Pub Date : 2021-10-11DOI: 10.36548/jucct.2021.3.002
Haoxiang Wang
In recent times Automation is emerging every day and bloomed in every sector. Intelligent Transportation System (ITS) is one of the important branches of Automation. The major constrain in the transportation system is traffic congestion. This slurps the individual’s time and consequently pollutes the environment. A centralized management is required for optimizing the transportation system. The current traffic condition is predicted by evaluating the historical data and thereby it reduces the traffic congestion. The periodic update of traffic condition in each and every street of the city is obtained and the data is transferred to the autonomous vehicle. These data are obtained from the simulation results of transportation prediction tool SUMO. It is proved that our proposed work reduces the traffic congestion and maintains ease traffic flow and preserves the fleet management.
{"title":"Novel Routing Algorithm for Autonomous Vehicles in Smart Transportation System","authors":"Haoxiang Wang","doi":"10.36548/jucct.2021.3.002","DOIUrl":"https://doi.org/10.36548/jucct.2021.3.002","url":null,"abstract":"In recent times Automation is emerging every day and bloomed in every sector. Intelligent Transportation System (ITS) is one of the important branches of Automation. The major constrain in the transportation system is traffic congestion. This slurps the individual’s time and consequently pollutes the environment. A centralized management is required for optimizing the transportation system. The current traffic condition is predicted by evaluating the historical data and thereby it reduces the traffic congestion. The periodic update of traffic condition in each and every street of the city is obtained and the data is transferred to the autonomous vehicle. These data are obtained from the simulation results of transportation prediction tool SUMO. It is proved that our proposed work reduces the traffic congestion and maintains ease traffic flow and preserves the fleet management.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87257491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-11DOI: 10.36548/jsws.2021.3.002
Christina Gnanamani, S. Pandiaraj
Wireless communication is a constantly evolving and forging domain. The action of the RF input module is critical in the radio frequency signal communication link. This paper discusses the design of a RF high frequency transistor amplifier for unlicensed 60 GHz applications. The Transistor used for analysis is a FET amplifier, operated at 60GHz with 10 mA at 6.0 V. The simulation of the amplifier is made with the Open Source Scilab 6.0.1 console software. The MESFET is biased such that Sll = 0.9<30°, S12 = 0.21<-60°, S21= 2.51<-80°, and S22 = 0.21<-15o. It is found that the transistor is unconditionally stable and hence unilateral approximation can be employed. With these assumptions, the maximum value of source gain of the amplifier is found to be at 7.212 dB and the various constant source gain circles and noise figure circles are computed. The transistor has the following noise parameters: Fmin = 3 dB, Rn = 4 Ω, and Γopt = 0.485<155°. The amplifier is designed to have an input and output impedance of 50 ohms which is considered as the reference impedance.
{"title":"Computation of Constant Gain and NF Circles for 60 GHz Ultra-low noise Amplifiers","authors":"Christina Gnanamani, S. Pandiaraj","doi":"10.36548/jsws.2021.3.002","DOIUrl":"https://doi.org/10.36548/jsws.2021.3.002","url":null,"abstract":"Wireless communication is a constantly evolving and forging domain. The action of the RF input module is critical in the radio frequency signal communication link. This paper discusses the design of a RF high frequency transistor amplifier for unlicensed 60 GHz applications. The Transistor used for analysis is a FET amplifier, operated at 60GHz with 10 mA at 6.0 V. The simulation of the amplifier is made with the Open Source Scilab 6.0.1 console software. The MESFET is biased such that Sll = 0.9<30°, S12 = 0.21<-60°, S21= 2.51<-80°, and S22 = 0.21<-15o. It is found that the transistor is unconditionally stable and hence unilateral approximation can be employed. With these assumptions, the maximum value of source gain of the amplifier is found to be at 7.212 dB and the various constant source gain circles and noise figure circles are computed. The transistor has the following noise parameters: Fmin = 3 dB, Rn = 4 Ω, and Γopt = 0.485<155°. The amplifier is designed to have an input and output impedance of 50 ohms which is considered as the reference impedance.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87412993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The invention of the first vaccine has also raised several anti-vaccination views among people. Vaccine reluctance may be exacerbated by the growing reliance on social media, which is considered as a source of health information. During this COVID'19 scenario, the verification of non-vaccinators via the use of biometric characteristics has received greater attention, especially in areas such as vaccination monitoring and other emergency medical services, among other things. The traditional digital camera utilizes the middle-resolution images for commercial applications in a regulated or contact-based environment with user participation, while the latter uses high-resolution latent palmprints. This research study attempts to utilize convolutional neural networks (CNN) for the first time to perform contactless recognition. To identify the COVID '19 vaccine using the CNN technique, this research work has used the contactless palmprint method. Further, this research study utilizes the PalmNet structure of convolutional neural network to resolve the issue. First, the ROI region of the palmprint was extracted from the input picture based on the geometric form of the print. After image registration, the ROI region is sent into a convolutional neural network as an input. The softmax activation function is then used to train the network so that it can choose the optimal learning rate and super parameters for the given learning scenario. The neural networks of the deep learning platform were then compared and summarized.
