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At least 289 records · Page 16

Chemical Vapor Deposition-Grown Hexagonal Boron Nitride and Graphene for Tandem Dielectric Capacitive Polymer Devices

To address the low energy density of polymeric capacitors, this work explores how tandem combinations of antagonistic properties can enhance energy storage. We introduce multilayer architecture integrating chemical vapor deposition (CVD)-grown ≈2 nm hexagonal boron nitride (hBN) and graphene with ferroelectric polyvinylidene fluoride (PVDF) and linear polyetherimide (PEI) layers to suppress leakage paths, reduce loss, and promote Maxwell–Wagner–Sillars polarization. Raman spectroscopy, X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), and plasma focused ion beam (PFIB) analyses confirm robust material integration. In conclusion, for the tandem device, E BD ≈600 V/μm, while individual layers show lower values (PVDF|Graphene (Gr)|PVDF ≈ 50 V/μm and PEI|hBN|PEI ≈ 275 V/μm), yielding an overall ≈6000% enhancement and demonstrating the effectiveness of the 2D multilayer design.

Chemical vapor deposition (CVD)↗

Biopolymer-Templated Titania Film Formation for Nanostructured Coatings Revealed by Machine Learning-Supported Time-Resolved Analysis

This study presents a machine learning approach to derive the film formation of biopolymer-templated titania nanostructures during spray deposition, in combination with in situ grazing-incidence small-angle X-ray scattering (GISAXS). A neural network trained on synthetic GISAXS data directly predicts domain-size distributions from experimental two-dimensional scattering patterns, capturing the full kinetics of nanostructure evolution with high temporal resolution. The predictions reveal hierarchical size distributions and periodic growth features, consistent with layer-by-layer spray deposition and validated by complementary scanning electron microscopy (SEM) imaging. Quantitative comparison with conventional parametric GISAXS fits shows good qualitative agreement, with systematic differences explained by domain-shape assumptions and resolved by applying a geometric scaling factor. Simulated SEM-like surfaces derived from neural network outputs reproduce the porous, foam-like nanoscale morphology observed experimentally, reinforcing the method’s credibility. This integrated approach enables real-time, nondestructive, statistically averaged monitoring of bulk nanostructure development in functional coatings, offering a scalable methodology to accelerate the characterization and process control of sustainably manufactured nanostructured titania films for energy-related applications such as photocatalysis and photovoltaics.

Heger, JulianEliah↗

Confined Growth of DNA-Assembled Superlattice Films

Here, we study the assembly of DNA-functionalized nanocubes under lateral confinement in microscale square trenches on a DNA-functionalized substrate. Microfocus small-angle X-ray scattering (SAXS) and scanning electron microscopy (SEM) are used to characterize the superlattices (SLs). The results indicate that nanocubes form simple-cubic SLs with square-prism morphology and a (100) out-of-plane orientation to maximize DNA bonding. In-plane, SLs align with the template, exposing their {100} side facets, and the degree of alignment depends on trench size. Interestingly, the distribution of in-plane orientations determined from SAXS and SEM do not agree, indicating that the internal and external structures of the SLs differ. To understand this discrepancy, X-ray ptychography is employed to image the internal structures of the SLs, revealing that SLs which appear to be single-crystalline in SEM may have subsurface grain boundaries, depending on trench size. SEM reveals that the SLs grow via nucleation and growth of randomly oriented domains, which then coalesce; this mechanism explains the observed dependence of alignment and defect structure on size. Interestingly, crystallization occurs via an unusual growth mode, whereby continuous SL layers grow on top of several misoriented islands. Overall, this work elucidates the effect of lateral confinement on the crystallization of DNA-functionalized nanoparticles and shows how X-ray ptychography can be used to gain insight into nanoparticle crystallization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonadditive Interactions Unlock Small-Particle Mobility in Binary Colloidal Monolayers

