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Updated: Jan 28, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
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弥合微观动力学和宏观命运:一种分子动力学-机器学习方法,用于预测PFAS在土壤和沉积物中的固体-液体分布.

Letian Zhang1,2, Chaozhong Tan1,2, Zhouyun Xie1,2

  • 1College of Environmental Science and Engineering, Hunan University, Changsha 410082, P.R.china.

Environmental science & technology
|January 26, 2026
PubMed
概括

一个新的框架通过整合分子动力学和机器学习来提高对 perfluoroalkyl 和 polyfluoroalkyl 物质 (PFAS) 环境流动性的预测. 这种方法提高了对这些持久污染物的建模准确度.

关键词:
在PFAS中,我们可以使用PFAS.机器学习 (ML) 是指机器学习.分子动力学模拟 (MD) 模型固体 - 液体分区系数 (logKd)堆叠模型的堆叠模型

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