In this study, a simulation of theoretical calculation of Lattice thermal conductivity of Bismuth bulk and nanowires with diameters of 98, 115, and 327 nm in the temperature range of 10 ‒ 300 K and pressure range of 0 ‒ 1.6 GPa was investigated. These calculations were achieved by using the Morelli Callaway model and the Clapeyron equation that both longitudinal and transverse modes are taken into account. Melting temperature, mass density, unit cell volume, mean bond length, lattice parameter, group velocity, and longitudinal and transverse Debye temperature for all transverse and longitudinal modes were calculated for each NW diameter mentioned.
{"title":"The Impact of Hydrostatic Pressure on Thermal Conductivity of Nanostructured Bi","authors":"Tahseen A. Husai̇n, I. Qader","doi":"10.31202/ecjse.1123146","DOIUrl":"https://doi.org/10.31202/ecjse.1123146","url":null,"abstract":"In this study, a simulation of theoretical calculation of Lattice thermal conductivity of Bismuth bulk and nanowires with diameters of 98, 115, and 327 nm in the temperature range of 10 ‒ 300 K and pressure range of 0 ‒ 1.6 GPa was investigated. These calculations were achieved by using the Morelli Callaway model and the Clapeyron equation that both longitudinal and transverse modes are taken into account. Melting temperature, mass density, unit cell volume, mean bond length, lattice parameter, group velocity, and longitudinal and transverse Debye temperature for all transverse and longitudinal modes were calculated for each NW diameter mentioned.","PeriodicalId":11622,"journal":{"name":"El-Cezeri Fen ve Mühendislik Dergisi","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76258970","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}
Sakthisudhan Karuppanan, Vinothini V R, Dr.EZHILAZHAGAN CHENGUTTUVAN
This article presents a polarization-switchable Microstrip Patch Antenna (MPA) that can be flexibly reconfigured. There are little parasitic patches connected to the corners of an MPA's circular patch as a radiator. The PIN diodes have made contact with O-shaped parasitic patch elements to form the circular patch. When the truncated corners are changed, enhanced the impedance bandwidth and axial ratio bandwidth has been obtained. 3.24 GHz is a resonant frequency for an impedance match (S11 less than 10dB) and for an axial ratio (AR less than 3 dB). The antenna's ability to transition between left- and right-handed circular polarizations (LHCP and RHCP) was verified by comparison of simulated and measured results observed. Vector Network Analyzer has also been used to evaluate the anticipated MPA under high RF strength in an anechoic room. Thus, the 5G networks and their related applications have been shown to work with these observed characteristics.
{"title":"Reconfigured antenna with switchable polarization for S Band Wireless applications","authors":"Sakthisudhan Karuppanan, Vinothini V R, Dr.EZHILAZHAGAN CHENGUTTUVAN","doi":"10.31202/ecjse.1137882","DOIUrl":"https://doi.org/10.31202/ecjse.1137882","url":null,"abstract":"This article presents a polarization-switchable Microstrip Patch Antenna (MPA) that can be flexibly reconfigured. There are little parasitic patches connected to the corners of an MPA's circular patch as a radiator. The PIN diodes have made contact with O-shaped parasitic patch elements to form the circular patch. When the truncated corners are changed, enhanced the impedance bandwidth and axial ratio bandwidth has been obtained. 3.24 GHz is a resonant frequency for an impedance match (S11 less than 10dB) and for an axial ratio (AR less than 3 dB). The antenna's ability to transition between left- and right-handed circular polarizations (LHCP and RHCP) was verified by comparison of simulated and measured results observed. Vector Network Analyzer has also been used to evaluate the anticipated MPA under high RF strength in an anechoic room. Thus, the 5G networks and their related applications have been shown to work with these observed characteristics.","PeriodicalId":11622,"journal":{"name":"El-Cezeri Fen ve Mühendislik Dergisi","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87221960","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}
