# Toward Full Autonomous Laboratory Instrumentation Control with Large Language Models

arXiv: https://arxiv.org/abs/2604.03286 · HTML: https://mlsanity.com/paper/2604.03286/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 25 references that are in the map.
- First posted on arXiv 25 Mar 2026.

## Builds on (most cited first, 3 of 3)

- [ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization](https://mlsanity.com/paper/2401.06949/) (2024)
- [Can ChatGPT be used to generate scientific hypotheses?](https://mlsanity.com/paper/2304.12208/) (2023)
- [1.5 million materials narratives generated by chatbots](https://mlsanity.com/paper/2308.13687/) (2023)

## Built on by (most cited first, 5 of 5)

- [QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding](https://mlsanity.com/paper/2604.25884/) (2026)
- [It's not the Language Model, it's the Tool: Deterministic Mediation for Scientific Workflows](https://mlsanity.com/paper/2605.13245/) (2026)
- [Onnes: A Physics-Grounded Multi-Agent LLM Simulator for Cryogenic Fault Diagnosis in Quantum Computing Infrastructure](https://mlsanity.com/paper/2607.05805/) (2026)
- [CausalVerify: End-to-End Verification of Causal Analyses by Language Models](https://mlsanity.com/paper/2609.07944/) (2026)
- [APEXA: Execution-Integrity Enforcement for Multi-Agent LLM Automation of Synchrotron Data Reduction](https://mlsanity.com/paper/2609.24165/) (2026)

## Abstract (arXiv)

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.