安全和可持续的设计与ML/AI:一个变革性的方法推进纳米技术的进步
1Hellenic Military Academy, Vari, Greece.
Beilstein journal of nanotechnology
|January 22, 2026
概括
机器学习和人工智能正在推进纳米技术的安全和可持续设计 (SSbD) 概念. 这些技术允许预测建模和风险评估,确保更安全,更可持续的纳米材料开发.
科学领域:
- 纳米技术纳米技术
- 材料科学 材料科学 材料科学
- 环境科学 环境科学
背景情况:
- 纳米技术在医学,能源和环境领域提供了变革性的应用.
- 纳米材料的创新带来了复杂的安全和可持续性挑战.
- 设计时安全和可持续 (SSbD) 概念在开发初期整合了安全和可持续性.
研究的目的:
- 突出机器学习 (ML) 和人工智能 (AI) 在推进纳米技术SSbD中的作用.
- 探索ML/AI如何增强预测毒理学,材料信息学和生命周期分析.
- 讨论整合ML/AI驱动的SSbD框架的挑战和机会.
主要方法:
- 审查当前文献和SSbD的ML/AI应用的进展.
- 专注于预测建模,风险评估和纳米材料的计算选.
- 在SSbD框架内探索数字双胞胎和生命周期分析.
主要成果:
- 通过提供安全和可持续性的预测能力,ML和AI显著提高了SSbD.
- 这些技术使积极的风险减轻和高效的材料选成为可能.
- 数字双胞胎和高级分析对于全面的生命周期评估至关重要.
结论:
- 机器学习和人工智能对于SSbD的发展,对于更安全和可持续的纳米技术至关重要.
- 集成ML/AI驱动的SSbD框架对于监管和工业采用至关重要.
- 需要继续进行研究,以应对这一领域的挑战和抓住机遇.
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