Search results for: materials extraction

Authors: Masek A., Diakowska K., Zaborski M.

Abstract:

Polymeric materials have found their use almost in every branch of industry worldwide. Most of them constitute so-called “petropolymers" obtained from crude oil. However literature information sounds a warning that its global sources are running out. Thus, it seems that one should search for polymeric materials from renewable raw materials belonging to the group of green polymers. Therefore on account of environmental protection and the issue of sustainable technologies, nowadays greater and greater achievements have been observed in the field of green technology using engineering sciences to develop composite materials. The main aim of this study was to research what is the influence of biofillers on the properties. We used biofillers like : cellulose with different length of fiber, cellulose UFC100, silica and montmorillonite. In our research, we reported on biodegradable composites exhibitingspecificity properties by melt blending of polylactide (PLA), one of the commercially available biodegradable material, and epoxidized natural rubber (ENR) containing 50 mol.%epoxy group. Blending hydrophilic natural polymers and aliphatic polyesters is of significant interest, since it could lead to the development of a new range of biodegradable polymeric materials. We research the degradation of composites on the basis epoxidized natural rubber and poly(lactide). The addition of biofillers caused far-reaching degradation processes. The greatest resistance to biodegradation showed a montmorillonite-based mixtures, the smallest inflated cellulose fibers of varying length.The final aim in the present study is to use ENR and poly(lactide) to design composite from renewable resources with controlled degradation.

Keywords: renewable resources, biopolymer, degradation, polylactide

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Authors: T. Bielewicz, S. Dogan, C. Klinke

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Two-dimensional, solution-processable semiconductor materials are interesting for low-cost electronic applications [1]. We demonstrate the synthesis of lead sulfide nanosheets and how their size, shape and height can be tuned by varying concentrations of pre-cursors, ligands and by varying the reaction temperature. Especially, the charge carrier confinement in the nanosheets’ height adjustable from 2 to 20 nm has a decisive impact on their electronic properties. This is demonstrated by their use as conduction channel in a field effect transistor [2]. Recently we also showed that especially thin nanosheets show a high carrier multiplication (CM) efficiency [3] which could make them, through the confinement induced band gap and high photoconductivity, very attractive for application in photovoltaic devices. We are already able to manufacture photovoltaic devices out of single nanosheets which show promising results.

Keywords: physical sciences, chemistry, materials, chemistry, colloids, physics, condensed-matter physics, semiconductors, two-dimensional materials

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Authors: Shan Zhang, Peter Suechting

Abstract:

Predicting trade patterns is critical to decision-making in public and private domains, especially in the current context of trade disputes among major economies. In the past, U.S. recycling has relied heavily on strong demand for recyclable materials overseas. However, starting in 2017, a series of new recycling policies (bans and higher inspection standards) was enacted by multiple countries that were the primary importers of recyclables from the U.S. prior to that point. As the global trade flow of recycling shifts, some new importers, mostly developing countries in South and Southeast Asia, have been overwhelmed by the sheer quantities of scrap materials they have received. As the leading exporter of recyclable materials, the U.S. now has a pressing need to build its recycling industry domestically. With respect to the global trade in scrap materials used for recycling, the interest in this paper is (1) predicting how the export of recyclable materials from the U.S. might vary over time, and (2) predicting how international trade flows for recyclables might change in the future. Focusing on three major recyclable materials with a history of trade, this study uses data-driven and machine learning (ML) algorithms---supervised (shrinkage and tree methods) and unsupervised (neural network method)---to decipher the international trade pattern of recycling. Forecasting the potential trade values of recyclables in the future could help importing countries, to which those materials will shift next, to prepare related trade policies. Such policies can assist policymakers in minimizing negative environmental externalities and in finding the optimal amount of recyclables needed by each country. Such forecasts can also help exporting countries, like the U.S understand the importance of healthy domestic recycling industry. The preliminary result suggests that gravity models---in addition to particular selection macroeconomic predictor variables--are appropriate predictors of the total export value of recyclables. With the inclusion of variables measuring aspects of the political conditions (trade tariffs and bans), predictions show that recyclable materials are shifting from more policy-restricted countries to less policy-restricted countries in international recycling trade. Those countries also tend to have high manufacturing activities as a percentage of their GDP.

