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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]

The single-flash geothermal cycle (SFGC) is not without its limitations, featuring drawbacks like diminished efficiency, restricted power generation capacity, and the incapability to yield multiple outputs concurrently. Furthermore, the SFGC requires a substantial water supply, potentially leading to adverse environmental consequences. In a concerted effort to enhance overall performance and facilitate the concurrent production of multiple valuable products, this study introduces a multigeneration system (MGS). By integrating additional subsystems into the SFGC framework, including a branched GAX cycle enabled by a thermoelectric generator (TEG), a domestic water heater (DWH), and a reverse osmosis unit, the objective is to surmount these limitations effectively. A thermodynamic and exergoeconomic analysis of the system is conducted and a bi-objective optimization is employed to minimize system cost and maximize exergy efficiency. The parametric study reveals that when degassing ranges are in the range of 0.2–0.37, the system product cost varies from $27.07/MWh to $28.44/MWh. In the optimized scenario there is a decrease of 67.7% in cooling provided by the system. This leads to an increase of 3.5% in generated electricity and a 3% increase in water purification compared to the base scenario. Through optimization the exergy efficiency of the system improves from 61.84% to 62.90% while the multigeneration gain output ratio (MGOR) decreases from 1.40 to 1.38. [ABSTRACT FROM AUTHOR]

Zeolites are among the most popular porous solids for hydrogen storage. Hydrogen attaches to the surface and microporous structure of zeolites. The literature mainly inspected the hydrogen adsorption capacity of zeolites (HACZ) experimentally and paid little attention to its modeling. Furthermore, there is no tool to compare/reveal the role of surface and pore characteristics of zeolites in hydrogen storage. This work applies several well-established artificial intelligence techniques to correlate the HACZ to surface and pore characteristics of zeolites, pressure, and temperature. The topology-tuned multi-layer perceptron neural network is the best model to simulate the hydrogen storage of fourteen systems (NH 4 Y, X, and ZSM-5). This model predicts the HACZ of a vast experimental databank with a regression coefficient of 0.99875 and an absolute average relative deviation of 6.43%. Results approve that the role of the BET surface area of zeolites on the HACZ is more vital than the pore volume. • Effect of surface and pore properties of zeolites on hydrogen storage is compared. • BET surface area of zeolites is more vital than pore volume for the H 2 storage. • Machine learning models are applied to simulate H 2 loading capacity of zeolites. • H 2 storage increases by increasing zeolites' BET surface area and total pore volume. • The proposed model predictions are interpretable by the Chahine's rule. [ABSTRACT FROM AUTHOR]

[Display omitted] • Cu-doped BC 3 nanosheet may be highly sensitive carbonyl sulfide gas sensor. • The carbonyl sulfide adsorption reduces the HOMO-LUMO energy gap of the Cu-doped BC 3 from 2.52 to 1.52 eV (∼-39.7%). • A short recovery time of 13.3 s is found for the carbonyl sulfide desorption. We explored the adsorption of carbonyl sulfide (COS) on a pristine and a Cu-doped graphene-like boron carbide nano-sheet (PBCNS and DBCNS) via density functional theory computations. When COS approached the BCNS, its adsorption released an energy of 6.8 to 7.5 kcal/mol, which demonstrates the weak nature of the adsorption. Furthermore, there was no appreciable alteration in the electronic characteristics of the nano-sheet. Cu-doping enhances the performance of the BCNS, improving it reactivity and sensitivity towards COS. The calculations demonstrated the adsorption of COS caused a reduction in the energy of the HOMO-LUMO gap of the DBCNS from 2.52 to 1.52 eV (∼-39.7%), suggesting a rise in the electrical conductance of the nano-sheet. Thus, DBCNS was capable of generating signals when the COS molecules approached, showing the promising nature of this nano-sheet as a sensor. The recovery time for DBCNS was 13.3 s , which was short. [ABSTRACT FROM AUTHOR]