{"title":"Identification of Covid’19 Vaccinator by Deep Learning Approach Using Contactless Palmprints","authors":"B. Vivekanandam","doi":"10.36548/jei.2021.3.003","DOIUrl":"https://doi.org/10.36548/jei.2021.3.003","url":null,"abstract":"The invention of the first vaccine has also raised several anti-vaccination views among people. Vaccine reluctance may be exacerbated by the growing reliance on social media, which is considered as a source of health information. During this COVID'19 scenario, the verification of non-vaccinators via the use of biometric characteristics has received greater attention, especially in areas such as vaccination monitoring and other emergency medical services, among other things. The traditional digital camera utilizes the middle-resolution images for commercial applications in a regulated or contact-based environment with user participation, while the latter uses high-resolution latent palmprints. This research study attempts to utilize convolutional neural networks (CNN) for the first time to perform contactless recognition. To identify the COVID '19 vaccine using the CNN technique, this research work has used the contactless palmprint method. Further, this research study utilizes the PalmNet structure of convolutional neural network to resolve the issue. First, the ROI region of the palmprint was extracted from the input picture based on the geometric form of the print. After image registration, the ROI region is sent into a convolutional neural network as an input. The softmax activation function is then used to train the network so that it can choose the optimal learning rate and super parameters for the given learning scenario. The neural networks of the deep learning platform were then compared and summarized.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91476582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-02DOI: 10.36548/jtcsst.2021.3.005
Haoxiang Wang
In recent days the need for energy resources is dramatically increasing world-wide. Overall 80% of the energy resource is supplied in the form of fuel based energy source and nuclear based energy source. Where fuel based energy resources are very essential in day-to-day life. Fossil fuel is also one among the energy resource and due to the high demand we face shortage in these resources. Providing electricity in rural areas is still a difficult process because of the shortage of energy resources. This issue can be rectified by choosing an alternate to electricity. To achieve this we have integrated many renewable energy sources to form a hybrid-renewable energy source system and this is capable of providing power supply to these areas. We have adopted artificial neural networks (ANN) technique based on machine learning to accomplish this process. For short-term prediction other techniques such as MLP, CNN, RNN and LSTM are used. These values are used as reference value in final execution.
{"title":"Fault Diagnosis in Hybrid Renewable Energy Sources with Machine Learning Approach","authors":"Haoxiang Wang","doi":"10.36548/jtcsst.2021.3.005","DOIUrl":"https://doi.org/10.36548/jtcsst.2021.3.005","url":null,"abstract":"In recent days the need for energy resources is dramatically increasing world-wide. Overall 80% of the energy resource is supplied in the form of fuel based energy source and nuclear based energy source. Where fuel based energy resources are very essential in day-to-day life. Fossil fuel is also one among the energy resource and due to the high demand we face shortage in these resources. Providing electricity in rural areas is still a difficult process because of the shortage of energy resources. This issue can be rectified by choosing an alternate to electricity. To achieve this we have integrated many renewable energy sources to form a hybrid-renewable energy source system and this is capable of providing power supply to these areas. We have adopted artificial neural networks (ANN) technique based on machine learning to accomplish this process. For short-term prediction other techniques such as MLP, CNN, RNN and LSTM are used. These values are used as reference value in final execution.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86249167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-02DOI: 10.36548/jtcsst.2021.3.006
C. Anand
Two important paradigms which are contradicting by nature namely: the efficient routing information diffusion and adaptability to dynamic network conditions using wireless routing protocols have been researched in recent years. One way of solving this issue is by using the past experiences of a node in network traffic condition through intelligent algorithm to predict the network traffic condition in the future. In this methodology we propose an algorithm which is used to to predict one hop delay per packet during routing process using neural networking. The one hop delay that is predicted is then further used by the participating nodes for information diffusion during routing. Experimental analysis indicate that using tapped delay line radial basis function and tapped delay line multilayer perceptron, it is possible to predict mean delays as a time series. The inputs used for prediction are mean delay time series with traffic loads and mean delay time series itself. The pros and cons of the proposed work are also present in this paper.
