scholarly journals Reaction and relaxation at surface hotspots: using molecular dynamics and the energy-grained master equation to describe diamond etching

2017 ◽  
Vol 375 (2092) ◽  
pp. 20160206 ◽  
Author(s):  
David R. Glowacki ◽  
W. J. Rodgers ◽  
Robin Shannon ◽  
Struan H. Robertson ◽  
Jeremy N. Harvey
Keyword(s):  
Molecular Dynamics ◽  
Energy Transfer ◽  
Master Equation ◽  
Gas Phase ◽  
Reasonable Agreement ◽  
Chemical Vapour ◽  
Md Simulations ◽  
State Theory ◽  
Structure Theory ◽  
Non Equilibrium

The extent to which vibrational energy transfer dynamics can impact reaction outcomes beyond the gas phase remains an active research question. Molecular dynamics (MD) simulations are the method of choice for investigating such questions; however, they can be extremely expensive, and therefore it is worth developing cheaper models that are capable of furnishing reasonable results. This paper has two primary aims. First, we investigate the competition between energy relaxation and reaction at ‘hotspots’ that form on the surface of diamond during the chemical vapour deposition process. To explore this, we developed an efficient reactive potential energy surface by fitting an empirical valence bond model to higher-level ab initio electronic structure theory. We then ran 160 000 NVE trajectories on a large slab of diamond, and the results are in reasonable agreement with experiment: they suggest that energy dissipation from surface hotspots is complete within a few hundred femtoseconds, but that a small fraction of CH 3 does in fact undergo dissociation prior to the onset of thermal equilibrium. Second, we developed and tested a general procedure to formulate and solve the energy-grained master equation (EGME) for surface chemistry problems. The procedure we outline splits the diamond slab into system and bath components, and then evaluates microcanonical transition-state theory rate coefficients in the configuration space of the system atoms. Energy transfer from the system to the bath is estimated using linear response theory from a single long MD trajectory, and used to parametrize an energy transfer function which can be input into the EGME. Despite the number of approximations involved, the surface EGME results are in reasonable agreement with the NVE MD simulations, but considerably cheaper. The results are encouraging, because they offer a computationally tractable strategy for investigating non-equilibrium reaction dynamics at surfaces for a broader range of systems. This article is part of the themed issue ‘Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces’.

Characterizing gaseous peptide structure with action-EET and simulated annealing

2015 ◽  
Vol 17 (39) ◽  
pp. 25822-25827 ◽  
Author(s):  
Nathan G. Hendricks ◽  
Ryan R. Julian
Keyword(s):  
Molecular Dynamics ◽  
Energy Transfer ◽  
Simulated Annealing ◽  
Gas Phase ◽  
Peptide Structure

Distance-sensitive energy transfer and molecular dynamics are used to generate experimentally corroborated structures for peptides in the gas phase.

Temperature profiles and heat fluxes observed in molecular dynamics simulations of force-driven liquid flows

2017 ◽  
Vol 19 (16) ◽  
pp. 10317-10325 ◽  
Author(s):  
Jafar Ghorbanian ◽  
Ali Beskok
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Md Simulations ◽  
Heat Fluxes ◽  
Temperature Profiles ◽  
Non Equilibrium Molecular Dynamics ◽  
Dynamics Simulations ◽  
Liquid Flows ◽  
Non Equilibrium

This paper concentrates on the unconventional temperature profiles and heat fluxes observed in non-equilibrium molecular dynamics (MD) simulations of force-driven liquid flows in nano-channels.

Fragment Pose Prediction Using Non-Equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations

2019 ◽  
Author(s):  
Nathan M. Lim ◽  
Meghan Osato ◽  
Gregory L. Warren ◽  
David L. Mobley
Keyword(s):  
Crystal Structure ◽  
Molecular Dynamics ◽  
Monte Carlo ◽  
Ligand Binding ◽  
Md Simulations ◽  
Binding Mode ◽  
Protein Crystal ◽  
Pose Prediction ◽  
Binding Modes ◽  
Non Equilibrium

