| In situ and Operando Raman Spectroscopy of Layered Transition Metal Oxides for Li-ion Battery Cathodes E Flores, P Novák, EJ Berg Frontiers in Energy Research 6, 82, 2018 | 113 | 2018 |
| Elucidation of LixNi0.8Co0.15Al0.05O2 Redox Chemistry by Operando Raman Spectroscopy E Flores, N Vonruti, P Novák, U Aschauer, EJ Berg Chemistry of materials 30 (14), 4694-4703, 2018 | 91 | 2018 |
| Solvation structure in dilute to highly concentrated electrolytes for lithium-ion and sodium-ion batteries E Flores, G Åvall, S Jeschke, P Johansson Electrochimica Acta 233, 134-141, 2017 | 77 | 2017 |
| Cation Ordering and Redox Chemistry of Layered Ni-Rich LixNi1–2yCoyMnyO2: An Operando Raman Spectroscopy Study E Flores, P Novák, U Aschauer, EJ Berg Chemistry of materials 32 (1), 186-194, 2019 | 72 | 2019 |
| Toward a unified description of battery data S Clark, FL Bleken, S Stier, E Flores, CW Andersen, M Marcinek, ... Advanced Energy Materials 12 (17), 2102702, 2022 | 52 | 2022 |
| Direct Operando Observation of Double Layer Charging and Early Solid Electrolyte Interphase Formation in Li-Ion Battery Electrolytes N Mozhzhukhina, E Flores, R Lundström, V Nyström, PG Kitz, K Edström, ... The Journal of Physical Chemistry Letters 11 (10), 4119, 2020 | 48 | 2020 |
| Data Management Plans: the Importance of Data Management in the BIG‐MAP Project IE Castelli, DJ Arismendi‐Arrieta, A Bhowmik, I Cekic‐Laskovic, S Clark, ... Batteries & Supercaps 4 (12), 1803-1812, 2021 | 27 | 2021 |
| Operando Monitoring the Insulator–Metal Transition of LiCoO2 E Flores, N Mozhzhukhina, U Aschauer, EJ Berg ACS Applied Materials & Interfaces, 2021 | 24 | 2021 |
| Uncertainty-aware and explainable machine learning for early prediction of battery degradation trajectory LH Rieger, E Flores, KF Nielsen, P Norby, E Ayerbe, O Winther, T Vegge, ... Digital Discovery 2 (1), 112-122, 2023 | 12 | 2023 |
| Learning the laws of lithium-ion transport in electrolytes using symbolic regression E Flores, C Wölke, P Yan, M Winter, T Vegge, I Cekic-Laskovic, ... Digital Discovery 1 (4), 440-447, 2022 | 11 | 2022 |
| Development of operando diagnostics for Li-ion cathodes by Raman spectroscopy EJF Cedeño ETH Zürich, 2019 | 6 | 2019 |
| Structural study on nickel doped Li2FeSiO4 JA Jaén, M Jiménez, E Flores, A Muñoz, JA Tabares, GAP Alcázar Hyperfine Interactions 232 (1-3), 127-140, 2015 | 5 | 2015 |
| PRISMA: A Robust and Intuitive Tool for High-Throughput Processing of Chemical Spectra E Flores, N Mozhzhukhina, X Li, P Norby, A Matic, Vegge, Tejs Chemistry—Methods, 1-9, 2022 | 4 | 2022 |
| Raman Microscopy: What Can the Technique Tell Us? E Flores, EJ Berg, P Novak ECS Meeting Abstracts, 24, 2019 | 2* | 2019 |
| (Digital Presentation) A Battery Interface Ontology for Data Interoperability and Semantic Knowledge Representation S Clark, CW Andersen, E Flores, FL Bleken, J Friis Electrochemical Society Meeting Abstracts 242, 2582-2582, 2022 | 1 | 2022 |
| Unravelling degradation mechanisms and overpotential sources in aged and non-aged batteries: A non-invasive diagnosis WA Appiah, LH Rieger, E Flores, T Vegge, A Bhowmik Journal of Energy Storage 84, 111000, 2024 | | 2024 |
| Correction: Understanding the patterns that neural networks learn from chemical spectra LH Rieger, M Wilson, T Vegge, E Flores Digital Discovery 3 (3), 610-610, 2024 | | 2024 |
| Thermo-Electrochemical Simulation of Large-Format Li-Ion Cells in 3D Using the Battery Modelling Toolbox (BattMo) A Johansson, O Bolzinger, S Clark, E Flores, H Nilsen, X Raynaud, ... Electrochemical Society Meeting Abstracts 244, 972-972, 2023 | | 2023 |
| Semantic Technologies to Model Battery Data and Knowledge E Flores, H Hansen, S Clark Electrochemical Society Meeting Abstracts 244, 112-112, 2023 | | 2023 |
| Understanding the patterns that neural networks learn from chemical spectra LH Rieger, M Wilson, T Vegge, E Flores Digital Discovery, 1957-1968, 2023 | | 2023 |
Erik J. BergProfessor in Chemistry, Uppsala UniversityDirección de correo verificada de kemi.uu.se
