This subject explores next-generation semiconductor technologies and materials that are shaping the future of the industry. Students learn about wide bandgap semiconductors, quantum devices, neuromorphic computing, flexible electronics, and other innovative technologies that extend beyond traditional silicon-based devices.
Students will understand the physics and applications of wide bandgap semiconductors, explore quantum computing and quantum device principles, analyze neuromorphic computing architectures and devices, investigate flexible and printed electronics technologies, evaluate emerging materials and their semiconductor applications, and assess the potential impact and challenges of next-generation semiconductor technologies.
Study of gallium nitride and silicon carbide properties, device structures, fabrication challenges, and applications in power electronics and RF systems.
Study of organic semiconductors, flexible substrates, printing processes, and applications in wearable and conformable electronics.
Study of graphene properties, carbon nanotube electronics, fabrication challenges, and potential applications in next-generation devices.
Study of quantum bits, quantum gates, superconducting qubits, silicon quantum dots, and the semiconductor infrastructure for quantum computing.
Study of artificial neurons, synaptic devices, memristors, spike-based computing, and hardware implementations of neural networks.
Study of optical waveguides, modulators, detectors, and the co-integration of photonic and electronic functions on silicon.
Study of spin injection, spin transport, magnetic tunnel junctions, and spintronic memory and logic devices.
Study of transition metal dichalcogenides, black phosphorus, and engineered heterostructures for novel device applications.
Study of DNA electronics, protein-based devices, bio-sensors, and molecular-scale switching and memory devices.
Study of resistive RAM, phase change memory, ferroelectric RAM, magnetic RAM, and storage-class memory concepts.
Study of near-threshold computing, energy harvesting circuits, power management ICs, and IoT-focused semiconductor solutions.
Study of AI accelerators, tensor processing units, edge computing architectures, and specialized semiconductor solutions for machine learning.