Results 161 to 170 of about 5,806,860 (302)

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

Chemical bonding manipulation unlocks high performance ionic-bonded thermoelectrics. [PDF]

Nat Commun
Li H, Lyu S, Li X, Xia Y, Liu K, Sun Y, Wang M, Cheng J, Wang W, Shen D, Wu H, Chen C, Zhang Q, Chen Y.   +13 more
europepmc   +1 more source

Electrochemical Behavior of Flame‐Sprayed Sc‐Doped AlCoCrFeMo High‐Entropy Alloy Coatings in 3.5% Sodium Chloride Solution

Advanced Engineering Materials, EarlyView.
Scandium (Sc)‐doped AlCoCrFeMo HEA coatings are fabricated via flame spraying with 0.1, 0.3, and 0.5 wt% Sc additions. Among these, the HEA‐Sc0.3 coating exhibits the highest corrosion resistance, indicated by a more positive corrosion potential and lower current density.
Pankaj Kumar, Akash Vyas, Mohammad Aatif Qazi, Nashit Jalal, Maria Ophelia Jarligo, Mostafa Yakout, Jing Liu, André McDonald   +7 more
wiley   +1 more source

Structure, Stability, Spectroscopy and Chemical Bonding Analyses on the Novel X₆ (X = N, P, As, Sb, Bi) Molecules. [PDF]

J Comput Chem
Cheng Y, Zhang SW, Dai XY, Zhang YY.
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

The Predictive Power of Chemical Bonding Analysis in Materials: A Perspective on Optoelectronic Properties. [PDF]

J Am Chem Soc
Saleh G, Manna L.
europepmc   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

Enhanced chemical bonding of copper-line treated by non-etching alkaline oxidation for high-frequency signal transmission. [PDF]

iScience
Huang J, Zou W, Di M, Zhou G, Hong Y, Wang S, He W, Yang W, Wen Z, Han Z, Li Z, Lin T.   +11 more
europepmc   +1 more source

High‐Resolution Corrosion Fingerprinting of Alloy Libraries via Microdroplet Spectroelectrochemistry

Advanced Engineering Materials, EarlyView.
Ionic‐liquid microdroplet spectroelectrochemistry enables stable, localized electrochemical measurements over extended timescales. By coupling impedance spectroscopy, wetting analysis, finite‐element simulations, and operando Raman spectroscopy, it disentangles geometrical and electrochemical effects, opening new opportunities for rapid corrosion ...
Ekaterina Kurchavova, Oumaïma Gharbi, Mireille Turmine, Vincent Vivier   +3 more
wiley   +1 more source

Correlation-Driven d-Band Modifications Promote Chemical Bonding at 3d-Ferromagnetic Surfaces. [PDF]

Small
Janas DM, Windischbacher A, Sala A, Feyer V, Cojocariu I, Gruber M, Bouatou M, Droghetti A, Puschnig P, Zamborlini G, Cinchetti M.   +10 more
europepmc   +1 more source