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• W4225935100 abstract "Due to their tunable physical and chemical properties, alloys are of fundamental importance in material science. The determination of stoichiometry is crucial for alloy engineering. Classical characterization tools such as energy-dispersive x-ray spectroscopy (EDX) are time consuming and cannot be performed in an ambient atmosphere. In this context, we introduce a new methodology to determine the stoichiometry of alloys from ellipsometric measurements. This approach, based on the analysis of ellipsometric spectra by an artificial neural network (ANN), is applied to electrum alloys. We demonstrate that the accuracy of this approach is of the same order of magnitude as that of EDX. In addition, the ANN analysis is sufficiently robust that it can be used to characterize rough alloys. Finally, we demonstrate that the exploitation of ellipsometric maps with the ANN is a powerful tool to determine composition gradients in alloys." @default.
• W4225935100 created "2022-05-05" @default.
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• W4225935100 date "2022-04-14" @default.
• W4225935100 modified "2023-10-09" @default.
• W4225935100 title "Rapid ellipsometric determination and mapping of alloy stoichiometry with a neural network" @default.
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• W4225935100 doi "https://doi.org/10.1364/ol.457147" @default.
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