Water-in-oil Pickering emulsion using ergosterol as an emulsifier solely.

As a crucial component of the fungal cell membranes, ergosterol has been demonstrated to possess surface activity attributed to its hydrophobic region and polar group. However, further investigation is required to explore its emulsification behavior upon migration to the oil-water interface. Therefore, this study was conducted to analyze the interface properties of ergosterol as a stabilizer for water in oil (W/O) emulsion. Moreover, the emulsion prepared under the optimal conditions was utilized to load the water-soluble bioactive substance with the chlorogenic acid as the model molecules. Our results showed that the contact angle of ergosterol was 117.017°, and its dynamic interfacial tension was obviously lower than that of a pure water-oil system. When the ratio of water to oil was 4: 6, and the content of ergosterol was 3.5 % (ergosterol/oil phase, w/w), the W/O emulsion had smaller particle size (438 nm), higher apparent viscosity, and better stability. Meanwhile, the stability of loaded chlorogenic acid was improved under unfavorable conditions (pH 1.2, 90 °C, ultraviolet irradiation, and oxidation), which were 73.87 %, 59.53 %, 62.53 %, and 69.73 %, respectively. Additionally, the bioaccessibility of chlorogenic acid (38.75 %) and ergosterol (33.69 %), and the scavenging rates of the emulsion on DPPH radicals (81.00 %) and hydroxyl radicals (82.30 %) were also enhanced. Therefore, a novel W/O Pickering emulsion was prepared in this work using ergosterol as an emulsifier solely, which has great potential for application in oil-based food and nutraceutical formulations.

Soil column-experimental research on the migration pattern of petroleum pollutant in the soil.

In the process of oilfield exploitation and production, harmful pollutants, such as Crude oil that falls to the ground (generally refers to crude oil that leaks to the ground during oil production or transportation), production wastewater and oil-bearing mud are produced. In this contribution, the soil and crude oil from Daqing area are adopted as experimental materials to make a soil column-experimental device. The results show that the maximum migration depth of petroleum pollutants is 25 cm, most of the pollutants exist above 10 cm. The components of pollutants in disturbed soil column are complex, and the peak area of each component is large, mainly distributed in C12-C28, while in undisturbed soil column, the content of pollutants is small, and the peak area of each component is also small, mainly distributed in C12-C22. With the increase of depth, the relative content of aromatic hydrocarbons increases. The migration ability of low carbon component is weaker than the other components in crude oil. The components with high carbon number are significantly higher in shallow part. The relative contents of each component from high to low are saturates, aromatic hydrocarbons, resin and asphaltene in the soil. Compared with disturbed soil columns, the structure of undisturbed soil is complex, and the migration rate of pollutants in undisturbed soil is slower than that in disturbed soil. With the increase of depth, the light components of disturbed soil columns gradually decrease, and the relative content of heavy components changes little. The light components of the undisturbed soil column also gradually decreased, and the heavy components greater than C22 did not migrate to the depth of the soil column.

Role of optical coherence tomography in pipeline embolization device for the treatment of vertebral-basilar artery dissecting aneurysms.

BACKGROUND: Vertebral-basilar artery dissecting aneurysms (VADAs) are an uncommon phenomenon in all fields of cerebrovascular disease. The flow diverter (FD) can be used as an endoluminal reconstruction device that promotes neointima formation at the aneurysmal neck and preserves the parent artery. To date, imaging examinations such as CT angiography, MR angiography, and DSA are the main methods used to evaluate the vasculature of patients. However, none of these imaging methods can reveal the situation of neointima formation, which is of great importance in evaluating occlusion of VADAs, especially those treated with a FD. METHODS: Three patients were included in the study from August 2018 to January 2019. All patients underwent preprocedural, postprocedural, and follow-up evaluations with high resolution MRI, DSA, and optical coherence tomography (OCT), as well as the formation of intima on the surface of the scaffold at the 6 month follow-up. RESULTS: Preprocedural, postoperative, and follow-up high resolution MRI, DSA, and OCT of all three cases successfully evaluated occlusion of the VADAs and occurrence of in stent stenosis from different views of intravascular angiography and neointima formation. CONCLUSIONS: OCT was feasible and useful to further evaluate VADAs treated with FD from a near pathological perspective, which may contribute toward guiding the duration of antiplatelet medication and early intervention of in stent stenosis.