We examine the organization and dynamics of binary colloidal monolayers composed of micron-scale silica particles interspersed with smaller-diameter silica particles that serve as minority component impurities. These binary monolayers are prepared at the surface of ionic liquid droplets over a range of size ratios (σ = 0.16–0.66) and are studied with low-dose minimally perturbative scanning electron microscopy (SEM). The high resolution of SEM imaging provides direct tracking of all particle coordinates over time, enabling a complete description of the microscopic state. In these bidisperse size mixtures, particle interactions are nonadditive because interfacial pinning to the droplet surface causes the equators of differently sized particles to lie in separate planes. By varying the size ratio, we control the extent of nonadditivity in order to achieve phase behavior inaccessible to additive 2D systems. Across the range of size ratios, we tune the system from a mobile small-particle phase (σ < 0.24) to an interstitial solid (0.24 < σ < 0.33) and furthermore to a disordered glass (σ > 0.33). These distinct phase regimes are classified through measurements of hexagonal ordering of the large-particle host lattice and the lattice’s capacity for small-particle transport. Altogether, we explain these structural and dynamic trends by considering the combined influence of interparticle interactions and the colloidal packing geometry. Our measurements are reproduced in molecular dynamics simulations of 2D nonadditive disks, suggesting an efficient method for describing confined systems with reduced dimensionality representations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Carbonyl and Azo-Based Polymer Cathode for Low-Temperature Na-Ion Batteries

Due to flexible structure tunability and abundant structure diversity, redox-active polymers are promising cathode materials for developing affordable and sustainable Na-ion batteries (NIBs). However, polymer cathodes still suffer from low capacity, poor cycle life, and sluggish reaction kinetics. Herein, we designed and synthesized a polymer cathode material bearing carbonyl and azo groups as well as extended conjugation structures in the repeating units. The polymer cathode exhibited exceptional electrochemical performance in NIBs in terms of high capacity, long lifetime, and fast kinetics. When coupled with a low-concentration electrolyte, it shows superior performance at low temperatures down to -50 °C, demonstrating great promise for low-temperature battery applications. Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM) were employed to study the reaction mechanism, interphase structure, and morphological evolution, confirming reversible redox reactions between azo/carbonyl groups in the polymer and Na + /electrons, a NaF-rich interphase, and high structure stability upon cycling. In conclusion, this work provides an effective approach to developing high-performance polymer cathodes for affordable, sustainable, and low-temperature NIBs.

25 ENERGY STORAGE↗

Resolving the Electron Plume within a Scanning Electron Microscope

Scanning electron microscopy (SEM), a century-old technique, is today a ubiquitous method of imaging the surface of nanostructures. However, most SEM detectors simply count the number of secondary electrons from a material of interest, and thereby overlook the rich material information contained within them. Here, by simple modifications to a standard SEM tool, we resolve the momentum and energy information on secondary electrons by directly imaging the electron plume generated by the electron beam of the SEM. Leveraging these spectroscopic imaging capabilities, our technique is able to image lateral electric fields across a prototypical silicon p–n junctions and to distinguish differently doped regions, even when buried beyond depths typically accessible by SEM. Intriguingly, the subsurface sensitivity of this technique reveals unexpectedly strong surface band bending within nominally passivated semiconductor structures, providing useful insights for complex layered component designs, in which interfacial dynamics dictate device operation. Further, these capabilities for noninvasive, multimodal probing of complicated electronic components are crucial in today’s electronic manufacturing but is largely inaccessible even with sophisticated techniques. These results show that seemingly simple SEM can be extended to probe complex and useful material properties.

36 MATERIALS SCIENCE↗

Spatial Distribution and Clustering of Glycosaminoglycans in Electrospun Gelatin-Based Scaffolds

