ERC Consolidator Grant #772873
Prof. Alejandro A. Franco

Publications

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An Invitation to Engage with Computational Modeling: User-Friendly Tool for In Silico Battery Component Generation and Meshing

Mehdi Chouchane, Alejandro A. Franco. Batteries & Supercaps (2021)

2021
Machine Learning-Based Assessment of the Impact of the Manufacturing Process on Battery Electrode Heterogeneity

Marc Duquesnoy, Iker Boyano, Larraitz Ganborena, Pablo Cereijo, Elixabete Ayerbe, Alejandro A. Franco. Energy & AI. 100090

2021
Heterogeneous Solid Electrolyte Interphase in Graphite Electrodes Assessed by 4D‐Resolved Computational Simulations

Mehdi Chouchane Oier Arcelus Alejandro A. Franco. Batteries & Supercaps (2021), 10.1002/batt.202100030 .

2021
Escape from flatland

Alejandro A. Franco. Nat Mach Intell (2021)

2021
Fabrication of High-Quality Thin Solid-State Electrolyte Films Assisted by Machine Learning

Yu-Ting Chen, Marc Duquesnoy, Darren H. S. Tan, Jean-Marie Doux, Hedi Yang, Grayson Deysher, Phillip Ridley, Alejandro A. Franco, Ying Shirley Meng and Zheng Chen. ACS Energy Lett. (2021), 6, 4, 1639-1648

2021
How Machine Learning Will Revolutionize Electrochemical Sciences

Aashutosh Mistry, Alejandro A. Franco, Samuel J. Cooper, Scott A. Roberts, Venkatasubramanian Viswanathan. ACS Energy Lett. (2021), 6, 1422–1431

2021
Insight on Electrolyte Infiltration of Lithium Ion Battery Electrodes by Means of a New Three-Dimensional-Resolved Lattice Boltzmann Model

Abbos Shodiev, Emiliano Primo, Oier Arcelus, Mehdi Chouchane, Markus Osenberg, André Hilger, Ingo Manke, Jianlin Li, Alejandro A. Franco. Energy Storage Materials (2021), In Press, Journal Pre-proof, Available online 24 February 2021

2021
Calendering of Li(Ni0.33Mn0.33Co0.33)O2‐Based Cathodes: Analyzing the Link Between Process Parameters and Electrode Properties by Advanced Statistics

Emiliano N. Primo, Matthieu Touzin, Alejandro A. Franco. Batteries & Supercaps (2021), 4, 1–12

2021
What Can Text Mining Tell Us About Lithium‐Ion Battery Researchers’ Habits?

Hassna El‐Bousiydy, Teo Lombardo, Emiliano N. Primo, Marc Duquesnoy, Mathieu Morcrette, Patrik Johansson, Patrice Simon, Alexis Grimaud, Alejandro A. Franco. Batteries & Supercaps (2021), 4, 1–10

2021
Understanding the calendering processability of Li(Ni0.33Mn0.33Co0.33)O2-based cathodes

Emiliano N. Primo, Mehdi Chouchane, Matthieu Touzin, Patricia Vazquez, Alejandro A. Franco. Journal of Power Sources (2021), 488, 229361

2021
Investigating Electrode Calendering and its Impact on Electrochemical Performance by Means of a New Discrete Element Method Model: Towards a Digital Twin of Li-Ion Battery Manufacturing

Alain C. Ngandjong, Teo Lombardo, Emiliano N. Primo, Mehdi Chouchane, Abbos Shodiev, Oier Arcelus, Alejandro A. Franco. Journal of Power Sources (2021), 485, 229320

2021
Entering the Augmented Era: Immersive and Interactive Virtual Reality for Battery Education and Research

Alejandro A. Franco, Jean-Noël Chotard, Emilie Loup-Escande, Yinghui Yin, Ruijie Zhao, Alexis J. Rucci, Alain C. Ndganjong, Simon Herbulot, Benjamin Beye, Jan Ciger, Romain Lelong. Batteries & Supercaps (2020), 3, 1147-1164

2020
Data-Driven Assessment of Electrode Calendering Process by Combining Experimental Results, In Silico Mesostructures Generation and Machine Learning

Marc Duquesnoy, Teo Lombardo, Mehdi Chouchane, Emiliano N. Primo, Alejandro A. Franco. Journal of Power Sources (2020) 480, 229103

2020
Accelerated Optimization Methods for Force‐Field Parametrization in Battery Electrode Manufacturing Modeling

Teo Lombardo, Jean-Baptiste Hoock, Emiliano Primo, Alain C. Ngandjong, Marc Duquesnoy, Alejandro A. Franco, Batteries & Supercaps (2020), 3, 721-730

2020
Mesoscale Effects in the Extraction of the Solid-State Lithium Diffusion Coefficient Values of Battery Active Materials: Physical Insights from 3D Modeling

Mehdi Chouchane, Emiliano N. Primo, Alejandro A. Franco, Journal of Physical Chemistry Letters (2020), 11, 7, 2775-2780

2020

Publications

An Invitation to Engage with Computational Modeling: User-Friendly Tool for In Silico Battery Component Generation and Meshing

Machine Learning-Based Assessment of the Impact of the Manufacturing Process on Battery Electrode Heterogeneity

Heterogeneous Solid Electrolyte Interphase in Graphite Electrodes Assessed by 4D‐Resolved Computational Simulations

Escape from flatland

Fabrication of High-Quality Thin Solid-State Electrolyte Films Assisted by Machine Learning

How Machine Learning Will Revolutionize Electrochemical Sciences

Insight on Electrolyte Infiltration of Lithium Ion Battery Electrodes by Means of a New Three-Dimensional-Resolved Lattice Boltzmann Model

Calendering of Li(Ni0.33Mn0.33Co0.33)O2‐Based Cathodes: Analyzing the Link Between Process Parameters and Electrode Properties by Advanced Statistics

What Can Text Mining Tell Us About Lithium‐Ion Battery Researchers’ Habits?

Understanding the calendering processability of Li(Ni0.33Mn0.33Co0.33)O2-based cathodes

Investigating Electrode Calendering and its Impact on Electrochemical Performance by Means of a New Discrete Element Method Model: Towards a Digital Twin of Li-Ion Battery Manufacturing

Entering the Augmented Era: Immersive and Interactive Virtual Reality for Battery Education and Research

Data-Driven Assessment of Electrode Calendering Process by Combining Experimental Results, In Silico Mesostructures Generation and Machine Learning

Accelerated Optimization Methods for Force‐Field Parametrization in Battery Electrode Manufacturing Modeling

Mesoscale Effects in the Extraction of the Solid-State Lithium Diffusion Coefficient Values of Battery Active Materials: Physical Insights from 3D Modeling