软分子机器和设备的理论建模视角:数据驱动方法与传统计算化学算法的融合
Costantino Zazza1, Nico Sanna1,2, Stefano Borocci1,3
1Department for Innovation in Biological, Agro-food and Forest systems, Università della Tuscia (DIBAF), L.go dell'Università, s.n.c., 01100, Viterbo, Italy.
ChemistryOpen
|July 10, 2025
概括
理论建模是设计复杂分子机器和设备的关键. 先进的计算方法,包括人工智能,正在为提高性能,彻底改变纳米技术和分子工程.
科学领域:
- 纳米技术纳米技术
- 合成化学 合成化学
- 分子工程分子工程分子工程
背景情况:
- 设计复杂的分子机器和设备是科学领域的前沿.
- 这些系统需要精确控制原子和电子相互作用.
- 理论建模对于预测分子行为和优化性能至关重要.
研究的目的:
- 突出理论建模在设计分子机器中的作用.
- 讨论在这个领域使用的先进计算方法.
- 探索人工智能和机器学习在分子设计中的整合.
主要方法:
- 密度函数理论 (DFT) 是一种密度函数理论.
- 分子中的原子量子理论 (QTAIM)
- 分子动力学 (MD) 模拟
- 量子力学/分子力学 (QM/MM) 的混合方法.
- 机器学习 (ML) 和人工智能 (AI)
主要成果:
- 计算方法提供了对分子稳定性和构造形状的洞察力.
- 理论方法可以实现跨学科的整合,以提高设备的性能.
- 人工智能和机器学习加速了分子架构的发现和改进.
结论:
- 理论建模对于推动纳米技术和分子工程不可或缺.
- 人工智能和机器学习的整合正在彻底改变软分子机器和设备的设计.
- 未来的分子设计将从数据驱动的计算方法中受益.
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