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Journal of Chemical Theory and Computation
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JAX-ReaxFF: A Gradient-Based Framework for Fast Optimization of Reactive Force Fields

descriptionPublicationkeyboard_double_arrow_right Article , Conference object , Other literature type 18 Aug 2022 English Publisher:American Chemical Society (ACS)Journal:Journal of Chemical Theory and Computation, volume 18, pages 5,181-5,194 (issn: 1549-9618, eissn: 1549-9626, Copyright policy )Funded by:NSF | Collaborative Research: C..., NIH | Modeling Transition Metal...
Authors: Mehmet Cagri Kaymak; Ali Rahnamoun; Kurt A. O’Hearn; Adri C. T. van Duin; Kenneth M. Merz; Hasan Metin Aktulga;

doi: 10.1021/acs.jctc.2c00363 , 10.5281/zenodo.6863899 , 10.5281/zenodo.6863898

pmid: 35978524

JAX-ReaxFF: A Gradient-Based Framework for Fast Optimization of Reactive Force Fields

Abstract

We describe the JAX-ReaxFF software which is a novel gradient-based framework for fast optimization of parameter sets for reactive force fields, specifically the Reax Force Field.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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OpenAIRE UsageCountsViews provided by UsageCounts
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