Results 161 to 170 of about 44,871 (219)

FastNano Liquid: An Automated Platform for Small‐Angle X‐ray Scattering‐Based Materials Discovery

Advanced Engineering Materials, EarlyView.
We present FastNano Liquid, an automated small‐ and wide‐angle X‐ray scattering platform for the combined synthesis and characterization of (nano)materials. The platform is coupled to varied reactor workflows for both in situ studies of reaction kinetics and ex situ screening of synthesis conditions to support machine learning‐guided exploration ...
Pierre‐Baptiste Flandrin, Émeline Cournède, Jens Krarup, Michael Lesa, Foyzul Hasan, Amandine Séné, Arnaud Lahouati, David Benhaiem, Jérémie‐Luc Sanchez, Simon Delacroix, Thierry Gacoin, Fabienne Testard, Damien Faivre, David Carriere, Corinne Chevallard, Olivier Taché, Mark A. Levenstein   +16 more
wiley   +1 more source

Women's preferences for HPV self-sampling in cervical cancer screening: a discrete choice experiment. [PDF]

Front Public Health
Ding N, Chen Y, Zhou X, Wang G, Li J, Wang X.   +5 more
europepmc   +1 more source

Impact of the Process Atmosphere During Hot Isostatic Pressing on the Near‐Surface Composition of an Additively Manufactured Austenitic High‐Interstitial Steel

Advanced Engineering Materials, EarlyView.
A high interstital austenitic steel is additively manufactured and postdensified by HIP to eliminate gas porosity. Thereby, the loss of N and Mn in Ar HIP atmosphere is investigated. Further, HIP using N2 atmosphere is investigated which led to excessive nitride formation.
F. Großwendt, J. Hahn, J. Kimm, S. Weber, J. Lentz   +4 more
wiley   +1 more source

Explaining Individual Differences in Metacognitive Monitoring: A Multilevel Analysis of Person-Level Predictors Across Academic Assessments. [PDF]

J Intell
Chen J, Zhang Q, Yin Y, Turner JE, Luo L, Yang C.   +5 more
europepmc   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

Time after time, the best-worst scaling method is more reliable than ranking. [PDF]

Behav Res Methods
Liang G, Glover M, Hawkins GE.
europepmc   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source

Exploring the Perspectives of Different Professions on Task-Based Upper-Limb Prosthesis Assessment Techniques. [PDF]

J Multidiscip Healthc
Siegel JR, Gavrilov MG, Roberts A, Waraich SA, Whittle RS, Schofield JS.   +5 more
europepmc   +1 more source