| 刘小平,刘耀虎,郑企雨,朱相丽.化学通报,2023,86(6):748-754. |
| 人工智能化学：变革研究范式,加速物质发现 |
| AI for Chemistry: Transforming the paradigm of research, accelerating chemical discovery |
| 投稿时间：2022-12-31 修订日期：2023-01-17 |
| DOI： |
| 中文关键词: 人工智能 机器学习 深度学习 化学 |
| 英文关键词:Artificial intelligence, Machine learning, Deep learning, Chemistry |
| 基金项目:国家自然科学基金项目(T2241001)资助 |
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| 中文摘要: |
| 化学科学领域的复杂性和海量数据为人工智能应用提供了契机。人工智能、机器学习、深度学习从海量数据中识别新的化合物,建立新的模型,提出新的理论,正在改变化学物质的发现、转化和功能研究范式,促进重大问题的解决。本文综述了近年来国际上人工智能在化学研究中的重要进展,分析了人工智能化学的主要发展态势。人工智能通过助力化学海量数据挖掘、实现化学实验室智能化和自动化、增强计算化学解决实际问题的能力,推动化学跨越式发展。 |
| 英文摘要: |
| The complexities and massive data in the field of chemical science provide opportunities for major breakthroughs of AI for chemistry. Artificial intelligence, machine learning, and deep learning are identifying new compounds from massive data, building new models, and proposing new theories, which are changing the research paradigm of chemical discovery, transformation and function. This paper reviews the important, latest progress in AI for chemistry in recent years, and analyzes its new trends. Artificial intelligence is promoting the development of chemical research, which is reflected in: assisting chemical massive data mining, realizing the intelligence and automation of chemical laboratories, and empowering computational chemistry. |
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