Results 141 to 150 of about 1,847,581 (285)

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source

Revealing unseen dynamical regimes of ecosystems from population time-series data. [PDF]

Proc Natl Acad Sci U S A
Medeiros LP, Sorenson DK, Johnson BJ, Palkovacs EP, Munch SB.   +4 more
europepmc   +1 more source

Fabrication of Organic/Inorganic Nanocomposites: From Traditional Synthesis to Additive Manufacturing

Advanced Materials, EarlyView.
It provides an overview of the synthesis of organic/inorganic nanocomposites, spanning from conventional methods to advanced 3D printing techniques. It summarizes key challenges in 3D‐printed nanocomposites and highlights emerging innovations, including 5D printing, AI‐assisted material design, nanoscale additive manufacturing, and sustainable closed ...
Liwen Zhang, Xumin Huang, Liwei Liu, Naufal Kabir Ahamed Nasar, Xinyan Gu, Thomas P. Davis, Xiaoyu (Rayne) Zheng, Lianzhou Wang, Ruirui Qiao   +8 more
wiley   +1 more source

Time-lagged recurrence: A data-driven method to estimate the predictability of dynamical systems. [PDF]

Proc Natl Acad Sci U S A
Dong C, Faranda D, Gualandi A, Lucarini V, Mengaldo G.   +4 more
europepmc   +1 more source

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials

Advanced Materials, EarlyView.
This review presents how AI accelerates the design of defect‐tuned thermoelectric materials. By integrating machine learning with high‐throughput data and physics‐informed representations, it enables efficient prediction of thermoelectric performance from complex defect landscapes.
Chu‐Liang Fu, Mouyang Cheng, Nguyen Tuan Hung, Eunbi Rha, Zhantao Chen, Ryotaro Okabe, Denisse Córdova Carrizales, Manasi Mandal, Yongqiang Cheng, Mingda Li   +9 more
wiley   +1 more source

Mathematical insights into epidemic spread: A computational and numerical perspective. [PDF]

PLoS One
Alsulami A, Shahid N, Ahmed N, Almalahi M, Mustafa A, Aldwoah K.   +5 more
europepmc   +1 more source

High‐Entropy Materials for Water Splitting: An Atomic Nanoengineering Approach to Sustainable Hydrogen Production

Advanced Materials, EarlyView.
High‐entropy materials (HEMs), typically composed of five or more principal elements in near‐equimolar ratios, offer significant potential due to their unique properties. This review outlines the emergence and structural evolution of HEMs, followed by an in‐depth discussion of the elemental roles (active sites, promoters, or stabilizers) for water ...
Yufei Zhao, Jinhu Wu, Xianjun Cao, Dongfang Li, Peng Huang, Hong Gao, Qinfen Gu, Jinqiang Zhang, Guoxiu Wang, Hao Liu   +9 more
wiley   +1 more source

Solving nonlinear and complex optimal control problems via multi-task artificial neural networks. [PDF]

Sci Rep
Kerdabadi AE, Malek A.
europepmc   +1 more source

Advances in Topological Thermoelectrics: Harnessing Quantum Materials for Energy Applications

Advanced Materials, EarlyView.
Topological materials offer a novel platform for thermoelectric energy conversion through unique band features, including band inversion, linear Dirac bands, surface states, and Berry curvature. These quantum characteristics enable enhanced longitudinal and transverse thermoelectric effects, establishing topological thermoelectrics as a promising ...
Guangsai Yang, Lina Sang, Chao Zhang, Khay See, Alex Hamilton, Michael Fuhrer, Ning Ye, G. Jeffrey Snyder, Xiaolin Wang   +8 more
wiley   +1 more source

Weak persistence and extinction of a stochastic epidemic model with distributed delay and Ornstein-Uhlenbeck process. [PDF]

Adv Contin Discret Model
Sun Y, Liu C, Cheung L.
europepmc   +1 more source