Makine Mühendisliği Bölümü Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1944
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Article A Distance-Dependent Random Graph Model and Its Analysis(Taylor & Francis Inc, 2026-04-14) Arslan, İlker; Işlak, ÜmitLet W-1,..., Wn be non-negative random variables. We consider an undirected random graph model on the node set {1,. ..,n}, where two nodes i < j are adjacent if W-i < W-j. In our setting, the Wi's are independent but not necessarily identically distributed, resulting in a model that generalizes the classical random permutation graphs. The model exhibits a certain dependence among the edges. Moreover, when nodes have physical interpretations- such as points on the real line R with node i located at position x = i-the model gains spatial structure and becomes, in particular, distance-dependent. We derive theoretical results on degree distributions, the number of isolated vertices, and the number of close neighbors. Simulation-based observations are also provided for the average clustering and the global efficiency.Article Citation - WoS: 1Citation - Scopus: 1A Few Layers Graphene Encapsulated Fe-Based Nanoparticles Synthesized from Ferrocene Containing Precursors: CVD Optimization and Evaluation for Possible Nanocatalyst Performance towards H2 Production(Pergamon-Elsevier Science Ltd, 2026-04-01) Demirbas, Derya; Kutluay, Sinan; Agaogullari, Duygu; Suzer-Cicek, Layda; Mertdinc-Ulkuseven, Siddika; Padberg, Gero; Felderhoff, Michael; Süzer-Çiçek, İlaydaThis study focuses on optimizing the synthesis of a few-layer graphene-encapsulated iron-based nanoparticles (Fe/Fe3C@C), prepared through spray drying, chemical vapor deposition (CVD), and leaching processes using ferrocene-based precursors, and their application as nanocatalysts for hydrogen (H2) production via sodium borohydride (NaBH4) methanolysis. Ferrocene-impregnated silica powders were prepared by spray drying them from a solution containing ferrocene, fumed silica, and ethanol. Then, these prepared powders, known as precursor powders, were subsequently introduced into the CVD system. Both the reduction of ferrocene and the encapsulation of Fe-based nanoparticles by graphene layers occurred in-situ during the CVD process. CVD temperature and the flow rates of CH4 and H2 gases are critical parameters that effects of the microstructural, thermal, and magnetic properties of synthesized nanoparticles. The CVD system was performed at temperatures ranging from 850 to 1000 degrees C, with variable gas flow rates of 50 or 100 mL/min. Additionally, acid leaching with hydrofluoric (HF) and hydrochloric (HCl) acids ensured the synthesis of pure powders free from silica and uncoated Fe, confirming the chemical stability of the nanoparticles. The presence of graphene in all synthesized samples within these parameter ranges were confirmed by Raman spectroscopy. Phase identifications were carried out using X-ray diffraction (XRD) and Mo & uml;ssbauer spectroscopy, revealing the Fe and trace amount Fe3C as core phases. Transmission electron microscopy (TEM) revealed the core-shell structure of the nanoparticles with a few layers of graphene coatings. Based on the coercivity and magnetic saturation values obtained from vibrating sample magnetometry (VSM), synthesized core-shell nanoparticles exhibited soft magnetic properties (Ms = 22.4-33.5 emu/g, Hc = 82.3-278.3 Oe). Fe/Fe3C@C nanoparticles obtained under optimum conditions achieved very high H2 production rate (HPR = 54200 mLH2 gcat h- 1) values, with low activation energy (Ea = 20.08 kJ mol- 1) value, highlighting their potential as an efficient and promising candidate catalyst for industrial-scale H2 production via the NaBH4 methanolysis reaction. In addition, it was found that the Fe/Fe3C@C nanoparticles retained 48% and 71% of their initial activity after 5 consecutive cycles, as measured by the HPR and TOF values, respectively.Article Increasing and Other Subsequence Problems for Random Interval Sequences(Elsevier, 2026-05-01) Arslan, Ilker; Islak, UmitVarious relations for comparison of intervals of real numbers are introduced, and the expected length of the corresponding longest increasing subsequence is analyzed. When intervals are randomly generated by taking the minimum and maximum of two independent uniform random variables, we prove that the expected length of the longest increasing subsequence grows on root the order of 3 n. We also investigate the asymptotic behavior of the expected length under alternative comparison relations and random interval models. Discussions on other subsequence problems for interval sequences are included.