M. Teke, Akif Kalinbaçoğlu, Fecir Duran, Meral Özarslan Yatak
Ultrasonik kaynak, sürtünme kaynak grubuna girmesiyle, günümüz endüstrisinde birleştirme metodu olarak birçok sektörde tercih edilmektedir. Bu yolla, kaynak yapılacak materyallere dolgu malzemesine gerek kalmadan birleştirme işlemi yapılmaktadır. Kaynak esnasında dolgu malzemesi olmadığından zehirli gaz ve atıklar çıkmamakta, bu yüzden de diğer kaynaklara göre daha çevreci bir yapıya sahip olmaktadır. Rezonans çalışma frekansında maksimum güç üretmesinin yanında rahatsız edici gürültü de ortaya çıkmaktadır. Rezonans çalışma anında optimum kaynak şeklini oluşturmaktadır. Bu nedenle kaynak yapılan materyallerin boyut ve mekaniksel özelliklerine göre frekans kayması oluşmaktadır. Bu kaymanın engellenmesi için, kaynak esnasında rezonans frekansının yakalanması gerekmektedir. Gerçekleştirilen bu çalışmada, sistemin verimliliğini arttırmak amacıyla, ultrasonik kaynak makinelerinin rezonans frekansının belirlenmesi için yeni bir metodoloji gerçekleştirilmiştir. Yük değiştiğinde yeniden belirlenmesi gereken bu değişken rezonans frekans değeri, kaynak işlemi sırasında gradient descent algoritması ile online olarak belirlenmektedir. Simülasyon çalışmaları Matlab/Simulink ortamında gerçekleştirilmiştir. Maksimum rasgele değişim %5 ve %20 olan iki farklı rezonans frekansı kullanılmıştır. Sonuç olarak, Gradient Descent algoritması ile 150 mS içinde %5 değişen rezonans frekansı ve 250 mS içinde %20 değişen rezonans frekansı elde edilmiştir.
{"title":"Gradient Descent Metodu ile Ultrasonik Kaynak Sisteminin Frekans Optimizasyonu","authors":"M. Teke, Akif Kalinbaçoğlu, Fecir Duran, Meral Özarslan Yatak","doi":"10.31202/ecjse.1132660","DOIUrl":"https://doi.org/10.31202/ecjse.1132660","url":null,"abstract":"Ultrasonik kaynak, sürtünme kaynak grubuna girmesiyle, günümüz endüstrisinde birleştirme metodu olarak birçok sektörde tercih edilmektedir. Bu yolla, kaynak yapılacak materyallere dolgu malzemesine gerek kalmadan birleştirme işlemi yapılmaktadır. Kaynak esnasında dolgu malzemesi olmadığından zehirli gaz ve atıklar çıkmamakta, bu yüzden de diğer kaynaklara göre daha çevreci bir yapıya sahip olmaktadır. Rezonans çalışma frekansında maksimum güç üretmesinin yanında rahatsız edici gürültü de ortaya çıkmaktadır. Rezonans çalışma anında optimum kaynak şeklini oluşturmaktadır. Bu nedenle kaynak yapılan materyallerin boyut ve mekaniksel özelliklerine göre frekans kayması oluşmaktadır. Bu kaymanın engellenmesi için, kaynak esnasında rezonans frekansının yakalanması gerekmektedir. Gerçekleştirilen bu çalışmada, sistemin verimliliğini arttırmak amacıyla, ultrasonik kaynak makinelerinin rezonans frekansının belirlenmesi için yeni bir metodoloji gerçekleştirilmiştir. Yük değiştiğinde yeniden belirlenmesi gereken bu değişken rezonans frekans değeri, kaynak işlemi sırasında gradient descent algoritması ile online olarak belirlenmektedir. Simülasyon çalışmaları Matlab/Simulink ortamında gerçekleştirilmiştir. Maksimum rasgele değişim %5 ve %20 olan iki farklı rezonans frekansı kullanılmıştır. Sonuç olarak, Gradient Descent algoritması ile 150 mS içinde %5 değişen rezonans frekansı ve 250 mS içinde %20 değişen rezonans frekansı elde edilmiştir.","PeriodicalId":11622,"journal":{"name":"El-Cezeri Fen ve Mühendislik Dergisi","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82732021","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}
