[2604.03286] Toward Full Autonomous Laboratory Instrumentation Control with Large Language Models

[2604.03286] Toward Full Autonomous Laboratory Instrumentation Control with Large Language Models

arXiv - AI 3 min read

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Abstract page for arXiv paper 2604.03286: Toward Full Autonomous Laboratory Instrumentation Control with Large Language Models

Computer Science > Artificial Intelligence arXiv:2604.03286 (cs) [Submitted on 25 Mar 2026] Title:Toward Full Autonomous Laboratory Instrumentation Control with Large Language Models Authors:Yong Xie, Kexin He, Andres Castellanos-Gomez View a PDF of the paper titled Toward Full Autonomous Laboratory Instrumentation Control with Large Language Models, by Yong Xie and 2 other authors View PDF Abstract:The control of complex laboratory instrumentation often requires significant programming expertise, creating a barrier for researchers lacking computational skills. This work explores the potential of large language models (LLMs), such as ChatGPT, and LLM-based artificial intelligence (AI) agents to enable efficient programming and automation of scientific equipment. Through a case study involving the implementation of a setup that can be used as a single-pixel camera or a scanning photocurrent microscope, we demonstrate how ChatGPT can facilitate the creation of custom scripts for instrumentation control, significantly reducing the technical barrier for experimental customization. Building on this capability, we further illustrate how LLM-assisted tools can be extended into autonomous AI agents capable of independently operating laboratory instruments and iteratively refining control strategies. This approach underscores the transformative role of LLM-based tools and AI agents in democratizing laboratory automation and accelerating scientific progress. Comments: Subjects: Arti...

Originally published on April 07, 2026. Curated by AI News.

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