Facile and scalable preparation of ZIF-67 decorated cotton fibers as recoverable and efficient adsorbents for removal of malachite green

AbstractRecently, metal–organic frameworks (MOFs) have received considerable attention as highly efficient adsorbents for dye wastewater remediation. However, the immobilization of MOFs on the substrate surfaces to fabricate easy recyclable adsorbents via a facile route is still a challenge. In this work, ZIF-67/cotton fibers as adsorbents for dye removal were prepared in a large-scale using a simple coordination replication method. The successful fabrication of the ZIF-67/cotton fibers was confirmed by FTIR, XRD, XPS, SEM and BET analysis, respectively. As expected, the as-prepared ZIF-67/cotton fibers exhibited high adsorption capacity of 3787 mg/g towards malachite green (MG). Meanwhile, the adsorption kinetics and isotherm obeyed the pseudo-second-order kinetics and Langmuir model, respectively. Moreover, its removal efficiency towards MG was not significantly influenced by the pH and ionic strength of aqueous solution. Most importantly, the ZIF-67/cotton fibers can remove MG from synthetic effluents, and it can be easily regenerated without filtration or centrifugation processes, with the regeneration efficiency remaining over 90% even after 10 cycles. Additionally, the ZIF-67/cotton fibers presented excellent antimicrobial performance against E. coli and S. aureus. Hence, the distinctive features of the as-prepared ZIF-67/cotton fibers make it promisingly applicable for the colored wastewater treatment.

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Scalable Sulfonate-Coated Cotton Fibers as Facile Recyclable and Biodegradable Adsorbents for Highly Efficient Removal of Cationic Dyes

10.21203/rs.3.rs-1148558/v1 ◽

2021 ◽

Author(s):

Linhua Li ◽

Baojie Dou ◽

Jianwu Lan ◽

Jiaojiao Shang ◽

Yafang Wang ◽

...

Keyword(s):

Adsorption Capacity ◽

Large Scale ◽

Ph Value ◽

Cationic Dyes ◽

Cotton Fibers ◽

Wastewater Remediation ◽

Efficient Removal ◽

Adsorption Sites ◽

Highly Efficient ◽

Coated Cotton

Abstract Adsorbents with superior adsorption capacity and facile recyclability are viewed as promising materials for dye wastewater treatment. In this work, a novel sulfonate decorated cotton fiber as a biodegradable and recyclable adsorbent was fabricated for highly efficient removal of cationic dyes. Herein, the poly(sodium p-styrenesulfonate-co-N-methylol acrylamide) (P(SSNa-co-NMAM)) with SSNa units as adsorption sites and NMAM units as thermal-crosslinking points was synthesized for modification of cotton fibers in a large scale at high temperature (160 oC). The various characterization investigations confirmed the successful construction of the P(SSNa-co-NMAM) coated cotton fibers (PCF). As expected, the as-obtained adsorbent presented outstanding adsorption performance toward cationic dyes in the both static and dynamic states, even in the synthetic effluent. The adsorption processes of cationic dyes onto the PCF were well fitted by the Langmuir isotherm model and Pseudo-second-order kinetics, respectively. The thermodynamics study showed that the adsorption reaction of the cationic dyes onto PCF was a spontaneous and endothermic process. The maximum adsorption capacities of PCF toward MEB, RhB and MG were 3976.10, 2879.80 and 3071.55 mg/g, respectively. The responsible adsorption of dyes ontothe PCF was electrostatic interaction. Moreover, the adsorption capacity of PCF toward cationic dyes was slight influenced by pH value of solution, because of the stable feature of sulfonate moiety in acid and alkali. In addition, the as-prepared PCF exhibited satisfactory recyclability and reusability. Given the aforementioned results, the as-obtained PCF is a promising adsorbent with great potential for practical application in the dye-contaminated wastewater remediation.

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Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model

10.26434/chemrxiv.9894224.v1 ◽

2019 ◽

Author(s):

Ryther Anderson ◽

Achay Biong ◽

Diego Gómez-Gualdrón

Keyword(s):

Neural Network ◽

Machine Learning ◽

Molecular Simulation ◽

Large Scale ◽

Learning Model ◽

Operating Conditions ◽

Small Subset ◽

Screening Methods ◽

Large Set ◽

Metal Organic

<div>Tailoring the structure and chemistry of metal-organic frameworks (MOFs) enables the manipulation of their adsorption properties to suit specific energy and environmental applications. As there are millions of possible MOFs (with tens of thousands already synthesized), molecular simulation, such as grand canonical Monte Carlo (GCMC), has frequently been used to rapidly evaluate the adsorption performance of a large set of MOFs. This allows subsequent experiments to focus only on a small subset of the most promising MOFs. In many instances, however, even molecular simulation becomes prohibitively time consuming, underscoring the need for alternative screening methods, such as machine learning, to precede molecular simulation efforts. In this study, as a proof of concept, we trained a neural network as the first example of a machine learning model capable of predicting full adsorption isotherms of different molecules not included in the training of the model. To achieve this, we trained our neural network only on alchemical species, represented only by their geometry and force field parameters, and used this neural network to predict the loadings of real adsorbates. We focused on predicting room temperature adsorption of small (one- and two-atom) molecules relevant to chemical separations. Namely, argon, krypton, xenon, methane, ethane, and nitrogen. However, we also observed surprisingly promising predictions for more complex molecules, whose properties are outside the range spanned by the alchemical adsorbates. Prediction accuracies suitable for large-scale screening were achieved using simple MOF (e.g. geometric properties and chemical moieties), and adsorbate (e.g. forcefield parameters and geometry) descriptors. Our results illustrate a new philosophy of training that opens the path towards development of machine learning models that can predict the adsorption loading of any new adsorbate at any new operating conditions in any new MOF.</div>

