Integrated self-healing coating system for outstanding corrosion protection of AA2024

This work reports the preparation of an integrated self-healing system that combines the anodization of Al-substrates with the deposition of environmentally friendly coatings prepared by sol-gel for obtaining an active corrosion protection of aluminum alloys AA2024. The system consists on a first step of forming appropriate anodized layers by controlling the potential and anodizing time. The second step is the infiltration of a cerium sol-gel sol and deposition of a Ce-glass like film, followed by a final hybrid silica sol-gel coating, creating an adherent, stable and active corrosion protective system. SEM, electrochemical techniques (potentiodynamic and EIS tests) as well as an accelerated corrosion test are used to analyze the structure of the coatings and to study the corrosion behavior of the different coatings on AA2024. The results of potentiodynamic measurements showed the excellent corrosion properties and EIS measurements confirmed the self-healing behavior by blocking the pitting defects. The outstanding self-healing corrosion protecting behavior provided by this integrated self-healing coating system offers an efficient chromium-free system for substituting chromium CCC and CCA coatings

A review of additive manufacturing of ceramics by powder bed selective laser processing (sintering / melting): Calcium phosphate, silicon carbide, zirconia, alumina, and their composites

This review offers an overview on the latest advances in the powder bed selective laser processing, known as selective laser sintering/melting, of calcium phosphate, silicon carbide, zirconia, alumina, and some of their composites. A number of published studies between 1991 and August 2020 was collected, analyzed and an inclusive state of the art was created for this review. The paper focuses on the process description, feedstock criteria and process parameters and strategy. A comparison is made between direct and indirect powder bed selective laser processing of each ceramic, regarding the present achievements, limitations and solutions. In addition, technical aspects and challenges about how to address these issues are presented

Frittage/fusion laser sélective de lit de poudre de céramiques à base de zircone et leurs assemblages avec des métaux en tant que multi-matériaux

