Browsing by Author "Batyrov, Merdan"

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Combining tensile test results with atomistic predictions of elastic modulus of graphene/polyamide-6,6 nanocomposites
(Elsevier, 2023-06) Batyrov, Merdan; Dericiler, K.; Palabıyık, Büşra Akkoca; Okan, B. S.; Öztürk, Hande; Fındıkçı, İlknur Eruçar; Mechanical Engineering; KAYMAKSÜT, Hande Öztürk; FINDIKÇI, Ilknur Eruçar; Batyrov, Merdan; Palabıyık, Büşra Akkoca
In this work, we combined tensile test results with atomistic simulations to investigate the effect of filler parameters including distribution, stacking, loading and lateral graphene size on elastic moduli of graphene/PA-6,6 nanocomposites. Stacked and randomly distributed atomistic models were adapted in Molecular Dynamics (MD) simulations to establish the limits of stiffness enhancement in graphene reinforced PA-6,6 nanocomposites with loading ratios changing from 0 to 1 wt%. Experimental results showed that incorporating of 0.3–0.4 wt% graphene loading improved the elastic modulus of the neat polymer by 41.7%−43.5%. While the test sample behaved close to the computational results of the stacked atomistic model at low graphene loadings up to 0.4 wt%, it overshot the predictions of the randomly distributed model at all considered loadings up to 1 wt%. Elastic moduli of graphene-based PA-6,6 nanocomposites increased linearly with graphene loading in the stacked model, however, no such relation was detected in the randomly distributed model. The lower stiffness enhancement provided by the randomly distributed model compared to the stacked model was revealed as the small lateral size of graphene plates in PA-6,6 matrix. As the graphene size increased, the elastic modulus of the graphene dramatically increased, directly improving the elastic modulus of the nanocomposite. The developed computational approach is highly useful to estimate the boundaries of stiffness enhancement provided by graphene dispersions in macroscale nanocomposite samples.
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Computational investigations of Bio-MOF membranes for uremic toxin separation
(Elsevier, 2022-01-15) Palabıyık, Büşra Akkoca; Batyrov, Merdan; Fındıkçı, İlknur Eruçar; Mechanical Engineering; FINDIKÇI, Ilknur Eruçar; Palabıyık, Büşra Akkoca; Batyrov, Merdan
Developing new and efficient methods as an alternative to hemodialysis is important due to the challenges associated with poor efficiency of membranes and long dialysis sessions. Recently, metal organic frameworks (MOFs) have attracted interest in the membrane community due to their tunable physical and chemical properties. However, their potential in uremic toxin separations is still unknown and it is not practical to test each synthesized MOF for uremic toxin separations. The main objective of this study is to computationally assess membrane-based uremic toxin separation performances of 60 bio-compatible MOFs (bio-MOFs). Combining grand canonical Monte Carlo (GCMC) and equilibrium molecular dynamics (EMD) simulations, we predicted urea, creatinine, and water permeabilities of bio-MOFs and their membrane selectivities for urea/water and creatinine/water separations. Results showed that OREZES, a carboxylate-based MOF exhibited the highest membrane selectivity (347.94) for urea/water separation whereas BEPPIX, an amino-based MOF gave the highest creatinine/water selectivity (1.5 × 105) at infinite dilution and 310 K. Guest-guest and host–guest interaction energies for uremic toxins were also computed during EMD simulations and van der Waals interactions were found to be much stronger than the coulombic interactions. We finally examined the effect of MOF's flexibility on the predicted membrane performance and membrane selectivities of bio-MOFs for urea/water separation significantly enhanced when the structural flexibility was considered in simulations. Our results will be a guide for further studies to design novel bio-MOF membranes for uremic toxin separations.