发表机构
State Key Laboratory of Physical Chemistry of Solid Surfaces; College of Chemistry; Xiamen University; School of Physics, Anhui University（固体表面物理化学国家重点实验室; 化学学院; 厦门大学; 安徽大学物理学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该文综述了截至2026年8月计算化学AI智能体的发展现状，指出其正从辅助任务向自主科研迈进，通用智能体或取代专用系统，引发领域未来走向的困惑。
AI 中文摘要
我们正见证计算化学模拟智能体系统的爆炸式增长：从2024年的6个增至2025年的12个，截至2026年8月8日，本综述中调查的当前数量已接近50个。这些智能体系统的能力正从协助执行部分计算任务，转向自主设计和执行计算机模拟实验、分析，甚至撰写手稿。最终目标是实现完全自主的AI科学家，即整个计算化学工作均由机器通过机器完成，无需人类监督。尽管目前尚未达到该目标，所有已报道的系统当前仍需人类参与其中，但这一趋势十分明确。甚至，通用智能体正日益将构建计算化学专用智能体系统的过程商品化，最终可能完全取代对专用智能体的需求，因为添加新能力将变得如同要求AI为你完成一样简单。其数量的爆炸式增长以及除开发者自身外采用率极低的情况均指向这一方向，本综述最后探讨了这留给我们需要做的事情。智能体系统给计算化学带来的颠覆速度和规模，让我们许多人对该领域的未来以及我们作为已确立的专家、教师和学生应投入精力的方向感到困惑，而我们尚无答案。
英文摘要
We are witnessing an explosion of agentic systems for computational chemistry: from four in 2024 to seventeen in 2025 and over sixty now, surveyed here. What is delegated to these systems is shifting from single calculations to whole in silico experiments and even manuscript writing. The ultimate destination is a fully autonomous AI scientist, where the entirety of computational chemistry is performed on a machine by a machine, without human supervision. Our survey shows that these systems are turning into vetted chemistry skills on general-purpose coding agents, and that they must be evaluated not only on their final answers but also on whether their calculations actually support these answers. The role of the human computational chemist is shifting from performing calculations to directing and supervising them, and the field should invest in the judgement that makes the supervision reliable: we propose a reporting standard, an evaluation reproducing published studies, a controlled comparison with general-purpose coding agents, and how to teach.
