scholarly journals Optical spectrum, perceived color, refractive index, and non-adiabatic dynamics of the photochromic diarylethene CMTE

2014 ◽  
Vol 16 (28) ◽  
pp. 14531-14538 ◽  
Author(s):  
Christian Wiebeler ◽  
Christina A. Bader ◽  
Cedrik Meier ◽  
Stefan Schumacher
Keyword(s):  
Molecular Dynamics ◽  
Refractive Index ◽  
Optical Absorption ◽  
Ab Initio ◽  
Optical Spectrum ◽  
Reaction Dynamics ◽  
Adiabatic Dynamics ◽  
Perceived Color ◽  
Comprehensive Study

A comprehensive study of the photochromic diarylethene CMTE is presented, including optical absorption, perceived color, refractive index, and reaction dynamics with non-adiabatic ab initio molecular dynamics.

scholarly journals Atomistic non-adiabatic dynamics of the LH2 complex with a GPU-accelerated ab initio exciton model

2017 ◽  
Vol 19 (23) ◽  
pp. 14924-14936 ◽  
Author(s):  
Aaron Sisto ◽  
Clem Stross ◽  
Marc W. van der Kamp ◽  
Michael O’Connor ◽  
Simon McIntosh-Smith ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Molecular Dynamics Simulations ◽  
Nonadiabatic Dynamics ◽  
Exciton Model ◽  
Adiabatic Dynamics ◽  
Dynamics Simulations

We present GPU-accelerated ab initio molecular dynamics simulations of nonadiabatic dynamics in the LH2 complex in full atomistic detail.

Nonadiabatic dynamics of floppy hydrogen bonded complexes: the case of the ionized ammonia dimer

2016 ◽  
Vol 18 (30) ◽  
pp. 20422-20432 ◽  
Author(s):  
Jan Chalabala ◽  
Petr Slavíček
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Molecular Dynamics Simulations ◽  
Nonadiabatic Dynamics ◽  
Adiabatic Dynamics ◽  
Dynamics Simulations ◽  
Ammonia Dimer ◽  
Bonded Complexes ◽  
Hydrogen Bonded

Non-adiabatic dynamics of a floppy hydrogen bonded ammonia dimer was studied by ab initio molecular dynamics simulations.

Combustion Driven by Fragment-based Ab Initio Molecular Dynamics Simulation

2019 ◽  
Author(s):  
Liqun Cao ◽  
Jinzhe Zeng ◽  
Mingyuan Xu ◽  
Chih-Hao Chin ◽  
Tong Zhu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Large Scale ◽  
Methane Combustion ◽  
Combustion Method ◽  
Dynamics Simulation ◽  
Ab Initio Molecular Dynamics ◽  
Computational Time ◽  
Combustion Mechanism ◽  
Daily Lives

Combustion is a kind of important reaction that affects people's daily lives and the development of aerospace. Exploring the reaction mechanism contributes to the understanding of combustion and the more efficient use of fuels. Ab initio quantum mechanical (QM) calculation is precise but limited by its computational time for large-scale systems. In order to carry out reactive molecular dynamics (MD) simulation for combustion accurately and quickly, we develop the MFCC-combustion method in this study, which calculates the interaction between atoms using QM method at the level of MN15/6-31G(d). Each molecule in systems is treated as a fragment, and when the distance between any two atoms in different molecules is greater than 3.5 Å, a new fragment involved two molecules is produced in order to consider the two-body interaction. The deviations of MFCC-combustion from full system calculations are within a few kcal/mol, and the result clearly shows that the calculated energies of the different systems using MFCC-combustion are close to converging after the distance thresholds are larger than 3.5 Å for the two-body QM interactions. The methane combustion was studied with the MFCC-combustion method to explore the combustion mechanism of the methane-oxygen system.

Active Learning Accelerates Ab Initio Molecular Dynamics on Pericyclic Reactive Energy Surfaces

2020 ◽  
Author(s):  
Shi Jun Ang ◽  
Wujie Wang ◽  
Daniel Schwalbe-Koda ◽  
Simon Axelrod ◽  
Rafael Gomez-Bombarelli
Keyword(s):  
Molecular Dynamics ◽  
Potential Energy ◽  
Transition State ◽  
Potential Energy Surface ◽  
Ab Initio ◽  
Energy Surface ◽  
Computational Cost ◽  
Reactive Trajectories ◽  
Dynamics Simulations ◽  
Energy Surfaces

<div>Modeling dynamical effects in chemical reactions, such as post-transition state bifurcation, requires <i>ab initio</i> molecular dynamics simulations due to the breakdown of simpler static models like transition state theory. However, these simulations tend to be restricted to lower-accuracy electronic structure methods and scarce sampling because of their high computational cost. Here, we report the use of statistical learning to accelerate reactive molecular dynamics simulations by combining high-throughput ab initio calculations, graph-convolution interatomic potentials and active learning. This pipeline was demonstrated on an ambimodal trispericyclic reaction involving 8,8-dicyanoheptafulvene and 6,6-dimethylfulvene. With a dataset size of approximately</div><div>31,000 M062X/def2-SVP quantum mechanical calculations, the computational cost of exploring the reactive potential energy surface was reduced by an order of magnitude. Thousands of virtually costless picosecond-long reactive trajectories suggest that post-transition state bifurcation plays a minor role for the reaction in vacuum. Furthermore, a transfer-learning strategy effectively upgraded the potential energy surface to higher</div><div>levels of theory ((SMD-)M06-2X/def2-TZVPD in vacuum and three other solvents, as well as the more accurate DLPNO-DSD-PBEP86 D3BJ/def2-TZVPD) using about 10% additional calculations for each surface. Since the larger basis set and the dynamic correlation capture intramolecular non-covalent interactions more accurately, they uncover longer lifetimes for the charge-separated intermediate on the more accurate potential energy surfaces. The character of the intermediate switches from entropic to thermodynamic upon including implicit solvation effects, with lifetimes increasing with solvent polarity. Analysis of 2,000 reactive trajectories on the chloroform PES shows a qualitative agreement with the experimentally-reported periselectivity for this reaction. This overall approach is broadly applicable and opens a door to the study of dynamical effects in larger, previously-intractable reactive systems.</div>

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