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At least 37 records · Page 2

Quasi-elastic neutron scattering study on dynamically asymmetric polymer blends

Compatibility between polymers with different glass transition temperatures controls the thermomechanical properties of blends. This work explores the segmental dynamics of poly(methyl acrylate) (PMA) chains when they are blended with polymers of different rigidities and miscibility. Inspired by the intriguing dynamic asymmetry of chains within the interfacial layer of nanoparticles, this study aims to understand dynamic heterogeneity in dynamically asymmetric blends of PMA/poly(methyl methacrylate) (PMMA), PMA/polystyrene (PS), and PMA/poly(ethylene oxide) (PEO) using the differential scanning calorimetry (DSC) and quasi-elastic neutron scattering (QENS) measurements below and above the glass transition temperature of PMMA or PS. Further, results revealed that the segmental jump distance of PMA increased on blending due to volume enhancement. The reduced effective diffusivity of PMA in PMMA is attributed to PMMA's enhanced flexibility (lower characteristic ratio, C ∞ ) and superior interaction (lower ) when compared with the PS environment. The results demonstrate that the chain rigidity and miscibility affect the free volume, interchain cooperativity, and segmental dynamics in dynamically asymmetric blends.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗

Localized and Collective Dynamics in Liquid-like Polyethylenimine-Based Nanoparticle Organic Hybrid Materials

In this work, broadband dielectric spectroscopy, rheology, and nuclear magnetic resonance spectroscopy are employed to study molecular dynamics in a nanoparticle organic hybrid materials(NOHMs)system comprising 20 wt% silica nanoparticles ionically-bonded to a polyethylenimine canopy. By comparing the neat polymer (used as a canopy) to the derivative NOHMs, we find that timescales characterizing segmental dynamics in the NOHM are identical to those for the neat polymer. Detailed analysis of the carbon-spin lattice relaxation times yields mechanistic insights into localized and collective dynamics, in quantitative agreement with dielectric results. Interestingly, the NOHMs retain liquid-like characteristics unlike conventional polymer nanocomposites but exhibit higher viscosity due to additional contributions from tethered polymer chains, and mesoscopic structuring. These findings demonstrate the potential of achieving unique and desired material properties via NOHMs by an informed choice of the canopy material.

36 MATERIALS SCIENCE↗

Experimental study of UV induced tensile properties deterioration and chemical aging of polyurea–POSS composites

Ultraviolet (UV) radiation present in natural sunlight degrades the chemical and mechanical properties of polymeric matrices in composites. Polyurea possess a unique set of chemical and mechanical properties due to its complex microstructure comprising of hard and soft segments (phases). The primary objective of the work presented here is to characterize the chemical and mechanical degradation of pure polyurea and polyurea - polyhedral oligomeric silsesquioxane (POSS) nanocomposites subjected to UV radiation exposure for 45 days. Control specimen in as-received condition (reference specimen) and UV-aged tensile test specimen are tested in the study. Analysis of Fourier transformed infrared (FTIR) spectra for UV-aged polyurea and polyurea-POSS composites reveals that the addition of POSS nanoparticles accelerate the deterioration of polyurea matrix by breaking the hard phase network and altering the mechanism of degradation for the soft phase present in polyurea microstructure. The deterioration of hard and soft segments cause a significant reduction in tensile properties of polyurea-POSS composites.

Materials Science↗

Dynamic Implications of Noncovalent Interactions in Amphiphilic Single-Chain Polymer Nanoparticles

Single-chain polymer nanoparticles (SCNPs) combine the chemical diversity of synthetic polymers with the intricate structure of biopolymers, generating versatile biomimetic materials. The mobility of polymer chain segments at length scales similar to secondary structural elements in proteins is critical to SCNP structure and thus function. However, the influence of noncovalent interactions used to form SCNPs (e.g., hydrogen-bonding and biomimetic secondary-like structure) on these conformational dynamics is challenging to quantitatively assess. To isolate the effects of noncovalent interactions on SCNP structure and conformational dynamics, we synthesized a series of amphiphilic copolymers containing dimethylacrylamide and monomers capable of forming these different interactions: (1) di(phenylalanine) acrylamide that forms intramolecular β-sheet-like cross-links, (2) phenylalanine acrylamide that forms hydrogen-bonds but lacks a defined local structure, and (3) benzyl acrylamide that has the lowest propensity for hydrogen-bonding. Each SCNP formed folded structures comparable to those of intrinsically disordered proteins, as observed by size exclusion chromatography and small angle neutron scattering. The dynamics of these polymers, as characterized by a combination of dynamic light scattering and neutron spin echo spectroscopy, was well described using the Zimm with internal friction (ZIF) model, highlighting the role of each noncovalent interaction to additively restrict the internal relaxations of SCNPs. These results demonstrate the utility of local scale interactions to control SCNP polymer dynamics, guiding the design of functional biomimetic materials with refined binding sites and tunable kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