<div>Part of early stage drug discovery involves determining how molecules may bind to the target protein. Through understanding where and how molecules bind, chemists can begin to build ideas on how to design improvements to increase binding affinities. In this retrospective study, we compare how computational approaches like docking, molecular dynamics (MD) simulations, and a non-equilibrium candidate Monte Carlo (NCMC) based method (NCMC+MD) perform in predicting binding modes for a set of 12 fragment-like molecules which bind to soluble epoxide hydrolase. We evaluate each method's effectiveness in identifying the dominant binding mode and finding any additional binding modes (if any). Then, we compare our predicted binding modes to experimentally obtained X-ray crystal structures.</div><div>We dock each of the 12 small molecules into the apo-protein crystal structure and then run simulations up to 1 microsecond each. Small and fragment-like molecules likely have smaller energy barriers separating different binding modes by virtue of relatively fewer and weaker interactions relative to drug-like molecules, and thus likely undergo more rapid binding mode transitions. We expect, thus, to see more rapid transitions betweeen binding modes in our study. </div><div><br></div><div>Following this, we build Markov State Models (MSM) to define our stable ligand binding modes. We investigate if adequate sampling of ligand binding modes and transitions between them can occur at the microsecond timescale using traditional MD or a hybrid NCMC+MD simulation approach. Our findings suggest that even with small fragment-like molecules, we fail to sample all the crystallographic binding modes using microsecond MD simulations, but using NCMC+MD we have better success in sampling the crystal structure while obtaining the correct populations.</div>

MasterMSM: A Package for Constructing Master Equation Models of Molecular Dynamics

2019 ◽  
Author(s):  
David De Sancho ◽  
Anne Aguirre
Keyword(s):  
Molecular Dynamics ◽  
Master Equation ◽  
Md Simulations ◽  
Distinctive Features ◽  
Markov State Models ◽  
Software Packages ◽  
Long Time ◽  
State Models ◽  
Definition Of ◽  
Kinetics Of

<div>Markov state models (MSMs) have become one of the most important techniques for understanding biomolecular transitions from classical molecular dynamics (MD) simulations. MSMs provide a systematized way of accessing the long time kinetics of the system of interest from the short-timescale microscopic transitions observed in simulation trajectories. At the same time, they provide a consistent description of the equilibrium and dynamical properties of the system of interest, and they are ideally suited for comparisons against experiment. A few software packages exist for building MSMs, which have been widely adopted. Here we introduce MasterMSM, a new Python package that uses the master equation formulation of MSMs and provides a number of new algorithms for building and analyzing these models. We demonstrate some of the most distinctive features of the package, including the estimation of rates, definition of core-sets for transition based assignment of states, the estimation of committors and fluxes, and the sensitivity analysis of the emerging networks. The package is available at https://github.com/daviddesancho/MasterMSM.</div>

Study of Thermal Energy Transport Between Hydrogen Gas Molecules and a Single-Wall Carbon Nanotube Using Molecular Dynamics Simulations

2005 ◽  
Author(s):  
Jose´ E. Solomon ◽  
Jay Kapat ◽  
Ranganathan Kumar ◽  
Deepak Srivastava
Keyword(s):  
Molecular Dynamics ◽  
Energy Transfer ◽  
Carbon Nanotube ◽  
Thermal Energy ◽  
Energy Transport ◽  
Md Simulations ◽  
Hydrogen Gas ◽  
Gas Density ◽  
Gas Molecules ◽  
Thermal Energy Transport

The focus of the current research is the investigation and characterization of the energy transport between a (10,10) single-wall carbon nanotube (SWCNT) and surrounding molecular hydrogen gas using molecular dynamics (MD) simulations. The MD simulations use Tersoff-Brenner hydrocarbon potential for C-C, C-H, and H-H bonding interactions and the conventional Lennard-Jones potential for soft-sphere gas-CNT collision dynamics of H-H and H-C non-bonding van der Waals interactions. A simulation cell with periodic boundary conditions is created for 1200 carbon atoms in an armchair nanotube configuration and three distinct gas densities corresponding to 252, 500, and 1000 H2 molecules in the same volume. The MD simulation runs are performed with time steps of 0.1 fs and the total simulation times of 40 ps. The simulations are initialized by setting the gas species and CNT at two different temperatures. Initial gas temperatures range from 2000K to 4000K, whereas the carbon nanotube is held at 300K. After the equilibrium temperatures of the CNT and the gas molecules are achieved, the external constraints to maintain the temperature are removed and the thermal energy transport between the two is studied. The kinetic energy exchange between the nanotube and the surrounding gas is monitored to study thermal energy transport over the duration of the simulation. A parameter is proposed, the coefficient of thermal energy transfer (CTET), to characterize the thermal transport properties of the modeled systems based on parameters governing the transport process, thus mimicking the conventional heat transfer coefficient. Values for CTET vary directly with gas density and range from 50 MW/m2K to 250MW/m2K, showing that gas density has a significant impact with higher density corresponding to higher collision rates and higher rates of energy transfer. In contrast, the gas temperature has a lower impact on CTET, with colder gas providing in certain cases a slightly lower value for the coefficient. In order to validate the MD simulations, the time-series data of molecular vibrations of the CNT is converted to a vibrational frequency spectrum through FFT. The characteristic frequencies obtained on the spectra of isolated SWCNT and H2 simulations are compared against the known natural frequencies of the CNT phonon modes and vibrational modes of H2 molecules. The comparison is quite favorable.

