Matches in SemOpenAlex for { <https://semopenalex.org/work/W3199058067> ?p ?o ?g. }
- W3199058067 endingPage "6202" @default.
- W3199058067 startingPage "6193" @default.
- W3199058067 abstract "We propose to analyze molecular dynamics (MD) output via a supervised machine learning (ML) algorithm, the decision tree. The approach aims to identify the predominant geometric features which correlate with trajectories that transition between two arbitrarily defined states. The data-driven algorithm aims to identify these features without the bias of human chemical intuition. We demonstrate the method by analyzing the proton exchange reactions in formic acid solvated in small water clusters. The simulations were performed with ab initio MD combined with a method to efficiently sample the rare event, path sampling. Our ML analysis identified relevant geometric variables involved in the proton transfer reaction and how they may change as the number of solvating water molecules changes." @default.
- W3199058067 created "2021-09-27" @default.
- W3199058067 creator A5026669029 @default.
- W3199058067 creator A5035281978 @default.
- W3199058067 creator A5089673197 @default.
- W3199058067 date "2021-09-24" @default.
- W3199058067 modified "2023-09-24" @default.
- W3199058067 title "Chemistrees: Data-Driven Identification of Reaction Pathways <i>via</i> Machine Learning" @default.
- W3199058067 cites W1809666471 @default.
- W3199058067 cites W1964585075 @default.
- W3199058067 cites W1967446390 @default.
- W3199058067 cites W1970361289 @default.
- W3199058067 cites W1977545273 @default.
- W3199058067 cites W2014166972 @default.
- W3199058067 cites W2016559264 @default.
- W3199058067 cites W2029667189 @default.
- W3199058067 cites W2037542442 @default.
- W3199058067 cites W2040478344 @default.
- W3199058067 cites W2047096362 @default.
- W3199058067 cites W2057274108 @default.
- W3199058067 cites W2059299337 @default.
- W3199058067 cites W2061681393 @default.
- W3199058067 cites W2074473238 @default.
- W3199058067 cites W2078184681 @default.
- W3199058067 cites W2092157292 @default.
- W3199058067 cites W2093237481 @default.
- W3199058067 cites W2095165857 @default.
- W3199058067 cites W2099039152 @default.
- W3199058067 cites W2116223045 @default.
- W3199058067 cites W2315242866 @default.
- W3199058067 cites W2315975849 @default.
- W3199058067 cites W2328508529 @default.
- W3199058067 cites W2333564429 @default.
- W3199058067 cites W2341723931 @default.
- W3199058067 cites W2346255894 @default.
- W3199058067 cites W2435408353 @default.
- W3199058067 cites W2527927485 @default.
- W3199058067 cites W2530254746 @default.
- W3199058067 cites W2606681842 @default.
- W3199058067 cites W2625977548 @default.
- W3199058067 cites W2741652401 @default.
- W3199058067 cites W2743483573 @default.
- W3199058067 cites W2751965935 @default.
- W3199058067 cites W2764223792 @default.
- W3199058067 cites W2781487518 @default.
- W3199058067 cites W2800395095 @default.
- W3199058067 cites W2890238694 @default.
- W3199058067 cites W2911964244 @default.
- W3199058067 cites W2915067821 @default.
- W3199058067 cites W2921184491 @default.
- W3199058067 cites W2959253776 @default.
- W3199058067 cites W2963383782 @default.
- W3199058067 cites W2990815339 @default.
- W3199058067 cites W3006326370 @default.
- W3199058067 cites W3007347579 @default.
- W3199058067 cites W3033877811 @default.
- W3199058067 cites W3036640743 @default.
- W3199058067 cites W3111876955 @default.
- W3199058067 cites W3115069587 @default.
- W3199058067 cites W3122702518 @default.
- W3199058067 cites W3135162129 @default.
- W3199058067 doi "https://doi.org/10.1021/acs.jctc.1c00458" @default.
- W3199058067 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8515787" @default.
- W3199058067 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34555907" @default.
- W3199058067 hasPublicationYear "2021" @default.
- W3199058067 type Work @default.
- W3199058067 sameAs 3199058067 @default.
- W3199058067 citedByCount "3" @default.
- W3199058067 countsByYear W31990580672022 @default.
- W3199058067 countsByYear W31990580672023 @default.
- W3199058067 crossrefType "journal-article" @default.
- W3199058067 hasAuthorship W3199058067A5026669029 @default.
- W3199058067 hasAuthorship W3199058067A5035281978 @default.
- W3199058067 hasAuthorship W3199058067A5089673197 @default.
- W3199058067 hasBestOaLocation W31990580671 @default.
- W3199058067 hasConcept C111472728 @default.
- W3199058067 hasConcept C11413529 @default.
- W3199058067 hasConcept C119857082 @default.
- W3199058067 hasConcept C121332964 @default.
- W3199058067 hasConcept C124101348 @default.
- W3199058067 hasConcept C132010649 @default.
- W3199058067 hasConcept C138885662 @default.
- W3199058067 hasConcept C147597530 @default.
- W3199058067 hasConcept C154945302 @default.
- W3199058067 hasConcept C178790620 @default.
- W3199058067 hasConcept C185592680 @default.
- W3199058067 hasConcept C199360897 @default.
- W3199058067 hasConcept C2777379063 @default.
- W3199058067 hasConcept C2777735758 @default.
- W3199058067 hasConcept C2781442258 @default.
- W3199058067 hasConcept C41008148 @default.
- W3199058067 hasConcept C43617362 @default.
- W3199058067 hasConcept C54516573 @default.
- W3199058067 hasConcept C55493867 @default.
- W3199058067 hasConcept C59593255 @default.
- W3199058067 hasConcept C62520636 @default.
- W3199058067 hasConcept C74187038 @default.
- W3199058067 hasConcept C99726746 @default.