Results 61 to 70 of about 99,709 (264)

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source

Hardware radial basis function neural network automatic generation

Journal of Computer Science and Technology, 2011
This paper presents a parallel architecture for a radial basis function (RBF) neural network used for pattern recognition. This architecture allows defining sub-networks which can be activated sequentially.
Lucas Leiva, Nelson Acosta
doaj  

Enhanced Strength and Corrosion Resistance of Ti‐13Nb‐12Ta‐10Zr‐4Sn Alloy by Aging Treatment

Advanced Engineering Materials, EarlyView.
This work systematically investigates the effect of aging treatment on mechanical properties and corrosion behavior of vacuum arc‐melted Ti‐13Nb‐12Ta‐10Zr‐4Sn alloy. Owing to the increased α″ martensite, strength and corrosion resistance were significantly enhanced by aging treatment.
Yuhua Li, Rong Zhao, Qian Zhang, Haojie Wang, Yujing Liu, Lai‐Chang Zhang   +5 more
wiley   +1 more source

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

Machine Learning Application of Generalized Gaussian Radial Basis Function and Its Reproducing Kernel Theory

Mathematics
Gaussian Radial Basis Function Kernels are the most-often-employed kernel function in artificial intelligence for providing the optimal results in contrast to their respective counterparts.
Himanshu Singh
doaj   +1 more source

Coking energy consumption radial basis function prediction model improved by differential evolution algorithm

Measurement + Control, 2019
This paper presents a radial basis function prediction model improved by differential evolution algorithm for coking energy consumption process, which is very difficult to get online and real time because of the complex process. In the energy consumption
Wenhua Tao, Jiao Chen, Yunjin Gui, Pingping Kong   +3 more
doaj   +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

Radial Basis Function Networks for Conversion of Sound Spectra

EURASIP Journal on Advances in Signal Processing, 2001
In many advanced signal processing tasks, such as pitch shifting, voice conversion or sound synthesis, accurate spectral processing is required. Here, the use of Radial Basis Function Networks (RBFN) is proposed for the modeling of the spectral changes ...
Carlo Drioli
doaj   +1 more source

Influence of Si Content and Milling Duration on the Microstructure and Mechanical–Tribological Properties of AlCoCrFeNiSi High‐Entropy Alloys

Advanced Engineering Materials, EarlyView.
Si‐doped AlCoCrFeNi high‐entropy alloys are synthesized by mechanical alloying to reveal the effect of Si content and milling time on phase evolution, microstructural refinement, and tribological behavior. A transition from FCC to BCC structure, significant grain refinement, and enhanced hardness and wear resistance are achieved, with the 4 at% Si ...
Mustafa Okumuş, Mehmet Emin Demir, Sercan Özpınar   +2 more
wiley   +1 more source