With a systematic and objective representation of the system. Our aim is to gain insights into reaction mechanisms Representation invariant to system translation, rotation, and changes Here propose a method based on DTs, which is both interpretableĪnd hypothesis-bias-free via an appropriate system Was previously adopted to select optimal collective variables with Interpreted if the source variables are also interpretable. Sensitive to highly correlated variables. DT 44 classifiers have a unique solution and are not Trial collective variables 38, 41, 42 is required, which could lead to a hypothesis-bias. Of these studies implementing neural networks, a pre-selection of Physically consistent interpretability, which is, instead, a characteristic 37− 43 Most of these approaches are based on neural networks, which lack That might support, and eventually surpass, human-biased “chemicalĭata-driven algorithms for enhanced samplingĬhemical simulations have significant recent contributions. Connecting the descriptors to measurable quantities providesĪ data-driven “unbiased” description of a transition Molecular structure (frame) is part of a reactive or a non-reactive The algorithm might then predict if a certain It is a classification problem, which a machine learning (ML) algorithmĬan be trained to solve. Generated and their correlations with the system dynamics asserted. Physically consistent, and measurable system descriptors might be Regardless of whether they involve crossing an entropic barrier. Procedure, approaches to pragmatically decode reaction mechanisms 5, 33− 36 Since significant amounts of data are often generated by the sampling Rates) while considering the entropic contribution in the analysis. The dynamics of chemical processes ( e.g., reaction The results generated have been used to describe The approach has been successfullyĮmployed to study transitions that would, otherwise, require prohibitively Such a state (an unreactive path), or reach a different New paths which start from a stable state and end up either back in RETIS, the transition region is explored by continuously generating Would be obtained by an infinitely long unbiased MD simulation. Order parameter, (c) its results are in principle identical to what Its main advantages are as follows: (a) it does not alter the naturalĭynamics of the system, (b) it does not require a particularly accurate 31, 32 Respecting the naturalĭynamics of the system, it allows the study of transitions even withĪ significant diffusive contribution 33, 34 ( i.e., a small reaction barrier) and enables the direct investigation Relatively novel methodologies such as replica exchange transition Of the adopted methods ( e.g., usage of a bias potentialĪnd continuous collective variables) could be overcome, thanks to While these studies led to valuable new insights, the limitations Have recently been used to examine FA deprotonation in aqueous solution, 18, 22 successfully describing the proton exchange reaction between waterĪnd FA. Initio molecular dynamics (MD) simulations In this study should be of considerable interest. Instead, these studies have beenįorced to approach each specific chemical example as a separate problem.Īs such, the use of a generalizable approach such as the one we present 24− 30 In these small systems, thermodynamic approaches appropriate for Of acidic proton transport in small water clusters. 9, 19− 23 By contrast, there are only a few papers which focus on the nature In the last decade is the study of acid ionization in bulk water 14− 18 or at the water–air interface. (H 5O 2 +) and Eigen (H 9O 4 +) cations and the mechanisms describing transformationsĪ related area with significant theoretical and computational View of the solvated proton in water focuses on the formation of Zundel In bulk aqueous media have a long history going back to the elucidation Of proton exchange reactions involving solvated FA can improve theĬurrent atmospheric models. 1 It has relatively high atmosphericĬoncentrations 2, 3 and contributes to the formation In regions far from urban areas, formic acid (FA) has been recognizedĪs one of the main factors which reduces the pH of rainwater, causingĪcid rain.
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