☆ 3.9 Article

Machine learning for optimal electrode wettability in lithium ion batteries

JOURNAL OF POWER SOURCES ADVANCES (2023)

Related references

Note: Only part of the references are listed.

Article Chemistry, Physical

Machine learning-assisted multi-objective optimization of battery manufacturing from synthetic data generated by physics-based simulations

Marc Duquesnoy et al.

Summary: The optimization of the electrodes manufacturing process is crucial for high-quality LIB cells, especially for automotive applications. A proposed deterministic ML-assisted pipeline is used for multi-objective optimization of electrode properties and inverse design of its manufacturing process. The pipeline generates a synthetic dataset from physics-based simulations and trains deterministic ML models to implement fast optimization. The successful fabrication of the electrode validates the physical relevance of the modeling pipeline.

ENERGY STORAGE MATERIALS (2023)

Add to Collection

Review Chemistry, Multidisciplinary

Artificial Intelligence Applied to Battery Research: Hype or Reality?

Teo Lombardo et al.

Summary: This article is a critical review of the application of artificial intelligence/machine learning methods in battery research. It aims to provide a comprehensive and authoritative review that is easily understandable to the battery community. The review discusses the concepts, approaches, tools, outcomes, and challenges of using AI/ML to accelerate the design and optimization of the next generation of batteries, and intends to make these tools accessible to the chemistry and electrochemical energy sciences communities while covering various aspects of battery R&D.

CHEMICAL REVIEWS (2022)

Add to Collection

Review Chemistry, Physical

Worldwide ubiquitous utilization of lithium-ion batteries: What we have done, are doing, and could do safely once they are dead?

A. R. Shekhar et al.

Summary: The accelerated industrialization of the global energy economy brings the need for battery recycling and upcycling technology, emphasizing environmental efficiency, lifecycle assessment, and safety mechanisms. This review aims to introduce the concept of worldwide sustainability and industrial battery hazard assessment, addressing knowledge gaps and exploring prospects for sustainable battery recycling.

JOURNAL OF POWER SOURCES (2022)

Add to Collection

Article Chemistry, Physical

Functional data-driven framework for fast forecasting of electrode slurry rheology simulated by molecular dynamics

Marc Duquesnoy et al.

Summary: This study proposes a functional data-driven framework to capture the influence of manufacturing parameters on the properties of lithium-ion battery composite electrodes, while ensuring a match with experimental data. The results demonstrate that this approach can significantly improve computational efficiency without sacrificing accuracy.

NPJ COMPUTATIONAL MATERIALS (2022)

Add to Collection

Article Chemistry, Physical

Designing electrode architectures to facilitate electrolyte infiltration for lithium-ion batteries

Abbos Shodiev et al.

Summary: Electrolyte infiltration is a critical step in Lithium-ion battery manufacturing, and it can be influenced by adjusting the porous mesostructure and dimensions of the electrodes and separator. By optimizing the porosity, porosity distribution, and particle size distribution of the active material, the electrolyte infiltration process can be improved, reducing both time and energy consumption in the manufacturing process.

ENERGY STORAGE MATERIALS (2022)

Add to Collection

Review Electrochemistry

Data Specifications for Battery Manufacturing Digitalization: Current Status, Challenges, and Opportunities

Franco M. Zanotto et al.

Summary: Using digital twin models in real-time information exchange and parameter correction can optimize the characteristics of the pilot line in lithium-ion battery manufacturing. This article discusses the parameters involved in each step of LIB manufacturing, presents available computational modeling approaches, and explores software implementation details. The importance of these parameters in terms of modeling set-up and validation, measurement accuracy, and rapidity is analyzed. Furthermore, the challenges and opportunities of integrating digital twin pilot lines are presented. The challenges of managing the data produced by these models are also discussed.

BATTERIES & SUPERCAPS (2022)

Add to Collection

Article Electrochemistry

Understanding Electrolyte Filling of Lithium-Ion Battery Electrodes on the Pore Scale Using the Lattice Boltzmann Method

Martin P. Lautenschlaeger et al.

Summary: The study used the lattice Boltzmann method to investigate the filling process of realistic 3D lithium-ion battery cathodes and analyzed the factors influencing electrolyte filling and optimal conditions. The results indicate that the amount and distribution of residual gas can adversely affect battery performance.

BATTERIES & SUPERCAPS (2022)

Add to Collection

Article Chemistry, Physical

Machine learning 3D-resolved prediction of electrolyte infiltration in battery porous electrodes

Abbos Shodiev et al.

Summary: An innovative machine learning model based on MLP approach has been proposed to predict electrolyte flow and wetting degree in LIB electrodes accurately and quickly. The trained ML model, along with systematic sensitivity analysis, provides a new way to optimize electrode wetting and infiltration conditions.

