Microelectronics

Materials and Processing

Rensselaer microelectronics researchers are developing new materials and processes for improved channel, interconnect, and dielectric performance and scaling. With access to our Class 100 cleanroom, they are defining new methods for 3D packaging and heterogeneous integration; leveraging new materials for new technologies, including high power and photonics integration; and devising new metrology methods for relevant materials structure and properties. Current research includes: 

• Fundamental interfacial and transport phenomena related to dielectric breakdown, device reliability, resistive memory, phase change, and thermal interface materials
• Ultrathin layer materials such as graphene that promote van der Waals epitaxial growth of interconnect metals; first-level metals including Ru, Re, and Ir; graphene as a barrier layer to prevent metal diffusion
• Computational design of materials for low-resistance interconnects needed for further downscaling chips and for future computing technologies, e.g., spintronics and quantum computers, using simulations of electron transport and quantum dynamics
• Materials synthesis and device fabrication/tests focusing on spintronics, neuromorphic computing, optoelectronics, and ferroelectric logic/memory
• Epitaxial layer growth and in situ transport measurements employed to study and discover new materials for future interconnects which yield high conductivity at small (<10 nm) dimensions
• Interfacial engineering (e.g., metal-dielectric, metal-semiconductor) for tailoring multiple properties (electronic and thermal transport, adhesion, chemical stability)

Computational Microelectronics

RPI’s strength in computation across scales has applications for both the present and future of microelectronics. Our researchers model new material structures, properties, interfaces, thermal and electronic transports, devices, processors, and circuits using novel quantum, atomistic, and continuum simulation methods. This work is enhanced by campus resources including the AiMOS supercomputer, other large-scale computing architectures, and access to cloud computing with electronic data automation capabilities. Current research topics include:

• Simulations of electron transport and quantum dynamics to computationally design materials for low-resistance interconnects needed for further downscaling chips, and for future computing technologies, e.g., spintronics and quantum computers
• Parallel circuit simulation; parallel static timing analysis; codesign of extreme-scale systems; modeling and simulation of next-generation neuromorphic processors using spintronic devices
• Electrical-thermal-mechanical computational modeling of devices and packaging for reliability; modeling effect of microstructure on degradation and fatigue; modeling semiconductor crystal growth, predicted defect formation
• Physics-informed stochastic surrogate modeling for high-fidelity simulation; reinforcement-learning-based optimization for manufacturing process optimization; data-driven defective identification and quality improvement
• Atomistic simulations of macromolecular systems; retrieval, processing, and analysis of primary and secondary data; interfacial transport processes
• Simulation and workflows, with emphasis on industrial relevance and timely answers, using physics-based and statistical tools, including stochastic machine learning methods and parallel numerical methods

Technologies for Future Artificial Intelligence

As artificial intelligence and machine learning (AI/ML) come to dominate the computing landscape, there is an urgent need for acceleration and increased energy efficiency for future AI developments and applications, which include autonomous vehicles, internet of things (IoT), financial technologies, and training in data centers. Rensselaer researchers are exploring solutions that involve low-precision computing, new materials for AI hardware, new architectures, software/hardware co-design, heterogeneous integration, and analog, in memory computation. Current research includes:

• Novel materials, high-speed terahertz, and far infrared devices; computer assisted design (CAD) tools for mixed analog/digital integrated circuits (ICs) and wide band gap semiconductor materials and devices
• Parallel circuit simulation; parallel static timing analysis; codesign of extreme-scale systems; modeling and simulation of next-generation neuromorphic processors using spintronic devices
• Domain-specific architecture and system design for AI and Machine Learning with emphasis on near-data processing, in-network processing, and co-optimized design using approximate / low-precision computing
• Rethinking the computing system software/hardware design by distributing computing capability across CPU, memory, and storage devices, and its implication to mainstream applications (e.g., AI/ML, data analytics)
• Development of sample-efficient and computationally inexpensive learning methods for deep neural networks with provable generalization guarantees
• Theoretical and algorithmic foundations of optimization, machine learning, and statistical signal processing

System Applications

Researchers apply advances in semiconductor device fabrication to high-power electronics, RF and THz photonics, microelectromechanical systems (MEMS), and biological tissues and sensors. Current research includes: 

• MEMS for thermal management
• Next-generation cooling solutions for high-power microelectronics based on phase change heat transfer, advanced manufacturing technologies, and state-of-the-art modeling and simulation techniques             
• Microelectronic THz-wave rotational absorption spectroscopy for quantitative industrial gas sensing; thin-film lithium-niobate-on-insulator device research for optoelectronics; dielectric and optical properties of materials in the THz-frequency band
• Electro-thermal transient analysis of microelectronic power devices under radiation; radiation-hardened SiC power device (diodes and transistors) development, fabrication, and testing; heavy ion transport and energy deposition in semiconductors
• Power packaging, thermal management, optical systems for sensing and control, smart systems development, lighting and visible light communications, monolithic optoelectronic integration and photonic integrated circuits, sensing for agriculture
• Optoelectronic devices (modulators, photodetectors, etc.); chip-scale photonic computing devices and systems 
• Use of microfabrication to make biological tissues; stimulation of cardiac tissues with microsize electrodes