QuPAINT: Physics-Aware Multimodal Reasoning for Quantum Material Characterization

2026-09-10

AI Summary

为解决2D量子材料表征问题，提出QuPAINT框架，通过生成合成图像和物理信息注意力机制来提高材料层厚识别的准确性。

Abstract

Characterizing two-dimensional (2D) quantum materials by optical microscopy requires localizing exfoliated flakes and determining their layer thickness from subtle optical contrast and interference color to select suitable flakes for device fabrication. However, models face synthetic-to-real domain shifts and variation across materials, substrates, laboratories, and imaging conditions. We present QuPAINT, a physics-aware multimodal framework for transferable quantum flake characterization. The Synthetic Materials Framework (Synthia) generates diverse synthetic microscopy images while preserving layer-dependent optical behavior. Using these images, we construct QMat-Instruct, a multimodal instruction dataset with image-specific reasoning traces generated from verified annotations and constrained to observable optical cues. QuPAINT integrates these signals through Physics-Informed Attention (PIA), which injects substrate-relative optical priors into the visual representation to support grounded multimodal reasoning. For evaluation, we introduce QF-Bench, to our knowledge, the largest real-world benchmark for this problem, spanning diverse microscopy and substrate conditions. Using its verified annotations, we study counting, visual grounding, reasoning quality, confidence calibration, and transfer to an unseen material. QuPAINT-8B substantially outperforms prior methods and establishes state-of-the-art performance for both general and monolayer flake detection. Additional experiments show that image-grounded supervision improves strict spatial grounding and confidence calibration while preserving robust general flake detection on the unseen material.

Problem

• quantum materials
• optical microscopy
• domain shifts
• material characterization
• layer thickness

Innovation

• Physics-Aware Multimodal Reasoning
• Synthetic Materials Framework (Synthia)
• Physics-Informed Attention (PIA)
• QMat-Instruct
• QF-Bench