IEEE Educational Events

Abstract- Lithium-ion batteries have become central to a wide range of applications due to their
high energy density, long cycle life, and decreasing costs. From electric vehicles to
large-scale energy storage systems, they are helping to drive innovation in energy
solutions. This talk will delve into the fundamentals of lithium-ion battery technology,
focusing on the underlying physics that govern their performance, including charge
transport, thermodynamics, and electrochemical processes. We will explore how these
physical principles directly impact key application areas such as energy efficiency,
safety, and aging, with an emphasis on degradation mechanisms that influence battery
life in different operational environments. In addition to covering the core science, we
will discuss how advanced testing and characterization techniques are employed to
optimize battery design and reliability. Furthermore, the integration of AI and machine
learning in battery development is reshaping the field, allowing for predictive
maintenance, accelerated testing, and enhanced performance. We will present cutting-
edge research from Idaho National Laboratory (INL) that addresses challenges in
scaling lithium-ion batteries for long-duration energy storage, electric vehicles, and
heavy-duty trucks, offering a glimpse into the future of this transformative technology.

Abstract- The integration of physics-informed machine learning (PIML) represents a paradigm shift in scientific and engineering research, offering a powerful framework to address complex, real-world problems by embedding physical laws into data-driven models. Investigating the synergy between traditional physics-based approaches and advanced machine learning techniques is important to enhance model efficiency, interpretability, and robustness. PIML has applications across various domains, including fluid dynamics, material science, climate modeling, and biomedical engineering. In fluid dynamics, PIML models demonstrate remarkable accuracy in predicting turbulent flows, significantly advancing simulation capabilities for aerospace and mechanical engineering applications. In material science, PIML accelerates the discovery of novel materials with optimized properties, driving innovation in sectors such as electronics and renewable energy. Climate modeling benefits from the enhanced precision of PIML, crucial for improving weather forecasts and addressing climate change impacts. In biomedical engineering, PIML enhances diagnostic accuracy and treatment planning, contributing to improved patient outcomes and healthcare efficiency.