{"title":"Efficient Routing Algorithm using MLP and RBX in a Four Model Neural Networks","authors":"C. Anand","doi":"10.36548/jtcsst.2021.3.006","DOIUrl":"https://doi.org/10.36548/jtcsst.2021.3.006","url":null,"abstract":"Two important paradigms which are contradicting by nature namely: the efficient routing information diffusion and adaptability to dynamic network conditions using wireless routing protocols have been researched in recent years. One way of solving this issue is by using the past experiences of a node in network traffic condition through intelligent algorithm to predict the network traffic condition in the future. In this methodology we propose an algorithm which is used to to predict one hop delay per packet during routing process using neural networking. The one hop delay that is predicted is then further used by the participating nodes for information diffusion during routing. Experimental analysis indicate that using tapped delay line radial basis function and tapped delay line multilayer perceptron, it is possible to predict mean delays as a time series. The inputs used for prediction are mean delay time series with traffic loads and mean delay time series itself. The pros and cons of the proposed work are also present in this paper.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84527352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-02DOI: 10.36548/jtcsst.2021.3.004
J. Manoharan
Forgeries have recently become more prevalent in the society as a result of recent improvements in media generation technologies. In real-time, modern technology allows for the creation of a forged version of a single image obtained from a social network. Forgery detection algorithms have been created for a variety of areas; however they quickly become obsolete as new attack types exist. This paper presents a unique image forgery detection strategy based on deep learning algorithms. The proposed approach employs a convolutional neural network (CNN) to produce histogram representations from input RGB color images, which are then utilized to detect image forgeries. With the image separation method and copy-move detection applications in mind, the proposed CNN is combined with an intelligent approach and histogram mapping. It is used to detect fake or true images at the initial stage of our proposed work. Besides, it is specially designed for performing feature extraction in image layer separation with the help of CNN model. To capture both geographical and histogram information and the likelihood of presence at the same time, we use vectors in our dynamic capsule networks to detect the forgery kernels from reference images. The proposed research work integrates the intelligence with a feature engineering approach in an efficient manner. They are well-known and efficient in the identification of forged images. The performance metrics such as accuracy, recall, precision, and half total error rate (HTER) are computed and tabulated with the graph plot.
{"title":"Design of an Intelligent Approach on Capsule Networks to Detect Forged Images","authors":"J. Manoharan","doi":"10.36548/jtcsst.2021.3.004","DOIUrl":"https://doi.org/10.36548/jtcsst.2021.3.004","url":null,"abstract":"Forgeries have recently become more prevalent in the society as a result of recent improvements in media generation technologies. In real-time, modern technology allows for the creation of a forged version of a single image obtained from a social network. Forgery detection algorithms have been created for a variety of areas; however they quickly become obsolete as new attack types exist. This paper presents a unique image forgery detection strategy based on deep learning algorithms. The proposed approach employs a convolutional neural network (CNN) to produce histogram representations from input RGB color images, which are then utilized to detect image forgeries. With the image separation method and copy-move detection applications in mind, the proposed CNN is combined with an intelligent approach and histogram mapping. It is used to detect fake or true images at the initial stage of our proposed work. Besides, it is specially designed for performing feature extraction in image layer separation with the help of CNN model. To capture both geographical and histogram information and the likelihood of presence at the same time, we use vectors in our dynamic capsule networks to detect the forgery kernels from reference images. The proposed research work integrates the intelligence with a feature engineering approach in an efficient manner. They are well-known and efficient in the identification of forged images. The performance metrics such as accuracy, recall, precision, and half total error rate (HTER) are computed and tabulated with the graph plot.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"94 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77393484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haitang Liu, Xin Jin, Lin Chen, Xiaochen Chang, Jie Li, Yongzhen An, Jing Liu, Chunxia Pang, Yujie Gao
By combining the structural properties and characteristics of phosphogypsum whiskers, a preliminary study on the modification of phosphogypsum whiskers and their application in papermaking was carried out. The effects of reaction temperature, reaction time, and reaction concentration on the solubility and retention of modified phosphogypsum whiskers and the effects of phosphogypsum whiskers on the physical properties of paper under different modified conditions were explored. The research results show that, after the phosphogypsum whiskers are modified with calcium stearate, a coating layer will be formed on the surface of the whiskers, which effectively reduces the solubility of the phosphogypsum whiskers. The best modification conditions are: the amount of calcium stearate relative to the absolute dry mass of the phosphogypsum whisker is 2.00%; the modification time is 30 min, and the modification temperature is 60°C. The use of modified phosphogypsum whiskers for paper filling will slightly reduce the whiteness, folding resistance, burst resistance, and tensile strength of the paper, but the tearing degree and retention of the filler will be increased to some extent.
