Metal-organic Frameworks For Adsorption Research Articles

Diamino-functionalized metal-organic framework for selective capture of gold ions

Adsorptive recovery of valuable gold (Au) ions from wastes is vital but still challenged, especially regarding adsorption capacity and selectivity. A novel M − 3,5-DABA metal-organic framework (MOF) adsorbent was prepared via anchoring 3,5-diaminobenzoic acid (3,5-DABA) molecule in the MOF-808 matrix. Benefiting from the positive charge property, dense amino groups (3.2 mmol g−1) and high porosity, the adsorption capacity of M − 3,5-DABA reaches 1391.5 mg g−1 (pH = 2.5) and adsorption equilibrium is attained in 5 min. This amino-based material shows excellent selectivity towards various metal ions, evading the poor selectivity problem of classical thiol groups (e.g. for Ag+, Cu2+, Pb2+ and Hg2+ ions). In addition, the regeneration was easily achieved via using a hydrochloric acid-thiourea eluent. Experimental analysis and density functional theory (DFT) calculation show the amino group works as a reductant for Au(III) ions and meanwhile acts as an active site for adsorbing Au(III) ions together with the μ-OH group. Thus, M − 3,5-DABA can act as a potential adsorbent for Au(III) ions, and our work offers a viable strategy to construct novel MOF-based adsorbents.

Adsorption of Humic Acid from Water Using Metal-Organic Frameworks (MOFs): An Effective Removal Strategy

The escalating presence of humic acid (HA) in aquatic systems poses significant ecological and potable water treatment challenges, altering the color, taste, and odor of water and fueling algal blooms that deplete oxygen levels to the detriment of aquatic life. Traditional techniques like coagulation-flocculation, membrane filtration, oxidation fall short in efficiency due to its small fraction of HA, Humic acids (HAs) can interact with various organic and inorganic substances, affecting their characteristics and behavior in water. These interactions can influence the efficiency of water treatment processes like adsorption and coagulation. Specifically, HAs may compete with other contaminants for treatment sites or alter the chemical conditions of the treatment processes, impacting their effectiveness. This thesis confronts the pervasive issue of HA contamination by leveraging the advanced properties of metal-organic frameworks (MOFs). In this work, four representative MOFs are synthesized and well characterized. Then, their capability to enhance coagulation processes in water for HA and HA-kaolin treatment are detailed evaluated. The findings from this research extend beyond academic curiosity, offering actionable insights for water treatment facilities and environmental management agencies. The synthesis of MOFs which are UiO-66(Zr), MIL-100(Fe), ZIF-8, and Al-fum. Each MOFs have been applied to remove HA by adsorption under different condition, effect of contact time, effect of initial pH, effect of adsorbent dosage. After adsorption experiment, MOF samples prepared to dry and went through characterization. Removal of HA by MOF adsorption showed UiO-66(Zr) and MIL-100(Fe) examined shortest reaching equilibrium state with 10-15 min, however, ZIF-8 and Al-fum gradually reached equilibrium state after 60 min. Among various pH conditions, UiO-66(Zr) and MIL-100(Fe) showed the highest adsorption capacity under acidic conditions, while ZIF-8 excelled at neutral pH, and Al-fum exhibited the highest adsorption capacity under both acidic and basic conditions. ZIF-8 has the highest adsorption capacity among the MOFs with capacity of 754 mg/g. MOF after adsorption samples went through characterizations and their remained characteristics indicating the adsorption not affected the structure of the MOFs.

Relay Adsorption in Metal-Organic Frameworks for One-Step Helium Purification at Ambient Temperature.

One-step He purification from natural gas represents a crucial solution for addressing the global He shortages. The prevailing method to produce high-grade He involves cryogenic distillation and ultralow temperature adsorption processes, which is highly cost- and energy-intensive. Separating and purifying He at ambient temperature is a great challenge because the fundamental limitation lies in the boiling point, polarizability, and kinetic diameters of CH4/N2/He gases. In this study, we seek to implement a relay adsorption strategy using Ni(ina)2 and MIL-100(Cr) metal-organic frameworks (MOFs) to produce high-purity He from ternary mixtures (CH4, N2, and He) at ambient temperature. The CH4/He selectivity in Ni(ina)2 and N2/He selectivity in MIL-100(Cr) both reach record 15.39 and 128.49, respectively, making the relay adsorption for helium purification highly efficient. The breakthrough experiments show that the two MOFs can sequentially adsorb CH4 and N2 in ternary mixtures, producing He with a purity of up to 99.99% in one step. The remarkable separation performance and stability of these MOFs underscore the industrial potential in purifying He at ambient temperature.

