MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation
🤖 AI Summary
This work proposes the first multi-scale digital twin system for chemical laboratories that integrates physical operations, continuous processes, and logical states. By leveraging GPU-accelerated multiphysics simulation, photorealistic rendering, a modular semantic engine, and hierarchical task planning, the system enables cross-level virtual design and testing—from abstract workflows to concrete robotic actions. It supports sim-to-real transfer, substantially reducing reliance on costly physical experiments. The framework facilitates efficient in silico validation of hypothetical automated protocols, thereby accelerating both materials discovery and the development of laboratory automation.
Application Category
📝 Abstract
Accelerated materials discovery is critical for addressing global challenges. However, developing new laboratory workflows relies heavily on real-world experimental trials, and this can hinder scalability because of the need for numerous physical make-and-test iterations. Here we present MATTERIX, a multiscale, graphics processing unit-accelerated robotic simulation framework designed to create high-fidelity digital twins of chemistry laboratories, thus accelerating workflow development. This multiscale digital twin simulates robotic physical manipulation, powder and liquid dynamics, device functionalities, heat transfer and basic chemical reaction kinetics. This is enabled by integrating realistic physics simulation and photorealistic rendering with a modular graphics processing unit-accelerated semantics engine, which models logical states and continuous behaviors to simulate chemistry workflows across different levels of abstraction. MATTERIX streamlines the creation of digital twin environments through open-source asset libraries and interfaces, while enabling flexible workflow design via hierarchical plan definition and a modular skill library that incorporates learning-based methods. Our approach demonstrates sim-to-real transfer in robotic chemistry setups, reducing reliance on costly real-world experiments and enabling the testing of hypothetical automated workflows in silico. MATTERIX, a multiscale graphics processing unit-accelerated framework for high-fidelity digital twins and workflows of chemistry laboratories, is presented, simulating robot and device operation, fluids and powders, and processes such as heat transfer and chemical kinetics.
Problem
Research questions and friction points this paper is trying to address.
materials discovery
laboratory automation
digital twin
workflow development
robotic chemistry
Innovation
Methods, ideas, or system contributions that make the work stand out.
digital twin
robotic simulation
multiscale modeling
GPU-accelerated semantics
sim-to-real transfer
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