scholarly journals On the Detection of Spectral Emissions of Iron Oxides in Combustion Experiments of Pyrite Concentrates

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1284 ◽  
Author(s):  
Carlos Toro ◽  
Sergio Torres ◽  
Víctor Parra ◽  
Rodrigo Fuentes ◽  
Rosario Castillo ◽  
...  
Keyword(s):  
Iron Oxides ◽  
Spectral Resolution ◽  
Flame Temperature ◽  
Sulfide Mineral ◽  
High Spectral Resolution ◽  
Multivariate Curve Resolution ◽  
Mineral Particle ◽  
Non Linear ◽  
Detection Schemes ◽  
Spectral Emissions

In this paper, we report on the spectral detection of wustite, Fe(II) oxide (FeO), and magnetite, Fe(II, III) oxide (Fe3O4), molecular emissions during the combustion of pyrite (FeS2), in a laboratory-scale furnace operating at high temperatures. These species are typically generated by reactions occurring during the combustion (oxidation) of this iron sulfide mineral. Two detection schemes are addressed: the first consisting of measurements with a built-in developed spectrometer with a high sensitivity and a high spectral resolution. The second one consisting of spectra measured with a low spectral resolution and a low sensitivity commercial spectrometer, but enhanced and analyzed with post signal processing and multivariate data analysis such as principal component analysis (PCA) and a multivariate curve resolution—the alternating least squares method (MCR-ALS). A non-linear model is also proposed to reconstruct spectral signals measured during pyrite combustion. Different combustion conditions were studied to evaluate the capacity of the detection schemes to follow the spectral emissions of iron oxides. The results show a direct correlation between FeO and Fe3O4 spectral features intensity, and non-linear relations with key combustion variables such as flame temperature, and the combusted sulfide mineral particle size.

scholarly journals A coma-free super-high resolution optical spectrometer using 44 high dispersion sub-gratings

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hua-Tian Tu ◽  
An-Qing Jiang ◽  
Jian-Ke Chen ◽  
Wei-Jie Lu ◽  
Kai-Yan Zang ◽  
...  
Keyword(s):  
High Resolution ◽  
Spectral Resolution ◽  
Wavelength Region ◽  
Ultra Violet ◽  
High Spectral Resolution ◽  
Visible Range ◽  
High Dispersion ◽  
Charge Coupled Device ◽  
Wide Range ◽  
High Resolution Spectrometer

AbstractUnlike the single grating Czerny–Turner configuration spectrometers, a super-high spectral resolution optical spectrometer with zero coma aberration is first experimentally demonstrated by using a compound integrated diffraction grating module consisting of 44 high dispersion sub-gratings and a two-dimensional backside-illuminated charge-coupled device array photodetector. The demonstrated super-high resolution spectrometer gives 0.005 nm (5 pm) spectral resolution in ultra-violet range and 0.01 nm spectral resolution in the visible range, as well as a uniform efficiency of diffraction in a broad 200 nm to 1000 nm wavelength region. Our new zero-off-axis spectrometer configuration has the unique merit that enables it to be used for a wide range of spectral sensing and measurement applications.

scholarly journals Hyperspectral Data Simulation (Sentinel-2 to AVIRIS-NG) for Improved Wildfire Fuel Mapping, Boreal Alaska

2021 ◽  
Vol 13 (9) ◽  
pp. 1693
Author(s):  
Anushree Badola ◽  
Santosh K. Panda ◽  
Dar A. Roberts ◽  
Christine F. Waigl ◽  
Uma S. Bhatt ◽  
...  
Keyword(s):  
Land Cover ◽  
Spectral Resolution ◽  
Hyperspectral Image ◽  
Spectral Response ◽  
Spectral Characteristics ◽  
Hyperspectral Data ◽  
Spectral Unmixing ◽  
High Spectral Resolution ◽  
Fuel Mapping ◽  
Sentinel 2

Alaska has witnessed a significant increase in wildfire events in recent decades that have been linked to drier and warmer summers. Forest fuel maps play a vital role in wildfire management and risk assessment. Freely available multispectral datasets are widely used for land use and land cover mapping, but they have limited utility for fuel mapping due to their coarse spectral resolution. Hyperspectral datasets have a high spectral resolution, ideal for detailed fuel mapping, but they are limited and expensive to acquire. This study simulates hyperspectral data from Sentinel-2 multispectral data using the spectral response function of the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor, and normalized ground spectra of gravel, birch, and spruce. We used the Uniform Pattern Decomposition Method (UPDM) for spectral unmixing, which is a sensor-independent method, where each pixel is expressed as the linear sum of standard reference spectra. The simulated hyperspectral data have spectral characteristics of AVIRIS-NG and the reflectance properties of Sentinel-2 data. We validated the simulated spectra by visually and statistically comparing it with real AVIRIS-NG data. We observed a high correlation between the spectra of tree classes collected from AVIRIS-NG and simulated hyperspectral data. Upon performing species level classification, we achieved a classification accuracy of 89% for the simulated hyperspectral data, which is better than the accuracy of Sentinel-2 data (77.8%). We generated a fuel map from the simulated hyperspectral image using the Random Forest classifier. Our study demonstrated that low-cost and high-quality hyperspectral data can be generated from Sentinel-2 data using UPDM for improved land cover and vegetation mapping in the boreal forest.

A Wavelet-Enhanced Inversion Method for Water Quality Retrieval From High Spectral Resolution Data for Complex Waters

2015 ◽  
Vol 53 (2) ◽  
pp. 869-882 ◽  
Author(s):  
Eva M. Ampe ◽  
Dries Raymaekers ◽  
Erin L. Hestir ◽  
Maarten Jansen ◽  
Els Knaeps ◽  
...  
Keyword(s):  
Water Quality ◽  
Spectral Resolution ◽  
High Spectral Resolution ◽  
Inversion Method ◽  
Resolution Data

scholarly journals Correlation relationships of stratospheric molecular constituents from high spectral resolution, ground-based infrared solar absorption spectra

2000 ◽  
Vol 105 (D11) ◽  
pp. 14637-14652 ◽  
Author(s):  
Curtis Rinsland ◽  
Aaron Goldman ◽  
Brian J. Connor ◽  
Thomas M. Stephen ◽  
Nicholas B. Jones ◽  
...  
Keyword(s):  
Absorption Spectra ◽  
Spectral Resolution ◽  
High Spectral Resolution ◽  
Solar Absorption
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