Depuis sa découverte au Japon dans les années 1980, la fabrication additive évolue et gagne en importance avec les contributions des établissements universitaires et industriels. La fabrication laser sur lit de poudre (appelée aussi fusion/frittage laser sélectif) est un procédé de fabrication additive bien maîtrisé pour la réalisation de pièces métalliques et polymères. Cette technologie devient rapidement un véritable processus de fabrication industrielle, permettant d’envisager de nouvelles applications telles que la production d'objets à base de multi-matériaux. Le déploiement de cette technologie avec les céramiques est assez difficile en raison de leur nature sujette à la fissuration lors des changements de températures rapides, de la faible absorption du faisceau incident produit par le laser Nd: YAG ( = 1.064 m) et de leur température de fusion élevée. Ainsi, l'objectif de ce doctorat a été de développer un assemblage céramique –métal par fabrication laser sur lit de poudre en une seule étape. Pour produire des pièces en zircone stabilisée à l'yttrine (8YSZ) et zircone renforcée à l'alumine (ATZ), l’interaction laser-matière est étudiée et améliorée par l'ajout d'un produit absorbant (0,75 % en poids de graphite). Ensuite, une campagne expérimentale a été menée pour optimiser les paramètres de procédé (puissance laser, vitesse de balayage laser, distance de lasage, taux de compactage et épaisseur de couche) permettant la fabrication reproductible d'objets denses. Pour les deux matériaux céramiques, des densités relatives d'environ 96% sont atteintes. Une précision dimensionnelle supérieure à 90 % est obtenue et des formes complexes sont fabriquées avec une résolution satisfaisante. Il s'avère que la microstructure est liée au modèle de fabrication utilisé, et son orientation peut être réglée avec des paramètres de fabrication changeants. Les pièces 8YSZ fabriquées avec le motif normal ont montré une structure en colonnes parallèle à la direction de la construction et leur largeur change avec la distance de hachure changeante. Lorsque le modèle de fabrication d'îlots hexagonaux est considéré, un modèle de fissuration avec une largeur de fissure variant de 9 à 49 m est observé. Lorsque des fabrications similaires sont appliquées sur ATZ, le motif de fissuration est orienté de manière aléatoire avec une largeur variant entre 5 et 13 m. La dureté Vickers des pièces 8YSZ et ATZ est mesurée à environ 1620 HV et 1770 HV respectivement, ce qui est supérieur aux études de la littérature réalisées avec des méthodes conventionnelles. Les caractérisations effectuées sur leur structure cristalline ont prouvé que le PBSLP peut provoquer des changements de phase dans la structure et leurs paramètres cellulaires ont montré une augmentation après traitement laser. Et aussi, des changements importants sont observés pour l'intensité de certaines phases après le processus laser. Lors de la fabrication de pièces solides ATZ, l'intensité de cristallite a-alumine diminue d'environ 9% après le processus de laser. L'étape suivante a consisté en la fabrication additive d'un assemblage céramique-métallique entre l'alliage d'aluminium (AlSi12) et des pièces en céramique 8YSZ/ATZ sans renoncer à l'approche directe PBSLP. Après leur fabrication, la section transversale métallo-céramique est exposée et la zone de transition est étudiée en profondeur par des méthodes de caractérisation élémentaire et de diffraction. Cette zone est identifiée comme « interphase » a une épaisseur comprise entre 25-210 m en multi-matériau AlSi12-8YSZ et 20-90 m en multi-matériau AlSi12-ATZ. On constate que la zone est constituée d'éléments provenant de part et d'autre de la structure multi-matériaux. Après une étude approfondie, il a été découvert que de nouvelles phases intermétalliques cristallines (ZrSi) et ternaires [Zr2(Al5Si)] et des phases amorphes sont créées au cours de la PBSLP. Il a été conclu qu'une réaction chimique se produit entre les côtés céramiques.Since its discovery in Japan in the 1980s, additive manufacturing is evolving and gaining importance with contributions of both academic and industrial establishments. The powder bed selective laser processing (PBSLP), also known as selective laser melting/sintering, is an additive manufacturing process well mastered for the production of metal and polymer parts. It is quickly turning into a real industrial manufacturing process, raising some new innovative applications such as the production of ceramic-metallic multi-materials objects. However, the implementation of this process with ceramics is quite challenging due to their prone to cracking under rapid heat changes, their low absorption of an incident beam produced by an Nd: YAG laser ( = 1.064 m), and their high melting temperature. Thus, this Ph.D. study aims to optimize powder bed selective laser processing parameters for the fabrication of dense zirconia-based solids, and afterward, to obtain a ceramic-metallic multi-material joining in a single step by using the same additive manufacturing method. To fabricate 8 mol% yttria-stabilized zirconia (8YSZ) and alumina toughened zirconia (ATZ) ceramic parts, their laser-matter interaction is studied and increased approximately from 2% to 60% by the addition of an absorbency enhancer (0.75 wt.% of graphite). Then, experiments were conducted to determine adequate process parameters (laser power, laser scan speed, hatch distance, compaction rate, and layer thickness) allowing the reproducible manufacture of dense objects. For both ceramic materials, relative densities of around 96% are obtained. Dimensional accuracy of over 90% is achieved, and complex shapes are fabricated with a satisfying resolution with a sub-limit of around 0.1mm. It is found that the microstructure is related to the fabrication pattern used, and its orientation can be tuned with changing fabrication parameters. The 8YSZ pieces fabricated with the normal pattern showed a columnar structure that is parallel to the building direction and their width changes with changing hatch distance. When the hexagonal island fabrication pattern is considered, a cracking pattern with crack width changing from 9 to 49 m is observed. When similar fabrications are applied on ATZ, the cracking pattern is randomly oriented with changing width between 5 to 13 m. Vickers hardness of 8YSZ and ATZ pieces are measured approximately as 1620 HV and 1770 HV respectively, which are higher than literature studies carried out with conventional methods. Characterizations carried on their crystalline structure proved that PBSLP can cause phase changes in the structure and their cell parameters showed an increase after laser processing. And also, significant changes are observed for the intensity of some phases after the lasing process. During the fabrication of ATZ solid pieces, the intensity of crystallite a-alumina decreases around 9% after the lasing process. The next stage consisted of the additive manufacturing of a ceramic-metallic assembly between aluminum alloy (AlSi12) and 8YSZ/ATZ ceramic parts without giving up on the direct PBSLP approach. After their fabrication, the metallic-ceramic cross-section is exposed and the transition zone is deeply studied by elemental and diffraction characterization methods. This zone is identified as “interphase” has thickness between 25-210 m in AlSi12-8YSZ multi-material and 20- 90 m in AlSi12-ATZ multi-material. It is found that the zone consists of elements coming from either side of the multi-material structure. When studied deeply, it was discovered that new crystalline intermetallic (ZrSi) and ternary [Zr2(Al5Si)] phases and amorphous phases are created during PBSLP. It was concluded that a chemical reaction occurs between the ceramic and metallic sides during PBSLP and that conducted the formation of interphase that creates a satisfactory joining adhesion between the ceramic and metallic part

