Using of artificial neural networks and different evolutionary algorithms to predict the viscosity and thermal conductivity of silica-alumina-MWCN/water nanofluid.

This study predicts the parameters such as viscosity and thermal conductivity in silica-alumina-MWCN/water nanofluid using the artificial intelligence method and using design variables such as solid volume fraction and temperature. In this study, 6 optimization algorithms were used to predict and numerically model the µnf and TC of silica-alumina-MWCNT/water-NF. In this study, six measurement criteria were used to evaluate the estimates obtained from the coupling process of GMDH ANN with each of these 6 optimization algorithms. The results reveal that the influence of the φ is notably higher on both µnf and TC with values of 0.83 for µnf and 0.92 for TC, while Temp has a relatively weaker impact with -0.5 for µnf and 0.38 for TC. Among various algorithms, the coupling of the evolutionary algorithm NSGA II with ANN and GMDH performs best in predicting µnf and TC for the NF, with a maximum margin of deviation of -0.108 and an R2 evaluation criterion of 0.99996 for µnf and 1 for TC, indicating exceptional model accuracy. In the subsequent phase, a meta-heuristic Genetic Algorithm minimizes µnf and TC values. Four points (A, B, C, and D) along the Pareto front are selected, with point A representing the optimal state characterized by low values of φ and Temp (0.0002 and 50.8772, respectively) and corresponding target function values of 0.9988 for µnf and 0.6344 for TC. In contrast, point D represents the highest values of φ and Temp (0.49986 and 59.9775, respectively) and yields target function values of 2.382 for µnf and 0.8517 for TC. This analysis aids in identifying the optimal operating conditions for maximizing NF performance.

The effect of the initial temperature, pressure, and shape of carbon nanopores on the separation process of SiO2 molecules from water vapor by molecular dynamics simulation.

Today, with the advancement of science in nanotechnology, it is possible to remove dust nanostructures from the air breathed by humans or other fluids. In the present study, the separation of SiO2 molecules from H2O vapor is studied using molecular dynamics (MD) simulation. This research studied the effect of initial temperature, nanopore geometry, and initial pressure on the separation of SiO2 molecules. The obtained results show that by increasing the temperature to 500 K, the maximum velocity (Max-Vel) of the samples reached 2.47 Å/fs. Regarding the increasing velocity of particles, more particles pass via the nanopores. Moreover, the shape of the nanopore could affect the number of passing particles. The results show that in the samples with a cylindrical nanopore, 20 and 40% of SiO2 molecules, and with the sphere cavity, about 32 and 38% of SiO2 particles passed in the simulated structure. So, it can be concluded that the performance of carbon nanosheets with a cylindrical pore and 450 K was more optimal. Also, the results show that an increase in initial pressure leads to a decrease in the passage of SiO2 particles. The results reveal that about 14 and 54% of Silica particles passed via the carbon membrane with increasing pressure. Therefore, for use in industry, in terms of separating dust particles, in addition to applying an EF, temperature, nanopore geometry, and initial pressure should be controlled.

Science and Technology of Additive Manufacturing Progress: Processes, Materials, and Applications.

As a special review article, several significant and applied results in 3D printing and additive manufacturing (AM) science and technology are reviewed and studied. Which, the reviewed research works were published in 2020. Then, we would have another review article for 2021 and 2022. The main purpose is to collect new and applied research results as a useful package for researchers. Nowadays, AM is an extremely discussed topic and subject in scientific and industrial societies, as well as a new vision of the unknown modern world. Also, the future of AM materials is toward fundamental changes. Which, AM would be an ongoing new industrial revolution in the digital world. With parallel methods and similar technologies, considerable developments have been made in 4D in recent years. AM as a tool is related to the 4th industrial revolution. So, AM and 3D printing are moving towards the fifth industrial revolution. In addition, a study on AM is vital for generating the next developments, which are beneficial for human beings and life. Thus, this article presents the brief, updated, and applied methods and results published in 2020.

Investigation of the effects of porosity and volume fraction on the atomic behavior of cancer cells and microvascular cells of 3DN5 and 5OTF macromolecular structures during hematogenous metastasis using the molecular dynamics method.

