Mr. David Beck

Hawai'i Natural Energy Institute, SOEST, University of Hawai'i at Mānoa, 1680 East-West Road, POST 109, Honolulu, HI 96822, USA

Mr. David Beck

Hawai'i Natural Energy Institute, SOEST, University of Hawai'i at Mānoa, 1680 East-West Road, POST 109, Honolulu, HI 96822, USA

Co-authors

Following

Followers

Research Focus & Metrics

Explore full metrics on Scilit

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications

1 December 2020 in Journal of Power Sources

Journal Article

Big data training data for artificial intelligence-based Li-ion diagnosis and prognosis

Matthieu Dubarry

David Beck

3 June 2021 in Energies

Journal Article

Inhomogeneities and Cell-to-Cell Variations in Lithium-Ion Batteries, a Review

Battery degradation is a fundamental concern in battery research, with the biggest challenge being to maintain performance and safety upon usage. From the microstructure of the materials to the design of the cell connectors in modules and their assembly in packs, it is impossible to achieve perfect reproducibility. Small manufacturing or environmental variations will compound big repercussions on pack performance and reliability. This review covers the origins of cell-to-cell variations and inhomogeneities on a multiscale level, their impact on electrochemical performance, as well as their characterization and tracking methods, ranging from the use of large-scale equipment to in operando studies.

22 April 2021 in Energies

Journal Article

Analysis of Synthetic Voltage vs. Capacity Datasets for Big Data Li-ion Diagnosis and Prognosis

Matthieu Dubarry

David Beck

The development of data driven methods for Li-ion battery diagnosis and prognosis is a growing field of research for the battery community. A big limitation is usually the size of the training datasets which are typically not fully representative of the real usage of the cells. Synthetic datasets were proposed to circumvent this issue. This publication provides improved datasets for three major battery chemistries, LiFePO₄, Nickel Aluminum Cobalt Oxide, and Nickel Manganese Cobalt Oxide 811. These datasets can be used for statistical or deep learning methods. This work also provides a detailed statistical analysis of the datasets. Accurate diagnosis as well as early prognosis comparable with state of the art, while providing physical interpretability, were demonstrated by using the combined information of three learnable parameters.

8 May 2024 in Batteries

Journal Article

Electrode Blending Simulations Using the Mechanistic Degradation Modes Modeling Approach

David Beck

Matthieu Dubarry

Blended electrodes are becoming increasingly more popular in lithium-ion batteries, yet most modeling approaches are still lacking the ability to separate the blend components. This is problematic because the different components are unlikely to degrade at the same pace. This work investigated a new approach towards the simulation of blended electrodes by replicating the complex current distributions within the electrodes using a paralleling model rather than the traditional constant-current method. In addition, a blending model was used to generate three publicly available datasets with more than 260,000 unique degradations for three exemplary blended cells. These datasets allowed us to showcase the necessity of considering all active components of the blend separately for diagnosis and prognosis.

21 November 2024 in Batteries

Journal Article

Improved Mechanistic Degradation Modes Modeling of Lithium and Sodium Plating

Lithium and sodium plating are inevitable when using negative electrodes with an electrochemical potential close to one of the charge carriers. Typical testing and modeling assume that plating occurs at 0 V when measured against the charge carrier. While this might be true under thermodynamic equilibrium, this is not true outside of steady state. This has significant implications as, by taking this into account, the testing voltage window of negative electrodes could be extended to allow gathering data for more complete discharges at higher rates. Moreover, from a modeling standpoint, it could also allow us to more accurately predict plating initiation potentials dynamically. This work presents the preliminary results of the investigation of what parameters are influencing the plating potential and how to take them into account in testing and modeling.

16 May 2026 in Batteries

Journal Article

Electrode-Level Emulation of Temperature Impact in Commercial Li-Ion Batteries

Matthieu Dubarry

Alexa Fernando

David Beck

Temperature affects the battery voltage response, and it is essential to take this influence into consideration for diagnosis purposes, as it could be misinterpreted for degradation. Temperature affects cell kinetics, and a good proxy to emulate this impact is to use electrode data at different C rates. This work further validates this concept by analyzing the relationship between temperature and rate at the electrode level for commercial graphite//LiFePO₄ and (silicon, graphite)//LiNi_0.8Mn_0.1Co_0.1O₂ cells. It will be shown that excellent emulation accuracy for both the voltage response and the capacity retention can be obtained for temperatures varying between −14 °C and 55 °C.

About Me

Dr. David Beck graduated in 2019 from EIGSI La Rochelle in France with a degree in Renewable Energy Engineering, specializing in transportation. He gained experience in battery degradation modeling during an internship for the European project SEEV4-City in England. He later worked at IFPEN Energies Nouvelles in Lyon, France, focusing on rapid diagnostic methods for second-life lithium-ion batteries. In 2020, he joined the University of Hawai‘i at Mānoa as a PhD student under the supervision of Dr. Matthieu Dubarry at the Pakali Battery Laboratory, part of the Hawai‘i Natural Energy Institute (HNEI). He earned his PhD in May 2024 and now continues as a postdoctoral researcher. His research centers on battery prototyping, with a focus on inhomogeneities and lithium plating and developing advanced tools to enhance the prognosis of Li-ion battery degradation, both at the single-cell and battery pack levels.

Mr. David Beck

Mr. David Beck

Research Focus & Metrics

Academic Career Length

Publication Type Breakdown

Representative Publications

About Me