Photomontage detection with deep learning methods

Günümüzde her geçen gün kullanımı artan sosyal medya ve internet sayesinde neredeyse çekilen her fotoğraf internet ortamına yüklenmektedir. Bu sebeple görüntü elde etmek çok daha kolay hale gelmiştir. Görüntülerin kolaylıkla elde edilmesi, gelişen teknolojiler sayesinde görüntü üzerinde değişiklik yapılmasını teşvik edici hale gelmiştir. Görüntüler üzerinde kişinin kendi isteği ile yapmış olduğu değişikliklerin yanı sıra kötü niyetli kişiler tarafından yapılan değişiklikler ise bir takım sorunlara yol açmakta olup istenmeyen durumlar yaratabilmektedir. Yapılan değişiklikler ile kişisel verilerin ihlalinden herhangi bir resmi belge üzerinde sahteciliğe kadar geniş bir alanı etkilemektedir. Sahtecilik yöntemleri farklı şekilde yapılmaktadır. Kopyala-taşı yöntemi, mevcut görüntüdeki bir alanın aynı görüntü üzerinde farklı bir alana kopyalanması ile yapılmaktadır. Görüntü birleştirme, farklı iki görüntünün istenilen alanları birleştirilmesi ile oluşturulmaktadır. Görüntü rötuşlama, görüntü üzerinde istenmeyen bölgelerin etkisi azaltarak ya da istenilen alan üzerinde iyileştirme yapılarak görüntü daha ilgi çekici hale getirilmektedir. Çalışmada bu düşünceden yola çıkılarak görüntüler üzerinde değişiklik olup olmadığının tespit edilmesi eğer değişiklik var ise o alanın işaretlenmesi için derin öğrenme yöntemi kullanılmıştır. Derin öğrenme yöntemleri sayesinde yüksek boyutlu verilerde daha hızlı ve daha yüksek başarı elde edilmiştir. Çalışmada CASIA ve CoMoFoD veri setleri üzerinde uygulama gerçekleştirilmiştir. Veri setleri üzerinde yapılan testler sonucunda ortalama %76,86 oranından doğruluk elde edilmiştir.Today, thanks to the increasing use of social media and the internet almost every photo taken is uploaded to the internet. For this reason, it has become much easier to obtain images. Easily obtaining images has become an encourage to make changes on the image thanks to the developing technologies. In addition to the changes made on the images by the person's own will, the changes made by malicious people cause some problems and can create unwanted situations. With the changes made, it affects a wide area from the violation of personal data to the forgery of any official document. Forgery methods are carried out in different ways. Copy-move method is done by copying an area in the current image to a different area on the same image. Image fusion is created by combining the desired areas of two different images. Image retouching makes the image more interesting by reducing the effect of unwanted areas on the image or by improving the desired area. Based on this idea, in the study, deep learning method was used to determine whether there is a change on the images, and if there is, to mark the area. Thanks to deep learning methods, faster and higher success has been achieved in high-dimensional data. In the study, an application was carried out on the CASIA and CoMoFoD data sets. As a result of the tests performed on the data sets, an average accuracy of 76.86% was obtained

Photomontage Detection with Deep Neural Networks

Son yıllarda hızla gelişen teknoloji ile birlikte verilerin sağlıklı bir şekildeelde edilmesi, elde edilen verilerin korunması ve elde edilen verilerin özgünolması büyük önem taşımaktadır. Özgünlüğün tespiti özellikle görüntülerüzerinde büyük önem teşkil etmektedir. Görüntülerde bozulma ya dadeğişiklik olup olmadığını tespit etmek ise tıptan, belgede sahteciliğe kadargeniş bir çalışma alanını etkilemektedir. Fotomontaj tespiti için derinöğrenme algoritmaları ile mevcut görüntü işleme metotlarının aynı andakullanılması verimliliği arttırmaktadır. Yapılan çalışmalar, derin sinir ağları,yüksek boyutlu girdilerden karmaşık istatistiksel özellikleri eldeedebildikleri ve hiyerarşik temsillerini etkili bir biçimde öğrenebildiklerinigöstermişlerdir. Bu çalışmada görüntü üzerinde değişiklik yapılmış kısım ileyapılmamış kısım arasındaki farkı daha rahat ayırabilmek için geliştirilmişmaske bölgesel evrişimsel sinir ağı (Mask R-CNN) ile bu sinir ağına bağlanansobel filtresi kullanılmaktadır. Sobel filtresi, sinir ağı ile tahmin edilenmaskelerin zemin üzerindeki maskeye benzer görüntü gradyanlarına sahipolmasını teşvik etmek için yardımcı bir görev görür. Ağ ile kopyala taşıma vebirleştirme işlemleri algılanabilmektedir. Sinir ağı uygulanırken COCO veriseti kullanılmıştır. Yapılan çalışma ile daha yüksek başarı oranları eldeedilmiştir.With the rapidly developing technology in recent years, obtaining the data properly, protection of the obtained data and it is very important that the obtained data are original. Identification of originality is of great importance, especially on images. Detecting whether there is distortion or change in images affects a wide range of work field from medicine to document forgery. The simultaneous use of deep learning algorithms and existing image processing methods for photomontage detection increases efficiency. Studies have shown that deep neural networks can obtain complex statistical properties from high dimensional inputs and can learn their hierarchical representation effectively. In this study, in order to discriminate the difference between the part that has been changed and the part that has not been changed, we used the improved mask regional convolutional neural network (Mask R-CNN) and the sobel filter connected to this neural network. The Sobel filter acts as an assistant to promote masks to have similar mask image gradients on the ground estimated by the neural network. Copy-move and splicing operations can be detected with the network. The COCO data set was used when applying the neural network. Higher success rates were obtained with the study