BACKGROUND AND OBJECTIVE: The molecular dynamics (MD) simulation is a powerful tool for researching how cancer patients are treated. The efficiency of many factors may be predicted using this approach in great detail and with atomic accuracy. METHODS: The MD simulation method was used to investigate the impact of porosity and the number of cancer cells on the atomic behavior of cancer cells during the hematogenous spread. In order to examine the stability of simulated structures, temperature and potential energy (PE) values are used. To evaluate how cell structure has changed, physical parameters such as gyration radius, interaction force, and interaction energy are also used. RESULTS: The findings demonstrate that the samples' gyration radius, interaction energy, and interaction force rose from 41.33 Å, -551.38 kcal/mol, and -207.10 kcal/mol Å to 49.49, -535.94 kcal/mol, and -190.05 kcal/mol Å, respectively, when the porosity grew from 0% to 5%. Also, the interaction energy and force in the samples fell from -551.38 kcal/mol and -207.10 kcal/mol to -588.03 kcal/mol and -237.81 kcal/mol Å, and the amount of gyration radius reduced from 41.33 to 37.14 Å as the number of cancer cells rose from 1 to 5 molecules. The strength and stability of the simulated samples will improve when the radius of gyration is decreased. CONCLUSIONS: Therefore, high accumulation of cancer cells will make them resistant to atomic collapse. It is expected that the results of this simulation should be used to optimize cancer treatment processes further.

The effect of initial temperature on the mechanical interaction of 3DN5/5OTF protein-based structures using molecular dynamics simulation.

Nowadays, advances in science and technology in biological macromolecules have led to the early detection and treatment of cancer-based cells. In this study, molecular dynamics (MD) simulation examines atomic interactions between 3DN5 and 5OTF structures. Technically, the effect of the initial temperature on the atomic behavior (AB) of the simulated samples is investigated. The stability of simulated structures is examined with changes in temperature and kinetic energy (KE) quantities. The biomechanical interaction is examined by the radius of gyration (RoG), interaction energy (IE), and interaction force (IF). The results show that the RoG changes from a numerical value of 40.25 to 41.33 Å, and the IE and IF converge to -552.38 kcal/mol and - 207.10 kcal/mol.Å after 10 ns, respectively. Due to the temperature effect on the AB of the structures, the RoG increases by increasing the initial temperature from 41.33 to 58.91 Å. By increasing the initial temperature to 350 K, the IE increases from -551.38 to -500.11 kcal/mol, and the IF increases from -207.10 to -183.39 kcal/mol.Å. Finally, the results of these studies are expected to lead to early detection and treatment of cancer cells.

Fabrication of HKUST-1/ZnO/SA nanocomposite for Doxycycline and Naproxen adsorption from contaminated water.

Doxycycline and Naproxen are among the most widely used drugs in the therapy of CoVID 19 disease found in surface water. Water scarcity in recent years has led to research to treat polluted water. One of the easy and low-cost methods for treatment is adsorption. The utilize of Metal-Organic Frameworks (MOFs) to evacuate pharmaceutical contaminants from water sources has been considered by researchers in the last decade. In this research, HKUST-1/ZnO/SA composite with high adsorption capacity, chemical and water stability, recovery, and reuse properties has been synthesized and investigated. By adding 10 wt% of ZnO and 50 wt% of sodium alginate to HKUST-1, at 25 °C and pH = 7, the specific surface area is reduced by 60%. The parameters of drugs concentration C0 =(5,80) mg/L, time=(15,240) min, and pH= (2,12) were investigated, and the results showed that the HKUST-1/ZnO/SA is stable in water for 14 days and it can be used in 10 cycles with 80% removal efficiency. The maximum Adsorption loading of doxycycline and Naproxen upon HKUST-1/ZnO/SA is 97.58 and 80.04 mg/g, respectively. Based on the correlation coefficient (R2), the pseudo-second-order and the Langmuir isotherm models were selected for drug adsorption. The proposed mechanism of drug uptake is by MOFs, hydrogen bonding, electrostatic bonding, and acid-base interaction.

The numerical study of pressure and temperature effects on mechanical properties of baghdadite-based nanostructure: molecular dynamics simulation.

