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  • Perspective
  • Open Access

Designing and Utilizing Material Acceleration Platforms: Need for Workforce Development

Carolin M. Sutter-Fella1,* and Shijing Sun2,3,†

  • *Contact author: csutterfella@lbl.gov
  • †Contact author: shijing@uw.edu
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PRX Energy 5, 011001 – Published 20 January, 2026

DOI: https://doi.org/10.1103/8c7b-3g6c

Abstract

In the quest to accelerate scientific discovery, the materials science field is rapidly moving toward the implementation of robotics and artificial intelligence driven workflows. Our recent summer school “Future Labs: Robotic Synthesis Coupled with Machine Learning for Energy Materials” provided learning opportunities for students, researchers, and educators in the materials science community. We describe this experience and provide our perspective on which new directions could be pursued to enable the future workforce to acquire cross-disciplinary skills.

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Popular Summary

This work describes how to train tomorrow’s materials scientists to work with robotic “self-driving” labs and artificial intelligence (AI), using a summer school as a testbed. While many articles explain how materials acceleration platforms (MAPs) speed up discovery and material optimization, far fewer ask what skills students actually need to design, operate, and critically evaluate these systems. Here, researchers and educators brought together participants from undergraduates to faculty to gain hands-on experience with robots that make halide perovskite films, tools for structuring and analyzing experimental data, and machine-learning methods that help plan new experiments. The perspective distills lessons about which concepts participants found hardest—such as orchestrating multistep robotic workflows and working with analysis code—and which skills improved. It argues that future curricula should treat MAP-related competencies (automation, data, and AI literacy) as core elements of material scientist training, and it outlines how short intensive programs like this summer school can evolve into more systematic courses and shared training hubs for the broader community.

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PRX Energy 5, 011001– Published 20 January, 2026
  • Received 2 October 2025
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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