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In this paper, we present a study on how to develop an efficient multiscale simulation strategy for the dynamics of chemically active systems on low-dimensional supports. Such reactions are encountered in a wide variety of situations,…

Computational Physics · Physics 2015-06-04 Giacomo Mazzi , Yannick De Decker , Giovanni Samaey

One of the most important and difficult parts of constructing a multidimensional numerical simulation of flame acceleration and deflagration-to-detonation transition (DDT) in a reacting flow is finding a reliable and affordable model of the…

Fluid Dynamics · Physics 2017-09-04 Carolyn R. Kaplan , Alp Ozgen , Elaine S. Oran

Molecular circuits capable of autonomous learning could unlock novel applications in fields such as bioengineering and synthetic biology. To this end, existing chemical implementations of neural computing have mainly relied on emulating…

Machine Learning · Computer Science 2025-09-23 Rajiv Teja Nagipogu , John H. Reif

We propose a direct optimization framework for learning reduced and sparse chemical reaction networks (CRNs) from time-series trajectory data. In contrast to widely used indirect methods-such as those based on sparse identification of…

Molecular Networks · Quantitative Biology 2025-08-27 Maurice Filo , Mustafa Khammash

Organic reactions are usually assigned to classes containing reactions with similar reagents and mechanisms. Reaction classes facilitate the communication of complex concepts and efficient navigation through chemical reaction space.…

Finding representative reaction pathways is necessary for understanding mechanisms of molecular processes, but is considered to be extremely challenging. We propose a new method to construct reaction paths based on mean first-passage times.…

Chemical Physics · Physics 2015-06-26 Sanghyun Park , Klaus Schulten

We first derive the Hamilton-Jacobi theory underlying continuous-time Markov processes, and then use the construction to develop a variational algorithm for estimating escape (least improbable or first passage) paths for a generic…

Statistical Mechanics · Physics 2023-03-29 Praful Gagrani , Eric Smith

Formal methods have enabled breakthroughs in many fields, such as in hardware verification, machine learning and biological systems. The key object of interest in systems biology, synthetic biology, and molecular programming is chemical…

Emerging Technologies · Computer Science 2020-08-11 Marko Vasic , David Soloveichik , Sarfraz Khurshid

Chemical reaction mechanisms are the foundation of how chemists evaluate reactivity and feasibility, yet current Computer-Assisted Synthesis Planning (CASP) systems operate without this mechanistic reasoning. We introduce a computational…

Machine Learning · Computer Science 2026-04-20 Théo A. Neukomm , Zlatko Jončev , Philippe Schwaller

We present the OptiBounce algorithm, a new and fast method for finding the bounce action for cosmological phase transitions. This is done by direct solution of the "reduced" minimisation problem proposed by Coleman, Glaser, and Martin. By…

Cosmology and Nongalactic Astrophysics · Physics 2022-01-05 Michael Bardsley

This paper introduces a new platform to accelerate the modeling of complex aerothermochemical interactions in new turbomachines, turbo-reactors, to decarbonise chemical processes. While previous work has aerothermally demonstrated the…

Computational Engineering, Finance, and Science · Computer Science 2025-02-13 Dylan Rubini , Budimir Rosic

Scanning transmission electron microscopy (STEM) is now the primary tool for exploring functional materials on the atomic level. Often, features of interest are highly localized in specific regions in the material, such as ferroelectric…

Materials Science · Physics 2021-08-11 Nicole Creange , Ondrej Dyck , Rama K. Vasudevan , Maxim Ziatdinov , Sergei V. Kalinin

A chemical reaction mechanism (CRM) is a sequence of molecular-level events involving bond-breaking/forming processes, generating transient intermediates along the reaction pathway as reactants transform into products. Understanding such…

Chemical Physics · Physics 2024-07-16 Ajnabiul Hoque , Manajit Das , Mayank Baranwal , Raghavan B. Sunoj

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

The use of machine learning algorithms is an attractive way to produce very fast detector simulations for scattering reactions that can otherwise be computationally expensive. Here we develop a factorised approach where we deal with each…

Data Analysis, Statistics and Probability · Physics 2022-07-26 D. Darulis , R. Tyson , D. G. Ireland , D. I. Glazier , B. McKinnon , P. Pauli

We propose a numerical technique for parameter inference in Markov models of biological processes. Based on time-series data of a process we estimate the kinetic rate constants by maximizing the likelihood of the data. The computation of…

Quantitative Methods · Quantitative Biology 2011-02-15 Aleksandr Andreychenko , Linar Mikeev , David Spieler , Verena Wolf

Multistationary chemical reaction networks are of interest to scientists and mathematicians alike. While some criteria for multistationarity exist, obtaining explicit reaction rates and steady states that exhibit multistationarity for a…

Dynamical Systems · Mathematics 2016-04-22 Bryan Félix , Anne Shiu , Zev Woodstock

Reaction coordinates are widely used throughout chemical physics to model and understand complex chemical transformations. We introduce a definition of the natural reaction coordinate, suitable for condensed phase and biomolecular systems,…

Statistical Mechanics · Physics 2017-03-08 Robert T. McGibbon , Brooke E. Husic , Vijay S. Pande

Estimating rate coefficients from complex chemical reactions is essential for advancing detailed chemistry. However, the stiffness inherent in real-world atmospheric chemistry systems poses severe challenges, leading to training instability…

Machine Learning · Computer Science 2025-09-01 Wenqing Peng , Zhi-Song Liu , Michael Boy

Here we focus on the challenge of verifying the correctness of molecular implementations of abstract chemical reaction networks, where operation in a well-mixed "soup" of molecules is stochastic, asynchronous, concurrent, and often involves…

Computational Engineering, Finance, and Science · Computer Science 2019-10-01 Seung Woo Shin , Chris Thachuk , Erik Winfree