ARISTMS: a new automated data acquisition capability to spectrally characterize samples and materials

Michael Wilson; Phil Coulter; Paul Beer

doi:10.1117/12.665653

18 April 2006 ARISTMS: a new automated data acquisition capability to spectrally characterize samples and materials

Michael Wilson, Phil Coulter, Paul Beer

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Proceedings Volume 6205, Thermosense XXVIII; 62050I (2006) https://doi.org/10.1117/12.665653
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

A new capability to acquire large amounts of spectrally determined optical data for a wide range of materials has been designed and developed from commercial off the shelf equipment. The software control system was written using LABVIEW 7.0. The Automated Rasterable Integrated Spectrometric and Total Integrated Scatter Measurement System (ARISTMS) represents a fusion of state-of-the-art technology and systems software to facilitate automated data acquisition to determine a material's spectral characteristics, surface roughness, and absorptance. It was developed as part of an ongoing Phase II SBIR effort to develop diffractively structured gallium arsenide infrared windows that are 100 mm in diameter transmitting between 1 and 10 microns. It was necessary to develop a capability that could scan or raster across the entire surface area of the window, vary the incident spot size, step size, and angle of incidence over the infrared spectrum of interest. The system offers a cost effective capability to screen many samples against preset thresholds for reflectance, transmittance, absorptance, and total integrated scatter for any number of measurement scenarios and sample classes.

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Michael Wilson, Phil Coulter, and Paul Beer "ARISTMS: a new automated data acquisition capability to spectrally characterize samples and materials", Proc. SPIE 6205, Thermosense XXVIII, 62050I (18 April 2006); https://doi.org/10.1117/12.665653

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KEYWORDS

Reflectivity

Transmittance

Spectroscopy

Data acquisition

Mirrors

Sensors

Gold

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