全球集体嵌入式图形神经网络,用于从晶体结构中直接预测光谱
Nguyen Tuan Hung1,2, Ryotaro Okabe2,3, Abhijatmedhi Chotrattanapituk2,4
1Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, Sendai, 980-8578, Japan.
一个新的机器学习模型,GNNOpt,使用图形神经网络准确预测固体的光学特性. 这一突破能够有效地发现用于太阳能电池和量子技术的先进材料.
科学领域:
- 固态物理 固态物理
- 材料科学是一种材料科学.
- 计算化学是一种计算化学.
背景情况:
- 在太阳能电池板和传感器等应用中,光学性能至关重要.
- 这些属性的第一原理计算在计算上昂贵且复杂.
- 机器学习显示出有希望的结果,但缺乏有效的方法来从晶体结构中预测光学属性.
研究的目的:
- 介绍GNNOpt,用于预测光学光谱的等价图神经网络.
- 通过有限的数据集实现高质量的光学属性预测.
- 促进光伏和量子材料的选.
主要方法:
- 开发了GNNOpt,一个具有普遍嵌入的等价图形神经网络.
- 利用克拉默斯-克罗尼格关系来预测各种光学属性.
- 在944种材料的数据集上训练模型.
- 通过第一原则计算验证的预测.
主要成果:
- GNNOpt实现了光学属性的高质量预测,包括吸收,介电函数,折射率和反射率.
- 该模型与未见材料的第一原则计算表现出了很好的一致性.
- 成功选了光伏材料,并确定了潜在的量子材料,如SiO.
结论:
- GNNOpt提供了一种高效和准确的方法来预测晶体结构的光学特性.
- 该模型加速了用于各种技术应用的新材料的发现.
- 突出了图形神经网络在材料科学和凝聚物质物理学中的潜力.
更多相关视频
07:24Hyperspectral Imaging as a Tool to Study Optical Anisotropy in Lanthanide-Based Molecular Single Crystals
Published on: April 14, 2020
07:11ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
Published on: August 19, 2021
相关概念视频
UV–Vis Spectroscopy: Woodward–Fieser Rules
Crystal Field Theory - Octahedral Complexes
To explain the observed behavior of transition metal complexes (such as colors), a model involving electrostatic interactions between the electrons from the ligands and the electrons in the unhybridized d orbitals of the central metal atom has been developed. This electrostatic model is crystal field theory (CFT). It helps to understand, interpret, and predict the colors, magnetic behavior, and some structures of coordination compounds of transition metals.
CFT focuses on...
Ultraviolet and Visible (UV–Vis) Spectroscopy: Overview
UV–Vis Spectroscopy: Molecular Electronic Transitions
Crystal Field Theory - Tetrahedral and Square Planar Complexes
Crystal field theory (CFT) is applicable to molecules in geometries other than octahedral. In octahedral complexes, the lobes of the dx2−y2 and dz2 orbitals point directly at the ligands. For tetrahedral complexes, the d orbitals remain in place, but with only four ligands located between the axes. None of the orbitals points directly at the tetrahedral ligands. However, the dx2−y2 and dz2 orbitals (along the Cartesian axes) overlap with the ligands less than the dxy,...
Predicting Molecular Geometry
