Effect of CO₂-based binary mixtures on the performance of radial-inflow turbines for the supercritical CO₂ cycles

Recently, the supercritical carbon dioxide (SCO₂) power cycle has become a hotspot in the field of energy-efficient utilization. The utilization of additives in the power cycle has been proven to be an effective way to improve the SCO₂ power cycle efficiency. As one of the core components of the system, the influence of...

Thickness-Independent Capacitive Performance of Holey Ti₃C₂T_x Film Prepared through a Mild Oxidation Strategy

The Ti₃C₂T_x film with metallic conductivity and high pseudo-capacitance holds profound promise in flexible high-rate supercapacitors. However, the restacking of Ti₃C₂T_x sheets hinders ion access to thick film electrodes. Herein, a mild yet green route has been developed to...

A new reinforcement learning-based variable speed limit control approach to improve traffic efficiency against freeway jam waves

Conventional reinforcement learning (RL) models of variable speed limit (VSL) control systems (and traffic control systems in general) cannot be trained in real traffic process because new control actions are usually explored randomly, which may result in high costs (delays) due to exploration and learning. For this reason, existing RL-based...

Multiple Strategies Differential Privacy on Sparse Tensor Factorization for Network Traffic Analysis in 5G

Due to high capacity and fast transmission speed, 5G plays a key role in modern electronic infrastructure. Meanwhile, sparse tensor factorization (STF) is a useful tool for dimension reduction to analyze high-order, high-dimension, and sparse tensor (HOHDST) data, which is transmitted on 5G Internet-of-things (IoT). Hence, HOHDST data relies...