Two‐Dimensional Copper‐Based Metal‐Organic Framework for Efficient Removal of Methylene Blue from Wastewater

Metal‐organic frameworks (MOFs) can effectively remove methylene blue (MB) from wastewater due to their abundant adsorption sites and multi‐level pores. In this paper, a copper‐based MOF: {[Cu·(L)·(H2O)]·(DMF)}n (1) (H2L = 2‐hydroxyterephthalic acid; DMF = N,N‐dimethylformamide), was synthesized by hydrothermal synthesis method. X‐ray single crystal diffraction showed that a two‐dimensional structure was formed by the carboxyl group of L2‐ in 1 took μ2‐η1：η1 bridged two adjacent Cu(II). In this two‐dimensional structure, the coordinated water molecules and hydroxyl group on L2‐ were distributed on the surface of 1. Thus, it had abundant adsorption sites. The transmission electron microscopy (TEM) of copper‐based MOF nano adsorbent showed that the particle diameter of the nano adsorbent prepared by a cell fragmentation apparatus was about 50 nm. The performance of the copper‐based MOF nano adsorbent in adsorbing MB indicated that the optimal adsorbent dosage was 0.20 g/L and the solution pH was 6. Under the optimal experimental conditions, its maximum adsorption capacity for MB was 143.3 mg/g, which was superior to most MOFs adsorbents. The adsorption thermodynamic analysis showed that the copper‐based MOF nano adsorbent at 25 ‐ 45 ℃ was an exothermic (△H < 0) , and spontaneous (△G < 0) process.

Linear regression model for metal–organic frameworks with CO2 adsorption based on topological data analysis

Metal–organic frameworks (MOFs), self-assembled porous materials synthesized from metal ions and organic ligands, are promising candidates for the direct capture of CO2 from the atmosphere. In this work, we developed a regression model to predict the optimal component of the MOF that governs the amount of CO2 adsorption per volume based on experimentally observed adsorption and structure data combined with MOF adsorption sites. The structural descriptors were generated by topological data analysis with persistence diagrams, an advanced mathematical method for quantifying the rings and cavities within the MOF. This enables us to analyze direct effects and significance of the geometric structure of the MOF on the efficiency of CO2 adsorption in a novel way. The proposed approach is proved to be highly correlated with experimental data and thus offers an effective screening tool for MOFs with optimized structures.

Topology Reconfiguration of Anion-Pillared Metal-Organic Framework from Flexibility to Rigidity for Enhanced Acetylene Separation.

Flexible metal-organic framework (MOF) adsorbents commonly encounter limitations in removing trace impurities below gate-opening threshold pressures. Topology reconfiguration can fundamentally eliminate intrinsic structural flexibility, yet remains a formidable challenge and is rarely achieved in practical applications. Herein, a solvent-mediated approach is presented to regulate the flexible CuSnF6-dpds-sql (dpds = 4,4''-dipyridyldisulfide) with sql topology into rigid CuSnF6-dpds-cds with cds topology. Notably, the cds topology is unprecedented and first obtained in anion-pillared MOF materials. As a result, rigid CuSnF6-dpds-cds exhibits enhanced C2H2 adsorption capacity of 48.61 cm3 g-1 at 0.01bar compared to flexible CuSnF6-dpds-sql (21.06 cm3 g-1). The topology transformation also facilitates the adsorption kinetics for C2H2, exhibiting a 6.5-fold enhanced diffusion time constant (D/r2) of 1.71 × 10-3 s-1 on CuSnF6-dpds-cds than that of CuSnF6-dpds-sql (2.64 × 10-4 s-1). Multiple computational simulations reveal the structural transformations and guest-host interactions in both adsorbents. Furthermore, dynamic breakthrough experiments demonstrate that high-purity C2H4 (>99.996%) effluent with a productivity of 93.9mmol g-1 can be directly collected from C2H2/C2H4 (1/99, v/v) gas-mixture in a single CuSnF6-dpds-cds column.

