用虚拟实验室加速材料研发,减少真实实验次数。
MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation
- 构建多尺度物理仿真系统,模拟机器人操作与化学反应过程。
- 支持从逻辑状态到连续行为的跨层次流程建模,实现高保真数字孪生。
- 开源工具链助力自动化实验设计,适合科研与工业界快速试错。
加速材料发现对应对全球挑战至关重要。然而,新实验流程的开发高度依赖真实世界中的试错,导致可扩展性受限。本文提出 MATTERIX,一个基于 GPU 加速的多尺度机器人仿真框架,用于创建高保真度的化学实验室数字孪生体,从而加速流程开发。该数字孪生体可模拟机器人物理操作、粉末与液体动力学、设备功能、热传递及基础化学反应动力学。通过集成真实物理仿真、逼真渲染与模块化 GPU 加速语义引擎,实现对不同抽象层级化学流程的逻辑状态与连续行为建模。MATTERIX 通过开源资产库和接口简化数字孪生环境搭建,并借助分层计划定义与模块化技能库(包含学习型方法)实现灵活工作流设计。本方法在机器人化学场景中验证了从仿真到现实的迁移能力,显著降低对昂贵真实实验的依赖,支持在虚拟环境中测试假设性自动化流程。项目官网:https://accelerationconsortium.github.io/Matterix/
原文摘要 · Abstract (English)
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. The project website is available at https://accelerationconsortium.github.io/Matterix/ .
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