Results 131 to 140 of about 53,796 (278)

Emergent Spin Fluctuation and Structural Metastability in Self‐Intercalated Cr1+xTe2${\rm Cr}_{1+x}{\rm Te}_2$ Compounds

Advanced Electronic Materials, EarlyView.
Metastable superstructure and emergent spin fluctuation in self‐intercalated Cr1+xTe2${\rm Cr}_{1+x}{\rm Te}_2$ ABSTRACT Intercalated van der Waals (vdW) magnetic materials host unique magnetic properties due to the interplay of competing interlayer and intralayer exchange couplings, which depend on the intercalant concentration within the van der ...
Clayton Conner, Ali Sarikhani, Theo Volz, Mathew Pollard, Mitchel Vaninger, Xiaoqing He, Steven Kelley, Jacob Cook, Avinash Sah, John Clark, Hunter Lucker, Cheng Zhang, Paul Miceli, Yew San Hor, Xiaoqian Zhang, Guang Bian   +15 more
wiley   +1 more source

Development of Deep Learning-Based Algorithm for Extracting Abnormal Deceleration Patterns

World Electric Vehicle Journal
A smart regenerative braking system for EVs can reduce unnecessary brake operations by assisting in the braking of a vehicle according to the driving situation, road slope, and driver’s preference.
Youngho Jun, Minha Kim, Kangjun Lee, Simon S. Woo   +3 more
doaj   +1 more source

Pressure‐Induced Structural and Magnetic Evolution in Layered Antiferromagnet YbMn2Sb2

Advanced Electronic Materials, EarlyView.
Pressure tunes the delicate balance between structure, magnetism, and electronic states in quantum materials. In YbMn2Sb2, high‐pressure X‐ray and neutron diffraction reveal a trigonal‐to‐monoclinic transition near 3.5 GPa, accompanied by unconventional magnetic ordering.
Mingyu Xu, Matt Boswell, Aya Rutherford, Cheng Peng, Ying Zhou, Shuyang Wang, Zhaorong Yang, Antonio M. dos Santos, Haidong Zhou, Weiwei Xie   +9 more
wiley   +1 more source

Topological Materials and Related Applications

Advanced Electronic Materials, EarlyView.
This review covers topological materials—including topological insulators, quantum valley Hall and quantum spin Hall insulators, and topological Weyl and Dirac semimetals—as well as their most recent advancements in fields such as spintronics, electronics, photonics, thermoelectrics, and catalysis.
Carlo Grazianetti, Roberto Mantovan, Emanuele Longo, Harold J. W. Zandvliet, Pantelis Bampoulis, Yu Pan, Fan Li, Xia Wang, Payton Downey, Alessandro Molle   +9 more
wiley   +1 more source

Dual Band Optimization and Defect Engineering Enable Ultrahigh Thermoelectric Performance in Filled Skutterudites

Advanced Energy Materials, EarlyView.
A synergistic dual‐modulation strategy is employed in Yb‐filled skutterudites through concurrent indium filling and tellurium doping to optimize electronic band structure and phonon scattering. Cooperative band convergence and nanoprecipitate‐induced lattice distortions yield a high zT of 1.72 and enable an ultra‐efficient thermoelectric device with 8 ...
Xuri Rao, Jianrui Wang, Xiao‐Bo Tan, Rui‐Heng Li, Huangshui Ma, Yu Yin, Fan Feng, Pingan Song, Min Hong, Jiaqing He, Ran Ang   +10 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Real-time Road Anomaly Detection using Advanced Sensor Networks

Abstract Real-time road anomaly detection is a critical aspect of modern urban transportation systems, aiming to enhance road safety and traffic management. In this paper, we propose an innovative methodology that integrates advanced sensor networks and machine learning algorithms to achieve accurate and efficient anomaly detection.
Ali Rahmani, Fatima Al-Farsi, Wei Chen, Zhou Shen   +3 more
openaire   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

opXRD: Open Experimental Powder X‐Ray Diffraction Database

Advanced Intelligent Discovery, EarlyView.
We introduce the Open Experimental Powder X‐ray Diffraction Database, the largest openly accessible collection of experimental powder diffractograms, comprising over 92,000 patterns collected across diverse material classes and experimental setups. Our ongoing effort aims to guide machine learning research toward fully automated analysis of pXRD data ...
Daniel Hollarek, Henrik Schopmans, Jona Östreicher, Jonas Teufel, Bin Cao, Adie Alwen, Simon Schweidler, Mriganka Singh, Tim Kodalle, Hanlin Hu, Gregoire Heymans, Maged Abdelsamie, Arthur Hardiagon, Alexander Wieczorek, Siarhei Zhuk, Ruth Schwaiger, Sebastian Siol, François‐Xavier Coudert, Moritz Wolf, Carolin M. Sutter‐Fella, Ben Breitung, Andrea M. Hodge, Tong‐yi Zhang, Pascal Friederich   +23 more
wiley   +1 more source