Phenol compounds are used in many industrial areas. Due to their high toxicity and stability, phenol compounds are carcinogenic to humans and animals even at low concentrations during their production and use. For this reason, the removal of phenol contaminants is both necessary and beneficial. Water pollution caused by phenols is one of the most serious problems globally, threatening both people and the environment. Increasing industrial and human activities have led to an increase in wastewater discharge into water resources. These phenolic chemicals are harmful, and although there are different methods used, it is very important to find new materials and effective methods to remove these pollutants from water. This study aimed to convert the phenols purified from water using tyrosinase paste to a less harmful state by making an enzymatic biofilter for phenol removal, thanks to the polyaniline structure we formed on the filter paper, to ensure phenol retention. While this process took place, FeCl3 solution was used as the reactor material, and aniline was turned into polyaniline with FeCl3 solution in HCl. While these processes are being carried out, it is aimed to prepare the most efficient biofilter by using the components that make up the experiment at different concentrations. By calculating the % efficiency of the catechols, absorbance values were measured before and after filtration. It was revealed that the highest percentage of biofilter activity was formed using 0.15 M aniline, 10 KU tyrosinase enzyme, and 1% chitosan concentrations.
{"title":"Paper-based PANI/Enzyme Biofilter Development for Phenol Removal","authors":"Nimet YILDIRIM TİRGİL, Necdet Bugra Ali̇ustaoglu","doi":"10.31202/ecjse.1128865","DOIUrl":"https://doi.org/10.31202/ecjse.1128865","url":null,"abstract":"Phenol compounds are used in many industrial areas. Due to their high toxicity and stability, phenol compounds are carcinogenic to humans and animals even at low concentrations during their production and use. For this reason, the removal of phenol contaminants is both necessary and beneficial. Water pollution caused by phenols is one of the most serious problems globally, threatening both people and the environment. Increasing industrial and human activities have led to an increase in wastewater discharge into water resources. These phenolic chemicals are harmful, and although there are different methods used, it is very important to find new materials and effective methods to remove these pollutants from water. This study aimed to convert the phenols purified from water using tyrosinase paste to a less harmful state by making an enzymatic biofilter for phenol removal, thanks to the polyaniline structure we formed on the filter paper, to ensure phenol retention. While this process took place, FeCl3 solution was used as the reactor material, and aniline was turned into polyaniline with FeCl3 solution in HCl. While these processes are being carried out, it is aimed to prepare the most efficient biofilter by using the components that make up the experiment at different concentrations. By calculating the % efficiency of the catechols, absorbance values were measured before and after filtration. It was revealed that the highest percentage of biofilter activity was formed using 0.15 M aniline, 10 KU tyrosinase enzyme, and 1% chitosan concentrations.","PeriodicalId":11622,"journal":{"name":"El-Cezeri Fen ve Mühendislik Dergisi","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84690793","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}
An license plate recognition system (LPRS) generally provides control and security. These systems are created using methods such as artificial intelligence, machine learning, artificial neural networks (ANN), deep learning, fuzzy logic, expert systems, and image processing. This study aims to create an LPRS using artificial intelligence and image processing techniques. The prepared system is for rectangular-sized plates. An LPRS consists of 3 main stages. The first stage is to detect the plate region. At this stage, converting to grayscale, bilateral filtering, canny filtering, and contour were applied to vehicle images. The second stage is to crop the plate region. In the second stage, the masking method was employed. The pytesseract algorithm was used to recognize license plate characters in the last stage. To create the system, Raspberry Pi 4 Single-Board Computer (SBC) was used for hardware; python programming language was utilized for software. The results showed that the system worked successfully at the rate of 100% in the first two stages and at the rate of 91.82% in the last stage. The results suggest that the system works successfully.
