Farrokh Yousefi

Bio: Farrokh Yousefi is an academic researcher from University of Zanjan. The author has contributed to research in topics: Thermal conductivity & Graphene. The author has an hindex of 7, co-authored 18 publications receiving 134 citations.

Investigation of tetracosane thermal transport in presence of graphene and carbon nanotube fillers––A molecular dynamics study

Abstract: This paper examines the thermal properties of pure tetracosane paraffin, tetracosane-graphene, and tetracosane-carbon nanotube mixed phase change materials (PCM). The most important properties studied were thermal capacity in constant volume (Cv), mean square displacement of atoms (MSD), radial distribution function (RDF), density, phonon density of states (PDOS) and thermal conductivity (k) under different temperatures. The results show that graphene and carbon nanotube increase the thermal conductivity of the tetracosane at different temperatures, but decrease the molecular movement and its thermal capacity (except after about 360 K), and it can be said that this slightly decreases the paraffin melting temperature. It was demonstrated that carbon nanotube is more efficient than graphene to increase the thermal conductivity of the proposed PCM.

Non-equilibrium molecular dynamics study on radial thermal conductivity and thermal rectification of graphene

Abstract: In the present study, the radial thermal rectification and thermal conductivity of the graphene were investigated by non-equilibrium molecular dynamics simulation and then corrected by quantum corr...

Boron Nitride Nanotube as an Antimicrobial Peptide Carrier: A Theoretical Insight.

Abstract: Introduction Nanotube-based drug delivery systems have received considerable attention because of their large internal volume to encapsulate the drug and the ability to penetrate tissues, cells, and bacteria. In this regard, understanding the interaction between the drug and the nanotube to evaluate the encapsulation behavior of the drug in the nanotube is of crucial importance. Methods In this work, the encapsulation process of the cationic antimicrobial peptide named cRW3 in the biocompatible boron nitride nanotube (BNNT) was investigated under the Canonical ensemble (NVT) by molecular dynamics (MD) simulation. Results The peptide was absorbed into the BNNT by van der Waals (vdW) interaction between cRW3 and the BNNT, in which the vdW interaction decreased during the simulation process and reached the value of −142.7 kcal·mol−1 at 4 ns. Discussion The increase in the potential mean force profile of the encapsulated peptide during the pulling process of cRW3 out of the nanotube showed that its insertion into the BNNT occurred spontaneously and that the inserted peptide had the desired stability. The energy barrier at the entrance of the BNNT caused a pause of 0.45 ns when half of the peptide was inside the BNNT during the encapsulation process. Therefore, during this period, the peptide experienced the weakest movement and the smallest conformational changes.

Theoretical Encapsulation of Fluorouracil (5-FU) Anti-Cancer Chemotherapy Drug into Carbon Nanotubes (CNT) and Boron Nitride Nanotubes (BNNT)

Abstract: Introduction: Chemotherapy with anti-cancer drugs is considered the most common approach for killing cancer cells in the human body. However, some barriers such as toxicity and side effects would limit its usage. In this regard, nano-based drug delivery systems have emerged as cost-effective and efficient for sustained and targeted drug delivery. Nanotubes such as carbon nanotubes (CNT) and boron nitride nanotubes (BNNT) are promising nanocarriers that provide the cargo with a large inner volume for encapsulation. However, understanding the insertion process of the anti-cancer drugs into the nanotubes and demonstrating drug-nanotube interactions starts with theoretical analysis. Methods: First, interactions parameters of the atoms of 5-FU were quantified from the DREIDING force field. Second, the storage capacity of BNNT (8,8) was simulated to count the number of drugs 5-FU encapsulated inside the cavity of the nanotubes. In terms of the encapsulation process of the one drug 5-FU into nanotubes, it was clarified that the drug 5-FU was more rapidly adsorbed into the cavity of the BNNT compared with the CNT due to the higher van der Waals (vdW) interaction energy between the drug and the BNNT. Results: The obtained values of free energy confirmed that the encapsulation process of the drug inside the CNT and BNNT occurred spontaneously with the free energies of −14 and −25 kcal·mol−1, respectively. Discussion: However, the lower value of the free energy in the system containing the BNNT unraveled more stability of the encapsulated drug inside the cavity of the BNNT comparing the system having CNT. The encapsulation of Fluorouracil (5-FU) anti-cancer chemotherapy drug (commercial name: Adrucil®) into CNT (8,8) and BNNT (8,8) with the length of 20 A in an aqueous solution was discussed herein applying molecular dynamics (MD) simulation.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.