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Updated: May 6, 2026

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates
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预测本顿石中的放射性核素的分布系数和有效扩散系数:多输出神经网络模拟和扩散实验研究

Jiaxing Feng1, Xuewen Gao1, Ke Xu1

  • 1Huzhou Key Laboratory of Environmental Functional Materials and Pollution Control, Huzhou University, Huzhou 313000, PR China.

Journal of hazardous materials
|March 9, 2025
PubMed
概括

一个新的AI模型准确地预测了放射性废物存储库中的放射性核素扩散 (Kd) 和吸附 (De). 该框架通过使用生成和实验数据提供可靠的预测来增强安全评估.

关键词:
托尼特 (Bentonite) 是一种托尼特.数据增强数据增强机器学习 机器学习放射性核化物 放射性核化物通过-扩散方法通过-扩散方法.

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