scholarly journals Theoretical insights into the dissociation process for dissociative electron attachment to adenine and its tautomer

2020 ◽  
Vol 38 (4) ◽  
pp. 277-284
Author(s):  
Ying Zhang ◽  
Xing Wang ◽  
Zhongfeng Xu
Keyword(s):  
Molecular Dynamics ◽  
Density Matrix ◽  
Gas Phase ◽  
Electron Attachment ◽  
Closed Shell ◽  
Md Simulations ◽  
Ab Initio Molecular Dynamics ◽  
Dissociative Electron Attachment ◽  
Dissociation Process ◽  
First Time

AbstractThe ab initio molecular dynamics (MD) simulations using an atom-centered density matrix propagation method are carried out in the first time to investigate the dissociative electron attachment (DEA) processes of adenine and its tautomer in the gas phase. Since the incoming electron are captured on the lowest π∗ anti-bond orbital, which is led to the different N–H bond, the C–H bond and the C–N bond are broken. The dominant anion observed in DEA dissociation process is the closed-shell dehydrogenated anion (Ade − H)−. The additional anions (Ade − NH2)− and (Ade − 2H)− are also obtained in ADMP simulation. The results are well consistent with the previous DEA experimental results. Thus, the ADMP method is used to gain a more intuitive and better understanding of the necessary dissociation process in the DEA experiment.

Fragment Pose Prediction Using Non-Equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations

2019 ◽  
Author(s):  
Nathan M. Lim ◽  
Meghan Osato ◽  
Gregory L. Warren ◽  
David L. Mobley
Keyword(s):  
Crystal Structure ◽  
Molecular Dynamics ◽  
Monte Carlo ◽  
Ligand Binding ◽  
Md Simulations ◽  
Binding Mode ◽  
Protein Crystal ◽  
Pose Prediction ◽  
Binding Modes ◽  
Non Equilibrium

<div>Part of early stage drug discovery involves determining how molecules may bind to the target protein. Through understanding where and how molecules bind, chemists can begin to build ideas on how to design improvements to increase binding affinities. In this retrospective study, we compare how computational approaches like docking, molecular dynamics (MD) simulations, and a non-equilibrium candidate Monte Carlo (NCMC) based method (NCMC+MD) perform in predicting binding modes for a set of 12 fragment-like molecules which bind to soluble epoxide hydrolase. We evaluate each method's effectiveness in identifying the dominant binding mode and finding any additional binding modes (if any). Then, we compare our predicted binding modes to experimentally obtained X-ray crystal structures.</div><div>We dock each of the 12 small molecules into the apo-protein crystal structure and then run simulations up to 1 microsecond each. Small and fragment-like molecules likely have smaller energy barriers separating different binding modes by virtue of relatively fewer and weaker interactions relative to drug-like molecules, and thus likely undergo more rapid binding mode transitions. We expect, thus, to see more rapid transitions betweeen binding modes in our study. </div><div><br></div><div>Following this, we build Markov State Models (MSM) to define our stable ligand binding modes. We investigate if adequate sampling of ligand binding modes and transitions between them can occur at the microsecond timescale using traditional MD or a hybrid NCMC+MD simulation approach. Our findings suggest that even with small fragment-like molecules, we fail to sample all the crystallographic binding modes using microsecond MD simulations, but using NCMC+MD we have better success in sampling the crystal structure while obtaining the correct populations.</div>

MasterMSM: A Package for Constructing Master Equation Models of Molecular Dynamics

