Achieving efficient p-type doping in gallium nitride (GaN) and its alloys remains one of the most critical challenges in realizing the full potential of III-nitride semiconductors for high-power electronics, deep-ultraviolet (DUV) optoelectronics, and quantum information technologies. While magnesium is the conventional acceptor dopant, its high ionization energy (≈0.22 eV in GaN and up to 0.6 eV in AlN) limits hole concentrations to below ~1% activation efficiency, constraining device performance. Our recent work explores beryllium as an alternative acceptor in (Al,Ga)N, leveraging metal-organic chemical vapor deposition (MOCVD) to achieve high-quality, low-defect epitaxial growth. Through extensive photoluminescence and time-resolved spectroscopy studies of over fifty MOCVD grown Be-doped GaN samples, we identified the UVLBe ​ band at ~3.38 eV as a signature of a shallow Be-related acceptor with an ionization energy of ~113–114 meV — significantly shallower than Mg in GaN. Complementary theoretical studies support the assignment of this shallow state to the BeGa​ONBeGa​ complex, suggesting a pathway toward achieving p-type conductivity in AlGaN and even AlN alloys. In recent limited MOCVD growth studies on co-doping with oxygen and Be, we have observed preliminary indications that oxygen incorporation can enhance the signature of the shallow Be acceptor, though further work is needed to fully establish the efficacy and stability of this co-doping strategy. These results provide new insight into the nature of Be-related defects in GaN and AlGaN, and they highlight co-doping pathways as a promising route to overcome the long-standing bottleneck of achieving high hole concentrations. When: Friday, November 7th, 2025 – 11:45AM to 1PM (PDT) 11:45AM - 12PM: Intro 12PM-12:45PM: Lecture 12:45PM-12:55PM: Q&A 1PM Adjourn Bio: Dr. F. Shadi Shahedipour-Sandvik is a Professor of Engineering at the State University of New York, where she leads research on wide bandgap III-nitride semiconductor materials and devices for applications in lighting, power electronics, sensing, and quantum information science. Her work spans two decades of innovation and pioneering work in (Al,In) GaN materials and device engineering, with contributions ranging from high-efficiency p-type doping techniques and defect engineering and characterization to novel photocathodes and betavoltaic devices. She has authored nearly 200 publications and delivered invited talks worldwide on growth, characterization, device physics with applications in emitters, power electronics, and detectors. Shahedipour-Sandvik lab has been continuously funded by a variety of sources including NSF, ARL/ARO, DARPA, DOE, ARPA-E, NASA, and by industry. She has advised more than a dozen Ph.D. students, many of whom now hold technical leadership positions in national labs, and industry. She served as Editor-in-Chief of the Journal of Electronic Materials (2015–2024) and has been recognized with the SUNY Excellence in Research Award and the IBM Faculty Award, among other honors. Virtual: https://events.vtools.ieee.org/m/502836

Free Registration (with a Zoom account; you can get one for free if you don't already have it. This requirement is to avoid Zoom bombing. Please sign in using the email address tied to your Zoom account — not necessarily the one you used to register for the event.): https://sjsu.zoom.us/meeting/register/qGy644m7StmKMra3Xs_x2g Synopsis: Please feel free to check out the work and thoughts of Prof. Alice Smith, Ph.D., https://en.wikipedia.org/wiki/Alice_E._Smith, https://www.eng.auburn.edu/~aesmith/ on Google Scholar at https://scholar.google.com/citations?hl=en&user=3WhioLIAAAAJ&view_op=list_works&sortby=pubdate, YouTube https://www.youtube.com/results?search_query=%22alice+smith%22+auburn and generally on the Internet. Then, please feel free to submit your questions - via Twitter by using the hashtag, #ProfSmithAMA and tagging @vishnupendyala - emailing vspendyala(at)hotmail(dot)com with #ProfSmithAMA in the subject - during your registration on Zoom Selected questions will be answered by Prof. Smith during the session. Audience may be able to ask follow-up questions during the session, using the Chat feature. --------------------------------------------------------------- By registering for this event, you agree that IEEE and the organizers are not liable to you for any loss, damage, injury, or any incidental, indirect, special, consequential, or economic loss or damage (including loss of opportunity, exemplary or punitive damages). The event will be recorded and will be made available for public viewing. Co-sponsored by: Vishnu S. Pendyala, SJSU Speaker(s): Dr. Vishnu S. Pendyala, Prof. Alice Smith Virtual: https://events.vtools.ieee.org/m/498694

