New moldable glasses for multispectral optics (Conference Presentation)

Shyam S. Bayya; Daniel Gibson; Vinh Nguyen; Jasbinder Sanghera; Mikhail Kotov; Collin McClain; Jay Vizgaitis

doi:10.1117/12.2321177

17 September 2018 New moldable glasses for multispectral optics (Conference Presentation)

Shyam S. Bayya, Daniel Gibson, Vinh Nguyen, Jasbinder Sanghera, Mikhail Kotov, Collin McClain, Jay Vizgaitis

Proceedings Volume 10743, Optical Modeling and Performance Predictions X; 1074309 (2018) https://doi.org/10.1117/12.2321177
Event: SPIE Optical Engineering + Applications, 2018, San Diego, California, United States

Abstract

There is a strong desire to reduce size and weight of single and multiband IR imaging systems in ISR operations on hand-held, helmet mounted or airborne platforms. NRL is developing new IR glasses that transmit from 0.9 to < 12 µm in wavelength, with refractive index ranging from 2.38 to 3.17, to expand the glass map and provide compact solutions to multispectral imaging systems. These glasses were specifically designed to have comparable glass molding temperatures and thermal properties so that they can be laminated and co-molded into optics with reduced number of air-glass interfaces (lower Fresnel reflection losses). These new NRL glasses also have negative or very low dn/dT, making it easier to athermalize the optical system. Our multispectral optics designs using these new materials demonstrate reduced size, complexity and improved performance. The glass database is now available for distribution. Some of the NRL glasses are also available commercially. This presentation will cover discussions on the new optical materials, multispectral designs, as well fabrication and characterization of new optics.

Conference Presentation

Citation Download Citation

Shyam S. Bayya, Daniel Gibson, Vinh Nguyen, Jasbinder Sanghera, Mikhail Kotov, Collin McClain, and Jay Vizgaitis "New moldable glasses for multispectral optics (Conference Presentation)", Proc. SPIE 10743, Optical Modeling and Performance Predictions X, 1074309 (17 September 2018); https://doi.org/10.1117/12.2321177

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