A Data-Driven Model for Power Loss Estimation of Magnetic Materials Based on Multi-Objective Optimization and Transfer Learning

Traditional methods such as Steinmetz's equation (SE) and its improved variant (iGSE) have demonstrated limited precision in estimating power loss for magnetic materials. The introduction of Neural Network technology for assessing magnetic component power loss has significantly enhanced accuracy. Yet, an efficient method to incorporate detailed...

Creation of memory–memory entanglement in a metropolitan quantum network

Towards realizing the future quantum internet, a pivotal milestone entails the transition from two-node proof-of-principle experiments conducted in laboratories to comprehensive multi-node set-ups on large scales. Here we report the creation of memory–memory entanglement in a multi-node quantum network over a metropolitan area. We use three...

A 2m-Range 711uW Body Channel Communication Transceiver Featuring Dynamically-Sampling Bias-Free Interface Front End

Body Channel Communication (BCC) offers a low-loss signal transmission medium for ultra-low-power wearable devices on human body [1]. However, the effective communication range on human body is limited to less than 1m in the state-of-the-art BCC transceivers [2], where the signal loss at the interface of body surface and BCC receiver remains to...

Cascade CO₂ electroreduction enables efficient carbonate-free production of ethylene

CO ₂ electroreduction offers a route to net-zero-emission production of C ₂H ₄—the most-produced organic compound. However, the formation of carbonate in this process causes loss of CO ₂ and a severe energy consumption/production penalty. Dividing the CO ₂-to-C ₂H ₄...