Results 211 to 220 of about 15,576,316 (273)

Analog Tensor Processing With Carbon Nanotube In‐Memory Matrix Multiplications for Edge Computer Vision Acceleration

Advanced Materials, EarlyView.
This work prototypes a carbon nanotube‐based analog tensor core that performs in‐memory, parallel visual processing. Integrating non‐volatile memories and compact circuits, the core enables high‐speed analog matrix multiplications and can demonstrate accurate three dimensional (3D) spatial transformation and edge detection. With lightweight design, the
Jingfang Pei, Lekai Song, Songwei Liu, Yingyi Wen, Yaoqiang Zhou, Yang Liu, Pengyu Liu, Wenyu Cui, Xin Lu, Teng Ma, Zegao Wang, Guohua Hu   +11 more
wiley   +1 more source

What Do We Gain When Tolerating Loss? The Information Bottleneck Wrings Out Recombination. [PDF]

Mol Biol Evol
Narechania A, Bobo D, DeSalle R, Mathema B, Kreiswirth B, Planet PJ.   +5 more
europepmc   +1 more source

Extreme Bond Ionicity in Mg─Te Chalcogenides for Ultrathin Low Voltage Selector‐Only Memory beyond the Leakage Scaling Limit

Advanced Materials, EarlyView.
Mg─Te chalcogenides address the leakage scaling trade‐off in ultrathin selector‐only memory. Structural partitioning in multiphase Mg─Te, combined with highly ionic Mg─Te bonding and Hf interfacial engineering, supports reliable 5 nm thickness operation at low write voltage with suppressed leakage current, narrow threshold voltage distributions, 10 ns ...
Yoori Seo, Dongmin Kim, Yu Bin Park, Jangseop Lee, Tae Hoon Lee, Hyunsang Hwang   +5 more
wiley   +1 more source

Electrolyte Engineering Challenges and Opportunities for Next‐Generation Aqueous Ammonium‐Ion Batteries

Advanced Materials, EarlyView.
Aqueous ammonium‐ion batteries (AAIBs) face a hydrogen‐bond paradox: the HB network enables fast NH4+ transport but triggers water decomposition. This review dissects this dilemma, evaluates multiple electrolyte engineering strategies, and outlines four future directions for next‐generation AAIB design ABSTRACT Aqueous ammonium‐ion batteries (AAIBs ...
Zi‐Hang Huang, Xiaoyu Liu, Shuai Mao, Lingfeng Zhu, Zhijun Wu, Hongge Pan, Tianyi Ma   +6 more
wiley   +1 more source

Exploring the Trade-Off in the Variational Information Bottleneck for Regression with a Single Training Run. [PDF]

Entropy (Basel)
Kudo S, Ono N, Kanaya S, Huang M.
europepmc   +1 more source

Decoding Synergistic Pathways in Bimetallic MOFs for Advanced Oxidation Processes

Advanced Materials, EarlyView.
This review presents a unified framework linking metal pairing and framework design with electronic structure, redox cycling, oxidant activation, reactive‐species generation, and catalytic performance across photocatalytic and oxidant‐based BMOF‐AOPs. The resulting design principles guide the development of hydrolytically stable and efficient BMOFs for
Karim El‐Naggar, Huayang Zhang, Shaobin Wang   +2 more
wiley   +1 more source

Augmenting Human Expertise in Weighted Ensemble Simulations through Deep Learning-Based Information Bottleneck. [PDF]

J Chem Theory Comput
Wang D, Tiwary P.
europepmc   +1 more source

Toward Pore‐Engineered 3D‐Printed Materials for Sorption Water Harvesting, Interfacial Evaporation, and Radiative Cooling

Advanced Materials, EarlyView.
Water harvesting, radiative cooling, and interfacial solar evaporation are fundamentally governed by coupled heat, mass, and light transport processes. These processes are mediated by pore architecture, including pore size, connectivity, and hierarchical organization.
Dejan J. Trajkovski, Higgins M. Wilson, Abdallah Y. M. Ali, Jiaxing Xu, Ruzhu Wang, Primož Poredoš   +5 more
wiley   +1 more source

CBCT-to-CT synthesis using a hybrid U-Net diffusion model based on transformers and information bottleneck theory. [PDF]

Sci Rep
Hu C, Cao N, Li X, He Y, Zhou H.
europepmc   +1 more source

Descriptors to Dynamics: A Materials and Device Perspective on in‐Materio Physical Reservoir Computing for Neuromorphic Edge Intelligence

Advanced Materials, EarlyView.
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh, Alif Syafiq Kamarol Zaman, Muzhen Xu, Yuki Usami, Saptarshi Das, Hirofumi Tanaka   +5 more
wiley   +1 more source