scholarly journals Machine learning dielectric screening for the simulation of excited state properties of molecules and materials

2021 ◽  
Vol 12 (13) ◽  
pp. 4970-4980
Author(s):  
Sijia S. Dong ◽  
Marco Govoni ◽  
Giulia Galli
Keyword(s):  
Machine Learning ◽  
Optical Properties ◽  
Excited State ◽  
First Principles ◽  
Finite Temperature ◽  
Dielectric Response ◽  
Explicit Calculation ◽  
Complex Materials ◽  
Dielectric Screening

Machine learning can circumvent explicit calculation of dielectric response in first principles methods and accelerate simulations of optical properties of complex materials at finite temperature.

Nanosecond Photodynamics Simulations of a Cis-Trans Isomerization Are Enabled by Machine Learning

2020 ◽  
Author(s):  
Jingbai Li ◽  
Patrick Reiser ◽  
André Eberhard ◽  
Pascal Friederich ◽  
Steven Lopez
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Excited State ◽  
Adaptive Sampling ◽  
Computational Cost ◽  
Ground Truth ◽  
Absolute Error ◽  
Photochemical Reactions ◽  
Computational Techniques ◽  
Full Potential

<p>Photochemical reactions are being increasingly used to construct complex molecular architectures with mild and straightforward reaction conditions. Computational techniques are increasingly important to understand the reactivities and chemoselectivities of photochemical isomerization reactions because they offer molecular bonding information along the excited-state(s) of photodynamics. These photodynamics simulations are resource-intensive and are typically limited to 1–10 picoseconds and 1,000 trajectories due to high computational cost. Most organic photochemical reactions have excited-state lifetimes exceeding 1 picosecond, which places them outside possible computational studies. Westermeyr <i>et al.</i> demonstrated that a machine learning approach could significantly lengthen photodynamics simulation times for a model system, methylenimmonium cation (CH<sub>2</sub>NH<sub>2</sub><sup>+</sup>).</p><p>We have developed a Python-based code, Python Rapid Artificial Intelligence <i>Ab Initio</i> Molecular Dynamics (PyRAI<sup>2</sup>MD), to accomplish the unprecedented 10 ns <i>cis-trans</i> photodynamics of <i>trans</i>-hexafluoro-2-butene (CF<sub>3</sub>–CH=CH–CF<sub>3</sub>) in 3.5 days. The same simulation would take approximately 58 years with ground-truth multiconfigurational dynamics. We proposed an innovative scheme combining Wigner sampling, geometrical interpolations, and short-time quantum chemical trajectories to effectively sample the initial data, facilitating the adaptive sampling to generate an informative and data-efficient training set with 6,232 data points. Our neural networks achieved chemical accuracy (mean absolute error of 0.032 eV). Our 4,814 trajectories reproduced the S<sub>1</sub> half-life (60.5 fs), the photochemical product ratio (<i>trans</i>: <i>cis</i> = 2.3: 1), and autonomously discovered a pathway towards a carbene. The neural networks have also shown the capability of generalizing the full potential energy surface with chemically incomplete data (<i>trans</i> → <i>cis</i> but not <i>cis</i> → <i>trans</i> pathways) that may offer future automated photochemical reaction discoveries.</p>

First-principles study on the electronic and optical properties of the orthorhombic CsPbBr3 and CsPbI3 with Cmcm space group

2021 ◽  
Author(s):  
Xianhao Zhao ◽  
Tianyu Tang ◽  
Quan Xie ◽  
like gao ◽  
Limin Lu ◽  
...  
Keyword(s):  
Optical Properties ◽  
Solar Cells ◽  
Energy Conversion ◽  
Conversion Efficiency ◽  
First Principles ◽  
Energy Conversion Efficiency ◽  
Space Group ◽  
Absorbing Materials ◽  
Halide Perovskites ◽  
Lead Halide

The cesium lead halide perovskites are regarded as effective candidates for light-absorbing materials in solar cells, which have shown excellent performances in experiments such as promising energy conversion efficiency. In...

A first-principles study on the electronic and optical properties of a type-II C2N/g-ZnO van der Waals heterostructure

2021 ◽  
Vol 23 (6) ◽  
pp. 3963-3973
Author(s):  
Jianxun Song ◽  
Hua Zheng ◽  
Minxia Liu ◽  
Geng Zhang ◽  
Dongxiong Ling ◽  
...  
Keyword(s):  
Optical Properties ◽  
Dft Calculations ◽  
First Principles ◽  
Van Der Waals ◽  
Band Alignment ◽  
Type Ii ◽  
Electronic And Optical Properties ◽  
Direct Bandgap ◽  
Van Der Waals Heterostructure ◽  
Vdw Heterostructure

The structural, electronic and optical properties of a new vdW heterostructure, C2N/g-ZnO, with an intrinsic type-II band alignment and a direct bandgap of 0.89 eV at the Γ point are extensively studied by DFT calculations.

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