scholarly journals Geochemical reaction mechanism discovery from molecular simulation

2015 ◽  
Vol 12 (1) ◽  
pp. 20 ◽  
Author(s):  
Andrew G. Stack ◽  
Paul R. C. Kent

Environmental context Computational simulations are providing an increasingly useful way to isolate specific geochemical and environmental reactions and to test how important they are to the overall rate. In this review, we summarise a few ways that one can simulate a reaction and discuss each technique’s overall strengths and weaknesses. Selected case studies illustrate how these techniques have helped to improve our understanding for geochemical and environmental problems. Abstract Methods to explore reactions using computer simulation are becoming increasingly quantitative, versatile and robust. In this review, a rationale for how molecular simulation can help build better geochemical kinetics models is first given. Some common methods are summarised that geochemists use to simulate reaction mechanisms, specifically classical molecular dynamics and quantum chemical methods and their strengths and weaknesses are also discussed. Useful tools such as umbrella sampling and metadynamics that enable one to explore reactions are discussed. Several case studies wherein geochemists have used these tools to understand reaction mechanisms are presented, including water exchange and sorption on aqueous species and mineral surfaces, surface charging, crystal growth and dissolution, and electron transfer. The effect that molecular simulation has had on our understanding of geochemical reactivity is highlighted in each case. In the future, it is anticipated that molecular simulation of geochemical reaction mechanisms will become more commonplace as a tool to validate and interpret experimental data, and provide a check on the plausibility of geochemical kinetic models.


Author(s):  
Dmitrij Rappoport ◽  
Alan Aspuru-Guzik

Studying organic reaction mechanisms using quantum chemical methods requires from the researcher an extensive knowledge of both organic chemistry and first-principles computation. The need for empirical knowledge arises because any reasonably complete exploration of the potential energy surfaces (PES) of organic reactions is computationally prohibitive. We have previously introduced the Heuristically-Aided Quantum Chemistry (HAQC) approach to modeling complex chemical reactions, which abstracts the empirical knowledge in terms of chemical heuristics—simple rules guiding the PES exploration—and combines them with structure optimizations using quantum chemical methods. The HAQC approach makes use of heuristic kinetic criteria for selecting reaction paths that are not only plausible, that is, consistent with the empirical rules of organic reactivity, but also feasible under the reaction conditions. In this work, we develop heuristic kinetic feasilibity criteria, which correctly predict feasible reaction pathways for a wide range of simple polar (substitutions, additions, and eliminations) and pericyclic organic reactions (cyclizations, sigmatropic shifts, and cycloadditions). In contrast to knowledge-based reaction mechanism prediction methods, the same kinetic heuristics are successful in classifying reaction pathways as feasible or infeasible across this diverse set of reaction mechanisms. We discuss the energy profiles of HAQC and their potential applications in machine learning of chemical reactivity.<br>



2018 ◽  
Author(s):  
Dmitrij Rappoport ◽  
Alan Aspuru-Guzik

Studying organic reaction mechanisms using quantum chemical methods requires from the researcher an extensive knowledge of both organic chemistry and first-principles computation. The need for empirical knowledge arises because any reasonably complete exploration of the potential energy surfaces (PES) of organic reactions is computationally prohibitive. We have previously introduced the Heuristically-Aided Quantum Chemistry (HAQC) approach to modeling complex chemical reactions, which abstracts the empirical knowledge in terms of chemical heuristics—simple rules guiding the PES exploration—and combines them with structure optimizations using quantum chemical methods. The HAQC approach makes use of heuristic kinetic criteria for selecting reaction paths that are not only plausible, that is, consistent with the empirical rules of organic reactivity, but also feasible under the reaction conditions. In this work, we develop heuristic kinetic feasilibity criteria, which correctly predict feasible reaction pathways for a wide range of simple polar (substitutions, additions, and eliminations) and pericyclic organic reactions (cyclizations, sigmatropic shifts, and cycloadditions). In contrast to knowledge-based reaction mechanism prediction methods, the same kinetic heuristics are successful in classifying reaction pathways as feasible or infeasible across this diverse set of reaction mechanisms. We discuss the energy profiles of HAQC and their potential applications in machine learning of chemical reactivity.<br>



2007 ◽  
Author(s):  
S. C. Parker ◽  
J. P. Allen ◽  
C. Arrouvel ◽  
D. Spagnoli ◽  
S. Kerisit ◽  
...  


