Publications

1. 

   Probing Non-Equilibrium Grain Boundary Dynamics with XPCS and Domain-Adaptive Machine Learning

   Mouyang Cheng†,*, Bowen Yu†, Chu-Liang Fu, Nina Andrejevic, Matthias T. Agne, Riley Hanus, Qiwei Wan, Nathan C. Drucker, Thanh Nguyen, Andrei Fluerasu, Lutz Wiegart, Xiaoqian M Chen, Daniel Pajerowski, Yongqiang Cheng, Joshua J Turner, G. Jeffrey Snyder, and Mingda Li*

   † Equal contribution. * Corresponding author.

   In review · arXiv May 2026

   Pairing X-ray photon correlation spectroscopy (XPCS) with semi-supervised domain adaptation to quantify slow, non-equilibrium grain-boundary dynamics in nanocrystalline silicon

2. 

   A Foundation Model for Non-Destructive Defect Identification from Vibrational Spectra

   Mouyang Cheng†,*, Chu-Liang Fu†, Bowen Yu†, Eunbi Rha, Abhijatmedhi Chotrattanapituk, Douglas L. Abernathy, Yongqiang Cheng, and Mingda Li*

   † Equal contribution. * Corresponding author.

   Matter · Published Mar 2026 · arXiv May 2025

   A non-destructive defect identification probe to predict the chemical identity and concentration of substitutional point defects directly from vibrational spectra

3. 

   Enhancing Materials Discovery with Valence Constrained Design in Generative Modeling

   Mouyang Cheng†,*, Weiliang Luo†, Hao Tang†, Bowen Yu†, Yongqiang Cheng, Weiwei Xie, Ju Li, Heather J. Kulik, and Mingda Li*

   † Equal contribution. * Corresponding author.

   Nature Computational Science · Published Mar 2026 · arXiv Jul 2025

   Integrating chemical valence constraints into the generative materials pipeline

1. 

   Can LLMs extract scientific consensus? A case study in high-temperature superconductivity

   Mouyang Cheng†,*, Wenhao He†, Zhuotao Jin†, Bowen Yu, Ju Li, Boris Kozinsky, Yao Wang, Pavel Volkov, Liangzi Deng, Ching-Wu Chu, Xiao-Gang Wen, and Mingda Li*

   † Equal contribution. * Corresponding author.

   In review · arXiv May 2026

   Robust, interpretable scientific consensus and its evolution from large, contested literatures can be extracted through LLM, by structuring ~18,000 high-temperature-superconductivity (HTS) papers into a knowledge graph of mechanisms, materials, evidence, and citations

2. 

   Probing Non-Equilibrium Grain Boundary Dynamics with XPCS and Domain-Adaptive Machine Learning

   Mouyang Cheng†,*, Bowen Yu†, Chu-Liang Fu, Nina Andrejevic, Matthias T. Agne, Riley Hanus, Qiwei Wan, Nathan C. Drucker, Thanh Nguyen, Andrei Fluerasu, Lutz Wiegart, Xiaoqian M Chen, Daniel Pajerowski, Yongqiang Cheng, Joshua J Turner, G. Jeffrey Snyder, and Mingda Li*

   † Equal contribution. * Corresponding author.

   In review · arXiv May 2026

   Pairing X-ray photon correlation spectroscopy (XPCS) with semi-supervised domain adaptation to quantify slow, non-equilibrium grain-boundary dynamics in nanocrystalline silicon

3. 

   Reinforcement learning-guided optimization of critical current in high-temperature superconductors

   Mouyang Cheng†,*, Qiwei Wan†, Bowen Yu†, Eunbi Rha, Michael J. Landry, and Mingda Li*

   † Equal contribution. * Corresponding author.

   In review · arXiv Oct 2025

   Combining reinforcement learning (RL) with time-dependent Ginzburg-Landau (TDGL) simulations to autonomously optimize defect configurations for high-temperature superconductors

4. 

   Enhancing Materials Discovery with Valence Constrained Design in Generative Modeling

   Mouyang Cheng†,*, Weiliang Luo†, Hao Tang†, Bowen Yu†, Yongqiang Cheng, Weiwei Xie, Ju Li, Heather J. Kulik, and Mingda Li*

   † Equal contribution. * Corresponding author.

   Nature Computational Science · Published Mar 2026 · arXiv Jul 2025

   Integrating chemical valence constraints into the generative materials pipeline

5. 

   A Foundation Model for Non-Destructive Defect Identification from Vibrational Spectra

   Mouyang Cheng†,*, Chu-Liang Fu†, Bowen Yu†, Eunbi Rha, Abhijatmedhi Chotrattanapituk, Douglas L. Abernathy, Yongqiang Cheng, and Mingda Li*

   † Equal contribution. * Corresponding author.

   Matter · Published Mar 2026 · arXiv May 2025

   A non-destructive defect identification probe to predict the chemical identity and concentration of substitutional point defects directly from vibrational spectra