Rice University secures $19.9 million NSF award to build AI-powered materials laboratory

The four-year READINESS project will combine robotics, digital twins and remote laboratory access, alongside training for students, teachers and semiconductor workers Rice University’s READINESS project will use AI, robotics and digital twins to support electronic and quantum materials research Rice University has received a $19.9 million National Science Foundation award to lead a four-year US project that will use artificial intelligence and robotics to automate experiments involving electronic and quantum materials. The project, called Revolutionizing AI-Driven Autonomous Experimentation for Next-Generation Semiconductor Synthesis, or READINESS, will create a cloud-based research platform through which users can propose, simulate and conduct experiments remotely. Rice materials scientist Jun Lou will serve as principal investigator. SUNY Polytechnic Institute and the University of Texas at Austin are collaborating on the project, while the Astera Institute is providing philanthropic support for open science, reusable research methods and faster data sharing. The award funds the development of the laboratory rather than evidence from an established research service. Details have not been provided about when external researchers will gain access, how projects will be approved or how capacity will be allocated among users. “This project will give researchers access to capabilities that have traditionally been available only in a handful of laboratories,” says David Sholl, Executive Vice President for Research at Rice University. “By lowering those barriers, READINESS can accelerate discovery and expand who can participate in cutting-edge materials research.” AI system will learn from successful and failed experiments Materials synthesis can require researchers to repeatedly adjust variables including temperature, pressure, gas flow and chemical composition. Small changes can alter the resulting material’s structure and properties. READINESS will connect automated synthesis equipment, robotic systems and materials characterization tools with a digital twin, a virtual representation of the physical laboratory. Researchers will be able to simulate experiments digitally before approved projects are carried out using laboratory equipment. An AI agent will analyze results, recommend further tests and refine future recommendations using information from both successful and unsuccessful experiments. The system is intended to operate within safety limits and consult researchers when it encounters uncertainty. Rice positions that human oversight as a core part of the laboratory design. “Responsible AI should complement researchers’ capabilities rather than replace their judgment,” says Luay Nakhleh, the William and Stephanie Sick Dean of Rice’s George R. Brown School of Engineering and Computing. “READINESS embodies this principle by combining automated systems with transparency, safeguards and human oversight at critical decision points.” Remote platform targets institutions without specialist equipment The laboratory is intended to widen access for emerging research institutions, startups and small to midsize companies that may lack the equipment and specialist staff required to produce advanced electronic and quantum materials. Through the cloud-based interface, users will be able to submit experiments, test them in the digital twin and conduct approved work remotely. Data gathered across each stage will be used to connect processing conditions with a material’s structure and performance. “Our goal is to create a laboratory that researchers from across the country can use to produce advanced electronic and quantum materials on demand,” explains Lou, the Karl F. Hasselmann Professor of Materials Science and Nanoengineering. “By integrating robotics, AI and digital twins, we aim to learn from every experiment and shorten the pathway from scientific discovery to practical technology.” The laboratory will be based in Rice’s Ralph S. O’Connor Building for Engineering and Science, using existing shared facilities and additional space assigned to the initiative. Partner sites will contribute equipment, technical expertise and workforce development programs. Initial research will focus on two-dimensional materials, oxide semiconductors and diamond thin films. The university says these materials have potential applications in faster electronics, lower-power computing, quantum devices and other emerging technologies. Training extends from K-12 outreach to professional credentials Alongside its research infrastructure, READINESS will support graduate research, undergraduate experience, teacher training, K-12 outreach and professional education. Students will receive practical experience across materials science, robotics, data management and AI. SUNY Polytechnic Institute will help develop short courses and stackable credentials for workers in semiconductor manufacturing, laboratory automation and related areas. The University of Texas at Austin will contribute expertise in digital twins, autonomous experimentation and AI training. Several Rice organizations and departments are also supporting the work, including the Ken Kennedy Institute, Advanced Materials Institute, AI and Machine Learning Initiative, Engineering Initiative for Energy Transition and Sustainability, Department of Computer Science and Department of Materials Science and Nanoengineering. READINESS is one of 20 projects selected for the NSF’s Programmable Cloud Laboratories Test Bed initiative. The wider initiative forms part of a $380 million investment in a national network, with up to $20 million available in matching funds.