scholarly journals Evaluating TiO2 Photocatalysis Performance in Microtubes on Paper Background by Smartphone: Principles and Application Examples

Chemosensors ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 235
Author(s):  
Xian Liu ◽  
Chengxiang Xu ◽  
Shiwei Xie ◽  
Lei Zhu ◽  
Xun Wang
Keyword(s):  
Colorimetric Detection ◽  
White Paper ◽  
High Tech ◽  
Color Model ◽  
Blue Color ◽  
Alternative Analysis ◽  
Tio2 Photocatalysis ◽  
Different Color ◽  
Physical And Chemical ◽  
Reaction Processes

Titanium dioxide (TiO2) photocatalysis is a popular and promising technology in water treatment, but the performance evaluation usually depends on expensive equipment. In this study, using a smartphone for colorimetric detection, a self-invented method based on paper and microtubes (PMTs) is proposed to test the photocatalytic performance of TiO2. Firstly, the study has identified that PMTs achieved a correlation coefficient of above 0.9 between the greyscale values and concentrations during the physical process of different color dyes (i.e., rhodamine B (RhB), reactive yellow (RY), methylene blue (MB), and mixtures of the two or three dyes). The results indicate that when the principle of solution color follows the CMYK (Cyan, Magenta, Yellow, Black) color model, its photo color on white paper background conforms to the RGB (Red, Green, Blue) color model. Compared to the results obtained from the absorbance method, the PMTs method showed high reliabilities up to 99.36% on the monitoring of the photocatalytic process of the different dye solutions. Interestingly, the colorless solution of salicylic acid (SA) could also be analyzed by the PMTs after complexed with Fe(III) ion to develop a purple solution. These results suggest that the PMTs could be an alternative analysis method to evaluating physical and chemical reaction processes when the high-tech analysis equipment is unviable.

Comparative Experiment of Color Reproduction Methods

2014 ◽  
Vol 1051 ◽  
pp. 967-970
Author(s):  
Qi Jia ◽  
Xu Liang Lv ◽  
Wei Dong Xu ◽  
Jiang Hua Hu ◽  
Xian Hui Rong
Keyword(s):  
Polynomial Regression ◽  
Rapid Development ◽  
Color Space ◽  
Digital Camera ◽  
Color Difference ◽  
High Tech ◽  
Comparative Experiment ◽  
Color Reproduction ◽  
Different Color ◽  
Time Image

Digital camera which has the advantage of real-time image transferring and easily processing is more and more widely used in the packaging and printing industry with the rapid development of high-tech electronics industry. However, the color in digital camera is not accurate which affect the application. To minimize the color difference between the color in the digital camera and the real color, the color reproduction methods is developing. The field comparative experiment is carried out to compare the performance of color reproduction methods, such as polynomial regression algorithm in different color space, and color checker passport. The results show that fourth order polynomial regression color reproduction in XYZ color space has the best performance.

Fe–Ni metal–organic frameworks with prominent peroxidase-like activity for the colorimetric detection of Sn2+ ions

The Analyst ◽  
2020 ◽  
Vol 145 (19) ◽  
pp. 6349-6356
Author(s):  
Ye Hu ◽  
Chaochao Yue ◽  
Jing Wang ◽  
Yuhua Zhang ◽  
Wenhui Fang ◽  
...  
Keyword(s):  
Colorimetric Detection ◽  
Metal Organic Frameworks ◽  
Blue Color ◽  
Metal Organic

The synthesized Fe–Ni-MOF could oxidize TMB to produce oxTMB with blue color. The presence of Sn2+ ions could make the oxTMB color lighter, hence colorimetric detection of Sn2+ ions is realized.

Patterning Scheme Based on Photoacid Induced Spectral Changes for Single Layer, Patterned Full Color Light Emitting Diodes

2006 ◽  
Vol 965 ◽  
Author(s):  
Maria Vasilopoulou ◽  
Giorgos Pistolis ◽  
Athanasios Botsialas ◽  
Nikos Stathopoulos ◽  
Maria Rangoussi ◽  
...  
Keyword(s):  
Single Layer ◽  
Spectral Shift ◽  
Blue Color ◽  
Light Emitting ◽  
Photoacid Generators ◽  
Onium Salts ◽  
Hole Transporting ◽  
Polymeric Layer ◽  
Different Color ◽  
Definition Of