Keywords: environmental economics, machine learning, recycling, international trade

Procedia PDF Downloads 168

Authors: Ajay Kumar Singh, Arvind Kumar, S. P. Singh

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Cellulose nanofibrils (CNF) have shown potential of their extensive use in various fields, including papermaking, due to their unique characteristics. In this study, CNF’s were prepared by fibrillating the pulp obtained from raw materials e.g. bagasse, hardwood and softwood using enzymatic pretreatment followed by mechanical refining. These nanofibrils, when examined under FE-SEM, show that partial fibrillation on fiber surface has resulted in production of nanofibers. Mixing these nanofibers with the unrefined and normally refined fibers show their reinforcing effect. This effect is manifested in observing the improvement in the physical and mechanical properties e.g. tensile index and burst index of paper. Tear index, however, was observed to decrease on blending with nanofibers. The optical properties of paper sheets made from blended fibers showed no significant change in comparison to those made from only mechanically refined pulp. Mixing of normal pulp fibers with nanofibers show increase in ºSR and consequent decrease in drainage rate. These changes observed in mechanical, optical and other physical properties of the paper sheets made from nanofibrils blended pulp have been tried to explain considering the distribution of the nanofibrils alongside microfibrils in the fibrous network. Since usually, paper/boards with higher strength are observed to have diminished optical properties which is a drawback in their quality, the present work has the potential for developing paper/boards having improved strength alongwith undiminished optical properties utilising the concepts of nanoscience and nanotechnology.

Keywords: enzymatic pretreatment, mechanical refining, nanofibrils, paper properties

Procedia PDF Downloads 353

Authors: M. Khoukhi

Abstract:

Accurate prediction of the cooling/heating load and consequently, the sizing of the heating, ventilating, and air-conditioning equipment require precise calculation of the heat transfer mainly by conduction through envelope components of a building. The thermal resistance of most thermal insulation materials depends on the operating temperature. The temperature to which the insulation materials are exposed varies, depending on the thermal resistance of the materials, the location of the insulation layer within the assembly system, and the effective temperature which depends on the amount of solar radiation received on the surface of the assembly. The main objective of this paper is to investigate the change of the thermal conductivity of polystyrene insulation material in terms of the temperature at the mid-thickness of the material and its effect on the cooling load required by the building.

Keywords: operating temperature, polystyrene insulation, thermal conductivity, cooling load

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Authors: Sadek Salah

Abstract:

The determination of the strength characteristics of waste materials is essential when evaluating the stability of waste fills during initial placement and at the time of closure and rehabilitation of the landfill. Significant efforts, mostly experimental, have been deployed to date in attempts to quantify the mechanical properties of municipal wastes various stages of decomposition. Even though the studies and work done so far have helped in setting baseline parameters and characteristics for waste materials, inherent concerns remain as to the scalability of the findings between the laboratory and the field along with questions as to the suitability of the actual test conditions. These concerns are compounded by the complexity of the problem itself with significant variability in composition, placement conditions, and levels of decay of the various constituents of the waste fills. A complimentary, if not necessarily an alternative approach is to rely on field observations of behavior and instability of such materials. This paper describes an effort at obtaining relevant shear strength parameters from back-analyses of failures which have been observed at a major un-engineered waste fill along the Mediterranean shoreline. Results from the limit-equilibrium failure back-analyses are presented and compared to results from laboratory-scale testing on comparable waste materials.

Keywords: solid waste, shear strength, landfills, slope stability

Procedia PDF Downloads 242

Authors: A. Brahma

Abstract:

Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.

Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction

Procedia PDF Downloads 337

Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

Abstract:

Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

Abstract:

Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

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Authors: Sonjida Mustafia

Abstract:

Glass-ceramic is a material that contains both the properties of glass and ceramic within. They always contain a residual glassy phase and one or more embedded crystalline phases. Ceramic tiles are very popular in the world because of their high structural strength, low absorption, increased hygiene, and hot and cold insulation. Glass-ceramic materials are used to produce marble-like floor and wall tiles. There are a huge amount of waste materials like rice husk ash (RHA), waste iron, waste glass, and other industrial solid waste in Bangladesh, which can be used to produce glass-ceramic floor and wall tiles. The raw materials (rice husk ash, waste glass, and k-feldspar) are a mixture, and the mixture is melted to form glass frit at 1175°C. The frits are grained to require fine particle size. The powder is moistened in 7-8% water with sodium silicate. The green glass-ceramic tiles were fired at different temperatures (800–1100°C) for a soaking time of 1 hour to form glass-ceramic tiles and to study the sintering-crystallization process. The results reveal that the modulus of rupture increases with increasing sintering temperature and reaches the highest value (95.25Mpa) at 925°C. Glossiness and linear shrinkage increase with increasing temperature.

Keywords: rice husk ash, waste glass, glass-ceramic, modulus of rupture, glossiness, linear shrinkage, micro-structure

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Authors: Štěpán Hýsek, Petra Gajdačová, Milan Podlena

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Annual plants are becoming more and more popular source of lignin and cellulose. In those days a lot of research is carried out in order to evaluate the possibility of utilization of fibres and particles from these plants in composite materials production. These lingo-cellulosic materials seem to be a great alternative to wood, however, due to waxy and silica layers on the surface of these stalks, one additional technological step is needed–erosion of the layers for the purpose of achieving better adhesion between particle and adhesive. In this research, we used several kinds of particle pre-treatment, in order to modify surface properties of these particles. Further, an adhesive was applied to the particles using laboratory blender and board were produced using laboratory press. Both physical and mechanical properties of boards were observed. It was found out that the surface modification of particles had statistically significant effect on properties of produced boards.

Keywords: annual plant, composites, mechanical properties, particleboard

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Authors: Prashanth Pillai, Purnaprajna Mangsuli

Abstract:

Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

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Authors: P. Karthick, K. Mahesh

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Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

Procedia PDF Downloads 187

Authors: Adedayo Jeremiah Adeyekun, Samuel Oluwagbemiga Ishola

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This research aims to study the use of traditional building materials for the repair and refurbishment of historic buildings in India and to provide an authentic treatment of historical buildings that will be highly considered by taking into consideration the new standards of rehabilitating process. This can be proven to be an effective solution over modern impervious material due to its compatibility with traditional building methods and materials. For example, their elastoplastic properties allow accommodating movement due to settlement or moisture/temperature changes without cracking. The use of lime also enhances workability, water retention and bond characteristics. Lime is considered to be a natural, traditional material, but it is also sustainable and energy-efficient, with production powered by biomass and emissions up to 25% less than cementitious materials. However, there is a lack of comprehensive data on the impact of lime‐based materials on the energy efficiency and thermal properties of traditional buildings and structures. Although lime mortars, renders and plasters were largely superseded by cement-based products in the first half of the 20th century, lime has a long and proven track record dating back to ancient times. This was used by the Egyptians in 4000BC to construct the pyramids. This doesn't mean that lime is an outdated technology, nor is it difficult to be used as a material. In fact, lime has a growing place in modern construction, with increasing numbers of designers choosing to use lime-based products because of their special properties. To carry out this research, some historic buildings will be surveyed and information will be derived from the textbooks and journals related to Architectural restoration.

Keywords: lime, materials, historic, buildings, sustainability

Procedia PDF Downloads 166

Authors: Hozaifa Zaki, Ghada Soliman

Abstract:

In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.

Keywords: computer vision, deep learning, image processing, character recognition

Procedia PDF Downloads 82

Authors: Passant Youssef, Ahmed El-Tair, Amr El-Nemr

Abstract:

