Inhibition of biofouling by in-situ grown zwitterionic hydrogel nanolayer on membrane surface in ultralow-pressurized ultrafiltration process.

Ultralow-pressurized ultrafiltration membrane process with low energy consumption is promising in surface water purification. However, membrane fouling and low selectivity are significant barriers for the wide application of this process. Herein, an ultrathin zwitterionic hydrogel nanolayer was in-situ grown on polysulfone ultrafiltration membrane surface through interfacially-initiated free radical polymerization. The hydrogel-modified membrane possessed improved biological fouling resistance during the dynamic filtration process (bovine serum albumin, Escherichia coli and Staphylococcus aureus), comparing with commercial polysulfone membrane. The enhanced biofouling resistance ability of zwitterionic hydrogel nanolayer was derived from the foulant repulsion of hydration shell and the bactericidal effect of quaternary ammonium, according to the results of foulant-membrane interaction energy analyses and antibacterial performances. In surface water treatment, the zwitterionic hydrogel layer inhibited biofouling and resulted in the formation of a loose and thin biofilm. In addition, the hydrogel-modified membrane possessed 22% improvement in dissolved organic carbon (DOC) removal and 134% increasement in stable water flux, compared to commercial polysulfone membrane. The in-situ grown zwitterionic hydrogel nanolayer on membrane surface offers a prospectively alternative for biofouling control in ultralow-pressurized membrane process.

Incomplete Data Meets Uncoupled Case: A Challenging Task of Multiview Clustering.

Incomplete multiview clustering (IMC) methods have achieved remarkable progress by exploring the complementary information and consensus representation of incomplete multiview data. However, to our best knowledge, none of the existing methods attempts to handle the uncoupled and incomplete data simultaneously, which affects their generalization ability in real-world scenarios. For uncoupled incomplete data, the unclear and partial cross-view correlation introduces the difficulty to explore the complementary information between views, which results in the unpromising clustering performance for the existing multiview clustering methods. Besides, the presence of hyperparameters limits their applications. To fill these gaps, a novel uncoupled IMC (UIMC) method is proposed in this article. Specifically, UIMC develops a joint framework for feature inferring and recoupling. The high-order correlations of all views are explored by performing a tensor singular value decomposition (t-SVD)-based tensor nuclear norm (TNN) on recoupled and inferred self-representation matrices. Moreover, all hyperparameters of the UIMC method are updated in an exploratory manner. Extensive experiments on six widely used real-world datasets have confirmed the superiority of the proposed method in handling the uncoupled incomplete multiview data compared with the state-of-the-art methods.

A Tensor Approach for Uncoupled Multiview Clustering.

Multiview clustering plays an important part in unsupervised learning. Although the existing methods have shown promising clustering performances, most of them assume that the data is completely coupled between different views, which is unfortunately not always ensured in real-world applications. The clustering performance of these methods drops dramatically when handling the uncoupled data. The main reason is that: 1) cross-view correlation of uncoupled data is unclear, which limits the existing multiview clustering methods to explore the complementary information between views and 2) features from different views are uncoupled with each other, which may mislead the multiview clustering methods to partition data into wrong clusters. To address these limitations, we propose a tensor approach for uncoupled multiview clustering (T-UMC) in this article. Instead of pairwise correlation, T-UMC chooses a most reliable view by view-specific silhouette coefficient (VSSC) at first, and then couples the self-representation matrix of each view with it by pairwise cross-view coupling learning. After that, by integrating recoupled self-representation matrices into a third-order tensor, the high-order correlations of all views are explored with tensor singular value decomposition (t-SVD)-based tensor nuclear norm (TNN). And the view-specific local structures of each individual view are also preserved with the local structure learning scheme with manifold learning. Besides, the physical meaning of view-specific coupling matrix is also discussed in this article. Extensive experiments on six commonly used benchmark datasets have demonstrated the superiority of the proposed method compared with the state-of-the-art multiview clustering methods.