The extracellular matrix (ECM) is comprised of components like collagen, elastin, and glycosaminoglycans (GAGs). Electrospun fibrous scaffolds are designed to replicate the form and composition of the native ECM, often requiring blending of various ECM component mimics to enhance cellular responses. However, the spatial distribution of blended components within these fibers remains unclear. This study investigates the spatial distribution of chondroitin sulfate-C (CSC) in electrospun gelatin-based scaffolds. scanning electron microscopy (SEM), attenuated reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), and Time-of-flight Secondary Ion Mass Spectrometry (ToF-SIMS) were applied for surface and subsurface chemical characterization of the fibrous scaffolds. SEM confirmed a fibrous morphology, while ATR-FTIR and XPS analyses indicated the presence of CSC through the identification of sulfate groups. ToF-SIMS imaging, alongside K-means clustering and Ripley’s K function, revealed a nonuniform CSC distribution with higher concentrations at the top layer of the scaffold. This study demonstrates that CSC presentation at the fiber surface varies with depth and differs from bulk incorporation while reveals nanoscale clustering and spatial heterogeneity at both the surface and subsurface of electrospun gelatin fibers. These findings define an underexplored design consideration with potential to influence cell–scaffold interactions.

Animal derived food↗

Geobacter sulfurreducens Immobilized Boron-Doped Diamond Electrodes for Uranium(VI) in Water Electrochemical Bioremediation

The proliferation of nuclear science and technology has resulted in an increase in nuclear waste containing uranium, posing significant risks to both human and environmental health. This study proposes the use of Geobacter sulfurreducens (G. sulfurreducens) modified boron-doped diamond electrodes to facilitate the reduction and removal of uranium(VI) from aqueous media. The bioremediation process involves electrochemically immobilizing the bacteria on a boron-doped diamond electrode (BDD). The immobilization process requires applying reduction potentials ranging from −0.40 to −0.70 V (vs Ag/AgCl (3 M NaCl)), with −0.60 V identified as the optimal potential for effective bacterial modification. The uranium source is provided by a 2.0 mM uranyl acetate solution in G. sulfurreducens growth medium. Scanning electron microscopy (SEM) reveals a highly uniform layer of uranium on the electrode surface. Energy-dispersive X-ray fluorescence spectroscopy (EDS) and cyclic voltammetry (CV) studies confirm the presence of uranium in the system. Raman spectroscopy and X-ray photoelectron spectroscopy (XPS) successfully elucidate the reduction process of U(VI) to predominantly U(IV) using a bacteria-electrode coupled system. Additionally, a comparison is made with the electrochemical removal of uranyl ions using the electrodeposition method on unmodified BDD. Results demonstrate the presence of three uranium oxide species (UO 2 , UO 3 , and U 3 O 8 ) on the BDD electrode after experimentation, in contrast to the G. sulfurreducens/BDD assembly, which achieves the predominant reduction of UO 2 2+ to UO 2 with a small quantity of UO 3 as the final species. This study highlights the efficient electrochemical removal of uranyl ions from aqueous media at the G. sulfurreducens/BDD interface through chronoamperometry, presenting a promising approach for remediating sites contaminated with radioactive materials. The findings contribute to the exploration of sustainable alternatives for managing nuclear waste, emphasizing the potential of this electrochemical bioremediation strategy.

Bacteria↗

Optimization of La 2 NiO 4+δ Electrolysis Cell Oxygen Electrode through Surfactant-Enabled LaCoO 3±δ Nanocatalyst Deposition

Lanthanum nickelate (LNO) has shown promise as a Cr-resistant air electrode material for SOECs but has suboptimal surface oxygen exchange properties. Nanocoating of the LNO surface with lanthanum cobaltite (LCO) was chosen to improve cell performance as a surface oxygen conductor. The work focused on the implementation of a two-step nano-LCO film deposition utilizing catechol molecules in a porous LNO electrode. The subgoals of the work were to maintain nanosized LCO particles/ grains to increase active surface area and to control the regularity/ homogeneity of the coating across the microstructure. To achieve these goals, a novel surfactant-enhanced liquid infiltration method was utilized, where nucleation sites were spread across the electrode structure to control the location and size of LCO particles. Various catechol surfactant compositions were evaluated for their ability to control the kinetics of nanoparticle deposition and the homogeneity of the coating. Chelated LCO was characterized by X-ray diffraction (XRD), which found a substantial improvement in LCO formation with surfactant addition and determined polymerized norepinephrine to be the best-performing surfactant, with 88.4% pure LCO formed at low temperature. X-ray photoelectron spectroscopy (XPS) confirmed LCO nanostructures formed by the two-step infiltration process, showing no impurities and a stable perovskite structure. Deposition kinetics were analyzed using atomic force microscopy (AFM), correlating infiltration times and solution molarity to nanoparticle size and distribution, the results of which were confirmed in symmetrical cell samples by scanning electron microscopy (SEM). Electrochemical impedance spectroscopy (EIS) testing demonstrated substantial improvements in polarization resistance, where the nanocoating reduced the resistance by ∼55% to 0.152 Ω·cm 2 at 700 °C and 0.039 Ω·cm 2 at 800 °C. Electrical conductivity relaxation (ECR) at this temperature confirmed an improved surface oxygen exchange coefficient of the LCO + LNO heterostructure predicted by the Bode data from EIS, alongside a reduction in activation energy by about 30%.

