Results 91 to 100 of about 331,435 (254)

Molecular Dynamics Studies of Shape Memory Polymers: From Bead–Spring Models to Atomistic Simulations

Advanced Engineering Materials, EarlyView.
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley   +1 more source

The Effect of Different Field of View Sizes on Contrast-to-Noise Ratio of Cone-Beam Computed Tomography Units: An In-Vitro Study. [PDF]

Front Dent, 2022
Niktash A, Mehralizadeh S, Talaeipour A.
europepmc   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Evaluation of Posture-Dependent Signal Intensity and Contrast Alterations in Low-Field Brain Magnetic Resonance Imaging

Diagnostics
Background/Objectives: Most brain magnetic resonance imaging (MRI) is performed in supine position, although posture may influence cerebrovascular signal characteristics through gravity-related physiological changes.
Chang-Soo Yun, Changheun Oh, Kyuseok Kim, Seong-Hyeon Kang, Hajin Kim, Youngjin Lee, Jun-Young Chung, Gun Choi   +7 more
doaj   +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

Assessment of subjective image quality, contrast to noise ratio and modulation transfer function in the middle ear using a novel full body cone beam computed tomography device. [PDF]

BMC Med Imaging, 2023
Heikkinen AK, Rissanen V, Aarnisalo AA, Nyman K, Sinkkonen ST, Koivisto J.   +5 more
europepmc   +1 more source

Triple Junctions as Dislocation‐Like Defects: The Role of Grain Boundary Crystallography Revealed by Experiment and Atomistic Simulation

Advanced Engineering Materials, EarlyView.
Grain boundary triple junctions are an essential ingredient of the microstructure of polycrystalline materials. In this study, a triple junction is observed using atomic‐resolution scanning transmission electron microscopy and characterized. Computer simulations reveal that the junction has a dislocation character that is determined by the joining ...
Tobias Brink, Saba Saood, Peter Schweizer, Jörg Neugebauer, Gerhard Dehm   +4 more
wiley   +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

Influence of Scan Strategies in Electron Beam Powder Bed Fusion on Solidification, Microstructure, and High‐Temperature Compressive Properties of γ′‐Strengthened Inconel 738LC

Advanced Engineering Materials, EarlyView.
Experiments and thermophysical simulations were conducted to investigate the electron beam powder bed fusion electron beam (PBF‐EB/M) process for the γ′‐strengthened nickel‐based superalloy Inconel 738LC. The results demonstrate the impact of process‐induced microstructural variations on high‐temperature mechanical behavior, providing a basis for ...
Jan Niklas Petenati, Karthik Kumar Banku, Prasanth Bondi, Ivan Zhirnov, Yangyiwei Yang, Gordon Schmidt, Jürgen Christen, Georg Hasemann, Manja Krüger, Bai‐Xiang Xu, Bilal Gökce, Silja‐Katharina Rittinghaus   +11 more
wiley   +1 more source

Initial quality performance results using a phantom to simulate chest computed radiography

Journal of Medical Physics, 2011
The aim of this study was to develop a homemade phantom for quantitative quality control in chest computed radiography (CR). The phantom was constructed from copper, aluminium, and polymenthylmethacrylate (PMMA) plates as well as Styrofoam materials ...
Muhogora Wilbroad, Padovani Renato, Msaki Peter   +2 more
doaj