ABSTRACTPhotochemically induced emission tuning (PIET) for the definition of different color emitting areas in a single conducting polymeric layer is demonstrated. The commercially available poly(9-vinylcarbazole) (PVK), well known as a hole transporting layer in OLEDs technology, was used. The three primary colors emitting areas in a single layer of PVK film were defined using a suitable green emitter 1-[4-(dimethylamino)phenyl]-6-phenylhexa-1,3,5,-triene (DMA-DPH) along with the red emitter (4-dimethylamino-4'-nitrostilbene) (DANS). The selected emitters were dispersed in the PVK films in the presence of a photoacid generator (PAG). Various onium salts were tested as photoacid generators in order to select those, which could cause effectivily the photoinduced protonation and emission tuning of the probes molecules. Through proton induced bleaching of the red emitter and proton induced spectral shift of the green one, the definition of all three primary color emitting areas was possible. In this way the unexposed areas of the film remain red, the areas exposed with the intermediate dose become green and the fully exposed areas emit blue color. Intermediate colors and white light can also be obtained.

scholarly journals Silhouette index for determining optimal k-means clustering on images in different color models

2018 ◽  
Vol 7 (2.14) ◽  
pp. 105 ◽  
Author(s):  
Abd Rasid Mamat ◽  
Fatma Susilawati Mohamed ◽  
Mohamad Afendee Mohamed ◽  
Norkhairani Mohd Rawi ◽  
Mohd Isa Awang
Keyword(s):  
Image Processing ◽  
Color Model ◽  
Cluster Validation ◽  
Validation Process ◽  
Color Models ◽  
Silhouette Index ◽  
Hsv Color Model ◽  
Different Color ◽  
Lab Color Model ◽  
Cie Lab

Clustering process is an essential part of the image processing. Its aim to group the data according to having the same attributes or similarities of the images. Consequently, determining the number of the optimum clusters or the best (well-clustered) for the image in different color models is very crucial. This is because the cluster validation is fundamental in the process of clustering and it reflects the split between clusters. In this study, the k-means algorithm was used on three colors model: CIE Lab, RGB and HSV and the clustering process made up to k clusters. Next, the Silhouette Index (SI) is used to the cluster validation process, and this value is range between 0 to 1 and the greater value of SI illustrates the best of cluster separation. The results from several experiments show that the best cluster separation occurs when k=2 and the value of average SI is inversely proportional to the number of k cluster for all color model. The result shows in HSV color model the average SI decreased 14.11% from k = 2 to k = 8, 11.1% in HSV color model and 16.7% in CIE Lab color model. Comparisons are also made for the three color models and generally the best cluster separation is found within HSV, followed by the RGB and CIE Lab color models.  

scholarly journals A Hybrid Methodology for Flower Images Segmentation & Recognition with extended Deep-Convolution Neural Network (CNN)

2021 ◽  
Author(s):  
Neeraj Kumar Rathore ◽  
Varshali Jaiswal ◽  
Varsha Sharma ◽  
Sunita Varma
Keyword(s):  
Neural Network ◽  
Image Segmentation ◽  
Deep Learning ◽  
Computation Time ◽  
Detection Algorithm ◽  
Convolution Neural Network ◽  
Color Model ◽  
Blue Color ◽  
Deep Convolution Neural Network ◽  
Hybrid Methodology

Abstract Deep-Convolution Neural Network (CNN) is the branch of computer science. Deep Learning CNN is a methodology that teaches computer systems to do what comes naturally to humans. It is a method that learns by example and experience. This is a heuristic-based method to solve computationally exhaustive problems that are not resolved in a polynomial computation time like NP-Hard problems. The purpose of this research is to develop a hybrid methodology for the detection and segmentation of flower images that utilize the extension of the deep CNN. The plant, leaf, and flower image detection are the most challenging issues due to a wide variety of classes, based on their amount of texture, color distinctiveness, shape distinctiveness, and different size. The proposed methodology is implemented in Matlab with deep learning Tool Box and the dataset of flower image is taken from Kaggle with five different classes like daisy, dandelion, rose, tulip, and sunflower. This methodology takes an input of different flower images from data sets, then converts it from RGB (Red, Green, Blue) color model to the L*a*b color model. L*a*b has reduced the effort of image segmentation. The flower image segmentation has been performed by the canny edge detection algorithm which provided better results. The implemented extended deep learning convolution neural network can accurately recognize varieties of flower images. The learning accuracy of the proposed hybrid method is up to 98% that is maximizing up to + 1.89% from state of the art.

