Results 141 to 150 of about 1,466,211 (327)

Printing Nacre‐Mimetic MXene‐Based E‐Textile Devices for Sensing and Breathing‐Pattern Recognition Using Machine Learning

Advanced Functional Materials, EarlyView.
This study presents a Ti3C2Tx MXene/WPU nacre‐mimetic nanomaterial as a printable ink for direct‐write printing onto textiles‐based sensors. The resulting wearable device demonstrates high sensitivity, biocompatibility, and mechanical strength. Furthermore, NFC‐enabled humidity sensor produces time‐series data, which informs a machine learning ...
Lulu Xu, Wenqing Chen, Qian Li, Rohit Gupta, Biswajoy Bagchi, Laurence B. Lovat, Manish K. Tiwari   +6 more
wiley   +1 more source

Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

Advanced Functional Materials, EarlyView.
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu, Junyuan Lu, Jian Hui, Ziyuan Rao, Yang Ren, Hong Wang   +5 more
wiley   +1 more source

Experimentally Validated Design Principles of D‐Block Transition Metal Single‐Atom Non‐Dissociative Chemisorption Solid‐State Hydrogen Storage Materials

Advanced Functional Materials, EarlyView.
A novel descriptor and a bottom‐up design principle are established to enable the rational design of hydrogen storage materials based on d‐block transition metal single‐atom COFs. By modulating H₂ adsorption through d‐orbital tuning, this approach achieves both high storage capacity and fast kinetics, while revealing a volcano‐type relationship between
Qiuyan Yue, Chao Li, Yong Gao, Zhenglong Li, Wen‐Gang Cui, Xinqiang Wang, Guoquan Na, Xiaowei Wang, Yiyang Wan, Mingchang Zhang, Yanxia Liu, Fulai Qi, Chenchen Li, Xu Xue, Jian Miao, Jing Zhang, Xiao Han, Pan Wang, Chang Guo, Xiacui Liu, Mingxia Gao, Wenping Sun, Jian Chen, Zhenhai Xia, Hongge Pan   +24 more
wiley   +1 more source

Incorporating Recurrent Networks for Online System Identification Alongside Traditional Sine-Sweep Experiments

IEEE Access
The experimental identification of an unknown system, and the blind system identification (BSI) methods, allows engineers to establish mathematical models that represent the real system behavior.
C. A. L. Segura
doaj   +1 more source

Steep‐Switching Memory FET for Noise‐Resistant Reservoir Computing System

Advanced Functional Materials, EarlyView.
We demonstrate the steep‐switching memory FET with CuInP2S6/h‐BN/α‐In2Se3 heterostructure for application in noise‐resistant reservoir computing systems. The proposed device achieves steep switching characteristics (SSPGM = 19 mV/dec and SSERS = 23 mV/dec) through stabilization between CuInP2S6 and h‐BN.
Seongkweon Kang, Jaerok Kim, Sang‐Min Lee, Sungpyo Baek, Saeroonter Oh, Yoonmyung Lee, Sungjoo Lee   +6 more
wiley   +1 more source

Advanced Surface Engineering and Passivation Strategies of Quantum Dots for Breaking Efficiency Barrier of Clean Energy Technologies: A Comprehensive Review

Advanced Functional Materials, EarlyView.
This review describes the different surface engineering strategies for quantum dots that addresses the challenges associated with surface defects, highlighting their role in enhancing the performance of solar energy conversion technologies. Abstract Colloidal quantum dots (QDs) have garnered significant attention for their unique potential in clean ...
Kokilavani S., Gurpreet Singh Selopal
wiley   +1 more source

Nanoplasmonics Reveal Ionic‐Strength‐Driven Hydration of Nanoparticles

Advanced Functional Materials, EarlyView.
Localized surface plasmon resonance (LSPR) of gold nanoparticles (AuNPs) is modulated by ionic‐strength‐dependent hydration shell compression. A predictive model connects shell thickness to non‐radiative damping and spectral shifts over seven orders of magnitude.
Yeeun Song, Abhijit Ganguly, Zoe Bradley, Doojin Lee, Nikhil Bhalla   +4 more
wiley   +1 more source

A model of Cognitive Capitalism: a preliminary analysis [PDF]

The aim of this paper is to present a first theoretical macro-modelling of cognitive capitalism, by utilizing the French regulation theory approach. With regard to the supply side analysis, we shall emphasize the role played by productivity dynamics: it ...
Fumagalli, Andrea, Lucarelli, Stefano
core   +1 more source

Design and Applications of Multi‐Frequency Programmable Metamaterials for Adaptive Stealth

Advanced Functional Materials, EarlyView.
This article provides a comprehensive overview of metamaterials, including their fundamental principles, properties, synthesis techniques, and applications in stealth, as well as their challenges and future prospects. It covers topics that are more advanced than those typically discussed in existing review articles, while still being closely connected ...
Jonathan Tersur Orasugh, Ankita Mohanty, Amit Malakar, Suryasarathi Bose, Suprakas Sinha Ray   +4 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source