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We studied the impact of dopants Al, Ga and In atoms on the dacarbazine (DAC) drug delivery performance of a BC3 nanosheet (BCNS) using the density functionals τ-HCTHhyb, M06-2X and B3LYP. It was found that the pristine BCNS is not a good choice for this drug delivery. Doping of the Al, Ga and In atoms into the BCNS surface raised the energy of adsorption of DAC from −6.7 to −26.4, −27.8 and −32.1 kcal / mol, respectively. According to the analysis of the partial density of states, the dopant atoms considerably contributed to the generation of virtual orbitals of doped BCNS. This showed that the dopants are more suitable for nucleophilic attack than the B atoms. Finally, the adsorption performance and capacity of the DAC are increased by dopants, making the nanosheet more favourable for drug delivery. A drug release mechanism was introduced in cancerous tissues, showing substantial protonation of the DAC in cancerous cells with low pH, leading to the separation of DAC from the sheet surface. The reaction mechanism of DAC with the BCNS changed from covalent bonding in the natural environment to H-bonding in the acidic environment of the cancer tissues. [ABSTRACT FROM AUTHOR]

Food and environment pollution is an international concern. It is, therefore, necessary to develop effective and fast techniques for determining contaminants in food samples and water. In this direction, 2D metal carbides and nitrides (MXenes), due to their rich surface functionalities, boosted effective surface area, and tunable physicochemical features have presented favorable performances in biosensing flatlands. This work concentrated on the role of MXenes in photoelectrochemical (bio)sensors, whose popularity has increased significantly in the last decade because of their functional structure and unique properties, such as low background signal, easy operation, high sensitivity, and inexpensive instrument. The MXene's effect on photoelectrochemical sensing procedures is reviewed comprehensively. In addition, the MXene's synthesis with a green strategy and incorporation of these processes into photoelectrochemical (bio)sensing applications are considered in depth, which provides new thoughts for the preparation of MXenes and the innovation of composite materials in the future PEC devices. Moreover, this work outlines the up-to-date trends in MXene-derived photoelectrochemical (bio)sensors for onsite sensing of agri-food contaminants. Mainly, we tried to provide a summary of various strategies used for target molecule analysis (pesticides, biotoxins, veterinary drug, and heavy metal ions). Finally, the challenges and future directions are concluded and depicted. [Display omitted] [ABSTRACT FROM AUTHOR]

The current research is conducted with the aim of investigating a multi-generation energy system (MGS) for electricity, hydrogen, heating, cooling and hot water production using SRC, Kalina cycle and proton exchange membrane (PEM) electrolysis as the main subsystems. The thermodynamic analysis namely energy, exergy, and exergo-economic examination carried out. Analysis for each component is done after thermodynamic modeling. The exergy investigation showed that regenerator 2, vapor generator and condenser had the highest exergy destruction rate, respectively. A comparison was made between the current work and the basic system, and according to the results obtained, the system's ability to produce electricity, cooling, heating and hydrogen are calculated as 782 kW, 173.2 kW, 2265 kW and 0.01613 mol/day, respectively. Also, the energy and exergy efficiency of the proposed system increased by 3.13% and 5.37%, respectively. The optimization based on PSO method was carried out. The results of PSO optimization represented that in the case exergy destruction and exergy efficiency will be the optimization target these two outputs can reach the value of 2208 kW and 9.84%, while optimization based on exergy efficiency and production cost rate will lead to 9.86% and 166.6 $/h. • Simulation a CSP based system to design a poly-generation energy system. • Using PEM electrolyzer to generate hydrogen as an energy storage media. • The exergy efficiency of introduced system is 3.13% higher than basic system. • The output power of new plant is 1.54 MW higher than basic cycle. [ABSTRACT FROM AUTHOR]

Electrode materials with appropriate mechanical, electronic and structural attributes are prerequisites for next generation renewable energy technology. An essential stage in development of batteries to achieve superior performance is selecting an appropriate anode material. In this research, application of B3S monolayer for anode materials has been investigated employing first-principles-based DFT. For B3S monolayer, as an anode material, it is anticipated to have high performance with a low sodium diffusion barrier (Ea < 0.45 eV), low open-circuit voltage (OCV∼0.12 V), and high storage capacity (1855 mA h g−1). In addition, metallicity of B3S monolayer has been maintained at the end of Na adsorption, which reveals a favorable battery operating cycle and electrical conductivity. Our findings elucidate that these outstanding attributes cause B3S monolayer to be an attractive option for anode materials in sodium-ion batteries (NIBs). [ABSTRACT FROM AUTHOR]

Non-alcoholic fatty liver disease is a type of fatty fat that causes an increase in alcohol consumption. Excessive alcohol consumption causes inflammation, and liver damage. The certain fatty acids (FAs) may be involved in this liver damage. Anti-inflammatory and blood lipid lowering effects are the effects of omega-3 unsaturated fatty acids (n-3 PUFAs). NAFLD is the hepatic manifestation of metabolic syndrome because obesity and insulin resistance are the main pathogenic factors of both diseases. NAFLD is a disease associated with metabolic syndrome. Most patients with NAFLD are obese, although the disease can also affect non-obese people. Metabolic and genetic factors play an important role in the occurrence of this disease. Oxidative stress, lipotoxicity and inflammation play a key role in the development of NAFLD. There is a lot of evidence for the therapeutic potential of omega-3 PUFAs fatty acids (n-3 PUFA), mainly docosahexaenoic acid and eicosatetraenoic acid in the treatment of metabolic diseases due to their antioxidant and anti-inflammatory properties. Therefore, in this review article, we examined the effects of omega-3 and omega-6 on alcoholic and non-alcoholic fatty liver disease. [ABSTRACT FROM AUTHOR]

