electrical and Electronics Engineers, 2020. <a href=\"https://doi.org/10.1109/tpami.2020.2994507\">https://doi.org/10.1109/tpami.2020.2994507</a>.","short":"S. Sommer, A.M. Bronstein, IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (2020) 811–822.","mla":"Sommer, Stefan, and Alex M. Bronstein. “Horizontal Flows and Manifold Stochastics in Geometric Deep Learning.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 44, no. 2, Institute of Electrical and Electronics Engineers, 2020, pp. 811–22, doi:<a href=\"https://doi.org/10.1109/tpami.2020.2994507\">10.1109/tpami.2020.2994507</a>.","ieee":"S. Sommer and A. M. Bronstein, “Horizontal flows and manifold stochastics in geometric deep learning,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 44, no. 2. Institute of Electrical and Electronics Engineers, pp. 811–822, 2020.","ista":"Sommer S, Bronstein AM. 2020. Horizontal flows and manifold stochastics in geometric deep learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(2), 811–822.","ama":"Sommer S, Bronstein AM. Horizontal flows and manifold stochastics in geometric deep learning. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. 2020;44(2):811-822. doi:<a href=\"https://doi.org/10.1109/tpami.2020.2994507\">10.1109/tpami.2020.2994507</a>","apa":"Sommer, S., &#38; Bronstein, A. M. (2020). Horizontal flows and manifold stochastics in geometric deep learning. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. Institute of Electrical and Electronics Engineers. <a href=\"https://doi.org/10.1109/tpami.2020.2994507\">https://doi.org/10.1109/tpami.2020.2994507</a>"},"volume":44,"scopus_import":"1","date_updated":"2024-10-15T06:56:47Z","title":"Horizontal flows and manifold stochastics in geometric deep learning","author":[{"last_name":"Sommer","first_name":"Stefan","full_name":"Sommer, Stefan"},{"first_name":"Alexander","last_name":"Bronstein","orcid":"0000-0001-9699-8730","full_name":"Bronstein, Alexander","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6"}],"external_id":{"arxiv":["1909.06397"]},"OA_place":"repository","arxiv":1,"article_type":"original","publication_identifier":{"eissn":["1939-3539"],"issn":["0162-8828"]},"day":"01","publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","status":"public","month":"02","issue":"2","intvolume":"        44","OA_type":"green","language":[{"iso":"eng"}],"publisher":"Institute of Electrical and Electronics Engineers","date_created":"2024-10-08T12:55:23Z","abstract":[{"text":"We introduce two constructions in geometric deep learning for 1) transporting orientation-dependent convolutional filters over a manifold in a continuous way and thereby defining a convolution operator that naturally incorporates the rotational effect of holonomy; and 2) allowing efficient evaluation of manifold convolution layers by sampling manifold valued random variables that center around a weighted diffusion mean. Both methods are inspired by stochastics on manifolds and geometric statistics, and provide examples of how stochastic methods – here horizontal frame bundle flows and non-linear bridge sampling schemes, can be used in geometric deep learning. We outline the theoretical foundation of the two methods, discuss their relation to Euclidean deep networks and existing methodology in geometric deep learning, and establish important properties of the proposed constructions.","lang":"eng"}],"date_published":"2020-02-01T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2020","article_processing_charge":"No","publication_status":"published","oa":1,"type":"journal_article","page":"811-822"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2020-10-01T00:00:00Z","publication_status":"published","article_processing_charge":"No","year":"2020","type":"journal_article","page":"2333-2345","status":"public","publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","month":"10","issue":"10","language":[{"iso":"eng"}],"OA_type":"closed