Self-Assembled Modified Soy Protein/Dextran Nanogel Induced by Ultrasonication as a Delivery Vehicle for Riboflavin

A simple and green approach was developed to produce a novel nanogel via self-assembly of modified soy protein and dextran, to efficiently deliver riboflavin. First, modified soy protein was prepared by heating denaturation at 60 °C for 30 min or Alcalase hydrolysis for 40 min. Second, modified soy protein was mixed with dextran and ultrasonicated for 70 min so as to assemble nanogels. The modified soy protein-dextran nanogels were characterized by Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) and ζ-potential studies to confirm the formation of NGs. Transmission electron microscopy (TEM) revealed the NGs to be spherical with core-shell structures, in the range of 32–40 nm size. The nanogels were stable against various environmental conditions. Furthermore, the particle size of the nanogels hardly changed with the incorporation of riboflavin. The encapsulation efficiency of nanogels was found to be up to 65.9% at a riboflavin concentration of 250 μg/mL. The nanogels exhibited a faster release in simulated intestine fluid (SIF) compared with simulated gastric fluid (SGF). From the results obtained it can be concluded that modified soy protein-dextran nanogels can be considered a promising carrier for drugs and other bioactive molecule delivery purposes

Preparation of Direct Reduced Iron and Titanium Nitride from Panzhihua Titanomagnetite Concentrate Through Carbothermic Reduction-Magnetic Separation

A novel process for preparing direct reduction iron (DRI) and titanium nitride (TiN) from Panzhihua titanomagnetite concentrate is proposed. This process involves pelletizing, direct reduction roasting and magnetic separation. The effects of reduction temperature, coal dosage and reduction time on the phase transformation of composite pellets were investigated by X-ray diffraction. Results show that TiN formation proceeds less easily than metallic iron formation. Increasing the reduction temperature, reduction time and coal dosage can promote the transformation of titanium to TiN. Titanium was almost completely transformed into TiN under the conditions of 1300 °C reduction temperature, 26 wt % coal dosage and 90 min reduction time. The scanning electron microscopy (SEM) analysis showed that near-spherical metallic iron particles with diameters from dozens of microns to about 300 μm were formed in the reduced pellets, whereas the TiN particles generally measured less than 10 μm. The energy dispersive spectroscopy (EDS) results revealed that the TiN phase contains a certain amount of vanadium and carbon, and traces of other impurities. The reduced composite pellets under the optimum conditions were processed by grinding and subsequent magnetic separation. As a result, a DRI with 92.88 wt % Fe, 1.00 wt % Ti, and 0.13 wt % V was obtained, and the recoveries of Fe, Ti, and V were 92.85 wt %, 9.00 wt %, and 19.40 wt %, respectively. 91.00 wt % Ti and 80.60 wt % V were concentrated in the rough TiN concentrate

Estimation of stress distribution in ferromagnetic tensile specimens using low cost eddy current stress measurement system and BP neural network

<div><p>Estimation of the stress distribution in ferromagnetic components is very important for evaluating the working status of mechanical equipment and implementing preventive maintenance. Eddy current testing technology is a promising method in this field because of its advantages of safety, no need of coupling agent, etc. In order to reduce the cost of eddy current stress measurement system, and obtain the stress distribution in ferromagnetic materials without scanning, a low cost eddy current stress measurement system based on Archimedes spiral planar coil was established, and a method based on BP neural network to obtain the stress distribution using the stress of several discrete test points was proposed. To verify the performance of the developed test system and the validity of the proposed method, experiment was implemented using structural steel (Q235) specimens. Standard curves of sensors at each test point were achieved, the calibrated data were used to establish the BP neural network model for approximating the stress variation on the specimen surface, and the stress distribution curve of the specimen was obtained by interpolating with the established model. The results show that there is a good linear relationship between the change of signal modulus and the stress in most elastic range of the specimen, and the established system can detect the change in stress with a theoretical average sensitivity of -0.4228 mV/MPa. The obtained stress distribution curve is well consonant with the theoretical analysis result. At last, possible causes and improving methods of problems appeared in the results were discussed. This research has important significance for reducing the cost of eddy current stress measurement system, and advancing the engineering application of eddy current stress testing.</p></div

Changes of signal modulus and the calibrated standard curves.

<p>Changes of signal modulus and the calibrated standard curves.</p

Schematic diagram of the eddy current stress measurement system.

<p>Schematic diagram of the eddy current stress measurement system.</p

Tensile specimen.

<p>Tensile specimen.</p

Stress distribution curve in the middle area of the central axis on specimen (under the tensile force of 600 kilogram-forces).

<p>Stress distribution curve in the middle area of the central axis on specimen (under the tensile force of 600 kilogram-forces).</p

Simulation results of the sensor.

<p>Simulation results of the sensor.</p

Appearance of the sensor.

<p>Appearance of the sensor.</p

Block diagram of the signal conditioning circuit.

<p>Block diagram of the signal conditioning circuit.</p