In recent years, metal-organic frameworks (MOFs) have attracted incredible chemical and
material research interests because of their prominent properties and charming structures. The …

We propose Algorithm Distillation (AD), a method for distilling reinforcement learning (RL)
algorithms into neural networks by modeling their training histories with a causal sequence …

Gas safety has penetrated into every corner of life. As such, detection and control of
hazardous gases or humidity will always be indispensable. Quartz crystal microbalance (QCM) …

Functionalized N-doped porous carbon nanofiber webs/sulfur (N-PCNF/S) composites are
first proposed as the cathode materials for an advanced lithium–sulfur battery. The …

Most successful self-supervised learning methods are trained to align the representations of
two independent views from the data. State-of-the-art methods in video are inspired by …

The effects of ultrasound and microwave on the physicochemical properties of normal
maize and potato starches were compared. The cavitation effect of ultrasound loosened the …

In the past ten years, the technology of mass-sensitive gas sensors has seen significant
progress, becoming essential in areas such as environmental monitoring and industrial safety. …

Building generalist agents that can accomplish many goals in rich open-ended environments
is one of the research frontiers for reinforcement learning. A key limiting factor for building …

The accelerating demand for wireless communication necessitates wideband, energy-efficient
photonic sub-terahertz sources to enable ultrafast data transfer. However, as critical …

We present InP-based evanescently-coupled waveguide modified uni-traveling carrier
photodiodes (MUTC-PDs) exhibiting a breakthrough in bandwidth. The optimization of carrier …