| The deep-DRT: A deep neural network approach to deconvolve the distribution of relaxation times from multidimensional electrochemical impedance spectroscopy data E Quattrocchi, TH Wan, A Belotti, D Kim, S Pepe, SV Kalinin, M Ahmadi, ... Electrochimica Acta 392, 139010, 2021 | 71 | 2021 |
| A general model for the impedance of batteries and supercapacitors: The non-linear distribution of diffusion times E Quattrocchi, TH Wan, A Curcio, S Pepe, MB Effat, F Ciucci Electrochimica Acta 324, 134853, 2019 | 59 | 2019 |
| Unlocking the potential of mechanochemical coupling: boosting the oxygen evolution reaction by mating proton acceptors with electron donors A Curcio, J Wang, Z Wang, Z Zhang, A Belotti, S Pepe, MB Effat, Z Shao, ... Advanced Functional Materials 31 (4), 2008077, 2021 | 55 | 2021 |
| Neural ordinary differential equations and recurrent neural networks for predicting the state of health of batteries S Pepe, J Liu, E Quattrocchi, F Ciucci Journal of Energy Storage 50, 104209, 2022 | 37 | 2022 |
| The influence of A-site deficiency on the electrochemical properties of (Ba0. 95La0. 05) 1-xFeO3-δ as an intermediate temperature solid oxide fuel cell cathode A Belotti, Y Wang, A Curcio, J Liu, E Quattrocchi, S Pepe, F Ciucci International Journal of Hydrogen Energy 47 (2), 1229-1240, 2022 | 37 | 2022 |
| Long-range battery state-of-health and end-of-life prediction with neural networks and feature engineering S Pepe, F Ciucci Applied Energy 350, 121761, 2023 | 24 | 2023 |
| Battery state prediction through hybrid modeling: Integrating neural networks with a single particle model S Pepe, LS Kwan, B Py, MJ Robson, A Maradesa, F Ciucci Journal of Energy Storage 108, 115044, 2025 | 1 | 2025 |
| Enhancing Battery Diagnostics and Prognostics Through Machine Learning Techniques S Pepe PQDT-Global, 2023 | | 2023 |
