[]For over three decades, Sn-based material solder joints have remained the silent workhorses of electronic packaging. Since the transition from eutectic Sn-Pb to SAC305 alloy systems, these interconnects have sustained the fast-moving pace of system- and device-level integration with sufficient mechanical, thermal, and electrical reliability. While the semiconductor industry has undergone unprecedented transformation toward higher performance systems, the SAC305 alloy solder joints have quietly absorbed stress, ensured functionality, and maintained manufacturability across generations of products. However, the emergence of high-performance computing (HPC) and AI-driven network systems places unprecedented demands on these long-serving SAC305 interconnects. Are we asking too much from the long pasting current solder material and technology that has already given so much? This seminar revisits the fundamentals of solder joint evolution, exploring why it has been so effective for thirty years and the inherent limitations now emerging. The general thermo-mechanical and electrical performance degradation mechanism will be reviewed, and compared with the new material systems such as low melting temperature alloy systems. The lessons between these different degradation mechanisms and further demand and new boundary conditions will provide a view of what solder challenges in the AI era might look like. We will discuss whether the era of traditional solder joints is approaching its boundary of service, and what emerging roles solder might play. Looking forward, we will consider how interconnects must adapt or be reimagined to meet the challenges of the next generation of AI and High-Performance computing systems. Speaker(s): Tae-Kyu Lee, Virtual: https://events.vtools.ieee.org/m/501073

Title: Brain Machine Interface: Challenges and Opportunities Date/Time: (PST)- 12:00pm to 1:00pm Thu, Oct 23 2025 Abstract: Brain Machine interfaces have the potential to revolutionize therapy for neurological diseases, because they target the nervous system with high spatiotemporal resolution as opposed to alternative therapies. Next-generation brain machine interfaces will benefit from an implantable neural recording IC with a dense, high channel count recording array that can be directly matched to a micro-electrode array (MEA) at the pitch of neurons (≈30 µm) to effectively capture spatiotemporal patterns of neural activity at single-cell resolution. These devices must support simultaneous recording from multiple thousands of neurons within the form factor and power budget of a fully implanted device. Hence, there is a requirement for an architectural paradigm shift to meet the design targets. In this talk, we will delve into specific challenges and approaches to achieve intended targets. Speaker Bio: Dante G. Muratore received a B.Sc. and an M.Sc. degree in Electrical Engineering from Politecnico of Turin, Italy in 2012 and 2013, respectively. He received a Ph.D. degree in Microelectronics from the University of Pavia, Italy in 2017 in the Integrated Microsystems Lab. From 2015 to 2016, he was a Visiting Scholar at Microsystems Technology labs at the Massachusetts Institute of Technology, USA. From 2016 to 2020, he was a Postdoctoral Fellow at Stanford University, USA. He is the recipient of the Wu Tsai Neurosciences Institute Interdisciplinary Scholar Award. Since 2020, he is an assistant professor in the Bioelectronics Section at Delft University of Technology, Netherlands, where he leads the Smart Brain Interfaces group. His research focuses on hardware design for brain-machine interfaces, bioelectronics and machine learning. https://microelectronics.tudelft.nl/People/bio.php?id=690 (https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m3d5beb80b9d84d4efbce27fdda8cc485) https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m3d5beb80b9d84d4efbce27fdda8cc485 Meeting number: 2535 991 4718 Meeting password: rQJZd3KZc32 Join from a video system or application Dial [email protected] You can also dial 173.243.2.68 and enter your meeting number. To dial from an IEEE Video Conference System: *1 2535 991 4718 Tap to join from a mobile device (attendees only) (tel:%2B1-415-655-0002,,*01*25359914718%23%23*01*) United States Toll (tel:1-855-282-6330,,*01*25359914718%23%23*01*) United States Toll Free Virtual: https://events.vtools.ieee.org/m/490922