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We provide a rigorous definition of free-energy transduction and its efficiency in arbitrary -- linear or nonlinear -- open chemical reaction networks (CRNs) operating at steady state. Our method is based on the knowledge of the…

Molecular Networks · Quantitative Biology 2022-06-15 Artur Wachtel , Riccardo Rao , Massimiliano Esposito

We present a systematic mathematical analysis of the qualitative steady-state response to rate perturbations in large classes of reaction networks. This includes multimolecular reactions and allows for catalysis, enzymatic reactions,…

Dynamical Systems · Mathematics 2017-11-22 Bernhard Brehm , Bernold Fiedler

It can be fruitful to view two-component physical systems of attractive monomers, A and B, ``chemically'' in terms of a reaction A + B <-> C, where C = AB is an associated pair or complex. We show how to construct free energies in the…

Chemical Physics · Physics 2009-10-31 Michael E. Fisher , Daniel M. Zuckerman

Traditional stochastic modeling of reactive systems limits the domain of applicability of the associated path thermodynamics to systems involving a single elementary reaction at the origin of each observed change in composition. An…

Statistical Mechanics · Physics 2023-01-18 F. Baras , A. L. Garcia , M. Malek Mansour

Current formulations of nonequilibrium thermodynamics of open chemical reaction networks only consider chemostats as free-energy sources sustaining nonequilibrium behaviours. Here, we extend the theory to include incoherent light as a…

Statistical Mechanics · Physics 2021-09-16 Emanuele Penocchio , Riccardo Rao , Massimiliano Esposito

Electrical forces are the background of all the interactions occurring in biochemical systems. From here and by using a combination of ab-initio and ad-hoc models, we introduce the first description of electric field profiles with intrabond…

Biomolecules · Quantitative Biology 2018-02-20 Y. B. Ruiz-Blanco , Y. Almeida , C. M. Sotomayor-Torres , Y. García

Generating molecular graphs with desired chemical properties driven by deep graph generative models provides a very promising way to accelerate drug discovery process. Such graph generative models usually consist of two steps: learning…

Machine Learning · Statistics 2020-06-19 Chengxi Zang , Fei Wang

Information thermodynamics relates the rate of change of mutual information between two interacting subsystems to their thermodynamics when the joined system is described by a bipartite stochastic dynamics satisfying local detailed balance.…

Statistical Mechanics · Physics 2022-08-05 Emanuele Penocchio , Francesco Avanzini , Massimiliano Esposito

Molecular modeling of thermally activated chemistry in condensed phases is essential to understand polymerization, depolymerization, and other processing steps of molecular materials. Current methods typically combine molecular dynamics…

Materials Science · Physics 2026-01-09 Baptiste Martin , Shukai Yao , Chunyu Li , Anthony Bocahut , Matthew Jackson , Alejandro Strachan

In this study, a versatile methodology for initiating polymerization from monomers in highly cross-linked materials is investigated. As polymerization progresses, force-field parameters undergo continuous modification due to the formation…

Computational Engineering, Finance, and Science · Computer Science 2024-01-15 Wonseok Lee , Sanggyu Chong , Jihan Kim

To design a drug given a biological molecule by using deep learning methods, there are many successful models published recently. People commonly used generative models to design new molecules given certain protein. LiGAN was regarded as…

Machine Learning · Computer Science 2022-11-15 Haotian Zhang , Linxiaoyi Wan

The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how…

Chemical Physics · Physics 2014-11-14 Piero Gasparotto , Michele Ceriotti

The article presents new model of equilibrium in open chemical systems suggesting a linear dependence of the reaction shift from equilibrium in presence of the external thermodynamic force. Basic equation of this model contains traditional…

Chemical Physics · Physics 2007-05-23 B. Zilbergleyt

Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and environmental challenges. Many of these processes involve the…

Materials Science · Physics 2019-07-11 Tian Xie , Arthur France-Lanord , Yanming Wang , Yang Shao-Horn , Jeffrey C. Grossman

Most elemental metals under ambient conditions adopt simple structures such as BCC, FCC and HCP in specific groupings across the Periodic Table, and on compression, many of these elements undergo transitions to surprisingly complex…

Materials Science · Physics 2022-06-27 Yuanhui Sun , Lei Zhao , Chris J. Pickard , Russell J. Hemley , Yonghao Zheng , Maosheng Miao

Biomolecular networks have already found great utility in characterizing complex biological systems arising from pair-wise interactions amongst biomolecules. Here, we review how graph theoretical approaches can be applied not only for a…

Molecular Networks · Quantitative Biology 2018-12-03 Heeralal Janwa , Steven E. Massey , Julian Velev , Bud Mishra

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable, or unstable. The combined law of thermodynamics derived by Gibbs about 150 years ago laid the foundation of thermodynamics. In Gibbs combined…

Statistical Mechanics · Physics 2023-08-03 Zi-Kui Liu

Recent laboratory measurements have confirmed that chemical desorption (desorption of products due to exothermic surface reactions) can be an efficient process. The impact of including this process into gas-grain chemical models entirely…

Astrophysics of Galaxies · Physics 2017-01-24 V. Wakelam , J. -C. Loison , R. Mereau , M. Ruaud

The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as…

Artificial Intelligence · Computer Science 2017-12-27 Marwin H. S. Segler , Mark P. Waller

Random graph models have been instrumental in characterizing complex networks, but chemical reaction networks (CRNs) are better represented as hypergraphs. Traditional models of random CRNs often reduce CRNs to bipartite graphs,…

Statistical Mechanics · Physics 2025-07-15 Shesha Gopal Marehalli Srinivas , Massimiliano Esposito , Nahuel Freitas