access","intvolume":"        42","date_created":"2024-10-08T13:04:18Z","abstract":[{"text":"Intel® RealSense™ SR300 is a depth camera capable of providing a VGA-size depth map at 60 fps and 0.125mm depth resolution. In addition, it outputs an infrared VGA-resolution image and a 1080p color texture image at 30 fps. SR300 form-factor enables it to be integrated into small consumer products and as a front facing camera in laptops and Ultrabooks™. The SR300 depth camera is based on a coded-light technology where triangulation between projected patterns and images captured by a dedicated sensor is used to produce the depth map. Each projected line is coded by a special temporal optical code, that enables a dense depth map reconstruction from its reflection. The solid mechanical assembly of the camera allows it to stay calibrated throughout temperature and pressure changes, drops, and hits. In addition, active dynamic control maintains a calibrated depth output. An extended API LibRS released with the camera allows developers to integrate the camera in various applications. Algorithms for 3D scanning, facial analysis, hand gesture recognition, and tracking are within reach for applications using the SR300. In this paper, we describe the underlying technology, hardware, and algorithms of the SR300, as well as its calibration procedure, and outline some use cases. We believe that this paper will provide a full case study of a mass-produced depth sensing product and technology.","lang":"eng"}],"pmid":1,"publisher":"Institute of Electrical and Electronics Engineers","title":"Intel® RealSense™ SR300 coded light depth camera","date_updated":"2024-10-15T09:40:01Z","author":[{"full_name":"Zabatani, Aviad","last_name":"Zabatani","first_name":"Aviad"},{"full_name":"Surazhsky, Vitaly","first_name":"Vitaly","last_name":"Surazhsky"},{"full_name":"Sperling, Erez","last_name":"Sperling","first_name":"Erez"},{"last_name":"Moshe","first_name":"Sagi Ben","full_name":"Moshe, Sagi Ben"},{"first_name":"Ohad","last_name":"Menashe","full_name":"Menashe, Ohad"},{"full_name":"Silver, David H.","first_name":"David H.","last_name":"Silver"},{"full_name":"Karni, Zachi","last_name":"Karni","first_name":"Zachi"},{"id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","first_name":"Alexander","orcid":"0000-0001-9699-8730","last_name":"Bronstein"},{"last_name":"Bronstein","first_name":"Michael K","full_name":"Bronstein, Michael K"},{"first_name":"Ron","last_name":"Kimmel","full_name":"Kimmel, Ron"}],"external_id":{"pmid":["31094683"]},"day":"01","publication_identifier":{"eissn":["1939-3539"],"issn":["0162-8828"]},"article_type":"original","_id":"18245","extern":"1","quality_controlled":"1","oa_version":"None","doi":"10.1109/tpami.2019.2915841","citation":{"chicago":"Zabatani, Aviad, Vitaly Surazhsky, Erez Sperling, Sagi Ben Moshe, Ohad Menashe, David H. Silver, Zachi Karni, Alex M. Bronstein, Michael K Bronstein, and Ron Kimmel. “Intel® RealSense<sup>TM</sup> SR300 Coded Light Depth Camera.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. Institute of Electrical and Electronics Engineers, 2020. <a href=\"https://doi.org/10.1109/tpami.2019.2915841\">https://doi.org/10.1109/tpami.2019.2915841</a>.","short":"A. Zabatani, V. Surazhsky, E. Sperling, S.B. Moshe, O. Menashe, D.H. Silver, Z. Karni, A.M. Bronstein, M.K. Bronstein, R. Kimmel, IEEE Transactions on Pattern Analysis and Machine Intelligence 42 (2020) 2333–2345.","ieee":"A. Zabatani <i>et al.</i>, “Intel® RealSense<sup>TM</sup> SR300 coded light depth camera,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 42, no. 10. Institute of Electrical and Electronics Engineers, pp. 2333–2345, 2020.","mla":"Zabatani, Aviad, et al. “Intel® RealSense<sup>TM</sup> SR300 Coded Light Depth Camera.