车牌识别系统(LPRS)通常提供控制和安全。这些系统是使用人工智能、机器学习、人工神经网络(ANN)、深度学习、模糊逻辑、专家系统和图像处理等方法创建的。本研究旨在利用人工智能和图像处理技术创建一个LPRS。所制备的系统适用于矩形大小的板。LPRS包括3个主要阶段。第一步是检测板块区域。该阶段对车辆图像进行灰度转换、双边滤波、canny滤波和轮廓化处理。第二阶段是裁切印版区域。在第二阶段，采用掩蔽法。最后，采用pytesseract算法对车牌字符进行识别。为了创建这个系统，硬件使用了Raspberry Pi 4单板计算机(SBC);软件采用Python编程语言。结果表明，该系统前两段的萃取率为100%，最后一段的萃取率为91.82%。结果表明，该系统运行良好。
{"title":"License Plate Recognition System Based on Artificial Intelligence with Different Approach","authors":"Aslı Göde, Ahmet Doğan","doi":"10.31202/ecjse.1172426","DOIUrl":"https://doi.org/10.31202/ecjse.1172426","url":null,"abstract":"An license plate recognition system (LPRS) generally provides control and security. These systems are created using methods such as artificial intelligence, machine learning, artificial neural networks (ANN), deep learning, fuzzy logic, expert systems, and image processing. This study aims to create an LPRS using artificial intelligence and image processing techniques. The prepared system is for rectangular-sized plates. An LPRS consists of 3 main stages. The first stage is to detect the plate region. At this stage, converting to grayscale, bilateral filtering, canny filtering, and contour were applied to vehicle images. The second stage is to crop the plate region. In the second stage, the masking method was employed. The pytesseract algorithm was used to recognize license plate characters in the last stage. To create the system, Raspberry Pi 4 Single-Board Computer (SBC) was used for hardware; python programming language was utilized for software. The results showed that the system worked successfully at the rate of 100% in the first two stages and at the rate of 91.82% in the last stage. The results suggest that the system works successfully.","PeriodicalId":11622,"journal":{"name":"El-Cezeri Fen ve Mühendislik Dergisi","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75946931","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}
Faik. Yilan, İbrahim. baki. Şahin, Fatih Koc, L. Urteki̇n
Fused Deposition Modeling (FDM) is a three-dimensional (3D) printing technique in which parts are produced with thermoplastic polymer layers in a highly controlled manner. However, the production of ready-made parts using FDM is quite tricky. At the same time, the mechanical properties of parts printed with current print parameters and low-cost 3D printers also vary. The quality and mechanical characteristics of the final part are influenced by production parameters such as the extrusion temperature, infill density, infill pattern, print speed, and layer height. This study focused on the effects of the infill pattern, infill density and print speed parameters on the tensile strength and production time of model structures printed with PLA+ material. The tensile strength of the printed parts have been determined by a WDM-100E model tensile testing machine. In addition, the tensile strengths and production times of the parts have been optimized by the signal-to-noise (SN) ratio analysis. The results reveal that triangle infill pattern exhibits the best tensile strength at 40 mm/sec printing speed and 100% infill density. On the other hand, the lowest production time is observed in the gyroid infill pattern.
{"title":"The Effects of Different Process Parameters of PLA+ on Tensile Strengths in 3D Printer Produced by Fused Deposition Modeling","authors":"Faik. Yilan, İbrahim. baki. Şahin, Fatih Koc, L. Urteki̇n","doi":"10.31202/ecjse.1179492","DOIUrl":"https://doi.org/10.31202/ecjse.1179492","url":null,"abstract":"Fused Deposition Modeling (FDM) is a three-dimensional (3D) printing technique in which parts are produced with thermoplastic polymer layers in a highly controlled manner. However, the production of ready-made parts using FDM is quite tricky. At the same time, the mechanical properties of parts printed with current print parameters and low-cost 3D printers also vary. The quality and mechanical characteristics of the final part are influenced by production parameters such as the extrusion temperature, infill density, infill pattern, print speed, and layer height. This study focused on the effects of the infill pattern, infill density and print speed parameters on the tensile strength and production time of model structures printed with PLA+ material. The tensile strength of the printed parts have been determined by a WDM-100E model tensile testing machine. In addition, the tensile strengths and production times of the parts have been optimized by the signal-to-noise (SN) ratio analysis. The results reveal that triangle infill pattern exhibits the best tensile strength at 40 mm/sec printing speed and 100% infill density. On the other hand, the lowest production time is observed in the gyroid infill pattern.","PeriodicalId":11622,"journal":{"name":"El-Cezeri Fen ve Mühendislik Dergisi","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72885357","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}
Ship type recognition has gained serious interest in applications required in the maritime sector. A large amount of the studies in literature focused on the use of images taken by shore cameras, radar images, and audio features. In the case of image-based recognition, a very large number and variety of ship images must be collected. In the case of audio-based recognition, systems may suffer from the background noise. In this study, we present a method, which uses the frequency domain characteristics with an image-based deep learning network. The method computes the fast Fourier transform of sound records of ships and generates the frequency vs magnitude graphs as images. Next, the images are given into the ResNet50 network for classification. A public dataset with nine different ship types is used to test the performance of the proposed method. According to the results, we obtained a 99% accuracy rate.
