A review on development and modification strategies of MOFs Z-scheme heterojunction for photocatalytic wastewater treatment, water splitting, and DFT calculations.

Increasing water pollution and decreasing energy reserves have emerged as growing concerns for the environment. These pollution are due to the dangerous effects of numerous pollutants on humans and aquatic organisms, such as hydrocarbons, biphenyls, pesticides, dyes, pharmaceuticals, and metal ions. On the other hand, the need for a clean environment, finding alternatives to fossil and renewable fuels is very important. Hydrogen (H2) is regarded as a viable and promising substitute for fossil fuels, and a range of methodologies have been devised to generate this particular source of energy. Metal-organic frameworks (MOFs) are a new generation of nanoporous coordination polymers whose crystal structure is composed of the juxtaposition of organic and inorganic constituent units. Due to their flexible nature, regular structure, and high surface area, these materials have attracted much attention for removing various pollutants from water and wastewater, and water splitting. MOFs Z-scheme heterojunctions have been identified as an economical and eco-friendly method for eliminating pollutants from wastewater systems, and producing H2. Their low-cost synthesis and unique properties increase their application in various energy and environment fields. The heterojunctions possess diverse properties, such as exceptional surface area, making them ideal for degradation and separation. The development and formulation of Z-scheme heterojunctions photocatalytic systems using MOFs, which possess stable and potent redox capability, have emerged as a successful approach for addressing environmental pollution and energy shortages in recent times. Through the utilization of the benefits offered by MOFs Z-scheme heterojunctions photocatalysts, such as efficient separation and migration of charge carriers, extensive spectrum of light absorption, among other advantages, notable enhancements can be attained. This review encompasses the synthesis techniques, structure, and properties of MOFs Z-scheme heterojunctions, and their extensive use in treating various wastewaters, including dyes, pharmaceuticals, and heavy metals, and water splitting. Also, it provides an overview of the mechanisms, pathways, and various theoretical and practical aspects for MOFs Z-scheme heterojunctions. Finally, it thoroughly assesses existing challenges and suggests further research on the promising applications of MOFs Z-scheme in industrial-scale wastewater treatment.

New insight into impact of humidity on direct air capture performance by SIFSIX-3-Cu MOF.

Removal of CO2 from air is one of the key human challenges in battling global warming. SIFSIX-3-Cu is a promising metal-organic framework (MOF) suggested for carbon capture even at low CO2 concentrations. However, the impact of humidity on its performance in direct air capture (DAC) is poorly understood. To evaluate the MOF performance for DAC application under humid conditions, we investigate the adsorption of H2O, CO2, and N2 using density functional theory (DFT), grand canonical Monte Carlo (GCMC), and molecular dynamics (MD) simulations. The simulation results show a higher tendency of SIFSIX-3-Cu towards H2O adsorption rather than CO2 (and N2). The results agree with the adsorption isotherms for the pure compounds from the Sips model. The extended Sips model shows 1.34 mmol g-1 CO2 adsorption at the atmospheric pressure and 298 K for the CO2/N2 mixture containing 400 ppm CO2, and low CO2 adsorption (less than 0.75 mmol g-1) at a low relative humidity (RH) of 20%. This finding highlights the efficiency of SIFSIX-3-Cu for DAC in dry air and the negative impact of humidity on the CO2 selective adsorption. Therefore, we suggest to consider the impairing of humidity effects when designing a SIFSIX-3-Cu-based CO2 separation process and removal of any water vapor before introduction of the air to SIFSIX-3-Cu.

Improving the estimation accuracy of confined vapor-liquid equilibria by fine-tuning the pure component parameter in the PC-SAFT equation of state.

