Showing 105–108 of 120 results
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Detecting Large Particles and Contaminants Using Dynamic Imaging and Adaptive Diffraction on Mastersizer 3000+
Large particles and contaminants may cause local hotspots in battery cells severely impacting safety and performance, making early detection of oversized particles an important analytical requirement. We will discuss how a combination of dynamic imaging and adaptive Laser diffraction can be used to detect oversized particles down to a few particles per million level.
This webinar will focus on the following key topics:
• Large particles and contaminants in electrode materials
• Laser diffraction for particle sizing
• Dynamic imaging for particle shape analysis and large particle detection
• Adaptive diffraction for large particle detectionPresenter
Umesh Tiwari – Market Development Manager, Advanced Battery at Malvern PanalyticalDr. Umesh Tiwari is the Market Development Manager, Advanced Battery at Malvern Panalytical. He has a Ph.D. in physics and has 17 years of experience working with academia and industries for lab and online solutions for advanced research and enhanced productivity. His expertise is in the structural, elemental, and morphological characterization of powder, slurry, and finished materials including online monitoring for process and quality controls. He has been closely associated with many development projects within Malvern Panalytical to bring technological enhancement in characterization tools to benefit battery research and manufacturing.
Malvern Panalytical is a proud sponsor of this event.
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Low Data Machine Learning for Accelerated Degradation Prediction of Lithium-ion Batteries
Meeting the demand for reliable energy storage, this work presents a machine-learning model for precise cycle life prediction in lithium-ion batteries (LIB). It explores battery aging features, utilizes data-driven methods for health assessment, and applies machine learning to predict cycle life. To address data limitations, synthetic data generation is employed, enhancing prediction accuracy. The presentation concludes by demonstrating the practical deployment of the proposed ML model for accelerated degradation prediction (for battery cell development and manufacturing feedback) and onboard deployment of low data AI on in-operation energy management. Discussions cover crucial aspects such as battery aging, data-driven health measurement, and the model’s versatility in handling accidental effects during operation.
This webinar will focus on the following key topics:
• Accelerated degradation based on low data AI for battery development for targeted applications
• Data-driven insights: machine learning for battery state of health assessment
• Prediction of rejection thresholds during cell manufacturing for application oriented cell development
• Prediction of targeted C-Rates for specific device applications
• Real-world impact: practical deployment of low data ML during real time device operationPresenter
Dr. Vikas Tomar – Professor at Purdue UniversityProf. Tomar’s interests lie in directed cell development using low data AI and vertical integration of targeted cells in c-rate and energy density specific devices. His research group has published extensively in topics related to developing data-driven models for agnostic BMS in UAVs and EVs, predicting degradation of COTS Li-ion batteries. The technology is now part of a startup, Primordis Inc., focused on launching vertically integrated Li-ion cells in autonomous systems within the framework of autonomous energy intelligence using an ASIC technology.
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Accelerating Factory Ramp-up and Quality Through Advanced In-line Electrochemical Techniques
Battery quality issues in production — more specifically, slow identification of issues — severely hamper both new factory ramp-up and in-field device performance and reliability.
By leveraging electrochemical techniques and the fundamental signatures of batteries during the end-of-line process, we can: 1) identify poor-performing cells before they would be otherwise be identified, 2) quickly correlate performance issues to upstream root cause, and 3) identify which electrochemical metrics are best correlated with long-term performance.
In the webinar, we will delve into strategies to leverage end-of-line electrochemical characteristics, encompassing thermodynamics, kinetics, and transport phenomena. The analysis of these fundamental metrics enables the identification of quality issues early to accelerate new factory ramp-up and ensure the performance and reliability of shipped devices.
This webinar will focus on the following key topics:
• The multi-year, multi-billion-dollar battery factory scale-up challenge
• The impact of battery quality variation on devices in the field
• Techniques to understand the fundamental electrochemical signatures of batteries
• Use of these techniques to accelerate factory ramp-up and improve shipped production qualityPresenter
Blake Hawley – Sr. Battery Engineer at VoltaiqBlake obtained a PhD from the University of Tennessee in Energy Science and Engineering and performed his dissertation research at Oak Ridge National Laboratory. In his career, he has developed next-generation electrode processing methods, including water-processed cathodes and dual-layered electrodes. He also has industrial experience with materials quality assurance, cell testing, and cobalt-free cathode technology.
Voltaiq is a proud sponsor of this event.
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Advances in Battery Performance and Safety Testing using Calorimetry
This presentation describes two main types of calorimetric techniques that can be used to carry out performance and safety testing on high-energy batteries.
The first half of the presentation introduces isothermal calorimetry; focused on the new IBCx system from Thermal Hazard Technology (THT). Method of operation, hardware overview and examples of data will be presented.
The second half of the presentation covers battery testing methods for the ARC adiabatic calorimeter system. The theoretical background of the test method will be described, and new developments to address blade-type batteries and high ampere-hour cells will be presented.
The presentation also mentions complementary test methods and optional modules that can be integrated with calorimetry to provide more useful analysis. For example; fast-tracking heaters, online gas analysis etc.
This webinar will focus on the following key topics:
• Principles of isothermal and adiabatic calorimetry testing for high-energy batteries
• Advantages and limitations of these two methods
• New product developments from THT to address market test requirements
• Discussion of THT lab testing resultsPresenter
Matthew Stewart – Application Scientist at THTMatthew Stewart joined Thermal Hazard Technology UK in 2021 following his graduation from Swansea University with a master’s degree in chemical engineering. In two years he has accrued a wealth of experience in battery testing and instrumentation. In his role as Application Scientist, he helps to manage THT’s test lab and carries out cutting-edge testing on the latest energy-dense cell designs. Matt has worked with several of the UK’s leading motorsports, aviation and performance vehicle manufacturers.
THT is a proud sponsor of this event.
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