Bioceramics have been commonly implemented to replace and restore hard tissues such as teeth and bones in recent years. Among different bioceramics, Baghdadite (BAG) has high bioactivity due to its ability to form apatite and stimulate cell proliferation. So, this structure is used widely for medical applications to treat bone-based diseases. Physically, we expect changes in temperature and pressure to affect the Baghdadite-based nanostructure's mechanical behaviour. So, in this computational study, we report the pressure/temperature effect on Baghdadite matrix with nanoscale size by using Molecular Dynamics (MD) approach. To this end, physical values like the total energy, temperature, final strength (FS), stress-strain curve, potential energy, and Young's modulus (YM) are reported. Simulation results indicated the mechanical properties of Baghdadite (BAG) nanostructure weakened by temperature and pressure increase. Numerically, the FS and YM of the defined structure reach 131.40 MPa/159.43 MPa, and 115.15 MPa/139.72 MPa with temperature/pressure increasing. Therefore, the increase in initial pressure and temperature leads to a decrease in the mechanical properties of nanostructures. These results indicate the importance of the initial condition in the Baghdadite-based nanostructures' mechanical behaviour that must be considered in clinical applications.

The improvement of mechanical properties of conventional concretes using carbon nanoparticles using molecular dynamics simulation.

In the present study, the improvement of mechanical properties of conventional concretes using carbon nanoparticles is investigated. More precisely, carbon nanotubes are added to a pristine concrete matrix, and the mechanical properties of the resulting structure are investigated using the molecular dynamics (MD) method. Some parameters such as the mechanical behavior of the concrete matrix structure, the validation of the computational method, and the mechanical behavior of the concrete matrix structure with carbon nanotube are also examined. Also, physical quantities such as a stress-strain diagram, Poisson's coefficient, Young's modulus, and final strength are calculated and reported for atomic samples under external tension. From a numerical point of view, the quantities of Young's modulus and final strength are converged to 35 GPa and 35.38 MPa after the completion of computer simulations. This indicates the appropriate effect of carbon nanotubes in improving the mechanical behavior of concrete and the efficiency of molecular dynamics method in expressing the mechanical behavior of atomic structures such as concrete, carbon nanotubes and composite structures derived from raw materials is expressed that can be considered in industrial and construction cases.

A well-trained artificial neural network for predicting the rheological behavior of MWCNT-Al2O3 (30-70%)/oil SAE40 hybrid nanofluid.

In this study, the influence of different volume fractions ([Formula: see text]) of nanoparticles and temperatures on the dynamic viscosity ([Formula: see text]) of MWCNT-Al2O3 (30-70%)/oil SAE40 hybrid nanofluid was examined by ANN. For this reason, the [Formula: see text] was derived for 203 various experiments through a series of experimental tests, including a combination of 7 different [Formula: see text], 6 various temperatures, and 5 shear rates. These data were then used to train an artificial neural network (ANN) to generalize results in the predefined ranges for two input parameters. For this reason, a feed-forward perceptron ANN with two inputs (T and [Formula: see text]) and one output ([Formula: see text]) was used. The best topology of the ANN was determined by trial and error, and a two-layer with 10 neurons in the hidden layer with the tansig function had the best performance. A well-trained ANN is created using the trainbr algorithm and showed an MSE value of 4.3e-3 along 0.999 as a correlation coefficient for predicting [Formula: see text]. The results show that an increase [Formula: see text] has a significant effect on [Formula: see text] value. As [Formula: see text] increases, the viscosity of this nanofluid increases at all temperatures. On the other hand, with increasing temperature, the viscosity of this nanofluid decreases. Based on all of the diagrams presented for the trained ANNs, we can conclude that a well-trained ANN can be used as an approximating function for predicting the [Formula: see text].

Thermal and hydrodynamic properties of coronavirus at various temperature and pressure via molecular dynamics approach.

COVID-19 is an epidemic virus arising from a freshly discovered coronavirus. Most people involved with the coronavirus will experience slight to moderate respiratory disease and recover without needing particular therapy. In this work, the atomic stability of the coronavirus at different thermodynamic properties such as temperature and pressure, was studied. For this purpose, the manner of this virus by atomic precession was described with a molecular dynamics approach. For the atomic stability of coronavirus description, physical properties such as temperature, total energy, volume variation, and atomic force of this structure were reported. In molecular dynamics approach, coronavirus is precisely simulated via S, O, N, and C atoms and performed Dreiding force field to describe these atoms interaction in the virus. Simulation results show that coronavirus stability has reciprocal relation with atomic temperature and pressure. Numerically, after 2.5 ns simulation, the potential energy varies from - 31,163 to - 26,041 eV by temperature changes from 300 to 400 K. Furthermore, this physical parameter decreases to - 28,045 eV rate at 300 K and 2 bar pressure. The volume of coronavirus is another crucial parameter to the stability description of this structure. The simulation shows that coronavirus volume 92% and 14% increases by 100 K and 2 bar variation of simulation temperature and pressure, respectively.

