Dive into the exciting world of nanoscience and nanotechnology at the dedicated Tutorial Session of the IEEE-NANO 25, designed exclusively for students and young professionals seeking invaluable insights into these cutting-edge fields. This unique opportunity offers a dynamic platform for participants to interact with experts from around the globe. Renowned professionals will offer a series of tutorials, providing a comprehensive overview of key aspects of various advancing technologies. This immersive experience aims to bridge the gap between theoretical knowledge and practical applications, offering a deepened understanding of the latest advancements. Whether you are a novice or a seasoned enthusiast, this tutorial day promises to inspire, educate, and connect students and young professionals with the forefront of innovation in nanotechnology. Don’t miss this chance to broaden your horizons and engage with leading minds during IEEE-NANO 2025.
Confirmed Tutorials:
Topic: The Third Dimension of Technology Scaling: Co-designing for Direct Functionality Embedding in a Device
Bio: Amit Ranjan Trivedi is an associate professor in the department of electrical and computer engineering at the University of Illinois at Chicago (UIC). Trivedi was awarded Sigma Xi best Ph.D. thesis award from Georgia Tech, IEEE Electron Device Society Fellowship, NSF CAREER Award, and best paper award at IEEE AICAS. His research interests include compute-in-memory and neuromorphic technologies. He has more than 100 publications in referred journals and conferences.
Abstract: This talk explores a novel approach to achieving enhanced scalability of AI models within ultra-low-power systems. As AI models continue to grow exponentially in size and complexity to address increasingly diverse use cases, the limitations of transistor scaling have become apparent. While techniques like 3D and heterogeneous integration offer an interim solution by opening a second scaling dimension, the exponential growth of machine learning models necessitates a fundamental rethinking of acceleration strategies. We present an innovative direction: device-based computing, where key functionalities of AI models are directly embedded into devices, such as building circuits in a device and architectures in a circuit, through co-design of hardware and models. Starting from memristors that encapsulate entire multiply-accumulate (MAC) units within a single device to Gaussian transistors enabling reasoning functions, we delve into the underlying currents of these emerging approaches. We present them systematically as a cohesive concept, ultimately revealing a third dimension of scalability. This new paradigm paves the way for achieving higher functionality within constrained area and power budgets, offering transformative pathways for AI acceleration.
Topic: The What, Why, and How of Perovskite Solar Cells
Bio: Makhsud Saidaminov is a Canada Research Chair Tier II in Advanced Functional Materials, and an Assistant Professor in the Department of Chemistry and Department of Electrical and Computer Engineering at the University of Victoria. Prior to this position, he was a Banting PDF at the University of Toronto (2017-2019), a Visiting Scholar at MIT (April-July 2018), and a PDF at KAUST (2014-2016). Grown-up in Tajikistan, he received his Ph.D. from Lomonosov Moscow University (2013). Makhsud was named Highly Cited Researcher by Clarivate Analytics (2021-2024) and Rising Star of Science by Research.com (2022-2024). He authored 150+ publications in peer-reviewed journals which were cited 25k+ times with an h-index of 70. Makhsud serves as an Associate Editor for ACS Photonics.
Abstract: In this tutorial, I will first explore the fundamental limitations of conventional silicon solar cells. I will then present an overview of the available alternatives, with a particular focus on perovskite materials, emphasizing three key advantages that make them promising candidates:
- Defect tolerance – perovskites can be processed under ambient conditions while maintaining high performance, making them remarkably forgiving compared to silicon
- Affordability – perovskite compositions enable cost-effective large-scale production
- Bandgap tunability – perovskite electronic structure can be tailored
Through case studies, I will illustrate how these properties translate into practical advantages for applications ranging from tandem solar cells to light-emitting devices. Time permitting, I will discuss our recent progress in upscaling perovskite photovoltaics using green solvents (1), and in perovskite X-ray detectors using machine-vision-augmented synthesis of centimeter-scale single crystals (2).
(1) Nature Energy, 2024, https://doi.org/10.1038/s41560-024-01672-x
(2) Nature Synthesis, 2024, 3, 1212
