Results 201 to 210 of about 1,443,742 (251)

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Mockup Test of UHPFRC Prestressed Arch. [PDF]

Materials (Basel)
Válek M, Pešková Š, Litoš J, Jogl M, Horáková E, Mára M, Horák P, Konvalinka P, Vítek P, Valentin J.   +9 more
europepmc   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

Vibration-Based Machine Learning Model Training for Railway Bridge Health Monitoring. [PDF]

Sensors (Basel)
Alaggio R, Asad M, Cirella R, Costantini S, De Gasperis G.   +4 more
europepmc   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Experimental and Numerical Investigation on Fe-SMA Strengthening of U-Rib Butt-Welded Joints with Porosity Defects. [PDF]

Materials (Basel)
Sui H, Liu Y, Yao Y, Zhou X, Bai X, Peng J.   +5 more
europepmc   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

Full-stage simulation and validation of multi-body incremental launching mechanics for complex curve bridges. [PDF]

Sci Rep
Xiao L, Zheng H.
europepmc   +1 more source

Bound Water as a Reinforcing Element for Ultra‐Strong Polyacrylamide

Advanced Science, EarlyView.
Rather than acting as a conventional plasticizer, bound water serves as a reinforcing element in polyacrylamide by constructing strong PAM–water–PAM hydrogen‐bond networks. This water‐mediated architecture delivers ultra‐high mechanical strength and exceptional flame resistance, redefining the role of water in polymer reinforcement.
Sirawit Pruksawan, Nannan Li, Zehuang Lin, Jianwei Zheng, Terence Jun En Loh, Yi Ting Chong, Junhua Kong, Xunan Hou, Xian Jun Loh, Chaobin He, FuKe Wang   +10 more
wiley   +1 more source

Correction: Rothen-Chaja et al. The Effect of In Situ Heat Treatment on the Microstructure and Mechanical Properties of H13 Tool Steel Specimens Produced by Laser-Engineered Net Shaping (LENS^®). <i>Materials</i> 2025, <i>18</i>, 5164. [PDF]

Materials (Basel)
Rothen-Chaja M, Kunce I, Radziwonko A, Płociński T, Dworecka-Wójcik J, Polański M.   +5 more
europepmc   +1 more source