Electron Transport in Boron-Rich Borides

1987 ◽  
Vol 97 ◽  
Author(s):  
O. A. Golikova
Keyword(s):  
Thermal Properties ◽  
Electron Transport ◽  
Chemical Properties ◽  
Amorphous Semiconductors ◽  
Physico Chemical

Boron-rich borides represent a class of unique semiconductors. They combine the physico-chemical properties of refractory crystals with the electrical, optical, thermal properties typical for amorphous semiconductors [ 1–3 ].

scholarly journals Influence of Plasticizers Over Some Physico-chemical Properties of PLA

2017 ◽  
Vol 54 (1) ◽  
pp. 73-78 ◽  
Author(s):  
Maria Rapa ◽  
Raluca Nicoleta Darie Nita ◽  
Cornelia Vasile
Keyword(s):  
Thermal Properties ◽  
Food Packaging ◽  
Chemical Properties ◽  
Melt Processing ◽  
Main Task ◽  
Mechanical And Thermal Properties ◽  
Oxygen Barrier ◽  
Physico Chemical ◽  
Different Types ◽  
Oxygen Barrier Property

The use of polylactic acid (PLA) for food packaging is limited because it has poor mechanical and thermal properties, low ductility, and its oxygen barrier property is quite poor compared with polymers obtained from petrochemical resources. One main task of processors is to modify these properties in such a way that PLA to be able to compete with conventional polymers such as polyethylene, polypropylene or poly(vinylchloride). Our studies were conducted to test the effect of different types of plasticizers on the PLA melt processing and also on its mechanical and thermal performance.

scholarly journals Magnetic, spectrochemical and thermal properties of the 2-chloro-5-nitrobenzoates of Co(II), Ni(II) and Cu(II)

2006 ◽  
Vol 71 (8-9) ◽  
pp. 929-937 ◽  
Author(s):  
Wiesława Ferenc ◽  
Agnieszka Walków-Dziewulska ◽  
Beata Cristóvão ◽  
Jan Sarzyñski
Keyword(s):  
Thermal Decomposition ◽  
Thermal Properties ◽  
Metal Ion ◽  
Chemical Properties ◽  
Water Molecules ◽  
Dehydration Process ◽  
Crystallization Water ◽  
Physico Chemical ◽  
One Step ◽  
Hydrated Complexes

Some physico-chemical properties of the 2-chloro-5-nitrobenzoates of Co(II) Ni(II) and Cu(II) were studied. The complexes were obtained as hydrates with a metal ion to ligand ratio of 1:2. All the complexes were polycrystalline compounds. Their colors depended on the nature of the central ion: pink for the Co(II) complex, green for the Ni(II) and blue for the Cu(II) compounds. Their thermal decomposition was studied in the range of 293-523 K because it was found that the 2-chloro-5-nitrobenzoates decomposed explosively on heating in air above 523 K. The hydrated complexes lost crystallization water molecules in one step. From the results, it appeared that no transformation of the nitro group to nitrite occurred during the dehydration process. Their solubilities in water at 293 K were of the order of 10-2 mol dm-3 for the Ni(II) and Co(II) complexes and 10-4 mol dm-3 for that of Cu(II). The magnetic moment values of Co2+, Ni2+ and Cu2+ in the 2-chloro-5-nitrobenzoates, experimentally determined in the range, of 76-303 K ranged from 3.48 to 3.82 ?B for Co(II), from 2.69 to 3.08 ?B for the Ni(II) and from 1.87 to 2.00 ?B for the Cu(II) complex. The 2-chloro-5-nitrobenzoates of Co(II), Ni(II) and Cu(II) followed the Curie-Weiss law.

Decoration of specific sites on freeze-fractured membranes

1978 ◽  
Vol 36 (2) ◽  
pp. 140-141
Author(s):  
H. Gross ◽  
H. Moor
Keyword(s):  
Pure Water ◽  
Freeze Fracture ◽  
Chemical Properties ◽  
Surface Forces ◽  
Sulfate Pentahydrate ◽  
Copper Sulfate Pentahydrate ◽  
Physico Chemical ◽  
Water Of Hydration ◽  
Small Container ◽  
Binding Forces

Fracturing under ultrahigh vacuum (UHV, p ≤ 10-9 Torr) produces membrane fracture faces devoid of contamination. Such clean surfaces are a prerequisite foe studies of interactions between condensing molecules is possible and surface forces are unequally distributed, the condensate will accumulate at places with high binding forces; crystallites will arise which may be useful a probes for surface sites with specific physico-chemical properties. Specific “decoration” with crystallites can be achieved nby exposing membrane fracture faces to water vopour. A device was developed which enables the production of pure water vapour and the controlled variation of its partial pressure in an UHV freeze-fracture apparatus (Fig.1a). Under vaccum (≤ 10-3 Torr), small container filled with copper-sulfate-pentahydrate is heated with a heating coil, with the temperature controlled by means of a thermocouple. The water of hydration thereby released enters a storage vessel.

