2 citations · 2 across the 1 of their papers we have counts for
5 papers
Prototype-guided transfer of sparse literature knowledge for electrolyte additive discovery
Weixiang Hong, Hongting Du, Jiayue Tang +4
Electrolyte additive discovery remains challenging because experimentally validated molecules are sparse, whereas accessible chemical spaces are vast and largely unlabeled. This ch…
BatteryMFormer: Multi-level Learning for Battery Degradation Trajectory Forecasting
Ruifeng Tan, Jintao Dong, Weixiang Hong +3
Early battery degradation trajectory forecasting (BDTF), which predicts the full-life state-of-health trajectory from early operational data, is critical for battery optimization,…
Pretrained battery transformer (PBT): A foundation model for battery life prediction
Ruifeng Tan, Weixiang Hong, Jia Li +2
Early prediction of battery cycle life is essential for improving battery design, manufacturing and deployment. However, despite encouraging progress with machine learning, battery…
Materials Generation in the Era of Artificial Intelligence: A Comprehensive Survey
Zhixun Li, Bin Cao, Rui Jiao +9
Materials are the foundation of modern society, underpinning advancements in energy, electronics, healthcare, transportation, and infrastructure. The ability to discover and design…
BatteryLife: A Comprehensive Dataset and Benchmark for Battery Life Prediction
Ruifeng Tan, Weixiang Hong, Jiayue Tang +6
Battery Life Prediction (BLP), which relies on time series data produced by battery degradation tests, is crucial for battery utilization, optimization, and production. Despite imp…