Leveraging Large Language Models and Social Media for Automation in Scanning Probe Microscopy

TL;DR

This paper introduces an automated SPM system that uses large language models and social media integration to enable real-time, language-agnostic control, enhancing accessibility and efficiency in microscopic measurements.

Contribution

It presents a novel integration of large language models with social media for controlling scanning probe microscopy in real-time.

Findings

Real-time control of SPM via social media and LLMs

Enhanced accessibility and efficiency in microscopy operations

Progress towards self-driving laboratory systems

Abstract

We present the development of an automated scanning probe microscopy (SPM) measurement system using an advanced large-scale language model (LLM). This SPM system can receive instructions via social networking services (SNS), and the integration of SNS and LLMs enables real-time, language-agnostic control of SPM operations, thereby improving accessibility and efficiency. The integration of LLMs with AI systems with specialized functions brings the realization of self-driving labs closer.