We propose a thermodynamic model that combines the Young-Laplace equation and perturbed chain-statistical associating fluid theory (PC-SAFT) equation of state to estimate capillary condensation pressure in microporous and mesoporous sorbents. We adjust the PC-SAFT dispersion-energy parameter when the pore size becomes comparable to the molecular dimension. This modelling framework is applied to diverse systems containing associating and non-associating gases, various sorbents, and a wide range of temperatures. Our simulation results show that under extreme confinement, a higher value of the dispersion-energy parameter (ε) is required. Furthermore, using the experimental saturation pressure data for 18 different associating and non-associating confined fluids, we find that the shift in the PC-SAFT dispersion energy correlates with the ratio of the sorbent mean pore size to the PC-SAFT segment size (rp/σ). By fitting to the capillary condensation data, the relative deviation between the confined and bulk PC-SAFT dispersion energy parameter is only 0.1% at rp/σ = 15; however, this deviation starts to increase exponentially as rp/σ decreases. For a sorbent with large pores, when rp/σ > 15, the capillary condensation pressure results from our model are similar to the predictions from the Kelvin equation. Using a dataset containing 235 saturation pressure data points composed of 18 pure gases and 4 binary mixtures, the overall AARD% from our model is 12.26%, which verifies the good accuracy of our model. Because the mean sorbent pore radius (rp), the PC-SAFT energy parameter (ε), and segment size (σ) are known a priori, our model estimates the corrected energy parameter for small pores and, thus, extends its applicability.

Adsorption of copper from water using TiO2-modified activated carbon derived from orange peels and date seeds: Response surface methodology optimization.

This study evaluated the application and efficiency of modified activated carbon in the removal of copper (Cu) from synthetic aquatic samples. The surface of activated carbon derived from orange peel (AC-OP) and date seeds (AC-DS) have been modified by Titanium dioxide nanoparticles (TiO2 NPs) (1:10 wt% mixing ratio) and used in a series of experiments designed by Response Surface Methodology (RSM) incorporating Central Composite Design (CCD). The Brunauer-Emmett-Teller (BET) test demonstrated that the modification has increased the surface area of AC-OP from 2.40 to 6.06 m2 g-1 and AC-DS from 51.10 to 81.37 m2 g-1. Effects of pH (1-7), ion initial concentration (10-60 mg L-1), adsorbent dose (0.5-8 g L-1), and contact time (0.4-6 h) have been investigated. The results showed that the optimum conditions for TiO2-modified AC-OP (OP-TiO2) are pH 5, initial concentration of 24.6 mg L-1, adsorbent dose of 4.9 g L-1, and contact time of 3.6 h. The optimum conditions for TiO2-modified AC-DS (DS-TiO2) are pH 6.4, initial concentration of 21.2 mg L-1, adsorbent dose of 5 g L-1, and contact time of 3.0 h. The modified quadratic models represented the results well with regression coefficients of 0.91 and 0.99 for OP-TiO2 and DS-TiO2, respectively. The maximum Cu removal for OP-TiO2 and DS-TiO2 were 99.90 % and 97.40 %, and the maximum adsorption capacity was found to be 13.34 and 13.96 mg g-1, respectively. Kinetic data have been fitted to pseudo first-order, pseudo second-order, intra-particle diffusion, and Elovich models. The pseudo second-order showed a better fit to the experimental data (R2 > 98 %). This study demonstrates the successful development of modified activated carbon derived from orange peels and date seeds, modified by TiO2 nanoparticles, for efficient adsorption of copper ions from water. The findings contribute to understanding the adsorption mechanism and provide valuable insights for designing environmentally friendly adsorbents.

Olive stone as an eco-friendly bio-adsorbent for elimination of methylene blue dye from industrial wastewater.

Adsorbents synthesized by activation and nanoparticle surface modifications are expensive and might pose health and ecological risks. Therefore, the interest in raw waste biomass materials as adsorbents is growing. In batch studies, an inexpensive and effective adsorbent is developed from raw olive stone (OS) to remove methylene blue (MB) from an aqueous solution. The OS adsorbent is characterized using scanning electron microscopy (SEM), Fourier Transform Infra-Red (FTIR), and Brunauer-Emmett-Teller (BET) surface area. Four isotherms are used to fit equilibrium adsorption data, and four kinetic models are used to simulate kinetic adsorption behavior. The obtained BET surface area is 0.9 m2 g-1, and the SEM analysis reveals significant pores in the OS sample that might facilitate the uptake of heavy compounds. The Langmuir and Temkin isotherm models best represent the adsorbtion of MB on the OS, with a maximum monolayer adsorption capacity of 44.5 mg g-1. The best dye color removal efficiency by the OS is 93.65% from an aqueous solution of 20 ppm at the OS doses of 0.2 g for 90 min contact time. The OS adsorbent serves in five successive adsorption cycles after a simple filtration-washing-drying process, maintaining MB removal efficiency of 91, 85, 80, and 78% in cycles 2, 3, 4, and 5, respectively. The pseudo second-order model is the best model to represent the adsorption process dynamics. Indeed, the pseudo second-order and the Elovich models are the most appropriate kinetic models, according to the correlation coefficient (R2) values (1.0 and 0.935, respectively) derived from the four kinetic models. The parameters of the surface adsorption are also predicted based on the mass transfer models of intra-particle diffusion and Bangham and Burt. According to the thermodynamic analysis, dye adsorption by the OS is endothermic and spontaneous. As a result, the OS material offers an efficient adsorbent for MB removal from wastewater that is less expensive, more ecologically friendly, and economically viable.