Deposition↗

Triacetic Acid Lactone and 4-Hydroxycoumarin as Bioprivileged Molecules for the Development of Performance-Advantaged Organic Corrosion Inhibitors

Biomass conversion, especially the development of bioprivileged molecules utilizing integration of biological and chemical processes, has shown potential to produce novel chemicals with enhanced properties. Here, organic corrosion inhibitors based on triacetic acid lactone and 4-hydroxycoumarin have been synthesized in good yield and tested for corrosion inhibition on mild steel in both sulfuric acid and hydrochloric acid. Sixteen novel corrosion inhibitors derived from triacetic acid lactone and 4-hydroxycoumarin were efficiently synthesized and twelve of them showed high corrosion inhibition efficiency as confirmed by electrochemical impedance spectroscopy (giving values greater than 78%) and polarization analysis. While triacetic acid lactone-based compounds showed good corrosion inhibition performance, the 4-hydroxycoumarin-based compounds showed further improvement in corrosion inhibition performance. Scanning electron microscopy (SEM) analysis of the mild steel coupon in the presence of selected inhibitors showed that corrosion was significantly diminished, with complementary X-ray photoelectron spectroscopy (XPS) analysis suggesting the inhibitor molecules strongly adsorbed on the steel surface. Quantum chemical calculations showed poor correlation between calculated parameters and the performance of these molecules. This large set of corrosion inhibitors containing a dozen promising corrosion inhibitors is useful for future rational design of corrosion inhibitors. In conclusion, the results demonstrate a new direction for the development of bioprivileged molecules.

09 BIOMASS FUELS↗

A study of real-world micrograph data quality and machine learning model robustness

Abstract Machine-learning (ML) techniques hold the potential of enabling efficient quantitative micrograph analysis, but the robustness of ML models with respect to real-world micrograph quality variations has not been carefully evaluated. We collected thousands of scanning electron microscopy (SEM) micrographs for molecular solid materials, in which image pixel intensities vary due to both the microstructure content and microscope instrument conditions. We then built ML models to predict the ultimate compressive strength (UCS) of consolidated molecular solids, by encoding micrographs with different image feature descriptors and training a random forest regressor, and by training an end-to-end deep-learning (DL) model. Results show that instrument-induced pixel intensity signals can affect ML model predictions in a consistently negative way. As a remedy, we explored intensity normalization techniques. It is seen that intensity normalization helps to improve micrograph data quality and ML model robustness, but microscope-induced intensity variations can be difficult to eliminate.

36 MATERIALS SCIENCE↗

Accurate segmentation of localized corrosion in structural alloys via deep learning

This study presents a deep learning-based approach for the automated segmentation of corrosion damage in scanning electron microscopy (SEM) images. The proposed method enables rapid and accurate segmentation of corrosion features in these SEM images, making it highly suitable for real-time applications such as automated microscopy. Specifically, a dedicated corrosion segmentation database tailored for this task is constructed. The newly constructed dataset, alongside data from two public databases, are employed to jointly train a deep learning-based model modified with a texture refinement module. Compared to the same model without the texture refinement module, the refined model substantially enhances the efficacy and efficiency of corrosion segmentation. Furthermore, the methodology developed here is extendable to segmentation tasks for other materials with similar resolution, texture, and contrast characteristics, thereby paving the way for accelerated and automated analysis in corrosion science and beyond.

