abstract

• In this work, an innovative cathodoluminescence (CL) system is coupled to a scanning electron microscope and synchronized with a Raspberry Pi computer integrated with an innovative processing signal. The post-processing signal is based on a Python algorithm that correlates the CL and secondary electron (SE) images with a precise dwell time correction. For CL imaging, the emission signal is collected through an optical fiber and transduced to an electrical signal via a photomultiplier tube (PMT). CL Images are registered in a panchromatic mode and can be filtered using a monochromator connected between the optical fiber and the PMT to produce monochromatic CL images. The designed system has been employed to study ZnO samples prepared by electrical arc discharge and microwave methods. CL images are compared with SE images and chemical elemental mapping images to correlate the emission regions of the sample. © 2018 Author(s).

authors

• Benitez A.
• Ponce A.
• Sanchez J.E.
• Santiago U.

publication date

• 2018-01-01

funding provided via

• Consejo Nacional de Ciencia y Tecnología, CONACYT: 382259  Grant
• National Institute on Minority Health and Health Disparities, NIMHD: G12MD007591  Grant

published in

• Review of Scientific Instruments  Journal

keywords

• Optical fibers; Photomultipliers; Scanning electron microscopy; Zinc compounds; Cathodoluminescence images; Electrical signal; Elemental mapping; Microwave methods; Photomultiplier tube; Post processing; Processing signal; Secondary electron images; Cathodoluminescence

Digital Object Identifier (DOI)

• 10.1063/1.4986044

PubMed ID

• 29390658

start page

end page

volume

• 89

issue

• 1