Results 201 to 210 of about 1,531 (279)

Tunable Surface Chemistry of Molten Salt Derived MXenes for Data‐Driven Electrochemical Materials Discovery

Small, EarlyView.
The surface chemistries of MXenes have been largely broadened by Lewis acid melts through expanded compositional diversity and functionalization routes. Such complexity makes data‐driven approaches particularly suitable for accelerated functionality discovery. This review examines surface chemistry from synthetic history to structure‐activity relations,
Yingrui Wang, Simin Li, Tao Yang, Xinmei Hou, Bo Shen   +4 more
wiley   +1 more source

Tri-domain prediction and optimization of nanocomposite polymers for high-performance 3D printing. [PDF]

Sci Rep
Lakshmaiya N, Prasad PHC, Paramasivam P, Maranan R, Rajendran A, Bacha GB.   +5 more
europepmc   +1 more source

Explainable artificial intelligence (XAI)‐powered design framework for lightweight strain‐hardening ultra‐high‐performance composites (SH‐UHPC)

Structural Concrete, EarlyView.
Abstract Lightweight strain‐hardening ultra‐high‐performance concrete composite (SH‐UHPC) is an outstanding alternative for engineering applications and infrastructure thanks to its outstanding strength, toughness, ductility, and low density. The integration of artificial intelligence (AI)‐based modeling strategies into engineering problems can ...
Metin Katlav, Kazim Turk
wiley   +1 more source

Spectral-Based Fault Detection Method in Marine Diesel Engine Operation. [PDF]

Sensors (Basel)
Radić J, Šarić M, Rubić A.
europepmc   +1 more source

Multi‐level fatigue reliability assessment of reinforced concrete railway bridges

Structural Concrete, EarlyView.
Abstract This paper presents a multi‐level reliability framework for assessing the fatigue life of reinforced concrete (RC) railway trough bridges subjected to cyclic loading. The framework incorporates increasing levels of analytical complexity and real‐world data in four steps. First, an analytical model applies S–N curves and the Palmgren–Miner rule
Silvia Sarmiento, Jaime Gonzalez‐Libreros, Chao Wang, Lennart Elfgren, Ola Enoksson, Tommy Höjsten, Lars‐Olof Andersson, Gabriel Sas   +7 more
wiley   +1 more source

AI-Powered Structural Health Monitoring Using Multi-Type and Multi-Position PZT Networks. [PDF]

Sensors (Basel)
Gharavi H, Taban F, Korivand S, Jalili N.   +3 more
europepmc   +1 more source

Enabling pandemic‐resilient healthcare: Narrowband Internet of Things and edge intelligence for real‐time monitoring

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract The Internet of Things (IoT) in deploying robotic sprayers for pandemic‐associated disinfection and monitoring has garnered significant attention in recent research. The authors introduce a novel architectural framework designed to interconnect smart monitoring robotic devices within healthcare facilities using narrowband Internet of Things ...
Md Motaharul Islam, Mohammad Kamrul Hasan, Shayla Islam, Mohammed Balfaqih, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Nurhizam Safie, Zaheed Ahmed Bhuiyan, Rahul Thakkar, Taher M. Ghazal   +9 more
wiley   +1 more source

Monitoring of ultra-high performance concrete manufacturing for reproducible quality and waste reduction. [PDF]

Sci Rep
Rezazadeh F, Abrishambaf A, Zimmermann G, Kroll A.   +3 more
europepmc   +1 more source

Application of Intelligent Systems in CO2 Management: State of the Art and Future Prospects

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Machine learning (ML) integration is becoming increasingly popular in advancing the 4th industrial revolution, known as Industry 4.0. This review paper examines ML applications in CO2 management stages: emission, capture, and conversion. ML models, including multiple linear regression (MLR), multiple nonlinear regression (MNLR), and artificial
Muhammad Zulkefal, Iftikhar Ahmad, Asad Habib, Asad Ayub, Hamza Sethi, Ihsanullah Ihsanullah, Hakan Caliskan, Hiki Hong   +7 more
wiley   +1 more source

Vision-Based Artificial Intelligence for Adaptive Peen Forming: Sensing Architectures, Learning Models, and Closed-Loop Smart Manufacturing. [PDF]

Sensors (Basel)
Farooq SS, Rehman A, Al-Yarimi FAM, Park S, Baik J, Lee H.   +5 more
europepmc   +1 more source