Insights into the Binding Profile of Anti-chlorpyrifos Recombinant Antibodies: From Computational Simulation to Immunoassay Validation.

A novel virtual screening strategy was proposed for the profiling and discovery of active variable regions (VRs) that encode hapten-specific recombinant antibodies (rAbs). Chlorpyrifos, a hazardous organophosphorus pesticide, was selected as the target. First, a VR model-14G4 from anti-chlorpyrifos hybridoma was built via homology modeling. Its binding pattern toward seven organophosphorus analogues was assessed through virtual screening by performing molecular docking. Based on energy scoring, visual examination, and molecular interaction analysis, chlorpyrifos-methyl was also inferred as the high-affinity target for model-14G4 and was then confirmed via a non-competitive surface plasmon resonance (SPR) assay. Subsequently, we attempted to discover hapten-specific VRs by creating a collection of VR models for anonymous testing. Chlorpyrifos and model-14G4 were employed as the known hit and active VRs, respectively. After molecular docking, a novel anti-chlorpyrifos VR (model-1) was identified due to its satisfactory energy scoring and a similar binding pattern to the reference model-14G4. Expressed by HEK293(F) mammalian cells, the newly prepared full-length rAb-model-1 and rAb-14G4 exhibited high sensitivities for detecting chlorpyrifos by the indirect competitive enzyme-linked immunosorbent assay (ic-ELISA), with IC50 of 3.01 ng/mL and 42.82 ng/mL, respectively. They recognized chlorpyrifos-methyl with a cross-reactivity (CR) of 2.5-17.3%. Moreover, the binding properties of rAb-model-1 for recognizing chlorpyrifos and chlorpyrifos-methyl were confirmed via a non-competitive microscale thermophoresis (MST) method. Thus, the experimental results showed good agreement with computational outputs on antibody profiling. Furthermore, the recognition diversity of rAb-model-1 for chlorpyrifos and chlorpyrifos-methyl was studied via molecular dynamics simulation. Overall, the proposed study provides a versatile and economical strategy for antibody characterization and promotes the in vitro production of rAbs for pesticide monitoring.

Longitudinal real world correlation study of blood pressure and novel features of cerebral magnetic resonance angiography by artificial intelligence analysis on elderly cognitive impairment.

Objective: This study aims to investigate novel clinical risk factors for cognitive impairment (CI) in elderly. Methods: A total of 3221 patients (259 patients with CI and 2,962 subjects without CI) were recruited into this nested case-control study who underwent cerebral magnetic resonance angiography (MRA) from 2007 to 2021. All of the clinical data with MRA imaging were recorded followed by standardization processing blindly. The maximum stenosis score of the posterior circulatory artery, including the basilar artery, and bilateral posterior cerebral artery (PCA), was calculated by the cerebral MRA automatic quantitative analysis method. Logistic regression (LR) analysis was used to evaluate the relationship between risk factors and CI. Four machine learning approaches, including LR, decision tree (DT), random forest (RF), and support vector machine (SVM), employing 5-fold cross-validation were used to establish CI predictive models. Results: After matching with age and gender, 208 CI patients and 208 control subjects were finalized the follow-up (3.46 ± 3.19 years) with mean age at 84.47 ± 6.50 years old. Pulse pressure (PP) in first tertile (<58 mmHg) (OR 0.588, 95% confidence interval (CI): 0.362-0.955) was associated with a decreased risk for CI, and ≥50% stenosis of the left PCA (OR 2.854, 95% CI: 1.387-5.872) was associated with an increased risk for CI after adjusting for body mass index, myocardial infarction, and stroke history. Based on the means of various blood pressure (BP) parameters, the performance of the LR, DT, RF and SVM models accurately predicted CI (AUC 0.740, 0.786, 0.762, and 0.753, respectively) after adding the stenosis score of posterior circulatory artery. Conclusion: Elderly with low pulse differential pressure may have lower risk for cognitive impairment. The hybrid model combined with the stenosis score of posterior circulatory artery, clinical indicators, and the means of various BP parameters can effectively predict the risk of CI in elderly individuals.

