Results 21 to 30 of about 170 (155)

Hierarchical Physical‐Cyber Encryption via Metasurface‐Encoded Holographic Keys

Advanced Science, EarlyView.
ABSTRACT Physical‐layer encryption based on metasurfaces has emerged as a promising alternative to conventional algorithmic cryptography by embedding security into physical processes. However, most existing metasurface‐based encryption schemes operate within single‐stage or static frameworks, where correct physical illumination directly reveals the ...
Zhen Liu, Changhong Dai, Wei Zhu, Ruisheng Yang, Bohan Zhang, Lei Zhang, Bobo Du, Shengxiang Wang, Guangwei Hu   +8 more
wiley   +1 more source

Soft, Multi‐Wavelength Photoplethysmography Enables Reliable Neonatal Blood Pressure Monitoring Via Error Stratification

Advanced Science, EarlyView.
A soft hybrid multi‐wavelength PPG wearable acquires neonatal signals. Synchronized PPG and invasive ABP data are segmented into fixed windows. A 1D‐EfficientNet model predicts segment‐level SBP and DBP. Model performance is examined with retrospective subgroup analysis across acquisition conditions.
Wenqi Shi, Lanlan Mi, Jiarong Chen, Biao Liu, Min Wang, Zisheng Dai, Bin Liu, Ruize Gao, Yunfeng Lin, Weiwei Guo, Guoxing Wang, Wenyi Luo, Cheng Chen   +12 more
wiley   +1 more source

Intrinsic Phonons as a Dynamic Control Knob for Catalytic Reactivity in 2D Materials

Advanced Science, EarlyView.
Intrinsic phonon excitations are demonstrated to serve as a dynamic control knob for catalytic reactivity in 2D materials. Mode‐selective lattice vibrations reconstruct the electronic structure, lower oxygen evolution reaction barriers, establishing a phonon‐engineering paradigm for dynamically regulating electrocatalysis beyond conventional static ...
Kai Ren, Feifan Wang, Yong‐Wei Zhang, Tianyang Liu, Liangzhi Kou, Yu Jing   +5 more
wiley   +1 more source

Latent Diffusion Process With Mechanistic Guidance For Designing Functionally Graded Metamaterials With Perfect Connectivity

Advanced Science, EarlyView.
A latent diffusion‐based framework is proposed for designing functionally graded metamaterials with perfect connectivity. By integrating vector‐quantized latent representations with mechanistic guidance, the framework enables accurate inverse design toward target elastic properties.
Jongbin Yu, Dosung Lee, Namjung Kim
wiley   +1 more source

Neuromorphic Devices and Computing for Sensing, Memory, and Control

Advanced Science, EarlyView.
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu, Nicholas Schaffer, Xiao Yang   +2 more
wiley   +1 more source

Conformal Reconfigurable Intelligent Surfaces: A Cylindrical Geometry Perspective

Advanced Electronic Materials, EarlyView.
Cylindrical reconfigurable intelligent surfaces are explored for low‐complexity beam steering using one‐bit meta‐atoms. A multi‐level modeling approach, including optimization‐based synthesis, demonstrates that even minimal hardware can support directive scattering.
Filippo Pepe, Ivan Iudice, Giuseppe Castaldi, Marco Di Renzo, Vincenzo Galdi   +4 more
wiley   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

Advanced Electronic Materials, EarlyView.
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky   +4 more
wiley   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source