Drug resistance is a hot topic issue in cancer research and therapy. Although cancer therapy including radiotherapy and anti‐cancer drugs can kill malignant cells within the tumor, cancer cells can develop a wide range of mechanisms to resist the toxic effects of anti‐cancer agents. Cancer cells may provide some mechanisms to resist oxidative stress and escape from apoptosis and attack by the immune system. Furthermore, cancer cells may resist senescence, pyroptosis, ferroptosis, necroptosis, and autophagic cell death by modulating several critical genes. The development of these mechanisms leads to resistance to anti‐cancer drugs and also radiotherapy. Resistance to therapy can increase mortality and reduce survival following cancer therapy. Thus, overcoming mechanisms of resistance to cell death in malignant cells can facilitate tumor elimination and increase the efficiency of anti‐cancer therapy. Natural‐derived molecules are intriguing agents that may be suggested to be used as an adjuvant in combination with other anticancer drugs or radiotherapy to sensitize cancer cells to therapy with at least side effects. This paper aims to review the potential of triptolide for inducing various types of cell death in cancer cells. We review the induction or resistance to different cell death mechanisms such as apoptosis, autophagic cell death, senescence, pyroptosis, ferroptosis, and necrosis following the administration of triptolide. We also review the safety and future perspectives for triptolide and its derivatives in experimental and human studies. The anticancer potential of triptolide and its derivatives may make them effective adjuvants for enhancing tumor suppression in combination with anticancer therapy. [ABSTRACT FROM AUTHOR]

The increasing concerns about pollutant emissions from the electricity generation sector have urged the deployment of novel and efficient technologies. In this regard, fuel cells are predicted to be essential in upcoming clean electricity generation systems. In particular, Flame-assisted Fuel Cells (FFCs) are among the new technologies and are envisaged to operate with various fuels; however, their relatively low electrical efficiency is a major drawback. The present research aims at the efficiency improvement of a methane-fueled FFC by recovering its waste heat for additional electricity generation using an Organic Rankine Cycle (ORC). To do so, a combined FFC-ORC framework is developed, and its thermodynamic performance as well as economic and environmental emission characteristics, are modeled. By implementation of parametric analysis, impacts on the performance of design/operating variables were examined. A tri-criteria optimization is also accomplished based on exergy efficiency, electricity cost, and CO 2 emission for the combined FFC-ORC and the standalone FFC. The results indicate better performance of the developed FFC-ORC over the standalone FFC in terms of efficiency and CO 2 emissions, respectively by 8.5-percentage points and 35.2%, under optimized cooperating conditions. However, the electricity cost shows an increment of 9.68% due to the additional expenditures associated with the ORC. [ABSTRACT FROM AUTHOR]

In this study, combining an excellent intrinsic property of polylactic acid (PLA) with the unique properties of three-dimensional (3D) printing technique and coating of chitosan-hydroxyapatite (CHI-HA) is used with electrospun nanofibers for the regeneration of hard tissues. This study aims to fabricate a microstructural scaffold with a PLA base by 3D fused deposition modeling (FDM) technique. High surface-to-volume ratio, high porosity, flexibility in surface performance, and exceptional mechanical performance are just a few of the characteristics that the small-diameter fibers display. Utilizing an examination from a scanning electron microscope (SEM), the morphological research is carried out. Besides, the biological reaction of the scaffolds is studied in phosphate buffer saline (PBS) and simulated body fluid (SBF). The samples are examined for wet and dry biological behavior, by SEM. Moreover, mechanical analyzes, including compressive strength and porosity, are performed on the samples and the results are evaluated in existing number models. Besides, the fuzzy modeling technique is used to forecast the properties of samples before fabricating and examining them. The results generally show that the presence of HA nanoparticles improves mechanical and biological properties. Specifically, the obtained results show that the sample with 10 wt% of HA is capable of suitable mechanical, chemical, and biological properties compared to other samples. [ABSTRACT FROM AUTHOR]

A new Fe3O4/Mo-MOF (metal–organic framework) magnetic nano polymer was synthesized in one step and Ultrasound assisted. Fe3O4/Mo-MOF magnetic nano polymer was characterized by XRD, SEM, EDX mapping BET, VSM, and FT-IR. The results of the structure confirmation revealed that the ultrasonic method had created unique properties in the Fe3O4/Mo-MOF magnetic nano polymer, and its biological and catalytic applications were investigated. A new pyrano[2,3-d]pyrimidines derivative was synthesized using the catalytic activity of Fe3O4/Mo-MOF magnetic nano polymer in a three-component reaction involving malononitrile, aldehyde derivatives, and barbituric acid derivatives with Fe3O4/Mo-MOF magnetic nano polymer as a magnetic catalyst. In the antimicrobial activity of Fe3O4/Mo-MOF magnetic nano polymer: Antimicrobial properties on gram-positive, gram-negative, and fungal strains based on MIC, MBC, and MFC value. The results of catalytic and biological studies proved that nanoparticles have unique properties attributed to their structure and synthesis method. [ABSTRACT FROM AUTHOR]

Air pollution is known as one of the most important causes of death in the whole world. Therefore, pollution reduction to achieve clean air was noticed by everyone. This way, using nanotechnology to control air and monitor is a novel approach. This paper investigates the effect of the number of graphene nano-pores on the SiO 2 separation from the H 2 O vapour in the presence of an external electric field with the magnitude of 0.01 V/Å using the molecular dynamics (MD) method. The electric field affects the charged particles and causes disturbance in the structure. It also prevents SiO 2 nanoparticles from passing through the graphene nanosheet. Also, the presence of carbon nanosheets acts as a membrane and affects the diffusion of water in the nanostructure. So, the results show that in the presence of a nano-pore, the number of H 2 O molecules reaches to 496 and 568 in reservoirs 2 and 3. Also, the number of SiO 2 nanoparticles reaches 10 and 4 in reservoirs 2 and 3. This shows that in reservoirs 2 and 3, about 80% and 60% of the SiO 2 nanoparticles are separated. As mentioned before, the electric field prevents the passage of SiO 2 nanoparticles through the graphene nanosheet. As the number of graphene nano-pores increases by 2, 3, 4, and 5, the number of passing water molecules increases. Considering that the number of graphene nano-pores has increased and the movement path of particles has increased, the number of passing particles almost increases. However, the electric field prevents the passage of SiO 2 nanoparticles. According to the results, the suggested setup can be employed for designing highly efficient nanostructured membranes for air purification and monitoring. [Display omitted] [ABSTRACT FROM AUTHOR]

