A Versatile Approach for the Synthesis of Antimicrobial Polymer Brushes on Natural Rubber/Graphene Oxide Composite Films via Surface-Initiated Atom-Transfer Radical Polymerization.

A simple strategy was adopted for the preparation of an antimicrobial natural rubber/graphene oxide (NR/GO) composite film modified through the use of zwitterionic polymer brushes. An NR/GO composite film with antibacterial properties was prepared using a water-based solution-casting method. The composited GO was dispersed uniformly in the NR matrix and compensated for mechanical loss in the process of modification. Based on the high bromination activity of α-H in the structure of cis-polyisoprene, the composite films were brominated on the surface through the use of N-bromosuccinimide (NBS) under the irradiation of a 40 W tungsten lamp. Polymerization was carried out on the brominated films using sulfobetaine methacrylate (SBMA) as a monomer via surface-initiated atom transfer radical polymerization (SI-ATRP). The NR/GO composite films modified using polymer brushes (PSBMAs) exhibited 99.99% antimicrobial activity for resistance to Escherichia coli and Staphylococcus aureus. A novel polymer modification strategy for NR composite materials was established effectively, and the enhanced antimicrobial properties expand the application prospects in the medical field.

Grafting photochromic spiropyran polymer brushes on graphene oxide surfaces via surface-initiated ring-opening metathesis polymerization.

A practical "grafting-from" strategy is described to grow photochromic polymer brushes bearing spiropyran (SP) functional groups on graphene oxide (GO) surfaces via surface-initiated ring-opening metathesis polymerization (SI-ROMP). The Grubbs II catalyst was fixed on the GO surface, and the norbornene derivatives functionalized using spiropyran were synthesized from this active site via the ROMP method. The results indicated that the spiropyran-modified polymer brushes were obtained on the GO surface in the form of thin films. The solubility of GO modified by spiropyran polymers (GO-SPs) in organic solvents was significantly improved. The GO-SPs exhibited excellent photochromic properties, including fast coloration/decoloration. The modified GO with an isomeric structure was colored in 90 s under ultraviolet irradiation and decolored in 360 s under white light. The fading kinetic rate in the dark was slow and the kinetic attenuation curve followed bi-exponential decay. The GO-SP composite materials took more than 2 h to return to thermodynamically stable forms. The reversible change in the water contact angle reached 8° after continuous cycling with ultraviolet and visible light. GO-SP maintained its photochromic performance and possessed excellent fatigue resistance after more than six successive UV/light cycles. This work describes a practical strategy for the preparation of photochromic polymer brush modified GO composite materials and extends the applications of GO in photochromic materials.

Multi-energy CT material decomposition using graph model improved CNN.

In spectral CT imaging, the coefficient image of the basis material obtained by the material decomposition technique can estimate the tissue composition, and its accuracy directly affects the disease diagnosis. Although the precision of material decomposition is increased by employing convolutional neural networks (CNN), extracting the non-local features from the CT image is restricted using the traditional CNN convolution operator. A graph model built by multi-scale non-local self-similar patterns is introduced into multi-material decomposition (MMD). We proposed a novel MMD method based on graph edge-conditioned convolution U-net (GECCU-net) to enhance material image quality. The GECCU-net focuses on developing a multi-scale encoder. At the network coding stage, three paths are applied to capture comprehensive image features. The local and non-local feature aggregation (LNFA) blocks are designed to integrate the local and non-local features from different paths. The graph edge-conditioned convolution based on non-Euclidean space excavates the non-local features. A hybrid loss function is defined to accommodate multi-scale input images and avoid over-smoothing of results. The proposed network is compared quantitatively with base CNN models on the simulated and real datasets. The material images generated by GECCU-net have less noise and artifacts while retaining more information on tissue. The Structural SIMilarity (SSIM) of the obtained abdomen and chest water maps reaches 0.9976 and 0.9990, respectively, and the RMSE reduces to 0.1218 and 0.4903 g/cm3. The proposed method can improve MMD performance and has potential applications.

Preparation and Self-Cleaning Performance of High-Strength Double-Layer PVDF-PVC-Nano-Graphite/PVDF-PVC Super-Hydrophobic Composite Membrane.

