Accelerate the development of energy storage materials and the role of autonomous synthesis laboratories

Advanced materials are the engine to drive high performing and sustainable technologies. Yet their development from design to synthesis and eventually scale-up span years, if not decades. In the field of electrochemical energy storage, all-solid-state batteries are emerging as an alternative solution that potentially offers enhanced safety and higher energy density than conventional Li-ion batteries which use liquid electrolytes. The advancement of all-solid-state batteries is dependent on the development of new materials – in this case, solid-state materials that act as electrochemically stable and fast ionic conductors. In this seminar, I will discuss a high-entropy compositional design strategy aimed at enhancing ion transport in oxides [1]. Our findings suggest that the local disorder in high-entropy materials induces overlapping site-energy distributions for charge-carrying ions, creating a percolating network of connected sites through which ions can move quickly. While the discovery of a material design strategy that generates promising materials candidates is exciting, the subsequent challenge lies in their synthesis and validation. In the second part of this seminar, I will discuss the development of an autonomous solid-state synthesis laboratory designed to accelerate the synthesis step [2]. This autonomous laboratory integrates several advanced tools: it designs synthesis recipes using knowledge text-mined from historical literature, executes experiments by robots and automated instruments, interprets data by machine learning models, and makes decisions for the subsequent experiments by active learning algorithms. In a recently published paper [2], this lab has demonstrated its capabilities in autonomous synthesis, but has also raised debate over the reliability of autonomous workflow in materials research. The autonomous labs, like many areas of scientific innovation in their early stage, are subjected to ongoing refinement. The precision in synthesis decision-making, for example, necessities a deeper understanding of synthesis mechanisms, which is essential for AI to provide reliable and impactful assistance [3].

[1] Zeng et al. High-entropy mechanism to boost ionic conductivity. Science 378,1320-1324 (2022).
[2] Szymanski, Zeng*, Ceder*, et al. An autonomous laboratory for the accelerated synthesis of novel materials. Nature 624, 86–91 (2023).
[3] Zeng et al. Selective formation of metastable polymorphs in solid-state synthesis. Science Advances 10, eadj5431 (2024).
 

Bio:
Yan Zeng is an Assistant Professor in the Department of Chemistry and Biochemistry at Florida State University, started in January 2024. Yan was a Staff Scientist and, before that, a postdoctoral researcher under Prof. Gerbrand Ceder at Lawrence Berkeley National Laboratory from 2020 to 2023. She led the build of an autonomous inorganic solid-state synthesis laboratory (the A-Lab) with a team at LBNL and UC Berkeley. Her interests include finding new materials for energy storage and exploring synthesis methods to make them. Yan obtained her Ph.D. degree in Materials Engineering from McGill University in 2020, where she developed Li-ion battery cathode materials using hydrothermal synthesis under the guidance of Prof. George P. Demopoulos. Her current research interests lie at the intersection of lab automation, energy storage materials, materials synthesis, and the extraction of critical metals.