Assessing cationic dye adsorption mechanisms on MIL-53 (Al) nanostructured MOF materials using quantum chemical and molecular simulations: Toward environmentally sustainable wastewater treatment

Salahshoori, Iman; Jorabchi, Majid Namayandeh; Ghasemi, Somayeh; Mirnezami, Seyedeh Masoomeh Sadat; Nobre, Marcos Augusto Lima; Khonakdar, Hossein Ali

doi:10.1016/j.jwpe.2023.104081

Cited by 30 publications

(9 citation statements)

References 105 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The adsorption mechanism of an MOF for dye removal can be explained with different interactions, including electrostatic forces, hydrogen bonding, and van der Waals forces. 30 Dye molecules can penetrate the pores of an MOF's structure, thereby allowing for higher adsorption capacity, and can be engineered to be selective for specific dyes or classes of dyes (for a summary of dye removal performance of various MOF adsorbents, 31 see Table S1). Colorimetric methods and UV−vis spectroscopy are two approaches that may be employed to determine the amount of dye present in the wastewater.…”

Section: Using Mofsmentioning

confidence: 99%

“…When MOFs come into contact with a dye-contaminated solution, they readily adsorb dye molecules within a few minutes. The adsorption mechanism of an MOF for dye removal can be explained with different interactions, including electrostatic forces, hydrogen bonding, and van der Waals forces . Dye molecules can penetrate the pores of an MOF’s structure, thereby allowing for higher adsorption capacity, and can be engineered to be selective for specific dyes or classes of dyes (for a summary of dye removal performance of various MOF adsorbents, see Table S1).…”

Section: Treatment Of Organic Contaminants Using Mofsmentioning

confidence: 99%

See 1 more Smart Citation

Recent Development of Metal–Organic Frameworks for Water Purification

El-Sewify,

2024

Langmuir

View full text Add to dashboard Cite

Water contamination is an increasing concern to mankind because of the increasing amount of pollutants in aquatic ecosystems. To purify the polluted water, various techniques have been used to remove hazardous components. Unfortunately, traditional cleanup techniques with a low uptake capacity are unable to achieve water purification. Metal−organic frameworks (MOFs) have recently shown potential in effective water pollutant isolation in terms of selectivity and adsorption capacity over traditional porous materials. The high surface area and versatile functionality of MOFs allow for the development of new adsorbents. The development of MOFs in a range of water treatments in the recent five years will be highlighted in this review, along with assessments of the adsorption performance relevant to the particular task. Moreover, the outlook on future opportunities for water purification using MOFs is also provided.

show abstract

Section: Using Mofsmentioning

confidence: 99%

Section: Treatment Of Organic Contaminants Using Mofsmentioning

confidence: 99%

Recent Development of Metal–Organic Frameworks for Water Purification

El-Sewify,

2024

Langmuir

View full text Add to dashboard Cite

show abstract

“…Addressing water pollution is crucial for environmental justice, combating climate change, and sustaining a healthy future 15 – 18 . Pollutants such as organic compounds, pharmaceuticals, and chemicals harm aquatic life and water quality, highlighting the need for effective management and regulation to protect both the environment and human health 19 – 24 .…”

Section: Introductionmentioning

confidence: 99%

Machine learning-powered estimation of malachite green photocatalytic degradation with NML-BiFeO3 composites

Salahshoori,

Yazdanbakhsh,

Baghban

2024

Sci Rep

Self Cite

View full text Add to dashboard Cite

This study explores the potential of photocatalytic degradation using novel NML-BiFeO3 (noble metal-incorporated bismuth ferrite) compounds for eliminating malachite green (MG) dye from wastewater. The effectiveness of various Gaussian process regression (GPR) models in predicting MG degradation is investigated. Four GPR models (Matern, Exponential, Squared Exponential, and Rational Quadratic) were employed to analyze a dataset of 1200 observations encompassing various experimental conditions. The models have considered ten input variables, including catalyst properties, solution characteristics, and operational parameters. The Exponential kernel-based GPR model achieved the best performance, with a near-perfect R2 value of 1.0, indicating exceptional accuracy in predicting MG degradation. Sensitivity analysis revealed process time as the most critical factor influencing MG degradation, followed by pore volume, catalyst loading, light intensity, catalyst type, pH, anion type, surface area, and humic acid concentration. This highlights the complex interplay between these factors in the degradation process. The reliability of the models was confirmed by outlier detection using William’s plot, demonstrating a minimal number of outliers (66–71 data points depending on the model). This indicates the robustness of the data utilized for model development. This study suggests that NML-BiFeO3 composites hold promise for wastewater treatment and that GPR models, particularly Matern-GPR, offer a powerful tool for predicting MG degradation. Identifying fundamental catalyst properties can expedite the application of NML-BiFeO3, leading to optimized wastewater treatment processes. Overall, this study provides valuable insights into using NML-BiFeO3 compounds and machine learning for efficient MG removal from wastewater.

