Burak Dikici

Synthesis of in situ TiC nanoparticles in liquid aluminum: the effect of sintering temperature

In this study, in situ TiC nanoparticles with a diameter range of 70—400 nm have been successfully synthesized in liquid aluminum by conventional hot-pressing method. The effect of production temperature on the formation of the TiC phase during sintering was investigated by differential thermal analysis, X-ray diffraction, and scanning and transmission electron microscopies. The results show that the synthesizing temperature has a great effect on the formation of the TiC. Also, increase of producing temperature accelerates the formation of in situ TiC nanoparticles and decreases the portion of Al3Ti intermetallic phase in the liquid aluminum.

Age hardening response of an Al/TiC hot pressed multi-layered composite: Influence on corrosion

In this study, Al–Cu-based three-layered metal matrix composites reinforced with TiC particles were produced successfully by a conventional hot pressing method under argon (Ar) atmosphere. To evaluate the effect of heat treatment, the composites were treated for 24 h at 530°C and then aged in an oil bath at 180°C for various aging periods. The multi-layered composite was characterized by SEM, EDS, XRD, and the Vickers microhardness test. It was concluded that the peak hardness for the multi-layered composite was observed, when the aging period was extended up to approximately 12 h. The hardness of the middle layer increased from approximately 140 to 291 HV within 12 h. The corrosion resistance of the composites decreased with increasing aging time and some preferential corrosion attack was detected in the composite layers. In addition, it was found that the pitting susceptibility of unaged composites was also higher than that of all the aged specimens.

Corrosion of Metallic Biomaterials

Metallic materials have been used as biomedical implants for various parts of the human body for many decades. The physiological environment (body fluid) is considered to be extremely corrosive to metallic surfaces; and corrosion is one of the major problems to the widespread use of the metals in the human body since the corrosion products can cause infections, local pain, swelling, and loosening of the implants. Recently, the most common corrosion-resistant metallic biomaterials are made of stainless steels and titanium and its alloys along with cobalt–chromium–molybdenum alloys. It is well known that protective surface films of the alloys play a key role in corrosion of the metallic implants. Key documents on the corrosion behavior of the metallic biomaterials in human body have been compiled under this chapter as a review.

An investigation on the aging responses and corrosion behaviour of A356/SiC composites by neural network: The effect of cold working ratio:

In the present study, an artificial neural network model has been used for predicting the corrosion behaviour, aging and hardness responses of aluminium-based metal matrix composites reinforced with silicon carbide particle. Hyperbolic tangent sigmoid and linear activation functions are employed as the most appropriate activation function for hidden and output layers, respectively. The developed artificial neural network model is used to predict the corrosion current density, peak aging time and peak hardness of the composites. Feed forward back propagation neural network has been trained by Levenberg Marquardt algorithm. The regression correlation coefficients (R2) between the predicted and the experimental values of the corrosion current densities are found as 0.99986, 0.99629 and 0.99671 for the training, testing and validation datasets, respectively. Also, some case studies have been predicted by artificial neural network model. Test results indicate that the proposed network can be used efficiently for the prediction of the polarization response, peak aging time and peak hardness of the composites for different SiC volume fractions and deformation ratio without using any experimental data.

Prediction of corrosion susceptibilities of Al-based metal matrix composites reinforced with SiC particles using artificial neural network

In this theoretical study, the prediction of the corrosion resistance of Al–Si–Mg-based metal matrix composites reinforced with SiC particles has been studied, using an artificial neural network. Four input vectors were used in the construction of the proposed network; namely, volume fraction of SiC reinforcement, aging time of the composites, environmental conditions, and potential. Current was used as the one output in the proposed network. Test results indicate that the proposed network can be used efficiently for the prediction of the corrosion resistance of Al–Si–Mg-based metal matrix composites reinforced with SiC particles, and the methodology is suitable for engineers to study the corrosion of metal matrix composites. In addition, a few forecasts regarding the polarization response for different SiC volume fractions and aging conditions have also been generated without using any experimental data.

ZİRKONYA TAKVİYELİ HİDROKSİAPATİT (HA) BAZLI BİYOAKTİF HİBRİD KAPLAMALARIN KOROZYON DUYARLILIKLARI

Titanyum (Ti) ve alasimlari sahip olduklari dusuk elastik modul, yuksek dayanim, iyi biyouyumluluk ve korozyona karsi gelismis direncleri nedeniyle implant uygulamalarinda en sik kullanilan metalik biyomalzemelerdir. Bu calismada; ticari safliktaki titanyum (CP Ti) altliklar uzerine sol ‐ jel teknigi kullanilarak hidroksiapatit (HA: Ca 5 (PO 4 ) 3 (OH)) bazli zirkonya (ZrO 2 ) katkili biyoaktif hibrid kaplamalar ile kaplanmasi ve bu kaplamalarin in-vitro ortamlardaki elektrokimyasal korozyon duyarliliklari arastirilmistir. Kaplamalarin korozyon duyarliliklari potansiyodinamik polarizasyon (PDS) testleri ile belirlenmistir. Karakterizasyon calismalarinda XRD, SEM ve EDS cihazlari kullanilmistir. Elde edilen bulgular HA icerisine katilan ZrO 2 partikullerinin implantin yuk tasima kapasitelerini artirmakla birlikte kaplanmamis numunelere oranla yuzey pasivizasyon ozelliklerini iyilestirdigi gorulmustur.

A comparative study: The combined effect of the cold working and age hardening processes on pitting behaviour of Al/SiC metal matrix composites under saline environment

The combined effect of cold working and age hardening treatment (T8) on the corrosion behaviour of Al-Si-Mg based metal matrix composite reinforced with silicon carbide particles has been investigated in 3.5 wt% NaCl solution by potentiodynamic polarization technique. Composites containing 10 and 20 vol% silicon carbide particles were produced by compocasting technique and cold–worked at ratios of 4, 6, 10, 25 and 50% prior to ageing heat treatment conducted at 175℃. Corroded surfaces of the composites were observed by using scanning electron microscopy. A significant change in the corrosion behaviour of composites was observed when cold work ratio was increased from 4 to 50%. In addition, it has been found that the influence of cold working on corrosion behaviour is relatively higher compared to the effect of reinforcement content and age-hardening treatment.

Corrosion performance and microstructural response of A380 matrix alloy reinforced with sol–gel TiO2-coated SiC particles: a perspective on previous studies

Abstract In this study, the corrosion susceptibility of aluminium matrix composites reinforced with sol–gel TiO2-coated silicon carbide particles has been investigated. The corrosion of the composite, fabricated by means of a liquid metal infiltration technique, was established in chloride-containing alkaline environments using the potentiodynamic polarisation technique. Microstructural and interfacial characterisation of the composite was carried out by using an optical microscope, scanning electron microscope, energy dispersion spectroscopy and X-ray diffractometer. The corrosion performance and its effect on the composite microstructure are discussed in relation to previous observations.