Researchers have demonstrated a new approach to building quantum convolutional neural networks (QCNNs) using photonic circuits, paving the way for more efficient quantum machine learning. The method, reported in Advanced Photonics, introduces an adaptive step called “state injection,” allowing the circuit to adjust its behavior based on real-time measurements. Using single photons and integrated quantum photonic processors, the team achieved over 92 percent classification accuracy on simple image patterns, closely matching theoretical predictions. This proof-of-concept shows that QCNNs can be implemented with existing photonic technology and highlights a path toward scalable quantum processors for future applications in AI and data processing.

Researchers from University of Shanghai for Science and Technology, China have developed a twisted double-layer graphene plasmonic metasurface that achieves unprecedented confinement of terahertz waves into nanoscale volumes, theoretically enabling fingerprint detection of molecular monolayers as thin as 1 nm. This system overcomes the critical challenge in terahertz sensing where the long wavelength (hundreds of micrometers) weakly interacts with nanoscale molecules. By engineering acoustic plasmon nanocavities through precise twist angles between graphene layers, the team demonstrated a mode volume as small as 10⁻¹³λ₀³ and sensitivity 48 times higher than conventional single-layer graphene and non-twist double-layer graphene structures. The platform provides a new insight for ultra-strong light-matter interaction at terahertz frequencies and opens possibilities for single-molecule spectroscopy and on-chip biosensing applications.

Micro/nanomotors (MNMs) have become a transformative force in biomedical engineering, playing a pivotal role in advancing next-generation drug delivery systems. These tiny propulsion systems are categorized by their actuation mechanisms, with gas-driven MNMs standing out due to their ability to harness chemically generated micro/nano-scale thrust for autonomous motion. By leveraging their dynamic self-propulsion and unique bio-interactive behaviors, gas-driven MNMs can efficiently navigate complex biological barriers, offering groundbreaking therapeutic solutions for cancer treatment, thrombolysis, and targeted drug delivery. This review first examines the fundamental propulsion mechanisms of gas-driven MNMs, then highlights their latest breakthroughs in overcoming physiological obstacles. Finally, it evaluates their future potential and clinical advantages, providing critical insights to drive innovation and accelerate their translation into real-world medical applications.