Effect of coke properties on anode properties = Effet des propriétés du coke sur les propriétés d'anodes

One of the major components of the primary aluminum fabrication process is carbon anode manufacturing. High density, low electrical resistivity, and consistence of the quality of anodes are of utmost interest in aluminum industry. This work was undertaken to determine the desired coke properties which have notable impact on coke/pitch wetting and the influence of some of these properties on anode quality, and finally to identify the factors effecting the consumption of industrial anodes throughout the entire process. Wettability of a coke by a pitch provides important information about the compatibility of a coke/pitch pair and mixing conditions. The ability of a liquid pitch to wet petroleum coke can be determined by means of the sessile-drop test. Different surface characterization techniques (SEM, optical microscopy, FT-IR, XPS, etc.) are used to establish the relation between the surface characteristics of different calcined cokes and their wettability by pitch. Physical characteristics such as crystalline length, porosity, and shape of coke particles were measured by XRD, pycnometer, and optical microscope, respectively. The factors that had the greatest influence on pitch wettability were coke porosity, particle shape, crystalline length, and finally surface chemical compositions. The available anode-quality petroleum coke is not sufficient to cover the need created by the increase in the world aluminum production. Understanding the consequences of varying calcined coke quality is necessary to possibly compensate and adjust the anode paste recipe in the subsequent use of coke in order to obtain economically viable production of aluminium. A new anode recipe (by adjusting the medium fraction in the paste) was proposed based on the predictions of an ANN model, which resulted in improved anode properties. Combined effects of coke calcination level, anode baking level, and sulfur content on anode properties were studied. Under-calcined coke gained interest as raw material for anodes used in aluminum production since it was reported in the literature that anodes produced with this coke have lower CO2 reactivity in the electrolytic cell. The cokified pitch and the petroleum coke reactivity become similar in anodes made of under-calcined coke depending on their baking conditions. Reactivities of the anodes produced from under-calcined coke were compared with those of the anodes produced from standard calcined coke. The former exhibited lower air reactivity and dusting (due to air reactivity) as well as similar CO2 reactivities and lower dusting (due to CO2 reactivity) at lower baking temperatures. Additionally, increase in sulfur was found to increase the air reactivity and decrease the carboxy reactivity. Dusting due to both air and CO2 reactivities decreased as the sulfur content increased. Increasing baking temperatures decreased both of the reactivities and dusting. The effects of the process parameters of industrial anode production as well as the impact of raw material properties on pitch distribution in anodes were studied. Pitch acts as the binder material for coke and butt, and its homogeneous distribution in a green anode has a great influence on the properties of baked anodes. An image analysis technique was developed by the UQAC/AAI Chair, which was used to analyze and quantify the weight percentages of pitch in green and baked anodes. This study demonstrated that the pitch distribution in a green/baked anode is dependent on different process parameters and raw materials used. The influence of top bellow pressure, paste recipe (amount of fine and recycled butts), and anode properties (crystalline length and electrical resistivity) on anode CO2 reactivity was studied extensively by developing an ANN model. It was found that the CO2 reactivity increases with increasing anode crystalline length, amount of fine particles, recycled butt content, and electrical resistivity and decreases with increasing bellow pressure. During mixing, the coarse particles might break, which would change the anode recipe, consequently, the anode properties. An inexpensive, quick, and nontoxic pitch separation method was developed. This method helps study the kneader performance by closely monitoring the effect of kneading action on granulometry during paste preparation. Considering all the findings of this work, this thesis constitutes a major technical and scientific contribution in the field of carbon anode production. La fabrication des anodes en carbone représente l'un des principaux éléments du processus de production de l'aluminium primaire. L’intérêt principal de l'industrie de l'aluminium est de former des anodes de haute densité avec une constance au niveau de la qualité. Ce