This review describes various types of low-power memristors, demonstrating their potential for a wide range of applications. This review summarizes low-power memristors for multi-level storage, ...

The staggering computational demands of AI have become impossible to ignore. McKinsey estimates that training an AI model costs $4 million to $200 million per training run. The environmental impact is ...

Scientists have discovered that electron spin loss, long considered waste, can instead drive magnetization switching in spintronic devices, boosting efficiency by up to three times. The scalable, ...

Researchers developed an Ag/Sb2O3/Au memristor array that mimics brain-like computing, performing on-device image feature extraction with low power consumption, promising smarter and faster electric ...

Low power Static Random-Access Memory (SRAM) design remains at the forefront of research in modern electronics due to its critical role in minimising energy consumption while maintaining high ...

They may be better known for stir-fries than supercomputing, but shiitake mushrooms have now been harnessed to function as living processors, storing and recalling data like a semiconductor chip but ...

Current laptops with Intel Core Ultra Series 2 processors rely on a hybrid chip design that is specifically geared towards energy efficiency. The Neural Processing Unit (NPU), used for the first time ...