人工智能和机器学习在材料科学和膜技术中的进展和应用:综合性审查
Simin Nazari1, Amira Abdelrasoul1,2
1Division of Biomedical Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK S7N 5A9, Canada.
Membranes
|December 24, 2025
概括
人工智能 (AI) 和机器学习 (ML) 加快了新膜材料的发现,超越了试错方法. 这些计算工具提高了膜设计,制造和性能,以实现可持续的工业应用.
科学领域:
- 膜科学与工程 膜科学与工程
- 材料科学 材料科学 材料科学
- 计算化学的计算化学
背景情况:
- 膜技术对于可持续发展至关重要,但由于依赖实证方法,材料的发现速度很慢.
- 人工智能 (AI) 和机器学习 (ML) 提供数据驱动的方法来加速膜科学领域的创新.
研究的目的:
- 在膜科学和材料开发中对AI和ML应用进行全面的审查.
- 突出AI/ML在克服传统实验方法的局限性方面的潜力.
主要方法:
- 审查 AI/ML 整合用于膜制造,性能预测,工艺建模,污染控制和材料设计的最新进展.
- 讨论基本的AI/ML概念及其与膜科学相关性的讨论.
主要成果:
- 人工智能和机器学习在加速膜制造,改进工艺模拟和增强材料表征方面显示出重大前景.
- 这些计算方法有效地处理复杂的数据集,导致与传统的实证方法相比更快的创新.
结论:
- 人工智能和机器学习为开发具有更高效率,选择性和可持续性的下一代膜提供了变革性的潜力.
- 需要进一步的研究来应对数据质量,模型解释性和特定领域知识整合方面的挑战.
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