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Synthesis of Metal Organic Frameworks by Ball-Milling

Crystals ◽

10.3390/cryst11010015 ◽

2020 ◽

Vol 11 (1) ◽

pp. 15

Author(s):

Cheng-An Tao ◽

Jian-Fang Wang

Keyword(s):

Ball Milling ◽

Large Scale ◽

Raw Materials ◽

Metal Organic Frameworks ◽

Research Topic ◽

Mass Ratio ◽

Time Consumption ◽

Metal Organic ◽

Short Time ◽

Made In

Metal-organic frameworks (MOFs) have been used in adsorption, separation, catalysis, sensing, photo/electro/magnetics, and biomedical fields because of their unique periodic pore structure and excellent properties and have become a hot research topic in recent years. Ball milling is a method of small pollution, short time-consumption, and large-scale synthesis of MOFs. In recent years, many important advances have been made. In this paper, the influencing factors of MOFs synthesized by grinding were reviewed systematically from four aspects: auxiliary additives, metal sources, organic linkers, and reaction specific conditions (such as frequency, reaction time, and mass ratio of ball and raw materials). The prospect for the future development of the synthesis of MOFs by grinding was proposed.

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Innovative Polymeric Hybrid Nanocomposites for Application in Photocatalysis

Polymers ◽

10.3390/polym13081184 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1184

Author(s):

Maria Cantarella ◽

Giuliana Impellizzeri ◽

Alessandro Di Mauro ◽

Vittorio Privitera ◽

Sabrina Carola Carroccio

Keyword(s):

Hybrid Systems ◽

Hybrid Materials ◽

Large Scale ◽

Mechanical Stability ◽

Low Cost ◽

Atomic Layer ◽

Hybrid Nanocomposites ◽

Polymeric Nanocomposites ◽

Wastewater Remediation ◽

Antibacterial Performance

The immobilization of inorganic nanomaterials on polymeric substrates has been drawing a lot of attention in recent years owing to the extraordinary properties of the as-obtained materials. The hybrid materials, indeed, combine the benefits of the plastic matter such as flexibility, low-cost, mechanical stability and high durability, with them deriving from their inorganic counterparts. In particular, if the inorganic fillers are nanostructured photocatalysts, the originated hybrid systems will be able to utilize the energy delivered by light, catalysing chemical reactions in a sustainable pathway. Most importantly, since the nanofillers can be ad-hoc anchored to the macromolecular structure, their release in the environment will be prevented, thus overcoming one of the main restrictions that impedes their applications on a large scale. In this review, several typologies of hybrid photocatalytic nanomaterials, obtained by using both organic and inorganic semiconductors and realized with different synthetic protocols, were reported and discussed. In the first part of the manuscript, nanocomposites realized by simply blending the TiO2 or ZnO nanomaterials in thermoplastic polymeric matrices are illustrated. Subsequently, the atomic layer deposition (ALD) technique is presented as an excellent method to formulate polymeric nanocomposites. Successively, some examples of polyporphyrins hybrid systems containing graphene, acting as photocatalysts under visible light irradiation, are discussed. Lastly, photocatalytic polymeric nanosponges, with extraordinary adsorption properties, are shown. All the described materials were deeply characterized and their photocatalytic abilities were evaluated by the degradation of several organic water pollutants such as dyes, phenol, pesticides, drugs, and personal care products. The antibacterial performance was also evaluated for selected systems. The relevance of the obtained results is widely overviewed, opening the route for the application of such multifunctional photocatalytic hybrid materials in wastewater remediation.

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Targeted classification of metal–organic frameworks in the Cambridge structural database (CSD)

Chemical Science ◽

10.1039/d0sc01297a ◽

2020 ◽

Vol 11 (32) ◽

pp. 8373-8387 ◽

Cited By ~ 6

Author(s):

Peyman Z. Moghadam ◽

Aurelia Li ◽

Xiao-Wei Liu ◽

Rocio Bueno-Perez ◽

Shu-Dong Wang ◽

...

Keyword(s):

Surface Chemistry ◽

Specific Surface ◽

Large Scale ◽

Metal Cluster ◽

Metal Organic Frameworks ◽

Cambridge Structural Database ◽

Metal Organic ◽

Structural Database

Large-scale targeted exploration of metal–organic frameworks (MOFs) with characteristics such as specific surface chemistry or metal-cluster family has not been investigated so far.

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