Accelerating the Discovery of Energy Materials via Autonomous Labs
Shijing Sun a
a Materials Science and Metallurgy Department, University of Cambridge - UK, Quayside, 1, United Kingdom
Proceedings of MATSUS Spring 2026 Conference (MATSUSSpring26)
F4 Discovery and Engineering of Energy Nanomaterials: From Robotics to Digital Twin
Barcelona, Spain, 2026 March 23rd - 27th
Organizer: Milena Arciniegas
Invited Speaker, Shijing Sun, presentation 174
Publication date: 15th December 2025

The possibilities for discovering new materials are boundless, yet physical resources are limited and the demand for functional materials to address climate and environmental challenges is more urgent than ever. In recent years, artificial intelligence (AI) and robotics have emerged as a transformative approach to accelerate scientific discovery. By coupling automated experiments with AI-driven decision-making, self-driving laboratories promise to reduce the materials innovation cycle from years to months. In this talk,I will highlight three complementary approaches to building autonomous research platforms spanning organic synthesis, halide perovskites, and metal-organic frameworks. First, I will discuss the advantages and limitations of all-in-one liquid-handling systems for high-throughput exploration of synthesis conditions. Second, I will introduce low-cost, DIY robots built from open-source hardware to democratize access to laboratory automation and adapt to evolving research needs from ex situ to in situ measurements. Third, I will present modular thin-film deposition systems designed to empower scientific creativity through human-in-the-loop autonomy, exemplified by the optimization of solution-processed semiconductors. Together, these strategies demonstrate how automation and AI can augment human expertise, accelerating the synthesis and characterisation of diverse classes of advanced materials and opening new pathways toward next-generation energy technologies. I will conclude by discussing the open challenges of interfacing AI with real-world scientific experiments and the emerging opportunities the field presents, envisioning a future of seamless human-AI-robot collaboration for materials discovery. 

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