travail a été entrepris pour l’identification de propriétés du coke qui présente une influence significative sur la mouillabilité du coke par le brai, l'évaluation de l’impact de certaines de ces propriétés sur la qualité des anodes et finalement l’identification des facteurs affectant la consommation des anodes industrielles dans toutes les étapes du procédé de fabrication des anodes. La mouillabilité du coke par le brai fournit des informations importantes sur la compatibilité du pair coke/brai et sur les conditions de malaxage. Les interactions qui ont lieu à ce stade affectent directement les propriétés finales de l’anode. La capacité d’un brai liquide à mouiller le coke de pétrole est déterminée par le test de la goutte-sessile. Différentes techniques de caractérisation de surface (MEB, microscopie optique, FT-IR, XPS, etc.) ont été utilisées pour établir la relation entre les caractéristiques surfaciques pour différents cokes calcinés et leurs mouillabilités par le brai. Les caractéristics physiques comme la longueur cristalline, la porosité, et la forme des particules de coke ont été mesurées respectivement par la diffraction des rayons X (XRD), le pycnomètre, et le microscope optique. Les facteurs qui ont eu la plus grande influence sur la mouillabilité du brai étaient la porosité du coke, la forme des particules, la longueur cristalline, et finalement la composition chimique de surface. La qualité du coke de pétrole disponible pour fabriquer les anodes n’est pas suffisante pour couvrir les exigences survenues par l'augmentation de la production mondiale de l’aluminium. La compréhension des conséquences de la variation de la qualité du coke calciné est nécessaire pour ajuster la recette de pâte d’anode pour ces différents cokes afin d’obtenir une production économique de l’aluminium. Une recette d’anode améliorée (en optimisant la quantité de la fraction moyenne dans la pâte) présentant une amélioration au niveau des propriétés des anodes a été formulée en se basant sur les prédictions d’un modèle de réseaux de neurones artificiels (RNN). Les effets combinés du niveau de calcination de coke, de la température de cuisson de l’anode et de la teneur en soufre sur les propriétés des anodes ont été étudiés. L’intérêt pour l’utilisation du coke sous calciné comme matière première pour la production de l’aluminium a augmenté car il a été rapporté dans la littérature que les anodes produites avec le coke sous calciné ont de faibles réactivités au CO2 dans les cuves d’électrolyse. Les réactivités du brai cokifié et du coke de pétrole deviennent similaires dans les anodes faites avec du coke sous-calciné dépendant les conditions de cuisson. L'étude a confirmé que les anodes produites avec du coke sous calciné démontraient une diminution des réactivités et des poussières à des températures de cuisson moins élevées. De plus, le soufre agit comme un catalyseur dans le cas de la réactivité à l’air et comme un inhibiteur pour la réactivité au CO2. Dans cette partie de l’étude, l'effet des paramètres du processus de la fabrication des anodes industrielles et l’influence des propriétés des matières premières sur la distribution du brai dans les anodes ont été étudiés. Le brai agit comme un liant pour le coke et le mégot et sa répartition homogène dans une anode crue à une grande influence sur les propriétés des anodes cuites. Une technique de l'analyse d'image a été développée par la chaire UQAC/AAI permettant d'analyser et de quantifier les pourcentages en poids du brai dans les anodes crues et cuites. Cette étude a démontré que la distribution du brai dans les anodes crues et cuites dépend des différents paramètres du procédé et des matières premières utilisées. Un modèle RNA a été développé afin d’étudier l’influence de la pression des ballons du haut, de la recette de la pâte (la quantité des fines et des mégots) et les propriétés des anodes (longueur cristalline et résistivité électrique) sur la réactivité au CO2 des anodes. Il a été obtenu que la réactivité au CO2 augmente avec l’augmentation de la longueur cristalline de l'anode, de la quantité des particules fines et des mégots et de la résistivité électrique des anodes. Une diminution de la réactivité au CO2 a été observée avec l'augmentation de la pression des ballons du haut. Durant le malaxage, les grosses particules pourraient être cassées, ce qui changerait la recette d'anode et par conséquent les propriétés des anodes. Une méthode simple, non toxique, rapide et peu chère pour l’extraction du brai a été développée. Cette méthode permet d’étudier la performance du malaxeur et l'effet de malaxage sur la granulométrie pendant la préparation de la pâte. En considérant tous les résultats de cette étude, cette thèse constitue une contribution technique et scientifique majeure dans le domaine de la fabrication des anodes de carbone