Molecular dynamics performance for coronavirus simulation by C, N, O, and S atoms implementation dreiding force field: drug delivery atomic interaction in contact with metallic Fe, Al, and steel.

Coronavirus causes some illnesses to include cold, COVID-19, MERS, and SARS. This virus can be transmitted through contact with different atomic matrix between humans. So, this atomic is essential in medical cases. In this work, we describe the atomic manner of this virus in contact with various metallic matrix such as Fe, Al, and steel with equilibrium molecular dynamic method. For this purpose, we reported physical properties such as temperature, total energy, distance and angle of structures, mutual energy, and volume variation of coronavirus. In this approach, coronavirus is precisely simulated by O, C, S, and N atoms and they are implemented dreiding force field. Our simulation shows that virus interaction with steel matrix causes the maximum removing of the virus from the surfaces. After 1 ns, the atomic distance between these two structures increases from 45 to 75 Å. Furthermore, the volume of coronavirus 14.62% increases after interaction with steel matrix. This atomic manner shows that coronavirus removes and destroyed with steel surface, and this metallic structure can be a promising material for use in medical applications.

Calculation of the thermal conductivity of human serum albumin (HSA) with equilibrium/non-equilibrium molecular dynamics approaches.

BACKGROUND AND OBJECTIVE: Human serum albumin (HSA) controls the flow of numerous chemical structures and molecules in the cardiovascular system. So, thermal conductivity of this atomic compound is important in medicinal applications. METHODS: In this work, the thermal conductivity of HSA is calculated with equilibrium/non-equilibrium molecular dynamic approaches. In these methods each HSA molecule is exactly represented by C, N, O and S atoms and their implemented dreiding potential. Finally by using Green-Kubo and Fourier's law the thermal conductivity of HSA/H2O mixture is calculated. RESULTS: Our calculated rates for thermal conductivity via equilibrium/non-equilibrium molecular dynamics methods are 0.496 W/m K and 0.448 W/m K, respectively. The calculated thermal conductivity for this structure was very close to the thermal conductivity calculated for water molecules which were reported by other research groups. Furthermore our simulated structures show that thermal conductivity of HAS/H2O mixtures has inverse relation with HAS molecules numbers and temperature of simulated atomic structures. CONCLUSIONS: Comparing thermal conductivity from equilibrium/non-equilibrium molecular dynamics methods for HAS/H2O shows that EMD and NEMD results are reliable and EMD calculated results are higher than NEMD results.

Investigation of thermal properties of DNA structure with precise atomic arrangement via equilibrium and non-equilibrium molecular dynamics approaches.

BACKGROUND AND OBJECTIVE: Thermal conductivity of Deoxyribonucleic acid molecules is important for nanotechnology applications. Theoretical simulations based on simple models predict thermal conductivity for these molecular structures. METHODS: In this work, we calculate the thermal properties of Deoxyribonucleic acid with precise atomic arrangement via equilibrium and non-equilibrium molecular dynamics approaches. In these methods, each Deoxyribonucleic acid molecule is represented by C, N, O, and P atoms and implemented dreidng potential to describe their atomic interactions. RESULTS: Our calculated rate for thermal conductivity via equilibrium and non-equilibrium molecular dynamics methods is 0.381 W/m K and 0.373 W/m K, respectively. By comparing results from these two methods, it was found that the results from equilibrium and non-equilibrium molecular dynamics methods are identical, approximately. On the other hand, the number of DNA molecules and the equilibrium temperature of the simulated structures were important factors in their thermal conductivity rates, and their thermal conductivity was calculated at 0.323 W/m K-0.381 W/m K intervals for equilibrium and 0.303 W/m K-0.373 W/m K interval for non-equilibrium calculations. CONCLUSIONS: These results are in good agreement with thermal conductivity calculation with other research groups.