tag: University of Maryland

Chip Industry Technical Paper Roundup: Feb. 6
By Liz Allan - 06 Feb, 2024 - Comments: 0

New technical papers added to Semiconductor Engineering’s library this week. [table id=187 /] More ReadingTechnical Paper Library home » read more

A New Phase-Change Memory For Processing Large Amounts Of Data 
By Technical Paper Link - 30 Jan, 2024 - Comments: 0

A technical paper titled “Novel nanocomposite-superlattices for low energy and high stability nanoscale phase-change memory” was published by researchers at Stanford University, TSMC, NIST, University of Maryland, Theiss Research and Tianjin University. Abstract: "Data-centric applications are pushing the limits of energy-efficiency in today’s computing systems, including those based on... » read more

Research Bits: Jan. 8
By Jesse Allen - 08 Jan, 2024 - Comments: 0

High mobility graphene Researchers at the Georgia Institute of Technology and Tianjin University created a functional semiconductor made from graphene that is compatible with conventional microelectronics processing methods. "We now have an extremely robust graphene semiconductor with 10 times the mobility of silicon, and which also has unique properties not available in silicon," said Walt... » read more

Chip Industry’s Technical Paper Roundup: October 9
By Liz Allan - 09 Oct, 2023 - Comments: 0

New technical papers added to Semiconductor Engineering’s library this week. [table id=153 /] More Reading Technical Paper Library home » read more

Chip Industry Week In Review
By The SE Staff - 06 Oct, 2023 - Comments: 0

By Jesse Allen, Liz Allan, and Gregory Haley A potential government shutdown beginning in November would be "massively disruptive" for the Commerce Department as it continues to disburse critical funding featured in the CHIPS Act to boost semiconductor research and development in the U.S., according to Secretary Gina Raimondo. Global semiconductor industry sales totaled $44 billion in Aug... » read more

New Type Of Hardware Trojans Based On Logic Locking
By Technical Paper Link - 03 Oct, 2023 - Comments: 0

A technical paper titled “Logic Locking based Trojans: A Friend Turns Foe” was published by researchers at University of Maryland and University of Florida. Abstract: "Logic locking and hardware Trojans are two fields in hardware security that have been mostly developed independently from each other. In this paper, we identify the relationship between these two fields. We find that a com... » read more

Chip Industry Week In Review
By The SE Staff - 22 Sep, 2023 - Comments: 0

By Jesse Allen, Karen Heyman, and Liz Allan The U.S. Department of Defense (DOD) announced $238 million in awards toward establishing eight regional innovation hubs under the CHIPS and Science Act. The hubs aim to accelerate hardware prototyping and "lab-to-fab" transition of semiconductor technologies for secure edge/IoT, 5G/6G, AI hardware, quantum technology, electromagnetic warfare, and ... » read more

Research Bits: Nov. 21
By Jesse Allen - 21 Nov, 2022 - Comments: 0

Graphene heater for phase-change switches Researchers from the University of Washington, Stanford University, Charles Stark Draper Laboratory, University of Maryland, and Massachusetts Institute of Technology designed an energy-efficient, silicon-based non-volatile switch that manipulates light through the use of a phase-change material and graphene heater. Aiming to reduce the power consum... » read more

Quantum Research Bits: Sept. 12
By Ed Sperling - 12 Sep, 2022 - Comments: 1

Making Qubits Last Longer One of the big challenges in quantum computing is extending the lifespan of qubits, called coherence time, long enough to do something useful with them. Research is now focused on how to increase that usable lifetime, and what factors can impact that. This has led to very different conclusions about whether silicon is a good substrate choice for quantum chips. Rese... » read more

Research Bits: June 14
By Jesse Allen - 14 Jun, 2022 - Comments: 0

Photonic deep neural network chip Engineers from the University of Pennsylvania built a photonic deep neural network on a 9.3 square millimeter chip they say is faster and more efficient at classifying images, with the ability to process nearly two billion images a second. The chip uses a series of waveguides that form 'neutron layers' mimicking the brain. “Our chip processes information ... » read more

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