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 42, no. 10, Institute of Electrical and Electronics Engineers, 2020, pp. 2333–45, doi:<a href=\"https://doi.org/10.1109/tpami.2019.2915841\">10.1109/tpami.2019.2915841</a>.","ama":"Zabatani A, Surazhsky V, Sperling E, et al. Intel® RealSense<sup>TM</sup> SR300 coded light depth camera. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. 2020;42(10):2333-2345. doi:<a href=\"https://doi.org/10.1109/tpami.2019.2915841\">10.1109/tpami.2019.2915841</a>","apa":"Zabatani, A., Surazhsky, V., Sperling, E., Moshe, S. B., Menashe, O., Silver, D. H., … Kimmel, R. (2020). Intel® RealSense<sup>TM</sup> SR300 coded light depth camera. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. Institute of Electrical and Electronics Engineers. <a href=\"https://doi.org/10.1109/tpami.2019.2915841\">https://doi.org/10.1109/tpami.2019.2915841</a>","ista":"Zabatani A, Surazhsky V, Sperling E, Moshe SB, Menashe O, Silver DH, Karni Z, Bronstein AM, Bronstein MK, Kimmel R. 2020. Intel® RealSense<sup>TM</sup> SR300 coded light depth camera. IEEE Transactions on Pattern Analysis and Machine Intelligence. 42(10), 2333–2345."},"scopus_import":"1","volume":42},{"_id":"18246","extern":"1","oa_version":"None","quality_controlled":"1","citation":{"short":"G. Mariani, L. Cosmo, A.M. Bronstein, E. Rodolà, Computer Graphics Forum 39 (2020) 253–264.","chicago":"Mariani, G., L. Cosmo, Alex M. Bronstein, and E. Rodolà. “Generating Adversarial Surfaces via Band‐limited Perturbations.” <i>Computer Graphics Forum</i>. Wiley, 2020. <a href=\"https://doi.org/10.1111/cgf.14083\">https://doi.org/10.1111/cgf.14083</a>.","ista":"Mariani G, Cosmo L, Bronstein AM, Rodolà E. 2020. Generating adversarial surfaces via band‐limited perturbations. Computer Graphics Forum. 39(5), 253–264.","ama":"Mariani G, Cosmo L, Bronstein AM, Rodolà E. Generating adversarial surfaces via band‐limited perturbations. <i>Computer Graphics Forum</i>. 2020;39(5):253-264. doi:<a href=\"https://doi.org/10.1111/cgf.14083\">10.1111/cgf.14083</a>","apa":"Mariani, G., Cosmo, L., Bronstein, A. M., &#38; Rodolà, E. (2020). Generating adversarial surfaces via band‐limited perturbations. <i>Computer Graphics Forum</i>. Wiley. <a href=\"https://doi.org/10.1111/cgf.14083\">https://doi.org/10.1111/cgf.14083</a>","mla":"Mariani, G., et al. “Generating Adversarial Surfaces via Band‐limited Perturbations.” <i>Computer Graphics Forum</i>, vol. 39, no. 5, Wiley, 2020, pp. 253–64, doi:<a href=\"https://doi.org/10.1111/cgf.14083\">10.1111/cgf.14083</a>.","ieee":"G. Mariani, L. Cosmo, A. M. Bronstein, and E. Rodolà, “Generating adversarial surfaces via band‐limited perturbations,” <i>Computer Graphics Forum</i>, vol. 39, no. 5. Wiley, pp. 253–264, 2020."},"doi":"10.1111/cgf.14083","scopus_import":"1","volume":39,"date_updated":"2024-10-15T09:36:46Z","title":"Generating adversarial surfaces via band‐limited perturbations","author":[{"last_name":"Mariani","first_name":"G.","full_name":"Mariani, G."},{"full_name":"Cosmo, L.","last_name":"Cosmo","first_name":"L."},{"first_name":"Alexander","last_name":"Bronstein","orcid":"0000-0001-9699-8730","full_name":"Bronstein, Alexander","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6"},{"first_name":"E.","last_name":"Rodolà","full_name":"Rodolà, E."}],"article_type":"original","publication_identifier":{"eissn":["1467-8659"],"issn":["0167-7055"]},"day":"01","month":"08","publication":"Computer Graphics Forum","status":"public","issue":"5","OA_type":"closed access","language":[{"iso":"eng"}],"intvolume":"        39","date_created":"2024-10-08T13:04:35Z","abstract":[{"lang":"eng","text":"Adversarial attacks have demonstrated remarkable efficacy in altering the output of a learning model by applying a minimal perturbation to the input data. While increasing attention has been placed on the image domain, however, the study of adversarial perturbations for geometric data has been notably lagging behind. In this paper, we show that effective adversarial