Tannins from Acacia mangium Bark as Natural Dyes for Textiles:Characteristics and Applications

Tannins are capable of producing natural dyes with antioxidant and antibacterial propertis,while synthetic dyes are commonly used in the textile industry,causing environmental issues like water pollution.This research aims to utilize waste tannins as natural dyes as an alternative to synthetic dyes.This study examined the effect of the extraction method on tannin properties such as phenolic content,antioxidants,and antibacterial activity.In addition,Pyrolysis Gas Chromatography‒Mass Spectrometry(Py-GCMS)analysis was used to identify the effect of extraction temperature on the chemical elucidation of tannin.The effect of tannin concentration was evaluated against four bacteria that are usually found on human skin:Staphylococcus epidermidis,Bacillus subtilis,Propionibacterium acnes,and Staphylococcus aureus.Extraction temperature significantly influences the chemical composition of tannin,which leads to different antioxidant properties.The maximum antibacterial properties of tannin were obtained at 90℃with the inhibition zone in the range of 0.9–1.0 mm against four bacteria,tannin yield of 26.59%,Gallic Acid Equivalents or total phenolic content(GAE)of 40.30 mg/g,and Radical Scavenging Activity or antioxidant activity(RSA)of 89.88%.Moreover,the concentration of tannin was significantly linear with its antibacterial properties.Tannin was successfully applied to the textile by using alum as a mordanting agent to create an antibacterial textile.The textile’s bacterial structure damage was analyzed under Field Emission Scanning Electron Microscopy(FESEM).After 50 washings,tannin-textiles with alum-modified properties remained stable compared to those without alum,with S.aureus and S.epidermidis being the most vulnerable bacteria,as confirmed by FESEM images.Hence,tannin is a feasible alternative to harmful and nondegradable synthetic dyes and antibacterial agents.

The extraction of potassium from K-feldspar ore by low temperature molten salt method

The low temperature molten salt method was used to extract potassium from K-feldspar ore, and some related factors including mass ratio between NaNO_3, NaOH, H_2O and K-feldspar ore, particle size of K-feldspar ore,reaction temperature and time were investigated, respectively. In addition, the optimum condition for this method was determined by a series of condition experiments. What was more, the K-feldspar ore and the leach residue after reaction based on the above optimum condition were analyzed by XRD, SEM and EDS,separately. The results of which indicated that the mechanism of extraction of potassium for this method was according to the ion exchange reaction between sodium ion and potassium ion, and the extraction ratio of potassium had an obvious improvement than that of traditional methods, which could reach up to 96.25%.Therefore, this method can be a feasible solution to extract potassium from K-feldspar ore for its low energy consumption and high efficiency.

The Influence of Drying Temperature and Extraction Methods on a-Mangostin in Mangosteen Pericarp

The effects of drying temperature and extraction methods on α-mangostin content in mangosteen pericarp （Garcinia mangostana L.） powder were investigated. In the first part of experiment suitable drying temperature for retention α-mangostin content was determined. Three levels of drying temperatures （55, 65 and 75 ℃） were used in this study. The drying rates were increased with drying temperature. Room temperature extraction method was performed to investigate the effect of drying temperature on retention α-mangostin content in mangosteen pericarp. The α-mangostin content extracted at three different drying temperatures （55, 65 and 75 ℃） was 35.98 ± 0.49%, 40.32 ± 0.24%, and 37.79±0.34% w/w, respectively. The results showed that the suitable temperature for drying mangosteen pericarp was 65 ℃ that gave the highest of α-mangostin content. The second part of experiment was the comparison between extraction methods, such as shaking water bath extraction （SWE）, soxhlet extraction （SE） and microwave-assisted extraction （MAE）. The results show that MAE gave the highest extraction rate and α-mangostin content as compare to SWE and SE. The α-mangostin content extraction from SWE, SE and MAE are 45.83 ± 0.02, 34.82± 0.17 and 49.79 ± 0.15% w/w of crude extract, respectively.

Land-Cover Classification and its Impact on Peshawar’s Land Surface Temperature Using Remote Sensing

Spatial and temporal informationon urban infrastructure is essential and requires various land-cover/land-use planning and management applications.Besides,a change in infrastructure has a direct impact on other land-cover and climatic conditions.This study assessed changes in the rate and spatial distribution of Peshawar district’s infrastructure and its effects on Land Surface Temperature(LST)during the years 1996 and 2019.For this purpose,firstly,satellite images of bands7 and 8 ETM+(Enhanced Thematic Mapper)plus and OLI(Operational Land Imager)of 30 m resolution were taken.Secondly,for classification and image processing,remote sensing(RS)applications ENVI(Environment for Visualising Images)and GIS(Geographic Information System)were used.Thirdly,for better visualization and more in-depth analysis of land sat images,pre-processing techniques were employed.For Land use and Land cover(LU/LC)four types of land cover areas were identified-vegetation area,water cover,urbanized area,and infertile land for the years under research.The composition of red,green,and near infra-red bands was used for supervised classification.Classified images were extracted for analyzing the relative infrastructure change.A comparative analysis for the classification of images is performed for SVM(Support Vector Machine)and ANN(Artificial Neural Network).Based on analyzing these images,the result shows the rise in the average temperature from 30.04℃ to 45.25℃.This only possible reason is the increase in the built-up area from 78.73 to 332.78 Area km^(2) from 1996 to 2019.It has also been witnessed that the city’s sides are hotter than the city’s center due to the barren land on the borders.

Rail temperature variation under heavy haul operations

There currently does not exist in industry a reliable method for the detection of rail foot flaws.Like their head-based counterparts,foot flaws result in broken rail with potentially catastrophic consequences.A proposed area of research for the detection of these flaws is thermography,a non-contact method of measuring and analysing infrared emissions from an object under test.In industry,active excitation thermography is the most common,requiring an excitation source.This paper will present a temperature measurement system and a method of transient temperature extraction from the running rails for the effects of a passing train to evaluate heat transfer in the practical rail environment.The outcomes of these results will provide future direction in the development of a rail heat transfer model and determine if train passage provides enough active excitation for a thermography-based detection technique.

Temperature-variable high-frequency dynamic modeling of PIN diode

The PIN diode model for high frequency dynamic transient characteristic simulation is important in conducted EMI analysis. The model should take junction temperature into consideration since equipment usually works at a wide range of temperature. In this paper, a temperature-variable high frequency dynamic model for the PIN diode is built, which is based on the Laplace-transform analytical model at constant temperature. The relationship between model parameters and temperature is expressed as temperature functions by analyzing the physical principle of these parameters. A fast recovery power diode MUR1560 is chosen as the test sample and its dynamic performance is tested under inductive load by a temperature chamber experiment, which is used for model parameter extraction and model verification. Results show that the model proposed in this paper is accurate for reverse recovery simulation with relatively small errors at the temperature range from 25 to 120 ℃.