Physico-Chemical Properties of Recombinant Desulphatohirudin

1990 ◽  
Vol 63 (03) ◽  
pp. 499-504 ◽  
Author(s):  
A Electricwala ◽  
L Irons ◽  
R Wait ◽  
R J G Carr ◽  
R J Ling ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Gel Filtration ◽  
Chemical Properties ◽  
Alpha Helix ◽  
Apparent Molecular Weight ◽  
Correlation Spectroscopy ◽  
Nmr Studies ◽  
Recombinant Hirudin ◽  
Physico Chemical ◽  
Recombinant Molecule

SummaryPhysico-chemical properties of recombinant desulphatohirudin expressed in yeast (CIBA GEIGY code No. CGP 39393) were reinvestigated. As previously reported for natural hirudin, the recombinant molecule exhibited abnormal behaviour by gel filtration with an apparent molecular weight greater than that based on the primary structure. However, molecular weight estimation by SDS gel electrophoresis, FAB-mass spectrometry and Photon Correlation Spectroscopy were in agreement with the theoretical molecular weight, with little suggestion of dimer or aggregate formation. Circular dichroism studies of the recombinant molecule show similar spectra at different pH values but are markedly different from that reported by Konno et al. (13) for a natural hirudin-variant. Our CD studies indicate the presence of about 60% beta sheet and the absence of alpha helix in the secondary structure of recombinant hirudin, in agreement with the conformation determined by NMR studies (17)

Physico-chemical properties of the rare-earth metals, scandium, and yttrium

1963 ◽  
Vol 79 (2) ◽  
pp. 263-293 ◽  
Author(s):  
E.M. Savitskii ◽  
V.F. Terekhova ◽  
O.P. Naumkin
Keyword(s):  
Rare Earth ◽  
Rare Earth Metals ◽  
Chemical Properties ◽  
Physico Chemical ◽  
The Rare Earth

Physico chemical properties and gas adsorption separation characteristics of Itaya zeolite and its modified products.

1990 ◽  
Vol 39 (442) ◽  
pp. 996-1000 ◽  
Author(s):  
Ayao TAKASAKA ◽  
Hideyuki NEMOTO ◽  
Hirohiko KONO ◽  
Yoshihiro MATSUDA
Keyword(s):  
Gas Adsorption ◽  
Chemical Properties ◽  
Physico Chemical

Development of Ketchup from Sudanese Red karkade (Hibiscus sabdariffa L.) byproduct

Food Biology ◽  
1970 ◽  
pp. 19-23
Author(s):  
Nawal Abdel-Gayoum Abdel-Rahman
Keyword(s):  
Sensory Quality ◽  
Chemical Properties ◽  
Storage Period ◽  
Gum Arabic ◽  
Raw Material ◽  
Soluble Solids ◽  
Hibiscus Sabdariffa ◽  
Overall Acceptability ◽  
Physico Chemical ◽  
Tomato Ketchup

The aim of this study is to use of karkede (Hibiscus sabdariffa L.) byproduct as raw material to make ketchup instead of tomato. Ketchup is making of various pulps, but the best type made from tomatoes. Roselle having adequate amounts of macro and micro elements, and it is rich in source of anthocyanine. The ketchup made from pulped of waste of soaked karkede, and homogenized with starch, salt, sugar, ginger (Zingiber officinale), kusbara (Coriandrum sativum) and gum Arabic. Then processed and filled in glass bottles and stored at two different temperatures, ambient and refrigeration. The total solids, total soluble solids, pH, ash, total titratable acidity and vitamin C of ketchup were determined. As well as, total sugars, reducing sugars, colour density, and sodium chloride percentage were evaluated. The sensory quality of developed product was determined immediately and after processing, which included colour, taste, odour, consistency and overall acceptability. The suitability during storage included microbial growth, physico-chemical properties and sensory quality. The karkede ketchup was found free of contaminants throughout storage period at both storage temperatures. Physico-chemical properties were found to be significantly differences at p?0.05 level during storage. There were no differences between karkade ketchup and market tomato ketchup concerning odour, taste, odour, consistency and overall acceptability. These results are encouraging for use of roselle cycle as a raw material to make acceptable karkade ketchup.

Graph Neural Networks for Prediction of Fuel Ignition Quality

2020 ◽  
Author(s):  
Artur Schweidtmann ◽  
Jan Rittig ◽  
Andrea König ◽  
Martin Grohe ◽  
Alexander Mitsos ◽  
...  
Keyword(s):  
Neural Networks ◽  
Octane Number ◽  
Molecular Graph ◽  
Chemical Properties ◽  
Graph Representation ◽  
Structure Property ◽  
Oxygenated Hydrocarbons ◽  
Physico Chemical ◽  
Ignition Quality ◽  
Graph Neural Networks

<div>Prediction of combustion-related properties of (oxygenated) hydrocarbons is an important and challenging task for which quantitative structure-property relationship (QSPR) models are frequently employed. Recently, a machine learning method, graph neural networks (GNNs), has shown promising results for the prediction of structure-property relationships. GNNs utilize a graph representation of molecules, where atoms correspond to nodes and bonds to edges containing information about the molecular structure. More specifically, GNNs learn physico-chemical properties as a function of the molecular graph in a supervised learning setup using a backpropagation algorithm. This end-to-end learning approach eliminates the need for selection of molecular descriptors or structural groups, as it learns optimal fingerprints through graph convolutions and maps the fingerprints to the physico-chemical properties by deep learning. We develop GNN models for predicting three fuel ignition quality indicators, i.e., the derived cetane number (DCN), the research octane number (RON), and the motor octane number (MON), of oxygenated and non-oxygenated hydrocarbons. In light of limited experimental data in the order of hundreds, we propose a combination of multi-task learning, transfer learning, and ensemble learning. The results show competitive performance of the proposed GNN approach compared to state-of-the-art QSPR models making it a promising field for future research. The prediction tool is available via a web front-end at www.avt.rwth-aachen.de/gnn.</div>

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