Monolithically integrated near-infrared InGaAa and mid-infrared quantum well infrare photodetector array

2007 ◽  
Author(s):  
S. V. Bandara ◽  
S. D. Gunapala ◽  
D. Z. Ting ◽  
J. K. Liu ◽  
C. J. Hill ◽  
...  
Keyword(s):  
Quantum Well ◽  
Near Infrared ◽  
Mid Infrared ◽  
Monolithically Integrated ◽  
Photodetector Array

Monolithically integrated near-infrared and mid-infrared detector array for spectral imaging

2007 ◽  
Vol 50 (2-3) ◽  
pp. 211-216 ◽  
Author(s):  
S.V. Bandara ◽  
S.D. Gunapala ◽  
D.Z. Ting ◽  
J.K. Liu ◽  
C.J. Hill ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Detector ◽  
Spectral Imaging ◽  
Detector Array ◽  
Mid Infrared ◽  
Monolithically Integrated ◽  
Infrared Detector Array

Monolithically integrated near-infrared and mid-infrared detector array

2005 ◽  
Author(s):  
S. V. Bandara ◽  
S. D. Gunapala ◽  
D Z. Ting ◽  
J. K. Liu ◽  
C. J. Hill ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Detector ◽  
Detector Array ◽  
Mid Infrared ◽  
Monolithically Integrated ◽  
Infrared Detector Array

A germanium photodetector array for the near infrared monolithically integrated with silicon CMOS readout electronics

2003 ◽  
Vol 16 (3-4) ◽  
pp. 614-619 ◽  
Author(s):  
Gianlorenzo Masini ◽  
Valentino Cencelli ◽  
Lorenzo Colace ◽  
Francesco DeNotaristefani ◽  
Gaetano Assanto
Keyword(s):  
Near Infrared ◽  
Readout Electronics ◽  
Monolithically Integrated ◽  
Photodetector Array ◽  
Silicon Cmos

Dilute nitride type-II 'W' quantum well lasers for the near-infrared and mid-infrared

2005 ◽  
Author(s):  
Jerry R. Meyer ◽  
Igor Vurgaftman ◽  
Anish A. Khandekar ◽  
B. E. Hawkins ◽  
J. Y. Yeh ◽  
...  
Keyword(s):  
Quantum Well ◽  
Near Infrared ◽  
Quantum Well Lasers ◽  
Dilute Nitride ◽  
Type Ii ◽  
Mid Infrared

Mid and near Infrared Study of Carbohydrates by Canonical Correlation Analysis

1993 ◽  
Vol 1 (2) ◽  
pp. 99-108 ◽  
Author(s):  
P. Robert ◽  
M.F. Devaux ◽  
A. Qannari ◽  
M. Safar
Keyword(s):  
Correlation Analysis ◽  
Infrared Spectra ◽  
Canonical Correlation ◽  
Near Infrared ◽  
Sugar Content ◽  
Infrared Region ◽  
Total Sugar ◽  
Mid Infrared ◽  
Total Sugar Content ◽  
Near Infrared Spectra

Multivariate data treatments were applied to mid and near infrared spectra of glucose, fructose and sucrose solutions in order to specify near infrared frequencies that characterise each carbohydrate. As a first step, the mid and near infrared regions were separately studied by performing Principal Component Analyses. While glucose, fructose and sucrose could be clearly identified on the similarity maps derived from the mid infrared spectra, only the total sugar content of the solutions was observed when using the near infrared region. Characteristic wavelengths of the total sugar content were found at 2118, 2270 and 2324 nm. In a second step, the mid and near infrared regions were jointly studied by a Canonical Correlation Analysis. As the assignments of frequencies are generally well known in the mid infrared region, it should be useful to study the relationships between the two infrared regions. Thus, the canonical patterns obtained from the near infrared spectra revealed wavelengths that characterised each carbohydrate. The OH and CH combination bands were observed at: 2088 and 2332 nm for glucose, 2134 and 2252 nm for fructose, 2058 and 2278 nm for sucrose. Although a precise assignment of the near infrared bands to chemical groups within the molecules was not possible, the present work showed that near infrared spectra of carbohydrates presented specific features.

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