DERİN SİNİR AĞLARI YARDIMIYLA FOTOMONTAJ TESPİTİ

Son yıllarda hızla gelişen teknoloji ile birlikte verilerin sağlıklı bir şekildeelde edilmesi, elde edilen verilerin korunması ve elde edilen verilerin özgünolması büyük önem taşımaktadır. Özgünlüğün tespiti özellikle görüntülerüzerinde büyük önem teşkil etmektedir. Görüntülerde bozulma ya dadeğişiklik olup olmadığını tespit etmek ise tıptan, belgede sahteciliğe kadargeniş bir çalışma alanını etkilemektedir. Fotomontaj tespiti için derinöğrenme algoritmaları ile mevcut görüntü işleme metotlarının aynı andakullanılması verimliliği arttırmaktadır. Yapılan çalışmalar, derin sinir ağları,yüksek boyutlu girdilerden karmaşık istatistiksel özellikleri eldeedebildikleri ve hiyerarşik temsillerini etkili bir biçimde öğrenebildiklerinigöstermişlerdir. Bu çalışmada görüntü üzerinde değişiklik yapılmış kısım ileyapılmamış kısım arasındaki farkı daha rahat ayırabilmek için geliştirilmişmaske bölgesel evrişimsel sinir ağı (Mask R-CNN) ile bu sinir ağına bağlanansobel filtresi kullanılmaktadır. Sobel filtresi, sinir ağı ile tahmin edilenmaskelerin zemin üzerindeki maskeye benzer görüntü gradyanlarına sahipolmasını teşvik etmek için yardımcı bir görev görür. Ağ ile kopyala taşıma vebirleştirme işlemleri algılanabilmektedir. Sinir ağı uygulanırken COCO veriseti kullanılmıştır. Yapılan çalışma ile daha yüksek başarı oranları eldeedilmiştir.With the rapidly developing technology in recent years, obtaining the data properly, protection of the obtained data and it is very important that the obtained data are original. Identification of originality is of great importance, especially on images. Detecting whether there is distortion or change in images affects a wide range of work field from medicine to document forgery. The simultaneous use of deep learning algorithms and existing image processing methods for photomontage detection increases efficiency. Studies have shown that deep neural networks can obtain complex statistical properties from high dimensional inputs and can learn their hierarchical representation effectively. In this study, in order to discriminate the difference between the part that has been changed and the part that has not been changed, we used the improved mask regional convolutional neural network (Mask R-CNN) and the sobel filter connected to this neural network. The Sobel filter acts as an assistant to promote masks to have similar mask image gradients on the ground estimated by the neural network. Copy-move and splicing operations can be detected with the network. The COCO data set was used when applying the neural network. Higher success rates were obtained with the study

Integrated self-healing coating system for outstanding corrosion protection of AA2024

[EN] This work reports the preparation of an integrated self-healing system that combines the anodization of Al-substrates with the deposition of environmentally friendly coatings prepared by sol-gel for obtaining an active corrosion protection of aluminum alloys AA2024. The system consists on a first step of forming appropriate anodized layers by controlling the potential and anodizing time. The second step is the infiltration of a cerium sol-gel sol and deposition of a Ce-glass like film, followed by a final hybrid silica sol-gel coating, creating an adherent, stable and active corrosion protective system. SEM, electrochemical techniques (potentiodynamic and EIS tests) as well as an accelerated corrosion test are used to analyze the structure of the coatings and to study the corrosion behavior of the different coatings on AA2024. The results of potentiodynamic measurements showed the excellent corrosion properties and EIS measurements confirmed the self-healing behavior by blocking the pitting defects. The outstanding self-healing corrosion protecting behavior provided by this integrated self-healing coating system offers an efficient chromium-free system for substituting chromium CCC and CCA coatings.This work was supported by Spanish MINECO under project MAT2017-87035-C2-1-PP. This paper is also part of dissemination activities of project FunGlass. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 739566Peer reviewe