[HTML][HTML] Challenges and Opportunities in the Implementation of AI in Manufacturing: A Bibliometric Analysis

L Espina-Romero, H Gutiérrez Hurtado, D Ríos Parra… - Sci, 2024 - mdpi.com
This study explores the evolution and impact of research on the challenges and
opportunities in the implementation of artificial intelligence (AI) in manufacturing between …

Charging Ahead: The Evolution and Reliability of Nickel‐Zinc Battery Solutions

IT Bello, H Raza, AT Michael, M Muneeswara… - …, 2025 - Wiley Online Library
ABSTRACT Nickel‐Zinc (Ni‐Zn) batteries offer an interesting alternative for the expanding
electrochemical energy storage industry due to their high‐power density, low cost, and …

Time‐Dependent Deep Learning Manufacturing Process Model for Battery Electrode Microstructure Prediction

DE Galvez‐Aranda, TL Dinh, U Vijay… - Advanced Energy …, 2024 - Wiley Online Library
The manufacturing process of Lithium‐ion battery electrodes directly affects the practical
properties of the cells, such as their performance, durability, and safety. While computational …

[HTML][HTML] Machine learning-driven optimization of gas diffusion layer microstructure for PEM fuel cells

RL Omongos, DE Galvez-Aranda, FM Zanotto… - Journal of Power …, 2025 - Elsevier
Abstract The Gas Diffusion Layer (GDL) is a vital component within Proton Exchange
Membrane Fuel Cells (PEMFCs), playing a crucial role in mass and heat transport …

The ARTISTIC Battery Manufacturing Digitalization Initiative: From Fundamental Research to Industrialization

JF Troncoso, FM Zanotto… - Batteries & …, 2025 - Wiley Online Library
Our ARTISTIC project was born in 2018 to improve the efficiency of lithium‐ion battery cell
manufacturing process through computational modelling, allowing the research and …

Coating Feature Analysis and Capacity Prediction for Digitalization of Battery Manufacturing: An Interpretable AI Solution

Q Peng, Y Liu, Y **, XG Yang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Battery production line is crucial for determining the performance of batteries, further
significantly affecting the industrial applications of relevant energy systems. As a complex …

[HTML][HTML] Carbon-Binder-Domain porosity extraction through lithium-ion battery electrode impedance data

S Pinilla, FM Zanotto, DZ Dominguez, T García… - Energy Storage …, 2025 - Elsevier
In the field of 3-D resolved computational modeling of Lithium-ion battery electrodes, the
arrangement and properties of the Carbon-Binder-Domain (CBD) play a critical role in the …

Interdependencies in Electrode Manufacturing: A Comprehensive Study Based on Design Augmentation and Explainable Machine Learning

S Haghi, Y Chen, A Molzberger… - Batteries & …, 2024 - Wiley Online Library
Electrode manufacturing, as the core of battery cell production, is a complex process chain
with a large number of interrelated parameters. An in‐depth understanding of the processes …

[HTML][HTML] A machine learning tool to investigate lithium-ion battery degradation under real automotive conditions

A El Malki, M Ati, M Asch, AA Franco - Journal of Power Sources, 2025 - Elsevier
In electric vehicle applications, operating conditions heavily affect the battery cell lifetime
and cost. The aging process of Lithium-ion Battery (LiB) cells is influenced by numerous …

[HTML][HTML] Multi-objective optimization of lithium-ion battery designs considering the dilemma between energy density and rate capability

XY Ma, WK Zhang, Y Yin, K Liu, XG Yang - Energy and AI, 2024 - Elsevier
Electrified transportation requires batteries with high energy density and high-rate capability
for both charging and discharging. Li-ion batteries (LiBs) face a dilemma: increasing areal …