{"title":"Ship Type Recognition using Deep Learning with FFT Spectrums of Audio Signals","authors":"M. E. Yıldırım","doi":"10.31202/ecjse.1149363","DOIUrl":"https://doi.org/10.31202/ecjse.1149363","url":null,"abstract":"Ship type recognition has gained serious interest in applications required in the maritime sector. A large amount of the studies in literature focused on the use of images taken by shore cameras, radar images, and audio features. In the case of image-based recognition, a very large number and variety of ship images must be collected. In the case of audio-based recognition, systems may suffer from the background noise. In this study, we present a method, which uses the frequency domain characteristics with an image-based deep learning network. The method computes the fast Fourier transform of sound records of ships and generates the frequency vs magnitude graphs as images. Next, the images are given into the ResNet50 network for classification. A public dataset with nine different ship types is used to test the performance of the proposed method. According to the results, we obtained a 99% accuracy rate.","PeriodicalId":11622,"journal":{"name":"El-Cezeri Fen ve Mühendislik Dergisi","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90827787","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}
Artificial neural networks have emerged as a promising tool for estimating hydrogen production process variables for reaction condition optimization. Here we aim to predict complex nonlinear systems that use of artificial neural networks for modeling hydrogen production via water electrolysis and to evaluate the common challenges that arise. To estimate the effect of different electrolyzer systems input parameters such as electrolyte material, electrolyte type, supplied power (voltage and current), temperature, and time on hydrogen production, a predictive model was developed. The percentage contributions of the input parameters to hydrogen production and the best network architecture to minimize computation time and maximize network accuracy were shown. The results show that the hydrogen production parameters from electrolysis and the predicted safety explosive limit are 7% of the average root mean square error. Furthermore, coefficient of determination value was found 0.93. This predicted value is very close to the observed values. The neural network algorithm developed in this study could be used to make critical decisions in the electrolysis process for parameters affecting hydrogen production.
