New Flory‐Huggins interaction parameter between SBR and p‐phenylenediamine antioxidants and the predictive power in molecular structure and rubber formula design

2021 ◽  
pp. 51840
Author(s):  
Susu Liu ◽  
Yuanrong Jing ◽  
Jieyun Tu ◽  
Huimin Zou ◽  
Zhanfu Yong ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Interaction Parameter ◽  
Predictive Power

scholarly journals The Bond-Valence Substituent Index for Predicting the Boiling Temperatures of Aliphatic Hydrocarbons

KIMIKA ◽  
2020 ◽  
Vol 31 (1) ◽  
pp. 38-55
Author(s):  
Florentino C. Sumera ◽  
Stephani Jacutin ◽  
Jan Michael Aficial ◽  
Aileen Filipino
Keyword(s):  
Molecular Structure ◽  
Physical Properties ◽  
Organic Compounds ◽  
Topological Index ◽  
Predictive Power ◽  
Molecular Descriptor ◽  
Bond Valence ◽  
Aliphatic Hydrocarbons ◽  
Boiling Temperature ◽  
Small Deviations

A simple molecular descriptor based on molecular structure for predicting the boiling temperature (BT) of alkanes was developed in this paper. This topological index was used to correlate the boiling temperature of aliphatic hydrocarbons with their bond-valence substituent structure instead of by atom-to-atom branching framework. The predictive power of the bond-valence substituent index (BVSI) was evaluated by comparing it with the popular predictor in literature, the Randic index and the more recently proposed index, the Fi of Manso et al. (2012). The model developed through a second order regression of the plot of the alkane’s boiling temperature versus the BVSI index proved successful in its predictive power such that the method was also applied to a combination of aliphatic hydrocarbons, the alkanes, alkenes, alkynes and cycloalkanes. This topological index provided higher correlation with small deviations compared to the topological index used for comparison. A further study of the BVSI index can be explored for other organic compounds with different functional groups and other physical properties besides their boiling temperatures in the future.

Predictive Power of Peer Behavioral Assessment for Subsequent Maladjustment in Community Samples of Disruptive and Nondisruptive Children

2000 ◽  
Vol 41 (2) ◽  
pp. 181-190 ◽  
Author(s):  
George M. Realmuto ◽  
Gerald J. August ◽  
Joel M. Hektner
Keyword(s):  
Predictive Power ◽  
Behavioral Assessment

Molecular Structure of the Outermost Cell Wall Component of Spirillum Serpens

1977 ◽  
Vol 35 ◽  
pp. 342-343
Author(s):  
Wah Chiu ◽  
David Grano
Keyword(s):  
Molecular Structure ◽  
Cell Wall ◽  
Outer Membrane ◽  
Gel Electrophoresis ◽  
Electron Microscopic Examination ◽  
Electron Microscopic ◽  
Cell Wall Component ◽  
Protein Components ◽  
Exposure Technique ◽  
Structural Aspects

The periodic structure external to the outer membrane of Spirillum serpens VHA has been isolated by similar procedures to those used by Buckmire and Murray (1). From SDS gel electrophoresis, we have found that the isolated fragments contain several protein components, and that the crystalline structure is composed of a glycoprotein component with a molecular weight of ∽ 140,000 daltons (2). Under an electron microscopic examination, we have visualized the hexagonally-packed glycoprotein subunits, as well as the bilayer profile of the outer membrane. In this paper, we will discuss some structural aspects of the crystalline glycoproteins, based on computer-reconstructed images of the external cell wall fragments.The specimens were prepared for electron microscopy in two ways: negatively stained with 1% PTA, and maintained in a frozen-hydrated state (3). The micrographs were taken with a JEM-100B electron microscope with a field emission gun. The minimum exposure technique was essential for imaging the frozen- hydrated specimens.

Molecular Structure by Diffraction Methods

2015 ◽  
Keyword(s):  
Molecular Structure

“And the Oscar goes to . . .”: Integrative complexity’s predictive power in the film industry.

2018 ◽  
Vol 12 (4) ◽  
pp. 392-398 ◽  
Author(s):  
Hayley McCullough ◽  
Lucian Gideon Conway
Keyword(s):  
Predictive Power ◽  
Film Industry

Communicating the predictive power of selection and admissions measures

2008 ◽  
Author(s):  
Sara Cooper ◽  
Nathan Kuncel ◽  
Kara Siegert
Keyword(s):  
Predictive Power

Where Does the Predictive Power of the Reading Span Test Come From?

2004 ◽  
Author(s):  
Akira Miyake ◽  
Naomi P. Friedman
Keyword(s):  
Predictive Power ◽  
Reading Span ◽  
Span Test
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