Research Acceleration in Self-Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery,Advanced Intelligent Systems

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Research Acceleration in Self-Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery
Advanced Intelligent Systems ( IF 6.8 ) Pub Date : 2022-12-23 , DOI: 10.1002/aisy.202200331
Fernando Delgado-Licona ₁ , Milad Abolhasani ₁

Affiliation

The urgency of finding solutions to global energy, sustainability, and healthcare challenges has motivated rethinking of the conventional chemistry and material science workflows. Self-driving labs, emerged through integration of disruptive physical and digital technologies, including robotics, additive manufacturing, reaction miniaturization, and artificial intelligence, have the potential to accelerate the pace of materials and molecular discovery by 10–100X. Using autonomous robotic experimentation workflows, self-driving labs enable access to a larger part of the chemical universe and reduce the time-to-solution through an iterative hypothesis formulation, intelligent experiment selection, and automated testing. By providing a data-centric abstraction to the accelerated discovery cycle, in this perspective article, the required hardware and software technological infrastructure to unlock the true potential of self-driving labs is discussed. In particular, process intensification as an accelerator mechanism for reaction modules of self-driving labs and digitalization strategies to further accelerate the discovery cycle in chemical and materials sciences are discussed.

中文翻译：

自动驾驶实验室的研究加速：加速材料和分子发现的技术路线图

寻找全球能源、可持续性和医疗保健挑战解决方案的紧迫性促使人们重新思考传统的化学和材料科学工作流程。通过整合颠覆性物理和数字技术（包括机器人技术、增材制造、反应微型化和人工智能）而出现的自动驾驶实验室有可能将材料和分子发现的速度加快 10-100 倍。使用自主机器人实验工作流程，自动驾驶实验室能够访问更大部分的化学宇宙，并通过迭代假设公式、智能实验选择和自动化测试缩短解决问题的时间。通过为加速发现周期提供以数据为中心的抽象，在这篇透视文章中，讨论了释放自动驾驶实验室真正潜力所需的硬件和软件技术基础设施。特别讨论了过程强化作为自动驾驶实验室反应模块的加速机制，以及进一步加速化学和材料科学发现周期的数字化策略。

更新日期：2022-12-23

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