Results 141 to 150 of about 446,106 (266)

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

A machine learning ensemble framework based on a clustering algorithm for improving electric power consumption performance. [PDF]

Sci Rep
Sim T, Ryu S, Lee D, Lee S, Chun CJ, Moon H.   +5 more
europepmc   +1 more source

Artificial optical synaptic devices with ultra-low power consumption. [PDF]

Light Sci Appl, 2023
Li G.
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

A near-real time daily European Power Consumption and Carbon Intensity Dataset (ECON-PowerCI). [PDF]

Sci Data
Zhang S, Zhao W, Zhu B, Yan C, Song X, Jiang H, Fang J, Ciais P, Xuan N, Gentine P, Davis SJ, Liu Z, Qiu GY.   +12 more
europepmc   +1 more source

Dataset of 15-minute values of active and reactive power consumption of 1000 households during single year. [PDF]

Data Brief, 2023
Cenký M, Bendík J, Cintula B, Janiga P, Eleschová Ž, Beláň A.   +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

Minimizing Delay and Power Consumption at the Edge. [PDF]

Sensors (Basel)
Gelenbe E.
europepmc   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

Drying kinetics, power consumption, economic and environmental analysis of pomegranate peels drying using a hybrid solar dryer compared with oven dryer. [PDF]

Sci Rep
Metwally KA, Khater EG, Bahnasawy AH, Tantawy AA, Elbeltagi A, Salem A, Marey SA, Okasha AM, Ali KAM, Elwakeel AE.   +9 more
europepmc   +1 more source