Results 101 to 110 of about 1,129,295 (286)

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

Data-Centric Engineering: integrating simulation, machine learning and statistics. Challenges and Opportunities [PDF]

Chemical Engineering and Science, 2021
Indranil Pan, L. Mason, O. Matar
semanticscholar   +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

Power quality daily predictions in smart off-grids using differential, deep and statistics machine learning models processing NWP-data

, 2023
Ladislav Zjavka
openalex   +1 more source

Mechanically Tunable Bone Scaffolds: In Vivo Hardening of 3D‐Printed Calcium Phosphate/Polycaprolactone Inks

Advanced Functional Materials, EarlyView.
A 3D bone scaffold with osteogenic properties and capable of hardening in vivo is developed. The scaffold is implanted in a ductile state, and a phase transformation of the ceramic induces the stiffening and strengthening of the scaffold in vivo. Abstract Calcium phosphate 3D printing has revolutionized customized bone grafting.
Miguel Mateu‐Sanz, Pablo Varela, Laura del‐Mazo‐Barbara, Irene Lodoso‐Torrecilla, Emilio Jiménez‐Piqué, Jordi Franch, Miguel Alaminos, Maria‐Pau Ginebra   +7 more
wiley   +1 more source

Recycling of Thermoplastics with Machine Learning: A Review

Advanced Functional Materials, EarlyView.
This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque, Florian Stephan, Annalena Pongratz, Christian Brütting, Katharina Krause, Holger Ruckdäschel   +5 more
wiley   +1 more source

Flame spray pyrolysis optimization via statistics and machine learning

, 2020
Noah H. Paulson, Joseph A. Libera, Marius Stan   +2 more
openalex   +1 more source

Polymer‐Incorporated Mechanically Compliant Carbon Nanotube Microelectrode Arrays for Multichannel Neural Signal Recording

Advanced Functional Materials, EarlyView.
This work presents a soft microelectrode array based on vertically aligned carbon nanotube (CNT) forests, combining high conductivity with mechanical softness. A densification process and air‐pressure‐assisted flexibilization improve structural integrity, ensuring stable insertion and reduced inflammation.
Hyeonhee Roh, Kwangjun Kim, Chaesung Kim, Minju Kim, Minwook Kim, Sangjun Sim, Jongbaeg Kim, Jong G. Ok, Maesoon Im   +8 more
wiley   +1 more source

Monitoring of aircraft operation using statistics and machine learning

, 2003
Fazel Famili, Sylvain Létourneau
openalex   +2 more sources