KUTE: Green-Kubo Uncertainty-Based Transport Coefficient Estimator.

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2025-03-19 DOI:10.1021/acs.jcim.4c02219
Martín Otero-Lema, Raúl Lois-Cuns, Miguel A Boado, Hadrián Montes-Campos, Trinidad Méndez-Morales, Luis M Varela
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Abstract

An algorithm for the calculation of transport properties from molecular dynamics simulations, kute, is introduced. The method estimates the integrals from the Green-Kubo theorem, taking into account the uncertainties of the correlation functions in order to eliminate arbitrary cutoffs or external parameters whose values could alter the result. In this contribution, the performance of kute is tested against other popular methods for the case of a protic ionic liquid for a variety of transport properties. It is found that kute achieves the same degree of accuracy as the equivalent formulation of the Einstein relations while performing better than other methods to calculate transport properties using Green-Kubo methods.

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9.80
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10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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