Browsing by Author "Hashemian, M."

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    Free vibration analysis of a functionally graded porous nanoplate in a hygrothermal environment resting on an elastic foundation
    (Elsevier B.V., 2024) Salahshour, Soheıl; Mokhtarian, A.; Hashemian, M.; Pirmoradian, M.; Salahshour, S.
    This research investigates the free vibrational behavior of a functionally graded porous (FGP) nanoplate resting on an elastic Pasternak foundation in a hygrothermal environment. The nanoplate is modeled based on the nonlocal strain gradient theory (NSGT) and considering several plate theories including the CPT (classical plate theory), the FSDT (first-order shear deformation theory), and the TSDT (third-order shear deformation theory). Several patterns are investigated for the dispersion of pores, and the surface effects are incorporated to enhance the precision of the model. The governing equations and boundary conditions are derived via Hamilton's principle and an exact solution is provided via the Navier method. The impacts of several parameters on the natural frequencies are inspected such as length scale and nonlocal parameters, surface effects, porosity parameter, hygrothermal environment, and coefficients of the foundation. The results show that the impact of the porosity parameter on the natural frequencies of nanoplates is significantly dependent on the porosity distribution pattern. It is discovered that by increasing the porosity parameter from 0 to 0.6, the relative changes of natural frequencies vary from a decrease of 30 % to an increase of 6 %. © 2024 The Author(s)
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    Investigating the Effect of Functionalized Carbon Nanotube With Cooh Group on the Drug Delivery Process of Doxorubicin in Capillary Networks Around Cancer Tumors Using Molecular Dynamics Simulation
    (Elsevier B.V., 2025) Salahshour, Soheıl; Gataa, I.S.; Alaridhee, Z.A.I.; Salahshour, S.; Sharma, P.; Kubaev, A.; Hashemian, M.
    This study investigated the interaction between functionalized carbon nanotubes and doxorubicin, a commonly used chemotherapy drug, aiming to enhance cancer therapy. Functionalizing CNTs with carboxyl (-COOH) groups aimed to improve the precision of drug delivery system, enabling more effective targeting of cancerous tumors while minimizing side effects on healthy tissues. Molecular dynamics simulations indicated that after 10 ns, the system stabilized at a potential energy of 5.676 kcal/mol and a total energy of 6.62 kcal/mol, suggesting thermodynamic equilibrium. Increasing the atomic ratio of COOH groups from 2.5 % to 10 % significantly raised the maximum structural density from 0.0035 atm/ų to 0.0042 atm/ų, thereby enhancing drug-loading capacity through stronger intermolecular interactions. Thermal stability improved as the maximum temperature decreased from 360.64 K to 346.08 K, indicating better heat dissipation and enhanced doxorubicin stability. Moreover, shear stress increased from 3.52 Pa to 3.79 Pa, indicating enhanced mechanical resistance. The mean squared displacement (MSD) decreased from 3.42 Ų to 3.24 Ų, and the root mean square deviation (RMSD) decreased from 1.85 Å to 1.80 Å These reductions indicated decreased molecular mobility and increased structural stability. These findings demonstrate that functionalized CNTs enhanced drug encapsulation, stability, and controlled release, maximizing the therapeutic effects of doxorubicin while minimizing side effects. This study highlighted the potential of nanotechnology to revolutionize drug delivery systems and improve cancer treatment outcomes. © 2024 Elsevier B.V.
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    Multi-Objective Optimization of Buckling Load and Natural Frequency in Functionally Graded Porous Nanobeams Using Non-Dominated Sorting Genetic Algorithm-Ii
    (Elsevier Ltd, 2025) Salahshour, Soheıl; Basem, A.; Jasim, D.J.; Hashemian, M.; Ali Eftekhari, S.; Al-fanhrawi, H.J.; Salahshour, S.
    This study investigates the fundamental natural frequency and critical buckling load of Functionally Graded Porous nanobeams supported by an elastic medium, addressing the need for optimized designs in advanced nanostructures. Utilizing a Genetic Algorithm and Non-Dominated Sorting Genetic Algorithm-II, the research aims to identify the Pareto front for these two objectives while incorporating surface effects. The nanobeam is modeled using Nonlocal Strain Gradient Theory and Gurtin-Murdoch surface elasticity theory, with governing equations solved via the Generalized Differential Quadrature Method based on Reddy's Third-order Shear Deformation Theory. Key input parameters, including temperature gradient, residual surface stress, porosity, and elastic foundation properties, are varied to train two Artificial Neural Networks for output prediction. Results indicate that for the fundamental frequency, significant factors include the material length scale and the Pasternak shear foundation parameter, while the critical buckling load is mainly influenced by the temperature gradient and the same material parameters. These findings provide critical insights for designers, allowing them to make informed decisions based on optimal values for eight input parameters. © 2024 Elsevier Ltd