JOURNAL OF POWER SOURCES (2021)

Add to Collection

Article Chemistry, Physical

Understanding the calendering processability of Li(Ni0.33Mn0.33Co (0.33))O-2-based cathodes

Emiliano N. Primo et al.

Summary: The study systematically investigated the impact of calendering conditions on electrode porosity and electrochemical performance, finding that higher levels of carbon black and PVdF in the electrodes, along with increased solvent amounts in slurries, lead to improved electronic conductivity and electrochemical performance.

JOURNAL OF POWER SOURCES (2021)

Add to Collection

Article Chemistry, Physical

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 et al.

Summary: This study presents an experimentally validated calendering model that optimizes the manufacturing of lithium-ion batteries by considering the active material and carbon-binder domain, improving their performance. The effect of calendering on the electrode mesostructure was analyzed, leading to insights into the links between calendering pressure, electrode mesostructure, and overall performance.

JOURNAL OF POWER SOURCES (2021)

Add to Collection

Article Chemistry, Physical

Opportunities and Challenges of Lithium Ion Batteries in Automotive Applications

Alvaro Masias et al.

Summary: Lithium ion batteries (LIBs) have evolved from consumer electronics to powering the automotive sector, meeting the unique requirements of vehicle applications. Automotive-driven battery targets are determined by international research groups and existing electric vehicle performance. Challenges and opportunities in transitioning LIBs from CE to automotive sector are assessed in terms of energy, life, cost, safety, and fast charge capability.

ACS ENERGY LETTERS (2021)

Add to Collection

Article Chemistry, Physical

Insight on electrolyte infiltration of lithium ion battery electrodes by means of a new three-dimensional-resolved lattice Boltzmann model

Abbos Shodiev et al.

Summary: Electrolyte filling is a crucial step in lithium ion battery manufacturing, affecting the quality and subsequent wetting process. A new 3D-LBM model has been developed to simulate the electrolyte filling process in LIB porous electrodes, emphasizing the impact of electrode mesostructures on filling dynamics.

ENERGY STORAGE MATERIALS (2021)

Add to Collection

Article Engineering, Mechanical

On electrolyte wetting through lithium-ion battery separators

Ali Davoodabadi et al.

EXTREME MECHANICS LETTERS (2020)

Add to Collection

Article Chemistry, Physical

Data-driven assessment of electrode calendering process by combining experimental results, in silico mesostructures generation and machine learning

Marc Duquesnoy et al.

JOURNAL OF POWER SOURCES (2020)

Add to Collection

Review Materials Science, Multidisciplinary

AI Applications through the Whole Life Cycle of Material Discovery

Jiali Li et al.

MATTER (2020)

Add to Collection

Article Chemistry, Physical

Analysis of electrolyte imbibition through lithium-ion battery electrodes

Ali Davoodabadi et al.

JOURNAL OF POWER SOURCES (2019)

Add to Collection

News Item Multidisciplinary Sciences

DEEP TROUBLE FOR DEEP LEARNING

Douglas Heaven

NATURE (2019)

Add to Collection

Article Energy & Fuels

Effect of calendering and temperature on electrolyte wetting in lithium-ion battery electrodes

Ali Davoodabadi et al.

JOURNAL OF ENERGY STORAGE (2019)

Add to Collection

Article Chemistry, Physical

Wettability in electrodes and its impact on the performance of lithium-ion batteries

Dong Hyup Jeon

ENERGY STORAGE MATERIALS (2019)

Add to Collection

Article Chemistry, Physical

Visualization of electrolyte filling process and influence of vacuum during filling for hard case prismatic lithium ion cells by neutron imaging to optimize the production process

W. J. Weydanz et al.

JOURNAL OF POWER SOURCES (2018)

Add to Collection

Article Electrochemistry

X-ray Based Visualization of the Electrolyte Filling Process of Lithium Ion Batteries

Antje Schilling et al.

JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2018)

Add to Collection

Article Electrochemistry

Introduction to Electrochemical Impedance Spectroscopy as a Measurement Method for the Wetting Degree of Lithium-Ion Cells

Florian J. Guenter et al.

JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2018)

Add to Collection

Article Electrochemistry

The Development and Future of Lithium Ion Batteries

George E. Blomgren

JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2017)

Add to Collection

Article Chemistry, Physical

In situ visualization of the electrolyte solvent filling process by neutron radiography

Thomas Knoche et al.

JOURNAL OF POWER SOURCES (2016)

Add to Collection

Article Electrochemistry

Lattice Boltzmann Simulation for Electrolyte Transport in Porous Electrode of Lithium Ion Batteries

Sang Gun Lee et al.

JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2013)

Add to Collection

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)

Add to Collection

© Peeref 2019-2024. All rights reserved.