Implementation of a novel low-noise InGaAs detector enabling rapid near-infrared multichannel Raman spectroscopy of pigmented biological samples

2015 ◽  
Vol 46 (7) ◽  
pp. 652-660 ◽  
Author(s):  
Inês P. Santos ◽  
Peter J. Caspers ◽  
Tom Bakker Schut ◽  
Remco van Doorn ◽  
Senada Koljenović ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Biological Samples ◽  
Near Infrared ◽  
Low Noise ◽  
Ingaas Detector

scholarly journals Gold nanoparticles as a substrate in bio-analytical near-infrared surface-enhanced Raman spectroscopy

The Analyst ◽  
2015 ◽  
Vol 140 (9) ◽  
pp. 3090-3097 ◽  
Author(s):  
Holly J. Butler ◽  
Simon W. Fogarty ◽  
Jemma G. Kerns ◽  
Pierre L. Martin-Hirsch ◽  
Nigel J. Fullwood ◽  
...  
Keyword(s):  
Gold Nanoparticles ◽  
Raman Spectroscopy ◽  
Biological Samples ◽  
Near Infrared ◽  
Surface Enhanced Raman Spectroscopy ◽  
Starting Point ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Good Starting Point

“Large” nanoparticles potentially are a good starting point in order to derive informative NIR/IR SERS analysis of biological samples.

Infrared and Visible—Near Infrared Electroluminescence Developments for FA in AlGaN/GaN HEMTS on SiC

2010 ◽  
Author(s):  
M. Bouya ◽  
D. Carisetti ◽  
J.C. Clement ◽  
N. Malbert ◽  
N. Labat ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Near Infrared ◽  
High Electron Mobility Transistor ◽  
Low Noise ◽  
Civil Defense ◽  
Base Stations ◽  
Infrared Range ◽  
High Electron ◽  
Radar Applications ◽  
Gan Hemts

Abstract HEMT (High Electron Mobility Transistor) are playing a key role for power and RF low noise applications. They are crucial components for the development of base stations in the telecommunications networks and for civil, defense and space radar applications. As well as the improvement of the MMIC performances, the localization of the defects and the failure analysis of these devices are very challenging. To face these challenges, we have developed a complete approach, without degrading the component, based on front side failure analysis by standard (Visible-NIR) and Infrared (range of wavelength: 3-5 µm) electroluminescence techniques. Its complementarities and efficiency have been demonstrated through two case studies.

scholarly journals Applications of Vibrational Spectroscopy for Analysis of Connective Tissues

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 922
Author(s):  
William Querido ◽  
Shital Kandel ◽  
Nancy Pleshko
Keyword(s):  
Raman Spectroscopy ◽  
Vibrational Spectroscopy ◽  
Near Infrared ◽  
Ex Vivo ◽  
Biological Tissues ◽  
Label Free ◽  
Connective Tissues ◽  
Bone Properties ◽  
Composition And Structure

Advances in vibrational spectroscopy have propelled new insights into the molecular composition and structure of biological tissues. In this review, we discuss common modalities and techniques of vibrational spectroscopy, and present key examples to illustrate how they have been applied to enrich the assessment of connective tissues. In particular, we focus on applications of Fourier transform infrared (FTIR), near infrared (NIR) and Raman spectroscopy to assess cartilage and bone properties. We present strengths and limitations of each approach and discuss how the combination of spectrometers with microscopes (hyperspectral imaging) and fiber optic probes have greatly advanced their biomedical applications. We show how these modalities may be used to evaluate virtually any type of sample (ex vivo, in situ or in vivo) and how “spectral fingerprints” can be interpreted to quantify outcomes related to tissue composition and quality. We highlight the unparalleled advantage of vibrational spectroscopy as a label-free and often nondestructive approach to assess properties of the extracellular matrix (ECM) associated with normal, developing, aging, pathological and treated tissues. We believe this review will assist readers not only in better understanding applications of FTIR, NIR and Raman spectroscopy, but also in implementing these approaches for their own research projects.

Application of FT-Raman spectroscopy to the study of selected organometallic complexes and proteins

1990 ◽  
Vol 68 (7) ◽  
pp. 1196-1200 ◽  
Author(s):  
Steven M. Barnett ◽  
François Dicaire ◽  
Ashraf A. Ismail
Keyword(s):  
Raman Spectroscopy ◽  
Near Infrared ◽  
Metal Carbonyl ◽  
Protein A ◽  
Organometallic Complexes ◽  
Laser Source ◽  
Chromium Tricarbonyl ◽  
Ft Raman Spectroscopy ◽  
Arene Chromium Tricarbonyl ◽  
Ft Raman

The study of colored organometallic complexes by dispersive Raman spectroscopy has been limited due to fluorescence or photodecomposition caused by the visible laser used as the excitation source. As a solution to this problem, FT-Raman spectroscopy with a near-infrared laser source has been useful in lowering fluorescence or photolysis in these samples. To investigate the utility of this technique, we have obtained and assigned the FT-Raman spectra of a series of arene chromium tricarbonyl complexes and of cyclopentadienyl manganese tricarbonyl. Some bands previously unobserved by dispersive Raman spectroscopy were seen, including a band assigned to a 13CO satellite in the spectrum of methylbenzoate chromium tricarbonyl. In addition, FT-Raman data for bovine serum albumin (BSA) and Protein-A are presented. Keywords: FT-Raman spectroscopy, metal carbonyl, proteins, organometallics, near infrared.

Near-infrared Raman spectroscopy to detect anti- Toxoplasma gondii antibodies in blood sera of domestic cats

2001 ◽  
Author(s):  
Janaina Duarte ◽  
Marcos T. T. Pacheco ◽  
Landulfo Silveira, Jr. ◽  
Rosangela Z. Machado ◽  
Rodrigo A. L. Martins ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Toxoplasma Gondii ◽  
Near Infrared ◽  
Domestic Cats

In vivo detection of cervical dysplasia with near-infrared Raman spectroscopy

2002 ◽  
Author(s):  
Amy Robichaux ◽  
Chad A. Lieber ◽  
Heidi Shappell ◽  
Beth Huff ◽  
Howard Jones III ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Near Infrared ◽  
Cervical Dysplasia

scholarly journals Deriving accurate molecular indicators of protein synthesis through Raman-based sparse classification

The Analyst ◽  
2021 ◽  
Author(s):  
Nicolas Pavillon ◽  
Nicholas I Smith
Keyword(s):  
Machine Learning ◽  
Raman Spectroscopy ◽  
Protein Synthesis ◽  
Biological Samples ◽  
Molecular Information ◽  
Molecular Indicators ◽  
Sparse Classification

Raman spectroscopy has the ability to retrieve molecular information from live biological samples non-invasively through optical means. Coupled with machine learning, it is possible to use this large amount of...

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