The double-layer PVDF-PVC (D-PP/PP) super-hydrophobic composite membrane was prepared by the coating immersion phase separation method to enhance the mechanical properties of the composite membrane. The D-PP/PP super-hydrophobic membrane was prepared using the casting solution concentration of 12 wt% PVDF-PVC composite membrane as basement and 4% casting of PVDF-PVC coating. The contact angle of the D-PP/PP membrane was 150.4 ± 0.3°, and the scanning electron microscope showed that the surface of the D-PP/PP membrane was covered by a cross-linked micro-nano microsphere. The mechanical properties showed that the maximum tensile force of the D-PP/PP composite membrane was 2.34 N, which was 19.4% higher than that of PVDF-PVC (1.96 N). Nano-graphite was added to the coating layer in the experiment. The prepared double-layer PVDF-PVC-nano-graphite/PVDF-PVC (D-PPG/PP) composite membrane reached 153.7 ± 0.5°, the contact angle increasing by 3.3°. The SEM comparison showed that the D-PPG/PP composite membrane had a more obvious micro-nano level microsphere layer. The mechanical properties are also superior. By preparing the D-PP/PP membrane, the mechanical properties of the membrane were improved, and the super-hydrophobic property of the coating was also obtained. At the same time, it was found that adding nano-graphite to the coating layer can better improve the hydrophobic, mechanical, and self-cleaning properties of the D-PP/PP composite membrane.

Study of a Multiple Responses, High Deformation, and Programmable PLA-PPC/PVA-PDA Actuator.

The intelligent response actuators based on bilayer polymer can deform under the stimulation of temperature, humidity, light, and other external environment, which is the focus of research. However, achieving multiple responses, high deformation, and programmability is still one of the challenges for these actuators. Herein, a nondetachable bilayer structure, polylactic acid-polypropylene carbonate/polyvinyl alcohol-polydopamine (PLA-PPC/PVA-PDA) multiresponse programmable actuator is prepared by a simple scraping film method. Using PLA-PPC as the solvent-driven response layer, the effects of length, thickness, shape, and solvent vapor on the deformation of PLA-PPC/PVA-PDA actuators are studied. Among them, the high curvature of the film stimulated by ethyl acetate (EA) solution is 29.85 cm-1 . Using PVA-PDA as the response layer to water molecules and infrared (IR) light, the bilayer film shows excellent curling performance. Moreover, the dynamic processes of human clothing and biomimetic squid under solvent stimulation, the picture rolling motion under water molecule stimulation, the biomimetic flower blooming and merging under the synergistic of water molecules and IR light, and the deformation process of biomimetic mimosa under the competition between water molecules and IR light are simulated, which broadens the road for the development of intelligent driving materials.

The Preparation of Superhydrophobic Polylactic Acid Membrane with Adjustable Pore Size by Freeze Solidification Phase Separation Method for Oil-Water Separation.

An environmentally friendly pore size-controlled, superhydrophobic polylactic acid (PLA) membrane was successfully prepared by a simpler freeze solidification phase separation method (FSPS) and solution impregnation, which has application prospects in the field of oil-water separation. The pore size and structure of the membrane were adjusted by different solvent ratios and solution impregnation ratios. The PLA-FSPS membrane after solution impregnation (S-PLA-FSPS) had the characteristics of uniform pore size, superhydrophobicity and super lipophilicity, its surface roughness Ra was 338 nm, and the contact angle to water was 151°. The S-PLA-FSPS membrane was used for the oil-water separation. The membrane oil flux reached 16,084 L·m-2·h-1, and the water separation efficiency was 99.7%, which was much higher than that of other oil-water separation materials. In addition, the S-PLA-FSPS membrane could also be applied for the adsorption and removal of oil slicks and underwater heavy oil. The S-PLA-FSPS membrane has great application potential in the field of oil-water separation.

Preparation of a Series of Highly Efficient Porous Adsorbent PGMA-N Molecules and Its Application in the Co-Removal of Cu(II) and Sulfamethoxazole from Water.

This paper presents a highly efficient porous adsorbent PGMA-N prepared through a series of amination reactions between polyglycidyl methacrylate (PGMA) and different polyamines. The obtained polymeric porous materials were characterized using Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), specific surface area test (BET), and elemental analysis (EA). Thereinto, the PGMA-EDA porous adsorbent exhibited excellent ability to synergistically remove Cu(II) ions and sulfamethoxazole from aqueous solutions. Moreover, we studied the effects of pH, contact time, temperature, and initial concentration of pollutants on the adsorption performance of the adsorbent. The experimental results showed that the adsorption process of Cu(II) followed the pseudo-second-order kinetic model and Langmuir isotherm. The maximum adsorption capacity of PGMA-EDA for Cu(II) ions was 0.794 mmol/g. These results indicate that PGMA-EDA porous adsorbent has great potential for application in treating wastewater coexisting with heavy metals and antibiotics.

