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Modeling excited state charge carrier dynamics and recombination in extended systems, such as metal-organic frameworks (MOFs), covalent organic frameworks (COFs), and other hybrid organic-inorganic materials, by surface-hopping approaches is a challenging task due to the high computational cost. In this work, the steps of the simulations and the bottlenecks for such systems are analyzed. In particular, the bottlenecks related to computation of the nonadiabatic coupling coefficients (NACs) are considered. A simple, inexpensive, and portable scheme for computing scalar NACs employing a grid representation of the wave functions is presented and implemented in a Python code. It is tested for the simulation of the electron-hole nonradiative recombination in the MIL-125-NH model system. The proposed approach allows for an on-the-fly estimation of the NACs alongside the simulation of the molecular dynamics trajectory and enables a straightforward interface between the Python libraries for nonadiabatic molecular dynamics and the majority of the existing quantum chemical codes.
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http://dx.doi.org/10.1021/acs.jpca.1c05636 | DOI Listing |
Nanoscale
September 2025
School of Materials Science and Engineering, Beihang University, Beijing 100191, China.
The challenge of photocatalytic hydrogen production has motivated a targeted search for MXenes as a promising class of materials for this transformation because of their high mobility and high light absorption. High-throughput screening has been widely used to discover new materials, but the relatively high cost limits the chemical space for searching MXenes. We developed a deep-learning-enabled high-throughput screening approach that identified 14 stable candidates with suitable band alignment for water splitting from 23 857 MXenes.
View Article and Find Full Text PDFJ Chem Phys
September 2025
Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA.
Proton-coupled electron transfer (PCET) is pervasive throughout chemistry, biology, and physics. Over the last few decades, we have developed a general theoretical formulation for PCET that includes the quantum mechanical effects of the electrons and transferring protons, including hydrogen tunneling, as well as the reorganization of the environment and the donor-acceptor fluctuations. Analytical rate constants have been derived in various well-defined regimes.
View Article and Find Full Text PDFJ Chem Theory Comput
September 2025
Key Laboratory of Theoretical and Computational Photochemistry, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.
Accurate and efficient simulation of photoinduced dynamics in materials remains a significant challenge due to the computational cost of excited-state electronic structure calculations and the necessity to account for excitonic effects. In this work, we present a machine learning (ML)-accelerated approach to nonadiabatic molecular dynamics simulations that incorporates excitonic effects by predicting excited-state wave functions via configuration interaction coefficients and excitation energies using a graph neural network (GNN) architecture. The GNN model leverages molecular orbital information from ground-state calculations to construct input graphs, enabling efficient and accurate prediction of relevant excited-state wave functions and energies required for ab initio-based fewest-switches surface hopping simulations.
View Article and Find Full Text PDFJ Phys Chem Lett
August 2025
Collaboratory for Advanced Computing and Simulations, University of Southern California, Los Angeles, California 90089-0242, United States.
Photoinduced phase transition holds the key to realizing novel states of matter and transition pathways that do not exist otherwise. An example is ultrafast graphitization of diamond using femtosecond soft X-ray laser pulses, for which the structural transformation pathways have not been fully explored. Using first-principles nonadiabatic quantum molecular dynamics simulations, we found a progression from order-to-order (diamond-to-graphite) to order-to-disorder (diamond-to-amorphous) phase transitions at elevated laser intensities.
View Article and Find Full Text PDFJ Phys Chem Lett
September 2025
Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.
An efficient potential energy surface from cutting-edge technologies such as quantum computing and deep learning has been incorporated into mixed quantum-classical dynamics. However, the intrinsic noise embedded in those methodologies continues to be the sword of Damocles, as the simulation results of nonadiabatic dynamics are heavily dependent on the numerical stability of potential energy surfaces as well as nonadiabatic couplings. To address this concern, we perform surface hopping and Ehrenfest mean field dynamics simulations on the photoisomerization of -azobenzene and investigate the influence of additional noises on the collective results by introducing Gaussian random numbers into on-the-fly electronic structure calculations at each dynamic step.
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