Nonadiabatic Derivative Couplings Calculated Using Information of Potential Energy Surfaces without Wavefunctions: Ab Initio and Machine Learning Implementations.

Wen-Kai Chen, Sheng-Rui Wang, Xiang-Yang Liu, Wei-Hai Fang, Ganglong Cui

Abstract read

In one paragraph

Article in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Estimating Nonradiative Excited-State Lifetimes in Photoactive Semiconducting Nanostructures.The journal of physical chemistry. C, Nanomaterials and interfaces · 2024
Article

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Wen-Kai ChenHebei Key Laboratory of Inorganic Nano-Materials, College of Chemistry and Materials Science, Hebei Normal University, Shijiazhuang 050024, China.ORCID 0000-0001-6019-7069

Sheng-Rui WangKey Laboratory of Theoretical and Computational Photochemistry, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.

Xiang-Yang LiuCollege of Chemistry and Material Science, Sichuan Normal University, Chengdu 610068, China.

Wei-Hai FangKey Laboratory of Theoretical and Computational Photochemistry, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.

Ganglong CuiKey Laboratory of Theoretical and Computational Photochemistry, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.

Funding

Innovation Program for Quantum Science and Technology 2021ZD0303305National Key Research and Development Program of China 2021YFA1500703National Science Foundation of China 22233001Science and Technology Project of Hebei Education Department QN2023176Science Foundation of Hebei Normal University L2023B12

6 · The paper itself

Abstract

In this work, we implemented an approximate algorithm for calculating nonadiabatic coupling matrix elements (NACMEs) of a polyatomic system with ab initio methods and machine learning (ML) models. Utilizing this algorithm, one can calculate NACMEs using only the information of potential energy surfaces (PESs), i.e., energies, and gradients as well as Hessian matrix elements. We used a realistic system, namely CH

Indexed as

excited statesmachine learningnonadiabatic couplings

Identifiers

PMID37241962

DOI10.3390/molecules28104222

PMCPMC10223463

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.