Today, the use of alternative fuels that have plant origin has attracted the attention of most countries because these fuels emit less pollution. In this research, bioethanol production has been evaluated considering solar energy sources. In the present study, the possibility of developing net-zero energy concepts in a bioethanol production plant as one of the most consumed energy industries in the field of bio-systems of the country from a technical and economic perspective was investigated. The purpose of this research is to model the bioethanol production plant with the aim of achieving zero net energy using a photovoltaic system. In addition, technical and economic analyses have been used in different approaches for a more detailed investigation. According to the modeling done, in the zero net energy approach, the results showed that the maximum production of electrical energy by the photovoltaic cell is 76.6 GWh/y. For this approach, the return on investment is 10.7 years. The area required to install photovoltaic modules in this approach is very large and equal to 88 334 m2. [ABSTRACT FROM AUTHOR]

New nanocomposites containing zirconium were synthesized using microwave irradiation. Their structure was confirmed by vibrating sample magnetometer (VSM) curves, X-ray diffraction (XRD) patterns, scanning electron microscope (SEM) and transmission electron microscopy (TEM) images, Fourier transform infrared spectroscopy (FT-IR), and Brunauer–Emmett–Teller (BET) N2 adsorption/desorption isotherms. After the structure confirmation of the zirconium magnetic nanocomposite, the catalytic properties in the synthesis of pyrazole derivatives were investigated. Next, the biological activities of the zirconium magnetic nanocomposite, such as the antibacterial and antifungal activities, were investigated. The research results showed that the zirconium magnetic nanocomposite has high catalytic properties and can be used as a magnetic nanocatalyst for synthesizing heterocyclic compounds such as pyrazole derivatives in addition to having high biological properties. The unique properties of the nanoparticles can be attributed to their synthesis method and microwave radiation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Molecular dynamics method was implemented. • The present research investigates the influence of palladium percentage and oxygen ratio on air-methane catalytic combustion. • Combustion performance in the presence of excess oxygen and oxygen deficiency is reported. • Increasing palladium percentage improves the combustion performance. • Oxygen and palladium ratios can benefit the combustion process. Combustion is an exothermic chemical process between an explosive substance and an oxidizing agent that is accompanied by heat generation and chemical change of raw materials. Catalysts are used in a combustion process for various reasons, including the speed at which the material reaches equilibrium. Catalysts are chemicals that increase the rate of reaction in chemical processes. The present research investigates the influence of palladium percentage and oxygen ratio on air-methane catalytic combustion in a helical microchannel. For this purpose, the atomic behavior and combustion performance of the simulated sample in the presence of excess oxygen and oxygen deficiency is reported by the molecular dynamics (MD) method. The potential functions used in this paper were Lennard-Jones, the embedded atom model (EAM), and Coulomb. It is concluded that increasing palladium percentage in limited ratios improves the atomic and combustion performance of the simulated structure, and this enhancement is greater in the presence of excess oxygen. In the presence of excess oxygen, the numerical value of maximum density, velocity and temperature converged from 0.138 atom/Å3, 0.33 Å/ps and 523 K to 0.144 atom/Å3, 0.36 Å/ps and 539 K, respectively with increasing palladium percentage from 1 % to 4 %. And by increasing the palladium ratio to 10 %, these numerical values decrease to 0.137 atom/Å3, 0.31 Å/ps and 530 K. Moreover, in the presence of oxygen deficiency, heat flux, thermal conductivity, and combustion efficiency of atomic samples reached 2049 W/m2, 1.23 W/m.K and 90 % after rising palladium to 4 %, and it decreased to 2035 W/m2, 1.19 W/m.K and 86 % by adding 10 % palladium. Therefore, the results indicate that the oxygen and the catalyst (palladium) ratios can benefit the combustion process. These results can optimize the atomic performance and combustion performance of structures essential for use in various industries. [ABSTRACT FROM AUTHOR]

In this project, the possibility of drug delivery application of three anti- Multiple sclerosis (MS) agents (containing diroximel fumarate (DXF), dimethyl fumarate (DMF), and mono methyl fumarate (MMF)) by using some heteroatom decorated graphitic carbonitride (g-C 3 N 4) (as nano-sized carriers) have been systematically investigated. The results of the study have indicated that As-g-C 3 N 4 QD is not a suitable candidate for drug delivery (at least in the cases of DMF, and DXF drugs); while, it would be an accurate semiconductor sensor for selective detection of each mentioned agents. Also, the use of the P -doped as well as pristine g-C 3 N 4 QD could lead to weak electronic signals with relatively same values (in electronvolts). It means that P -g-C 3 N 4 , and g-C 3 N 4 QDs are not good sensors for detection of each of the three considered drugs. However, those two sorbents would be suitable carriers for delivering of all three mentioned pharmaceuticals. [Display omitted] • The results of the work showed that the pristine and the P -doped-g-C 3 N 4 QDs could be used as suitable vehicles for delivery of all three considered MS drugs; while, the As-g-C 3 N 4 QD could not be applied as a control released carrier at least for those mentioned drugs. • The frontier molecular orbital (FMO) studies showed that among all the three considered QDs, only the As-g-C 3 N 4 QD could be applied as a selective semiconductor sensor for detection of all three MS drugs. [ABSTRACT FROM AUTHOR]

• Flow of a Newtonian nanofluid in a porous cavity containing a heating element is simulated. • The finite volume method and mixture two-phase model have been used. • The heating element inside the cavity moves up or down to the width of the element. • Change in position of the heating element have significant effects on the physical patterns. • Increasing the ϕ and Ha decreases the entropy generation due to heat transfer and increases the frictional entropy generation. By increasing the efficiency of heating systems, more heat flux can be transferred in a certain dimension, thus lowering the operating temperature, or a specific heat flux can be transferred using a smaller heat exchanger. In this study, the flow of a Newtonian nanofluid in a square cavity containing a heating element filled with a porous medium is simulated under the effect of a uniform magnetic field in different rotation angles. The finite volume method (FVM) and two-phase mixture model were used. Water is used as the base fluid and Al 2 O 3 nanoparticles are used as the solid nanoparticles. The heating element inside the cavity, which is filled with porous medium with porosity percentage ε moves up or down to the width of the element. The fields of velocity, streamlines, and temperature are physically plotted, and Nusselt number and entropy generations diagrams are plotted. The results show that the change in the angle of the cavity and the change in position of the heating element on the hot wall have significant effects on the physical patterns. Other results indicate that with increasing volume fraction of nanoparticles and Rayleigh number (Ra), Nusselt number increases. Also, increasing the volume fraction of nanoparticles and Hartmann number (Ha) decreases the entropy generation due to heat transfer and increases the entropy generation due to friction. Also, it was found that in the cavity without a heating element, with increasing θ , the amount of local velocity increases in more places; so that, in case A and θ = 90 ° , it reaches its maximum value in the cavity without a heating element. As can be seen, by placing the heating element at θ = 0 ° , the maximum local velocity occurs above the heating element. Gradually, this value decreases with increasing the angle of the cavity filled with the porous medium relative to the x-axis to reach its minimum value in the cavity with θ = 90 °. [ABSTRACT FROM AUTHOR]