attacks can be concocted for surfaces embedded in 3D, under weak smoothness assumptions on the perceptibility of the attack. We address the case of deformable 3D shapes in particular, and introduce a general model that is not tailored to any specific surface representation, nor does it assume access to a parametric description of the 3D object. In this context, we consider targeted and untargeted variants of the attack, demonstrating compelling results in either case. We further show how discovering adversarial examples, and then using them for adversarial training, leads to an increase in both robustness and accuracy. Our findings are confirmed empirically over multiple datasets spanning different semantic classes and deformations."}],"publisher":"Wiley","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2020-08-01T00:00:00Z","article_processing_charge":"No","year":"2020","publication_status":"published","type":"journal_article","page":"253-264"},{"month":"09","status":"public","publication":"2020 International Joint Conference on Neural Networks (IJCNN)","abstract":[{"lang":"eng","text":"Convolutional neural networks (CNNs) achieve state-of-the-art accuracy in a variety of tasks in computer vision and beyond. One of the major obstacles hindering the ubiquitous use of CNNs for inference on low-power edge devices is their high computational complexity and memory bandwidth requirements. The latter often dominates the energy footprint on modern hardware. In this paper, we introduce a lossy transform coding approach, inspired by image and video compression, designed to reduce the memory bandwidth due to the storage of intermediate activation calculation results. Our method does not require fine-tuning the network weights and halves the data transfer volumes to the main memory by compressing feature maps, which are highly correlated, with variable length coding. Our method outperform previous approach in term of the number of bits per value with minor accuracy degradation on ResNet-34 and MobileNetV2. We analyze the performance of our approach on a variety of CNN architectures and demonstrate that FPGA implementation of ResNet-18 with our approach results in a reduction of around 40% in the memory energy footprint, compared to quantized network, with negligible impact on accuracy. When allowing accuracy degradation of up to 2%, the reduction of 60% is achieved. A reference implementation accompanies the paper."}],"date_created":"2024-10-08T13:04:52Z","publisher":"IEEE","language":[{"iso":"eng"}],"publication_status":"published","year":"2020","article_processing_charge":"No","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","date_published":"2020-09-28T00:00:00Z","article_number":"9206968","type":"conference","oa":1,"_id":"18247","extern":"1","quality_controlled":"1","oa_version":"Preprint","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.1905.10830"}],"scopus_import":"1","doi":"10.1109/ijcnn48605.2020.9206968","citation":{"chicago":"Chmiel, Brian, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Yevgeny Yermolin, Alex Karbachevsky, Alex M. Bronstein, and Avi Mendelson. “Feature Map Transform Coding for Energy-Efficient CNN Inference.” In <i>2020 International Joint Conference on Neural Networks (IJCNN)</i>. IEEE, 2020. <a href=\"https://doi.org/10.1109/ijcnn48605.2020.9206968\">https://doi.org/10.1109/ijcnn48605.2020.9206968</a>.","short":"B. Chmiel, C. Baskin, E. Zheltonozhskii, R. Banner, Y. Yermolin, A. Karbachevsky, A.M. Bronstein, A. Mendelson, in:, 2020 International Joint Conference on Neural Networks (IJCNN), IEEE, 2020.","ieee":"B. Chmiel <i>et al.