3 papers
physics.data-an2026
Accelerating Electrochemical Impedance Spectroscopy Measurements by Reducing Reliance on Noisy Low-Frequency Data
Qiuyu Shi, Naohiro Fujinuma, Yonatan Kurniawan +4
Electrochemical impedance spectroscopy (EIS) is a powerful tool for probing kinetic and transport processes in electrochemical systems, but its practical use is often limited by th…
cs.LG2026
Exploring the Limitations of kNN Noisy Feature Detection and Recovery for Self-Driving Labs
Qiuyu Shi, Kangming Li, Yao Fehlis +4
Self-driving laboratories (SDLs) have shown promise to accelerate materials discovery by integrating machine learning with automated experimental platforms. However, errors in the…
cs.LG2025
Assessment of different loss functions for fitting equivalent circuit models to electrochemical impedance spectroscopy data
Ali Jaberi, Amin Sadeghi, Runze Zhang +5
Electrochemical impedance spectroscopy (EIS) data is typically modeled using an equivalent circuit model (ECM), with parameters obtained by minimizing a loss function via nonlinear…