Hydrogen (H 2) as a clean and environmentally-friendly carrier can be introduced as the fuel of future to mitigate the air pollution caused by industrial anthropogenic activities. With the aim of fulfilling the need of a green H 2 green production, disparate technological processes have been developed in current decades. Purposeful review of these H 2 production processes can allow the expert readers as well as non-expert readers to properly perceive the limitations and future perspectives for future research. H 2 may be manufactured from renewable or non-renewable energy sources. Despite significant advancements in the techniques of H 2 production, the emergence of various operational/technical challenges in obtaining a steady state and stable H 2 economy via increasing the process yield and decreasing production costs has motivated the researchers the study more to develop more efficient processes. Therefore, development of a scientific techno-economic analysis for all existed H 2 production techniques is of great importance to highlight the future perspective of this important energy source. The main objective of this paper is to comprehensively review the advantages and disadvantages of various H 2 production techniques. Moreover, the economic dimensions of each technique along with the role of nanotechnology in the production of H 2 are aimed to be reviewed in this paper. • Review of limitations and future perspectives for future research of H 2 production. • Operational/technical challenges in obtaining a steady state and stable H 2. • Techno-economic analysis for all existed H 2 production techniques. • The role of nanotechnology in the production of H 2. [ABSTRACT FROM AUTHOR]

[Display omitted] • 5-FU adsorption on MgO nanotube is evaluated using DFT study and molecular docking simulation. • Adsorption process of 5-FU on MgO nanotube surface is chemisorption. • MgO nanotube is electronically sensitive to 5-FU drug. • Molecular docking results illustrated that 5-FU/MgO complexes have a good docking score with HER2. We evaluated the adsorption process and anti-cancer activity of functionalized magnesium oxide nanotube (MgONT) adsorbed with 5-Fluorouracil (5-FU) in vacuum and solution (water and toluene) phases via density functional theory (DFT) and time-dependent density functional theory (TD-DFT) calculations. 5-FU is chemisorbed preferentially by oxygen and hydrogen atoms to Mg and O atoms at the end tube (state III) with adsorption energies of approximately −2.01 eV (vacuum), −1.72 eV (water), and −1.84 eV (toluene) by the Perdew-Burke-Ernzerhof (PBE) functional and 6-311+G** standard basis set. TDDFT methods illustrated that the maximum optical absorption by the CAM-B3LYP method is in the UV region with an energy of 4.57 eV and a maximum absorption at 271.36 nm. Analysis of molecular docking illustrated that the interaction of 5-FU, as antineoplastic agent, with Mg and O atoms of the nanotube via its O- and H-atoms can enhanced inhibitory effects against Human Epidermal growth factor Receptor 2 (HER2) and Epidermal growth factor receptor (EGFR). The results illustrated that 5-FU/MgO complex could be useful for the development of novel anti-cancer agents to treat breast cancer patients. [ABSTRACT FROM AUTHOR]

Studying the dynamic viscosity (DV) is a key factor to determine the nanofluids' hydrodynamic behavior (NFs). In this research, the effect of volume fraction (φ), shear rate (SR), and temperature (T) on the DV, and torque of SiO 2 nanoparticles (NPs)/ Ethylene glycol (EG) nanofluid (NF) are studied with an artificial neural network (ANN). Different machine learning (ML) models are examined to predict the rheological properties, and then the best model is selected for prediction. The results show that the torque mostly increased linearly with the SR in all samples. The slope of this enhancing trend is higher for lower T. The Gaussian Process Regression (GPR) models with the Matérn covariance function provided the best results on both datasets to predict the DV. The correlation results provided by this method to predict the DV in terms of Pearson's Linear Correlation Coefficient (PLCC), and Spearman's Rank Order Correlation Coefficient (SROCC) were 0.999 and 1, respectively. R squared (R2) was 0.996 and, the Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) values of about 0.24 and 1.61 represented the accuracy and power of this method to predict the DV values unseen data by the model. The GPR torque predictor model performed very well by providing a correlation of about 0.98 and an RMSE of about 4. Matérn covariance functions that used separate length scales per predictor with ν = 3 / 2 (ardmatern 32) and ν = 5 / 2 (ardmatern52) were superior to other functions. All 100 models trained on each dataset were well-trained and quite reliable. The trained models were accurate enough to be used in related applications. [ABSTRACT FROM AUTHOR]

• Advanced modeling analysis of liquid-phase drug dissolution. • Validation of models using experimental data of drug solubility. • ET model was chosen as the most accurate and general model of process. Green processing based on supercritical solvents has attracted much attention recently in different fields such as pharmaceutical industry due to its superior characteristics. Comprehensive modeling was performed in this study to analyze the preparation of nanomedicine using green supercritical processing. Computational analysis was performed in order to estimate the solubility at different pressures and temperatures. The model was developed based on the input parameters and can estimate the only output of the process which is drug solubility in the supercritical solvent. In this work, we examined how temperature and pressure affect EXE (Exemestane) drug solubility using different tree-based ensemble methods. The models used in this analysis are the Random Forest (RF), the Extremely Randomized Tree (ET), and the Gradient Boosting (GB). Model optimization and hyper-parameter tuning are also accomplished with the aid of Golden eagle optimizer (GEOA). The R2 values for the test phases of ET, GB, and RF were 0.993, 0.985, and 0.978, respectively. The scores are 0.9945, 0.9758, and 0.9904 in train phases. Specifically, the ET model was chosen since it is the most accurate one. Error rates for this model are 2.317 with MSE, 1.522 with RMSE, and 0.2113 with MAPE. [ABSTRACT FROM AUTHOR]

