On combining molecular dynamics and stochastic dynamics simulations to compute reaction rates in liquids

2004 ◽  
Vol 120 (2) ◽  
pp. 898-902 ◽  
Author(s):  
Yin Guo ◽  
Donald L. Thompson
Keyword(s):  
Molecular Dynamics ◽  
Stochastic Dynamics ◽  
Reaction Rates ◽  
Dynamics Simulations

scholarly journals Fast predictions of liquid-phase acid-catalyzed reaction rates using molecular dynamics simulations and convolutional neural networks

2020 ◽  
Vol 11 (46) ◽  
pp. 12464-12476 ◽  
Author(s):  
Alex K. Chew ◽  
Shengli Jiang ◽  
Weiqi Zhang ◽  
Victor M. Zavala ◽  
Reid C. Van Lehn
Keyword(s):  
Neural Networks ◽  
Molecular Dynamics ◽  
Liquid Phase ◽  
Molecular Dynamics Simulations ◽  
Convolutional Neural Networks ◽  
Reaction Rates ◽  
Acid Catalyzed ◽  
Dynamics Simulations

Solvent-mediated, acid-catalyzed reaction rates relevant to the upgrading of biomass into high-value chemicals are accurately predicted using a combination of molecular dynamics simulations and 3D convolutional neural networks.

scholarly journals Fast Predictions of Liquid-Phase Acid-Catalyzed Reaction Rates Using Molecular Dynamics Simulations and Convolutional Neural Networks

2020 ◽  
Author(s):  
Alex Chew ◽  
Shengli Jiang ◽  
Weiqi Zhang ◽  
Victor Zavala ◽  
Reid Van Lehn
Keyword(s):  
Neural Networks ◽  
Molecular Dynamics ◽  
Liquid Phase ◽  
Molecular Dynamics Simulations ◽  
Convolutional Neural Networks ◽  
Reaction Rates ◽  
Solvent Mixtures ◽  
Acid Catalyzed ◽  
Solvent Systems ◽  
Dynamics Simulations

The rates of liquid-phase, acid-catalyzed reactions relevant to the upgrading of biomass into high-value chemicals are highly sensitive to solvent composition and identifying suitable solvent mixtures is theoretically and experimentally challenging. We show that the atomistic configurations of reactant-solvent environments generated by classical molecular dynamics simulations can be exploited by 3D convolutional neural networks to enable fast predictions of Brønsted acid-catalyzed reaction rates for model biomass compounds. We develop a computational implementation, which we call SolventNet, and train it using experimental reaction data for seven biomass-derived oxygenates in water-cosolvent mixtures. We show that SolventNet can predict reaction rates for additional reactants and solvent systems an order of magnitude faster than prior simulation methods. This combination of machine learning with molecular dynamics enables the rapid screening of solvent systems and identification of improved biomass conversion conditions.

scholarly journals Density artefacts at interfaces caused by multiple time-step effects in molecular dynamics simulations

F1000Research ◽  
2019 ◽  
Vol 7 ◽  
pp. 1745 ◽  
Author(s):  
Dominik Sidler ◽  
Marc Lehner ◽  
Simon Frasch ◽  
Michael Cristófol-Clough ◽  
Sereina Riniker
Keyword(s):  
Molecular Dynamics ◽  
Weak Coupling ◽  
Stochastic Dynamics ◽  
Md Simulations ◽  
Multiple Time ◽  
Time Step ◽  
Nonbonded Interactions ◽  
Multiple Time Step ◽  
Wide Range ◽  
Dynamics Simulations

