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Reactive and elastic cross-sections, and rate coefficients, have been calculated for the S(1D)+ D2 (v=0, j=0) reaction using a modified hyperspherical quantum reactive scattering method. The considered collision energy ranges from the…

Chemical Physics · Physics 2023-05-24 Manuel Lara , P. G. Jambrina , F. J. Aoiz

Empirical scoring functions based on either molecular force fields or cheminformatics descriptors are widely used, in conjunction with molecular docking, during the early stages of drug discovery to predict potency and binding affinity of a…

Machine Learning · Computer Science 2017-03-31 Joseph Gomes , Bharath Ramsundar , Evan N. Feinberg , Vijay S. Pande

We investigate performance and optimization of the "digital" bioanalytical response. Specifically, we consider the recently introduced approach of a partial input conversion into inactive compounds, resulting in the "branch point effect"…

Molecular Networks · Quantitative Biology 2013-05-27 Sergii Domanskyi , Vladimir Privman

Time-dependent wave packet calculations for the reaction H+HCl and its isotopic reactions are carried out on the potential energy surface (PES) of Bian and Werner (BW2) [Bian, W.; Werner, H. -J., J. Chem. Phys. 2000, 112, 220]. Reaction…

Chemical Physics · Physics 2007-05-23 Li Yao , Ke-Li Han , He-Shan Song , Dong-Hui Zhang

The construction of a reaction network containing all relevant intermediates and elementary reactions is necessary for the accurate description of chemical processes. In the case of a complex chemical reaction (involving, for instance, many…

Chemical Physics · Physics 2017-12-19 Gregor N. Simm , Markus Reiher

In this work, rate coefficients of four prototypical insertion reactions, X + H2 -- H + XH (X=C(1D), N(2D), O(1D), S(1D)) and associated isotope reactions are calculated based on ring polymer molecular dynamics (RPMD) with Cayley propagator…

Chemical Physics · Physics 2024-06-04 Wenbin Jiang , Yuhao Chen , Yongle Li

We present OrbNet Denali, a machine learning model for electronic structure that is designed as a drop-in replacement for ground-state density functional theory (DFT) energy calculations. The model is a message-passing neural network that…

Predicting the biological function of molecules, be it proteins or drug-like compounds, from their atomic structure is an important and long-standing problem. Function is dictated by structure, since it is by spatial interactions that…

Synthesis of organic bi-layers on silicon was realized by a combination of surface functionalization under ultra-high vacuum (UHV) conditions and solution-based click chemistry. The silicon (001) surface was prepared with a high degree of…

Materials Science · Physics 2020-12-11 T. Glaser , J. Meinecke , C. Länger , J. Heep , U. Koert , M. Dürr

Machine-learning potentials (MLPs) for atomistic simulations are a promising alternative to conventional classical potentials. Current approaches rely on descriptors of the local atomic environment with dimensions that increase…

Materials Science · Physics 2017-12-05 Nongnuch Artrith , Alexander Urban , Gerbrand Ceder

The identification of meaningful reaction coordinates plays a key role in the study of complex molecular systems whose essential dynamics is characterized by rare or slow transition events. In a recent publication, precise defining…

Computational Physics · Physics 2018-11-14 Andreas Bittracher , Ralf Banisch , Christof Schütte

We develop a method combining machine learning (ML) and density functional theory (DFT) to predict low-energy polymorphs by introducing physics-guided descriptors based on structural distortion modes. We systematically generate crystal…

Materials Science · Physics 2022-09-07 Bastien F. Grosso , Nicola A. Spaldin , Aria Mansouri Tehrani

The structure of the Borromean nucleus $^9$Be ($\alpha+\alpha+n$) is addressed within a three-body approach using the analytical transformed harmonic oscillator method. The three-body formalism provides an accurate description of the…

Nuclear Theory · Physics 2016-04-26 J. Casal , M. Rodríguez-Gallardo , J. M. Arias , I. J. Thompson

Computer-assisted synthesis planning aims to help chemists find better reaction pathways faster. Finding viable and short pathways from sugar molecules to value-added chemicals can be modeled as a retrosynthesis planning problem with a…

Other Computer Science · Computer Science 2019-11-19 Peihong Jiang , Hieu Doan , Sandeep Madireddy , Rajeev Surendran Assary , Prasanna Balaprakash

Three-body nuclear reactions in two-nucleon plus core systems are described in the framework of exact scattering equations including the core excitation. A nucleon-core optical potential is constructed that can be easily adjusted to the…

Nuclear Theory · Physics 2015-02-18 A. Deltuva

How and where proteins interface with one another can ultimately impact the proteins' functions along with a range of other biological processes. As such, precise computational methods for protein interface prediction (PIP) come highly…

Quantitative Methods · Quantitative Biology 2021-10-08 Alex Morehead , Chen Chen , Ada Sedova , Jianlin Cheng

Prediction of complete step-by-step chemical reaction mechanisms (CRMs) remains a major challenge. Whereas the traditional approaches in CRM tasks rely on expert-driven experiments or costly quantum chemical computations, contemporary deep…

Chemical Physics · Physics 2025-12-11 Manajit Das , Ajnabiul Hoque , Mayank Baranwal , Raghavan B. Sunoj

A first principles study of the dynamics of $^6$Li($^{2}$S) + $^6$Li$^{174}$Yb($^2\Sigma^+$)$ \to ^6$Li$_2(^1\Sigma^+$) + $^{174}$Yb($^1$S) reaction is presented at cold and ultracold temperatures. The computations involve determination and…

Full quantum dynamics calculations have been carried out for the ionic reaction 4He2+ + 3He and state-to-state reactive probabilities have been obtained using both a time-dependent (TD) and a time-independent (TI) approach. An accurate…

Chemical Physics · Physics 2009-11-11 Enrico Bodo , Manuel Lara , Franco A. Gianturco

Atomic structures and adatom geometries of surfaces encode information about the thermodynamics and kinetics of the processes that lead to their formation, and which can be captured by a generative physical model. Here we develop a workflow…

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