Unraveling How a ‘Magnetic Twist’ Induces One-Way Electric Flow
Unraveling How a ‘Magnetic Twist’ Induces One-Way Electric Flow
Researchers at Tohoku University, the University of Manchester, and Osaka University have made a breakthrough that has the potential to ignite the development of next-gen chiral information technology.
Terabytes of Data in a Millimeter Crystal
Terabytes of Data in a Millimeter Crystal
UChicago Pritzker Molecular Engineering researchers created a "quantum-inspired” revolution in microelectronics, storing classical computer memory in crystal gaps where atoms should be.
Breakthrough Results on Layered Perovskites
Breakthrough Results on Layered Perovskites
The results now published pinpoint the spiral magnetic structure of these materials, finally establishing the common origin of its promising magnetic and electric properties up to room temperatures. The experiments were fully conducted at the ILL, using five instruments out of a state-of-the-art suite of over 40, and taking advantage of advanced sample environment technologies.
A Spintronic View of the Effect of Chiral Molecules
A Spintronic View of the Effect of Chiral Molecules
Researchers at Mainz University verified the chiral-induced spin selectivity effect, i.e., the influence of chiral molecules on spin, using spintronic analytical techniques
Quantonation Announced Investment in Pioniq, Which Is Developing Novel Energy Storage Devices Utilizing Quantum Materials
Quantonation, the leading early-stage investment fund dedicated to quantum technologies, announced yesterday that it has invested in Paris-based Pioniq Technologies through its fund Quantonation II. Pioniq Technologies is developing novel solid-state energy storage devices utilizing quantum materials. Quantonation stated that the pre-seed funding it provided would enable Pioniq to bring its first products to market while continuing to research innovative energy materials using quantum simulation.
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Quantum AI Framework Targets Energy Intensive Data Centers
Quantum AI Framework Targets Energy Intensive Data Centers
A new quantum computing-based optimization framework developed at Cornell could reduce energy consumption in large data centers handling artificial intelligence (AI) workloads by as much as 12.5% and reduce their carbon emissions by as much as 9.8%.
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