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Technical Paper Round-up: June 14


New technical papers added to Semiconductor Engineering’s library this week. [table id=33 /] Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a good fit f... » read more

Deep Learning Applications For Material Sciences: Methods, Recent Developments


New technical paper titled "Recent advances and applications of deep learning methods in materials science" from researchers at NIST, UCSD, Lawrence Berkeley National Laboratory, Carnegie Mellon University, Northwestern University, and Columbia University. Abstract "Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning... » read more

Power/Performance Bits: Jan. 18


3D printed custom wearables Researchers from the University of Arizona created a 3D printed wearable that can operate continuously through wireless power to track body temperature and muscle deformation during exercise. Based on 3D body scans of the wearer, the medical-grade 'biosymbiotic device' can be custom printed to conform to a user's skin without the need for adhesives, which can irr... » read more

Manufacturing Bits: Jan. 10


Finding new materials with inverse design The Singapore-MIT Alliance for Research and Technology (SMART) has found a new way to perform general inverse design, a technique that can accelerate the discovery of new materials. The concept of inverse design is simple. Let’s say you want to develop products with select materials. In a computer, you input the desired materials and the propertie... » read more

Field-free spin-orbit torque-induced switching of perpendicular magnetization in a ferrimagnetic layer with a vertical composition gradient


Abstract "Current-induced spin-orbit torques (SOTs) are of interest for fast and energy-efficient manipulation of magnetic order in spintronic devices. To be deterministic, however, switching of perpendicularly magnetized materials by SOT requires a mechanism for in-plane symmetry breaking. Existing methods to do so involve the application of an in-plane bias magnetic field, or incorporation o... » read more

Power/Performance Bits: Dec. 28


Shrinking LEDs Researchers from King Abdullah University of Science and Technology (KAUST) are working to make LEDs smaller. Micrometer-scale light-emitting diodes (μLEDs) could be an ideal building block for future microLED displays, but devices based on nitride-based alloys used to achieve a broad color range become poor emitters of light when shrunk to micrometer scales. “The main ... » read more

Power/Performance Bits: Sept. 8


Backscatter radios for 5G Researchers at the Georgia Institute of Technology, Nokia Bell Labs, and Heriot-Watt University propose using backscatter radios to support high-throughput communication and 5G-speed Gb/sec data transfer using only a single transistor. “Our breakthrough is being able to communicate over 5G/millimeter-wave (mmWave) frequencies without actually having a full mmWave... » read more

Manufacturing Bits: May 10


Synaptic transistors The University of Hong Kong and Northwestern University have developed an organic electrochemical synaptic transistor, a technology that could one day process and store information like the human brain. Researchers have demonstrated that the transistor can mimic the synapses in the human brain. It can build on memories to learn over time, according to researchers. Th... » read more

Power/Performance Bits: May 10


Probabilistic bit Researchers at Tohoku University are working on building probabilistic computers by developing a spintronics-based probabilistic bit (p-bit). The researchers utilized magnetic tunnel junctions (MTJs). Most commonly used in MRAM technology, where thermal fluctuation typically poses a threat to the stable storage of information, in this case it was a benefit. The p-bits f... » read more

Manufacturing Bits: Dec. 1


New phase-change materials The National Institute of Standards and Technology (NIST) has developed an open source machine learning algorithm for use in discovering and developing new materials. NIST’s technology, called CAMEO, has already been used by researchers to discover a new phase-change memory material. CAMEO, which stands for Closed-Loop Autonomous System for Materials Exploration... » read more

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