Abstract Automatic segmentation of key microstructural features in atomic-scale electron microscope images is critical to improved understanding of structure–property relationships in many important materials and chemical systems. However, the present paradigm involves time-intensive manual analysis that is inherently biased, error-prone, and unable to accommodate the large volumes of data produced by modern instrumentation. While more automated approaches have been proposed, many are not robust to a high variety of data, and do not generalize well to diverse microstructural features and material systems. Here, we present a flexible, semi-supervised few-shot machine learning approach for segmentation of scanning transmission electron microscopy images of three oxide material systems: (1) epitaxial heterostructures of SrTiO 3 /Ge, (2) La 0.8 Sr 0.2 FeO 3 thin films, and (3) MoO 3 nanoparticles. We demonstrate that the few-shot learning method is more robust against noise, more reconfigurable, and requires less data than conventional image analysis methods. This approach can enable rapid image classification and microstructural feature mapping needed for emerging high-throughput characterization and autonomous microscope platforms.

36 MATERIALS SCIENCE↗

Cross-reactive sarbecovirus antibodies induced by mosaic RBD nanoparticles

Broad immune responses are needed to mitigate viral evolution and escape. To induce antibodies against conserved receptor-binding domain (RBD) regions of SARS-like betacoronavirus (sarbecovirus) spike proteins that recognize SARS-CoV-2 variants of concern and zoonotic sarbecoviruses, we developed mosaic-8b RBD nanoparticles presenting eight sarbecovirus RBDs arranged randomly on a 60-mer nanoparticle. Mosaic-8b immunizations protected animals from challenges from viruses whose RBDs were matched or mismatched to those on nanoparticles. Here, we describe neutralizing mAbs isolated from mosaic-8b-immunized rabbits, some on par with Pemgarda, the only currently FDA-approved therapeutic mAb. Deep mutational scanning, in vitro selection of spike resistance mutations, and single-particle cryo-electron microscopy structures of spike–antibody complexes demonstrated targeting of conserved RBD epitopes. Rabbit mAbs included critical D-gene segment RBD-recognizing features in common with human anti-RBD mAbs, despite rabbit genomes lacking an equivalent human D-gene segment, thus demonstrating that the immune systems of humans and other mammals can utilize different antibody gene segments to arrive at similar modes of antigen recognition. These results suggest that animal models can be used to elicit anti-RBD mAbs with similar properties to those raised in humans, which can then be humanized for therapeutic use, and that mosaic RBD nanoparticle immunization coupled with multiplexed screening represents an efficient way to generate and select broadly cross-reactive therapeutic pan-sarbecovirus and pan-SARS-CoV-2 variant mAbs.

Science & Technology - Other Topics↗

Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images

Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since these complex models may have difficultly learning meaningful image features that would enable extension to new datasets. In situ electron microscopy provides a clear platform for utilizing automated image analysis. In this work, we consider the case of studying coarsening dynamics in supported nanoparticles, which is important for understanding, for example, the degradation of industrial catalysts. By systematically studying dataset preparation, neural network architecture, and accuracy evaluation, we describe important considerations in applying deep learning to physical applications, where generalizable and convincing models are required. With a focus on unique challenges that arise in high-resolution images, we propose methods for optimizing performance of image segmentation using convolutional neural networks, critically examining the application of complex deep learning models in favor of motivating intentional process design.