Refining Graph Structure for Incomplete Multi-View Clustering.

As a challenging problem, incomplete multi-view clustering (MVC) has drawn much attention in recent years. Most of the existing methods contain the feature recovering step inevitably to obtain the clustering result of incomplete multi-view datasets. The extra target of recovering the missing feature in the original data space or common subspace is difficult for unsupervised clustering tasks and could accumulate mistakes during the optimization. Moreover, the biased error is not taken into consideration in the previous graph-based methods. The biased error represents the unexpected change of incomplete graph structure, such as the increase in the intra-class relation density and the missing local graph structure of boundary instances. It would mislead those graph-based methods and degrade their final performance. In order to overcome these drawbacks, we propose a new graph-based method named Graph Structure Refining for Incomplete MVC (GSRIMC). GSRIMC avoids recovering feature steps and just fully explores the existing subgraphs of each view to produce superior clustering results. To handle the biased error, the biased error separation is the core step of GSRIMC. In detail, GSRIMC first extracts basic information from the precomputed subgraph of each view and then separates refined graph structure from biased error with the help of tensor nuclear norm. Besides, cross-view graph learning is proposed to capture the missing local graph structure and complete the refined graph structure based on the complementary principle. Extensive experiments show that our method achieves better performance than other state-of-the-art baselines.

Multiview Subspace Clustering With Grouping Effect.

Multiview subspace clustering (MVSC) is a recently emerging technique that aims to discover the underlying subspace in multiview data and thereby cluster the data based on the learned subspace. Though quite a few MVSC methods have been proposed in recent years, most of them cannot explicitly preserve the locality in the learned subspaces and also neglect the subspacewise grouping effect, which restricts their ability of multiview subspace learning. To address this, in this article, we propose a novel MVSC with grouping effect (MvSCGE) approach. Particularly, our approach simultaneously learns the multiple subspace representations for multiple views with smooth regularization, and then exploits the subspacewise grouping effect in these learned subspaces by means of a unified optimization framework. Meanwhile, the proposed approach is able to ensure the cross-view consistency and learn a consistent cluster indicator matrix for the final clustering results. Extensive experiments on several benchmark datasets have been conducted to validate the superiority of the proposed approach.

Accelerated catalytic oxidation of dissolved manganese(II) by chlorine in the presence of in situ-growing 3D manganese(III)/(IV) oxide nanosheet assembly in zeolite filter.

Manganese contamination is ubiquitous in ground water. Water eutrophication also exaggerates manganese release and contamination in surface water. However, conventional manganese(II) removal process through sand filter is low-efficiency and long-term ripening. Manganese exceeding standard is still a bottleneck issue for drinking water plants. To provide a quick-setup and low-cost means, we invented an accelerated catalytic oxidation filtration process through porous zeolite filter with dynamically coating of manganese oxide nanocatalysts. In dynamic filtration process, the addition of chlorine less than redox stoichiometric consumption can efficiently remove dissolved manganese(II) from contaminated tap water, ground water and Songhua river water. Characterization results showed that a continuous manganese(III)/(IV) oxide nanosheet catalyst was dynamically in situ-growing and assembled into 3D porous superstructure in the reactive Zeolite@MnOx(s) filter. Active Mn(III) species on the edges of MnOx(s) nanosheets were dynamically generated and transferred into stable Mn(IV) species on the layer-structured surface. The cycling transformation of manganese(III)/(IV) species was responsible for the accelerated catalytic oxidation of dissolved manganese(II) by chlorine. Without process changes in drinking water plant, the porous Zeolite@MnOx(s) media could be feasibly integrated onto the existing sand filtration tanks for emergence handling of manganese(II) contamination. This novel reactive Zeolite@MnOx(s) filter with higher hydraulic conductivity provides a high-efficiency, scalable and low-cost technique for the manganese(II) removal from various of water environments.

Enhanced Water Permeability and Antifouling Property of Coffee-Ring-Textured Polyamide Membranes by In Situ Incorporation of a Zwitterionic Metal-Organic Framework.

