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相关概念视频

Crystal Growth: Principles of Crystallization01:25

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Crystallization is a phase transformation process in which crystals are precipitated from a supersaturated solution or formed from other sources. During crystallization, atoms or molecules arrange themselves into a well-defined, rigid crystal lattice to minimize energy.
Initiating crystallization involves manipulating the concentration of the solute and the temperature of the solution. Since crystal growth occurs when the ratio of concentration and solubility of the solute in the solvent...
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相关实验视频

Updated: Jun 12, 2025

Growing Protein Crystals with Distinct Dimensions Using Automated Crystallization Coupled with In Situ Dynamic Light Scattering
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使用无代深度生成模型进行可扩展的晶体结构放松,具有不确定性量化.

Ziduo Yang1,2,3, Yi-Ming Zhao1, Xian Wang4

  • 1Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore.

Nature communications
|September 17, 2024
PubMed
概括

深度生成模型DeepRelax可以在没有代的情况下快速预测平衡水晶结构,从而加速材料发现. 这种人工智能驱动的方法可以实现新型材料的高通量虚拟选.

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科学领域:

  • 计算分子和材料科学计算分子和材料科学
  • 科学领域的人工智能
  • 发现材料的发现.

背景情况:

  • 确定平衡结构对于计算材料科学中准确的属性计算至关重要.
  • 传统的方法与新发现的复杂晶体结构的规模作斗争.
  • 现有的计算方法中的代过程限制了大规模选的可扩展性.

研究的目的:

  • 介绍DeepRelax,这是一个新的深度生成模型,用于快速放松晶体结构.
  • 解决材料科学传统计算方法的可扩展性挑战.
  • 允许对大型数据集的平衡结构进行快速准确的预测.

主要方法:

  • 开发了DeepRelax,一个深度生成模型学习平衡结构分布.
  • 从未放松的结构中实现放松结构的直接预测,绕过代过程.
  • 综合不确定性量化以提高模型可靠性.

主要成果:

  • DeepRelax实现了每个结构的毫秒级放松时间.
  • 在五个不同的材料数据库中 (氧化物,材料项目,2D材料,范德瓦尔斯晶体,有缺陷的晶体) 证明了高精度和效率.
  • 与密度函数理论计算对比的验证结果.

结论:

  • DeepRelax显著加速了材料科学中的计算工作流程.
  • 为材料发现提供强大,可靠和可扩展的机器学习解决方案.
  • 推动人工智能在科学研究和开发中的应用.