36 MATERIALS SCIENCE↗

Nonlinear Architectures Can Alter the Dynamics of Polymer–Nanoparticle Composites

Polymer nanocomposites exhibit remarkable physical properties that are attractive for many applications. These systems have been so far investigated by using linear polymer chains; the role of polymer matrix architecture on local dynamics, bulk rheology and nanoparticle motion remains unexplored. Here, using quasielastic neutron scattering, bulk rheology and x-ray photon correlation spectroscopy, we investigated nanocomposites with spherical silica nanoparticles well dispersed in poly (ethylene oxide) matrices having different architectures (specifically linear, stars and hyperbranched). The results reveal that the mechanical reinforcement of the nanocomposites with the nonlinear polymers can be altered by orders of magnitude with respect to the conventional nanocomposite with the linear polymer. Additionally, the polymer compactness and inter-penetrability are found to play crucial roles in determining their bulk rheology. At microscopic level, average segmental dynamics is remarkably slowed down by the attractive NPs in the matrices of high degree of branching whereas no significant effect is observed in linear polymer matrix at the same NP loading. In addition, the nanoscale dynamics of particles in the compact nonlinear matrices exhibit strong decoupling from the bulk viscoelasticity, allowing their fast relaxation even at ≈ 30% by volume. These results provide an experimental evidence that macromolecular architecture is a powerful new tool for tuning the bulk rheological properties as well as the nanoscale dynamics of PNCs without the need for changing polymer molecular weight, nanoparticle size, shape, loading or dispersion state.

36 MATERIALS SCIENCE↗

A Mesopore-Confined and Graphene Oxide-Localized Ruthenium Catalyst Increases Rates of Mid-Chain Polyolefin Hydrogenolysis

A catalyst architecture with mesoporous silica coating Ru nanoparticles on reduced graphene oxide (mSiO 2 /Ru/rGO) localizes the 2 nm Ru solely at the closed bottoms of 2.9 nm diameter mesopores. mSiO 2 /Ru/rGO catalyzes the rapid, selective hydrogenolysis of polyolefins at wax formation rates (ν wax ) up to 1700 g wax ·g Ru –1 ·h –1 and a turnover frequency (TOF) for C–C bond cleavage of 130 ± 8 min –1 . The ν wax and TOF for mSiO 2 /Ru/rGO are 23× and 16× those of nonporous Ru/rGO, respectively, indicating that faster chain cleavage is also more selective inside mesopores. The methane yield from mSiO 2 /Ru/rGO is ca. 30% of the value obtained from Ru/rGO. Methane decreases, and wax selectivity improves with narrow-pore (2.3 nm) mSiO 2 /Ru/rGO. The reaction rate decreases at lower and higher H 2 pressures from its maximum at 37 bar. Log(TOF)-log(P H2 ) plots reveal rates ∝ [P H2 ] 2.8 or [P H2 ] −2.0 in the lower or higher pressure ranges, respectively. Corresponding plots for Ru/C give rates ∝ [P H2 ] 1 or [P H2 ] −2.4 . Ru is hydrocarbon-covered at low pressure; thus, the higher H 2 order for mSiO 2 /Ru/rGO indicates that mesopores increase the density of cleavable unsaturated moieties on the Ru surface. The lower H 2 order on Ru/C implies a lower density of cleavable groups because saturated segments occupy a larger fraction of the Ru surface. Higher surface occupancy by the hydrocarbon reactant correlates with more methane formation. Therefore, pore confinement, narrower pore diameter in mSiO 2 /Ru/rGO, or higher H 2 pressure leads to lower methane yields. Ru nanoparticles in mSiO 2 /Ru/rGO maintain equivalent activity and selectivity over five recycling tests.

Catalysts↗

Spatially-resolved dynamic sampling of different phasic magnetic resonances of nanoparticle ensembles in a magnetotactic bacterium Magnetospirillum magnetotacticum

Abstract Nanoscaled magnetic particle ensembles are promising building blocks for realizing magnon based binary logic. Element-specific real-space monitoring of magnetic resonance modes with sampling rates in the GHz regime is imperative for the experimental verification of future complex magnonic devices. Here we present the observation of different phasic magnetic resonance modes using the element-specific technique of time-resolved scanning transmission x-ray microscopy within a chain of dipolarly coupled Fe 3 O 4 nanoparticles (40–50 nm particle size) inside a single cell of a magnetotactic bacterium Magnetospirillum magnetotacticum . The particles are probed with 25 nm resolution at the Fe L 3 x-ray absorption edge in response to a microwave excitation of 4.07 GHz. A plethora of resonance modes is observed within multiple particle segments oscillating in- and out-of-phase, well resembled by micromagnetic simulations.

time-resolved scanning transmission x-ray microsco↗

Dual-Responsive Turn-On T 1 Imaging-Guided Mild Photothermia for Precise Apoptotic Cancer Therapy

