scholarly journals The Science and Application of Satellite Based Fire Radiative Energy

Author(s):  
Evan Ellicott ◽  
Eric Vermote
Keyword(s):  
Nanomaterials ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1145
Author(s):  
Prem. C. Pandey ◽  
Shubhangi Shukla ◽  
Roger J. Narayan

Prussian blue nanoparticles (PBN) exhibit selective fluorescence quenching behavior with heavy metal ions; in addition, they possess characteristic oxidant properties both for liquid–liquid and liquid–solid interface catalysis. Here, we propose to study the detection and efficient removal of toxic arsenic(III) species by materializing these dual functions of PBN. A sophisticated PBN-sensitized fluorometric switching system for dosage-dependent detection of As3+ along with PBN-integrated SiO2 platforms as a column adsorbent for biphasic oxidation and elimination of As3+ have been developed. Colloidal PBN were obtained by a facile two-step process involving chemical reduction in the presence of 2-(3,4-epoxycyclohexyl)ethyl trimethoxysilane (EETMSi) and cyclohexanone as reducing agents, while heterogeneous systems were formulated via EETMSi, which triggered in situ growth of PBN inside the three-dimensional framework of silica gel and silica nanoparticles (SiO2). PBN-induced quenching of the emission signal was recorded with an As3+ concentration (0.05–1.6 ppm)-dependent fluorometric titration system, owing to the potential excitation window of PBN (at 480–500 nm), which ultimately restricts the radiative energy transfer. The detection limit for this arrangement is estimated around 0.025 ppm. Furthermore, the mesoporous and macroporous PBN-integrated SiO2 arrangements might act as stationary phase in chromatographic studies to significantly remove As3+. Besides physisorption, significant electron exchange between Fe3+/Fe2+ lattice points and As3+ ions enable complete conversion to less toxic As5+ ions with the repeated influx of mobile phase. PBN-integrated SiO2 matrices were successfully restored after segregating the target ions. This study indicates that PBN and PBN-integrated SiO2 platforms may enable straightforward and low-cost removal of arsenic from contaminated water.


2021 ◽  
Vol 275 ◽  
pp. 116740
Author(s):  
Maiara de Jesus Bassi ◽  
Luana Wouk ◽  
Wesley Renzi ◽  
Camilla Karla Oliveira ◽  
José Leonil Duarte ◽  
...  

Photonics ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 275
Author(s):  
Herbert Schneckenburger ◽  
Verena Richter

A short overview on 3D live cell imaging is given. Relevant samples are described and various problems and challenges—including 3D imaging by optical sectioning, light scattering and phototoxicity—are addressed. Furthermore, enhanced methods of wide-field or laser scanning microscopy together with some relevant examples and applications are summarized. In the future one may profit from a continuous increase in microscopic resolution, but also from molecular sensing techniques in the nanometer range using e.g., non-radiative energy transfer (FRET).


Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2667
Author(s):  
Ander Vieira ◽  
Jon Arrue ◽  
Begoña García-Ramiro ◽  
Felipe Jiménez ◽  
María Asunción Illarramendi ◽  
...  

In this paper, useful models that enable time-efficient computational analyses of the performance of luminescent solar concentrators (LSCs) are developed and thoroughly described. These LSCs are based on polymer optical fibers codoped with organic dyes and/or europium chelates. The interest in such dopants lies in the availability of new dyes with higher quantum yields and in the photostability and suitable absorption and emission bands of europium chelates. Time-efficiency without compromising accuracy is especially important for the simulation of europium chelates, in which non-radiative energy transfers from the absorbing ligands to the europium ion and vice versa are so fast that the discretization in time, in the absence of some simplifying assumptions, would have to be very fine. Some available experimental results are also included for the sake of comparison.


2016 ◽  
Vol 55 (1) ◽  
pp. 93-117 ◽  
Author(s):  
Ehrhard Raschke ◽  
Stefan Kinne ◽  
William B. Rossow ◽  
Paul W. Stackhouse ◽  
Martin Wild

AbstractThis study examines radiative flux distributions and local spread of values from three major observational datasets (CERES, ISCCP, and SRB) and compares them with results from climate modeling (CMIP3). Examinations of the spread and differences also differentiate among contributions from cloudy and clear-sky conditions. The spread among observational datasets is in large part caused by noncloud ancillary data. Average differences of at least 10 W m−2 each for clear-sky downward solar, upward solar, and upward infrared fluxes at the surface demonstrate via spatial difference patterns major differences in assumptions for atmospheric aerosol, solar surface albedo and surface temperature, and/or emittance in observational datasets. At the top of the atmosphere (TOA), observational datasets are less influenced by the ancillary data errors than at the surface. Comparisons of spatial radiative flux distributions at the TOA between observations and climate modeling indicate large deficiencies in the strength and distribution of model-simulated cloud radiative effects. Differences are largest for lower-altitude clouds over low-latitude oceans. Global modeling simulates stronger cloud radiative effects (CRE) by +30 W m−2 over trade wind cumulus regions, yet smaller CRE by about −30 W m−2 over (smaller in area) stratocumulus regions. At the surface, climate modeling simulates on average about 15 W m−2 smaller radiative net flux imbalances, as if climate modeling underestimates latent heat release (and precipitation). Relative to observational datasets, simulated surface net fluxes are particularly lower over oceanic trade wind regions (where global modeling tends to overestimate the radiative impact of clouds). Still, with the uncertainty in noncloud ancillary data, observational data do not establish a reliable reference.


1996 ◽  
Vol 10 (10) ◽  
pp. 1359-1367 ◽  
Author(s):  
G. N. FLERCHINGER ◽  
J. M. BAKER ◽  
E. J. A. SPAANS

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