[Display omitted] • This study investigates the effect of different nanoparticles on methyl ester-biodiesel fuel's combustion performance. • The following investigated the effects of different volume fractions of CuO nanoparticles. • This research used the MD simulation and the LAMMPS software package. • Heat flux reaches to 4448.89 W/m2 in the presence of 10% CuO nanoparticles. • It is expected that by optimizing this process, the combustion performance of fuels will be improved. Today, the problems, such as the environmental pollution caused by the consumption of fossil fuels, which have disrupted the ecological conditions and created environmental risks, as well as the limited reserves of fossil fuels, have caused countries worldwide to pay more attention to this type of energy. Biofuels are a type of fuel obtained from biomass sources. Biodiesel is one of the fuels produced from natural and renewable sources, which does not harm the environment. On the other hand, the presence of nanoparticles in alternative fuels is particularly important because adding nanoparticles reduces the ignition delay. This study investigated the effect of different nanoparticles, such as copper oxide (CuO) and aluminium oxide (Al 2 O 3), on methyl ester-biodiesel (as base fluid) fuel's combustion performance. The following investigated the effects of different volume fractions of CuO nanoparticles. This research used the molecular dynamics (MD) simulation, and the LAMMPS software package. The results show that CuO nanoparticles had better thermal performance than Al 2 O 3 nanoparticles. By adding Al 2 O 3 and CuO nanoparticles to the base fluid, the heat flux of the simulated nanofluid converged to a numerical value of 2410.31 W/m2 and 2410.31 W/m2, respectively. Because CuO nanoparticles show better thermal performance than Al 2 O 3 nanoparticles, the effect of the volume fractions of CuO nanoparticles on the thermal performance of the studied nanofluid was investigated. For this purpose, CuO nanoparticles with atomic ratios of 1%, 2%, 3%, 5% and 10% were added to the base fluid. The results reveal that the heat flux in atomic samples reached 4448.89 W/m2 in the presence of 10% CuO nanoparticles. It is expected that by optimizing this process, the combustion performance of fuels will be improved, fuel consumption will be optimized, and the emission of pollutants will be reduced. [ABSTRACT FROM AUTHOR]

• Investigation the thermal performance of the PCMs microcapsules with gold nanoparticles. • Using of C 2 H 5 NO, BrC 16 and PCM as microcapsules. • Importance of dimensions of structures in microcapsules to perform the heat transfer process. • Dimensions of designed structures in microcapsules to perform the heat transfer were important. • Increasing the shell thickness in these structures will reduce the heat transfer in the structures under study. This research studied the thermal performance of phase change material (PCM) microcapsules containing gold (Au) nanoparticles (NPs) in a nanochannel (NC) using molecular dynamics (MD) simulations. The MD simulation method is a reliable method for studying at micro and nano scales. In this simulation, the physical equilibrium was studied in the first stage by examining the simulated structure's kinetic and total energies. In the second stage, the thermal performance of simulated structure was surveyed. The thermal performance of structures was studied at different initial temperatures and initial pressure and the number of metal layers in NC shells. The results show that by increasing the initial temperature, the charging and discharging time, the viscosity and phase transition time decrease, and heat flux (HF) and thermal conductivity (TC) increase. Moreover, by changing the initial pressure (from 0 to 5 bar), the simulated samples' charging and discharging time, HF, and TC did not change much. This atomic behavior in the simulated samples shows that the simulated samples could operate without a drop in different initial conditions. The results indicate that by increasing the number of metal layers in the NC shells from 1 to 12, the force on fluid–structure increased, and consequently, the charging and discharging times increase to 2.54 ns and 3.40 ns. On the other hand, increasing the number of metal layers led to decreasing HF and TC of structures to 287.37 W/m2 and 1.18 W/m.K. Therefore, the dimensions of designed structures in atomic microcapsules to perform the heat transfer process were important. Increasing the shell thickness in these structures will reduce the heat transfer in the structures under study. [ABSTRACT FROM AUTHOR]

[Display omitted] • Efficient Mn 2 CuO 4 /CdO electrode was developed for photoelectrocatalytic efficiency. • The OH and h+ promoted CEP removal in PEC system. • The Mn 2 CuO 4 /CdO shows the excellent antibacterial activity versus E. coli and S. aurous. • Possible CEP degradation mechanism and pathways were investigated. • The Mn 2 CuO 4 /CdO depicts the great activity as probe for detection of Vitamin B1. Cadmium sulfide improved with dimanganese copper oxide (Mn 2 CuO 4 /CdO) was prepared and applied this semiconductor nanocomposites in advanced oxidative processes via the photoelectrocatalytic efficiency for cephalexin degradation. The Z-scheme Mn 2 CuO 4 /CdO nanocomposites was characterized by FESEM, XPS, UV–vis, EIS, and XRD. The photocurrent response were conducted in to evaluate the photo generated in the degradation reaction. Mn 2 CuO 4 /CdO was obtained to displays better photoelectrocatalytic response compared to bare CdO; this result shows the role of other semiconductor oxide material as photoanode construction. The degradation of cephalexin in photoelectrocatalytic response is higher than the photocatalytic process. A possible catalysis mechanism was depicted using free radicals scavengers. It was observed that hydroxyl radical and holes contribute as the main role in antibiotic degradation. The Mn 2 CuO 4 /CdO was used as great antibacterial agent versus Gram+/−. The Mn 2 CuO 4 /CdO probe was used to determine of vitamin B1 in peroxidase activity. The limit of detection was 41.21 nM. [ABSTRACT FROM AUTHOR]