Hybrid Smart Strategies to Predict Amine Thermal Degradation in Industrial CO2 Capture Processes.

CO2 emission reduction is an essential step to achieve the climate change targets. Solvent-based post-combustion CO2 capture (PCC) processes are efficient to be retrofitted to the existing industrial operations/installations. Solvent degradation (and/or loss) is one of the main concerns in the PCC processes. In this study, the thermal degradation of monoethanolamine (MEA) is investigated through the utilization of hybrid connectionist strategies, including an artificial neural network-particle swarm optimization (ANN-PSO), a coupled simulated annealing-least squares support vector machine (CSA-LSSVM), and an adaptive neuro-fuzzy inference system (ANFIS). Moreover, gene expression programming (GEP) is employed to generate a correlation that relates the solvent concentration to the operating variables involved in the adverse phenomenon of solvent thermal degradation. The input variables are the MEA initial concentration, CO2 loading, temperature, and time, and the output variable is the remaining/final MEA concentration after the degradation phenomenon. According to the training and testing phases, the most accurate model is ANFIS, and the reliability/performance of its optimal network is assessed by the coefficient of determination (R2), mean squared error, and average absolute relative error percentage, which are 0.992, 0.066, and 2.745, respectively. This study reveals that the solvent initial concentration has the most significant impact, and temperature plays the second most influential effect on solvent degradation. The developed models can be used to predict the thermal degradation of any solvent in a solvent-based PCC process regardless of the complicated reactions involved in the degradation phenomenon. The models introduced in this study can be employed for the development of more accurate hybrid models to optimize the proposed systems in terms of cost, energy, and environmental prospects.

Strategies To Improve the Performance of Hydrogen Storage Systems by Liquefaction Methods: A Comprehensive Review.

The main challenges of liquid hydrogen (H2) storage as one of the most promising techniques for large-scale transport and long-term storage include its high specific energy consumption (SEC), low exergy efficiency, high total expenses, and boil-off gas losses. This article reviews different approaches to improving H2 liquefaction methods, including the implementation of absorption cooling cycles (ACCs), ejector cooling units, liquid nitrogen/liquid natural gas (LNG)/liquid air cold energy recovery, cascade liquefaction processes, mixed refrigerant systems, integration with other structures, optimization algorithms, combined with renewable energy sources, and the pinch strategy. This review discusses the economic, safety, and environmental aspects of various improvement techniques for H2 liquefaction systems in more detail. Standards and codes for H2 liquefaction technologies are presented, and the current status and future potentials of H2 liquefaction processes are investigated. The cost-efficient H2 liquefaction systems are those with higher production rates (>100 tonne/day), higher efficiency (>40%), lower SEC (<6 kWh/kgLH2), and lower investment costs (1-2 $/kgLH2). Increasing the stages in the conversion of ortho- to para-H2 lowers the SEC and increases the investment costs. Moreover, using low-temperature waste heat from various industries and renewable energy in the ACC for precooling is significantly more efficient than electricity generation in power generation cycles to be utilized in H2 liquefaction cycles. In addition, the substitution of LNG cold recovery for the precooling cycle is associated with the lower SEC and cost compared to its combination with the precooling cycle.

Recovery of fuel from real waste oily sludge via a new eco-friendly surfactant material used in a digital baffle batch extraction unit.

