The rapid adoption of artificial intelligence in semiconductor systems has exposed a persistent gap in engineering education: students often learn AI using high-level software platforms without understanding how underlying silicon realities shape performance, efficiency, and reliability. This disconnect, referred to as the Cleanroom Barrier, separates algorithmic learning from hardware...
The semiconductor industry cannot scale without people. In this keynote, Michelle Williams, Executive Director of the SEMI Foundation, shares how the SEMI Foundation is transforming lives and strengthening communities through bold new initiatives coupled with tried-and-true programs. From sparking industry curiosity in K–12 classrooms, to helping veterans launch new careers, to launching and...
Presentation describes the application of Q-switched lasers to the concurrent multi-beam multi-target pulsed laser deposition (CMBMT-PLD) of the high-entropy alloy (HEA) films. A six-beam system included permanent magnets under the PLD targets and the substrate and a substrate heater. Magnets narrowed down the plasma plumes from the targets and increased the material deposition rate. Three-...
The Chips & Science Act, while focused on strengthening U.S. semiconductor manufacturing, also creates critical opportunities for workforce development. However, chip design and manufacturing demand advanced facilities and interdisciplinary STEM expertise, posing significant challenges for small institutions. These challenges include limited access to training resources, difficulty sustaining...
Defects in semiconductors and diamond are emerging as highly efficient platforms for quantum sensing applications. Machine learning offers a powerful alternative to conventional model-based data analysis in quantum sensing, particularly for computationally intensive techniques such as continuous-wave optically detected magnetic resonance (CW-ODMR) using nitrogen-vacancy (NV) centers in...
Two-dimensional transition metal dichalcogenides (TMDs) show immense potential for next-generation nanoelectronics and optoelectronics, owing to their atomic-scale thickness and compatibility with van der Waals (vdW) integration. Consequently, TMDs have become central to emerging technologies such as neuromorphic computing, high-speed photodetectors, and superconducting quantum circuits....
The project is conducted as a collaborative effort involving undergraduate engineering and physics students, with the dual objectives of achieving a tapeout-ready design and providing hands-on training in modern VLSI workflows. The ALU architecture is optimized for wide-word arithmetic commonly required in public-key cryptography, including modular addition, subtraction, and logic...
The semiconductor industry relies heavily on photolithography processes conducted in controlled cleanroom environments, where training and collaboration are constrained by stringent contamination protocols, high operational costs, and physical limitations. To address these challenges, we present a novel immersive Collaborative Virtual Training Environment (CVTE) designed for multiuser...
We extract the infrared dielectric function from Fourier transform infrared reflectance spectra 650−4000 cm−1 for conducting single crystal and polycrystalline boron-doped (3−6×1020 cm−3) diamond (BDD) by Kramers–Kronig (K–K) analysis, validating our method on commercial SiC substrates. This method highlights the importance of using integrable functions in K–K, solving issues with convergence...
In the HBCU Chips 2025 conference, M.R. Hadizadeh, B. Sarker, and M.A. Khan presented an approach for solving 1D quantum systems using machine learning. Here, we present a discussion and feasibility consideration of numerical methods for computing multiple eigenpairs of Hamiltonian matrix $A\in\mathbb{R}^{n\times n}$ using a block formulation of the Rayleigh quotient in either Python or Julia...
As the U.S. advances efforts to strengthen its semiconductor and microelectronics workforce, institutional websites have become a primary source of information for students, researchers, industry partners, and federal funders seeking to identify research capacity, workforce initiatives, and collaboration opportunities. These stakeholders, particularly students exploring workforce pathways and...
Cubic boron nitride (c-BN) is an ultrawide-bandgap semiconductor with a 6.4 eV bandgap, a high breakdown field above 15 MV/cm, and great thermal conductivity of 940 W/m·K. This makes it excellent for the next generation high-power and high-temperature electronic devices. In this work, we report the growth of c-BN using a custom-built Electron Cyclotron Resonance Chemical Vapor Deposition...
