A Search for Limonite Near-Infrared Spectral Features on Mars

1966 ◽  
Vol 144 ◽  
pp. 809 ◽  
Author(s):  
Robert L. Younkin
Keyword(s):  
Near Infrared ◽  
Spectral Features ◽  
Infrared Spectral

Investigation of the particle size-dependent near-infrared spectral features of binary mixture samples in conjunction with Monte Carlo simulation and the influence of particle size on the accuracy of quantitative analysis

The Analyst ◽  
2018 ◽  
Vol 143 (18) ◽  
pp. 4306-4315 ◽  
Author(s):  
Pham K. Duy ◽  
Seulah Chun ◽  
Yoonjeong Lee ◽  
Hoeil Chung
Keyword(s):  
Monte Carlo Simulation ◽  
Particle Size ◽  
Monte Carlo ◽  
Quantitative Analysis ◽  
Near Infrared ◽  
Spectral Variation ◽  
Spectral Features ◽  
Size Dependent ◽  
Infrared Spectral ◽  
Mixture Samples

The origin of particle size-induced near-infrared (NIR) spectral variation, which is fundamental for robust quantitative analysis, was systematically studied in conjunction with Monte Carlo simulation.

Prediction of gasoline octane numbers from near-infrared spectral features in the range 660-1215 nm

1989 ◽  
Vol 61 (4) ◽  
pp. 313-320 ◽  
Author(s):  
Jeffrey J. Kelly ◽  
Clyde H. Barlow ◽  
Thomas M. Jinguji ◽  
James B. Callis
Keyword(s):  
Near Infrared ◽  
Spectral Features ◽  
Infrared Spectral

Near‐infrared detection of ammonium minerals

Geophysics ◽  
1987 ◽  
Vol 52 (7) ◽  
pp. 924-930 ◽  
Author(s):  
M. Dennis Krohn ◽  
Stephen P. Altaner
Keyword(s):  
Crystal Structure ◽  
Nitrogen Cycle ◽  
Near Infrared ◽  
Hot Spring ◽  
Ore Deposits ◽  
Infrared Detection ◽  
Spectral Features ◽  
Spectral Bands ◽  
Band Position ◽  
Infrared Spectral

Diagnostic near‐infrared spectral features have been identified for minerals with ammonium [Formula: see text] bound in the crystal structure. Spectral bands near 2.12, 2.02, and 1.56 μm are characteristic of synthetic and natural [Formula: see text] minerals. Laboratory spectra of [Formula: see text] minerals are distinct from spectra of OH‐bearing minerals and have diagnostic shifts in band position among different mineral types. [Formula: see text] minerals were detected at several mineralized hot‐spring deposits in the western U.S. by means of hand‐held and airborne instruments. Near‐infrared detection of [Formula: see text] minerals may provide useful information for prospecting for certain ore deposits and may provide a better understanding of the nitrogen cycle within geologic environments.

scholarly journals Rapid identification of Lactobacillus species using near infrared spectral features of bacterial colonies

2019 ◽  
Vol 27 (4) ◽  
pp. 302-313
Author(s):  
Jiyong Shi ◽  
Xuetao Hu ◽  
Xiaobo Zou ◽  
Zhiming Guo ◽  
Mel Holmes ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Near Infrared ◽  
Rapid Identification ◽  
Lactobacillus Species ◽  
Support Vector ◽  
Spectral Features ◽  
Mid Infrared ◽  
Near Infrared Spectra ◽  
Infrared Spectral ◽  
Chemical Groups

The feasibility of rapid identification of Lactobacillus species using near-infrared spectral features coupled with chemometrics was investigated. First, bacterial colonies of 11 Lactobacillus strains covering four species ( Lactobacillus casei, Lactobacillus reuteri, Lactobacillus brevis, and Lactobacillus fermentum) were cultured using the spread-plate technique. Near-infrared spectra data of the Lactobacillus species were collected directly from the bacterial colonies. Second, 10 wavenumbers were selected from the near-infrared spectra data using uninformative variables elimination and genetic algorithm, and calibration models based on the 10 selected wavenumbers were built using least squares support vector machine. The identification rates for the prediction set and validation set were 89.04 and 85%, respectively. Third, chemical groups of the Lactobacillus cells contributing to the identification of the Lactobacillus strains were identified using mid infrared. The results of mid infrared data analysis indicated that 9 chemical groups could be considered characteristics for categorizing the 11 Lactobacillus strains. The relationship between the 10 selected wavenumbers and identified chemical groups was identified, which supported the satisfactory performance of the least squares support vector machine calibration model. This study demonstrated that near-infrared spectral features of bacterial colonies could be used for Lactobacillus typing at the strain level.

