Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Predicting Molecular Geometry02:27

Predicting Molecular Geometry

45.2K
VSEPR Theory for Determination of Electron Pair Geometries
45.2K
Molecular Models02:00

Molecular Models

43.5K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
43.5K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Reactive Machine Learning Interatomic Potentials for Chemistry and Materials Science.

Chemical reviews·2026
Same author

Optimizing cross-domain transfer for universal machine learning interatomic potentials.

Nature communications·2026
Same author

Self-assembly networks of azobenzene with hydrogen and halogen bonds on Au(111).

The Journal of chemical physics·2026
Same author

BaGe<sub>2</sub>P<sub>2</sub> and BaGe<sub>2</sub>As<sub>2</sub> pnictides as promising ferroelectric semiconductors for thin film solar cell.

Physical chemistry chemical physics : PCCP·2025
Same author

Nonmelting Disordering Facilitated by Electron Delocalization.

ACS nano·2025
Same author

Data-Efficient Multifidelity Training for High-Fidelity Machine Learning Interatomic Potentials.

Journal of the American Chemical Society·2024
Same journal

Tuning Piezoelectricity and Pyroelectricity in Poly(vinylidene fluoride) through Ionic Liquid Anion-Size Directed Polymorph and Interface Engineering.

ACS applied materials & interfaces·2026
Same journal

Adsorption-Induced Ferroelectric Symmetry Breaking in Two-Dimensional CuInP<sub>2</sub>S<sub>6</sub>.

ACS applied materials & interfaces·2026
Same journal

Nanocomplexes Integrated into a Polymeric Bilayer Film Enhance Buccal Permeation of a GLP-1 Peptide Analogue.

ACS applied materials & interfaces·2026
Same journal

Correction to "Multienzyme Active Nanozyme for Efficient Sepsis Therapy through Modulating Immune and Inflammation Inhibition".

ACS applied materials & interfaces·2026
Same journal

A Programmable Perfusion Platform with Temperature Monitoring Achieves Multiscale Cryopreservation.

ACS applied materials & interfaces·2026
Same journal

Oral Delivery of Mesenchymal Stem Cell-Derived Extracellular Vesicles To Treat Intestinal Inflammation.

ACS applied materials & interfaces·2026
查看所有相关文章

相关实验视频

Updated: Jan 16, 2026

Contrast-Matching Detergent in Small-Angle Neutron Scattering Experiments for Membrane Protein Structural Analysis and Ab Initio Modeling
10:27

Contrast-Matching Detergent in Small-Angle Neutron Scattering Experiments for Membrane Protein Structural Analysis and Ab Initio Modeling

Published on: October 21, 2018

13.0K

在无形GeSe中揭示缺陷图案,使用机器学习的原子间潜力.

Minseok Moon1, Seungwoo Hwang1, Jaesun Kim1

  • 1Department of Materials Science and Engineering and Research Institute of Advanced Materials, Seoul National University, Seoul 08826, Korea.

ACS applied materials & interfaces
|October 1, 2025
PubMed
概括
此摘要是机器生成的。

机器学习潜能准确地模拟无形GeSe,揭示了对Ovonic Threshold Switching (OTS) 存储器设备至关重要的两个缺陷类型. 这些与特定原子结构相关的缺陷解释了非易失性记忆中的切换行为.

关键词:
没有形态的GeSeSe.密度函数理论密度函数理论电子结构 电子结构机器学习 原子间潜力 原子间潜力中间间隙缺陷的缺陷转换 Ovonic 的值值.

更多相关视频

Theoretical Calculation and Experimental Verification for Dislocation Reduction in Germanium Epitaxial Layers with Semicylindrical Voids on Silicon
06:57

Theoretical Calculation and Experimental Verification for Dislocation Reduction in Germanium Epitaxial Layers with Semicylindrical Voids on Silicon

Published on: July 17, 2020

2.6K
Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
05:56

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

1.7K

相关实验视频

Last Updated: Jan 16, 2026

Contrast-Matching Detergent in Small-Angle Neutron Scattering Experiments for Membrane Protein Structural Analysis and Ab Initio Modeling
10:27

Contrast-Matching Detergent in Small-Angle Neutron Scattering Experiments for Membrane Protein Structural Analysis and Ab Initio Modeling

Published on: October 21, 2018

13.0K
Theoretical Calculation and Experimental Verification for Dislocation Reduction in Germanium Epitaxial Layers with Semicylindrical Voids on Silicon
06:57

Theoretical Calculation and Experimental Verification for Dislocation Reduction in Germanium Epitaxial Layers with Semicylindrical Voids on Silicon

Published on: July 17, 2020

2.6K
Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
05:56

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

1.7K

科学领域:

  • 材料科学 材料科学 材料科学
  • 计算材料科学科学 计算材料科学
  • 固态物理 固态物理

背景情况:

  • 卵子值切换 (OTS) 选择器是非易失性内存的关键组件.
  • 它们的非线性电特性和极性依赖的值电压是至关重要的.
  • 驱动OTS的缺陷状态的原子尺度起源仍然不太清楚.

研究的目的:

  • 系统地研究无形GeSe中的缺陷状态.
  • 了解OTS行为在原子尺度上的起源.
  • 为了将电子缺陷水平与特定的结构特征相关联.

主要方法:

  • 利用了机器学习原子间潜力 (MLIPs) 加速的分子动力学模拟.
  • 基准测试了各种MLIP架构,包括基于描述符和基于图形神经网络 (GNN) 的潜能.
  • 采用了优化的GNN模型来分析20个独立的无形GeSe结构.

主要成果:

  • 确定了高阶相互作用 (≥4体) 和中距离秩序对于准确的无形GeSe建模至关重要.
  • GNN架构有效地捕捉这些复杂的交互,防止虚假缺陷.
  • 发现了两个不同的缺陷模式:对齐的Ge链 (导电带缺陷) 和过度协调的Ge链 (价值带缺陷).
  • 与结合角度对齐和皮尔尔斯扭曲相关的电子缺陷水平.

结论:

  • 基于GNN的优化MLIP提供了无形GeSe的准确模拟.
  • 确定了两种特定的缺陷类型及其在无形GeSe中的结构起源.
  • 这些发现为了解缺陷驱动的OTS现象提供了理论基础.