{"title":"Effects of phosphogypsum whiskers modification with calcium stearate and their impacts on properties of bleached softwood paper sheets","authors":"Haitang Liu, Xin Jin, Lin Chen, Xiaochen Chang, Jie Li, Yongzhen An, Jing Liu, Chunxia Pang, Yujie Gao","doi":"10.32964/tj20.9.567","DOIUrl":"https://doi.org/10.32964/tj20.9.567","url":null,"abstract":"By combining the structural properties and characteristics of phosphogypsum whiskers, a preliminary study on the modification of phosphogypsum whiskers and their application in papermaking was carried out. The effects of reaction temperature, reaction time, and reaction concentration on the solubility and retention of modified phosphogypsum whiskers and the effects of phosphogypsum whiskers on the physical properties of paper under different modified conditions were explored. \u0000The research results show that, after the phosphogypsum whiskers are modified with calcium stearate, a coating layer will be formed on the surface of the whiskers, which effectively reduces the solubility of the phosphogypsum whiskers. The best modification conditions are: the amount of calcium stearate relative to the absolute dry mass of the phosphogypsum whisker is 2.00%; the modification time is 30 min, and the modification temperature is 60°C. The use of modified phosphogypsum whiskers for paper filling will slightly reduce the whiteness, folding resistance, burst resistance, and tensile strength of the paper, but the tearing degree and retention of the filler will be increased to some extent.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86579553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates the influence of the degree of delignification of kraft spruce pulp cooked at seven different kappa numbers, ranging from 18.1 to 50.1, on the efficiency of displacement washing under laboratory conditions. Although the pulp bed is a polydispersive and heterogeneous system, the correlation dependence of the wash yield and bed efficiency on the Péclet number and the kappa number of the pulp showed that washing efficiency increased not only with an increasing Péclet number, but also with an increasing kappa number. The linear dependence between the mean residence time of the solute lignin in the bed and the space time, which reflects the residence time of the wash liquid in the pulp bed, was found for all levels of the kappa number. Washing also reduced the kappa number and the residual lignin content in the pulp fibers.
{"title":"Displacement washing of softwood pulp cooked to various levels of residual lignin content","authors":"Md. Mostafizur Rahman, F. Potůček","doi":"10.32964/tj20.9.553","DOIUrl":"https://doi.org/10.32964/tj20.9.553","url":null,"abstract":"This study investigates the influence of the degree of delignification of kraft spruce pulp cooked at seven different kappa numbers, ranging from 18.1 to 50.1, on the efficiency of displacement washing under laboratory conditions. Although the pulp bed is a polydispersive and heterogeneous system, the correlation dependence of the wash yield and bed efficiency on the Péclet number and the kappa number of the pulp showed that washing efficiency increased not only with an increasing Péclet number, but also with an increasing kappa number. The linear dependence between the mean residence time of the solute lignin in the bed and the space time, which reflects the residence time of the wash liquid in the pulp bed, was found for all levels of the kappa number. Washing also reduced the kappa number and the residual lignin content in the pulp fibers.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"161 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79042070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Starches have recently regained attention as ecofriendly barrier materials due to the increased demand for sustainable packaging. They are easily processable by conventional plastics processing equipment and have been utilized for oil and grease barrier applications. While starches have excellent oxygen barrier properties and decent water barrier properties at low relative humidity (RH), they are moisture sensitive, as demonstrated by the deterioration of the barrier properties at higher RH values. Starch esters are chemically modified starches where the hydroxyl group of the starch has been substituted by other moieties such as acetates. This imparts hydrophobicity to starches and has been claimed as a good way of retaining water vapor barrier properties of starches, even at high RH conditions. We studied the water vapor barrier properties of one class of starch esters, i.e., high amylose starch acetates that were assumed to have good water vapor barrier properties. Our investigations found that with a high degree of substitution of hydroxyl groups, the modified starches did indeed show improvements in water vapor response as compared to pure high amylose starch films; however, the barrier properties were orders of magnitude lower than commercially used water vapor barriers like polyethylene. Even though these materials had improved water vapor barrier response, high amylose starch acetates are likely unsuitable as water vapor barriers by themselves, as implied by previous literature studies and patents.