Combining computational screening and machine learning to explore MOFs and COFs for methane purification

Metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) have great potential to be used as porous adsorbents and membranes to achieve high-performance methane purification. Although the continuous increase in the number and diversity of MOFs and COFs is a great opportunity for the discovery of novel adsorbents and membranes with superior performances, evaluating such a vast number of materials in the quickest and most effective manner requires the development of computational approaches. High-throughput computational screening based on molecular simulations has been extensively used to identify the most promising MOFs and COFs for methane purification. However, the enormous and ever-growing material space necessitates more efficient approaches in terms of time and effort. Combining data science with molecular simulations has recently accelerated the discovery of optimal MOF and COF materials for methane purification and revealed the hidden structure–performance relationships. In this perspective, we highlighted the recent developments in combining high-throughput molecular simulations and machine learning to accurately identify the most promising MOF and COF adsorbents and membranes among thousands of candidates for separating methane from other gases including acetylene, carbon dioxide, helium, hydrogen, and nitrogen. After providing a brief overview of the topic, we reviewed the pioneering contributions in the field and discussed the current opportunities and challenges that we need to direct our efforts for the design and discovery of adsorbent and membrane materials.

Efficient Modeling of Water Adsorption in MOFs Using Interpolated Transition Matrix Monte Carlo.

With the specter of accelerating climate change, securing access to potable water has become a critical global challenge. Atmospheric water harvesting (AWH) through metal-organic frameworks (MOFs) emerges as one of the promising solutions. The standard numerical methods applied for rapid and efficient screening for optimal sorbents face significant limitations in the case of water adsorption (slow convergence and inability to overcome high energy barriers). To address these challenges, we employed grand canonical transition matrix Monte Carlo (GC-TMMC) methodology and proposed an efficient interpolation scheme that significantly reduces the number of required simulations while maintaining accuracy of the results. Through the example of water adsorption in three MOFs: MOF-303, MOF-LA2-1, and NU-1000, we show that the extrapolation of the free energy landscape allows for prediction of the adsorption properties over a continuous range of pressure and temperature. This innovative and versatile method provides rich thermodynamic information, enabling rapid, large-scale computational screening of sorbents for adsorption, applicable for a variety of sorbents and gases. As the presented methodology holds strong applicative potential, we provide alongside this paper a modified version of the RASPA2 code with a ghost swap move implementation and a Python library designed to minimize the user's input for analyzing data derived from the TMMC simulations.

Flat-Histogram Monte Carlo Simulation of Water Adsorption in Metal-Organic Frameworks.

Molecular simulations of water adsorption in porous materials often converge slowly due to sampling bottlenecks that follow from hydrogen bonding and, in many cases, the formation of water clusters. These effects may be exacerbated in metal-organic framework (MOF) adsorbents, due to the presence of pore spaces (cages) that promote the formation of discrete-size clusters and hydrophobic effects (if present), among other reasons. In Grand Canonical Monte Carlo (MC) simulations, these sampling challenges are typically manifested by low MC acceptance ratios, a tendency for the simulation to become stuck in a particular loading state (i.e., macrostates), and the persistence of specific clusters for long periods of the simulation. We present simulation strategies to address these sampling challenges, by applying flat-histogram MC (FHMC) methods and specialized MC move types to simulations of water adsorption. FHMC, in both Transition-matrix and Wang-Landau forms, drives the simulation to sample relevant macrostates by incorporating weights that are self-consistently adjusted throughout the simulation and generate the macrostate probability distribution (MPD). Specialized MC moves, based on aggregation-volume bias and configurational bias methods, separately address low acceptance ratios for basic MC trial moves and specifically target water molecules in clusters; in turn, the specialized MC moves improve the efficiency of generating new configurations which is ultimately reflected in improved statistics collected by FHMC. The combined strategies are applied to study the adsorption of water in CuBTC and ZIF-8 at 300 K, through examination of the MPD and the adsorption isotherm generated by histogram reweighting. A key result is the appearance of nontrivial oscillations in the MPD, which we show to be associated with water clusters in the adsorption system. Additionally, we show that the probabilities of certain clusters become similar in value near the boundaries of the isotherm hysteresis loop, indicating a strong connection between cluster formation/destruction and the thermodynamic limits of stability. For a hydrophobic MOF, the FHMC results show that the phase transition from low density to high density is suppressed to water pressure far above the bulk-fluid saturation pressure; this is consistent with results presented elsewhere. We also compare our FHMC simulation isotherm to one measured by a different technique but with ostensibly the same molecular interactions and comment on observed differences and the need for follow-up work. The simulation strategies presented here can be applied to the simulation of water in other MOFs using heuristic guidelines laid out in our text, which should facilitate the more consistent and efficient simulation of water adsorption in porous materials in future applications.