scholarly journals ABOUT FEATURES OF SETTING AND QUALITY OF MEALS OF BOARD FEED IN THE CONDITIONS OF CATERING «KOLTSOVO»

2019 ◽  
pp. 82-88
Author(s):  
N. I. Naumova ◽  
E. A. Burmistrov ◽  
O. M. Burmistrova
Keyword(s):  
Raw Materials ◽  
Chloride Content ◽  
High Tech ◽  
Technological Stage ◽  
Cadmium Lead ◽  
Physical And Chemical ◽  
The City ◽  
Foreign Impurities ◽  
Organoleptic Parameters

Onboard food is one of the components of normal flight tolerance. At enterprises for the production of on-board meals, ready meals and culinary products are produced, and their sale and consumption are organized. The purpose of the research was to study the features of manning and the quality of meals onboard food in the conditions of «Catering «Koltsovo» (the city of Yekaterinburg). As an object of research, a meat snack from the meals of the economy class food was used. In the course of physical and chemical tests, it has been established that the quality of raw materials (cheese of Dutch, boiled-smoked sausage and corn canned) used to make snacks, the content of table salt, moisture, foreign impurities, toxic metals (cadmium, lead) Regulated requirements. At the enterprise under study every technological stage is taken: storage, preparation, bundling of onboard food. On-board meals are prepared using high-tech equipment of Russian, Italian and German companies with observance of the temperature regime. Examination of the on-board dish revealed that the meat snack was placed in a disposable plate and packed in a polymer film with sealed ends from both sides. The label is marked on the package, the label contains the date of manufacture of the snack, the flight number of the aircraft and the shift. Organoleptic parameters of meat snacks, as well as sodium chloride content, average dish mass meet the requirements of the current regulatory documents. The onboard food prepared in conditions «Catering «Koltsovo», distinguish excellent taste qualities and attractive appearance.

Red cabbage anthocyanins content as a natural colorant for obtaining different color on wool fibers

2020 ◽  
Vol 49 (3) ◽  
pp. 229-238
Author(s):  
Hossein Barani ◽  
Homa Maleki
Keyword(s):  
Process Parameters ◽  
Blue Color ◽  
Content Type ◽  
Natural Colorant ◽  
Red Cabbage ◽  
Dyeing Process ◽  
Wool Fibers ◽  
Hue Angle ◽  
Promising Application ◽  
Different Color

Purpose Finding blue colorants from natural sources is extremely difficult and, usually, the anthocyanin compounds are used for producing the blue color. This study aims to apply the Red Cabbage as a natural colorant to obtain different colors on wool yarn, as well as specify the optimum dyeing condition by response surface methodology for obtaining a blue color. Design/methodology/approach The effect of dyeing process parameters such as mordant concentration, dyeing time, pH of dyeing bath and dyeing temperature examined in the color characteristics of the dyed wool samples. Findings The obtained results indicated that the diverse colors achieve by varying the dyeing process parameters, which is in the range of 26° up to 271°. The non-mordanted dyed wool samples showed a red and red brownish color (Hue angle = 26° up to 70°), and the mordanted dyed wool samples showed a blue and blue-greenish color (Hue angle = 230° up to 271°). The obtained blue color with the optimized dyeing condition presented a considerable good wash and lightfastness. Originality/value This study provides a promising application of Red Cabbage as a natural colorant for obtaining different colors by varying the dyeing process parameters such as pH and stannous ion concentrations. The stannous ions yielded a co-pigmentation and presented a blue color on wool fibers, which is extremely difficult to obtain with natural colorant.

Preparation of TiO2 Photocatalysis Antibacterial Ceramics

2013 ◽  
Vol 575-576 ◽  
pp. 302-305
Author(s):  
Jun Ding
Keyword(s):  
High Temperature ◽  
Chemical Stability ◽  
Sewage Disposal ◽  
Temperature Resistance ◽  
Tio2 Photocatalysis ◽  
Antibacterial Materials ◽  
High Temperature Resistance ◽  
Self Cleaning ◽  
Physical And Chemical

Among various inorganic antibacterial materials, TiO2 photocatalysis antibacterial materials possess unique properties including long lifespan, nontoxicity, high temperature resistance as well as high physical and chemical stability. More significantly, they are largely involved in many photocatalytic effects such as degradation of organics, purification of air, sewage disposal and self-cleaning.

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