Results 11 to 20 of about 13,100,253 (279)

Determination of the energy loss function of tungsten from reflection electron energy loss spectroscopy spectra

open access: yesResults in Physics
We incorporate experimental reflection electron energy loss spectroscopy (REELS) spectrum data with theoretical analysis to precisely determine the energy loss function (ELF) of tungsten (W) in the energy loss range of 0.1–110 eV at the incident electron
Z. Li   +5 more
doaj   +5 more sources

Analysis of Plasmon Loss Peaks of Oxides and Semiconductors with the Energy Loss Function. [PDF]

open access: yesMaterials (Basel), 2023
This paper highlights the use and applications of the energy loss function (ELF) for materials analysis by using electron energy loss spectroscopy (EELS). The basic Drude–Lindhart theory of the ELF is briefly presented along with reference to reflection electron energy loss (REELS) data for several dielectric materials such as insulating high-k binary ...
Costantini JM, Ribis J.
europepmc   +5 more sources

Energy-loss Function for Lead [PDF]

open access: yesCommunications in Physics, 2017
We study the energy-loss function for lead in the framework of the time-dependent density functional theory, using the full-potential linearized augmented plane-wave plus local orbitals method. The ab initio calculations are performed in the adiabatic local density approximation.
Hieu T. Nguyen-Truong   +4 more
core   +4 more sources

Retrieving the energy-loss function from valence electron energy-loss spectrum: Separation of bulk-, surface-losses and Cherenkov radiation

open access: yesUltramicroscopy, 2018
With recent rapid advancement in electron microscopy instrumentation, in particular, bright electron sources and monochromators, valence electron energy-loss spectroscopy (VEELS) has become attractive for retrieving band structures, optical properties, dielectric functions and phonon information of materials.
Qingping, Meng   +3 more
openaire   +5 more sources

Optimizing the Neural Network Loss Function in Electrical Tomography to Increase Energy Efficiency in Industrial Reactors

open access: yesEnergies
This paper presents innovative machine-learning solutions to enhance energy efficiency in electrical tomography for industrial reactors. Addressing the key challenge of optimizing the neural model’s loss function, a classifier tailored to precisely ...
Monika Kulisz   +5 more
doaj   +3 more sources

Energy-loss function of TTF-TCNQ

open access: yesOpen Physics, 2012
Abstract We investigate the energy-loss function for a previously developed model of quasi-one-dimensional metals with two one-dimensional electron bands per donor and acceptor chains and the three-dimensional long-range Coulomb electron-electron interaction within the random phase approximation.
Lošić Željana
doaj   +2 more sources

Electron energy-loss spectroscopy: DFT modelling and application to experiment [PDF]

open access: yes, 2010
The all-electron density functional theory (DFT) code Wien2k has an established track record of modelling energy-loss near-edge structure (ELNES). The pseudopotential DFT code CASTEP can reproduce results found using Wien2k.
Seabourne, Che Royce
core   +7 more sources

Loss functions, utility functions and Bayesian sample size determination. [PDF]

open access: yes, 2011
PhDThis thesis consists of two parts. The purpose of the first part of the research is to obtain Bayesian sample size determination (SSD) using loss or utility function with a linear cost function. A number of researchers have studied the Bayesian SSD
Islam, A. F. M. Saiful
core   +4 more sources

Loss function for image segmentation [PDF]

open access: yes, 2022
openQuesta trattazione si pone due obiettivi: Il primo obiettivo consiste nell’analisi del comportamento di una rete neurale volta alla segmentazione di immagini di polipi al colon, ovvero il processo di delineare e discriminare accuratamente la regione ...
LORENZON, NICOLA
core  

Stein-Rule Estimation under an Extended Balanced Loss Function [PDF]

open access: yes, 2007
This paper extends the balanced loss function to a more general set up. The ordinary least squares and Stein-rule estimators are exposed to this general loss function with quadratic loss structure in a linear regression model.
Toutenburg, Helge   +3 more
core   +1 more source

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