Data-Driven Discovery of Gas-Selective Organic Linkers in Metal-Organic Frameworks for the Separation of Ethylene and Ethane.

Metal-organic frameworks (MOFs) are potential candidates for gas-selective adsorbents for the separation of an ethylene/ethane mixture. To accelerate material discovery, high-throughput computational screening is a viable solution. However, classical force fields, which were widely employed in recent studies of MOF adsorbents, have been criticized for their failure to cover complicated interactions such as those involving π electrons. Herein, we demonstrate that machine learning force fields (MLFFs) trained on quantum-chemical reference data can overcome this difficulty. We have constructed a MLFF to accurately predict the adsorption energies of ethylene and ethane on the organic linkers of MOFs and discovered that the π electrons from both the ethylene molecule and the aromatic rings in the linkers could substantially influence the selectivity for gas adsorption. Four kinds of MOF linkers are identified as having promise for the separation of ethylene and ethane, and our results could also offer a new perspective on the design of MOF building blocks for diverse applications.

Optimizing Trace Acetylene Removal from Acetylene/Ethylene Mixture in a Flexible Metal-Organic Framework by Crystal Downsizing.

Improving the gas separation performance of metal-organic frameworks (MOFs) by crystal downsizing is an important but often overlooked issue. Here, we report three different-sized flexible ZUL-520 MOFs (according to the crystal size from large to small, the three samples are, respectively, named ZUL-520-0, ZUL-520-1, and ZUL-520-2) with the same chemical structure for optimizing trace acetylene (C2H2) removal from acetylene/ethylene (C2H2/C2H4) mixture. The three differently sized activated ZUL-520 (denoted as ZUL-520a) exhibited almost identical C2H2 uptake of 4.8 mmol/g at 100 kPa, while the C2H2 uptake at 1 kPa increased with a downsizing crystal. The C2H2 uptake of activated ZUL-520-2 (denoted as ZUL-520-2a) at 1 kPa was ∼55% higher than that of activated ZUL-520-0 (denoted as ZUL-520-0a). The adsorption isotherms and adsorption kinetics validated that gas adsorptive separation is governed not only by adsorption thermodynamics but also by adsorption kinetics. In addition, all three different-sized ZUL-520a MOFs showed high C2H2/C2H4 selectivity. Grand canonical Monte Carlo (GCMC) simulations and dispersion-corrected density functional theory (DFT-D) computations illustrated a plausible mechanism of C2H2 adsorption in MOFs. Importantly, breakthrough experiments demonstrated that ZUL-520a can effectively separate the C2H2/C2H4 (1/99, v/v) mixture and the C2H4 productivity obtained by ZUL-520-2a was much higher than that by ZUL-520-0a. Our work may provide an easy but powerful strategy for upgrading the performance of gas adsorptive separation in MOFs.

Improving gas adsorption modeling for MOFs by local calibration of Hubbard U parameters.

