Conversational LLM-Based Decision Support for Defect Classification in AFM Images

Atomic force microscopy (AFM) has emerged as a powerful tool for nanoscale imaging and quantitative characterization of organic (e.g., live cells, proteins, DNA, and lipid bilayers) and inorganic (e.g., silicon wafers and polymers) specimens. However, image artifacts in AFM height and peak force err...

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Bibliographic Details
Main Authors:	Angona Biswas, Jaydeep Rade, Nabila Masud, Md Hasibul Hasan Hasib, Aditya Balu, Juntao Zhang, Soumik Sarkar, Adarsh Krishnamurthy, Juan Ren, Anwesha Sarkar
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Series:	IEEE Open Journal of Instrumentation and Measurement
Subjects:	atomic force microscopy (AFM) conversational LLM image defect classification large language models (LLMs)
Online Access:	https://ieeexplore.ieee.org/document/11096088/
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Conversational LLM-Based Decision Support for Defect Classification in AFM Images

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