Self-Powered Carbon Ink/Filter Paper Flexible Humidity Sensor Based on Moisture-Induced Voltage Generation.

Cellulose paper-based materials are highly flexible, hydrophilic, low-cost, and environmentally friendly and are good substrates for use as humidity sensors. Therefore, developing a paper-based humidity sensor with facile fabrication, low cost, and high sensitivity is important for expanding its practical applications. Herein, we propose a CI/FP self-powered humidity sensor based on everyday items such as writing and drawing carbon ink (CI), cellulose filter paper (FP), and polyester conductive adhesive tape, which is fabricated with the help of facile dip-coating and pasting methods. This sensor is self-powered, and the paper-based material itself can absorb water molecules in a humid environment to generate humidity-related voltage and current, which can indirectly reflect the ambient humidity level. They are characterized by a wide relative humidity (RH) sensing range (11-98%), good linearity (R2 = 0.97011), high response voltage (0.19 V), and excellent flexibility (over 1000 bends). This humidity sensor can be successfully applied to monitor human health (breathing, coughing), air humidity, and noncontact humidity sensing (skin, wet objects). This work not only proposes a low-cost and facile method for flexible humidity sensors but also provides a valuable strategy for the development of self-powered wearable electronics.

Computer-aided profiling of a unique broad-specific antibody and its application to an ultrasensitive fluoroimmunoassay for five N-methyl carbamate pesticides.

Pollution of N-methyl carbamate (NMC) pesticides is threatening the non-target organisms' survival. Thus, broad-specific antibodies and class-selective immunoassays are demanding for multiple NMCs determination. In this study, we employed a molecular docking-based virtual screening strategy to fast profile antibody spectrum, based on a designed chemical pool containing 17 compounds. A monoclonal antibody (mAb)-6G against carbofuran was used as the objective. The recombinant full-length IgG was successfully expressed to validate the antibody sequences for homology modeling. After docking, we manually categorized the antibody-chemical binding strength into three groups. Non-competitive surface plasmon resonance (SPR) demonstrated the mAb-6G affinitive binding toward five NMCs (carbofuran, isoprocarb, propoxur, carbaryl and carbosulfan), which were classified into strong and moderate binding categories. Antibody binding properties were confirmed again by ic-ELISA and lateral flow immunochromatographic strip. Subsequently, an ultrasensitive indirect competitive fluoromicrosphere-based immunoassay (ic-FMIA) was established with the IC50 (half-maximal inhibitory concentration) values of 0.08-3.37 ng/mL. This portable assay presented a 30-230-fold improved sensitivity than traditional ic-ELISA and was applied in European surface water analysis. Overall, our work provides an efficient platform integrating in-silico and experimental methodologies to accelerate the characterization of hapten-specific antibody binding properties and the development of high-sensitive immunoassays for multi-pollutants monitoring.

Deep Learning-Based Morphological Classification of Endoplasmic Reticulum Under Stress.

