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MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation
Kourosh Darvish1,2,3, Arjun Sohal4, Abhijoy Mandal4
1University of Toronto, Toronto, Ontario, Canada. kourosh.darvish@utoronto.ca.
Nature Computational Science
|December 31, 2025
Summary
MATTERIX accelerates materials discovery by creating digital twins of chemistry labs. This robotic simulation framework reduces physical experiments, enabling faster workflow development and testing of automated processes in silico.
Area of Science:
- Materials Science
- Robotics
- Computational Chemistry
Background:
- Accelerated materials discovery is crucial for global challenges.
- Developing new lab workflows is hindered by extensive physical experimentation.
- Current methods require numerous make-and-test iterations, limiting scalability.
Purpose of the Study:
- To present MATTERIX, a novel simulation framework for accelerating laboratory workflow development.
- To create high-fidelity digital twins of chemistry laboratories.
- To reduce the reliance on physical experimentation in materials discovery.
Main Methods:
- Developed a multiscale, GPU-accelerated robotic simulation framework (MATTERIX).
- Integrated realistic physics simulation and photorealistic rendering with a semantics engine.
- Simulated robotic manipulation, fluid dynamics, device functions, heat transfer, and reaction kinetics.
- Enabled flexible workflow design via hierarchical planning and a modular skill library.
Main Results:
- Demonstrated high-fidelity digital twins of chemistry laboratories.
- Achieved sim-to-real transfer in robotic chemistry setups.
- Reduced the need for costly and time-consuming physical experiments.
- Enabled in silico testing of hypothetical automated workflows.
Conclusions:
- MATTERIX significantly accelerates materials discovery and laboratory automation.
- The digital twin approach offers a scalable and efficient alternative to physical experimentation.
- This framework facilitates the development and validation of novel automated chemistry workflows.