• Solubility enhancement through SCCO 2 system. • Machine learning approaches to estimate and optimize the salicylsalicylic acid. • KNN model has been used as the best model to optimize the solubility of drug. Over the last decades, significant drawbacks of organic solvents such as high toxicity have motivated the scientists to find more eco-friendly solvents. Supercritical fluids (SCFs), especially SCCO 2 , are known as a promising class of solvent, which have shown their indisputable potential of application in industrial-based pharmaceutical activities due to possessing various advantages such as high abundancy, low cost, and insignificant toxicity. Machine Learning (ML) is considered as a numerical approach to estimate drug solubility in pharmaceutical industry. The purpose of this manuscript is to estimate the solubility of salicylsalicylic acid in SCCO 2 and compare it with experimental data using machine learning (ML) approach. A regression problem with 32 input vectors is the subject of this study, which is being conducted. This dataset contains two input features (P and T) and one output feature. We utilized Decision Tree (DT), K-nearest neighbor (KNN), and Multilayer perceptron (MLP) regression models as the first time for salicylsalicylic acid, which had error rates of 1.10E-01, 1.07E-01, and 7.13E-01, respectively, when using the MAPE measure. In addition, the R-squared scores for the DT, KNN, and MLP models are 0.974, 0.996, and 0.809, respectively. The third statistic is MAE, in which the error rates of models are 5.27E-05 for DT, 5.53E-05 for KNN, and 2.61E-04 for MLP. The error rates of DT, KNN, and MLP are all 5.27E-05. Finally, KNN was the most general model, with optimal values of P = 400, T = 338.0, and Y = 0.00388 being obtained. [ABSTRACT FROM AUTHOR]

• Solubility enhancement through advanced artificial intelligence model. • Applying different modeless of machine learning such as Random Forest, Extremely Random Trees, and Gradient Boosting Trees. • The GBRT has shown the less error rate and can be used as the best model. Over the last ten years, the application of novel mathematical models of Machine Learning employed to model the solubility of drugs especially anticancer drugs, in supercritical carbon dioxide (ScCO 2) system has gained remarkable popularity. In this research, three distinct ensemble models have been employed on the data as a novel method for busulfan as anticancer drug for the first time, based on decision trees, including Random Forest (RF), Gradient Boosting Trees (GBRT), and Extremely Randomized Tree (ERT) to predict the solubility of busulfan as an anticancer drug. The dataset has two input parameters, T = Temperature and P = Pressure, and Y = Solubility is the single output. After implementing and tuning these ensemble models' hyper parameters, the performance has been assessed through several metrics. All three models show R-squared score of more than 0.9, but in terms of RMSE, the error rates are 1.80E-04, 1.72E-04, and 1.03E-04 for RF, ERT, and GBRT models, respectively. Also, MAPE metrics 4.51E-01, 4.87E-01, and 3.62E-01 errors had found for RF, ERT, and GBRT models, respectively. GBRT has been selected as the best model due to the less rate of RMSE and MAPE. An analysis has also been performed to find the optimal amount of solubility, which can be considered the (x1 = 38.3, x2 = 333.1, Y = 1.36E-03) vector. [ABSTRACT FROM AUTHOR]

This study describes the mechanical behavior of a brick structure by inserting graphene nano-sheet (GNS) into this construction material using the Molecular Dynamics (MD) approach. Technically, we utilized Universal Force Field (UFF) and Tersoff Force Field (TFF), respectively, to simulate ideal brick (pristine brick) and graphene structures. The consequence of the equilibrium procedure of atomic structures indicates their suitable physical stability, which emerges from the proper MD simulation settings. Technically, to characterize the mechanical properties (MP) of pristine brick matrix (PBM) and reinforced brick-graphene (RBG) nanocomposite, some parameters like Stress-Strain (S–S) Curve, Young's modulus (YM), and Ultimate Strength (US) of a pristine compound, and reinforced structure are mentioned. Numerically, by inserting the GNS into the PBM with a 5% atomic ratio, Young's modulus of simulated nanostructure reaches 3379 MPa, and the US of brick increases to 19.14 MPa. These simulation results show the important effect of GNS on the MP of the PBM, which is suitable for construction applications such as cologne arches. • We investigated the mechanical behavior of brick structure by inserting Graphene nanosheets. • Stress-strain curve, Young's modulus, and ultimate strength of pristine compound and reinforced structure were reported. • Young's module reaches to 3379 MPa and the ultimate strength of brick increases to 19.14 MPa. • TResults show the effect of graphene nanosheets on mechanical properties. [ABSTRACT FROM AUTHOR]

• Cu-CNT (7, 0) and Cu-BNNT (7, 0) handled SO 2 oxidation via ER and LH mechanisms. • In ER and LH pathways two and one SO 3 molecules released, respectively. • High potential of Cu-CNT (7, 0) and Cu-BNNT (7, 0) to SO 2 oxidation was proved. • Systematic picture to design of novel metal-doped nano-catalysts was presented. The SO 2 oxidation by using of the Cu-carbon nanotube and Cu-borne nitride nanotube is investigated by LH and ER mechanisms. The E formation values of CNT (7, 0), BNNT (7, 0), Cu-CNT (7, 0) and Cu-BNNT (7, 0) are negative and so the CNT (7, 0), BNNT (7, 0), Cu-CNT (7, 0) and Cu-BNNT (7, 0) are stable structures, from thermodynamic viewpoint. Based on abilities of Cu-CNT and Cu-BNNT, SO 2 is joined to Cu-surface-O 2 * to produce intermediate. The cis-Cu-surface-O-SO 2 -O* in ER is more stable than corresponding complex in LH. Results indicated that the most stable complexes of O 2 , SO 2 and SO 3 species have lower E HLG values than other corresponding complexes, significantly. The ER pathway can be considered to oxidize of SO 2 molecule via Cu-CNT and Cu-BNNT surfaces. The ER pathway is recommended pathway to creation of primary SO 3 molecule as main step in SO 2 oxidation (SO 2 + Cu-surface-O 2 * → SO 3 + Cu-surface-O*). Finally, the Cu-CNT and Cu-BNNT can catalyze oxidation of SO 2 , efficiently. [ABSTRACT FROM AUTHOR]