Endoplasmic reticulum stress (ER stress) is a condition that is defined by abnormal accumulation of unfolded proteins. It plays an important role in maintaining cellular protein, lipid, and ion homeostasis. By triggering the unfolded protein response (UPR) under ER stress, cells restore homeostasis or undergo apoptosis. Chronic ER stress is implicated in many human diseases. Despite extensive studies on related signaling mechanisms, reliable image biomarkers for ER stress remain lacking. To address this deficiency, we have validated a morphological image biomarker for ER stress and have developed a deep learning-based assay to enable automated detection and analysis of this marker for screening studies. Specifically, ER under stress exhibits abnormal morphological patterns that feature ring-shaped structures called whorls (WHs). Using a highly specific chemical probe for unfolded and aggregated proteins, we find that formation of ER whorls is specifically associated with the accumulation of the unfolded and aggregated proteins. This confirms that ER whorls can be used as an image biomarker for ER stress. To this end, we have developed ER-WHs-Analyzer, a deep learning-based image analysis assay that automatically recognizes and localizes ER whorls similarly as human experts. It does not require laborious manual annotation of ER whorls for training of deep learning models. Importantly, it reliably classifies different patterns of ER whorls induced by different ER stress drugs. Overall, our study provides mechanistic insights into morphological patterns of ER under stress as well as an image biomarker assay for screening studies to dissect related disease mechanisms and to accelerate related drug discoveries. It demonstrates the effectiveness of deep learning in recognizing and understanding complex morphological phenotypes of ER.

Characterization of Variable Region Genes and Discovery of Key Recognition Sites in the Complementarity Determining Regions of the Anti-Thiacloprid Monoclonal Antibody.

Sequence-defined recombinant antibodies (rAbs) have emerged as alternatives to hybridoma-secreted monoclonal antibodies (mAbs) for performing immunoassays. However, the polyploidy nature of hybridomas often leads to the coexistence of aberrant or non-specific functional variable region (VR) gene transcripts, which complicates the identification of correct VR sequences. Herein, we introduced the use of LC-MS/MS combined with next-generation sequencing to characterize VR sequences in an anti-thiacloprid mAb, which was produced by a hybridoma with genetic antibody diversity. The certainty of VR sequences was verified by the functional analysis based on the recombinant antibody (rAb) expressed by HEK293 mammalian cells. The performance of the rAb was similar to that of the parental mAb, with IC50 values of 0.73 and 0.46 µg/L as measured by ELISAs. Moreover, molecular docking analysis revealed that Ser52 (H-CDR2), Trp98, and Trp93 (L-CDR3) residues in the complementarity determining regions (CDRs) of the identified VR sequences predominantly contributed to thiacloprid-specific recognition through hydrogen bonds and the CH-π interaction. Through single-site-directed alanine mutagenesis, we found that Trp98 and Trp93 (L-CDR3) showed high affinity to thiacloprid, while Ser52 (H-CDR2) had an auxiliary effect on the specific binding. This study presents an efficient and reliable way to determine the key recognition sites of hapten-specific mAbs, facilitating the improvement of antibody properties.

Application of Deep Learning for Early Screening of Colorectal Precancerous Lesions under White Light Endoscopy.

METHODS: We collected and sorted out the white light endoscopic images of some patients undergoing colonoscopy. The convolutional neural network model is used to detect whether the image contains lesions: CRC, colorectal adenoma (CRA), and colorectal polyps. The accuracy, sensitivity, and specificity rates are used as indicators to evaluate the model. Then, the instance segmentation model is used to locate and classify the lesions on the images containing lesions, and mAP (mean average precision), AP50, and AP75 are used to evaluate the performance of an instance segmentation model. RESULTS: In the process of detecting whether the image contains lesions, we compared ResNet50 with the other four models, that is, AlexNet, VGG19, ResNet18, and GoogLeNet. The result is that ResNet50 performs better than several other models. It scored an accuracy of 93.0%, a sensitivity of 94.3%, and a specificity of 90.6%. In the process of localization and classification of the lesion in images containing lesions by Mask R-CNN, its mAP, AP50, and AP75 were 0.676, 0.903, and 0.833, respectively. CONCLUSION: We developed and compared five models for the detection of lesions in white light endoscopic images. ResNet50 showed the optimal performance, and Mask R-CNN model could be used to locate and classify lesions in images containing lesions.

