MEASUREMENT OF SOOT MORPHOLOGY, CHEMISTRY, AND OPTICAL PROPERTIES IN THE VISIBLE AND NEAR-INFRARED SPECTRUM IN THE FLAME ZONE AND OVERFIRE REGION OF LARGE JP-8 POOL FIRES

2007 ◽  
Vol 179 (12) ◽  
pp. 2453-2487 ◽  
Author(s):  
KIRK A. JENSEN ◽  
JILL M. SUO-ANTTILA ◽  
LINDA G. BLEVINS
Keyword(s):  
Optical Properties ◽  
Infrared Spectrum ◽  
Near Infrared ◽  
Pool Fires ◽  
Flame Zone ◽  
Soot Morphology ◽  
Near Infrared Spectrum

Measurement of soot optical properties in the near-infrared spectrum

2000 ◽  
Vol 43 (18) ◽  
pp. 3299-3303 ◽  
Author(s):  
Jinyu Zhu ◽  
Mun Young Choi ◽  
George W. Mulholland ◽  
Louis A Gritzo
Keyword(s):  
Optical Properties ◽  
Infrared Spectrum ◽  
Near Infrared ◽  
Near Infrared Spectrum

Towards Characterization of Soot Morphology, Composition, and Optical Properties From Large Pool Fires

2002 ◽  
Author(s):  
Jill Suo-Anttila ◽  
Patrick Drozda ◽  
Louis Gritzo ◽  
Mun Young Choi
Keyword(s):  
Optical Properties ◽  
Morphological Properties ◽  
Pool Fires ◽  
Flame Zone ◽  
Large Pool ◽  
Transmission Electron ◽  
Soot Morphology ◽  
Large Fires ◽  
Insight Into

The thermal hazard posed by large hydrocarbon fires is dominated by the radiative emission from high temperature soot. Since the optical and morphological properties of soot are not well known, especially in the infrared, efforts to characterize these properties are underway. Measurements of optical properties and morphology in large fires are important in heat transfer calculations, interpretation of laser-based diagnostics, and to build revised soot property models for fire field models. This research utilizes extractive measurement diagnostics to characterize soot morphology, composition, and optical properties in pool fires. The fires of interest are realistic in size, and considerably larger than recent studies, from transitionally turbulent to fully turbulent JP-8 pool fires. For measurement of the extinction coefficient, soot extracted from the flame zone is transported to a transmission cell where measurements are made using both visible and infrared lasers. Soot morphological properties are obtained by analysis via transmission electron microscopy of soot samples obtained thermophoretically within the flame zone, overfire region, and in the transmission cell. Soot composition, including carbon-to-hydrogen ration and PAH concentration, is obtained by analysis of soot collected on filters. In addition to providing insight into optical properties, soot samples obtained allow researchers to determine that the soot morphology is not affected by the transport to the transmission cell. This paper describes the diagnostics and presents some preliminary data for soot morphology, composition, and optical properties measurements within the flame zone of pool fires.

scholarly journals Nanopatterned metallic transparent electrodes for the near-infrared spectrum

AIP Advances ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 045005
Author(s):  
Aliaksandr Hubarevich ◽  
Mikita Marus ◽  
Yauhen Mukha ◽  
Aliaksandr Smirnov ◽  
Xiao Wei Sun
Keyword(s):  
Infrared Spectrum ◽  
Near Infrared ◽  
Transparent Electrodes ◽  
Near Infrared Spectrum

An electrically driven whispering gallery polariton microlaser

Nanoscale ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 5448-5459
Author(s):  
Mingming Jiang ◽  
Peng Wan ◽  
Kai Tang ◽  
Maosheng Liu ◽  
Caixia Kan
Keyword(s):  
Infrared Spectrum ◽  
Near Infrared ◽  
Whispering Gallery ◽  
Near Infrared Spectrum

An electrically driven whispering gallery polariton microlaser composed of a ZnO:Ga microwire and a p-GaAs template was fabricated. Its working characteristics of polariton lasing in the near-infrared spectrum were demonstrated.

scholarly journals Theoretical Simulation of Near-Infrared Spectrum of Piperine: Insight into Band Origins and the Features of Regression Models

2021 ◽  
pp. 000370282110279
Author(s):  
Justyna Grabska ◽  
Krzysztof B. Beć ◽  
Sophia Mayr ◽  
Christian W. Huck
Keyword(s):  
Infrared Spectrum ◽  
Regression Models ◽  
Near Infrared ◽  
Computing Time ◽  
Black Pepper ◽  
Partial Least Square ◽  
Least Square ◽  
Complex Nature ◽  
Chemical Information ◽  
Near Infrared Spectrum

We investigated the near-infrared spectrum of piperine using quantum mechanical calculations. We evaluated two efficient approaches, DVPT2//PM6 and DVPT2//ONIOM [PM6:B3LYP/6-311++G(2df, 2pd)] that yielded a simulated spectrum with varying accuracy versus computing time factor. We performed vibrational assignments and unveiled complex nature of the near-infrared spectrum of piperine, resulting from a high level of band convolution. The most meaningful contribution to the near-infrared absorption of piperine results from binary combination bands. With the available detailed near-infrared assignment of piperine, we interpreted the properties of partial least square regression models constructed in our earlier study to describe the piperine content in black pepper samples. Two models were compared with spectral data sets obtained with a benchtop and a miniaturized spectrometer. The two spectrometers implement distinct technology which leads to a profound instrumental difference and discrepancy in the predictive performance when analyzing piperine content. We concluded that the sensitivity of the two instruments to certain types of piperine vibrations is different and that the benchtop spectrometer unveiled higher selectivity. Such difference in obtaining chemical information from a sample can be one of the reasons why the benchtop spectrometer performs better in analyzing the piperine content of black pepper. This evidenced direct correspondence between the features critical for applied near-infrared spectroscopic routine and the underlying vibrational properties of the analyzed constituent in a complex sample.

Functional Classification of Feed Items in Pampa Grassland, Based on Their Near-Infrared Spectrum

2020 ◽  
Vol 73 (3) ◽  
pp. 358-367
Author(s):  
Júlio Cezar Rebés Azambuja Filho ◽  
Paulo Cesar de Faccio Carvalho ◽  
Olivier Jean François Bonnet ◽  
Denis Bastianelli ◽  
Magali Jouven
Keyword(s):  
Infrared Spectrum ◽  
Near Infrared ◽  
Functional Classification ◽  
Near Infrared Spectrum
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