Publications

• Y. Ye, J. Ren, S. Wang, Y. Wan, I. Razzak, T. Xie, and W. Zhang, “Construction of Functional Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model,” arXiv preprint arXiv:2404.03080, 2024.
• Y. Wan, A. Ajith, Y. Liu, K. Lu, C. Grazian, B. Hoex, W. Zhang, C. Kit, T. Xie, and I. Foster, “SciQAG: A Framework for Auto-Generated Scientific Question Answering Dataset with Fine-grained Evaluation,” Nature Communication, manuscripts under review, 2024.
• T. Xie, Y. Wan, W. Huang, Y. Zhou, Y. Liu, Q. Linghu, S. Wang, C. Kit, C. Grazian, B. Hoex, and I. Razzak, “Large Language Models as Master Key: Unlocking the Secrets of Materials Science with GPT,” arXiv preprint arXiv:2304.02213, 2023.
• T. Xie, Y. Wan, W. Huang, Z. Yin, Y. Liu, S. Wang, Q. Linghu, C. Kit, C. Grazian, B. Hoex, and I. Razzak, “Darwin series: Domain-specific large language models for natural science,” arXiv preprint arXiv:2308.13565, 2023.
• S. Wang, T. Xie, R. Liang, Y. Zhang, F. J. Ma, D. Payne, G. Scardera, and B. Hoex, "An artificial-intelligence-assisted investigation on the potential of black silicon nanotextures for silicon solar cells," ACS Applied Nano Materials, vol. 5, no. 8, pp. 11636-11647, 2022.
• T. Xie, Y. Wan, H. Wang, I. Østrøm, S. Wang, M. He, R. Deng, X. Wu, C. Grazian, B. Hoex, and I. Razzak, "Opinion Mining by Convolutional Neural Networks for Maximizing Discoverability of Nanomaterials," Journal of Chemical Information and Modeling, 2023. (cover paper)
• Liao, Baochen; Wu, Xinyuan; Wu, Weiliang; Liu, Changming; Ma, Sheng; Wang, Shaozhou; Xie, Tong; Wang, Qiang; Du, Zheren; Shen, Wenzhong; Li, Xiang; Li, Weimin; Hoex, Bram, "Tube‐type plasma‐enhanced atomic layer deposition of aluminium oxide: Enabling record lab performance for the industry with demonstrated cell efficiencies > 24%," Progress in Photovoltaics: Research and Applications, 2023.
• T. Xie, Y. Wan, W. Li, Q. Linghu, S. Wang, Y. Cai, H. Liu, C. Kit, C. Grazian, B. Hoex, and I. Razzak, "Interdisciplinary Discovery of Nanomaterials Based on Convolutional Neural Networks," NeruIPS 2022 AI for Science Workshop, 2022.
• T. Xie, Y. Wan, K. Lu, W. Zhang, C. Kit, and B. Hoex, “Tokenizer Effect on Functional Material Prediction: Investigating Contextual Word Embeddings for Knowledge Discovery,” AI for Accelerated Materials Design-NeurIPS 2023 Workshop, 2023.
• T. Xie, Y. Wan, Y. Zhou, W. Huang, Y. Liu, Q. Linghu, S. Wang, C. Kit, C. Grazian, B. Hoex, and I. Razzak, "Creation of a structured solar cell material dataset and performance prediction using large language models," Cell Patterns, 2024.
• S. Wang, Y. Wan, N. Song, Y. Liu, T. Xie, and B. Hoex, "Automatically Generated Datasets: Present and Potential Self-Cleaning Coating Materials," Nature Scientific Data, 2024.
• Yuwei Wan, Nan Wu, Wenjie Zhang, Chunyu Kit, Bram Hoex, Tong Xie, “Leverage Language Models Embedding for Material Discovery,” manuscripts under review.