While computational screening with density functional theory (DFT) is frequently employed for the screening of metal-organic frameworks (MOFs) for gas separation and storage, commonly applied generalized gradient approximations (GGAs) exhibit self-interaction errors, which hinder the predictions of adsorption energies. We investigate the Hubbard U parameter to augment DFT calculations for full periodic MOFs, targeting a more precise modeling of gas molecule-MOF interactions, specifically for N2, CO2, and O2. We introduce a calibration scheme for the U parameter, which is tailored for each MOF, by leveraging higher-level calculations on the secondary building unit (SBU) of the MOF. When applied to the full periodic MOF, the U parameter calibrated against hybrid HSE06 calculations of SBUs successfully reproduces hybrid-quality calculations of the adsorption energy of the periodic MOF. The mean absolute deviation of adsorption energies reduces from 0.13eV for a standard GGA treatment to 0.06eV with the calibrated U, demonstrating the utility of the calibration procedure when applied to the full MOF structure. Furthermore, attempting to use coupled cluster singles and doubles with perturbative triples calculations of isolated SBUs for this calibration procedure shows varying degrees of success in predicting the experimental heat of adsorption. It improves accuracy for N2 adsorption for cases of overbinding, whereas its impact on CO2 is minimal, and ambiguities in spin state assignment hinder consistent improvements of O2 adsorption. Our findings emphasize the limitations of cluster models and advocate the use of full periodic MOF systems with a calibrated U parameter, providing a more comprehensive understanding of gas adsorption in MOFs.

Programmable Water Sorption through Linker Installation into a Zirconium Metal-Organic Framework.

Hydrolytically stable materials exhibiting a wide range of programmable water sorption behaviors are crucial for on-demand water sorption systems. While notable advancements in employing metal-organic frameworks (MOFs) as promising water adsorbents have been made, developing a robust yet easily tailorable MOF scaffold for specific operational conditions remains a challenge. To address this demand, we employed a topology-guided linker installation strategy using NU-600, which is a zirconium-based MOF (Zr-MOF) that contains three vacant crystallographically defined coordination sites. Through a judicious selection of three N-heterocyclic auxiliary linkers of specific lengths, we installed them into designated sites, giving rise to six new MOFs bearing different combinations of linkers in predetermined positions. The resulting MOFs, denoted as NU-606 to NU-611, demonstrate enhanced structural stability against capillary force-driven channel collapse during water desorption due to the increased connectivity of the Zr6 clusters in the resulting MOFs. Furthermore, incorporating these auxiliary linkers with various hydrophilic N sites enables the systematic modulation of the pore-filling pressure from about 55% relative humidity (RH) for the parent NU-600 down to below 40% RH. This topology-driven linker installation strategy offers precise control of water sorption properties for MOFs, highlighting a facile route to design MOF adsorbents for use in water sorption applications.

Tunning MIL-101(Cr) MOF polymorphism towards efficient adsorption and localized Fenton-like degradation of para-nitroaniline by Fe incorporation

The employment of metal–organic frameworks (MOFs) in the context of eliminating organic contaminants from water has garnered significant interest in contemporary research. This study investigated the impact of varying quantities of iron on the MIL-101(Cr) adsorbent. For the first time, a polymorphic Cr/Fe-MOF was utilized for the adsorption and localized Fenton-like degradation of p-nitroaniline (PNA). Importantly, the Fe centers exhibited a ternary role of (i) transforming MIL-101 into MIL-53lt morphology, (ii) boosting PNA adsorption on the MIL(Cr) material, and (iii) enabling the Fenton-like decomposition of the adsorbed PNA in reduced solution volume. Cr:Fe(50:50) exhibited the highest adsorption capacity of 378.9 mg/g, notwithstanding its smaller surface area (SBET = 8.9 m2/g). Overall, adsorption kinetics and isotherms correlated better with pseudo-second-order and Langmuir models, respectively. The adsorption mechanism was attributed to breathing effect, H-bonding and π-π interaction. Besides, PNA degradation kinetics stood at 0.21 min−1, and the reactive oxygen species were identified as •OH, •O2– and 1O2. During continuous removal of PNA, the Cr:Fe(50:50) MOF immobilized onto cotton met the environmental discharge standard (1 mg/L) up to 52 bed volumes (initial P = 10.0 mg/L at 1 mL/min). This study not only presents a superior polymorphic MOF adsorbent but also promotes the fabrication of localized Fenton-like catalysts for the removal of organic contaminants in wastewater.