Kinetics of electric field induced vertical orientation of halloysite nanotubes in photocurable nanocomposites.

The fast transient evolution of electric field assisted vertical orientation and assembly of halloysite nanotubes (HNTs) in a photo-curable matrix is investigated using a custom-built real-time birefringence measurement system. The effect of applied electric field strength and HNT loadings on the kinetics of orientation and organization of halloysite nanotubes into nanocolumns is systematically investigated. The following organization in the matrix is frozen by curing the precursor under ultraviolet (UV) light. The final structure is characterized by scanning electron microscopy (SEM) and wide angle X-ray scattering (WAXS). The nanocomposite films show vertically oriented and aligned HNTs due to the electric field. The orientation factor of HNTs decreases with the increase of particle concentration due to the higher viscosity and stronger inter-particle interaction.

Anisotropic swelling wound dressings with vertically aligned water absorptive particles.

A multi-layer solution casting method was utilized to fabricate a three-layer wound dressing film consisting of a wound contact layer, an absorbing layer and a backing layer. The absorbing layer, whose function is to absorb and retain the exudate thus providing a moist environment for wound healing, was made of superabsorbent particles and a thermoplastic polyurethane matrix. In this study, the superabsorbent particles were aligned into chains whose axes oriented along the thickness direction of the film by an external electric field. This structure could minimize the lateral swelling of the absorbing layer while preferentially expanding in the thickness direction during the water absorption process, and therefore eliminate the lateral stress or shear induced friction between the films and the wound. When compared to the wound dressing films with non-aligned particles, the films with aligned particles could achieve up to 33% smaller lateral expansion. The effect of particle shape on anisotropic swelling was also investigated, and the rod-like particles with higher aspect ratio were more effective at improving the anisotropic swelling and reducing lateral expansion compared to irregular-shaped particles. Additionally, the imprinted patterns on the contact layer resulting from the electric field alignment process promoted the efficiency of absorbing and transporting the exudate into the absorbing layer.

An efficient and robust hybrid method for segmentation of zebrafish objects from bright-field microscope images.

Accurate segmentation of zebrafish from bright-field microscope images is crucial to many applications in the life sciences. Early zebrafish stages are used, and in these stages the zebrafish is partially transparent. This transparency leads to edge ambiguity as is typically seen in the larval stages. Therefore, segmentation of zebrafish objects from images is a challenging task in computational bio-imaging. Popular computational methods fail to segment the relevant edges, which subsequently results in inaccurate measurements and evaluations. Here we present a hybrid method to accomplish accurate and efficient segmentation of zebrafish specimens from bright-field microscope images. We employ the mean shift algorithm to augment the colour representation in the images. This improves the discrimination of the specimen to the background and provides a segmentation candidate retaining the overall shape of the zebrafish. A distance-regularised level set function is initialised from this segmentation candidate and fed to an improved level set method, such that we can obtain another segmentation candidate which preserves the explicit contour of the object. The two candidates are fused using heuristics, and the hybrid result is refined to represent the contour of the zebrafish specimen. We have applied the proposed method on two typical datasets. From experiments, we conclude that the proposed hybrid method improves both efficiency and accuracy of the segmentation of the zebrafish specimen. The results are going to be used for high-throughput applications with zebrafish.

Three-dimensional reconstruction and measurements of zebrafish larvae from high-throughput axial-view in vivo imaging.

