Unique memristor design with analog switching shows promise for high-efficiency neuromorphic computing

The growing use of artificial intelligence (AI)-based models is placing greater demands on the electronics industry, as many of these models require significant storage space and computational power. Engineers worldwide have thus been trying to develop neuromorphic computing systems that could help meet these demands, many of which are based on memristors.

Aquatic robot’s self-learning optimization enhances underwater object manipulation skills

In recent years, roboticists have introduced robotic systems that can complete missions in various environments, ranging from the ground to underground, aboveground and underwater settings. While several of these robots can grasp and move objects on the ground, the handling of objects by robotic systems underwater has so far proved more challenging.

Leveraging machine learning to find promising compositions for sodium-ion batteries

Energy storage is an essential part of many rapidly growing sustainable technologies, including electric cars and renewable energy generation. Although lithium-ion batteries (LIBs) dominate the current market, lithium is a relatively scarce and expensive element, creating both economic and supply stability challenges. Accordingly, researchers all over the world are experimenting with new types of batteries …