This study focused on developing a new cocktail extraction agent (CEA) composed of solvent and a new surfactant material (SM) for enhancing the efficiency of fuel recovery from real waste oil sludge (WSO). The effects of different solvents (e.g. methyl ethyl ketone (MEK), naphtha, petrol and kerosene), SMs (Dowfax and sodium thiosulfate), extraction time (10-20 min), extraction temperatures (20-60 °C) and CEA/sludge ratios (1-4) on the extraction performance were investigated. SMs and DBBE design enhanced the extraction efficiency by increasing the dispersion of solvent in WSO and enhancing the mixing and mass transfer rates. Results proved that Dowfax was the best SM for oil recovery under various conditions. The best CEA (e.g. MEK and Dowfax) provides the maximum fuel recovery rate of 97% at a period of 20 min, temperature of 60 °C and 4:1 CEA/sludge ratio. The produced fuel was analysed and fed to the distillation process to produce diesel oil. The characteristics of diesel oil were measured, and findings showed that it needs treatment processes prior its use as a finished fuel.

Applying MCM-48 mesoporous material, equilibrium, isotherm, and mechanism for the effective adsorption of 4-nitroaniline from wastewater.

In this work, the MCM-48 mesoporous material was prepared and characterized to apply it as an active adsorbent for the adsorption of 4-nitroaniline (4-Nitrobenzenamine) from wastewater. The MCM-48 characterizations were specified by implementing various techniques such as; scanning electron microscopy (SEM), Energy dispersive X-ray analysis (EDAX), X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) surface area, pore size distribution (PSD), and Fourier transform infrared (FTIR). The batch adsorption results showed that the MCM-48 was very active for the 4-nitroaniline adsorption from wastewater. The adsorption equilibrium results were analyzed by applying isotherms like Langmuir, Freundlich, and Temkin. The maximum experimental uptake according to type I Langmuir adsorption was found to be 90 mg g-1 approximately. The Langmuir model with determination coefficient R2 = 0.9965 is superior than the Freundlich model R2 = 0.99628 and Temkin model R2 = 0.9834. The kinetic adsorption was investigated according to pseudo 1st order, pseudo 2nd order, and Intraparticle diffusion model. The kinetic results demonstrated that the regression coefficients are so high R2 = 0.9949, that mean the pseudo 2nd order hypothesis for the adsorption mechanism process appears to be well-supported. The findings of adsorption isotherms and kinetics studies indicate the adsorption mechanism is a chemisorption and physical adsorption process.

Application of Functionalized Fe3O4 Magnetic Nanoparticles Using CTAB and SDS for Oil Separation from Oil-in-Water Nanoemulsions.

Using magnetic nanoparticles (MNPs) for emulsified oil separation from wastewater is becoming increasingly widespread. This study aims to synthesize MNPs using amphiphilic coatings to stabilize the MNPs and prevent their agglomeration for efficiently breaking oil-in-water nanoemulsions. We coat two different sizes of Fe3O4 nanoparticles (15-20 and 50-100 nm) using cetyltrimethylammonium bromide (CTAB) and sodium dodecyl sulfate (SDS) with surfactant-to-MNP mass ratios of 0.4 and 0.8. We study the effect of various variables on the demulsification performance, including the MNP size and concentration, coating materials, and MNP loading. Based on the oil-water separation analysis, the smaller size MNPs (MNP-S) show a better demulsification performance than the larger ones (MNP-L ) for a 1000 ppm dodecane-in-water emulsion containing nanosized oil droplets (250-300 nm). For smaller MNPs (MNP-S) and at low dosage level of 0.5 g/L, functionalizing with surfactant-to-MNP mass ratio of 0.4, the functionalization increases the separation efficiency (SE) from 57.5% for bare MNP-S to 86.1% and 99.8 for the SDS and CTAB coatings, respectively. The highest SE for MNP-S@CTAB and the zeta potential measurements imply that electrostatic attraction between negatively charged oil droplets (-55.9 ± 2.44 mV) and positively charged MNP-S@CTAB (+35.8 ± 0.34 mV) is the major contributor to a high SE. Furthermore, the reusability tests for MNP-S@CTAB reveal that after 10 cycles, the amount of oil adsorption capacity decreases slightly, from 20 to 19 mg/g, indicating an excellent stability of synthesized nanoparticles. In conclusion, functionalized MNPs with tailored functional groups feature a high oil SE that could be effectively used for oil separation from emulsified oily wastewater streams.