20 citations · 26 across the 4 of their papers we have counts for
6 papers
LATHE: LAnguage-driven Toolkit for Hypothesis-based crystal Editing
Qianyu Zheng, Shuyi Jia, Victor Fung
Manipulating crystal structures towards targeted geometric properties or symmetry constraints is a longstanding challenge. Existing computational frameworks fall short: LLMs have p…
Electronic Structure Guided Inverse Design Using Generative Models
Shuyi Jia, Panchapakesan Ganesh, Victor Fung
The electronic structure of a material fundamentally determines its underlying physical, and by extension, its functional properties. Consequently, the ability to identify or gener…
Pre-training Graph Neural Networks with Structural Fingerprints for Materials Discovery
Shuyi Jia, Shitij Govil, Manav Ramprasad +1
In recent years, pre-trained graph neural networks (GNNs) have been developed as general models which can be effectively fine-tuned for various potential downstream tasks in materi…
Representation-space diffusion models for generating periodic materials
Anshuman Sinha, Shuyi Jia, Victor Fung
Generative models hold the promise of significantly expediting the materials design process when compared to traditional human-guided or rule-based methodologies. However, effectiv…
LLMatDesign: Autonomous Materials Discovery with Large Language Models
Shuyi Jia, Chao Zhang, Victor Fung
Discovering new materials can have significant scientific and technological implications but remains a challenging problem today due to the enormity of the chemical space. Recent a…
Atomic structure generation from reconstructing structural fingerprints
Victor Fung, Shuyi Jia, Jiaxin Zhang +3
Data-driven machine learning methods have the potential to dramatically accelerate the rate of materials design over conventional human-guided approaches. These methods would help…