Lately, with the environmental changes, enthusiasts trigger to stop the contamination of environment. Thus, various efforts were exerted for innovating environmental friendly concrete to sustain as a ‘Green Building’ material. Green building materials consider the cement industry as one of the most sources of air pollutant with high rate of carbon dioxide (CO₂) emissions. Several methods were developed to extensively reduce the influence of cement industry on environment. These methods such as using supplementary cementitious material or improving the cement manufacturing process are still under investigation. However, with the presence of recycled wastes from construction and finishing materials, the use of supplementary cementitious materials seems to provide an economic solution. Furthermore, it improves the mechanical properties of cement paste, in addition to; it modulates the workability and durability of concrete. In this paper, the glass powder was considered to be used as partial replacement of cement. This study provided the mechanical influence for using the glass powder as partial replacement of cement. In addition, it examines the microstructure of cement mortar using scanning electron microscope and X-ray diffraction. The cement in concrete is replaced by waste glass powder in steps of 5%, 10%, 15%, 20% and 25% by weight of cement and its effects on compressive and flexure strength were determined after 7 and 28 days. It was found that the 5% glass powder replacement increased the 7 days compressive strength by 20.5%, however, there was no increase in compressive strength after 28 days; which means that the glass powder did not react in the cement mortar due to its amorphous nature on the long run, and it can act as fine aggregate better that cement replacement. As well as, the 5% and 10% glass powder replacement increased the 28 days flexural strength by 46.9%. SEM micrographs showed very dense matrix for the optimum specimen compared to control specimen as well; some glass particles were clearly observed. High counts of silica were optimized from XRD while amorphous materials such as calcium silicate cannot be directly detected.

Keywords: supplementary materials, glass powder, concrete, cementitious materials

Procedia PDF Downloads 210

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 60

Authors: I. Benhsine, M. Hellou, F. Lominé, Y. Roques

Abstract:

During the manufacture of fertilizer, it is necessary to add water for granulation purposes. The water content is then removed or reduced using rotary dryers. They are commonly used to dry wet granular materials and they are usually fitted with lifting flights. The transport of granular materials occurs when particles cascade from the lifting flights and fall into the air stream. Each cascade consists of a lifting and a falling cycle. Lifting flights are thus of great importance for the transport of granular materials along the dryer. They also enhance the contact between solid particles and the air stream. Optimization of the drying process needs an understanding of the behavior of granular materials inside a rotary dryer. Different approaches exist to study the movement of granular materials inside the dryer. Most common of them are based on empirical formulations or on study the movement of the bulk material. In the present work, we are interested in the behavior of each particle in the cross section of the dryer using Discrete Element Method (DEM) to understand. In this paper, we focus on studying the hold-up, the cascade patterns, the falling time and the falling length of the particles leaving the flights. We will be using two segment flights. Three different profiles are used: a straight flight (180° between both segments), an angled flight (with an angle of 150°), and a right-angled flight (90°). The profile of the flight affects significantly the movement of the particles in the dryer. Changing the flight angle changes the flight capacity which leads to different discharging profile of the flight, thus affecting the hold-up in the flight. When the angle of the flight is reduced, the range of the discharge angle increases leading to a more uniformed cascade pattern in time. The falling length and the falling time of the particles also increase up to a maximum value then they start decreasing. Moreover, the results show an increase in the falling length and the falling time up to 70% and 50%, respectively, when using a right-angled flight instead of a straight one.

Keywords: discrete element method, granular materials, lifting flight, rotary dryer

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Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng

Abstract:

The adsorptive ability of different carbon materials, tire char (TC), demineralized tire char (DTC), activated tire char (ATC) and Aldrich supplied commercial activated carbon (CAC) was studied for desulfurization of tire pyrolytic oil (TPO). TPO with an initial sulfur content of 7767.7 ppmw was used in this present study. Preparation of ATC was achieved by chemical treatment of raw TC using a potassium hydroxide (KOH) solution and subsequent activation at 800°C in the presence of nitrogen. The thermal behavior of TC, surface microstructure, and the surface functional groups of the carbon materials was investigated using TGA, SEM, and FTIR, respectively. Adsorptive desulfurization of TPO using the carbon materials was performed and they performed in the order of CAC>ATC>DTC>TC. Adsorption kinetics were studied, and pseudo-first order kinetic model displayed a better fit compared to pseudo-second order model. For isotherm studies, the Freundlich isotherm model fitted to the equilibrium data better than the Langmuir isotherm model.

Keywords: ATC, desulfurization, pyrolysis, tire, TPO

Procedia PDF Downloads 116

Authors: Abdelmalk Brahma

Abstract:

Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.

Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction

Procedia PDF Downloads 264

Authors: Hien Thi Dieu Truong, Mahmoud Al-Sarayreh, Pullanagari Reddy, Marlon M. Reis, Richard Archer

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New Zealand mānuka honey is a honeybee product derived mainly from Leptospermum scoparium nectar. The potent antibacterial activity of mānuka honey derives principally from methylglyoxal (MGO), in addition to the hydrogen peroxide and other lesser activities present in all honey. MGO is formed from dihydroxyacetone (DHA) unique to L. scoparium nectar. Mānuka honey also has an idiosyncratic phenolic profile that is useful as a chemical maker. Authentic mānuka honey is highly valuable, but almost all honey is formed from natural mixtures of nectars harvested by a hive over a time period. Once diluted by other nectars, mānuka honey irrevocably loses value. We aimed to apply hyperspectral imaging to honey frames before bulk extraction to minimise the dilution of genuine mānuka by other honey and ensure authenticity at the source. This technology is non-destructive and suitable for an industrial setting. Chemometrics using linear Partial Least Squares (PLS) and Support Vector Machine (SVM) showed limited efficacy in interpreting chemical footprints due to large non-linear relationships between predictor and predictand in a large sample set, likely due to honey quality variability across geographic regions. Therefore, an advanced modelling approach, one-dimensional convolutional neural networks (1D-CNN), was investigated for analysing hyperspectral data for extraction of biochemical information from honey. The 1D-CNN model showed superior prediction of honey quality (R² = 0.73, RMSE = 2.346, RPD= 2.56) to PLS (R² = 0.66, RMSE = 2.607, RPD= 1.91) and SVM (R² = 0.67, RMSE = 2.559, RPD=1.98). Classification of mono-floral manuka honey from multi-floral and non-manuka honey exceeded 90% accuracy for all models tried. Overall, this study reveals the potential of HSI and deep learning modelling for automating the evaluation of honey quality in frames.

Keywords: mānuka honey, quality, purity, potency, deep learning, 1D-CNN, chemometrics

Procedia PDF Downloads 139

Authors: Hamed Khezrzadeh

Abstract:

Many investigations on the micromechanical structure of materials indicate that there exist fractal patterns at the micro scale in some of the main construction and industrial materials. A recently presented micro-fractal theory brings together the well-known periodic homogenization and the fractal geometry to construct an appropriate model for determination of the mechanical properties of particle reinforced composite materials. The proposed multi-step homogenization scheme considers the mechanical properties of different constituent phases in the composite together with the interaction between these phases throughout a step-by-step homogenization technique. In the proposed model the interaction of different phases is also investigated. By using this method the effect of fibers grading on the mechanical properties also could be studied. The theory outcomes are compared to the experimental data for different types of particle-reinforced composites which very good agreement with the experimental data is observed.

Keywords: fractal geometry, homogenization, micromehcanics, particulate composites

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Authors: A. Feliczak Guzik, I. Nowak

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Zeolites, classified as microporous materials, are a large group of crystalline aluminosilicate materials commonly used in the chemical industry. These materials are characterized by large specific surface area, high adsorption capacity, hydrothermal and thermal stability. However, the micropores present in them impose strong mass transfer limitations, resulting in low catalytic performance. Consequently, mesoporous (hierarchical) zeolites have attracted considerable attention from researchers. These materials possess additional porosity in the mesopore size region (2-50 nm according to IUPAC). Mesoporous zeolites, based on commercial MFI-type zeolites modified with silver, were synthesized as follows: 0.5 g of zeolite was dispersed in a mixture containing CTABr (template), water, ethanol, and ammonia under ultrasound for 30 min at 65°C. The silicon source, which was tetraethyl orthosilicate, was then added and stirred for 4 h. After this time, silver(I) nitrate was added. In a further step, the whole mixture was filtered and washed with water: ethanol mixture. The template was removed by calcination at 550°C for 5h. All the materials obtained were characterized by the following techniques: X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), nitrogen adsorption/desorption isotherms, FTIR spectroscopy. X-ray diffraction and low-temperature nitrogen adsorption/desorption isotherms revealed additional secondary porosity. Moreover, the structure of the commercial zeolite was preserved during most of the material syntheses. The aforementioned materials were used in the epoxidation reaction of cyclohexene using conventional heating and microwave radiation heating. The composition of the reaction mixture was analyzed every 1 h by gas chromatography. As a result, about 60% conversion of cyclohexene and high selectivity to the desired reaction products i.e., 1,2-epoxy cyclohexane and 1,2-cyclohexane diol, were obtained.

