Results 201 to 210 of about 561,904 (322)

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

Do AI-based contouring algorithms influence physicians in the online adaptive radiotherapy of patients with bladder cancer? [PDF]

Tech Innov Patient Support Radiat Oncol
Guberina N, Khouya A, Hoffmann C, Fischedick G, Alberti Y, Hlouschek J, Freisleben F, Herz A, Ton MTT, Kiwitt LO, Sahin EC, Santiago Garcia A, Gauler T, Pöttgen C, Guberina M, Stuschke M.   +15 more
europepmc   +1 more source

Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure

Advanced Engineering Materials, EarlyView.
Strategic geometric reinforcement transforms auxetic performance. This study evaluates 3D‐printed arrowhead metastructures, revealing that a modified design with local ring reinforcement suppresses premature failure to achieve superior energy absorption and structural efficiency.
Muhammad Gulzari, Supharoek Sornsomrit, Muhammad Ayaz Akbar, Stephan Rudykh   +3 more
wiley   +1 more source

Model-Driven Deep Learning Enables Speckle-Free Holography for 3D Parallel Nanofabrication. [PDF]

Research (Wash D C)
Liu K, Ouyang W, Chen C, Wu J, Cao L, Chen SC.   +5 more
europepmc   +1 more source

Inverse Identification of Energy‐Dependent Laser Absorptivity in NiTi Laser Powder‐Bed Fusion via Calibrated Melt Pool Simulation

Advanced Engineering Materials, EarlyView.
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi, Hadi Moutablaleh, Ignatius A. Setiawan, Mehrshad Mehrpouya   +3 more
wiley   +1 more source

Deep Learning-Based Tracking of Neurovascular Features Toward Semi-Automated Ultrasound-Guided Peripheral Nerve Blocks by Non-Specialists. [PDF]

Bioengineering (Basel)
Gjesteby LA, Carruthers A, Werblin J, DeLosa N, Bedolla C, Wolak M, Roop BW, Slavkovsky E, Hernandez Torres SI, Amezcua KL, Snider EJ, Kesner SB, Telfer BA, Kirkwood BJ, Brattain LJ.   +14 more
europepmc   +1 more source

Algorithms and Data Structures

, 1999
openaire   +2 more sources

Compatibility of Methacrylate Based Resins Controls Interfacial Failure and Toughness in 3D‐Printed Multimaterial Composites

Advanced Engineering Materials, EarlyView.
This work shows that the mechanical performance of multimaterial digital light processing (DLP) printed thermoset composites is governed by resin compatibility and interfacial design rather than spatial patterning alone. Brittle and ductile resin combinations produced premature interfacial failure, while graded interfaces and mechanically compatible ...
Ahmed M. H. Ibrahim, Li Meng, Ahmad R. Najafi, Nicolas J. Alvarez   +3 more
wiley   +1 more source

Benchmarking Spatial Clustering Methods for Mass Spectrometry-Based Spatial Metabolomics. [PDF]

Metabolites
Lu Y, Mei Z, Deng H, Zhao Y, Feng C, Liu S.   +5 more
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