scholarly journals Formation of Natural Egg Yolk Granule Stabilized Pickering High Internal Phase Emulsions by Means of NaCl Ionic Strength and pH Change

Foods ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 229
Author(s):  
Sijie Mi ◽  
Minquan Xia ◽  
Xinyue Zhang ◽  
Jihong Liu ◽  
Zhaoxia Cai
Keyword(s):  
Ionic Strength ◽  
Storage Stability ◽  
Volume Fraction ◽  
Egg Yolk ◽  
Yolk Granule ◽  
Ph Change ◽  
Phase Volume Fraction ◽  
Emulsion Droplets ◽  
Internal Phase ◽  
Enrich Food

Pickering high internal phase emulsions (HIPEs) are gel-like concentrated emulsions that have the potential to be an alternative to partially hydrogenated oil (PHO). In this study, egg yolk granules (EYGs), natural complexes of protein and lipid isolated from egg yolk, were used as an emulsifier to prepare Pickering HIPEs. Gel-like HIPEs with an oil phase volume fraction of 85% and with an emulsifier concentration of only 0.5% could be prepared by using EYGs as an emulsifier. The EYGs were able to form stable HIPEs at NaCl ionic strengths over 0.2 M and at pH over 5.0 with NaCl ionic strength of 0.3 M. The EYGs, which could stabilize HIPEs, were easily to adsorb and cover the oil-water interface to form emulsion droplets with small particle size. In addition, interacting EYGs in the aqueous phase formed a continuous network structure, and the oil droplets packed closely, exhibiting high elasticity and shear thinning behavior. Furthermore, the formed HIPEs had suitable storage stability with no significant changes in appearance and microstructure after storage for 60 days. This work can transform traditional oils from liquid-like to solid-like by using EYGs to enrich food processing diversity and improve the storage stability of oils while reducing the intake of PHO and providing a healthier diet for consumers.

A two-step approach for copper and nickel extracting and recovering by emulsion liquid membrane

2016 ◽  
Vol 74 (10) ◽  
pp. 2454-2461
Author(s):  
Qiang Bi ◽  
Juanqin Xue ◽  
Yingjuan Guo ◽  
Guoping Li ◽  
Haibin Cui
Keyword(s):  
Liquid Membrane ◽  
Volume Fraction ◽  
Process Variable ◽  
Phase Volume ◽  
Optimum Conditions ◽  
Application Technology ◽  
Emulsion Liquid Membrane ◽  
Phase Volume Fraction ◽  
Internal Phase ◽  
Valuable Metals

The recycling of copper and nickel from metallurgical wastewater using emulsion liquid membrane (ELM) was studied. P507 (2-ethylhexyl phosphonic acid-2-ethylhexyl ester) and TBP (tributyl phosphate) were used as carriers for the extraction of copper and nickel by ELMs, respectively. The influence of four emulsion composition variables, namely, the internal phase volume fraction (ϕ), surfactant concentration (Wsurf), internal phase stripping acid concentration (Cio) and the carrier concentration (Cc), and the process variable treat ratio on the extraction efficiencies of copper or nickel were studied. Under the optimum conditions, 98% copper and nickel were recycled by using ELM. The results indicated that ELM extraction is a promising industrial application technology to retrieve valuable metals in low concentration metallurgical wastewater.

scholarly journals Surfactant location and internal phase volume fraction dictate emulsion electrospun fiber morphology and modulate drug release and cell response

2021 ◽  
Author(s):  
Pamela M. Johnson ◽  
Kelsey E. Knewtson ◽  
Jacob G. Hodge ◽  
Justin M. Lehtinen ◽  
Anna S. Trofimoff ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Tissue Engineering ◽  
Drug Release ◽  
Volume Fraction ◽  
Electrospun Fiber ◽  
Phase Volume ◽  
Fiber Morphology ◽  
Phase Volume Fraction ◽  
Internal Phase ◽  
Versatile Technique

Emulsion electrospinning is a versatile technique used to create tunable fibrous meshes for applications in drug delivery and tissue engineering.

scholarly journals Vinyl Ester Oligomer Crosslinked Porous Polymers Prepared via Surfactant-Free High Internal Phase Emulsions

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Yun Zhu ◽  
Ye Hua ◽  
Shengmiao Zhang ◽  
Jianding Chen ◽  
Chun Pu Hu
Keyword(s):  
Elastic Modulus ◽  
Vinyl Ester ◽  
Volume Fraction ◽  
Porous Polymers ◽  
Diameter Distribution ◽  
Phase Volume ◽  
Phase Volume Fraction ◽  
Internal Phase ◽  
External Phase ◽  
Hierarchical Pore

Using vinyl ester resin (VER) containing styrene (or methyl methacrylate) and vinyl ester oligomer (VEO) as external phase, Pickering high internal phase emulsions (Pickering HIPEs) having internal phase volume fraction of up to 95 vol% were prepared with copolymer particles as sole stabilizer. Polymerizing the external phase of these Pickering HIPEs led to porous polymers (poly-Pickering-HIPEs). Compared to the polystyrene- (PS-) based poly-Pickering-HIPEs which were prepared with mixture of styrene and divinylbenzene (DVB) as crosslinker, the poly-Pickering-HIPEs herein showed much higher elastic modulus and toughness. The elastic modulus of these poly-Pickering-HIPEs increased with increasing the VEO concentration in the external phase, while it decreased with increasing internal phase volume fraction. Increasing VEO concentration in the external phase also resulted in a decrease in the average void diameter as well as a narrow void diameter distribution of the resulting poly-Pickering-HIPEs. In addition, there were many small pores in the voids surface caused by the volume contraction of VER during the polymerization, which suggests a new method to fabricate porous polymers having a well-defined hierarchical pore structure.

