Results 201 to 210 of about 396,315 (265)

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

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

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

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

A Tri-Direction Guided Moss Growth Optimizer with Adaptive Differential Evolution for Engineering Design Problems. [PDF]

Biomimetics (Basel)
Pang C, Wang Y, Cheng W.
europepmc   +1 more source

Engineering-Oriented Genetic Algorithm Framework for Ultra-Broadband Metasurface Absorber Inverse Design. [PDF]

Materials (Basel)
Wu L, Zhang D.
europepmc   +1 more source

Sclareol Production Driven by Advanced Synthetic Biology Strategies. [PDF]

ACS Omega
Yu Y, Wang L, Zhang Y, Zhang R, Shah AA, Gong C.   +5 more
europepmc   +1 more source

The Evolution of Artificial Intelligence in Antibody Design: From Structure-Based Engineering to Generative Models. [PDF]

Antibodies (Basel)
Szataniak I, Packi K.
europepmc   +1 more source

Mechanism and Optimization of Quasi-Static Compression Performance in Hexagonal Honeycomb Sandwich Structures. [PDF]

ACS Omega
Hong A, Li H, Song X, Fu Y, Yang Y, Liu Z, Ye X, Yang J.   +7 more
europepmc   +1 more source