{"title":"Modeling of Artificial Neural Networks for Hydrogen Production via Water Electrolysis","authors":"Gulbahar Bilgic, B. Öztürk","doi":"10.31202/ecjse.1172965","DOIUrl":"https://doi.org/10.31202/ecjse.1172965","url":null,"abstract":"Artificial neural networks have emerged as a promising tool for estimating hydrogen production process variables for reaction condition optimization. Here we aim to predict complex nonlinear systems that use of artificial neural networks for modeling hydrogen production via water electrolysis and to evaluate the common challenges that arise. To estimate the effect of different electrolyzer systems input parameters such as electrolyte material, electrolyte type, supplied power (voltage and current), temperature, and time on hydrogen production, a predictive model was developed. The percentage contributions of the input parameters to hydrogen production and the best network architecture to minimize computation time and maximize network accuracy were shown. The results show that the hydrogen production parameters from electrolysis and the predicted safety explosive limit are 7% of the average root mean square error. Furthermore, coefficient of determination value was found 0.93. This predicted value is very close to the observed values. The neural network algorithm developed in this study could be used to make critical decisions in the electrolysis process for parameters affecting hydrogen production.","PeriodicalId":11622,"journal":{"name":"El-Cezeri Fen ve Mühendislik Dergisi","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91025870","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}
In this study, the incipient wetness impregnation (IWI) method was used to prepare tin oxide nanoparticles supported on reduced graphene oxide nanosheets (SnO2/rGO). Characterize of catalyst composite were analyzed by X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR), Field emission scanning electron microscope (FESEM), energy dispersive X-ray spectroscopy (EDX), and Raman spectroscopy. The activity of the SnO2/rGO catalyst was evaluated in the catalytic oxidation process of dibenzothiophene (DBT) for modeled oil and diesel fuel in the presence of H2O2 as an oxidant. Optimum reaction conditions (the loading quantity of the tin oxide, the concentration of dibenzothiophene, the time of reaction, the temperature, the amount of oxidant, and the catalyst dosage) were investigated in a batch reactor. High-value of dibenzothiophene (DBT) removal from modeled oil samples was 79% at temperature = 60 ◦C, reaction time = 90 min, catalyst dosage = 0.04 g, amount of H2O2 = 0.375 mL, and 385 ppm concentration of dibenzothiophene. Catalyst activity at the same operating condition was also investigated for diesel fuel and the removal of sulfur was 41%
{"title":"Performance of tin oxide supported on reduced graphene oxide for oxidative desulfurization","authors":"Qahtan Mahmood","doi":"10.31202/ecjse.1210453","DOIUrl":"https://doi.org/10.31202/ecjse.1210453","url":null,"abstract":"In this study, the incipient wetness impregnation (IWI) method was used to prepare tin oxide nanoparticles supported on reduced graphene oxide nanosheets (SnO2/rGO). Characterize of catalyst composite were analyzed by X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR), Field emission scanning electron microscope (FESEM), energy dispersive X-ray spectroscopy (EDX), and Raman spectroscopy. The activity of the SnO2/rGO catalyst was evaluated in the catalytic oxidation process of dibenzothiophene (DBT) for modeled oil and diesel fuel in the presence of H2O2 as an oxidant. Optimum reaction conditions (the loading quantity of the tin oxide, the concentration of dibenzothiophene, the time of reaction, the temperature, the amount of oxidant, and the catalyst dosage) were investigated in a batch reactor. High-value of dibenzothiophene (DBT) removal from modeled oil samples was 79% at temperature = 60 ◦C, reaction time = 90 min, catalyst dosage = 0.04 g, amount of H2O2 = 0.375 mL, and 385 ppm concentration of dibenzothiophene. Catalyst activity at the same operating condition was also investigated for diesel fuel and the removal of sulfur was 41%","PeriodicalId":11622,"journal":{"name":"El-Cezeri Fen ve Mühendislik Dergisi","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78941822","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}
Küresel ölçekte elektrikli otomobil satışları 2021 yılında pandemi koşulları ve tedarik zincirinde yaşanan zorluklara rağmen rekor seviyeye ulaşarak, toplam elektrikli otomobil kullanımını 16,5 Milyonun üzerine çıkmasına ve söz konusu artışın yaklaşık 70% oranında bataryalı elektrikli araçlardan meydana gelmesine imkân sunmuştur. Birçok ülke tarafından bildirilen ve yakın geleceğe yönelik içten yanmalı motorlu araçların kısıtlamasına/yasaklanması dair açıklamalar; bu kapsamda sağlanan teşvikler, elektrikli araç pazarına olan yönelimi arttırmaktadır. Türkiye’de ise 2021 yılı verilerine göre elektrikli otomobil satışları, toplam satışlarının 5,03% karşılık gelmektedir. Artan elektrikli otomobil kullanımının, otomotiv endüstrisi için temel gereksinimlerden olan ve önemli bir ticari potansiyeli barındıran satış sonrası hizmet kulvarındaki bakım & onarım süreçlerine dair değişiklikleri beraberinde getirmesi beklenmektedir. Yapılan birçok araştırmada şehir içi kullanıma uygun elektrikli otomobillerin bakım & onarım maliyetlerinin, içten yanmalı motorlu otomobillere göre 20-35 % oranında daha ekonomik olduğu belirtilmektedir. Söz konusu bu avantaj özellikle filolar nezdinde daha da belirgin hale gelmekte; filolar için söz konusu maliyetlerin araç türüne ve kullanım amacına bağlı olarak araç bazında toplam sahip olma maliyetinin 7-12%' sine karşılık geldiği ifade edilmektedir. Bu çalışmada elektrikli araçlara özel periyodik bakım & onarım yaklaşımlarına yer verilecektir. Türkiye özelinde çok yeni olan işbu konuya dair bakış açısının geliştirilmesi hedeflenmektedir. Mevcut durumda standartlardan uzak ve birçok belirsizlikler yaşandığı değerlendirilen elektrikli araçlara özel bakım & onarım faaliyetleri için bireysel / kurumsal (kamu) kullanıcılarına hitaben, içten yanmalı motorlu araçlardan farklı olarak, araçların güç sistem bileşenlerini esas alan temel bakım & onarım süreç ve prosedürlerine değinilerek; konuya dair farkındalık sağlanılması hedeflenmektedir.