Modulation of the polyamide structure is critically important for the reverse-osmosis performance of thin-film composite (TFC) membranes in the field of water reuse and desalination. Herein, zwitterionic nanoparticles of zeolitic imidazolate framework-8 (PZ@ZIF-8) were fabricated and incorporated into the polyamide active layer through the interfacial polymerization method. A hydrophilic, zwitterionic coffee-ring structure was formed on the surface of polyamide thin-film nanocomposite (TFN) membranes due to the adjusted diffusion rate of m-phenylenediamine (MPD) from the aqueous phase into the organic phase during the interfacial polymerization process. Surface characterization demonstrated that the coffee-ring structure increased the amounts of water transport channels on the membrane surface and the intrinsic pores of PZ@ZIF-8 maintained the salt rejection. Antifouling and bactericidal activities of TFN membranes were enhanced remarkably owing to the bacterial-"defending" and bacterial-"attacking" behaviors of hydrophilic and zwitterionic groups from PZ@ZIF-8 nanoparticles. This work would provide a promising method for the application of MOFs to enhance the bio-/organic-fouling resistance of TFN membranes with high water permeation and salt rejection.

Smoothness Regularized Multiview Subspace Clustering With Kernel Learning.

Multiview subspace clustering has attracted an increasing amount of attention in recent years. However, most of the existing multiview subspace clustering methods assume linear relations between multiview data points when learning the affinity representation by means of the self-expression or fail to preserve the locality property of the original feature space in the learned affinity representation. To address the above issues, in this article, we propose a new multiview subspace clustering method termed smoothness regularized multiview subspace clustering with kernel learning (SMSCK). To capture the nonlinear relations between multiview data points, the proposed model maps the concatenated multiview observations into a high-dimensional kernel space, in which the linear relations reflect the nonlinear relations between multiview data points in the original space. In addition, to explicitly preserve the locality property of the original feature space in the learned affinity representation, the smoothness regularization is deployed in the subspace learning in the kernel space. Theoretical analysis has been provided to ensure that the optimal solution of the proposed model meets the grouping effect. The unique optimal solution of the proposed model can be obtained by an optimization strategy and the theoretical convergence analysis is also conducted. Extensive experiments are conducted on both image and document data sets, and the comparison results with state-of-the-art methods demonstrate the effectiveness of our method.

Catalytic degradation of micropollutant by peroxymonosulfate activation through Fe(III)/Fe(II) cycle confined in the nanoscale interlayer of Fe(III)-saturated montmorillonite.

Low cost, green, regenerable catalyst for persulfate activation is the popularly concerned topic for the degradation of persistent organic micropollutants in drinking water. In this work, natural montmorillonite (MMT) saturated with Fe(III) ions was used to activate peroxymonosulfate (PMS) for the degradation of atrazine in raw drinking water. Results showed that the adsorption of atrazine was quickly completed within 1 min and the percentage degradation was finally increased up to 94.1% in 60 min. The d001-spacing of MMT was enlarged to 2.91 nm at the most by Fe(III) saturation. Atrazine was adsorbed into the nanoscale interlayer of Fe(III)-saturated montmorillonite (Fe-MMT), where the Fe(III)/Fe(II) cycle was sustainably realized through the accelerated transformation of electrons between Fe(III) and PMS. Meanwhile, the in-situ generated Fe(II) accelerated the decomposition of PMS to further proceed the degradation of atrazine through the oxidation of HO• and SO4•- radicals. This nanoconfined effect of PMS activation by Fe(III) was further confirmed through the degradation of various micropollutants in the backgrounds of river water. The selective catalytic oxidation of micropollutants through PMS activation was attributed to the 2D mesoporous structure of Fe-MMT, inhibiting the interlayer adsorption of larger molecular backgrounds (humic acids etc.). Fe(III)-saturated montmorillonite (Fe-MMT) provided a feasible and scalable method of PMS activation by Fe(III) for the degradation of micropollutants in drinking water.