Modification of biochar by phosphoric acid via wet pyrolysis and using it for adsorption of methylene blue.

Algae biochar (ABC), coconut shell biochar (CSBC), and coconut coat biochar (CCBC) were prepared by wet pyrolysis in a phosphoric acid solvent under normal pressure. Materials were characterized for their micromorphology, specific surface area, and surface functional groups by scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) nitrogen adsorption-desorption spectrum technique and Fourier transform infrared diffraction (FT-IR). The evaluation of the liquid-phase adsorption performance using methylene blue (MB) as a pigment model, and the effects of temperature, pH, adsorbent dosage, and pollutant concentration of the MB adsorption onto modified biochars were fully investigated. The adsorption mechanism was proposed based on the adsorption kinetics curve and adsorption isotherm. The synthetic biochar showed great adsorption properties toward cationic dyes rather than anionic dyes. Specifically, the adsorption abilities for algal biochar, coconut shell biochar, and coconut coat biochar were determined to be 97.5%, 95.4% and 21.2%, respectively. The isothermal adsorption of MB by the three kinds of biochar conformed to the Langmuir equation, and the adsorption process fitted to the quasi-second-order kinetic equation, which suggested that ABC and CSBC effectively adsorbed MB dye molecules through hydrogen bonding, π-π stacking, and electrostatic interactions.

In-Depth Insight into the Ag/CNQDs/g-C3N4 Photocatalytic Degradation of Typical Antibiotics: Influence Factor, Mechanism and Toxicity Evaluation of Intermediates.

In this paper, the photocatalytic degradation efficiency of typical antibiotics (norfloxacin (NOR), sulfamethoxazole (SMX) and tetracycline hydrochloride (TCH)) by Ag/CNQDs/g-C3N4 under visible light irradiation was studied. Various strategies were applied to characterize the morphology, structure and photochemical properties of the Ag/CNQDs/g-C3N4 composites. The superior photocatalytic activity of Ag/CNQDs/g-C3N4 was attributed to the wide light response range and the enhancement of interfacial charge transfer. At the same time, the effect of the influence factors (pH, Humic acid (HA) and coexisting ions) on the antibiotics degradation were also investigated. Furthermore, the electron spin resonance (ESR) technology, free radical quenching experiments, LC/MS and DFT theoretical calculations were applied to predict and identify the active groups and intermediates during the photocatalytic degradation process. In addition, Ag/CNQDs/g-C3N4 exhibited the obvious antibacterial effect to Escherichia coli due to the addition of Ag NPs. This study develops a new way for the removal of emerging antibiotic pollution from wastewaters.

Circularly polarized luminescence of pinene-modified tetradentate platinum(II) enantiomers containing fused 5/6/6 metallocycles.

In this study, a couple of tetradentate Pt(II) enantiomers ((-)-1 and (+)-1) and a couple of tetradentate Pt(IV) enantiomers ((-)-2 and (+)-2) containing fused 5/6/6 metallocycles have been synthesized by controlling reaction conditions. Two valence forms could transform into each other through mild chemical oxidants and reductants. Single-crystal X-ray diffraction confirms the structures of (-)-1 and (-)-2. The coordination sphere of the Pt(II) cation in (-)-1 displays a distorted square-planar geometry and a platinum centroid helix chirality. In contrast, the structure of (-)-2 reveals a distorted octahedral geometry. The solution and the solid of (-)-1 are highly luminescent. Complex (-)-1 shows a prominent aggregation-induced emission enhancement (AIEE) behavior in DMSO/water solution with emission quantum yield (Φ em) up to 73.2%. Furthermore, highly phosphorescent Pt(II) enantiomers exhibit significant circularly polarized luminescence (CPL) with a dissymmetry factor (g lum) of order 10-3 in CH2Cl2 solutions at room temperature. Symmetrically appreciable CPL signals are observed for the enantiomers (-)-1 and (+)-1.

Study on the Control of Membrane Fouling by Pulse Function Feed and CFD Simulation Verification.

A complex-function fluid controller placed in front of a membrane module was used to control the velocity change with feed fluid and reduce membrane fouling. Using humic acid as the simulated pollutant, the effects of the square wave function, sine function, reciprocal function, and power function feeding on the membrane flux were investigated. For sine function feeding, the membrane-specific flux was the largest and was maintained above 0.85 under the intermittent frequency of 9 s. Compared with the final membrane-specific flux with steady-flow feeding of 0.55, functional feeding could significantly reduce membrane fouling. SEM results showed that sine feeding led to slight contamination on the membrane surface. Furthermore, the Computational Fluid Dynamics (CFD) simulation results showed that the shear force of sine function feeding was about three times that of the steady flow (6 × 105 N). Compared with steady feeding, functional feeding could significantly improve the shear force on the membrane surface and reduce membrane fouling.

