Mühendislik Fakültesi
Faculty of Engineering
https://hdl.handle.net/20.500.12573/30
2024-03-28T10:18:46Z
2024-03-28T10:18:46Z
Recovery of Vanadium and Nickel from a High CaCO3 Containing Petroleum Coke Ash by Roasting and Acidic Leaching
Yurtseven, Ozgun
Ibrahim, Ahmedaljaali Ibrahim Idrees
Top, Soner
Kursunoglu, Sait
Altiner, Mahmut
https://hdl.handle.net/20.500.12573/2042
2024-03-28T09:21:31Z
2023-01-01T00:00:00Z
Recovery of Vanadium and Nickel from a High CaCO3 Containing Petroleum Coke Ash by Roasting and Acidic Leaching
Yurtseven, Ozgun; Ibrahim, Ahmedaljaali Ibrahim Idrees; Top, Soner; Kursunoglu, Sait; Altiner, Mahmut
In this study, it was aimed to extract vanadium (V) and nickel (Ni) from a petroleum coke ash (PCA) using a roasting process
without additives, followed by leaching with sulfuric acid (H2SO4). The experiments were designed based on the Taguchi
approach, taking into account the parameters of temperature, acid concentration, time, and solid ratio. Additional leaching
tests were conducted on the non-roasted PCA for comparison, to assess the efect of roasting on the extractions of V and Ni.
The results showed that no extra reducing agent was needed as the PCA contained high levels of CaCO3, which could be
used as a reducing agent during roasting. It was found that roasting was essential for high Ni extractions, but had no strong
efects on V extractions. The Ni extraction was found to be between 13.3 and 80.8% for the non-roasted PCA and between
43.6 and 99.3% for the roasted PCA. The V extraction was between 36 and 97.9% for the non-roasted PCA and between
45.4 and 99.9% for the roasted PCA. The optimal leaching conditions were determined to be a sulfuric acid of 4.5 M, a solid
ratio of 10%, a temperature of 75 °C, and a time of 75 min. In addition, it was determined that the leaching conditions had
a great efect on the oxidation state of vanadium ions, and an increase in the acid concentration led to the formation of V3+
ions (green color) instead of VO2+ ions (blue color) in the pregnant leach solution. The fnal pregnant leach solution containing 1056.50 mg/L V, and 251.85 mg/L Ni was achieved with an extraction yields of>98%. The experimental results were
greatly ftted by the shrinking core model and the activation energy (Ea) for V and Ni was calculated as 3.60 and 4.01 kJ/
mol, indicating that the leaching mechanism can be explained by the difusion control model.
2023-01-01T00:00:00Z
Magnetic Separation of Micro Beads and Cells on a Paper-Based Lateral Flow System
Farooqi, Muhammed Fuad
Icoz, Kutay
https://hdl.handle.net/20.500.12573/2040
2024-03-28T08:50:20Z
2023-01-01T00:00:00Z
Magnetic Separation of Micro Beads and Cells on a Paper-Based Lateral Flow System
Farooqi, Muhammed Fuad; Icoz, Kutay
Paper based lateral flow systems are widely used biosensor platforms to detect biomolecules in a
liquid sample. Proteins, bacteria, oligonucleotides, and nanoparticles were investigated in the
literature. In this work we designed a magnetic platform including dual magnets and tested the
flow of micron size immunomagnetic particles alone and when loaded with cells on two different
types of papers. The prewetting conditions of the paper and the applied external magnetic field
are the two dominant factors affecting the particle and cell transport in paper. The images recorded
with a cell phone, or with a bright field optical microscope were analyzed to measure the flow of
particles and cells. The effect of prewetting conditions and magnetic force were measured, and it
was shown that in the worst case, minimum 90% of the introduced cells reached to the edge of
the paper. The paper based magnetophoretic lateral flow systems can be used for cell assays.
2023-01-01T00:00:00Z
Estimation of cohesion for intact rock materials using regression and soft computing analyses
Köken, Ekin
Strzałkowski P.
Kazmierczak U.
https://hdl.handle.net/20.500.12573/2039
2024-03-28T08:39:34Z
2024-01-01T00:00:00Z
Estimation of cohesion for intact rock materials using regression and soft computing analyses
Köken, Ekin; Strzałkowski P.; Kazmierczak U.
Shear strength parameters such as cohesion (c) and internal friction angle (.) are among the most critical rock properties used in the geotechnical design of most engineering projects. However, the determination of these properties is laboring and requires special equipment. Therefore, this study introduces several predictive models based on regression and artificial intelligence methods to estimate the c of different rock types. For this purpose, a comprehensive literature survey is carried out to collect quantitative data on the shear strength properties of different rock types. Then, regression and soft computing analyses are performed to establish several predictive models based on the collected data. As a result of these analyses, five different predictive models (M1-M5) were established. Based on the performance of the established predictive models, the artificial neural network-based predictive model (model 5, M5) was the most suitable choice for evaluating the c for different rock types. In addition, mathematical expressions behind the M5 model are also presented in this study to allow users to implement it more efficiently. In this regard, the present study can be declared a case study showing the applicability of regression and soft computing analyses to evaluate the c of different rock types. However, the number of datasets used in this study should be increased to get more comprehensive predictive models in future studies. © 2024 Institute of Physics Publishing. All rights reserved.
2024-01-01T00:00:00Z
Data-driven discovery and DFT modeling of Fe4H on the atomistic level
Zagorac, Dejan
Zagorac, Jelena
Djukic, Milos B.
Bal, Burak
Schön, J. Christian
https://hdl.handle.net/20.500.12573/2038
2024-03-28T08:27:49Z
2024-01-01T00:00:00Z
Data-driven discovery and DFT modeling of Fe4H on the atomistic level
Zagorac, Dejan; Zagorac, Jelena; Djukic, Milos B.; Bal, Burak; Schön, J. Christian
Since their discovery, iron and hydrogen have been two of the most interesting elements in scientific research, with a variety of
known and postulated compounds and applications. Of special interest in materials engineering is the stability of such materials,
where hydrogen embrittlement has gained particular importance in recent years. Here, we present the results for the Fe-H system.
In the past, most of the work on iron hydrides has been focused on hydrogen-rich compounds since they have a variety of interesting
properties at extreme conditions (e.g. superconductivity). However, we present the first atomistic study of an iron-rich Fe4H
compound which has been predicted using a combination of data mining and quantum mechanical calculations. Novel structures
have been discovered in the Fe4H chemical system for possible experimental synthesis at the atomistic level.
2024-01-01T00:00:00Z