</i>, “Feature map transform coding for energy-efficient CNN inference,” in <i>2020 International Joint Conference on Neural Networks (IJCNN)</i>, Glasgow, United Kingdom, 2020.","mla":"Chmiel, Brian, et al. “Feature Map Transform Coding for Energy-Efficient CNN Inference.” <i>2020 International Joint Conference on Neural Networks (IJCNN)</i>, 9206968, IEEE, 2020, doi:<a href=\"https://doi.org/10.1109/ijcnn48605.2020.9206968\">10.1109/ijcnn48605.2020.9206968</a>.","apa":"Chmiel, B., Baskin, C., Zheltonozhskii, E., Banner, R., Yermolin, Y., Karbachevsky, A., … Mendelson, A. (2020). Feature map transform coding for energy-efficient CNN inference. In <i>2020 International Joint Conference on Neural Networks (IJCNN)</i>. Glasgow, United Kingdom: IEEE. <a href=\"https://doi.org/10.1109/ijcnn48605.2020.9206968\">https://doi.org/10.1109/ijcnn48605.2020.9206968</a>","ista":"Chmiel B, Baskin C, Zheltonozhskii E, Banner R, Yermolin Y, Karbachevsky A, Bronstein AM, Mendelson A. 2020. Feature map transform coding for energy-efficient CNN inference. 2020 International Joint Conference on Neural Networks (IJCNN). International Joint Conference on Neural Networks, 9206968.","ama":"Chmiel B, Baskin C, Zheltonozhskii E, et al. Feature map transform coding for energy-efficient CNN inference. In: <i>2020 International Joint Conference on Neural Networks (IJCNN)</i>. IEEE; 2020. doi:<a href=\"https://doi.org/10.1109/ijcnn48605.2020.9206968\">10.1109/ijcnn48605.2020.9206968</a>"},"author":[{"first_name":"Brian","last_name":"Chmiel","full_name":"Chmiel, Brian"},{"full_name":"Baskin, Chaim","first_name":"Chaim","last_name":"Baskin"},{"first_name":"Evgenii","last_name":"Zheltonozhskii","full_name":"Zheltonozhskii, Evgenii"},{"full_name":"Banner, Ron","first_name":"Ron","last_name":"Banner"},{"full_name":"Yermolin, Yevgeny","last_name":"Yermolin","first_name":"Yevgeny"},{"full_name":"Karbachevsky, Alex","last_name":"Karbachevsky","first_name":"Alex"},{"id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","first_name":"Alexander","orcid":"0000-0001-9699-8730","last_name":"Bronstein"},{"last_name":"Mendelson","first_name":"Avi","full_name":"Mendelson, Avi"}],"title":"Feature map transform coding for energy-efficient CNN inference","date_updated":"2024-12-12T10:04:54Z","day":"28","publication_identifier":{"eissn":["2161-4407"],"isbn":["9781728169279"]},"arxiv":1,"conference":{"location":"Glasgow, United Kingdom","name":"International Joint Conference on Neural Networks","start_date":"2020-07-19","end_date":"2020-07-24"},"external_id":{"arxiv":["1905.10830"]}},{"oa_version":"None","status":"public","quality_controlled":"1","month":"07","publication":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","_id":"18248","extern":"1","publisher":"IEEE","abstract":[{"lang":"eng","text":"Learning an object detection or retrieval system requires a large data set with manual annotations. Such data are expensive and time-consuming to create and therefore difficult to obtain on a large scale. In this work, we propose using the natural correlation in narrations and the visual presence of objects in video to learn an object detector and retriever without any manual labeling involved. We pose the problem as weakly supervised learning with noisy labels, and propose a novel object detection and retrieval paradigm under these constraints. We handle the background rejection by using contrastive samples and confront the high level of label noise with a new clustering score. Our evaluation is based on a set of ten objects with manual ground truth annotation in almost 5000 frames extracted from instructional videos from the web. We demonstrate superior results compared to state-of-the-art weakly- supervised approaches and report a strongly-labeled upper bound as well. While the focus of the paper is object detection and retrieval, the proposed methodology can be applied to a broader range of noisy weakly-supervised problems."}],"date_created":"2024-10-08T13:05:08Z","scopus_import":"1","doi":"10.1109/cvprw50498.2020.00485","citation":{"ista":"Amrani E, Ben-Ari R, Shapira I, Hakim T, Bronstein AM. 2020. Self-supervised object detection and retrieval using unlabeled videos. