COMPUTING MODELS OF THE AVERAGE ABSORPTION COEFFICIENTS IN DIATOMIC SPECTRA

1997 ◽  
Author(s):  
L. A. Kuznetsova ◽  
Sergey T. Surzhikov
Keyword(s):  
Absorption Coefficients ◽  
Computing Models

Interfacial properties of GaSb/InAs superlattices

1993 ◽  
Vol 51 ◽  
pp. 826-827
Author(s):  
M. E. Twigg ◽  
B. R. Bennett ◽  
J. R. Waterman ◽  
J. L. Davis ◽  
B. V. Shanabrook ◽  
...  
Keyword(s):  
Gaas Substrate ◽  
Molecular Beam ◽  
Infrared Detector ◽  
Interfacial Properties ◽  
Ex Situ ◽  
X Ray Diffraction ◽  
Absorption Coefficients ◽  
X Ray ◽  
Short Period ◽  
High Optical Absorption

Recently, the GaSb/InAs superlattice system has received renewed attention. The interest stems from a model demonstrating that short period Ga1-xInxSb/InAs superlattices will have both a band gap less than 100 meV and high optical absorption coefficients, principal requirements for infrared detector applications. Because this superlattice system contains two species of cations and anions, it is possible to prepare either InSb-like or GaAs-like interfaces. As such, the system presents a unique opportunity to examine interfacial properties.We used molecular beam epitaxy (MBE) to prepare an extensive set of GaSb/InAs superlattices grown on an GaSb buffer, which, in turn had been grown on a (100) GaAs substrate. Through appropriate shutter sequences, the interfaces were directed to assume either an InSb-like or GaAs-like character. These superlattices were then studied with a variety of ex-situ probes such as x-ray diffraction and Raman spectroscopy. These probes confirmed that, indeed, predominantly InSb-like and GaAs-like interfaces had been achieved.

Estimation of chlorophyll content by absorption spectra of native Spirulina platensis cells

2020 ◽  
pp. 25-33
Author(s):  
Leonid E. Paramonov
Keyword(s):  
Chlorophyll Content ◽  
Chlorophyll A ◽  
Absorption Spectra ◽  
Spirulina Platensis ◽  
Intracellular Concentration ◽  
Absorption Coefficients

A method for retrieving the absorption coefficients of Spirulina platensis pigments using absorption spectra of native cells and excluding the use of extracts is considered. Estimates of the intracellular concentration of chlorophyll a, С-phycoerythrin, С- phycocyanin and allophycocyanin in native cells are discussed.

Reversible Computing: An Introduction

2019 ◽  
Author(s):  
Federica Eftimiadi ◽  
Enrico Pugni Trimigliozzi
Keyword(s):  
Laws Of Nature ◽  
Physical Property ◽  
Computing Systems ◽  
Reversible Computing ◽  
Physical Laws ◽  
Structural Aspects ◽  
Computing Models

Reversible computing is a paradigm where computing models are defined so that they reflect physical reversibility, one of the fundamental microscopic physical property of Nature. Also, it is one of the basic microscopic physical laws of nature. Reversible computing refers tothe computation that could always be reversed to recover its earlier state. It is based on reversible physics, which implies that we can never truly erase information in a computer. Reversible computing is very difficult and its engineering hurdles are enormous. This paper provides a brief introduction to reversible computing. With these constraints, one can still satisfactorily deal with both functional and structural aspects of computing processes; at the same time, one attains a closer correspondence between the behavior of abstract computing systems and the microscopic physical laws (which are presumed to be strictly reversible) that underlay any implementation of such systems Available online at https://int-scientific-journals.com

scholarly journals Applications of soft computing models for predicting sea surface temperature: a comprehensive review and assessment

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Masoud Haghbin ◽  
Ahmad Sharafati ◽  
Davide Motta ◽  
Nadhir Al-Ansari ◽  
Mohamadreza Hosseinian Moghadam Noghani
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Soft Computing ◽  
Sea Surface ◽  
Linear Processes ◽  
Comprehensive Review ◽  
Droughts And Floods ◽  
Input Variables ◽  
And Performance ◽  
Computing Models

AbstractThe application of soft computing (SC) models for predicting environmental variables is widely gaining popularity, because of their capability to describe complex non-linear processes. The sea surface temperature (SST) is a key quantity in the analysis of sea and ocean systems, due to its relation with water quality, organisms, and hydrological events such as droughts and floods. This paper provides a comprehensive review of the SC model applications for estimating SST over the last two decades. Types of model (based on artificial neural networks, fuzzy logic, or other SC techniques), input variables, data sources, and performance indices are discussed. Existing trends of research in this field are identified, and possible directions for future investigation are suggested.

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