show abstract

“…Traditional pharmaceutical waste disposal methods, relying on experimental approaches, can be laborious and costly. Computational methodologies offer efficient alternatives, such as molecular simulation. − These tools predict adsorption processes, assess efficacy against pollutants, and expedite the adsorbent discovery, providing invaluable insights for environmental reparation. − Molecular simulation empowers researchers in the field of pharmaceutical pollutant removal to develop effective adsorbents and investigate their adsorption and physicochemical properties with incredible precision, paving the way for improved environmental remediation strategies and verifying experimental findings. ,− Salahshoori et al utilized carboxylic acid-functionalized MIL-53 (Al) for removing pharmaceutical pollutants through molecular simulations. Functionalization improved the adsorption affinity, demonstrating the potential of such MOFs as promising solutions for pollutant removal.…”

Section: Introductionmentioning

confidence: 99%

Molecular Simulation Studies of Pharmaceutical Pollutant Removal (Rosuvastatin and Simvastatin) Using Novel Modified-MOF Nanostructures (UIO-66, UIO-66/Chitosan, and UIO-66/Oxidized Chitosan)

Salahshoori,

Vaziri,

Jahanmardi

et al. 2024

ACS Appl. Mater. Interfaces

Self Cite

View full text Add to dashboard Cite

The ubiquitous presence of pharmaceutical pollutants in the environment significantly threatens human health and aquatic ecosystems. Conventional wastewater treatment processes often fall short of effectively removing these emerging contaminants. Therefore, the development of high-performance adsorbents is crucial for environmental remediation. This research utilizes molecular simulation to explore the potential of novel modified metal–organic frameworks (MOFs) in pharmaceutical pollutant removal, paving the way for the design of efficient wastewater treatment strategies. Utilizing UIO-66, a robust MOF, as the base material, we developed UIO-66 functionalized with chitosan (CHI) and oxidized chitosan (OCHI). These modified MOFs’ physical and chemical properties were first investigated through various characterization techniques. Subsequently, molecular dynamics simulation (MDS) and Monte Carlo simulation (MCS) were employed to elucidate the adsorption mechanisms of rosuvastatin (ROSU) and simvastatin (SIMV), two prevalent pharmaceutical pollutants, onto these nanostructures. MCS calculations demonstrated a significant enhancement in the adsorption energy by incorporating CHI and OCHI into UIO-66. This increased ROSU from −14,522 to −16,459 kcal/mol and SIMV from −17,652 to −21,207 kcal/mol. Moreover, MDS reveals ROSU rejection rates in neat UIO-66 to be at 40%, rising to 60 and 70% with CHI and OCHI. Accumulation rates increase from 4 Å in UIO-66 to 6 and 9 Å in UIO-CHI and UIO-OCHI. Concentration analysis shows SIMV rejection surges from 50 to 90%, with accumulation rates increasing from 6 to 11 Å with CHI and OCHI in UIO-66. Functionalizing UIO-66 with CHI and OCHI significantly enhanced the adsorption capacity and selectivity for ROSU and SIMV. Abundant hydroxyl and amino groups facilitated strong interactions, improving performance over that of unmodified UIO-66. Surface functionalization plays a vital role in customizing the MOFs for pharmaceutical pollutant removal. These insights guide next-gen adsorbent development, offering high efficiency and selectivity for wastewater treatment.

show abstract

Assessing cationic dye adsorption mechanisms on MIL-53 (Al) nanostructured MOF materials using quantum chemical and molecular simulations: Toward environmentally sustainable wastewater treatment

Cited by 30 publications

References 105 publications

Recent Development of Metal–Organic Frameworks for Water Purification

Recent Development of Metal–Organic Frameworks for Water Purification

Machine learning-powered estimation of malachite green photocatalytic degradation with NML-BiFeO3 composites

Molecular Simulation Studies of Pharmaceutical Pollutant Removal (Rosuvastatin and Simvastatin) Using Novel Modified-MOF Nanostructures (UIO-66, UIO-66/Chitosan, and UIO-66/Oxidized Chitosan)

Contact Info

Product

Resources

About