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Non-equilibrium in the Cell01:16

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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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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
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Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
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Intrinsically disordered proteins are a group of proteins that do not fold into specific three-dimensional structures. Their structural flexibility allows them to complement ordered proteins to perform functions that are inaccessible to rigid structures. They are more common in eukaryotes than prokaryotes and may either be exclusively intrinsically disordered or hybrid proteins, consisting of a mix of ordered and disordered regions. The absence of a rigid structure in these proteins can be...
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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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Author Spotlight: Accelerating Discovery in Microporous Material Chemistry
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材料发现,开发和优化的人工智能

Benediktus Madika1, Aditi Saha1, Chaeyul Kang1

  • 1Department of Materials Science and Engineering, KAIST, Daejeon 34141, Korea.

ACS nano
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PubMed
概括
此摘要是机器生成的。

人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 正在改变材料科学,加速发现,开发和优化. 这些人工智能方法使先进的材料设计和分析成为可能,克服了未来创新的当前挑战.

关键词:
自主实验的自主实验.计算材料的设计设计.深度学习是一种深度学习.生成型模型是一种生成型模型.高通量选的高通量选机器学习是机器学习.材料属性预测 材料属性预测材料信息学 材料信息学基于物理知识的人工智能

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科学领域:

  • 材料科学 材料科学 材料科学
  • 计算科学 计算科学
  • 数据科学数据科学数据科学

背景情况:

  • 人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 是现代科学研究中越来越重要的工具.
  • 材料科学通过整合计算方法和数据分析取得了重大进展.

研究的目的:

  • 审查人工智能,ML和DL对材料科学的变革性影响,涵盖发现,开发和优化.
  • 引入与材料信息学相关的基本AI/ML概念和先进的DL模型.
  • 讨论人工智能驱动材料科学的挑战和未来方向.

主要方法:

  • 在材料发现 (结构生成,属性预测,高通量选,计算设计) 中对AI/ML/DL应用的审查.
  • 在材料开发 (特征化,自主实验) 和优化 (设计,流程) 中探索AI.
  • 介绍监督,无监督,半监督和强化学习,以及RNN,CNN,GNN,生成模型和变压器.

主要成果:

  • 人工智能方法已经彻底改变了材料的发现和开发,提高了设计和流程.
  • 材料信息学主题包括结构-属性关系,描述符,QSPR和数据管理策略等.
  • 目前面临的挑战包括数据质量,模型可解释性和数据共享标准化.

结论:

  • 未来的工作重点是提高AI的稳定性,整合因果推理和基于物理的AI,并使用多式模式模型.
  • 量子计算与人工智能的整合承诺更快,更准确的结果.
  • 伦理框架对于负责任的人类-人工智能合作至关重要,解决偏见,透明度和问责制.