[Display omitted] • The fabrication of ZnCo 2 O 4 -ZnO NSs was expanded using Polyethylene glycol. • The catalyst's properties were specified by FT-IR, SEM, TEM, XRD, and EDS analyses. • ZnCo 2 O 4 -ZnO NSs were deployed for the adsorption and elimination of asphaltene from crude oil. An advanced and eco-friendly method for the fabrication of ZnCo 2 O 4 -ZnO nanostructures (NSs), as highly effective nanocatalyst, was expanded using Polyethylene glycol (PEG) which is a new type of fuel and stabilizer. The influence of effectual elements such as the type of PEG and its quantity on the morphological features and function of ZnCo 2 O 4 -ZnO nanocatalyst was probed. The findings showed that changing the type of PEG and its amount can effectively control the dimensions, performance, and shape of ZnCo 2 O 4 -ZnO nanoparticles. The properties of produced ZnCo 2 O 4 -ZnO NSs were probed by FTIR, XRD, TGA, and, SEM, TEM. ZnCo 2 O 4 -ZnO NSs were employed as an extremely effectual recoverable adsorbent for the adsorption and elimination of asphaltene from crude oil. The existence of heterogeneity did not stop the progress. The products were effortlessly isolated from the green media, and the catalyst was employed many times without a distinguished drop in activity and selectivity. [ABSTRACT FROM AUTHOR]

[Display omitted] • The predictive PC-SAFT EoS has been utilized to predict the speed of sound, the isochoric and isobaric heat capacity of ionic liquids. • The surface area and molecular volume of the UNIFAC model have been used to estimate the segment number and hard sphere diameter. • The predictive PC-SAFT model can predict the specific isochoric and isobaric heat capacity of ILs up to high pressure, accurately. In this work, the predictive PC-SAFT EoS has been developed to predict the speed of sound, the isochoric and isobaric heat capacity of ionic liquids (ILs) over a wide range of pressures and temperatures. In this new methodology, the segment number and diameter of ILs have been estimated using the surface area and molecular volume of the UNIFAC model. The segment energy and association energy parameters have been obtained using an inverse relationship between dispersion/association energy and segment diameter. The results show that the predictive PC-SAFT model can predict the specific isochoric and isobaric heat capacity of ILs up to high pressure, accurately. In the case of the speed of sound, the model performance is acceptable by considering using no adjustable model parameters. To check the model capability, the new model results have been compared to the electrolyte PC-SAFT EoS. [ABSTRACT FROM AUTHOR]

• Computational analysis of drug solubility in supercritical CO 2. • Investigations on the influence of pressure and temperature on solubility. • Validating the proposed models using measured dataset. Preparation of drug nanoparticles has been studied and evaluated in this study based on supercritical-based processing as green technology. Computational works have been conducted to evaluate the possibility of manufacturing nanomedicine using this novel technology, and the results are compared with experimental measurements. Chlorothiazide, used as a diuretic and as an antihypertensive was considered as model drug in this work. For the modeling, we used a small data set consisting of two input features, namely temperature and pressure, and one output, namely solubility, in order to analyze the data. Tree ensemble models, including bagging and boosting based on decision trees, have been selected to analyze and model the data. Extremely randomized Trees (Extra Tree), Adaptive Boosting (AdaBoost), and Gradient Boosting models are specifically chosen for this modeling. The hyperparameters of the models were optimized with the help of genetic algorithm (GA) and finally the optimal models were obtained for each of the three methods. Finally, the models were evaluated with different methods. Based on the evaluations, the gradient boosting model showed the best results, and its score was 0.9820 with the coefficient of determination (R2-score) criterion. Also, the error of the final model with the MEA criterion is 1.51 × 10-2, with the RMSE criterion equal to 2.51 × 10-2, and the MAPE error value is 1.59 × 10-2. [ABSTRACT FROM AUTHOR]

Graphene is one of the most important two-dimensional carbon allotropes with a plate structure similar to honeycomb nets. Due to its high thermal conductivity (TC), it is an excellent material for the thermal management of electronic nano-components. Investigating and obtaining thermal attributes of graphene for use and replacement in electronic components to study the cooling of parts is one of the important topics discussed by researchers. This research investigates monolayer graphene (MG) and helical graphene (HG). First, the TC of MG is calculated and compared using the equilibrium method (Green-Kubo) and the non-equilibrium method. The produced graphene sheets are usually not perfect and have various defects affecting graphene's thermal and mechanical attributes. Then, the impact of nitrogen doping defect on the TC of MG is investigated. In addition, three samples of HG in different dimensions are simulated using the non-equilibrium method. The TC for each of these samples is obtained and compared. Finally, as an innovation of this research, simulated graphene coated with hydrogen atoms and TC are calculated for this model. The results show that nitrogen doping in the graphene structure reduces the amount of TC. The TC of HG depends on the effective length of the structure and the cross-sectional area of the structure. Also, the TC was reduced by hydrogenating the HG structure. [Display omitted] [ABSTRACT FROM AUTHOR]

• The properties of nanofluid in nanochannel in the presence of surfactant molecules are investigated in rectangular atomic channel. • Water molecules are considered as the base fluid, copper atoms as nanoparticles and CTAB molecules were considered as surfactant. • The Atomic stability of simulated nanofluid don't disrupted by surfactant molecules adding to MD simulation box. • Cu nanoparticles and CTAB molecules adding to base fluid molecules improve their thermal behavior. • MD simulation results which calculated by using the Drieding UFF force, and Charm force fields have similar form. The poor heat transfer properties of the base fluid are the first effective obstacle to improving heat exchangers' efficiency. The key point of using very high conductivity of solid particles (in nanometer dimension) is hundreds of times more than common fluids in heat transfer in the composition of these fluids. Therefore, adding nanoparticles (NPs) to base fluids has been a solution to increase the heat transfer (HT) properties of common energy-carrying fluids. On the other hand, adding surfactants prevents the sedimentation and instability of NPs and improves the thermal performance of nanofluids (NF). So, this study surveyed the thermal properties of water-copper NF with/without surfactant molecules in a rectangular nanochannel using molecular dynamics (MD) simulation. Cetryltrimethylammoniu Bromide (CTAB) molecules were used as surfactants, copper structure as NPs, and water molecules as a base fluid in this simulation. In the present study, the effect of nanochannel wall temperature, copper nanoparticle (NP) size, and force field type (DREIDING, Universal Force-Field (UFF), and CHARM) on thermal conductivity (K nf) of water-copper NF were studied. The results show that as the wall temperature decreased from 80 to 30 K, K nf decreased from 0.783 to 0.753 Wm-1K−1. On the other hand, by increasing the radius of NPs from 0.5 to 2 nm, K nf and heat flux (HF) increase from 0.77 to 0.798 Wm-1K−1 and 5734 to 6352 W.m−2, respectively. One of the important purposes of researchers and engineers in various industries is to increase efficiency and reduce the systems' size. Therefore, it is expected that the results of this study will be effective in many different thermal industries. [ABSTRACT FROM AUTHOR]

