Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)

Abstract

Discoveries of novel electrolyte–electrode combinations require comprehensive structure–property–interface correlations. Herein, we present autonomous millimeter scale high-throughput battery research system (Auto-MISCHBARES) operated with an asynchronous web-based orchestration framework that integrates modular research instrumentation designed for autonomous electrochemical experimentation. The platform allows researchers to define a range of experiments with granular parameter control, start the process, and receive a live visualization of measurements through a web-based user interface. This paper presents a proof of concept for cathode electrolyte interphase (CEI) formation in lithium-ion batteries (LiBs) at various potentials, all controlled through Auto-MISCHBARES and correlating its high-throughput electrochemistry results with X-ray photoelectron spectroscopy (XPS) characterization. We believe quality control, complex data analysis, and management to be the missing puzzle pieces toward more complex workflow automation. Auto-MISCHBARES integrates automatic quality control for both hardware and software using AI enablers to ensure high reliability through an on-the-fly fidelity assessment of each experiment. In the presented case study, voltammetry measurements are handled through a modular platform capable of performing fully automated analysis, while data lineage is provided through relational data storage in adherence with Findable, Accessible, Interoperable, and Reusable (FAIR) guidelines, all in real-time. Thus, Auto-MISCHBARES represents a point of contact between the orchestration of automated instrumentation, quality control, real-time data analysis, and management, enabling reproducible and versatile workflows for the discovery of new materials, especially for batteries. We demonstrate this integrated workflow for reliable charging/discharging protocols.