Background: Molecular dynamics (MD) simulations have become an important tool to provide insight into molecular processes involving biomolecules such as proteins, DNA, carbohydrates and membranes. As these processes cover a wide range of time scales, multiple time-step integration methods are often employed to increase the speed of MD simulations. For example, in the twin-range (TR) scheme, the nonbonded forces within the long-range cutoff are split into a short-range contribution updated every time step (inner time step) and a less frequently updated mid-range contribution (outer time step). The presence of different time steps can, however, cause numerical artefacts. Methods: The effects of multiple time-step algorithms at interfaces between polar and apolar media are investigated with MD simulations. Such interfaces occur with biological membranes or proteins in solution. Results: In this work, it is shown that the TR splitting of the nonbonded forces leads to artificial density increases at interfaces for weak coupling and Nosé-Hoover (chain) thermostats. It is further shown that integration with an impulse-wise reversible reference system propagation algorithm (RESPA) only shifts the occurrence of density artefacts towards larger outer time steps. Using a single-range (SR) treatment of the nonbonded interactions or a stochastic dynamics thermostat, on the other hand, resolves the density issue for pairlist-update periods of up to 40 fs. Conclusion: TR schemes are not advisable to use in combination with weak coupling or Nosé-Hoover (chain) thermostats due to the occurrence of significant numerical artifacts at interfaces.

scholarly journals Impact of volatile organic compounds on chromium containing atmospheric particulate: insights from molecular dynamics simulations

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Dhawal Shah ◽  
Mirat Karibayev ◽  
Enoch Kwasi Adotey ◽  
Mehdi Amouei Torkmahalleh
Keyword(s):  
Molecular Dynamics ◽  
Ascorbic Acid ◽  
Volatile Organic Compounds ◽  
Molecular Dynamics Simulations ◽  
Organic Compounds ◽  
Reaction Rates ◽  
Atmospheric Particles ◽  
Solution Chemistry ◽  
Volatile Organic ◽  
Dynamics Simulations

Abstract The effect of volatile organic compounds (VOCs) on chromium-containing atmospheric particles remains obscured because of difficulties in experimental measurements. Moreover, several ambiguities exist in the literature related to accurate measurements of atmospheric chromium concentration to evaluate its toxicity. We investigated the interaction energies and diffusivity for several VOCs in chromium (III)-containing atmospheric particles using classical molecular dynamics simulations. We analyzed xylene, toluene, ascorbic acid, carbon tetrachloride, styrene, methyl ethyl ketone, naphthalene, and anthracene in Cr(III) solutions, with and without air, to compare their effects on solution chemistry. The interaction energy between Cr(III) and water changed from 48 to 180% for different VOCs, with the highest change with anthracene and the lowest change with naphthalene. The results revealed no direct interactions between Cr(III) particles and the analyzed volatile organic compounds, except ascorbic acid. Interactions of Cr(III) and ascorbic acid differ significantly between the solution phase and the particulate phase. The diffusion of Cr(III) and all the VOCs also were observed in a similar order of magnitude (~ 10−5 cm2/s). The results can further assist in exploring the variation in chromium chemistry and reaction rates in the atmospheric particles in the presence of VOCs.

Mean field ring polymer molecular dynamics for electronically nonadiabatic reaction rates

2016 ◽  
Vol 195 ◽  
pp. 253-268 ◽  
Author(s):  
Jessica Ryan Duke ◽  
Nandini Ananth
Keyword(s):  
Molecular Dynamics ◽  
Mean Field ◽  
Golden Rule ◽  
Reaction Rates ◽  
State Theory ◽  
Time Dynamics ◽  
Ring Polymer ◽  
Ring Polymer Molecular Dynamics ◽  
Dividing Surface ◽  
Dynamics Simulations

We present a mean field ring polymer molecular dynamics method to calculate the rate of electron transfer (ET) in multi-state, multi-electron condensed-phase processes. Our approach involves calculating a transition state theory (TST) estimate to the rate using an exact path integral in discrete electronic states and continuous Cartesian nuclear coordinates. A dynamic recrossing correction to the TST rate is then obtained from real-time dynamics simulations using mean field ring polymer molecular dynamics. We employ two different reaction coordinates in our simulations and show that, despite the use of mean field dynamics, the use of an accurate dividing surface to compute TST rates allows us to achieve remarkable agreement with Fermi's golden rule rates for nonadiabatic ET in the normal regime of Marcus theory. Further, we show that using a reaction coordinate based on electronic state populations allows us to capture the turnover in rates for ET in the Marcus inverted regime.

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