A semi-supervised learning method of latent features based on convolutional neural networks for CT metal artifact reduction.

PURPOSE: X-ray computed tomography (CT) has become a convenient and efficient clinical medical technique. However, in the presence of metal implants, CT images may be corrupted by metal artifacts. The metal artifact reduction (MAR) methods based on deep learning are mostly supervised methods trained with labeled synthetic-artifact CT images. However, this causes the neural network to be biased toward learning specific synthetic-artifact patterns and leads to a poor generalization for unlabeled real-artifact CT images. In this study, a semi-supervised learning method of latent features based on convolutional neural networks (SLF-CNN) is developed to remove metal artifacts while ensuring a good generalization ability for real-artifact CT images. METHODS: The proposed semi-supervised method extracts CT image features in alternate iterations of a synthetic-artifact learning stage and a real-artifact learning stage. In the synthetic-artifact learning stage, SLF-CNN is fed with paired synthetic-artifact CT images and is constrained using mean-squared-error (MSE) loss and perceptual loss in a supervised learning fashion. In the real-artifact learning stage, the network weight is updated by minimizing the error between the pseudo-ground truths and the predicted latent features. The feature level pseudo-ground truths are obtained by modeling latent features using the Gaussian process. The overall framework of SLF-CNN adopts an encoder-decoder structure. The encoder is composed of artifact information collection groups to map the input artifact-affected synthetic-artifact CT images and real-artifact CT images into latent features. The decoder is composed of stacked ResNeXt blocks and is responsible for decoding latent features with high-level semantic information to reconstruct artifact-free CT images. The performance of the proposed method is evaluated through contrast experiments and ablation experiments. RESULTS: The contrast experimental results indicate that the artifact-free CT images obtained by SLF-CNN have good metrics values, which are close to or better than those of typical supervised MAR methods. The metal artifacts in artifact-affected CT images are eliminated and the tissue structure details are preserved using SLF-CNN. The ablation experiment shows that adding real-artifact CT images greatly improves the generalization ability of the network. CONCLUSIONS: The proposed semi-supervised learning method of latent features for MAR effectively suppresses metal artifacts and improves the generalization ability of the network.

Mechanochromic luminescence properties of fluoro-substituted pinene-containing cyclometalated platinum(II) complexes with multiple triplet excited states.

The structure-mechanochromism relationship is explored with respect to packing patterns and corresponding intermolecular interactions that are affected by the number and location of -F. The distinct and reversible mechanochormic luminescence (Δλem up to ca. 90 nm) of yellow solids (-)-1-Yg, (-)-2-Yg, and (-)-3-Yg was displayed with a simultaneous crystal-to-amorphous transformation. The change of multiple triplet excited states accounted for the mechanochormic luminescence, and a switch from the 3π,π* monomer to the excimer/3MMLCT occurred in the grinding process. The mechanical force led to perturbation in the molecular packing, and aggregates with effective PtPt and π-π interactions were formed in the amorphous phase, leading to the variation of excited states. The mechanochromic luminescence could be reverted by dropping in CH2Cl2 and could be cycled multiple times without perceivable performance degradation. This work gives a reference for designing mechanochromic luminescent materials toward multicolor and multicomponent responses.

An x-ray crosstalk correction method using FCNN for a novel energy resolving scheme in spectral CT.

Spectral computed tomography has great potential for multi-energy imaging and anti-artifacts. The complete absorption-based energy resolving scheme of x-rays has been used for the integrity of detected information. However, this scheme is limited by the fact that the detector pixel thickness is high and fixed. Here, an energy resolving scheme is proposed using the crosstalk correction method for the incomplete absorption detection of x-rays. A fully connected neural network (FCNN)-based method was used to correct the difference caused by internal x-ray crosstalk of the edge-on detector. The energy and spatial features of the data which is collected in layers were combined to establish the mapping between the ideal data and the data with crosstalk at the pre-processing stage. Thereafter, to reconstruct the stable and highly accurate energy-resolving equations, the layers with low relative energy difference were selected and grouped together to reduce the accumulation difference. The experiment results demonstrate the feasibility of this energy resolving scheme. The differences caused by crosstalk can be suppressed through the proposed FCNN-based method. The resolving accuracy can be further improved by grouping more layers at forward positions in the pixel. Moreover, this improvement can be observed in the reconstructed images with reduced artifacts and improved quality.