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 9150938.","apa":"Amrani, E., Ben-Ari, R., Shapira, I., Hakim, T., &#38; Bronstein, A. M. (2020). Self-supervised object detection and retrieval using unlabeled videos. In <i>2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</i>. Seattle, WA, United States: IEEE. <a href=\"https://doi.org/10.1109/cvprw50498.2020.00485\">https://doi.org/10.1109/cvprw50498.2020.00485</a>","ama":"Amrani E, Ben-Ari R, Shapira I, Hakim T, Bronstein AM. Self-supervised object detection and retrieval using unlabeled videos. In: <i>2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</i>. IEEE; 2020. doi:<a href=\"https://doi.org/10.1109/cvprw50498.2020.00485\">10.1109/cvprw50498.2020.00485</a>","ieee":"E. Amrani, R. Ben-Ari, I. Shapira, T. Hakim, and A. M. Bronstein, “Self-supervised object detection and retrieval using unlabeled videos,” in <i>2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</i>, Seattle, WA, United States, 2020.","mla":"Amrani, Elad, et al. “Self-Supervised Object Detection and Retrieval Using Unlabeled Videos.” <i>2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</i>, 9150938, IEEE, 2020, doi:<a href=\"https://doi.org/10.1109/cvprw50498.2020.00485\">10.1109/cvprw50498.2020.00485</a>.","short":"E. Amrani, R. Ben-Ari, I. Shapira, T. Hakim, A.M. Bronstein, in:, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, 2020.","chicago":"Amrani, Elad, Rami Ben-Ari, Inbar Shapira, Tal Hakim, and Alex M. Bronstein. “Self-Supervised Object Detection and Retrieval Using Unlabeled Videos.” In <i>2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</i>. IEEE, 2020. <a href=\"https://doi.org/10.1109/cvprw50498.2020.00485\">https://doi.org/10.1109/cvprw50498.2020.00485</a>."},"language":[{"iso":"eng"}],"author":[{"full_name":"Amrani, Elad","last_name":"Amrani","first_name":"Elad"},{"full_name":"Ben-Ari, Rami","last_name":"Ben-Ari","first_name":"Rami"},{"last_name":"Shapira","first_name":"Inbar","full_name":"Shapira, Inbar"},{"first_name":"Tal","last_name":"Hakim","full_name":"Hakim, Tal"},{"full_name":"Bronstein, Alexander","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","last_name":"Bronstein","orcid":"0000-0001-9699-8730","first_name":"Alexander"}],"year":"2020","article_processing_charge":"No","publication_status":"published","date_updated":"2024-12-12T09:59:41Z","article_number":"9150938","date_published":"2020-07-28T00:00:00Z","title":"Self-supervised object detection and retrieval using unlabeled videos","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","publication_identifier":{"eissn":["2160-7516"],"isbn":["9781728193618"]},"day":"28","type":"conference","conference":{"name":"IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops","location":"Seattle, WA, United States","start_date":"2020-06-14","end_date":"2020-06-19"}},{"doi":"10.1109/icassp40776.2020.9054542","citation":{"apa":"Weiss, T., Vedula, S., Senouf, O., Michailovich, O., Zibulevsky, M., &#38; Bronstein, A. M. (2020). Joint learning of cartesian undersampling and reconstruction for accelerated MRI. In <i>ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>. Barcelona, Spain: IEEE. <a href=\"https://doi.org/10.1109/icassp40776.2020.9054542\">https://doi.org/10.1109/icassp40776.2020.9054542</a>","ista":"Weiss T, Vedula S, Senouf O, Michailovich O, Zibulevsky M, Bronstein AM. 2020. Joint learning of cartesian undersampling and reconstruction for accelerated MRI. ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE International Conference on Acoustics, Speech, and Signal Processing, 9054542.","ama":"Weiss T, Vedula S, Senouf O, Michailovich O, Zibulevsky M, Bronstein AM. Joint learning of cartesian undersampling and reconstruction for accelerated MRI. In: <i>ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>. IEEE; 2020. doi:<a href=\"https://doi.org/10.1109/icassp40776.2020.9054542\">10.1109/icassp40776.2020.9054542</a>","ieee":"T. Weiss, S. Vedula, O. Senouf, O. Michailovich, M. Zibulevsky, and A. M. Bronstein, “Joint learning of cartesian undersampling and reconstruction for accelerated MRI,” in <i>ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>, Barcelona, Spain, 2020.","mla":"Weiss, Tomer, et al. “Joint Learning of Cartesian Undersampling and Reconstruction for Accelerated MRI.” <i>ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>, 9054542, IEEE, 2020, doi:<a href=\"https://doi.org/10.1109/icassp40776.2020.9054542\">10.1109/icassp40776.2020.9054542</a>.","short":"T. Weiss, S. Vedula, O. Senouf, O. Michailovich, M. Zibulevsky, A.M. Bronstein, in:, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2020.","chicago":"Weiss, Tomer, Sanketh Vedula, Ortal Senouf, Oleg Michailovich, Michael Zibulevsky, and Alex M. Bronstein. “Joint Learning of Cartesian Undersampling and Reconstruction for Accelerated MRI.” In <i>ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>. IEEE, 2020. <a href=\"https://doi.org/10.1109/icassp40776.2020.9054542\">https://doi.org/10.1109/icassp40776.2020.9054542</a>."},"scopus_import":"1","_id":"18249","extern":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.1905.09324"}],"quality_controlled":"1","oa_version":"Preprint","conference":{"end_date":"2020-05-08","start_date":"2020-05-04","location":"Barcelona, Spain","name":"IEEE International Conference on Acoustics, Speech, and Signal Processing"},"external_id":{"arxiv":["1905.09324"]},"publication_identifier":{"eissn":["2379-190X"],"isbn":["9781509066322"]},"day":"09","arxiv":1,"date_updated":"2024-12-11T16:06:20Z","title":"Joint learning of cartesian undersampling and reconstruction for accelerated MRI","author":[{"last_name":"Weiss","first_name":"Tomer","full_name":"Weiss, Tomer"},{"full_name":"Vedula, Sanketh","first_name":"Sanketh","last_name":"Vedula"},{"full_name":"Senouf, Ortal","last_name":"Senouf","first_name":"Ortal"},{"full_name":"Michailovich, Oleg","last_name":"Michailovich","first_name":"Oleg"},{"full_name":"Zibulevsky, Michael","first_name":"Michael","last_name":"Zibulevsky"},{"id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","first_name":"Alexander","orcid":"0000-0001-9699-8730","last_name":"Bronstein"}],"language":[{"iso":"eng"}],"abstract":[{"text":"Magnetic Resonance Imaging (MRI) is considered today the golden-standard modality for soft tissues. The long acquisition times, however, make it more prone to motion artifacts as well as contribute to the relative high costs of this examination. Over the years, multiple studies concentrated on designing reduced measurement schemes and image reconstruction schemes for MRI, however these problems have been so far addressed separately. On the other hand, recent works in optical computational imaging have demonstrated growing success of simultaneous learning-based design of the acquisition and reconstruction schemes manifesting significant improvement in the reconstruction quality with a constrained time budget. Inspired by these successes, in this work, we propose to learn accelerated MR acquisition schemes (in the form of Cartesian trajectories) jointly with the image reconstruction operator. To this end, we propose an algorithm for training the combined acquisition-reconstruction pipeline end-to-end in a differentiable way. We demonstrate the significance of using the learned Cartesian trajectories at different speed up rates. Code available at https://github.com/tomer196/fastMRI-Cartesian.","lang":"eng"}],"date_created":"2024-10-08T13:05:24Z","publisher":"IEEE","publication":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","status":"public","month":"04","type":"conference","oa":1,"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","article_number":"9054542","date_published":"2020-04-09T00:00:00Z","year":"2020","article_processing_charge":"No","publication_status":"published"}]