Ultramicropore Engineering by Dehydration to Enable Molecular Sieving of H2 by Calcium Trimesate.

The high energy footprint of commodity gas purification and increasing demand for gases require new approaches to gas separation. Kinetic separation of gas mixtures through molecular sieving can enable separation by molecular size or shape exclusion. Physisorbents must exhibit the right pore diameter to enable separation, but the 0.3-0.4 nm range relevant to small gas molecules is hard to control. Herein, dehydration of the ultramicroporous metal-organic framework Ca-trimesate, Ca(HBTC)⋅H2 O (H3 BTC=trimesic acid), bnn-1-Ca-H2 O, affords a narrow pore variant, Ca(HBTC), bnn-1-Ca. Whereas bnn-1-Ca-H2 O (pore diameter 0.34 nm) exhibits ultra-high CO2 /N2 , CO2 /CH4 , and C2 H2 /C2 H4 binary selectivity, bnn-1-Ca (pore diameter 0.31 nm) offers ideal selectivity for H2 /CO2 and H2 /N2 under cryogenic conditions. Ca-trimesate, the first physisorbent to exhibit H2 sieving under cryogenic conditions, could be a prototype for a general approach to exert precise control over pore diameter in physisorbents.

Synergistic oxidation - filtration process analysis of catalytic CuFe2O4 - Tailored ceramic membrane filtration via peroxymonosulfate activation for humic acid treatment.

This work synthesized catalytic CuFe2O4 tailored ceramic membrane (CuFeCM), and systematically investigated the intercorrelated oxidation - filtration mechanism of peroxymonosulfate (PMS)/CuFeCM catalytic filtration for treating humic acid (HA). PMS/CuFeCM filtration exhibited enhanced HA removal efficiency while reduced the irreversible fouling resistance as compared with the conventional CM filtration. Results from HA characterizations showed that PMS/CuFeCM catalytic filtration oxidized HA into conjugated structures of smaller molecular weight. The unsaturated bonds further caused the re-agglomeration of HA, hence enhancing the size exclusion of CuFeCM. Meanwhile, oxidized HA particles with changing physicochemical properties reduced the total attractive interaction energy between CuFeCM and HA, mainly attributed to the reduced acid-base interaction energy according to the Extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) analysis. The changing of HA properties and HA-CuFeCM physicochemical interactions rendered more re-agglomerated HA particles retained above membrane with less attachment, which induced decreasing irreversible fouling resistance and facilitated easier external fouling removal by hydraulic cleaning. Overall, the PMS/CuFeCM configuration demonstrated in this study could provide a new insight into the synergistic oxidation - filtration interaction mechanism of hybrid catalytic ceramic membrane filtration process.

Welcoming Gallium- and Indium-Fumarate MOFs to the Family: Synthesis, Comprehensive Characterization, Observation of Porous Hydrophobicity, and CO2 Dynamics.

The properties and applications of metal-organic frameworks (MOFs) are strongly dependent on the nature of the metals and linkers, along with the specific conditions employed during synthesis. Al-fumarate, trademarked as Basolite A520, is a porous MOF that incorporates aluminum centers along with fumarate linkers and is a promising material for applications involving adsorption of gases such as CO2. In this work, the solvothermal synthesis and detailed characterization of the gallium- and indium-fumarate MOFs (Ga-fumarate, In-fumarate) are described. Using a combination of powder X-ray diffraction, Rietveld refinements, solid-state NMR spectroscopy, IR spectroscopy, and thermogravimetric analysis, the topologies of Ga-fumarate and In-fumarate are revealed to be analogous to Al-fumarate. Ultra-wideline 69Ga, 71Ga, and 115In NMR experiments at 21.1 T strongly support our refined structure. Adsorption isotherms show that the Al-, Ga-, and In-fumarate MOFs all exhibit an affinity for CO2, with Al-fumarate being the superior adsorbent at 1 bar and 273 K. Static direct excitation and cross-polarized 13C NMR experiments permit investigation of CO2 adsorption locations, binding strengths, motional rates, and motional angles that are critical to increasing adsorption capacity and selectivity in these materials. Conducting the synthesis of the indium-based framework in methanol demonstrates a simple route to introduce porous hydrophobicity into a MIL-53-type framework by incorporation of metal-bridging -OCH3 groups in the MOF pores.