{"title":"Commercially relevant water vapor barrier properties of high amylose starch acetates: Fact or fiction?","authors":"Chinmay C. Satam, Ashoka Ghosh, P. Hart","doi":"10.32964/tj20.9.599","DOIUrl":"https://doi.org/10.32964/tj20.9.599","url":null,"abstract":"Starches have recently regained attention as ecofriendly barrier materials due to the increased demand for sustainable packaging. They are easily processable by conventional plastics processing equipment and have been utilized for oil and grease barrier applications. While starches have excellent oxygen barrier properties and decent water barrier properties at low relative humidity (RH), they are moisture sensitive, as demonstrated by the deterioration of the barrier properties at higher RH values. \u0000Starch esters are chemically modified starches where the hydroxyl group of the starch has been substituted by other moieties such as acetates. This imparts hydrophobicity to starches and has been claimed as a good way of retaining water vapor barrier properties of starches, even at high RH conditions. \u0000We studied the water vapor barrier properties of one class of starch esters, i.e., high amylose starch acetates that were assumed to have good water vapor barrier properties. Our investigations found that with a high degree of substitution of hydroxyl groups, the modified starches did indeed show improvements in water vapor response as compared to pure high amylose starch films; however, the barrier properties were orders of magnitude lower than commercially used water vapor barriers like polyethylene. Even though these materials had improved water vapor barrier response, high amylose starch acetates are likely unsuitable as water vapor barriers by themselves, as implied by previous literature studies and patents.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84962721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Beko Mesic, Mathew Cairns, J. Johnston, Meeta Patel
An aqueous styrene-butadiene latex dispersion coating containing in-situ processed tetraethyl orthosilicate (TEOS) applied on paperboard demonstrated improved water barrier performance. Coatings containing TEOS equivalent to 0.8% silicon dioxide (SiO2; dry basis) exhibited water vapor performance of < 25 g/m2/day (23°C, 50% relative humidity [RH]) and liquid water barrier performance Cobb 1800 s of < 6 g/m2, when applied as a single-layer 18 g/m2 coating. Cobb 1800 s barrier performance was still good (< 11 g/m2) at coat weights of 7–10 g/m2. The use of filler materials such as kaolin improved the vapor barrier properties of the coating, but this was not critical to the liquid water barrier properties.
{"title":"Tetraethyl orthosilicate-containing dispersion coating — water vapor and liquid water barrier properties","authors":"Beko Mesic, Mathew Cairns, J. Johnston, Meeta Patel","doi":"10.32964/tj20.9.583","DOIUrl":"https://doi.org/10.32964/tj20.9.583","url":null,"abstract":"An aqueous styrene-butadiene latex dispersion coating containing in-situ processed tetraethyl orthosilicate (TEOS) applied on paperboard demonstrated improved water barrier performance. Coatings containing \u0000TEOS equivalent to 0.8% silicon dioxide (SiO2; dry basis) exhibited water vapor performance of < 25 g/m2/day (23°C, 50% relative humidity [RH]) and liquid water barrier performance Cobb 1800 s of < 6 g/m2, when applied as a single-layer 18 g/m2 coating. Cobb 1800 s barrier performance was still good (< 11 g/m2) at coat weights of 7–10 g/m2. The use of filler materials such as kaolin improved the vapor barrier properties of the coating, but this was not critical to the liquid water barrier properties.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86741187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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