{"title":"Elektrikli Araçlara Özel Periyodik Bakım & Onarım Yaklaşımları","authors":"Orhan Topal","doi":"10.31202/ecjse.1161081","DOIUrl":"https://doi.org/10.31202/ecjse.1161081","url":null,"abstract":"Küresel ölçekte elektrikli otomobil satışları 2021 yılında pandemi koşulları ve tedarik zincirinde yaşanan zorluklara rağmen rekor seviyeye ulaşarak, toplam elektrikli otomobil kullanımını 16,5 Milyonun üzerine çıkmasına ve söz konusu artışın yaklaşık 70% oranında bataryalı elektrikli araçlardan meydana gelmesine imkân sunmuştur. Birçok ülke tarafından bildirilen ve yakın geleceğe yönelik içten yanmalı motorlu araçların kısıtlamasına/yasaklanması dair açıklamalar; bu kapsamda sağlanan teşvikler, elektrikli araç pazarına olan yönelimi arttırmaktadır. Türkiye’de ise 2021 yılı verilerine göre elektrikli otomobil satışları, toplam satışlarının 5,03% karşılık gelmektedir. Artan elektrikli otomobil kullanımının, otomotiv endüstrisi için temel gereksinimlerden olan ve önemli bir ticari potansiyeli barındıran satış sonrası hizmet kulvarındaki bakım & onarım süreçlerine dair değişiklikleri beraberinde getirmesi beklenmektedir. Yapılan birçok araştırmada şehir içi kullanıma uygun elektrikli otomobillerin bakım & onarım maliyetlerinin, içten yanmalı motorlu otomobillere göre 20-35 % oranında daha ekonomik olduğu belirtilmektedir. Söz konusu bu avantaj özellikle filolar nezdinde daha da belirgin hale gelmekte; filolar için söz konusu maliyetlerin araç türüne ve kullanım amacına bağlı olarak araç bazında toplam sahip olma maliyetinin 7-12%' sine karşılık geldiği ifade edilmektedir. \u0000Bu çalışmada elektrikli araçlara özel periyodik bakım & onarım yaklaşımlarına yer verilecektir. Türkiye özelinde çok yeni olan işbu konuya dair bakış açısının geliştirilmesi hedeflenmektedir. Mevcut durumda standartlardan uzak ve birçok belirsizlikler yaşandığı değerlendirilen elektrikli araçlara özel bakım & onarım faaliyetleri için bireysel / kurumsal (kamu) kullanıcılarına hitaben, içten yanmalı motorlu araçlardan farklı olarak, araçların güç sistem bileşenlerini esas alan temel bakım & onarım süreç ve prosedürlerine değinilerek; konuya dair farkındalık sağlanılması hedeflenmektedir.","PeriodicalId":11622,"journal":{"name":"El-Cezeri Fen ve Mühendislik Dergisi","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75384128","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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