Results 81 to 90 of about 17,173,168 (192)

Modeling chemical reaction networks on the Pontryagin bundle with the Hamilton-Pontryagin approach

IFAC-PapersOnLine, 2015
Abstract The Lagrange-d'Alembert-Pontryagin principle is a versatile approach to model dynamical systems including resistive forces from the Lagrangian view. We show in this work, how this method can be applied to open stoichiometric reaction networks.
Lindhorst, H., Waldherr, S.
openaire   +2 more sources

Reaction kinetics for chemical engineers

, 1989
Reaction Kinetics for Chemical ...
Walas, Stanley M.
core  

Artificial Intelligence in Numerical Modeling of Silver Nanoparticles Prepared in Montmorillonite Interlayer Space

Journal of Chemistry, 2013
Artificial neural network (ANN) models have the capacity to eliminate the need for expensive experimental investigation in various areas of manufacturing processes, including the casting methods.
Parvaneh Shabanzadeh, Norazak Senu, Kamyar Shameli, Maryam Mohaghegh Tabar   +3 more
doaj   +1 more source

Rule-based spatial modeling with diffusing, geometrically constrained molecules

BMC Bioinformatics, 2010
Background We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems.
Lohel Maiko, Lenser Thorsten, Ibrahim Bashar, Gruenert Gerd, Hinze Thomas, Dittrich Peter   +5 more
doaj   +1 more source

Quantifying the C/O Ratio in the Planet-forming Environments around Very Low-mass Stars

The Astrophysical Journal
The material in planet-forming disks determines the composition of planets; hence, it is crucial to understand the physical and chemical processes that set the abundance and distribution of key volatiles.
Javiera K. Díaz-Berríos, Catherine Walsh, Ewine F. van Dishoeck   +2 more
doaj   +1 more source

Chemical reaction dynamics

, 2017
Guest editors Xueming Yang, David Clary and Daniel Neumark introduce the chemical reaction dynamics themed issue of Chemical Society Reviews.
David C. Clary, Daniel M. Neumark, Clary, David C., Xueming Yang, Neumark, Daniel M., Yang, Xueming   +5 more
core   +1 more source

Machine Learning of Reaction Properties via Learned Representations of the Condensed Graph of Reaction

, 2022
The estimation of chemical reaction properties such as activation energies, rates, or yields is a central topic of computational chemistry. In contrast to molecular properties, where machine learning approaches such as graph convolutional neural networks
Green, William H., Green Jr, William H, Heid, Esther   +2 more
core   +1 more source

Scaling limits of spatial compartment models for chemical reaction networks

The Annals of Applied Probability, 2015
We study the effects of fast spatial movement of molecules on the dynamics of chemical species in a spatially heterogeneous chemical reaction network using a compartment model. The reaction networks we consider are either single- or multi-scale.
Pfaffelhuber, Peter, Popovic, Lea
openaire   +5 more sources

Can Cyanide Radicals Drive Molecular Backbone Growth on Interstellar Icy Grains?

The Astrophysical Journal
Motivated by the value of CN-bearing molecules as tracers of interstellar physical conditions, we investigate the reactions of adsorbed CN radicals with acetylene and ethylene (C _2 H _2 and C _2 H _4 ) on interstellar dust-grain analogs using quantum ...
Germán Molpeceres, Joan Enrique-Romero
doaj   +1 more source

Real-Time Optimization and Control of Nonlinear Processes Using Machine Learning

Mathematics, 2019
Machine learning has attracted extensive interest in the process engineering field, due to the capability of modeling complex nonlinear process behavior. This work presents a method for combining neural network models with first-principles models in real-
Zhihao Zhang, Zhe Wu, David Rincon, Panagiotis D. Christofides   +3 more
doaj   +1 more source