NIMS-OS: An automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science

TL;DR

NIMS-OS is a Python-based system that automates materials exploration by integrating AI techniques and robotic experiments in a closed loop, with real-time visualization and easy extensibility.

Contribution

The paper introduces NIMS-OS, a flexible, modular platform that combines AI and robotic experiments for autonomous materials discovery.

Findings

Successfully demonstrated automated electrolyte exploration.

Real-time visualization of optimization results.

System is extensible with new AI modules and robotic setups.

Abstract

NIMS-OS (NIMS Orchestration System) is a Python library created to realize a closed loop of robotic experiments and artificial intelligence (AI) without human intervention for automated materials exploration. It uses various combinations of modules to operate autonomously. Each module acts as an AI for materials exploration or a controller for a robotic experiments. As AI techniques, Bayesian optimization (PHYSBO), boundless objective-free exploration (BLOX), phase diagram construction (PDC), and random exploration (RE) methods can be used. Moreover, a system called NIMS automated robotic electrochemical experiments (NAREE) is available as a set of robotic experimental equipment. Visualization tools for the results are also included, which allows users to check the optimization results in real time. Newly created modules for AI and robotic experiments can be added easily to extend the functionality of the system. In addition, we developed a GUI application to control NIMS-OS.To demonstrate the operation of NIMS-OS, we consider an automated exploration for new electrolytes. NIMS-OS is available at https://github.com/nimsos-dev/nimsos.