Probing Calcium-Based Metal-Organic Frameworks via Natural Abundance 43 Ca Solid-State NMR Spectroscopy.

Calcium-based metal-organic frameworks (MOFs) are of high importance due to their low cost and bio-compatible metal centers. Understanding the local environment of calcium in these materials is critical for unraveling the origins of specific MOF properties. 43 Ca solid-state NMR spectroscopy is one of the very few techniques that can directly characterize calcium metal centers, however, the 43 Ca nucleus is a very challenging target for solid-state NMR spectroscopy due to its extremely low natural abundance and resonant frequency. In this work, natural abundance 43 Ca solid-state NMR spectroscopy, at a high magnetic field of 21.1 T, has been employed to characterize several calcium-based MOFs. We demonstrate that 43 Ca NMR spectra and quantum chemical calculations can probe the local structure of calcium metal centers within MOFs, investigate the presence of guests, and monitor phase changes.

Structure and magnetism of two chair-shaped hexanuclear dysprosium(iii) complexes exhibiting slow magnetic relaxation.

Two novel hexanuclear DyIII complexes with polyhydroxy Schiff-base ligands, [Dy6(L1)4(µ3-OH)4(MeOH)4]Cl2·2MeOH·2MeCN (1) and [Dy6(HL2)2(µ3-OH)2(µ3-OCH3)2(piv)10(MeOH)2] (2) (H3L1 = N,N'-bis(3-methoxysalicylidene)(propylene-2-ol)-1,3-diamine, H3L2 = 2,3-dihydroxypropylimino)methyl)-6-methoxyphenol, piv = pivalate), have been prepared under solvothermal conditions and structurally characterized by single-crystal X-ray diffraction, elemental analyses, thermal analyses, and IR spectroscopy. Each of the hexanuclear complexes is constructed with Dy3 triangular motifs as building blocks, and the six DyIII ions are arranged in a chair-shaped conformation. Variable-temperature magnetic susceptibility measurements in the temperature range of 2-300 K indicate dominant ferromagnetic exchange interactions between the DyIII ions in the complexes. Both complexes exhibit slow magnetic relaxation behavior.

An infinite two-dimensional hybrid water-chloride network in a 4'-(furan-2-yl)-2,2':6',2''-terpyridine nickel(II) matrix.

A new complex, namely bis-[4'-(furan-2-yl)-2,2':6',2''-terpyridine]-nickel(II) dichloride deca-hydrate, [Ni(C19H13N3O)2]Cl2·10H2O, has been crystallized by solvent evaporation and characterized by single-crystal X-ray diffraction. The coordination environment of the NiII cation is distorted octa-hedral with slight deviations from an idealized geometry. The most intriguing structural feature is an infinite two-dimensional hybrid water-chloride network parallel to (011) constructed by O-H⋯O and O-H⋯Cl hydrogen bonds involving two independent chloride ions and ten independent solvent water mol-ecules with an l-shaped pattern. One of the furyl rings is disordered with a refined occupancy ratio of 0.786 (13):0.214 (13).

Poly[diaqua[µ4-4-(isonicotinamido)phthalato]nickel(II)] displaying an sra topology.

In the title compound, [Ni(C14H8N2O5)(H2O)2]n, the Ni(II) cation is six-coordinate with a slightly distorted octahedral coordination geometry and the 4-(isonicotinamido)phthalate ligand links the Ni(II) centres into a three-dimensional structure with sra topology. The structure is also stabilized by N-H···O hydrogen bonding between the uncoordinated amide groups of the ligand and extensive O-H···O hydrogen bonding between the two coordinated water molecules. The magnetic and thermal stability properties of the title compound are also discussed.

