Reorganization energy and Stokes shift calculations from spectral data as new efficient approaches in distinguishing the end point of micellization/aggregation

2016 ◽  
Vol 8 (13) ◽  
pp. 2805-2811 ◽  
Author(s):  
Mintu Halder ◽  
Shubhashis Datta ◽  
Priyanka Bolel ◽  
Niharendu Mahapatra ◽  
Sudipta Panja ◽  
...  
Keyword(s):  
Spectral Data ◽  
Stokes Shift ◽  
Reorganization Energy ◽  
End Point

Variation of the reorganization energy with surfactant concentrations.

Density dependence of the Stokes shift and solvent reorganization energy in supercritical fluids

1999 ◽  
Vol 55 (5-6) ◽  
pp. 579-581 ◽  
Author(s):  
Kenji Takahashi ◽  
Katsutoshi Fujii ◽  
Sadashi Sawamura ◽  
Charles D Jonah
Keyword(s):  
Density Dependence ◽  
Supercritical Fluids ◽  
Stokes Shift ◽  
Reorganization Energy ◽  
Solvent Reorganization Energy

Stokes Shift as a Tool for Probing the Solvent Reorganization Energy

1997 ◽  
Vol 101 (19) ◽  
pp. 3433-3442 ◽  
Author(s):  
Edward L. Mertz ◽  
Vyacheslav A. Tikhomirov ◽  
Lev I. Krishtalik
Keyword(s):  
Stokes Shift ◽  
Reorganization Energy ◽  
Solvent Reorganization Energy

End Point

2020 ◽  
Author(s):  
Keyword(s):  
End Point

Settler Colonialism and the Revolutionary War

2019 ◽  
Vol 41 (4) ◽  
pp. 7-35
Author(s):  
Andrea Lynn Smith
Keyword(s):  
New York ◽  
Settler Colonialism ◽  
Revolutionary War ◽  
The State ◽  
The Public ◽  
150Th Anniversary ◽  
End Point ◽  
Indian Land ◽  
Indian Relations ◽  
Major General

The centerpiece of New York State’s 150th anniversary of the Sullivan Expedition of 1779 was a pageant, the “Pageant of Decision.” Major General John Sullivan’s Revolutionary War expedition was designed to eliminate the threat posed by Iroquois allied with the British. It was a genocidal operation that involved the destruction of over forty Indian villages. This article explores the motivations and tactics of state officials as they endeavored to engage the public in this past in pageant form. The pageant was widely popular, and served the state in fixing the expedition as the end point in settler-Indian relations in New York, removing from view decades of expropriations of Indian land that occurred well after Sullivan’s troops left.

Estimating Pigment Concentrations from Spectral Images Using an Encoder‐Decoder Neural Network

2020 ◽  
Vol 64 (3) ◽  
pp. 30502-1-30502-15
Author(s):  
Kensuke Fukumoto ◽  
Norimichi Tsumura ◽  
Roy Berns
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Absorption Coefficient ◽  
Spectral Data ◽  
High Accuracy ◽  
Pigment Concentration ◽  
Scattering Coefficient ◽  
A Value ◽  
Input And Output ◽  
Pigment Concentrations

Abstract A method is proposed to estimate the concentration of pigments mixed in a painting, using the encoder‐decoder model of neural networks. The model is trained to output a value that is the same as its input, and its middle output extracts a certain feature as compressed information about the input. In this instance, the input and output are spectral data of a painting. The model is trained with pigment concentration as the middle output. A dataset containing the scattering coefficient and absorption coefficient of each of 19 pigments was used. The Kubelka‐Munk theory was applied to the coefficients to obtain many patterns of synthetic spectral data, which were used for training. The proposed method was tested using spectral images of 33 paintings, which showed that the method estimates, with high accuracy, the concentrations that have a similar spectrum of the target pigments.

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