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Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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Updated: Jun 5, 2025

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
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数据驱动的并发纳米结构优化基于条件生成对抗网络.

Arthur Baucour1, Myungjoon Kim1, Jonghwa Shin1

  • 1Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, South Korea.

Nanophotonics (Berlin, Germany)
|December 5, 2024
PubMed
概括
此摘要是机器生成的。

这项研究将条件生成对抗网络 (CGAN) 集成到光学纳米结构设计中,通过学习过程结构关系来弥合模拟和现实世界制造之间的差距,以提高性能.

关键词:
颜色过器 颜色过器制造宽容度 制造宽容度 制造宽容度生成性的对抗性网络.数字优化数字优化结构色彩 结构色彩

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科学领域:

  • 纳米光子学 纳米光子学
  • 计算材料科学科学 计算材料科学
  • 机器学习应用 机器学习应用

背景情况:

  • 代数值优化是设计光学纳米结构的标准.
  • 在模拟原始结构和实验测量变形配置文件之间存在性能差距.
  • 准确的模拟到制造映射对于可靠的纳米结构设计至关重要.

研究的目的:

  • 在光学纳米结构的优化循环中引入条件生成对抗网络 (CGAN).
  • 学习和建模制造过程参数与产生的纳米结构形状之间的关系.
  • 为了实现纳米结构的数据驱动设计,这些纳米结构可以解释现实世界的制造缺陷.

主要方法:

  • 条件生成对抗网络 (CGAN) 集成到代优化中.
  • 将优化从结构参数转移到工艺参数 (例如沉积率,回火时间).
  • 关于设计基于金属格子的颜色过器 (红色,绿色,蓝色) 的演示.

主要成果:

  • CGAN学习了复杂的非线性过程结构关系.
  • 生成的模拟配置文件与各种制造条件下的实验数据密切匹配.
  • 与原始结构的标准优化相比,基于CGAN的优化产生了更高的优点.

结论:

  • 这种数据驱动的方法准确地将制造条件映射到纳米结构设计中.
  • 该方法通过专注于制造精确的参数来加速纳米结构设计.
  • 最佳的过程参数自动确定,改善实验结果.