Advanced Materials Technologies最新文献

Smart Wearable Electronic Textiles

In the field of smart wearable electronic textiles, the integration of soft actuators is gaining significant recognition for their distinct advantages. In article number 2400079, Bao Yang and co-workers show that by seamlessly integrating with textiles, these actuators empower textiles to accurately detect and respond to diverse stimuli. This study timely reviews recent advancements, offering a systematic overview of key strategies and hurdles in optimizing actuator functionality.

Resonance Rayleigh Scattering

Accurate monitoring of neurotransmitters and precise characterization of the secretory ability of neurons are essential for effective treatment of neurological diseases. In article number 2301701, Mohamad Sawan and co-workers discover that the binding of small neurotransmitters to aptamers induces a conformational change that alters the effective radius of Au nanoclusters-aptamer complexes. This change can be detected in the resonance Rayleigh scattering intensity.

Surface-Level Muscle Deformation

In article number 2400444, Jonathan T. Alvarez, Conor J. Walsh, and co-workers introduce a non-contact method using a 2D laser profilometer to measure surface-level muscle deformation, a promising signal for estimating joint torque. The findings demonstrate strong correlations between deformation metrics—peak radial displacement, surface curvature, and surface strain—and volitional elbow torque across varying measurement locations and joint angles. This methodology standardizes evaluations, informing future wearable sensor design.

Fiber-Chip Edge Couplers

In article number 2400196, Xingchen Ji, Yikai Su, and co-workers introduce a high-efficiency edge coupler based on an alumina-on-insulator platform, which consists of a symmetric double-tip taper and a multimode interference (MMI)-based optical combiner. The edge coupler is designed to realize efficient mode matching between the single-mode fiber and chip facet via the symmetric double-tip taper at the initial stage, and then combine the two channels in the taper into a highly confined strip waveguide through the MMI-based combiner.

Stretchable Thermoelectric Devices

In article number 2301171, Joonbum Bae and Hayeon Kim present a stretchable thermoelectric device designed to improve heating and cooling performance. The device utilizes direct ink writing for precise liquid metal deposition and features a double-layer structure with an air gap. This configuration enables enhanced stretchability and facilitates twisting motion.

The rapid advancement of neuromorphic computing demands innovative hardware solutions capable of efficiently mimicking the functionality of biological neural systems. In this context, dynamic memristors have emerged as promising candidates for realizing neuromorphic reservoir computing (RC) architectures. The dynamic memristors characterized by their ability to exhibit nonlinear conductance variations and transient memory behaviors offer unique advantages for constructing RC systems. Unlike recurrent neural networks (RNNs) that face challenges such as vanishing or exploding gradients during training, RC leverages a fixed-size reservoir layer that acts as a nonlinear dynamic memory. Researchers can capitalize on their adaptable and efficient characteristics by integrating dynamic memristors into RC systems to enable rapid information processing with low learning costs. This perspective provides an overview of the recent developments in dynamic memristors and their applications in neuromorphic RC. It highlights their potential to revolutionize artificial intelligence hardware by offering faster learning speeds and enhanced energy efficiency. Furthermore, it discusses challenges and opportunities associated with integrating dynamic memristors into RC architectures, paving the way for developing next-generation cognitive computing systems.