High-throughput imaging is applied to provide observations for accurate statements on phenomena in biology and this has been successfully applied in the domain of cells, i.e. cytomics. In the domain of whole organisms, we need to take the hurdles to ensure that the imaging can be accomplished with a sufficient throughput and reproducibility. For vertebrate biology, zebrafish is a popular model system for High-throughput applications. The development of the Vertebrate Automated Screening Technology (VAST BioImager), a microscope mounted system, enables the application of zebrafish high-throughput screening. The VAST BioImager contains a capillary that holds a zebrafish for imaging. Through the rotation of the capillary, multiple axial-views of a specimen can be acquired. For the VAST BioImager, fluorescence and/or confocal microscopes are used. Quantitation of a specific signal as derived from a label in one fluorescent channel requires insight in the zebrafish volume to be able to normalize quantitation to volume units. However, from the setup of the VAST BioImager, a specimen volume cannot be straightforwardly derived. We present a high-throughput axial-view imaging architecture based on the VAST BioImager. We propose profile-based 3D reconstruction to produce 3D volumetric representations for zebrafish larvae using the axial-views. Volume and surface area can then be derived from the 3D reconstruction to obtain the shape characteristics in high-throughput measurements. In addition, we develop a calibration and a validation of our methodology. From our measurements we show that with a limited amount of views, accurate measurements of volume and surface area for zebrafish larvae can be obtained. We have applied the proposed method on a range of developmental stages in zebrafish and produced metrical references for the volume and surface area for each stage.

Roll-to-Roll Continuous Manufacturing Multifunctional Nanocomposites by Electric-Field-Assisted "Z" Direction Alignment of Graphite Flakes in Poly(dimethylsiloxane).

A roll-to-roll continuous process was developed to manufacture large-scale multifunctional poly(dimethylsiloxane) (PDMS) films embedded with thickness direction ("Z" direction) aligned graphite nanoparticles by application of electric field. The kinetics of particle "Z" alignment and chain formation was studied by tracking the real-time change of optical light transmission through film thickness direction. Benefiting from the anisotropic structure of aligned particle chains, the electrical and thermal properties of the nanocomposites were dramatically enhanced through the thickness direction as compared to those of the nanocomposites containing the same particle loading without electrical field alignment. With 5 vol % graphite loading, 250 times higher electrical conductivity, 43 times higher dielectric permittivity, and 1.5 times higher thermal conductivity was achieved in the film thickness direction after the particles were aligned under electrical field. Moreover, the aligned nanocomposites with merely 2 vol % graphite particles exhibit even higher electric conductivity and dielectric permittivity than those of the nonaligned nanocomposites at random percolation threshold (10 vol % particles), as the "electric-field-directed" percolation threshold concentration is substantially decreased using this process. As the graphite loading increases to 20 vol %, the aligned nanocomposites exhibit thermal conductivity as high as 6.05 W/m·K, which is 35 times the thermal conductivity of pure matrix. This roll-to-roll electric field continuous process provides a simple, low-cost, and commercially viable method to manufacture multifunctional nanocomposites for applications as embedded capacitor, electromagnetic (EM) shielding, and thermal interface materials.

Hierarchical Electrospun and Cooperatively Assembled Nanoporous Ni/NiO/MnOx/Carbon Nanofiber Composites for Lithium Ion Battery Anodes.

A facile method to fabricate hierarchically structured fiber composites is described based on the electrospinning of a dope containing nickel and manganese nitrate salts, citric acid, phenolic resin, and an amphiphilic block copolymer. Carbonization of these fiber mats at 800 °C generates metallic Ni-encapsulated NiO/MnOx/carbon composite fibers with average BET surface area (150 m(2)/g) almost 3 times higher than those reported for nonporous metal oxide nanofibers. The average diameter (∼900 nm) of these fiber composites is nearly invariant of chemical composition and can be easily tuned by the dope concentration and electrospinning conditions. The metallic Ni nanoparticle encapsulation of NiO/MnOx/C fibers leads to enhanced electrical conductivity of the fibers, while the block copolymers template an internal nanoporous morphology and the carbon in these composite fibers helps to accommodate volumetric changes during charging. These attributes can lead to lithium ion battery anodes with decent rate performance and long-term cycle stability, but performance strongly depends on the composition of the composite fibers. The composite fibers produced from a dope where the metal nitrate is 66% Ni generates the anode that exhibits the highest reversible specific capacity at high rate for any composition, even when including the mass of the nonactive carbon and Ni(0) in the calculation of the capacity. On the basis of the active oxides alone, near-theoretical capacity and excellent cycling stability are achieved for this composition. These cooperatively assembled hierarchical composites provide a platform for fundamentally assessing compositional dependencies for electrochemical performance. Moreover, this electrospinning strategy is readily scalable for the fabrication of a wide variety of nanoporous transition metal oxide fibers.