Keywords: catalytic application, characterization, epoxidation, hierarchical zeolites, synthesis

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Authors: E. C. Mattos, V. S. M. G. Daros, R. Dal Col, A. L. Nascimento

Abstract:

The aim of this study is to present the results of a retrospective survey on the foreign matter found in foods analyzed at the Adolfo Lutz Institute, from July 2001 to July 2015. All the analyses were conducted according to the official methods described on Association of Official Agricultural Chemists (AOAC) for the micro analytical procedures and Food and Drug Administration (FDA) for the macro analytical procedures. The results showed flours, cereals and derivatives such as baking and pasta products were the types of food where foreign matters were found more frequently followed by condiments and teas. Fragments of stored grains insects, its larvae, nets, excrement, dead mites and rodent excrement were the most foreign matter found in food. Besides, foreign matters that can cause a physical risk to the consumer’s health such as metal, stones, glass, wood were found but rarely. Miscellaneous (shell, sand, dirt and seeds) were also reported. There are a lot of extraneous materials that are considered unavoidable since are something inherent to the product itself, such as insect fragments in grains. In contrast, there are avoidable extraneous materials that are less tolerated because it is preventable with the Good Manufacturing Practice. The conclusion of this work is that although most extraneous materials found in food are considered unavoidable it is necessary to keep the Good Manufacturing Practice throughout the food processing as well as maintaining a constant surveillance of the production process in order to avoid accidents that may lead to occurrence of these extraneous materials in food.

Keywords: extraneous materials, food contamination, foreign matter, surveillance

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Authors: Flavio Araujo, Livia Dias, Fabiolla Lima, Paulo Scalize, Antonio Albuquerque

Abstract:

Water treatment residues (WTR) are solid waste produced during drinking water treatment and have recently been seen as a reusable material. The aim of this research was show how to use the residue generated in a Water Treatment Plant, located in Goiania, Brazil, following the considerations of the law of solid waste to obtain normative parameters and consider sustainable alternatives for reincorporation of the residues in the productive chain for manufacturing various materials construction. In order to reduce the environmental liabilities generated by sanitation companies and discontinue unsustainable forms of disposal. The analyzes performed: Granulometry, Scanning Electron Microscopy and X-Ray Diffraction demonstrated the potential application of residues to replace the soil and sand, because it has characteristics compatible with small aggregate and can be used as feedstock for the manufacture of materials as ceramic and soil-cement bricks, mortars, interlocking floors and concrete artifacts.

Keywords: residue, sustainable, water treatment plants, WTR, WTP

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Authors: Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Sakir Tasdemir, Sevda Altin

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In this study, an experimental study was executed related to the strength of wooden materials which have been commonly used both in the past and present against pressure and whether fire retardant materials used against fire have any effects or not. Totally, 81 samples which included three different wood species, three different sizes, two different fire retardants and two unprocessed samples were prepared. Compressive pressure tests were applied to the prepared samples, their variance analyses were executed in accordance with the obtained results and it was aimed to determine the most convenient wooden materials and fire-retardant coating material. It was also determined that the species of wood and the species of coating caused the decrease and/or increase in the resistance against pressure.

Keywords: resistance of wood against pressure, species of wood, variance analysis, wood coating, wood fire safety

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Authors: Amina Ramadni, Safia Taleb, André Dératani

Abstract:

The present study presents, firstly, to characterize the physicochemical quality of brackish groundwater of the Terminal Complex (TC) from the region of Eloued-souf and to investigate the presence of fluoride, and secondly, to study the comparison of adsorbing power of three materials, such as (activated alumina AA, sodium clay SC and hydroxyapatite HAP) against the groundwater in the region of Eloued-souf. To do this, a sampling campaign over 16 wells and consumer taps was undertaken. The results show that the groundwater can be characterized by very high fluoride content and excessive mineralization that require in some cases, specific treatment before supply. The study of adsorption revealed removal efficiencies fluoride by three adsorbents, maximum adsorption is achieved after 45 minutes at 90%, 83.4% and 73.95%, and with an adsorbed fluoride content of 0.22 mg/L, 0.318 mg/L and 0.52 mg/L for AA, HAP and SC, respectively. The acidity of the medium significantly affects the removal fluoride. Results deducted from the adsorption isotherms also showed that the retention follows the Langmuir model. The adsorption tests by adsorbent materials show that the physicochemical characteristics of brackish water are changed after treatment. The adsorption mechanism is an exchange between the OH^- ions and fluoride ions. Three materials are proving to be effective adsorbents for fluoride removal that could be developed into a viable technology to help reduce the salinity of the Saharan hyper-fluorinated waters. Finally, a comparison between the results obtained from the different adsorbents allowed us to conclude that the defluoridation by AA is the process of choice for many waters of the region of Eloued-souf, because it was shown to be a very interesting and promising technique.

Keywords: fluoride removal, hydrochemical characterization of groundwater, natural materials, nanofiltration

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Authors: J. Chow

Abstract:

In laboratory settings, this study measured and reported the effects of undergraduate students watching animated videos on learning microeconomics as compared with the effectiveness of reading written texts. The study described an experiment on learning microeconomics in higher education using two different types of learning materials. It reported the effectiveness on microeconomics learning of watching animated videos and reading written texts. Undergraduate students in the university were randomly assigned to either a ‘video group’ or a ‘text group’ in the experiment. Previously-validated multiple-choice questions on fundamental concepts of microeconomics were administered. Both groups showed improvement between the pre-test and post-test. The experience of learning using text and video materials was also assessed. After controlling the student characteristics variables, the analyses showed that both types of materials showed comparable level of perceived learning experience. The effect size and statistical significance of these results supported the hypothesis that animated video is an effective alternative to text materials as a learning tool for students. The findings suggest that such animated videos may support teaching microeconomics in higher education.

Keywords: animated videos for education, laboratory experiment, microeconomics education, undergraduate economics education

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Authors: Andrei Tiberiu Cucuruz, Ecaterina Andronescu, Cristina Daniela Ghitulica, Andreia Cucuruz

Abstract:

In modern dentistry, the application of resin-based composites continues to increase and in the majority of countries has completely replaced mercury amalgams. Alumina (Al2O3) is a representative bioinert ceramic with a variety of applications in industry as well as in medicine. Alumina has the potential to improve electrical resistivity and thermal conductivity of polymers. The application of poly(methacrylic acid) (PMAA) in medicine was poorly investigated in the past but can lead to good results by the incorporation of alumina particles that can bring bioinertness to the composite. However, because of the differences related to chemical bonding of these materials, the interaction is very weak at the interface leading to no significant values in practical situations. The aim of this work was to modify the structure of alumina with silane coupling agents and to study the influence of silanization on the physicomechanical properties of the resulting composite materials. Two silanes were used in this study: 3-aminopropyl-trimethoxysilane (APTMS) and dichlorodimethylsilane (DCDMS). Both silanes proved to have a significant effect on the overall performance of composites by establishing bonds with the polymer matrix and the filler. All these improvements in dental adhesive systems made for bonding resin composites to tooth structure have enhanced the clinical application of polymeric restorative materials to the position that they are now considered the material of choice for esthetic restoration.

Keywords: alumina, compressive strength, dental materials, silane coupling agents, poly(methacrylic acid)

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Authors: Brandtner-Hafner Martin

Abstract:

Adhesives have established themselves as an innovative joining technology in the industry. Their strengths lie in joining different materials, avoiding structural weakening as in welding or screwing, and enabling lightweight construction methods. Now there are a variety of ways to improve the efficiency and effectiveness of bonded joints. One way is to add fiber fillers. This leads to an improvement in adhesion and cohesion (structural integrity). In this study, the effectiveness of fiber-modified adhesives for bonding different construction materials is reviewed. A series of experimental tests were performed using the fracture analytical GF principle to study the adhesive bonding safety and performance of the joint. Three different structural adhesive systems based on epoxy, CA/A hybrid, and PUR were modified with different fiber materials on different substrates. The results show that significant performance improvements can be achieved and that bonding reliability can be sustainably increased.

Keywords: fiber-modified adhesives, bonding safety, GF-principle, fracture analysis

Procedia PDF Downloads 173