High-throughput computational screening of MOF adsorbents for efficient propane capture from air and natural gas mixtures.

In this study, we used a high-throughput computational screening approach to examine the potential of metal-organic frameworks (MOFs) for capturing propane (C3H8) from different gas mixtures. We focused on Quantum MOF (QMOF) database composed of both synthesized and hypothetical MOFs and performed Grand Canonical Monte Carlo (GCMC) simulations to compute C3H8/N2/O2/Ar and C3H8/C2H6/CH4 mixture adsorption properties of MOFs. The separation of C3H8 from air mixture and the simultaneous separation of C3H8 and C2H6 from CH4 were studied for six different adsorption-based processes at various temperatures and pressures, including vacuum-swing adsorption (VSA), pressure-swing adsorption (PSA), vacuum-temperature swing adsorption (VTSA), and pressure-temperature swing adsorption (PTSA). The results of molecular simulations were used to evaluate the MOF adsorbents and the type of separation processes based on selectivity, working capacity, adsorbent performance score, and regenerability. Our results showed that VTSA is the most effective process since many MOFs offer high regenerability (>90%) combined with high C3H8 selectivity (>7 × 103) and high C2H6 + C3H8 selectivity (>100) for C3H8 capture from air and natural gas mixtures, respectively. Analysis of the top MOFs revealed that materials with narrow pores (<10Å) and low porosities (<0.7), having aromatic ring linkers, alumina or zinc metal nodes, typically exhibit a superior C3H8 separation performance. The top MOFs were shown to outperform commercial zeolite, MFI for C3H8 capture from air, and several well-known MOFs for C3H8 capture from natural gas stream. These results will direct the experimental efforts to the most efficient C3H8 capture processes by providing key molecular insights into selecting the most useful adsorbents.

Deep learning and big data mining for Metal–Organic frameworks with high performance for simultaneous desulfurization and carbon capture

Carbon capture and desulfurization of flue gases are crucial for the achievement of carbon neutrality and sustainable development. In this work, the “one-step” adsorption technology with high-performance metal–organic frameworks (MOFs) was proposed to simultaneously capture the SO2 and CO2. Four machine learning algorithms were used to predict the performance indicators (NCO2+SO2, SCO2+SO2/N2, and TSN) of MOFs, with Multi-Layer Perceptron Regression (MLPR) showing better performance (R2 = 0.93). To address sparse data of MOF chemical descriptors, we introduced the Deep Factorization Machines (DeepFM) model, outperforming MLPR with a higher R2 of 0.95. Then, sensitivity analysis was employed to find that the adsorption heat and porosity were the key factors for SO2 and CO2 capture performance of MOF, while the influence of open alkali metal sites also stood out. Furthermore, we established a kinetic model to batch simulate the breakthrough curves of TOP 1000 MOFs to investigate their dynamic adsorption separation performance for SO2/CO2/N2. The TOP 20 MOFs screened by the dynamic performance highly overlap with those screened by the static performance, with 76 % containing open alkali metal sites. This integrated approach of computational screening, machine learning, and dynamic analysis significantly advances the development of efficient MOF adsorbents for flue gas treatment.

Thiadiazole-Functionalized Th/Zr-UiO-66 for Efficient C2H2/CO2 Separation.

Adsorptive separation technology provides an effective approach for separating gases with similar physicochemical properties, such as the purification of acetylene (C2H2) from carbon dioxide (CO2). The high designability and tunability of metal-organic framework (MOF) adsorbents make them ideal design platforms for this challenging separation. Herein, we employ an isoreticular functionalization strategy to fine-tune the pore environment of Zr- and Th-based UiO-66 by the immobilization of the benzothiadiazole group via bottom-up synthesis. The functionalized UPC-120 exhibits an enhanced C2H2/CO2 separation performance, which is confirmed by adsorption isotherms, dynamic breakthrough curves, and theoretical simulations. The synergy of ligand functionalization and metal ion fine-tuning guided by isoreticular chemistry provides a new perspective for the design and development of adsorbents for challenging gas separation processes.