[Display omitted] • Novel SPE sorbent based on PET based AC were prepared by a facile cross-linking procedure. • GAC shows outstanding efficiency for PAHs extraction from environmental water samples. • The proposed SPE method illustrated high sensitivity and precision. In this study, granular activated carbon (GAC) from polyethyleneterephthalate (PET) bottle waste was employed for the solid phase extraction (SPE) of trace levels of some polycyclic aromatic hydrocarbons (PAHs) in environmental waters. The structure of GAC was studied using scanning electron microscopy (SEM), X-ray diffraction analysis (XRD) and Brunauer-Emmett-Teller (BET) adsorption technique. Using high performance liquid chromatography coupled with an ultraviolet detector (HPLC-UV) system, the produced porous sorbent was used for the extraction and measurement of trace levels of PAHs. Due to its high porosity and easy collection, the GAC can be considered as a potential solid phase sorbent towards PAHs. The experimental factors such as GAC mass, sorption time, elution solvent and salt concentration were explored and optimized. The linear dynamic ranges and detection limits under optimal conditions were in the range of 0.1–200 ng mL−1 and 0.01–0.07 ng mL−1, respectively. The analysis of PAHs in the real water samples using this platform was successfully investigated with appropriate recovery values (93.5–102.2 %). [ABSTRACT FROM AUTHOR]

In this study, the wave propagation and vibration analysis of sandwich structure with a bio-based flexible core and composite face sheets subjected to magnetic field are studied. In the present analysis, the material properties of composite face sheets are assumed viscoelastic based on Kelvin -Voigt model, and high-order sandwich panels theory is used for core modeling. The analysis of wave propagation and vibration of the sandwich structure is performed assuming complete adhesion between core and face sheets, and the governing equations of motion are derived by Hamilton's principle. Finally, the semi-analytical solution is applied to obtain the effects of the structural and foundation damping coefficients, different angles of the layers, the ratio of width to thickness, the ratio of the thickness of the core to the procedures, temperature variations, wave number, aspect ratios, elastic properties and number of layers on the wave propagation behavior of the sandwich plate for complete adhesion between layers. The results show that by increasing the ratio of the thickness of the core to the layers, the velocity of the wave propagation initially increases, and then decreases. Also, the application of the magnetic field has an increasing effect on the sandwich plate frequency. Finally, with the increase in the number of layers and the number of waves, the phase velocity increases, while the hardness of the system decreases when the temperature and damping coefficient rises. [ABSTRACT FROM AUTHOR]

• The Molecular Dynamics simulation method is implemented. • This study simulates ammonia refrigerant's atomic behavior with Cu nanoparticles in a nanochannel. • With increasing the external electric field amplitude to 5 Å, the heat flux values converge to 1395 W/m2. • The sample has a higher heat flux in the presence of a rectangular cubic atomic cavity. • Heat flux and aggregation time values for samples with rectangular cubic cavities are 1650 W/m2, 4.59 ns, respectively. With the ever-increasing energy costs, the need to improve the efficiency of cooling systems, reduce costs, and optimize the design is usually the first goal for system designers. One way to improve these systems is to use nano-refrigerants (NRs). This study simulates the thermal manner of ammonia refrigerant with Cu nanoparticles (NPs) in a nanochannel (NC) by calculating parameters such as velocity (V) and temperature (T) profiles, aggregation time (AT), and heat flux (HF). The result shows that by increasing the electric field amplitude (EFA) from 1 to 5 V/m, the maximum V and maximum T increase from 0.00086 Å/ps and 240 K to 0.00089 Å/ps and 245 K, respectively. With increasing the external EFA to 5 V/m, the HF value converges to 1395 W/m2, and the AT decreases to 3.90 ns. On the other hand, the change in maximum V in the samples with the pyramid, half-spherical (HS), and rectangular cubic (RC) cavities reached 0.74000 Å/ps, 0.00072 Å/ps, and 0.6565 Å/ps, respectively, and the maximum T changes to 232 K, 238 K, and 235 K in the RC, HS, and pyramid cavities samples. The results show that the structure has a higher HF in the presence of the RC cavity. So, the HF and AT values for samples with RC cavities are 1650 W/m2 and 4.59 ns, respectively. [ABSTRACT FROM AUTHOR]

The novel Ag0/Cu 2 MoO 4 nanoparticles was simply synthesized via chemical method. Ag/Cu 2 MoO 4 nanoparticles was characterized by FESEM image, XRD curve, UV–vis spectroscopy, BET analysis, and XPS spectrum. XRD pattern depicts that the cubic crystalline phase of particles. The band gap of Ag/Cu 2 MoO 4 nanoparticles was achieved to 2.04 eV, which that depicted the best activity under visible light irradiation. Ag/Cu 2 MoO 4 nanoparticles exhibits 99.74% degradation under light and persulfate ion which was higher response than Cu 2 MoO 4 nanoparticles (83.56%) under this condition. The scavenging test indicates the important reactive species in removal process were •OH, and •SO 4 −. The Ag/Cu 2 MoO 4 nanoparticles was indicated highly photo-stability for the MG degradation after 5th cycle. Ag/Cu 2 MoO 4 exhibits substantial antibacterial properties against P. aeruginosa and S. pneumoniae. Moreover, Ag/Cu 2 MoO 4 nanoparticles was experimented to peroxidase-like performance for the colorimetric detection of glucose with the Limit of Detection about 52.23 nM. • Ag/Cu 2 MoO 4 nanoparticles synthesized by facile chemical method. • Ag/Cu 2 MoO 4 nanoparticles proficiently activate persulfate ions resulting in enhanced photocatalytic dye degradation. • Ag/Cu 2 MoO 4 nanoparticles exhibit the highest bactericidal activity. • The peroxidase like activity of Ag/Cu 2 MoO 4 nanoparticles was tested to detection glucose detection. [ABSTRACT FROM AUTHOR]