Author(s):  
Craig M. Bethke

Geochemical reaction modeling plays an increasingly vital role in several areas of geoscience, from environmental geochemistry and petroleum geology to the study of geothermal and hydrothermal fluids. This book provides an up-to-date overview of the use of numerical methods to model reaction processes in the Earth's crust and on its surface. Early chapters develop the theoretical foundations of the field, derive a set of governing equations, and show how numerical methods can be used to solve these equations. Other chapters discuss the distribution of species in natural waters; methods for computing activity coefficients in dilute solutions and in brines; the complexation of ions into mineral surfaces; the kinetics of precipitation and dissolution reactions; and the fractionation of stable isotopes. Later chapters provide a large number of fully worked calculation examples and case studies demonstrating the modeling techniques that can be applied to scientific and practical problems. Students in a variety of specialties from low-temperature geochemistry to groundwater hydrology will benefit from the wealth of information and practical applications this book has to offer.





Author(s):  
C.R.A Catlow ◽  
S.A French ◽  
A.A Sokol ◽  
J.M Thomas

We apply quantum chemical methods to the study of active site structures and reaction mechanisms in mesoporous silica and metal oxide catalysts. Our approach is based on the use of both molecular cluster and embedded cluster (QM/MM) techniques, where the active site and molecular complex are described using density functional theory (DFT) and the embedding matrix simulated by shell model potentials. We consider three case studies: alkene epoxidation over the microporous TS-1 catalyst; methanol synthesis on ZnO and Cu/ZnO and C–H bond activation over Li-doped MgO.



SPE Journal ◽  
2005 ◽  
Vol 10 (03) ◽  
pp. 267-275 ◽  
Author(s):  
Mohammed H. Al-Khaldi ◽  
Hisham A. Nasr-El-Din ◽  
Matthew E. Blauch ◽  
Gary P. Funkhouser


Inorganics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 95 ◽  
Author(s):  
Per E. M. Siegbahn ◽  
Shi-Lu Chen ◽  
Rong-Zhen Liao

The advancements of quantum chemical methods and computer power allow detailed mechanistic investigations of metalloenzymes. In particular, both quantum chemical cluster and combined QM/MM approaches have been used, which have been proven to successfully complement experimental studies. This review starts with a brief introduction of nickel-dependent enzymes and then summarizes theoretical studies on the reaction mechanisms of these enzymes, including NiFe hydrogenase, methyl-coenzyme M reductase, nickel CO dehydrogenase, acetyl CoA synthase, acireductone dioxygenase, quercetin 2,4-dioxygenase, urease, lactate racemase, and superoxide dismutase.



2018 ◽  
Vol 8 (1) ◽  
pp. 67-75
Author(s):  
Arlex Chaves-Guerrero

This paper describes the development and implementation of a molecular simulation model to predict the nucleation process during the condensation of heavy components of the gas natural mixtures of linear alkane (C1 - C6 and C9) at transport conditions (10-40 bar). Specifically, it was used the Monte Carlo method with configurational-bias, the united-atom  force field known as “Transferable Potentials for Phase Equilibria (TraPPE-UA)," and the Umbrella sampling technique. The growth of the droplets was evaluated with the model of Young considering numbers of Knudsen below 0.1. The simulation results obtained for the droplet nucleation and growth were compared with experimental data reported in the literature with the aim of validating the implemented models. The simulations predict a droplets size of 2.09 μm which is in good agreement with the experimental results.



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