Sub-bandgap charge harvesting and energy up-conversion in metal halide perovskites: ab initio quantum dynamics
Metal halide perovskites (MHPs) exhibit unusual properties and complex dynamics. By
combining ab initio time-dependent density functional theory, nonadiabatic molecular …
combining ab initio time-dependent density functional theory, nonadiabatic molecular …
Photocatalytic activity of dual defect modified graphitic carbon nitride is robust to tautomerism: machine learning assisted ab initio quantum dynamics
Two-dimensional graphitic carbon nitride (GCN) is a popular metal-free polymer for
sustainable energy applications due to its unique structure and semiconductor properties …
sustainable energy applications due to its unique structure and semiconductor properties …
Advancing nonadiabatic molecular dynamics simulations for solids: Achieving supreme accuracy and efficiency with machine learning
C Zhang, Y Zhong, ZG Tao, X Qing, H Shang… - arxiv preprint arxiv …, 2024 - arxiv.org
Non-adiabatic molecular dynamics (NAMD) simulations have become an indispensable tool
for investigating excited-state dynamics in solids. In this work, we propose a general …
for investigating excited-state dynamics in solids. In this work, we propose a general …
Estimating Nonradiative Excited-State Lifetimes in Photoactive Semiconducting Nanostructures
The time evolution of the exciton generated by light adsorption in a photocatalyst is an
important feature that can be approached from full nonadiabatic molecular dynamics …
important feature that can be approached from full nonadiabatic molecular dynamics …
Nonadiabatic Dynamics in Two-Dimensional Perovskites Assisted by Machine Learned Force Fields
An exploration of the “on-the-fly” nonadiabatic couplings (NACs) for nonradiative relaxation
and recombination of excited states in 2D Dion–Jacobson (DJ) lead halide perovskites …
and recombination of excited states in 2D Dion–Jacobson (DJ) lead halide perovskites …
Time-reversible bridges of data with machine learning
L Winkler - arxiv preprint arxiv:2412.13665, 2024 - arxiv.org
The analysis of dynamical systems is a fundamental tool in the natural sciences and
engineering. It is used to understand the evolution of systems as large as entire galaxies …
engineering. It is used to understand the evolution of systems as large as entire galaxies …
Machine learning accelerated nonadiabatic dynamics simulations of materials with excitonic effects
SR Wang, Q Fang, XY Liu, WH Fang… - The Journal of Chemical …, 2025 - pubs.aip.org
This study presents an efficient methodology for simulating nonadiabatic dynamics of
complex materials with excitonic effects by integrating machine learning (ML) models with …
complex materials with excitonic effects by integrating machine learning (ML) models with …
Construction of Intelligent Question-Answering System to Improve Knowledge Management Service from the Perspective of Education Informatization
Q Han - Journal of Information & Knowledge Management, 2024 - World Scientific
With the continuous reform of education informatization, modern information technology
gradually became a key technology in education. An intelligent question-answering system …
gradually became a key technology in education. An intelligent question-answering system …