NSF awards $42.4M in new grants to support the future of semiconductors

Today, the U.S. National Science Foundation, in partnership with Ericsson, Intel Corporation, Micron Technology and Samsung, announced $42.4 million in grants for its Future of Semiconductors (NSF FuSe2) competition. The investment will fuel groundbreaking research and education across various semiconductor technologies, advancing U.S. leadership in semiconductor research and innovation and addressing key challenges in this critical field, including emerging computing tasks and applications, energy efficiency, performance, manufacturing and supply chains.

The NSF FuSe2 awards will fund semiconductor research to drive technology forward and strengthen the U.S. semiconductor industry and will support the broader goals of the "CHIPS and Science Act of 2022" to ensure long-term leadership in the microelectronics sector and growth in our regional economies across the country. As the demand for advanced computing capabilities grows, particularly in artificial intelligence and machine learning, the need for more efficient, scalable and reliable semiconductor technologies becomes increasingly vital. The awarded projects will explore novel approaches to overcome existing limitations in semiconductor design and fabrication, ensuring that the U.S. remains at the forefront of global technological advancements.

This marks the next stride in the FuSe program. One year ago, almost to the date, NSF launched the initial FuSe program that provided $45.6 million to fund 24 research and education projects supported by funding from the Biden administration's "CHIPS and Science Act of 2022."

"Innovation in semiconductor research is crucial to the future of our global competitiveness in modern electronics, computing and supply chains," said NSF Director Sethuraman Panchanathan. "These investments are not only supporting the future of semiconductors as a driver of our economy but also our national security. As such, we must ensure that we harness the full potential of emerging technologies and develop a skilled workforce ready to unleash new opportunities and tackle global grand challenges."

The broader impacts of these awards include:

• Advanced computing technology. The projects aim to revolutionize computing by developing cutting-edge technologies such as ultra-thin oxide semiconductors, novel chip designs and advanced algorithms. By enhancing the performance of AI workloads and developing energy-efficient solutions for edge devices, these innovations promise to democratize access to advanced computing and improve efficiency across various applications, from wearable health devices to large-scale data centers.
• Improved energy efficiency and environmental impacts. The projects will advance energy efficiency within computing systems, including hardware for deep neural networks, vertical power delivery systems and high-density 3D-integrated circuits. These initiatives could dramatically reduce power consumption and cooling requirements, addressing the growing energy demands of modern data centers and contributing to environmental sustainability.
• Advanced function and high-performance electronics. The projects aim to accelerate the adoption of advanced electronic, photonic and hybrid devices and components for sensing, memory and energy to enable cutting-edge functionality in semiconductor technology. They support the holistic co-design of systems across devices, circuits and algorithms by integrating new components and materials compatible with future technologies. Projects will focus on system-level strategies enabling the most robust, compact, energy-efficient and cost-effective solutions that address how analog and digital information can be processed, stored, communicated and acted upon.
• Next-generation materials and devices: Projects will focus on developing new materials and devices that overcome existing limitations in data storage, processing and quantum information processing, leading to breakthroughs in solving complex computational problems.

FuSe2 supports 23 cutting-edge research projects across 15 different states and 20 institutions, including nine first-time FuSe awardees, seven minority-serving institutions, and two NSF Established Program to Stimulate Competitive Research jurisdictions:

Topic 1: Collaborative Research in Domain-Specific Computing

• Bridging Atomic Layers and Foundation Models: An Indium-Oxide-Based Versatile Neural Computing Platform. Purdue University.
• Co-Design of 3D Vertical Back-End-Of-Line Ferroelectric Memcapacitors and In-Memory Computing Circuits for Extreme Energy Efficiency in Computing. University of Minnesota, Twin Cities.
• Domain-specific probabilistic computing with stochastic antiferromagnetic tunnel junctions. Northwestern University. 
• Edge Reinforcement Learning with Algorithm, Architecture and Circuit Co-Design. Texas A&M University.
• Efficient Edge Inference and Heterogeneous Integration in Systems for Health and Chemical Sensing. The University of Texas at Austin.
• Energy-Efficient, Near-Memory CMOS+X Architecture for Hardware Acceleration of DNNs with Application to NextG Wireless Systems. Arizona State University.
• One-Shot PetaOps/W Analog Margin-Propagation Compute Paradigm Advancing RF-MIMO Radar Processing and Classification. Washington University.

Topic 2: Advanced Function and High Performance by Heterogenous Integration

• Heterogeneously Integrated Arrays for Massively Scalable sub-THz Communications and Sensing. The Pennsylvania State University.
• Heterogeneous 3D Integration of Energy-Efficient Electronics (H3E3) with Low-Dimensional Device Layers. Stanford University.
• Heterogeneous In-Package Photonics with Reconfigurable Optical Switching for AI Clusters (HEROIC-AI). University of Michigan.
• Heterogenous Integration of Wide-Bandgap Microelectronics and Power Electronics for Efficient Power Delivery to AI Processors in Data Centers. Virginia Tech.
• High-Resolution Imaging of Defects in Semiconductors: Detection, Reliability, and Mitigation. Purdue University.
• Magnonic Combinatorial Memory and Logic Devices on a Silicon Platform. University of California, Riverside.
• Co-Designing a Semiconductor-Based Quantum Architecture Platform for Scalable Quantum Information Processing. Massachusetts Institute of Technology.

Topic 3: New Materials for Energy-Efficient, Enhanced-Performance and Sustainable Semiconductor-Based Systems

• AI-Enhanced Material-Device Codesign of Boron Arsenide as the Next-Generation Semiconductor. University of California, Santa Barbara.
• Co-Design of sub-2nm Wide-Bandgap Semiconductor Memristors for Neuromorphic Computing. University of Kansas.
• Co-Designing Indium-Based Sol-Gel Precursors for Extreme Ultraviolet Resist and Back-End-Of-The-Line Oxide Nanoelectronics. The University of Texas at Dallas.
• Energy-Efficient Nanoelectronics Based on CMOS-Compatible Magnetoelectric Transistors. The University at Buffalo.
• High-Performance & Energy-Efficient In-Memory Computing Devices with Co-Designed 2D Ferroelectric Materials and Stacks. University of Maryland, College Park.
• Louisiana Synchrotron-Sourced UV for Advanced Resist Materials and Mechanisms. Louisiana State University.
• SPRINT: Scalable, High Performance and Reliable Interconnect Technologies Based on Interface Co-Design. Texas A&M University.
• Strain and Temperature Ex-Situ Processing of Ferroelectric Oxides (STEP FOx) for BEOL Performance. Purdue University.
• Ultrafast Energy Efficient Antiferromagnetic Tunnel Junctions. The University of Arizona.

In addition, the projects will include comprehensive educational programs, from workshops and online courses to new degree offerings. They will also emphasize participation by all Americans, including those who have been underrepresented in STEM fields, and provide broader exposure to semiconductor technology, thereby fostering a diverse and skilled workforce.