scholarly journals Space Group Approximation of a Molecular Crystal by Classifying Molecules for Their Electric Potentials and Roughness on Their Inertial Ellipsoid Surface

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Jose Fayos
Keyword(s):  
Electric Potential ◽  
Molecular Crystal ◽  
Potential Distribution ◽  
Molecular Shape ◽  
Molecular Surface ◽  
Space Group ◽  
Two Factors ◽  
Electric Potentials ◽  
Main Factors ◽  
Probable Space

In order to predict the most probable space group where a molecule crystallizes, it is assumed that molecular shape and electric potential distribution on the molecular surface are the main factors or predictors. However, to compare and classify molecules by these two factors seems to be very difficult for in general such different objects. Thus, in order to compare molecules, they are reduced to their inertial ellipsoid in which surface 26 equally spaced points were chosen where a roughness factor and an electric potential due to all atomic charges of the whole molecule are calculated. By this procedure, different molecules encoded by these two predictor vectors can be compared and classified, showing that molecules that crystallize in the same space group have more similar predictor vectors. This result opens the possibility to predict the more probable spatial group associated with a molecule.

scholarly journals Crystal-to-Crystal Transformation from K2[Co(C2O4)2(H2O)2]·4H2O to K2[Co(μ-C2O4)(C2O4)]

2021 ◽  
Vol 7 (6) ◽  
pp. 77
Author(s):  
Bin Zhang ◽  
Yan Zhang ◽  
Guangcai Chang ◽  
Zheming Wang ◽  
Daoben Zhu
Keyword(s):  
Hydrogen Bond ◽  
Physical Properties ◽  
Crystal Structures ◽  
Molecular Crystal ◽  
Trigonal Prism ◽  
Space Group ◽  
Cell Parameters ◽  
Oxalate Anion ◽  
Crystal Transformation ◽  
Antiferromagnetic Ordering

Crystal-to-crystal transformation is a path to obtain crystals with different crystal structures and physical properties. K2[Co(C2O4)2(H2O)2]·4H2O (1) is obtained from K2C2O4·2H2O, CoCl2·6H2O in H2O with a yield of 60%. It is crystallized in the triclinic with space group P1 and cell parameters: a = 7.684(1) Å, b = 9.011(1) Å, c = 10.874(1) Å, α = 72.151(2)°, β = 70.278(2)°, γ = 80.430(2)°, V = 670.0(1) Å3, Z = 2 at 100 K. 1 is composed of K+, mononuclear anion [Co(C2O4)2(H2O)22−] and H2O. Co2+ is coordinated by two bidentated oxalate anion and two H2O in an octahedron environment. There is a hydrogen bond between mononuclear anion [Co(C2O4)2(H2O)22−] and H2O. K2[Co(μ-C2O4)(C2O4)] (2) is obtained from 1 by dehydration. The cell parameters of 2 are a = 8.460(5) Å, b = 6.906 (4) Å, c = 14.657(8) Å, β = 93.11(1)°, V = 855.0(8) Å3 at 100 K, with space group in P2/c. It is composed of K+ and zigzag [Co(μ-C2O4)(C2O42−]n chain. Co2+ is coordinated by two bisbendentate oxalate and one bidentated oxalate anion in trigonal-prism. 1 is an antiferromagnetic molecular crystal. The antiferromagnetic ordering at 8.2 K is observed in 2.

scholarly journals The effect of dipole housing and feeding wires in physical phantoms for EEG

2019 ◽  
Vol 5 (1) ◽  
pp. 85-88
Author(s):  
René Machts ◽  
Alexander Hunold ◽  
Jens Haueisen
Keyword(s):  
Electric Potential ◽  
Volume Conductor ◽  
Constant Current ◽  
Twisted Pair ◽  
Eeg Data ◽  
Phantom Measurements ◽  
Average Change ◽  
Electric Potentials ◽  
The Difference ◽  
Signal Sources