Artificial Intelligence↗

Rapid biodegradation of microplastics generated from bio-based thermoplastic polyurethane

The accumulation of microplastics in various ecosystems has now been well documented and recent evidence suggests detrimental effects on various biological processes due to this pollution. Accumulation of microplastics in the natural environment is ultimately due to the chemical nature of widely used petroleum-based plastic polymers, which typically are inaccessible to biological processing. One way to mitigate this crisis is adoption of plastics that biodegrade if released into natural environments. In this work, we generated microplastic particles from a bio-based, biodegradable thermoplastic polyurethane (TPU-FC1) and demonstrated their rapid biodegradation via direct visualization and respirometry. Furthermore, we isolated multiple bacterial strains capable of using TPU-FC1 as a sole carbon source and characterized their depolymerization products. Finally, to visualize biodegradation of TPU materials as real-world products, we generated TPU-coated cotton fabric and an injection molded phone case and documented biodegradation by direct visualization and scanning electron microscopy (SEM), both of which indicated clear structural degradation of these materials and significant biofilm formation.

09 BIOMASS FUELS↗

Two-step route to size and shape controlled gibbsite nanoplates and the crystal growth mechanism

Mastery of gibbsite (α-Al(OH) 3 ) nucleation and crystal growth is significant in fundamental aluminum chemistry and also beneficial for industrial applications and the remediation of nuclear waste. Herein, we developed an additive-free two-step route to size and morphology controlled synthesis of gibbsite nanoplates. Independent temperature manipulation of nucleation and crystal growth regimes was used to control the efficacy and yield of the process, producing gibbsite nanoplates with tunable morphologies and sizes. We achieve morphologies ranging from hexagon, pseudo hexagon, truncated triangle to rhombic, and average basal plane diameters from 120 to 850 nm, with thicknesses between 8 and 45 nm. Analysis of gibbsite structure, size and morphology with techniques including powder X-ray diffraction (p-XRD), 27 Al magic angle spinning nuclear magnetic resonance spectroscopy (MAS NMR), scanning electron microscopy (SEM), and atomic force microscopy (AFM) provided key details on the nucleation and crystal growth mechanisms. The results indicate the temperature of the nucleation aging step is the most important factor controlling the final particle size. Particularly small nanoplates were obtained with a low nucleation aging temperature followed by high crystal growth temperature, suggesting that gibbsite growth can be approximated via a LaMer-type burst nucleation and crystal growth mechanism. Scalability was demonstrated by triplicate of 2 L experiments which prepared gibbsite nanoplates of ~200 nm size and with an average yield of ~55% after 84 h. Compared to existing techniques, this improved two-step route is cheaper, more efficient and environmentally friendly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Liquid ToF-SIMS revealing the oil, water, and surfactant interface evolution

Bilge water from ships is regarded as a major pollutant in the marine environment. Bilge water exists in a stable oil-in-water (O/W) emulsion form. However, little is known about the O/W liquid–liquid (l–l) interface. Traditional bulk characterization approaches are not capable of capturing the chemical changes at the O/W l–l interface. Although surfactants are deemed essential in droplet formation, their roles in bilge water stabilization have not been fully revealed. We have utilized novel in situ chemical imaging tools including in situ scanning electron microscopy (SEM) and in situ time-of-flight secondary ion mass spectrometry (ToF-SIMS) to study the evolving O/W interface using a NAVY bilge model for the first time. The droplet size distribution (DSD) does not change significantly without the addition of X-100 surfactants under static or rocking conditions. Both the oil components and the water clusters are shown to evolve over time at the O/W droplet interface by in situ liquid SIMS imaging. Of particular interest to droplet stabilization, the contribution of surfactants to the aged bilge droplets becomes more significant as the droplet size increases. The higher mass surfactant component does not appear on the droplet surface immediately while many lower mass surfactants are solvated inside the droplet. We have provided the first three-dimensional images of the evolving O/W interface and demonstrated that in situ surface chemical mapping is powerful enough to reveal the complex and dynamic l–l interface in the liquid state. Our observational insights suggest that surfactants are important in mediating droplet growth and facilitating effective separation of bilge water emulsion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanically tunable elastomer and cellulose nanocrystal composites as scaffolds for in vitro cell studies