Analyzing the cosmic web environment in the vicinity of grand-design and flocculent spirals with local geometric index

We explore the environment of a combined set of $367$ grand-design and $619$ flocculent spiral galaxies. We introduce a novel estimator called the \textit{local geometric index} to quantify the morphology of the local environment of these $986$ spirals. The local geometric index allows us to classify the environment of galaxies into voids, sheets, filaments, and clusters. We find that grand-designs are mostly located in dense environments like clusters and filaments ($\sim 78\%$), whereas the fraction of the flocculents lying in sparse environments like voids and sheets is significantly higher ($> 10\%$) than that of the grand-designs. A $p$-value $<$ $10 ^{-3}$ from a Kolmogorov-Smirnov test indicates that our results are statistically significant at $99.9\%$ confidence level. Further, we note that dense environments with large tidal flows are dominated by the grand-designs. On the other hand, low-density environments such as sheets and voids favor the growth of flocculents.Comment: Accepted for publication in JCAP. arXiv admin note: substantial text overlap with arXiv:2302.0808

Identification of Grand-design and Flocculent Spirals from SDSS using Convolutional Neural network

Spiral galaxies can be classified into the {\it Grand-designs} and {\it Flocculents} based on the nature of their spiral arms. The {\it Grand-designs} exhibit almost continuous and high contrast spiral arms and are believed to be driven by density waves, while the {\it Flocculents} have patchy and low-contrast spiral features and are primarily stochastic in origin. We train a convolutional neural network (CNN) model to classify spirals into {\it Grand-designs} and {\it Flocculents}, with a testing accuracy of $\mathrm{97.2\%}$. We then use the above model for classifying $\mathrm{1,354}$ new spirals from the SDSS. Out of these, $\mathrm{721}$ were identified as {\it Flocculents}, and the rest as {\it Grand-designs}. We find the median asymptotic rotational velocities of our newly classified {\it Grand-designs} and {\it Flocculents} are $218 \pm 86$ and $145 \pm 67$ respectively, indicating that the {\it Grand-designs} are mostly the high-mass and the {\it Flocculents} the intermediate-mass spirals. This is further corroborated by the observation that the median morphological indices of the {\it Grand-designs} and {\it Flocculents} are $2.6 \pm 1.8$ and $4.7 \pm 1.9$ respectively, implying that the {\it Flocculents} primarily consist of a late-type galaxy population in contrast to the {\it Grand-designs}. Finally, an almost equal fraction of of bars $\sim$ 0.3 in both the classes of spiral galaxies reveals that the presence of a bar component does not regulate the type of spiral arm hosted by a galaxy. Our results may have important implications for formation and evolution of spiral arms in galaxies.Comment: 19 pages, 8 figures (Accepted for publication in the MNRAS

Coke–pitch interactions during anode preparation

The information on the interactions between coke and pitch is of great value for the aluminum industry. This information can help choose the suitable coke and pitch pairs as well as the appropriate mixing parameters to be used during the production of anodes. In this study, the interaction mechanisms of pitch and coke at the mixing stage were studied by a sessile-drop test using two coal-tar pitches as the liquid and three petroleum cokes as the substrate. The results showed that the coke–pitch interactions are related to both pitch and coke chemical compositions. The contact angle of different coke–pitch systems decreased with increasing time and temperature. At high temperatures, decreasing the pitch viscosity facilitated the spreading of pitch and its penetration into the coke bed. The chemical behavior of petroleum cokes and coal tar pitches were studied using the FT-IR spectroscopy and XPS. The results showed that the wettability behavior of cokes by pitches depends on their physical properties as well as the presence of surface functional groups of coke and pitch which can form chemical bonds

