Results 121 to 130 of about 15,636,570 (229)

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

Virtual Patients from the Learner's Perspective: A Convergent Parallel Mixed Method Study Utilizing Evaluation of Technology-enhanced Learning Materials. [PDF]

Acta Med Philipp
Mendoza RD, Reyes LB, Awayan-Lat AD.
europepmc   +1 more source

High‐Entropy Alloy Interlayers Toward Advanced Joining for High‐Performance Structural Applications: Current Progress and Emerging Challenges

Advanced Engineering Materials, EarlyView.
HEA interlayers offer a versatile route for joining high‐performance structural materials. Their compositional and structural design regulates interfacial reactions, suppresses brittle IMCs, and improves metallurgical bonding. Sandwich interlayers further integrate defect healing with precipitation strengthening, enabling improved strength–ductility ...
Lin Yuan, Jiafen Song, Jinglong Li, Jiangtao Xiong, Tao Yang   +4 more
wiley   +1 more source

Comparing the outcomes of the technology-enhanced learning of sectional anatomy with and without preceding demonstrations: A study about the worked-example effect in anatomy education. [PDF]

Anat Sci Educ
Fonseca GRBC, Tipoe GL, Ganotice FA.
europepmc   +1 more source

Technology-enhanced learning: Principles and products

, 2009
Technology-enhanced learning is a timely topic, the importance of which is recognized by educational researchers, practitioners, software designers, and policy makers. This volume presents and discusses current trends and issues in technology-enhanced learning from a European research and development perspective. This multifaceted and multidisciplinary
Balacheff, Nicolas, Ludvigsen, Sten, de Jong, Ton, Lazonder, Ard, Barnes, Sally   +4 more
openaire   +2 more sources

Stretching the Printability Metric in Direct‐Ink Writing with Highly Extensible Yield‐Stress Fluids

Advanced Functional Materials, EarlyView.
This study introduces “drawability” as a new metric for assessing printability in direct‐ink writing, focusing on gap‐spanning performance and speed robustness. By designing yield‐stress fluids with high extensibility, we demonstrate that extensional strain‐to‐break significantly enhances printability.
Chaimongkol Saengow, Samya Sen, Joaquin Yus, Eliza E. Lovrich, Amanda G. Hoika, Kelly M. Chang, Arielle A. Pfeil, Nellie Haug, Amy J. Wagoner Johnson, Randy H. Ewoldt   +9 more
wiley   +1 more source

Contextualizing institutional strategies for technology enhanced learning

, 2016
An analysis of strategic planning documents for public universities in Australia identifies some patterns in institutional strategies for technology-enhanced learning (TEL).
Russell, Carol (R16902)
core  

Technology-enhanced learning frequency and perceived academic acceleration in AI-mediated digital learning environments: self-efficacy as an indirect pathway and learning motivation as a boundary condition. [PDF]

Front Psychol
Chen X, Qi Z, Ou Y.
europepmc   +1 more source

Using medical reality television as a technology-enhanced learning strategy to provide authentic patient care experiences during clinical placements: a case study research investigation. [PDF]

BMC Med Educ, 2021
Osborne F, Harrison M, Fisher J, Bateman B.   +3 more
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