Considering the range of properties that various materials offer for tissue engineering it has come clear that no one size fits all, as no one material can be fully effective for all types of cell and ensuing tissues. Scaffolds need to address the delicate balance between cell-scaffold interactions and the particular requirements of different cell types. To address the specific needs for the controlled growth of tissues it is imperative to match scaffold stiffness and elasticity to cells and tissues of interest to promote regeneration success. We here report an efficient method for creating scaffolds of tunable elasticity by generating a range of composites based on ε-caprolactone-D,L-lactide-based elastomer with cellulose nanocrystals (CNC). Two specific composites with different Young's modulus (E) values (~5 MPa and ~15 MPa) were selected and fully evaluated by tensile tests, Fourier Transform-Infrared (FT-IR), Scanning Electron Microscopy (SEM), contact angle measurements, and X-ray scattering. As a proof of concept this work studies how matching the scaffold's mechanical properties to neuroblastomas and fibroblasts cells affects cell behavior. Specifically, the composite with lower E, by design with less CNC content, is more suitable for neuroblastomas, whereas the one with higher E via higher CNC content is more suited for human dermal fibroblasts. The approach of matching cells with appropriate mechanical environments can provide important insights into fundamental cell behaviors.

36 MATERIALS SCIENCE↗

Alignment of Au nanorods along de novo designed protein nanofibers studied with automated image analysis

In this paper, we focus on exploring the directional assembly of anisotropic Au nanorods along de novo designed 1D protein nanofiber templates. Using machine learning and automated image processing, we analyze scanning electron microscopy (SEM) images to study how the attachment density and alignment fidelity are influenced by variables such as the aspect ratio of the Au nanorods, and the salt concentration of the solution. We find that the Au nanorods prefer to align parallel to the protein nanofibers. This preference decreases with increasing salt concentration, but is only weakly sensitive to the nanorod aspect ratio. While the overall specific Au nanorod attachment density to the protein fibers increases with increasing solution ionic strength, this increase is dominated primarily by non-specific binding to the substrate background, and we find that greater specific attachment (nanorods attached to the nanofiber template as compared to the substrates) occurs at the lower studied salt concentrations, with the maximum ratio of specific to non-specific binding occurring when the protein fiber solutions are prepared in 75 mM NaCl concentration.

36 MATERIALS SCIENCE↗

Electrodeposition of ligand-free copper nanoparticles from aqueous nanodroplets

Copper nanoparticles have emerged as promising electrocatalysts for energy storage and conversion. Generally, homogenous nanoparticle synthesis requires a stabilizing ligand, which may influence the electrocatalysis. Ligands can be avoided by direct nanoparticle electrodeposition. Here, we extend nanodroplet-mediated electrodeposition to the electrodeposition of copper nanoparticles from aqueous nanodroplets suspended in 0.1 M tetrabutylammonium hexafluorophosphate ([TBA][PF 6 ]) and 1,2-dichloroethane. Stochastic electrochemistry on microelectrodes was used to elucidate nanoparticle growth kinetics for various solution conditions and substrate materials. A study on the effect of surfactants on nanoparticle morphology and growth kinetics demonstrated the surfactant's role as an avenue for morphological control. Nanoparticle morphology was studied by Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). Energy-dispersive X-ray Spectroscopy (EDX) confirmed the presence of copper nanoparticles. TEM and Selected Area Electron Diffraction (SAED) confirmed nanoparticle size, morphology, and polycrystallinity. We demonstrate tunable nanoparticle size using cyclic voltammetry on single aqueous nanodroplets by altering the voltammetric sweeping potentials of copper electroreduction. Finite element simulations validate the voltammetric response and ability to control the nanoparticle size with nanometer resolution during a voltammetric sweep. These results inform the electrodeposition of copper nanoparticles from aqueous nanodroplets for important applications, such as the conversion of CO 2 to hydrocarbon fuels.

36 MATERIALS SCIENCE↗