“Papers of School of Nano-Sciences”

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1. M. Abedini , R. Mohammadpour, H. Rafii-Tabar and P. Sasanpour,
Nanomatryoshka as a nano-material for use in laser-induced hyperthermia in biological tissues: A multiphysics-based computational modeling approach,
Int. J. Thermal Sciences 196(2024),   [abstract]

   2. N.S.. Riyahi, M. Goli and S. Shahbazian,
Quantifying errors of electron-proton/muon correlation functionals through the Kohn-Sham inversion of a two-component model system,
PHYSICAL REVIEW B (2023),   [abstract]

   3. S. Abbasi Aghda and A. Naji,
Drag force on cylindrical intruders in granular media: Experimental study of lateral vs axial intrusion and high grain-size polydispersity,
Powder Technology 415(2023), 118194  [abstract]

   4. Z. Fazli and A. Naji,
Rectification of polymer translocation through nanopores by nonchiral and chiral active particles,
Phys. Rev. E 107(2023), 024602   [abstract]

   5. M. Goli, D. Bressanini and S. Shahbazian,
On the Nature of the Two-Positron Bond: Evidence for a Novel Bond Type,
Physical Chem. Chemical Phys. 25(2023), 29531-29547  [abstract]

   6. s. M. K.. Manzoorolajdad, H. Hamzehpour and J. Sarabadani,
Electro-osmotic flow in different phosphorus nanochannels,
Phys. Fluids 35(2023), 042006  [abstract]

   7. H. Khalilian, J. Sarabadani and T. Ala-Nissila,
Polymer translocation in an environment of active rods,
PHYSICAL REVIEW RESEARCH 5(2023), 023107   [abstract]

   8. A. Rezaie-Dereshgi, H. Khalilian and J. Sarabadani,
Translocation of an active polymer into a two dimensional circular nano-container,
Journal of Physics: Condensed Matter 35(2023), 355101  [abstract]

   9. M. Jannesari, E. Asadian, F. Ejehi, N. English, R. Mohammadpour and P. Sasanpour,
Boosting on-demand antibacterial activity using electrical stimulations from polypyrrole-graphene oxide triboelectric nanogenerator,
Nano Energy (2023),   [abstract]

   10. K. Ghorbani, P. Mirchi, S. Arabha, A. Rajabpour and S. Volz ,
Lattice thermal conductivity and Young's modulus of XN4 (X = Be, Mg and Pt) 2D materials using machine learning interatomic potentials,
Phys. Chem. Chem Phys. (2023),   [abstract]

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