Jones Seminar: Emerging Materials and Devices for Energy-Efficient Nanoelectronics

Optional ZOOM LINK
Meeting ID: 935 8655 7757
Passcode: 008066

The rapid rise of data-intensive workloads, driven by artificial intelligence, is exposing the fundamental energy and latency limits of conventional computing hardware. The memory wall bottleneck, in particular, demands a shift toward new hardware architectures designed to minimize costly data movement.

In this seminar, I will present advances at the intersection of materials science and device engineering that address this challenge. First, I will discuss adaptive oxide-based resistive memories for in-memory computing, detailing how novel MAX-phase electrodes achieve record-low off-state currents and how an in-situ recovery method enables robust transfer learning on analog AI accelerators. Next, I will introduce complementary back-end-of-line technologies that advance scalability for high-density, on-chip memory, including oxide semiconductor gain-cells and an interface-dipole engineering strategy for precise threshold voltage tuning. Together, these results highlight a practical and scalable path toward vertically integrated, energy-efficient electronics for future data-centric applications.

Hosted by Professor Cong Chen

About the Speaker(s)

Fabia Farlin Athena
Energy Postdoctoral Fellow in Electrical Engineering, Stanford

Fabia Farlin Athena is an energy postdoctoral fellow in electrical engineering at Stanford University, working to develop high-bandwidth oxide-semiconductor gain-cell memories and monolithic 3-D memory/logic stacks for ultra-low-power AI systems. She earned her PhD and MS in electrical and computer engineering from Georgia Institute of Technology, where her research focused on adaptive oxide memristors for brain-inspired AI, receiving the Sigma Xi Best PhD Thesis Award. She has also held research scientist intern positions at IBM TJ Watson. Fabia's interdisciplinary contributions have been recognized with the IBM PhD Fellowship, MRS Graduate Student Award, Cadence Technology Scholarship, VLSI Symposium Highlight Paper, EECS Rising Stars, Stanford Energy Postdoctoral Fellowship, and Forbes 30 Under 30 North America.

Contact

For more information, contact Amos Johnson at amos.l.johnson@dartmouth.edu.