2019 ◽  
Author(s):  
David De Sancho ◽  
Anne Aguirre
Keyword(s):  
Molecular Dynamics ◽  
Master Equation ◽  
Md Simulations ◽  
Distinctive Features ◽  
Markov State Models ◽  
Software Packages ◽  
Long Time ◽  
State Models ◽  
Definition Of ◽  
Kinetics Of

<div>Markov state models (MSMs) have become one of the most important techniques for understanding biomolecular transitions from classical molecular dynamics (MD) simulations. MSMs provide a systematized way of accessing the long time kinetics of the system of interest from the short-timescale microscopic transitions observed in simulation trajectories. At the same time, they provide a consistent description of the equilibrium and dynamical properties of the system of interest, and they are ideally suited for comparisons against experiment. A few software packages exist for building MSMs, which have been widely adopted. Here we introduce MasterMSM, a new Python package that uses the master equation formulation of MSMs and provides a number of new algorithms for building and analyzing these models. We demonstrate some of the most distinctive features of the package, including the estimation of rates, definition of core-sets for transition based assignment of states, the estimation of committors and fluxes, and the sensitivity analysis of the emerging networks. The package is available at https://github.com/daviddesancho/MasterMSM.</div>

scholarly journals Mechanisms in Carbon Nanotube Growth: Modelling and Molecular Dynamics Simulations

2021 ◽  
Author(s):  
◽  
Dmitri Schebarchov
Keyword(s):  
Molecular Dynamics ◽  
Carbon Nanotube ◽  
Supported Catalysts ◽  
Critical Role ◽  
Chemical Vapour ◽  
Catalyst Particle ◽  
Md Simulations ◽  
Capillary Absorption ◽  
Supported Nickel Catalyst ◽  
Lift Off

<p>A selection of nanoscale processes is studied theoretically, with the aim of identifying themechanisms that could lead to selective carbon nanotube (CNT) growth. Only mechanisms relevant to catalytic chemical vapour deposition (CVD) are considered. The selected processes are analysed with classical molecular dynamics (MD) simulations and continuum modelling. The melting and pre-melting behaviour of supported nickel catalyst particles is investigated. Favourable epitaxy between a nanoparticle and the substrate is shown to significantly raise themelting point of the particle. It is also demonstrated that substrate binding can induce solid-solid transformations, whilst the epitaxy may even determine the orientation of individual crystal planes in supported catalysts. These findings suggest that the substrate crystal structure alone can potentially be used to manipulate the properties of catalyst particles and, hence, influence the structure of CNTs. The first attempt at modelling catalyst dewetting, a process where the catalyst unbinds from the inner walls of a nucleating nanotube, is presented. It is argued that understanding this process and gaining control over itmay lead to better selectivity in CNT growth. Two mutually exclusive dewetting mechanisms, namely cap lift-off and capillary withdrawal, are identified and then modelled as elastocapillary phenomena. The modelling yields an upper bound on the diameter of CNTs that can stem from a catalyst particle of a given size. It is also demonstrated that cap lift-off is sensitive to cap topology, suggesting that it may be possible to link catalyst characteristics to the structural properties of nucleating CNTs. However, a clear link to the chiral vector remains elusive. It is shown that particle size, as well as binding affinity, plays a critical role in capillary absorption and withdrawal of catalyst nanoparticles. This size dependence is explored in detail, revealing interesting ramifications to the statics and dynamics of capillary-driven flows at the nanoscale. The findings bear significant implications for our understanding of CNT growth from catalyst particles, whilst also suggesting new nanofluidic applications and methods for fabricating composite metal-CNT materials.</p>

Intramolecular vibrational redistribution in the non-radiative excited state decay of uracil in the gas phase: an ab initio molecular dynamics study

2015 ◽  
Vol 17 (17) ◽  
pp. 11615-11626 ◽  
Author(s):  
Philippe Carbonniere ◽  
Claude Pouchan ◽  
Roberto Improta
Keyword(s):  
Molecular Dynamics ◽  
Excited State ◽  
Ab Initio ◽  
Gas Phase ◽  
Ground State ◽  
Md Simulations ◽  
Ab Initio Molecular Dynamics ◽  
State Decay ◽  
State Recovery

MD simulations provide the first atomistic insights into the IVR processes of photoexcited uracil soon after ground state recovery.

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