Rethinking Chip Design to deliver Faster, Smarter, More Compact Solutions [] Abstract: CDimension is rethinking chip design from the ground up, delivering solutions that are faster, smarter, and more compact. We’re moving beyond the limitations of traditional technology. Our foundational innovations in advanced materials and semiconductor integration unlock unprecedented gains in performance, efficiency, and scalability – ranging from 10x to 1,000x times greater than current approaches. Our first milestone: the commercial release of ultra-thin 2D semiconductor materials — a foundational step toward our vision of vertically integrated systems that unify compute, memory, and power. [] Speaker: Dr. Jiadi Zhu CEO CDimension Jiadi Zhu is the CEO and founder of CDimension, a company rethinking chip design to deliver faster, smarter, more compact solutions for the most demanding and complex computing workloads. His vision is to redefine how chips are designed, not just for higher performance, but for fundamentally better structure and efficiency. Jiadi’s technical foundation spans over a decade of work at the frontier of 2D materials, monolithic 3D integration, and device scaling. He earned his Ph.D. in Electrical Engineering from the Massachusetts Institute of Technology and has been recognized across both academia and industry for his originality in device design, novel semiconductor materials, and integration. His research–from MIT to the lab bench of CDimension–has focused on how to break architectural bottlenecks through physics-aware, layout-driven design. Jiadi’s research has been widely cited in the field and published and presented in top-tier journals and conferences, including Nature Nanotechnology and IEEE’s International Electron Devices Meeting. Jiadi’s transition from research into startup leadership has drawn attention from leaders in semiconductors, high-performance computing, and next-generation AI hardware. Today, under Jiadi’s leadership, CDimension is overcoming the limitations of traditional chip architectures and delivering significantly better performance, efficiency, and scalability across modern computing environments. AGENDA: Thursday November 13, 2025 11:30 AM: Networking, Pizza & Drinks Noon -- 1 pm: Seminar Please register on Eventbrite before 9:30 AM on Thursday November 13, 2025 $4 IEEE members $6 non IEEE members (discounts for unemployed and students ) See examplesAdd Co-sponsored by: 636940-Santa Clara Valley Section Chapter,EMB18 Bldg: ==> Use corner entrance: Kifer Road / San Lucar Court ==> Do not enter at main entrance on Kifer Road, EAG Labs, 810 Kifer Road, Sunnyvale, California, California, United States, 95051

The rapid growth of 3D advanced packaging introduces new challenges in inspection and failure analysis, where complex structures such as microbumps, redistribution layers (RDLs), and through-silicon vias (TSVs) demand reliable non-destructive testing (NDT). Conventional approaches, including Scanning Acoustic Microscopy (SAM) and X-ray imaging, are limited by noise, resolution, and defect visibility, creating barriers for reproducible and scalable analysis. To address these challenges, our work advances an AI-powered multimodal inspection framework that couples physics-informed machine learning with structured data infrastructure. A Physics-Informed Neural Network (PINN) approach enhances SAM imaging by embedding acoustic wave physics into reconstructions, producing higher-fidelity images validated through structural similarity and physical accuracy metrics. Complementing this, multimodal data fusion across SAM, X-ray laminography, optical microscopy, and CT establishes richer defect detection and cross-validation. Central to this effort is the creation of multimodality benchmark datasets built on standardized acquisition protocols, structured metadata schemas, and annotation pipelines. These datasets provide not only a foundation for AI model training but also enable reproducibility, traceability, and interoperability across future programs. Speaker(s): Navid Asadi, Virtual: https://events.vtools.ieee.org/m/498529

Millimeter-wave (mmWave) power amplifiers (PAs) are critical building blocks in next-generation radar, satellite, defense, and 6G communication systems, where output power, bandwidth, and efficiency must be achieved under stringent size, weight, and power (SWaP) constraints. Among the enabling technologies, Gallium Arsenide (GaAs) and Gallium Nitride (GaN) continue to dominate due to their complementary strengths in linearity, noise performance, and high-power density. This talk will focus on design considerations unique to mmWave GaAs and GaN PAs, with particular emphasis on stability and biasing challenges at frequencies above 20 GHz. Unlike lower microwave designs, mmWave PAs are highly susceptible to low-frequency oscillations, odd-mode instabilities, and bias-induced resonances. To mitigate these, stability networks—ranging from RC shunt loading and resistive feedback to series loading and quarter-wave stabilization—must be co-optimized with matching and biasing schemes. Special attention will be given to the integration of stability networks with bias networks, where parasitics from bias chokes, decoupling capacitors, and high-impedance bias lines can introduce additional poles/zeros in the response, affecting both gain flatness and unconditional stability. The presentation will review practical approaches to stabilizing mmWave PAs without compromising efficiency or bandwidth, including the use of lossy transmission lines, broadband bias tees, and RC filtering strategies tailored for GaAs vs. GaN processes. Case studies will illustrate how bias network design impacts stability margins and overall PA performance, and how distributed versus lumped stabilization choices evolve with frequency. The session will conclude with a discussion of packaging and integration considerations, where bondwire inductances, via transitions, and LTCC/SiP bias routing play a defining role in amplifier stability at mmWave frequencies. Speaker(s): Asmita Dani, Room: 4021, Bldg: Sobrato Campus for Discovery and Innovation, Santa Clara University, 500 El Camino Real, Santa Clara, California, United States, 95054, Virtual: https://events.vtools.ieee.org/m/505939