scholarly journals Near‐Infrared Spectral Features in Single‐aged Stellar Populations

2000 ◽  
Vol 532 (1) ◽  
pp. 453-460 ◽  
Author(s):  
R. P. Schiavon ◽  
B. Barbuy ◽  
G. Bruzual A.
Keyword(s):  
Near Infrared ◽  
Stellar Populations ◽  
Spectral Features ◽  
Infrared Spectral

Metastructures for the Giant Enhancement of Raman Scattering in the Near Infrared Spectral Range

JETP Letters ◽  
2020 ◽  
Vol 112 (1) ◽  
pp. 31-36
Author(s):  
V. I. Kukushkin ◽  
V. E. Kirpichev ◽  
E. N. Morozova ◽  
V. V. Solov’ev ◽  
Ya. V. Fedotova ◽  
...  
Keyword(s):  
Raman Scattering ◽  
Spectral Range ◽  
Near Infrared ◽  
Infrared Spectral Range ◽  
Infrared Spectral

scholarly journals ALD Deposited ZnO:Al Films on Mica for Flexible PDLC Devices

Nanomaterials ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1011
Author(s):  
Dimitre Z. Dimitrov ◽  
Zih Fan Chen ◽  
Vera Marinova ◽  
Dimitrina Petrova ◽  
Chih Yao Ho ◽  
...  
Keyword(s):  
Near Infrared ◽  
Atomic Layer ◽  
Optical Transmittance ◽  
Force Microscopy ◽  
Flexible Polymer ◽  
Layer Deposition ◽  
Polymer Dispersed ◽  
Muscovite Mica ◽  
Infrared Spectral ◽  
Continuous Bending

In this work, highly conductive Al-doped ZnO (AZO) films are deposited on transparent and flexible muscovite mica substrates by using the atomic layer deposition (ALD) technique. AZO-mica structures possess high optical transmittance at visible and near-infrared spectral range and retain low electric resistivity, even after continuous bending of up to 800 cycles. Structure performances after bending tests have been supported by atomic force microscopy (AFM) analysis. Based on performed optical and electrical characterizations AZO films on mica are implemented as transparent conductive electrodes in flexible polymer dispersed liquid crystal (PDLC) devices. The measured electro-optical characteristics and response time of the proposed devices reveal the higher potential of AZO-mica for future ITO-free flexible optoelectronic applications.

scholarly journals Phenotypic and genetic variation of ultraviolet–visible-infrared spectral wavelengths of bovine meat

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giovanni Bittante ◽  
Simone Savoia ◽  
Alessio Cecchinato ◽  
Sara Pegolo ◽  
Andrea Albera
Keyword(s):  
Meat Quality ◽  
Genetic Improvement ◽  
Near Infrared ◽  
Infrared Region ◽  
Phenotypic Variance ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Infrared Spectral ◽  
Portable Spectrometers ◽  
Absorbance Spectra

AbstractSpectroscopic predictions can be used for the genetic improvement of meat quality traits in cattle. No information is however available on the genetics of meat absorbance spectra. This research investigated the phenotypic variation and the heritability of meat absorbance spectra at individual wavelengths in the ultraviolet–visible and near-infrared region (UV–Vis-NIR) obtained with portable spectrometers. Five spectra per instrument were taken on the ribeye surface of 1185 Piemontese young bulls from 93 farms (13,182 Herd-Book pedigree relatives). Linear animal model analyses of 1481 single-wavelengths from UV–Vis-NIRS and 125 from Micro-NIRS were carried out separately. In the overlapping regions, the proportions of phenotypic variance explained by batch/date of slaughter (14 ± 6% and 17 ± 7%,), rearing farm (6 ± 2% and 5 ± 3%), and the residual variances (72 ± 10% and 72 ± 5%) were similar for the UV–Vis-NIRS and Micro-NIRS, but additive genetics (7 ± 2% and 4 ± 2%) and heritability (8.3 ± 2.3% vs 5.1 ± 0.6%) were greater with the Micro-NIRS. Heritability was much greater for the visible fraction (25.2 ± 11.4%), especially the violet, blue and green colors, than for the NIR fraction (5.0 ± 8.0%). These results allow a better understanding of the possibility of using the absorbance of visible and infrared wavelengths correlated with meat quality traits for the genetic improvement in beef cattle.

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