A material decomposition method for dual-energy CT via dual interactive Wasserstein generative adversarial networks.

PURPOSE: Dual-energy computed tomography (DECT) is highly promising for material characterization and identification, whereas reconstructed material-specific images are affected by magnified noise and beam-hardening artifacts. Although various DECT material decomposition methods have been proposed to solve this problem, the quality of the decomposed images is still unsatisfactory, particularly in the image edges. In this study, a data-driven approach using dual interactive Wasserstein generative adversarial networks (DIWGAN) is developed to improve DECT decomposition accuracy and perform edge-preserving images. METHODS: In proposed DIWGAN, two interactive generators are used to synthesize decomposed images of two basis materials by modeling the spatial and spectral correlations from input DECT reconstructed images, and the corresponding discriminators are employed to distinguish the difference between the generated images and labels. The DECT images reconstructed from high- and low-energy bins are sent to two generators separately, and each generator synthesizes one material-specific image, thereby ensuring the specificity of the network modeling. In addition, the information from different energy bins is exploited through the feature sharing of two generators. During decomposition model training, a hybrid loss function including L1 loss, edge loss, and adversarial loss is incorporated to preserve the texture and edges in the generated images. Additionally, a selector is employed to define the generator that should be trained in each iteration, which can ensure the modeling ability of two different generators and improve the material decomposition accuracy. The performance of the proposed method is evaluated using digital phantom, XCAT phantom, and real data from a mouse. RESULTS: On the digital phantom, the regions of bone and soft tissue are strictly and accurately separated using the trained decomposition model. The material densities in different bone and soft-tissue regions are near the ground truth, and the error of material densities is lower than 3 mg/ml. The results from XCAT phantom show that the material-specific images generated by directed matrix inversion and iterative decomposition methods have severe noise and artifacts. Regarding to the learning-based methods, the decomposed images of fully convolutional network (FCN) and butterfly network (Butterfly-Net) still contain varying degrees of artifacts, while proposed DIWGAN can yield high quality images. Compared to Butterfly-Net, the root-mean-square error (RMSE) of soft-tissue images generated by the DIWGAN decreased by 0.01 g/ml, whereas the peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM) of the soft-tissue images reached 31.43 dB and 0.9987, respectively. The mass densities of the decomposed materials are nearest to the ground truth when using the DIWGAN method. The noise standard deviation of the decomposition images reduced by 69%, 60%, 33%, and 21% compared with direct matrix inversion, iterative decomposition, FCN, and Butterfly-Net, respectively. Furthermore, the performance of the mouse data indicates the potential of the proposed material decomposition method in real scanned data. CONCLUSIONS: A DECT material decomposition method based on deep learning is proposed, and the relationship between reconstructed and material-specific images is mapped by training the DIWGAN model. Results from both the simulation phantoms and real data demonstrate the advantages of this method in suppressing noise and beam-hardening artifacts.

Enhanced Circularly Polarized Luminescence Activity in Chiral Platinum(II) Complexes With Bis- or Triphenylphosphine Ligands.

Distinct circularly polarized luminescence (CPL) activity was observed in chiral (C∧N∧N)Pt(II) [(C∧N∧N) = 4,5-pinene-6'-phenyl-2,2'-bipyridine] complexes with bis- or triphenylphosphine ligands. Compared to the pseudo-square-planar geometry of chiral (C∧N∧N)Pt(II) complexes with chloride, phenylacetylene (PPV) and 2,6-dimethylphenyl isocyanide (Dmpi) ligands, the coordination configuration around the Pt(II) nucleus of chiral (C∧N∧N)Pt(II) complexes with bulk phosphine ligands is far more distorted. The geometry is straightforwardly confirmed by X-ray crystallography. The phosphines' participation enhanced the CPL signal of Pt(II) complexes profoundly, with the dissymmetry factor (g lum) up to 10-3. The distorted structures and enhanced chiroptical signals were further confirmed by time-dependent density functional theory (TD-DFT) calculations.

A new 1,2,3-triazole and its rhodamine B derivatives as a fluorescence probe for mercury ions.

