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MATTERIX：迈向机器人辅助化学实验室自动化数字孪生

MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation

University of Toronto（多伦多大学）；Acceleration Consortium（加速联盟）；Vector Institute（向量研究所）；University of Liverpool（利物浦大学）；University of Salento（萨勒诺大学）；NVIDIA Canadian Institute for Advanced Research（NVIDIA加拿大高级研究机构）；Georgia Institute of Technology（佐治亚理工学院）
Kourosh Darvish, Arjun Sohal, Abhijoy Mandal, Hatem Fakhruldeen, Nikola Radulov, Zhengxue Zhou, Satheeshkumar Veeramani, Joshua Choi, Sijie Han, Brayden Zhang, … 展开作者

Kourosh Darvish, Arjun Sohal, Abhijoy Mandal, Hatem Fakhruldeen, Nikola Radulov, Zhengxue Zhou, Satheeshkumar Veeramani, Joshua Choi, Sijie Han, Brayden Zhang, Jeeyeoun Chae, Alex Wright, Yijie Wang, Hossein Darvish, Yuchi Zhao, Gary Tom, Han Hao, Miroslav Bogdanovic, Gabriella Pizzuto, Andrew I. Cooper, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg

备注：
Darvish, K., Sohal, A., Mandal, A. et al. MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation. Nat Comput Sci (2025)
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AI总结：

MATTERIX通过多尺度仿真和模块化引擎，实现机器人辅助化学实验室的数字孪生，加速工作流程开发并减少现实实验依赖。

摘要：

加速材料发现对于解决全球挑战至关重要。然而，开发新的实验室工作流程严重依赖于现实世界的实验试验，这会阻碍可扩展性，因为需要大量的物理制造和测试迭代。本文提出了MATTERIX，一个多尺度、图形处理器加速的机器人仿真框架，旨在创建高保真的化学实验室数字孪生，从而加速工作流程开发。该多尺度数字孪生模拟机器人物理操作、粉末和液体动力学、设备功能、热传递和基本化学反应动力学。这通过整合真实的物理模拟和逼真的渲染与一个模块化的图形处理器加速语义引擎实现，该引擎建模逻辑状态和连续行为，以模拟不同抽象层次的化学工作流程。MATTERIX通过开源资产库和接口简化了数字孪生环境的创建，同时通过分层计划定义和模块化技能库实现灵活的工作流程设计。我们的方法在机器人化学设置中展示了仿真到现实的转移，减少了对昂贵现实世界实验的依赖，并允许在硅中测试假设的自动化工作流程。项目网站可在https://accelerationconsortium.github.io/Matterix/上找到。

英文摘要：

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/ .

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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