Results 171 to 180 of about 289,825 (222)

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +1 more source

Machine Learning Applied to High Entropy Alloys under Irradiation

Advanced Engineering Materials, EarlyView.
Designing alloys for extreme environments demands fast, trustworthy prediction. This review charts how machine learning—especially machine‐learned interatomic potentials and predictive models based on experiment‐informed datasets—captures the complexity of high‐entropy alloys in extreme environments, predicts phase formation, mechanical properties, and
Amin Esfandiarpour, Sri Tapaswi Nori, Silvia Bonfanti, Mikko Alava, Antoni Wadowski, Wenyi Huo, Łukasz Kurpaska, Michał Pecelerowicz, Jan S. Wróbel   +8 more
wiley   +1 more source

Review for "Simple click chemistry‐based derivatization to quantify endogenous formaldehyde in milk using ultra‐high‐performance liquid chromatography tandem mass spectrometry in selected reaction monitoring mode"

, 2020
Ana Barros
openalex   +1 more source

Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

Advanced Engineering Materials, EarlyView.
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley   +1 more source

Rapid Bacterial Identification, Resistance, Virulence and Type Profiling using Selected Reaction Monitoring Mass Spectrometry. [PDF]

Sci Rep, 2015
Charretier Y, Dauwalder O, Franceschi C, Degout-Charmette E, Zambardi G, Cecchini T, Bardet C, Lacoux X, Dufour P, Veron L, Rostaing H, Lanet V, Fortin T, Beaulieu C, Perrot N, Dechaume D, Pons S, Girard V, Salvador A, Durand G, Mallard F, Theretz A, Broyer P, Chatellier S, Gervasi G, Van Nuenen M, Roitsch CA, Van Belkum A, Lemoine J, Vandenesch F, Charrier JP.   +30 more
europepmc   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

A computational tool to detect and avoid redundancy in selected reaction monitoring. [PDF]

Mol Cell Proteomics, 2012
Röst H, Malmström L, Aebersold R.
europepmc   +1 more source

MOESM2 of Quantification of angiotensin II-regulated proteins in urine of patients with polycystic and other chronic kidney diseases by selected reaction monitoring

, 2016
Ana Konvalinka, Ihor Batruch, Tomáš Tokár, Apostolos Dimitromanolakis, Shelby Reid, Xuewen Song, York Pei, Andrei P. Drabovich, Eleftherios P. Diamandis, Igor Jurišica, James W. Scholey   +10 more
openalex   +1 more source

First‐Principles Modeling of Solid Solution Softening and Hardening Effects in Al–Mg–Zr–Si Aluminum Alloys

Advanced Engineering Materials, EarlyView.
The role of various alloying elements in face‐centered cubic aluminum on the barrier of a Shockley partial dislocation during its motion is presented. The study aims to understand how alloying atoms such as Mg, Si, and Zr affect the energy landscape for dislocation motion, thus influencing the solid solution hardening and softening in aluminum, which ...
Inna Plyushchay, Zhengqing Wei, Nebahat Bulut, Sibylle Gemming   +3 more
wiley   +1 more source

Laboratory‐Scale Procedure for Evaluating the Flux Efficiency on Melt Cleanliness and Tensile Properties of Recycled Aluminum Alloys

Advanced Engineering Materials, EarlyView.
A laboratory‐scale procedure is developed to evaluate the efficiency of melt‐cleaning and drossing fluxes during aluminium alloy recycling, studying their effects on melt cleanliness and tensile properties of secondary foundry alloys. This work provides a practical tool for foundries and aluminium refiners to assess the efficiency of salt fluxes in ...
Veronica Milani, Giulio Timelli
wiley   +1 more source