A newly synthesized compound, 5-methyl-1-phenyl-1H-1,2,3-triazole-4- carboxylic acid (MPC) was analyzed for its quantum chemical parameters and theoretical spectrum by computational chemistry. The calculated spectrum was in accord with the experimental measurements in a great degree. Then MPC was successfully designed and synthesized to a novel rhodamine B derivative RMPC. The RMPC exhibited about a 4000-fold increase in fluorescence intensity in the presence of Hg2+ ions over most other competitive metal ions. The triazole appended colorless chemodosimeter RMPC turns to pink upon the complex formation only with Hg2+ ions as a 1: 2 M ratio and enables naked-eye detection. The coordination mechanism of turning on/off fluorescence for Hg2+ ions were well proposed by explaining Hg2+ inducing the ring-opened rhodamine B moiety. The fluorescence imaging experiments of Hg2+ in HeLa cell demonstrated that the probe was labeled and it could be used in biological systems.

Highly efficient removal of Cu(ii) by novel dendritic polyamine-pyridine-grafted chitosan beads from complicated salty and acidic wastewaters.

In this study, dendritic polyamine chitosan beads with and without 2-aminomethyl pyridine were facilely prepared and characterized. Compared to CN (without the pyridine function), more adsorption active sites, larger pores, higher nitrogen content, higher specific surface area, and higher strength could be obtained for CNP (with the pyridine function). CNP microspheres afforded a larger adsorption capacity than those obtained by CN for different pH values; further, the uptake amounts of Cu(ii) were 0.84 and 1.12 mmol g-1 for CN and CNP beads, respectively, at pH 5. The CNP microspheres could scavenge Cu(ii) from highly acidic and salty solutions: the maximum simulated uptake amount of 1.93 mmol g-1 at pH 5 could be achieved. Due to the strong bonding ability and weakly basic property of pyridine groups, the adsorption capacity of Cu(ii) at pH 1 was 0.75 mmol g-1 in highly salty solutions, which was comparative to those obtained from the commercial pyridine chelating resin M4195 (Q Cu(II) = 0.78 mmol g-1 at pH 1). In addition, a distinct salt-promotion effect could be observed for CNP beads at both pH 5 and 1. Therefore, the prepared adsorbent CNP beads can have promising potential applications in the selective capturing of heavy metals in complex solutions with higher concentrations of H+ and inorganic salts, such as wastewaters from electroplating liquid and battery industries.

A Reconfigurable energy-resolving method for a layered edge-on detector.

Currently, most of the x-ray spectral detectors can extract signals in a set number of energy bins, that inevitably reduces the dynamic range and energy resolution of the imaging system. Inspired by the idea of dynamic thresholding, we previously proposed a pixel architecture and an energy-resolving method for layered edge-on detector. However, the complicated energy exchange mechanism of x-rays in the detector that ultimately affects the practical applications of the layered detectors had not been previously considered. In this study, we modify the energy-depositing model of x-ray photons and propose a reconfigurable energy-resolving method to improve the spectral performance of a layered energy integrating detector. We analyze the errors associated with the energy-resolving process and present our numerical simulation results obtained with energy bins and dynamically changed detection layers to demonstrate the utility and reliability of the proposed method.

Entrapment of bacterial cellulose nanocrystals stabilized Pickering emulsions droplets in alginate beads for hydrophobic drug delivery.

In this work, the interfacial assembly of amphiphilic bacterial cellulose nanocrystals (BCNs) by Pickering emulsion method was proposed to improve the compatibility between the alginate and hydrophobic drug. BCNs prepared by sulfuric acid hydrolysis of biosynthesized bacterial cellulose was used as the particulate emulsifiers, whereas the model drug, alfacalcidol, dissolved in CH2Cl2 was used as the oil phase. The oil-in-water Pickering emulsions were prepared by ultrasonic dispersion method and then they were well dispersed in alginate solution. Ultimately, the drug-loaded alginate composite beads were successfully fabricated by external gelation. The characterization results revealed that BCNs possessed good colloidal property and could form flocculated fibril network, which was beneficial to stabilize Pickering emulsions. The irreversible adsorption of BCNs at the oil-water interface could make the Pickering emulsions preserve the droplets against coalescence and Ostwald ripening when they were dispersed in alginate solution. The interfacial assembly of amphiphilic BCNs and the hydrogel shells of the alginate composite beads formed by external gelation achieved the loading and sustained release of alfacalcidol. The release curves were well fitted by Korsmeyer Peppas model and the release mechanism of alfacalcidol from the composite beads was attributed to non-Fickian transport. In addition, the resultant alginate composite beads exhibited low cytotoxicity and good capabilities for osteoblast differentiation.