Graduate Certificate in I-BEAM: Intelligent Battery Engineering and Automated Manufacturing

From grid energy storage and data centers to robotics and electric vehicles, battery technologies are playing an increasingly vital role across a wide range of applications that impact our daily lives. While considerable progress has been made in unlocking the potential of new battery materials in the laboratory, transitioning to large-scale materials and components manufacturing requires addressing scientific and engineering challenges from entirely new perspectives. This course provides a comprehensive overview of advanced battery manufacturing. Covering the full value chain—from raw material extraction to cell fabrication—it explores state-of-the-art materials, electrode processing techniques, cell design strategies, and methods for estimating production costs. A key focus of the course is smart manufacturing which involves using numerical modeling, AI, and digital twins to speed up the process of optimizing electrode and cell preparation.

Instructors: Jie Xiao, Alejandro Franco

This course introduces fundamental artificial intelligence (AI) techniques and their applications in battery manufacturing. Students will learn the mathematical foundations of AI while gaining hands-on experience with data analytics and real-world manufacturing case studies. By the end of the course, students will be prepared to address complex challenges in battery manufacturing and contribute to advancing AI-driven research in the field.

Instructor: Congrui Grace Jin

This course covers the fundamentals of equipment design and the integration of sensing technologies in energy manufacturing processes, including batteries, solar cells, and fuel cells. Students will learn principles of sensor selection, system integration, and real-time monitoring, along with data-driven control strategies. Emphasis is placed on how advanced sensing improves process efficiency, product quality, and automation in modern energy manufacturing.

Instructor: Arunachala Mada Kannan

This course examines the supply chain of battery materials, covering raw metals, polymers, lithium compounds, and components such as cell and pack casings. Students will gain a working understanding of the origins, processing, and applications of the diverse materials that underpin battery manufacturing. Industry perspectives will be incorporated, including a featured speaker from Dow Chemical who will discuss the company’s role in the supply chain and the production of polyolefins for industrial applications.

Instructors: Holyun Sun, Chi-Hao Chang

This course introduces cost and market dynamics in lithium-based battery manufacturing. Students will examine the value chain from raw material extraction to cell assembly, with attention to how supply chain constraints, synthesis choices, and process parameters affect cost structures. Case studies highlight tradeoffs in material and process decisions, industry competitiveness, and the influence of global supply chains. Students will gain tools for cost modeling, evaluating cost-performance tradeoffs, and assessing the impact of evolving technologies on manufacturing strategies.

Instructors: Julia Lamb, Nick Grundish 

This course aims to explore science and engineering behind manufacturing soft matters in lithium-ion rechargeable batteries, including electrode binders, plastic separators and organic and polymer electrolyte and additives. From polymer materials production, the state-of-the-art processing, and their applications in the batteries will be taught. The knowledge gap between fundamental research and cost-effective materials scale-up for further industry manufacturing will also be discussed.

Instructors: Gao Liu, Alvaro Videla

The development of high-performance, safe, and long-lasting batteries relies on a deep understanding of materials, interfaces, and full-cell behavior. From the atomic arrangement of active materials to the performance of complete battery systems, characterization techniques are essential tools that drive innovation, ensure high quality, and help to detect and solve problems in battery R&D and manufacturing.

In this course, we will explore a wide range of characterization techniques that are indispensable for both battery research and development (R&D) as well as quality control in large-scale manufacturing. We will examine how requirements and optimization goals differ across various applications and across different stages of product development, from laboratory-scale research to pilot scale and industrial production. We will highlight how characterization needs to shift based on specific use cases. A key part of this course will involve examining how characterization experiments can fail, highlighting common mistakes and showing how to avoid them to achieve successful results.

Instructors: Yijin Liu, Katharina Gerber, Zhao Liu