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通过整合人工智能和机器学习来推进聚合物科学和能源存储解决方案:一种变革性的方法
1Department of Chemistry, Zonguldak Bülent Ecevit University, 67100 Zonguldak, Türkiye.
Polymers
|December 31, 2025
概括
人工智能 (AI) 和机器学习 (ML) 正在彻底改变用于储能的聚合物科学. 这些技术加速了先进聚合物的发现和设计,克服了当前的局限性.
科学领域:
- 聚合物科学 聚合物科学
- 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:
- 聚合物对于储能至关重要,因为它们的导电性,灵活性和稳定性.
- 人工智能 (AI) 和机器学习 (ML) 的整合改变了聚合物设计和发现.
- 目前的方法面临着先进材料的速度,成本和创新的挑战.
研究的目的:
- 审查AI和ML对聚合物科学对储能应用的影响.
- 为突出聚合物设计,表征和材料发现方面的进步.
- 确定AI/ML驱动的聚合物研究中的挑战和未来方向.
主要方法:
- 在聚合物科学中对AI/ML应用的文献综述.
- 对材料设计和属性预测的AI/ML技术的分析.
- 探索储能材料开发中的案例研究.
主要成果:
- 人工智能/ML加速了材料发现,并使得聚合物属性的预测建模成为可能.
- 这些技术有效地处理复杂的数据集,并优化多项财产的权衡.
- 在高通量选和揭示结构与财产关系方面取得了显著进展.
结论:
- 人工智能和机器学习为开发下一代聚合物用于储能提供了强大的工具.
- 解决数据的局限性,可解释性和合成可行性是未来的主要挑战.
- 进一步整合物理原理和可持续设计对于未来的进步至关重要.
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