Results 221 to 230 of about 4,436,251 (260)

Investigating the Low‐Temperature Phase Stability of the Binary Ta–W System

Advanced Engineering Materials, EarlyView.
Atomistic simulations show that the binary Ta–W system forms ordered intermetallic phases, B2‐TaW and D03‐TaW3, as 0 K ground states. Configurational entropy, however, lowers the free energy of the disordered bcc solid solution, which becomes the stable phase above about 400 K.
Klemens Lechner, Anna Sophie Jelinek, Velislava Terziyska, Peter Wagatha, Wolfram Knabl, Christian Mitterer, Helmut Clemens, David Holec   +7 more
wiley   +1 more source

Enhancing genomic prediction accuracy in Huaxi cattle through integration of transcriptomic data and a self-attention-based SNP selection strategy. [PDF]

BMC Bioinformatics
Qian L, Du L, Liang M, Li K, Wang J, Qiu S, Mao M, Zhang L, Gao X, Xu L, Zheng C, Zhu B, Chen Y, Wang Z, Li J, Gao H.   +15 more
europepmc   +1 more source

Elastic–Plastic Modeling and Experimental Characterization of Granular Jamming Actuators

Advanced Engineering Materials, EarlyView.
Granular jamming enables rapid switching between soft and rigid mechanical states. Here, a reduced‐order elastic‐perfectly‐plastic beam framework captures pressure‐dependent loading, unloading, residual deformation, and hysteresis in jammed beams, while matching three‐point bending experiments across materials and geometries. The framework links design
Saheli Patel, Prashant K. Purohit, Jordan R. Raney   +2 more
wiley   +1 more source

Decomposition prediction and optimal ensemble strategy improve river dissolved oxygen prediction accuracy. [PDF]

Sci Rep
Xie Y, Rao Y, Wan J, Huang Q, Lai Q, Lu X, Liu J.   +6 more
europepmc   +1 more source

Thermal Cycle–Microstructure–Property Relationships in Rail Steel Heat‐Affected Zone Simulated by Gleeble

Advanced Engineering Materials, EarlyView.
Microstructural evolution of premium rail steel during flash butt welding (FBW), comparing physically simulated heat‐affected zones with actual weld regions. Thermal cycles induce phase transformations and microstructural heterogeneity that influence weld quality and mechanical performance. These findings provide insights into optimizing FBW parameters
Emmanoelle Cintra da Cunha Araújo, João Marcos da Silva Nunes, Marcelly Cristiny Nunes de Carvalho, Alex Rojas, Cristie Luis Kugelmeier, Cristhian Ricardo Loayza Loayza, João Carlos Ferreira, Maria Veronica Goncalves Rodrigues, Rute Sayuri Kano, Isaac Araújo Furtado, Jacyara Dalylla da Silva Nunes, Jhonatan Peres de Sousa, Marcos Natan da Silva Lima, Eden Santos Silva, Gedeon Silva Reis, Samuel Filgueiras Rodrigues   +15 more
wiley   +1 more source

Polygenic risk score prediction accuracy convergence. [PDF]

HGG Adv
Henches L, Kim J, Yang Z, Rubinacci S, Pires G, Albiñana C, Boetto C, Julienne H, Frouin A, Auvergne A, Suzuki Y, Djebali S, Delaneau O, Ganna A, Vilhjálmsson B, Privé F, Aschard H.   +16 more
europepmc   +1 more source

Investigation of Resonance Characteristics of More Than 10 000 Metal‐Coated Silicon MEMS Cantilevers Using Machine Learning

Advanced Engineering Materials, EarlyView.
More than 10 000 metal‐coated silicon MEMS cantilevers are fabricated and characterized to build a large‐scale experimental dataset spanning multiple vibrational modes. Machine learning algorithms are benchmarked to predict resonance frequency and quality factor, with ensemble based models achieving accuracy approaching experimental uncertainty.
Sina Zare Pakzad, Saurabh Thorat, Andre Loch Gesing, Dominik Huber, Christopher Zellner, Patrick Egger, Georg Pfusterschmied, Ulrich Schmid, Michael Schneider   +8 more
wiley   +1 more source

Learning, prediction accuracy, and neural plasticity in sensory cortex. [PDF]

Curr Opin Neurobiol
Barth AL, Christian JA, Ray A.
europepmc   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source