Roll to Roll Electric Field "Z" Alignment of Nanoparticles from Polymer Solutions for Manufacturing Multifunctional Capacitor Films.

A roll to roll continuous processing method is developed for vertical alignment ("Z" alignment) of barium titanate (BaTiO3) nanoparticle columns in polystyrene (PS)/toluene solutions. This is accomplished by applying an electric field to a two-layer solution film cast on a carrier: one is the top sacrificial layer contacting the electrode and the second is the polymer solution dispersed with BaTiO3 particles. Flexible Teflon coated mesh is utilized as the top electrode that allows the evaporation of solvent through the openings. The kinetics of particle alignment and chain buckling is studied by the custom-built instrument measuring the real time optical light transmission during electric field application and drying steps. The nanoparticles dispersed in the composite bottom layer form chains due to dipole-dipole interaction under an applied electric field. In relatively weak electric fields, the particle chain axis tilts away from electric field direction due to bending caused by the shrinkage of the film during drying. The use of strong electric fields leads to maintenance of alignment of particle chains parallel to the electric field direction overcoming the compression effect. At the end of the process, the surface features of the top porous electrodes are imprinted at the top of the top sacrificial layer. By removing this layer a smooth surface film is obtained. The nanocomposite films with "Z" direction alignment of BaTiO3 particles show substantially increased dielectric permittivity in the thickness direction for enhancing the performance of capacitors.

Transparent and through thickness conductive polystyrene films using external magnetic fields for "Z" alignment of nickel nanoparticles.

A combination of transparency, electrical conductivity and flexibility is desired in the emerging flexible electronics industry for current and future applications. In this paper, we report the development of through thickness electrical conductivity in polystyrene films filled with nickel nanopowder by external magnetic field application. This process leads to the formation of nanocolumns of nickel spanning across the thickness direction while generating nanoparticle depleted regions in between. This leads to directionally dependent enhancement in optical light transmission particularly in the normal direction of the films. With the use of as little as 2 wt% (0.22 vol%) nickel we were able to achieve high through thickness conductivity under the influence of a magnetic field. While these films exhibit high through thickness conductivity they remain non-conductive in their planes as a result of the unique nanomorphology created which eliminates potential side branch formations. These films are anticipated to be used as electrodes for touch screens, electric dissipative materials for electronic packaging and other sensors.

Large-scale roll-to-roll fabrication of ordered mesoporous materials using resol-assisted cooperative assembly.

Roll-to-roll (R2R) processing enables the rapid fabrication of large-area sheets of cooperatively assembled materials for production of mesoporous materials. Evaporation induced self-assembly of a nonionic surfactant (Pluronic F127) with sol-gel precursors and phenolic resin oligomers (resol) produce highly ordered mesostructures for a variety of chemistries including silica, titania, and tin oxide. The cast thick (>200 µm) film can be easily delaminated from the carrier substrate (polyethylene terephthalate, PET) after cross-linking the resol to produce meter-long self-assembled sheets. The surface areas of these mesoporous materials range from 240 m(2)/g to >1650 m(2)/g with these areas for each material comparing favorably with prior reports in the literature. These R2R methods provide a facile route to the scalable production of kilograms of a wide variety of ordered mesoporous materials that have shown potential for a wide variety of applications with small-batch syntheses.