Tracking variabilities in the simulation of Lithium Ion Battery electrode fabrication and its impact on electrochemical performance

Rucci, A.; Ngandjong, Alain C.; Primo, Emiliano N.; Maiza, Mariem; Franco, Alejandro A.

doi:10.1016/j.electacta.2019.04.110

Cited by 59 publications

(57 citation statements)

References 43 publications

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“…In order to face the "bad apples" of these revolutions, such as pollution and climate change, the humankind urgently needs technologies able to transform efficiently renewable energies into electrical one, as well as devices to store it. A possible strategy to address this challenge is through computational simulations, as it was reported by us [5][6][7] and by Thomitzek et al [8] who developed an agent-based process chain model in order to evaluate the impact of the manufacturing process parameters on the battery performance. [1][2][3] The performance of LIBs is strongly correlated to their manufacturing process.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Investigation of NMC Cathode Manufacturing Parameters Interdependencies

Cunha

Lombardo

Primo

et al. 2019

Batteries & Supercaps

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The number of parameters involved in lithium-ion battery electrode manufacturing and the complexity of the physicochemical interactions throughout the associated processes make highly complex to find interdependencies between the final electrode characteristics and the fabrication parameters. In this work, we have analyzed three different machine-learning algorithms (decision tree, support vector machine, and deep neural network) in order to find the best one to uncover the interdependencies between the slurry manufacturing parame-ters and the final properties of NMC-based cathodes. The results revealed that the support vector machine method shows high accuracy and the possibility to predict the influence of manufacturing parameters on themass loading and porosity of the electrodes in a straightforward graphical way. Furthermore, we report for the first time this new approach and a case study that, by comparing the trends observed experimentally and from the model, demonstrates the validity and the quality of the proposed approach.[a] R.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Investigation of NMC Cathode Manufacturing Parameters Interdependencies

Cunha

Lombardo

Primo

et al. 2019

Batteries & Supercaps

Self Cite

120

110

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“…The latter model, already reported by us, [54–57] is supported on a Coarse Grained Molecular Dynamics (CGMD) approach simulating LIB electrode slurries and the resulting electrode mesostructures upon the slurry solvent evaporation. By using CGMD, we have calculated several electrode mesostructures resulting from several formulations quantified by the weight ratio between LiNi 1/3 Mn 1/3 Co 1/3 O 2 active material particles and carbon‐binder, and the LiNi 1/3 Mn 1/3 Co 1/3 O 2 particles size distribution [54–56] . Figure 11 shows the example of a LIB composite positive electrode of 50×50×50 μm 3 of volume, where large particles represent the LiNi 1/3 Mn 1/3 Co 1/3 O 2 active material and small particles represent the CBDs.…”

Section: Battery Virtual Reality Serious Gamesmentioning

confidence: 85%

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

Franco

Chotard

Loup-Escande

et al. 2020

Batteries & Supercaps

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We present a series of innovative serious games we develop since four years using Virtual Reality (VR) technology to teach battery concepts at the University (from undergraduate to doctorate levels) and also to the general public in the context of science festivals and other events. These serious games allow interacting with battery materials, electrodes and cells in an immersive way. They allow experiencing impossible situations in real life, such as building with hands battery active material crystal structures at the nanometer scale, flying inside battery composite electrodes to calculate their geometrical tortuosities at the micrometer scale, experiencing the electrochemical behavior of different battery types by driving an electric vehicle and interacting with a virtual smart electrical grid impacted by 3D‐printed devices operated from the real world. Such serious games embed mathematical models with different levels of complexity representing the physical processes at different scales. We describe the technical characteristics of our VR serious games and their teaching goals, and we provide some discussion about their impact on the motivation, engagement and learning following four years of experimentation with them. Finally, we discuss why our VR serious games have also the potential to pave the way towards an augmented era in the battery field by supporting the R&D activities carried out by scientists and engineers.

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“…Finally, an optimal combined design is a very versatile tool to identify limiting factors and optimal settings for any mixture, be it a polymer blend, electrolyte formulation or material synthesis. It may also be used in conjunction with multi-scale simulations to obtain smaller, statistically comparable datasets [21,[31][32][33].…”

Section: Discussionmentioning

confidence: 99%

“…While a factor's range has no effect on the number of required experiments to run, it is generally known that the wider the range, the less precise the model will be. Extensive literature is available on Li-ion battery electrodes; although optimal formulations are not known, the constraints inherent to the system are [19][20][21]. On one hand, the active material is the only component responsible for energy storage, so it is highly desirable to maximize its content.…”

Section: Defining the Parametersmentioning

confidence: 99%

Designs of Experiments for Beginners—A Quick Start Guide for Application to Electrode Formulation

et al. 2019

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In this paper, we will describe in detail the setting up of a Design of Experiments (DoE) applied to the formulation of electrodes for Li-ion batteries. We will show that, with software guidance, Designs of Experiments are simple yet extremely useful statistical tools to set up and embrace. An Optimal Combined Design was used to identify influential factors and pinpoint the optimal formulation, according to the projected use. Our methodology follows an eight-step workflow adapted from the literature. Once the study objectives are clearly identified, it is necessary to consider the time, cost, and complexity of an experiment before choosing the responses that best describe the system, as well as the factors to vary. By strategically selecting the mixtures to be characterized, it is possible to minimize the number of experiments, and obtain a statistically relevant empirical equation which links responses and design factors.

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Tracking variabilities in the simulation of Lithium Ion Battery electrode fabrication and its impact on electrochemical performance

Cited by 59 publications

References 43 publications

Artificial Intelligence Investigation of NMC Cathode Manufacturing Parameters Interdependencies

Artificial Intelligence Investigation of NMC Cathode Manufacturing Parameters Interdependencies

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

Designs of Experiments for Beginners—A Quick Start Guide for Application to Electrode Formulation

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