This two-part review examines how automation has contributed to different aspects of discovery in the chemical sciences. In this second part, we reflect on a selection of exemplary studies. It is increasingly important to articulate what the role of automation and computation has been in the scientific process and how that has or has not accelerated discovery. One can argue that even the best automated systems have yet to ``discover'' despite being incredibly useful as laboratory assistants. We must carefully consider how they have been and can be applied to future problems of chemical discovery in order to effectively design and interact with future autonomous platforms. The majority of this article defines a large set of open research directions, including improving our ability to work with complex data, build empirical models, automate both physical and computational experiments for validation, select experiments, and evaluate whether we are making progress toward the ultimate goal of autonomous discovery. Addressing these practical and methodological challenges will greatly advance the extent to which autonomous systems can make meaningful discoveries.

中文翻译：

---

化学科学中的自主发现第二部分：展望

这篇由两部分组成的评论探讨了自动化如何对化学科学中发现的不同方面做出贡献。在第二部分中，我们反思了一些示例性研究。阐明自动化和计算在科学过程中的作用以及它们如何加速或未加速发现变得越来越重要。人们可能会争辩说，即使是最好的自动化系统也尚未“发现”，尽管它作为实验室助手非常有用。我们必须仔细考虑它们是如何以及如何应用于未来化学发现的问题的，以便有效地设计未来的自主平台并与之交互。本文的大部分内容定义了大量开放的研究方向，包括提高我们处理复杂数据的能力、建立经验模型、自动化物理和计算实验以进行验证、选择实验并评估我们是否正在朝着自主发现的最终目标取得进展。解决这些实际和方法上的挑战将大大提高自主系统做出有意义发现的程度。