TSMC

TSMC is a global leader in the semiconductor foundry business. The company’s industry-leading process technologies and portfolio of design enablement solutions help its customers and partners unleash semiconductor innovation. With its recent expansion into Phoenix, TSMC sees the benefit of a strong partnership with ASU faculty and student researchers. TSMC supports the FURI program by providing additional funding for exceptional research projects related to the semiconductor industry. FURI student researchers who pursue a project related to the Semiconductor Manufacturing research theme are eligible for this sponsorship. TSMC-supported FURI students receive a $2,600 stipend and $400 to use for materials. Exceptional research proposals that align with the research theme of Semiconductor Manufacturing will be considered for this additional funding.

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Fall 2024

Sean M. Lowe

Computer systems engineering

Improving Hardware Verification Coverage using LLMs

Integrating fine-tuned large language models in hardware verification automates testbench creation, cuts resources and speeds up the verification process.

Program: FURI

Max Westby

Mechanical engineering

Deconvolution of Atomic Force Microscopy Data from the Effects of Destructive Indentation and Rigid Body Motion of Embedded Particles in Heterogeneous Systems

Furthering the advancement of atomic force microscopy will assist scientists in making discoveries in medicine, advanced materials, semiconductors and more.

Program: FURI

Ryan Flaherty

Mechanical engineering

3D Printed Auxetic Honeycombs: Investigation of Fatigue Behavior and Interface Characteristics in Fiber-Reinforced Metamaterials

Improving the performance of 3D printed materials will help them be used in a wide range of industries.

Program: FURI

Fuad Hossain

Electrical engineering

Integration of Virtual and Augmented Reality with Nanoscale Data Visualization for Enhanced Semiconductor Manufacturing

Virtual reality and augmented reality will improve fault detection and quality control in semiconductor manufacturing, leading to more efficient advanced technology production.

Program: FURI

David M. McComas

Electrical engineering

Diamond Static Induction Transistors

Diamond static induction transistors will achieve higher output power than the leading technology at high-frequency, very-high-frequency and ultra-high-frequency bands.

Program: FURI

Nguyen Michael Do

Electrical engineering

TCAD Simulations Aided by Physics-Informed Neural Networks

Using physics-informed neural network aided by TCAD simulation data will free up computational resources and runtime.

Program: FURI

Daniel Eduardo Abreu

Electrical engineering

Quantifying Elemental Diffusion Within Semiconducting Diodes Due to Thermal Stresses

This research will help find a new way to interpret and understand material diffusion throughout semiconductor devices.

Program: FURI

Jay Edward Schroeder

Chemical engineering

Tetrafluoromethane Adsorption on FAU Framework Zeolites – a Molecular Dynamics and Grand Monte Carlo Study

Making the removal of tetrafluoromethane easier will help to make the manufacturing of silicon more sustainable and less expensive.

Program: FURI

Summer 2024

William Boutin

Mechanical engineering

Flat Punch vs Spherical Indenter Probes for Fracture Testing of GaAs Single Crystals Utilized in Microelectronics and Semiconductor Industries

Investigating the effects of diverse nanoindentation probes can enhance the reliability and sustainability of semiconductor materials.

Program: FURI

Spring 2024

Po-Heng Ho

Electrical engineering

Optimizing Compact Model of Nanosheet FET (NSFET) for Analog/Digital IC Design

Developing an optimized machine-learning-aided compact model for nanosheet field-effect transistors can help carry out accurate and reliable circuit design.

Program: FURI

David M. McComas

Electrical engineering

TCAD Simulation of Diamond Static Induction Transistors for Radio Frequency Power Amplifiers

Vertical diamond static induction transistors can offer five times higher output power at ultra-high and S-band frequencies for future radar and communication systems.

Program: FURI

Tyler Norkus

Mechanical engineering

Finite Element Analysis of Atomic Force Microscopy Measurement of Heterogeneous Nodules Suspended in a Membrane with Application in the Semiconductor, Health, and Security Industries

Simulating nanoscale measurements of particles helps the semiconductor industry analyze complex data, map inclusions and improve products.

Program: FURI

Tomoki J. Inoue

Materials science and engineering

Developing a Theoretical Understanding of Water-Network Formation On The Surface of Metal Oxides

This project explores the water-surface interface on metal-oxides through Density Functional Theory in conjunction with machine learning.

Program: FURI

Alma Samuel Babbitt

Computer systems engineering

Verification Code Generation in the Hardware Description Language Verilog

Using large language models for verification code generation in Verilog for integrated circuit designs will shorten testing and remove roadblocks.

Program: FURI

Daniel Eduardo Abreu

Electrical engineering

Measuring Material Diffusion And Performance Changes in Semiconductor Diodes

Studying and modeling the correlation between the performance of semiconductor diodes and defects after aging.

Program: FURI

William Boutin

Mechanical engineering

Advancing the Semiconductor Industry through the Development of a Miniaturized Reinforced Mixed-Mode Bending Apparatus (MRMMB) with Out-Of-Plane Shear Mode Consideration, Initially Invented at Arizona State University

The inclusion of mode III characterization offers a valuable opportunity to enhance our comprehension of component and system failures.

Program: FURI

Fall 2023

Mykhaylo Mykhaylov

Computer science

Deep Gaussian Process and Reinforcement Learning Approach to Adaptive Maintenance Scheduling in Semiconductor Manufacturing

Optimizing semiconductor production with AI-driven maintenance predictions will boost reliability, cut downtime and supercharge production.

Program: FURI

Biplove Baral

Aerospace engineering

Exploration of Potential Anisotropic Optical Properties of Triclinic SiGe Lattices

The study of effective silicon photonics is a necessity for improving the operation speed of semiconductors.

Program: FURI

Tyler Norkus

Mechanical engineering

Finite Element Analysis of Atomic Force Microscopy Measurement of Heterogeneous Nodules Suspended in a Membrane with Application in the Semiconductor, Health, and Security Industries

Simulating nanoscale measurements of particles helps the semiconductor industry analyze complex data, map inclusions and improve products.

Program: FURI

Summer 2023

Jacob Burrows

Electrical engineering

Low-Temperature Reduction of Metal Oxide Semiconductors Using Open-Air Plasma

Open-air plasma technology improves semiconductor device performance and longevity by reducing metal oxidation in printed circuit boards.

Program: FURI

Brianna Grace Ashcroft

Mechanical engineering

Computational Discovery of Novel Wide-Bandgap Semiconductors

Studying the optimization of Ga2O3-based semiconductors can lead to significant advancements in high-performance electronic devices.

Program: FURI

Spring 2023

Jayashree Adivarahan

Electrical engineering

Ultrawide Bandgap Material for Our Future Power Electronics

Exploring techniques to integrate ultrawide bandgap semiconductor material in place of silicon will aid in building robust energy systems.

Program: FURI

Favian Rios

Biomedical engineering

Automated PID Controller Using LabVIEW for Patch-Clamping Experimentation

Developing a proportional-integral-derivative controlled pressure system will improve neuronal targeting and enable faster neuroscience instrumentation development.

Program: FURI

Priyanka Ravindran

Electrical engineering

Characterization of Emerging Devices that will Integrate Memristor and Transistor Functions for Brain-Inspired Computing

Characterizing the operation of semiconductor devices will help enhance performance toward neuromorphic computing hardware.

Program: FURI

Hailey Warner

Electrical engineering

Exploring the Physics of Resistive-Switching Behavior in Emerging Two-Dimensional Hexagonal Boron Nitride (2D h-BN) Memristors

Characterizing h-BN memristor devices will help reveal their prospects within neuromorphic (or "brain-inspired") computing.

Program: FURI