2 citations · 2 across the 2 of their papers we have counts for
4 papers
Graph Neural Network Predictions of Carbon 1s Binding Energies with Near-Experimental Accuracy
Adam E. A. Fouda, Joshua Zhou, Rodrigo Ferreira +10
Graph neural networks are promising architectures for fast, accurate and transferable predictions of core-electron binding energies, which depend on the local bond environment. Her…
Hierarchical Deep Research with Local-Web RAG: Toward Automated System-Level Materials Discovery
Rui Ding, Rodrigo Pires Ferreira, Yuxin Chen +1
We present a long-horizon, hierarchical deep research (DR) agent designed for complex materials and device discovery problems that exceed the scope of existing Machine Learning (ML…
Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts
Rui Ding, Jianguo Liu, Kang Hua +5
Developing advanced catalysts for acidic oxygen evolution reaction (OER) is crucial for sustainable hydrogen production. This study introduces a novel, multi-stage machine learning…
YZS-model: A Predictive Model for Organic Drug Solubility Based on Graph Convolutional Networks and Transformer-Attention
Chenxu Wang, Haowei Ming, Jian He +2
Accurate prediction of drug molecule solubility is crucial for therapeutic effectiveness and safety. Traditional methods often miss complex molecular structures, leading to inaccur…