Automated Knowledge Modeling for Cancer Clinical Practice Guidelines

Clinical Practice Guidelines (CPGs) for cancer diseases evolve rapidly due to new evidence generated by active research. Currently, CPGs are primarily published in a document format that is ill-suited for managing this developing knowledge. A knowledge model of the guidelines document suitable for programmatic interaction is required. This work proposes an automated method for extraction of knowledge from National Comprehensive Cancer Network (NCCN) CPGs in Oncology and generating a structured model containing the retrieved knowledge. The proposed method was tested using two versions of NCCN Non-Small Cell Lung Cancer (NSCLC) CPG to demonstrate the effectiveness in faithful extraction and modeling of knowledge. Three enrichment strategies using Cancer staging information, Unified Medical Language System (UMLS) Metathesaurus & National Cancer Institute thesaurus (NCIt) concepts, and Node classification are also presented to enhance the model towards enabling programmatic traversal and querying of cancer care guidelines. The Node classification was performed using a Support Vector Machine (SVM) model, achieving a classification accuracy of 0.81 with 10-fold cross-validation

Effect of coke granulometry on the properties of carbon anodes based on experimental study and ANN analysis

The available anode-quality petroleum coke is not sufficient to cover the need created by the increase in the world aluminum production. Understanding the consequences of varying calcined coke quality is necessary to possibly compensate for the reduction in coke quality and adjust the anode paste recipe in the subsequent use of coke in order to obtain economically viable production of aluminum. Different fractions of coke particles were mixed to optimize the anode recipe; however, it was laborious to find experimentally the suitable percentage of each fraction in anode paste which would give good anode properties. In this study, Artificial Neural Network (ANN) model was developed for adjusting the granulometry of the raw materials for anode production. Tapped bulk density of dry aggregates was used to predict the anode paste recipe using the ANN method. A new anode recipe (by adjusting the medium fraction in the paste) was proposed based on the predictions of an ANN model, which resulted in improved anode properties

Characterization of dry aggregates in carbon anodes by image analysis

Carbon anode is one of the key components in the electrolytic production of primary aluminum. Anodes are mainly composed of dry aggregates such as calcined petroleum coke and recycled materials with pitch as the binder. Granulometry of the dry aggregates is important to obtain good physical, chemical, electrical, and mechanical anode properties. Sieving can indicate the size range of particles, but it does not reveal much information about the shape or nature of the individual particles. This article presents an image analysis technique to study not only the granulometry, but also the physical characteristics (e.g. aspect ratio, roundness, form factor, etc.) of each and every particle. The custom-made software for the image analysis can also separately identify the butt and coke particles based on different shape parameters. This technique could help track changes in granulometry at different stages of the anode production and consequently improve the quality

Characterization of petroleum coke and butts used in anode manufacturing in aluminum industry

Prebaked anodes are produced from aggregates (calcined coke, recycled butts and anodes) and binder pitch. Good binding between aggregates and pitch results in dense anodes and has a direct impact on the electrical resistivity. The quality of coke and butts has a strong influence on anode properties. A comprehensive study of the physical and chemical interactions taking place during mixing allows a better understanding of the important factors and helps determine conditions that will lead to improved anode properties. The objective of this research is to characterize the surface properties of a calcined petroleum coke and butt particles and then relate them to their wettability by pitch. The wetting tests were carried out using the sessile drop method. Further investigations were carried out using SEM, FTIR, and XPS. In the article, the results of this study is presented and discussed

Utilization of artificial neural network to analyze and predict the influence of different parameters on anode properties

Carbon anode is an important component of the electrolytic production of primary aluminum. Anodes are made of dry aggregates (calcined petroleum coke, butts and recycled green and baked anodes) and the binder coal tar pitch. The production of anodes involves the mixing of the raw materials, the compaction of the paste, and the baking of green anodes to produce baked anodes with appropriate properties. An anode property is influenced by the quality of raw materials and the process conditions. It is usually difficult to correlate a given anode property with a particular constituent of a raw material or a particular processing condition because of the lack of a well-established mathematical relationship available for such a correlation. In these cases, the artificial neural network (ANN) can be a useful predictive tool to analyze the effect of a variable on a desired anode property. The analysis provides an insight into the effect of different parameters on anode properties and, in turn, helps improve the quality of anodes. In this article, the ANN approach will be discussed within the context of the analysis of the data on anode production. The results will be presented which show the application of the ANN methods to predict various anode properties