Year: 2026
Type: preprint
Abstract: While modern Large Language Models (LLMs) and agentic artificial intelligence (AI) have demonstrated transformative capabilities in digital domains, the realization of embodied AI capable of real-world scientific discovery remains a difficult frontier. The advancements are hindered by the inherent complexity of integrating high-level reasoning, multimodal information processing and real-time physical execution. Here we introduce Qumus, the first AI quantum materials experimentalist. Physically embodied within a robotic mini-laboratory, Qumus is an intelligent, multimodal, and multi-agent system designed for the creation and nano-processing of atomically thin two-dimensional (2D) materials and stacked van der Waals (vdW) structures. Qumus autonomously navigates the full scientific cycle, from hypothesis generation and protocol planning to multi-step experimental execution, result analysis and reporting, acting as an experimentalist. Markedly, the system has achieved, for the first time, the AI-creation of graphene, as well as the first AI-fabrication of complex nanodevices including atomically thin field-effect transistors via vdW stacking. Qumus excels at these tasks by demonstrating autonomous error correction and closed-loop experimentation. Our results establish a generalizable framework for self-improving embodied AI systems that learn directly from the quantum world, opening a pathway toward accelerated discovery in quantum materials, electronics and beyond.
Source: arXiv (Cornell University)
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: green
Funders: National Science Foundation, U.S. Department of Defense, Gordon and Betty Moore Foundation, Princeton University, Ministry of Education, Culture, Sports, Science and Technology, Materials Research Science and Engineering Center, Harvard University, National Defense Science and Engineering Graduate, Multidisciplinary University Research Initiative, Division of Materials Research, Core Research for Evolutional Science and Technology, Air Force Office of Scientific Research, Army Research Office
Awards: QuSeC-TAQS: Nanoscale Covariance Magnetometry with Diamond Quantum Sensors, G1746067696, G1877134453, G2174132073, G2696751721, A Novel Far-infrared Optical Spectroscopy And Nanoscale Microscopy Platform To Study Two-dimensional Quantum Materials, G3715997057, G4091144171, Visualizing Novel Electronic Orders in Bilayer Graphene Systems, G5232617493, G6536552022, Princeton Center for Complex Materials, G708600390, G8187799158, G9000842863
OpenAlex ID: W7161682443