Instrumentation For Quantitative Microscopy

1977 ◽  
Vol 35 ◽  
pp. 206-209
Author(s):  
B. Ralph ◽  
A.R. Jones
Keyword(s):  
Volume Fraction ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Automatic Data ◽  
Phase Volume Fraction ◽  
Statistical Confidence ◽  
Resultant Data ◽  
Automatic Data Collection ◽  
Third Dimension ◽  
Evolution Of Microstructure

In all fields of microscopy there is an increasing interest in the quantification of microstructure. This interest may stem from a desire to establish quality control parameters or may have a more fundamental requirement involving the derivation of parameters which partially or completely define the three dimensional nature of the microstructure. This latter categorey of study may arise from an interest in the evolution of microstructure or from a desire to generate detailed property/microstructure relationships. In the more fundamental studies some convolution of two-dimensional data into the third dimension (stereological analysis) will be necessary.In some cases the two-dimensional data may be acquired relatively easily without recourse to automatic data collection and further, it may prove possible to perform the data reduction and analysis relatively easily. In such cases the only recourse to machines may well be in establishing the statistical confidence of the resultant data. Such relatively straightforward studies tend to result from acquiring data on the whole assemblage of features making up the microstructure. In this field data mode, when parameters such as phase volume fraction, mean size etc. are sought, the main case for resorting to automation is in order to perform repetitive analyses since each analysis is relatively easily performed.

scholarly journals Estimating the phase volume fraction of multi-phase steel via unsupervised deep learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sung Wook Kim ◽  
Seong-Hoon Kang ◽  
Se-Jong Kim ◽  
Seungchul Lee
Keyword(s):  
High Performance ◽  
Materials Science ◽  
Volume Fraction ◽  
Training Data ◽  
Phase Fraction ◽  
Phase Volume ◽  
Generative Adversarial Network ◽  
Phase Volume Fraction ◽  
Original Dataset ◽  
Multi Phase

AbstractAdvanced high strength steel (AHSS) is a steel of multi-phase microstructure that is processed under several conditions to meet the current high-performance requirements from the industry. Deep neural network (DNN) has emerged as a promising tool in materials science for the task of estimating the phase volume fraction of these steels. Despite its advantages, one of its major drawbacks is its requirement of a sufficient amount of training data with correct labels to the network. This often comes as a challenge in many areas where obtaining data and labeling it is extremely labor-intensive. To overcome this challenge, an unsupervised way of learning DNN, which does not require any manual labeling, is proposed. Information maximizing generative adversarial network (InfoGAN) is used to learn the underlying probability distribution of each phase and generate realistic sample points with class labels. Then, the generated data is used for training an MLP classifier, which in turn predicts the labels for the original dataset. The result shows a mean relative error of 4.53% at most, while it can be as low as 0.73%, which implies the estimated phase fraction closely matches the true phase fraction. This presents the high feasibility of using the proposed methodology for fast and precise estimation of phase volume fraction in both industry and academia.

Biological characteristics of an enterotoxin produced by Bacillus cereus

1975 ◽  
Vol 21 (8) ◽  
pp. 1236-1246 ◽  
Author(s):  
W. M. Spira ◽  
J. M. Goepfert
Keyword(s):  
Ionic Strength ◽  
Bacillus Cereus ◽  
Exponential Growth ◽  
Biological Activities ◽  
Egg Yolk ◽  
Immune Serum ◽  
Fluid Accumulation ◽  
Ileal Loop ◽  
Receptor Sites ◽  
Ph Range

An enterotoxin synthesized during exponential growth by Bacillus cereus produces fluid accumulation in rabbit ileal loops, alters vascular permeability in the skin of rabbits, and kills mice when injected intravenously. All activities are eluted simultaneously from a Sephadex G-75 column and are distinct from the hemolysin and egg yolk turbidity factor of B. cereus. The enterotoxin is a true exotoxin. It interacts with intestinal receptor sites in a highly transient manner in the ileal loop system. Rabbit immune serum produced against the culture fluids from one strain of B. cereus neutralized the three biological activities in all other strains tested except strain B-6-ac for which none of the activities were neutralized.Enterotoxin proved to be unstable under a wide variety of conditions; ionic strength was especially critical. Enterotoxin was most stable in a pH range of 5.0 to 10.0, but lost activity rapidly outside this range. Alkylation provided some protection of enterotoxin activity in crude preparations but failed to protect activity during purification procedures. It did not appear to affect critically the enterotoxin molecule itself, since elution profiles on Sephadex G-75 chromatography were unchanged after alkylation.

scholarly journals Bentonite-supported catalase

2005 ◽  
Vol 70 (5) ◽  
pp. 721-726 ◽  
Author(s):  
S. Alkan ◽  
H. Ceylan ◽  
O. Arslan
Keyword(s):  
Ionic Strength ◽  
Kinetic Parameters ◽  
Enzyme Immobilization ◽  
Storage Stability ◽  
High Ionic Strength ◽  
Enzyme Inactivation ◽  
Valuable Method ◽  
And Storage

The properties of the clay bentonite as a support for enzyme immobilization were studied using the enzyme catalase. Such an immobilization does not result in enzyme inactivation and constitutes a valuable method for immobilizing catalase at high ionic strength. The bentonite-supported catalase was characterized in terms of pH and ionic strength dependencies, thermal and storage stability and kinetic parameters. These studies indicate that bentonite is a valuable support for the simple adsorption of enzymes. .

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