Development and application of a new deep eutectic solvent based magnetic metal–organic framework adsorbent for the detection of fluorotelomer alcohols in edible oils

The enrichment of per- and polyfluoroalkyl substances (PFASs) poses significant challenges for environmental and food safety monitoring, given their toxic and persistent nature, highly fluorinated character, and low concentration. This study focuses on the construction of a new deep eutectic solvent (DES)-functionalized magnetic metal–organic framework (MOF) adsorbent for fluorotelomer alcohols (FTOHs) analysis in foods. The DES, composed of levulinic acid and trifluoromethoxylbenzene, was modified onto the surface of magnetic UiO-66-NH2 to enable the specific adsorption of FTOHs during the pretreatment process, which was then followed by GC–MS analysis. The method exhibited a limit of detection (LOD) ranging from 31.51 to 185.76 pg g – 1 with satisfactory recoveries (73.83 %-128.55 %), and was successfully used in detecting FTOHs in 12 edible oils samples with the concentrations ranging from 401.89 to 8006.18 pg g − 1. The proposed adsorbent exhibited significantly improved enrichment performance for PFASs, primarily attributed to the cooperative enhancement of double hydrogen-bonding interactions and fluorine affinity via the elucidation of 1H nuclear magnetic resonance (1H NMR), 19F NMR, and quantum chemical calculations. This study provided new insights and directions for the design and fabrication of selective materials to pretreatment ultra-trace emerging contaminants in complex matrices.

In Situ Synthesis of NH2-MIL-53-Al/PAN Nanofibers for Removal Co(II) through an Electrospinning Process.

In this study, researchers developed a novel composite material called NH2-MIL-53-Al/PAN, which consists of metal-organic frameworks (MOFs) grown on electrospun PAN nanofibers (NFs). The successful formation of the composite was confirmed by X-ray diffraction (XRD) and Fourier transform infrared (FTIR), and the hydrophilicity of NH2-MIL-53-Al/PAN was demonstrated by the water contact angle (WCA). Batch experiments were conducted to investigate the adsorption performance of Co(II) under different conditions. The maximum adsorption capacity reached 58.72 mg/g, and almost 95% of the adsorption was achieved within the first 6 h. The adsorption process was found to be spontaneous and endothermic and followed the pseudo-second-order kinetics and Langmuir models. Chemisorption and molecular layer adsorption are the main mechanisms of adsorption, and X-ray photoelectron spectroscopy (XPS) analysis further reveals that the interaction between the adsorbent and cobalt is a coordination interaction. In this study, NH2-MIL-53-Al was grown in situ on PAN to ensure effective loading of MOFs and prevent agglomeration during the NF mixing process. This approach successfully addressed the challenge of exposing active sites within the embedded MOF crystals. Additionally, it overcame the difficulty of recycling traditional MOF adsorbents. As a result, the exceptional performance of MOF NFs offers a promising solution for the efficient removal of cobalt-containing wastewater.

Novel Zr-based MOF with Ortho-hydroxyl group selectively traps germanium from aqueous media

Recovery of Ge(IV) from solution is of increasing interest. A novel metal–organic framework adsorbent (Ma-Zr-MOF) is synthesized using mucic acid. A series of characterizations prove the successful synthesis of Ma-Zr-MOF. The maximum adsorption capacity of germanium by Ma-Zr-MOF is 82.06 mg/g at 298 K and pH 6.0, which is better than some of the previously reported adsorbents. The adsorption of germanium ions by Ma-Zr-MOF is in accordance with the pseudo-second-order kinetics and Langmuir isothermal models, the adsorption type is single-layer chemical adsorption on a uniform surface. Thermodynamic calculations yield that the adsorption process is endothermic and spontaneous. Ma-Zr-MOF has good selectivity and anti-interference, and maintains repeatability after five adsorption and desorption cycles. Based on the experimental analysis and density functional theory (DFT) calculations, it is concluded that the Ortho-hydroxyl group played an important role in the adsorption of germanium and that the adsorption mechanism included chelation and ion exchange. In conclusion, Ma-Zr-MOF is proved to be a feasible material for the recovery of Ge(IV) from aqueous media.