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Fast Automated Phase Differentiation in Industrial Stainless Steel by Combining Low-Loss EELS Experiments with Machine Learning-based Algorithms

Published online by Cambridge University Press:  30 July 2021

Luc Lajaunie ,
Beatriz Amaya Dolores ,
Ashwin Ramasubramaniam ,
Lorena González-Souto ,
Rafael Sanchez ,
Juan Almagro ,
Javier Botana  and
José Calvino
Luc Lajaunie
Affiliation:
Departamento de Ciencia de los Materiales e Ingeniería Metalúrgica y Química Inorgánica, Facultad de Ciencias, Universidad de Cádiz, Cádiz, Spain
Beatriz Amaya Dolores
Affiliation:
Departamento de Ciencia de los Materiales e Ingeniería Metalúrgica y Química Inorgánica, Facultad de Ciencias, Universidad de Cádiz, Spain
Ashwin Ramasubramaniam
Affiliation:
Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Massachusetts, United States
Lorena González-Souto
Affiliation:
Departamento de Ciencia de los Materiales e Ingeniería Metalúrgica y Química Inorgánica, Facultad de Ciencias, Universidad de Cádiz, Spain
Rafael Sanchez
Affiliation:
ACERINOX EUROPA SAU, Technical Department, Spain
Juan Almagro
Affiliation:
ACERINOX EUROPA SAU, Technical Department, Spain
Javier Botana
Affiliation:
Departamento de Ciencia de los Materiales e Ingeniería Metalúrgica y Química Inorgánica, Facultad de Ciencias, Universidad de Cádiz, Spain
José Calvino
Affiliation:
Departamento de Ciencia de los Materiales e Ingeniería Metalúrgica y Química Inorgánica, Facultad de Ciencias, Universidad de Cádiz, United States

Abstract

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Type
Microscopy and Microanalysis for Real World Problem Solving
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 34 - 36
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

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