{"page":"7429–7434","date_created":"2026-06-10T07:27:19Z","type":"journal_article","article_processing_charge":"Yes (via OA deal)","_id":"21980","das_tickbox":"1","ddc":["540"],"PlanS_conform":"1","corr_author":"1","intvolume":"        26","issue":"22","publication_identifier":{"eissn":["1530-6992"],"issn":["1530-6984"]},"doi":"10.1021/acs.nanolett.6c01462","date_updated":"2026-07-28T09:57:28Z","title":"A computationally efficient and accurate method for predicting conductance of single-molecule junctions","date_published":"2026-06-01T00:00:00Z","abstract":[{"text":"Despite significant progress in the field of molecular electronics over the last two decades, the quantitative prediction of metal-molecule-metal junction conductance remains a challenge. The standard computational framework combines density functional theory (DFT) with nonequilibrium Green’s functions (NEGF) using low-rung exchange-correlation functionals such as PBE, which overestimate the conductances. More advanced correction methods exist but require complex workflows and high computational cost, limiting their accessibility. Here, we introduce a physically motivated approach that approximates results obtained with high-rung functionals. Our method fits the PBE-calculated transmission to a Breit-Wigner form and subsequently refines the fit parameters using molecular orbital energies and metal densities of states computed for the isolated subsystems with high-rung functionals. This approach is applicable to a broad range of molecular junctions yielding conductance values in quantitative agreement with experiments. Our approach is simple, low-cost, and accurate, making it well-suited for routine and large-scale prediction of single-molecule junction conductance.","lang":"eng"}],"acknowledgement":"This work was supported primarily by the Institute of Science and Technology Austria. L.V. was supported in part by the National Science Foundation (No. NSF-DMR 2241180). Z.-F.L. was supported by an NSF CAREER Award, No. DMR-2044552 and an Alfred P. Sloan Research Fellowship, No. FG-2024-21750.","pmid":1,"oa":1,"publication":"Nano Letters","publication_status":"published","OA_place":"publisher","language":[{"iso":"eng"}],"author":[{"last_name":"Gulyaev","first_name":"Artem","full_name":"Gulyaev, Artem","id":"83ed7901-7380-11f0-bf20-a0788d5e654d"},{"id":"d87714c4-663d-11f0-bd06-caece19833e5","full_name":"Hazarika, Jyotisman","orcid":"0009-0007-2542-7878","first_name":"Jyotisman","last_name":"Hazarika"},{"first_name":"Zhen-Fei","last_name":"Liu","full_name":"Liu, Zhen-Fei"},{"id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","full_name":"Venkataraman, Latha","first_name":"Latha","orcid":"0000-0002-6957-6089","last_name":"Venkataraman"}],"quality_controlled":"1","OA_type":"hybrid","year":"2026","oa_version":"Published Version","file_date_updated":"2026-06-16T09:11:35Z","scopus_import":"1","publisher":"American Chemical Society","file":[{"success":1,"relation":"main_file","date_created":"2026-06-16T09:11:35Z","content_type":"application/pdf","date_updated":"2026-06-16T09:11:35Z","file_name":"2026_NanoLetters_Gulyaev.pdf","creator":"dernst","access_level":"open_access","file_size":3362800,"checksum":"897551374cac28e0db26dcb0b676b8e7","file_id":"22013"}],"status":"public","chemrxivid":1,"tmp":{"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","image":"/images/cc_by.png"},"has_accepted_license":"1","day":"01","article_type":"letter_note","month":"06","department":[{"_id":"LaVe"},{"_id":"GradSch"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","volume":26,"external_id":{"chemrxivid":["10.26434/chemrxiv.15001696"],"pmid":["42223342"]},"citation":{"ieee":"A. Gulyaev, J. Hazarika, Z.-F. Liu, and L. Venkataraman, “A computationally efficient and accurate method for predicting conductance of single-molecule junctions,” <i>Nano Letters</i>, vol. 26, no. 22. American Chemical Society, pp. 7429–7434, 2026.","chicago":"Gulyaev, Artem, Jyotisman Hazarika, Zhen-Fei Liu, and Latha Venkataraman. “A Computationally Efficient and Accurate Method for Predicting Conductance of Single-Molecule Junctions.” <i>Nano Letters</i>. American Chemical Society, 2026. <a href=\"https://doi.org/10.1021/acs.nanolett.6c01462\">https://doi.org/10.1021/acs.nanolett.6c01462</a>.","ama":"Gulyaev A, Hazarika J, Liu Z-F, Venkataraman L. A computationally efficient and accurate method for predicting conductance of single-molecule junctions. <i>Nano Letters</i>. 2026;26(22):7429–7434. doi:<a href=\"https://doi.org/10.1021/acs.nanolett.6c01462\">10.1021/acs.nanolett.6c01462</a>","apa":"Gulyaev, A., Hazarika, J., Liu, Z.-F., &#38; Venkataraman, L. (2026). A computationally efficient and accurate method for predicting conductance of single-molecule junctions. <i>Nano Letters</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.nanolett.6c01462\">https://doi.org/10.1021/acs.nanolett.6c01462</a>","ista":"Gulyaev A, Hazarika J, Liu Z-F, Venkataraman L. 2026. A computationally efficient and accurate method for predicting conductance of single-molecule junctions. Nano Letters. 26(22), 7429–7434.","mla":"Gulyaev, Artem, et al. “A Computationally Efficient and Accurate Method for Predicting Conductance of Single-Molecule Junctions.” <i>Nano Letters</i>, vol. 26, no. 22, American Chemical Society, 2026, pp. 7429–7434, doi:<a href=\"https://doi.org/10.1021/acs.nanolett.6c01462\">10.1021/acs.nanolett.6c01462</a>.","short":"A. Gulyaev, J. Hazarika, Z.-F. Liu, L. Venkataraman, Nano Letters 26 (2026) 7429–7434."}}