AutoREC is an open‑source Python platform that uses reinforcement learning to automatically generate equivalent circuit models (ECMs) from electrochemical impedance spectroscopy (EIS) data. The platform frames ECM generation as a Markov decision process, training a Double Deep Q‑Network agent that iteratively modifies circuit topologies based on state, actions, and model feedback. It supports end‑to‑end workflows—including EIS preprocessing, agent training, ECM generation, and visualization—and has been demonstrated on synthetic datasets and real experimental spectra from batteries, corrosion, oxygen evolution, and CO₂ reduction systems.
By Ali Jaberi (Clean Energy Innovation Research Centre, National Research Council Canada, Mississauga, ON, Canada), Yonatan Kurniawan (Department of Materials Science and Engineering, University of Toronto, Toronto, ON, Canada), Robert Black (Clean Energy Innovation Research Centre, National Research Council Canada, Mississauga, ON, Canada), Shayan Mousavi M. (Clean Energy Innovation Research Centre, National Research Council Canada, Mississauga, ON, Canada), Kabir Verma (Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, Canada), Zoya Sadighi (Clean Energy Innovation Research Centre, National Research Council Canada, Mississauga, ON, Canada), Santiago Miret (Lila Sciences, San Francisco, CA, USA), Jason Hattrick-Simpers (Department of Materials Science and Engineering, University of Toronto, Toronto, ON, Canada)
The paper introduces SO(3) Equivariant Neural Kalman Networks (SENK), a model that predicts vibrational spectra by cascading an equivariant transformer backbone, an Equivariant Neural Kalman bridge, and an NBO-informed electronic-prior pathway. SENK improves accuracy over DetaNet on QM9S and QMe14S datasets while maintaining full-spectrum IR and Raman fidelity from small molecules to drug-like systems. It also remains stable and selectively enhances spectrally sensitive features in biomolecular systems with complex stereoelectronic effects, enabling transferable vibrational spectroscopy across diverse molecular materials.
By Zetong Li, Zhuosong Xie, Hengyu Fan, Jiaao Yu, Qiyao Hua, Zheng Lu, Liming Xu, Juanni Wu, Honglin Li
arXiv:2607. 11943v1 Announce Type: cross Abstract: Long-horizon physics-based simulations of battery degradation provide mechanistic insight but remain computationally expensive, limiting their use for dense exploration of operating conditions over extended cycle life.
By Raghvender Raghvender, Mahdi Abid, Ferran Brosa Planella, Charles Delacourt, Arnaud Demorti\`ere
arXiv:2609.39340v1 Announce Type: new
Abstract: Electrolyte formulation design requires balancing multiple physicochemical properties, yet existing models often focus on a limited subset. Learning ea...
By Jiaxin Yu, Shuo Wang, Peng Wang, Yongcai Wang, Deying Li