Poly[[tetra-aqua-tetra-kis-[µ3-5-(pyridine-4-carboxamido)-isophthalato]nickel(II)diterbium(III)] tetra-hydrate].

In the title compound, {[NiTb2(C14H8N2O5)4(H2O)4]·4H2O} n , the Tb(III) ion is coordinated by one water mol-ecule and seven O atoms from four 5-(pyridine-4-carboxamido)-isophthalate (L) ligands in a distorted square-anti-prismatic arrangement, while the Ni(II) ion, lying on an inversion center, is six-coordinated in an octa-hedral geometry by two pyridine N atoms, two carboxyl-ate O atoms and two water mol-ecules. One L ligand bridges two Tb(III) ions and one Ni(II) ion through two carboxyl-ate groups and one pyridine N atom. The other L ligand bridges two Tb(III) ions and one Ni(II) ion through two carboxyl-ate groups, while the uncoordinating pyridine N atom is hydrogen bonded to an adjacent coordinating water mol-ecule. Extensive O-H⋯O, N-H⋯O and O-H⋯N hydrogen bonds play an important role in stabilizing the crystal structure.

(4,6-Dimethyl-2-sulfanylidenepyrimidin-1-ium) trichlorido(thiourea-κS)zinc(II).

The title compound, (C6H9N2S)[ZnCl3{SC(NH2)2}], exists as a zincate where the zinc(II) centre is coordinated by three chloride ligands and a thiourea ligand to form the anion. The organic cation adopts the protonated 4,6-dimethyl-2-sulfanylidenepyrimidin-1-ium (L) form of 4,6-dimethylpyrimidine-2(1H)-thione. Two short N-H···Cl hydrogen bonds involving the pyrimidine H atoms and the [ZnCl3L](-) anion form a crystallographically centrosymmetric dimeric unit consisting of two anions and two cations. The packing structure is completed by longer-range hydrogen bonds donated by the thiourea NH2 groups to chloride ligand hydrogen-bond acceptors.

Poly[[(µ2-4,4'-bipyridine)(µ3-5-isonicotinamidoisophthalato)cobalt(II)] trihydrate].

In the title compound, {[Co(C(14)H(8)N(2)O(5))(C(10)H(8)N(2))]·3H(2)O}(n), the Co(II) cation is five-coordinated with a slightly distorted trigonal-bipyramidal geometry, and the 5-isonicotinamidoisophthalate ligands link Co(II) atoms into a layered structure. These two-dimensional arrays are further pillared by rod-like 4,4'-bipyridine ligands to give a three-dimensional framework with pcu (primitive cubic) topology. The magnetic and adsorption properties of the title compound are also discussed.

Poly[[tetra-aquatetrakis-[µ(3)-5-(pyridine-4-carboxamido)-isophthalato]cobalt(II)digadolinium(III)] tetra-hydrate].

In the centrosymmetric polymeric title compound, {[CoGd(2)(C(14)H(8)N(2)O(5))(4)(H(2)O)(4)]·4H(2)O}(n), the Gd(III) cation is coordinated by one water mol-ecule and four pyridine-4-carboxamido-isophthalate (L) anions in a distorted square-anti-prismatic arrangement, while the Co(II) cation, located on an inversion center, is coordinated by two pyridyl-N atoms, two carboxyl-ate-O atoms and two water mol-ecules in a distorted octa-hedral geometry. The asymmetric unit contains two anionic L ligands: one bridges two Gd cations and one Co cation through two carboxyl groups and one pyridine-N atom; the other bridges two Gd cations and one Co cation through two carboxyl groups and the uncoordinated pyridine-N atom is hydrogen-bonded to the adjacent coordinated water mol-ecule. Extensive O-H⋯O and N-H⋯O hydrogen bonds are present in the crystal structure.