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Owl-AuraID 1.0: An Intelligent System for Autonomous Scientific Instrumentation and Scientific Data Analysis

Han Deng, Anqi Zou, Hanling Zhang, Ben Fei, Chengyu Zhang, Haobo Wang, Xinru Guo, Zhenyu Li, Xuzhu Wang, Peng Yang, Fujian Zhang, Weiyu Guo, Xiaohong Shao, Zhaoyang Liu, Shixiang Tang, Zhihui Wang, Wanli Ouyang

Abstract

Scientific discovery increasingly depends on high-throughput characterization, yet automation is hindered by proprietary GUIs and the limited generalizability of existing API-based systems. We present Owl-AuraID, a software-hardware collaborative embodied agent system that adopts a GUI-native paradigm to operate instruments through the same interfaces as human experts. Its skill-centric framework integrates Type-1 (GUI operation) and Type-2 (data analysis) skills into end-to-end workflows, connecting physical sample handling with scientific interpretation. Owl-AuraID demonstrates broad coverage across ten categories of precision instruments and diverse workflows, including multimodal spectral analysis, microscopic imaging, and crystallographic analysis, supporting modalities such as FTIR, NMR, AFM, and TGA. Overall, Owl-AuraID provides a practical, extensible foundation for autonomous laboratories and illustrates a path toward evolving laboratory intelligence through reusable operational and analytical skills. The code are available at https://github.com/OpenOwlab/AuraID.

Owl-AuraID 1.0: An Intelligent System for Autonomous Scientific Instrumentation and Scientific Data Analysis

Abstract

Scientific discovery increasingly depends on high-throughput characterization, yet automation is hindered by proprietary GUIs and the limited generalizability of existing API-based systems. We present Owl-AuraID, a software-hardware collaborative embodied agent system that adopts a GUI-native paradigm to operate instruments through the same interfaces as human experts. Its skill-centric framework integrates Type-1 (GUI operation) and Type-2 (data analysis) skills into end-to-end workflows, connecting physical sample handling with scientific interpretation. Owl-AuraID demonstrates broad coverage across ten categories of precision instruments and diverse workflows, including multimodal spectral analysis, microscopic imaging, and crystallographic analysis, supporting modalities such as FTIR, NMR, AFM, and TGA. Overall, Owl-AuraID provides a practical, extensible foundation for autonomous laboratories and illustrates a path toward evolving laboratory intelligence through reusable operational and analytical skills. The code are available at https://github.com/OpenOwlab/AuraID.

Paper Structure

This paper contains 38 sections, 6 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. AI for Scientific Discovery and Self-Driving Laboratories
  4. LLM Agents for Scientific Experimentation
  5. GUI Agents for Real-World Software Operation
  6. Why GUI-Native Interaction Matters for Scientific Characterization
  7. Method
  8. Design Motivation
  9. AuraID as a Scientific Agent Runtime
  10. From Coding Agent to Scientific Agent
  11. Conversation-First Interaction over a Tool-Using Core
  12. Extensibility through Importable Skills
  13. Skill-Centric Capability Accumulation
  14. Why Skills Are Needed
  15. Two Types of Skills
  16. ...and 23 more sections

Figures (6)

  • Figure 1: Overview of the Owl-AuraID 1.0 architecture for autonomous scientific characterization. User command is translated and executed by an embodied multi-agent system managing a suite of precision characterization instruments (UV-vis, PL, SEM, Micro-CT). The platform achieves scientific data acquisition and autonomous multi-modal analytics (multiscale imaging, spectral analysis, and properties quantification), establishing an efficient loop for rapid characterization-analysis cycles.
  • Figure 2: The platform integrates fluorescence emission spectroscopy with UV-Vis absorption spectroscopy, SEM, EDS, and Micro-CT for multi-modal characterization.
  • Figure 3: AuraID workflow for spectral characterization of UV-vis and PL.
  • Figure 4: AuraID workflow for microscopic imaging characterization of SEM, Micro-CT, and EDS.
  • Figure 5: AuraID workflow for spectral analysis.
  • ...and 1 more figures