在化工化学的不确定性量化.
Tom Frömbgen1, Elizaveta Surzhikova2, Jürgen Dölz3
1Mulliken Center for Theoretical Chemistry, Clausius-Institute for Physical and Theoretical Chemistry, University of Bonn, Beringstraße 4, 53115 Bonn, Germany.
Chemical reviews
|March 4, 2026
概括
不确定性量化 (UQ) 对于in silico化学变得越来越重要. 本综述建立了一个共同的语言,并调查UQ方法,以提高计算化学预测的可靠性.
科学领域:
- 计算化学的计算化学
- 数据科学数据科学数据科学
背景情况:
- 全球计算能力在化学方面取得了进步,使得性能和过程预测成为可能.
- 来自量子化学,分子动力学和机器学习的丰富数据需要强大的错误和不确定性评估.
- 不确定性量化 (UQ) 提供了数学框架来解决计算化学中的准确性,精度和可靠性.
研究的目的:
- 在化学的背景下,为UQ建立一个共同的语言.
- 为UQ引入关键的数学形式主义.
- 调查UQ在各种in silico化学领域的应用.
主要方法:
- 在计算化学中对不确定性量化的文献综述.
- 解释与UQ相关的数学框架.
- 在化工学不同领域的UQ应用的分类.
主要成果:
- 介绍了UQ在化学中的统一视角.
- 详细介绍了量化不确定性的关键数学方法.
- 提供了当前在计算化学中的UQ应用的全面概述.
结论:
- UQ对于提高in silico化学预测的可靠性至关重要.
- 对UQ的标准化语言和方法将加速其采用.
- 整合UQ为化学现象提供了更深入的见解,并改善了研究中的决策.
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