AbstractCurrent dipoles are well established models in the localization of neuronal activity to electroencephalography (EEG) data. In physical phantoms, current dipoles can be used as signal sources. Current dipoles are often powered by constant current sources connected via twisted pair wires mostly consisting of copper. The poles are typically formed by platinum wires. These wires as well as the dipole housing might disturb the electric potential distributions in physical phantom measurements. We aimed to quantify this distortion by comparing simulation setups with and without the wires and the housing. The electric potential distributions were simulated using finite element method (FEM). We chose a homogenous volume conductor surrounding the dipoles, which was 100 times larger than the size of the dipoles. We calculated the difference of the electric potential at the surface of the volume conductor between the simulations with and without the connecting wires and the housing. Comparing simulations neglecting all connecting wires and the housing rod to simulations considering them, the electric potential at the surface of the volume conductor differed on average by 2.85 %. Both platinum and twisted pair copper wires had a smaller effect on the electric potentials with a maximum average change of 6.38 ppm. Consequently, source localization of measurements in physical head phantoms should consider these rods in the forward model.

scholarly journals Quantitative Observation of Electric Potential Distribution of Brittle Polyelectrolyte Hydrogels Using Microelectrode Technique

2016 ◽  
Vol 49 (8) ◽  
pp. 3100-3108 ◽  
Author(s):  
Honglei Guo ◽  
Takayuki Kurokawa ◽  
Masakazu Takahata ◽  
Wei Hong ◽  
Yoshinori Katsuyama ◽  
...  
Keyword(s):  
Electric Potential ◽  
Potential Distribution ◽  
Electric Potential Distribution ◽  
Microelectrode Technique

scholarly journals Observation of Electric Potential Distribution in Model Capacitor Sample Using Electron Holography

2012 ◽  
Vol 53 (4) ◽  
pp. 696-699 ◽  
Author(s):  
Ryuichi Kuramae ◽  
Hiroyuki Ono ◽  
Yoshinori Fujikawa ◽  
Yasukazu Murakami ◽  
Daisuke Shindo
Keyword(s):  
Electric Potential ◽  
Potential Distribution ◽  
Electron Holography ◽  
Electric Potential Distribution

scholarly journals Calculation of Electric Potentials Transferred by Grounding Systems

2020 ◽  
Author(s):  
Rooney R. A. Coelho ◽  
Mauricio B. C. Salles ◽  
Luciano Martins Neto ◽  
José Roberto Cardoso
Keyword(s):  
Electric Potential ◽  
Calculation Procedure ◽  
Metal Elements ◽  
Railway Tracks ◽  
Safety Risks ◽  
Electric Potentials

Buried metal elements such as fences, pipelines, building rebar, and railway tracks are subject to electric potential rise due to current flowing through the ground. In fact, theremay be a potential transfer of substations to remote regions in which such safety risks are not generally expected. This work presents a calculation procedure for this potential rise in uniform soils. The presented procedure is applied to cases extracted from the literature as a form of validation.

scholarly journals Economic and IT determinants of innovative projects in the textiles, wearing apparel, leather and related products industry

2018 ◽  
Vol 69 (04) ◽  
pp. 338-344
Author(s):  
SIMION CEZAR-PETRE ◽  
ALEXANDRU ADRIANA ◽  
CEPTUREANU SEBASTIAN ION ◽  
CEPTUREANU EDUARD GABRIEL
Keyword(s):  
European Union ◽  
Correlation Analysis ◽  
Volume Index ◽  
Major Influence ◽  
Factors Influencing ◽  
Global Demand ◽  
Two Factors ◽  
Main Factors ◽  
Potential Factors

In this paper the main factors that influence the innovative projects in the field of textiles, wearing apparel, leather and related products were identified and analyzed. Eleven potential factors influencing innovative projects have been considered and the correlation analysis has identified the two factors that have a major influence on innovative projects in the field: volume index of production in European Union for NACE codes 13-15 and exports value for textiles, wearing apparel, leather and related products. The research has shown that the scale of innovative projects in textiles, clothing, leather and related products depends on European Union production and on global demand.

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