57 citations · 87 across the 5 of their papers we have counts for
5 papers
XxaCT-NN: Structure Agnostic Multimodal Learning for Materials Science
Jithendaraa Subramanian, Linda Hung, Daniel Schweigert +2
Recent advances in materials discovery have been driven by structure-based models, particularly those using crystal graphs. While effective for computational datasets, these models…
UniMat: Unifying Materials Embeddings through Multi-modal Learning
Janghoon Ock, Joseph Montoya, Daniel Schweigert +3
Materials science datasets are inherently heterogeneous and are available in different modalities such as characterization spectra, atomic structures, microscopic images, and text-…
De novo Design of Polymer Electrolytes with High Conductivity using GPT-based and Diffusion-based Generative Models
Zhenze Yang, Weike Ye, Xiangyun Lei +3
Solid polymer electrolytes hold significant promise as materials for next-generation batteries due to their superior safety performance, enhanced specific energy, and extended life…
A Self-Improvable Polymer Discovery Framework Based on Conditional Generative Model
Arash Khajeh, Xiangyun Lei, Weike Ye +3
In this work, we introduce a polymer discovery platform to efficiently design polymers with tailored properties, exemplified by the discovery of high-performance polymer electrolyt…
A cloud platform for automating and sharing analysis of raw simulation data from high throughput polymer molecular dynamics simulations
Tian Xie, Ha-Kyung Kwon, Daniel Schweigert +9
Open material databases storing hundreds of thousands of material structures and their corresponding properties have become the cornerstone of modern computational materials scienc…