Apoptosis has gained increasing attention in cancer therapy as an intrinsic signaling pathway, which leads to minimal leakage of waste products from a dying cell to neighboring normal cells. Among various stimuli to trigger apoptosis, mild hyperthermia is attractive but confronts limitations of non-specific heating and acquired resistance from elevated expression of heat shock proteins. Here, a dual-stimulation activated turn-on T 1 imaging-based nanoparticulate system (DAS) is developed for mild photothermia (≈43 °C)-mediated precise apoptotic cancer therapy. In the DAS, a superparamagnetic quencher (ferroferric oxide nanoparticles, Fe 3 O 4 NPs) and a paramagnetic enhancer (Gd-DOTA complexes) are connected via the N6-methyladenine (m 6 A)-caged, Zn 2+ -dependent DNAzyme molecular device. The substrate strand of the DNAzyme contains one segment of Gd-DOTA complex-labeled sequence and another one of HSP70 antisense oligonucleotide. When the DAS is taken up by cancer cells, overexpressed fat mass and obesity-associated protein (FTO) specifically demethylates the m 6</-sup>A group, thereby activating DNAzymes to cleave the substrate strand and simultaneously releasing Gd-DOTA complex-labeled oligonucleotides. The restored T 1 signal from the liberated Gd-DOTA complexes lights up the tumor to guide the location and time of deploying 808 nm laser irradiation. Afterward, locally generated mild photothermia works in concert with HSP70 antisense oligonucleotides to promote apoptosis of tumor cells. This highly integrated design provides an alternative strategy for mild hyperthermia-mediated precise apoptotic cancer therapy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Leveraging Hydration Forces for Size-Specific Nanoparticle Enrichment with a Redox-Responsive Silica-Binding Elastin-Like Polypeptide

Elastin-like polypeptides (ELPs) are low-complexity proteins that coacervate above a characteristic lower critical solution temperature (LCST). While the thermoresponsiveness of ELPs has been widely exploited in the biomedical and biomaterials fields, their ability to mediate nanoparticle assembly below their transition temperature remains largely unexplored. Here, we show that unmodified ELPs induce the reversible flocculation of silica nanoparticles (SiNPs) by forming backbone hydrogen bonds with surface silanols. Interparticle bridging is modulated by ELP length and concentration and by the presence of N- and C-terminal anchoring groups such as a cysteine residue and a Car9 silica-binding peptide. Using a redox-responsive fusion protein consisting of disulfide-bonded ELP domains terminated by Car9 segments, we stabilize 20 nm SiNPs under oxidizing conditions while triggering particle flocculation upon addition of reductant. We find that SiNP sedimentation under reducing conditions exhibits a sharp dependency on particle size that arises from the curvature-dependent structure of surface silanols. While the isolated silanols of SiNPs smaller than 30 nm are efficiently engaged by the ELP domains of Car9-anchored proteins, repulsion forces associated with the presence of a layer of molecular water together with increased electrostatic repulsion preclude efficient engagement of H-bonded silanols displayed on the surface of SiNPs larger than 60 nm. We harness these findings to selectively enrich SiNPs based on size and expand the concept to titania (TiO2) by demonstrating that rutile nanoparticles can be stabilized or sedimented with solid-binding ELPs by adjusting the solution pH to promote or discourage the formation of a hydration layer. These strategies should prove broadly useful for the separation of other oxides and their polymorphs and provide a tunable strategy for nanoparticle assembly and bioinspired colloidal design.

ELP↗

Effect of surface properties and polymer chain length on polymer adsorption in solution

In polymer nanoparticle composites (PNCs) with attractive interactions between nanoparticles (NPs) and polymers, a bound layer of the polymer forms on the NP surface, with significant effects on the macroscopic properties of the PNCs. The adsorption and wetting behaviors of polymer solutions in the presence of a solid surface are critical to the fabrication process of PNCs. In this study, we use both classical density functional theory (cDFT) and molecular dynamics (MD) simulations to study dilute and semi-dilute solutions of short polymer chains near a solid surface. Using cDFT, we calculate the equilibrium properties of polymer solutions near a flat surface while varying the solvent quality, surface–fluid interactions, and the polymer chain lengths to investigate their effects on the polymer adsorption and wetting transitions. Using MD simulations, we simulate polymer solutions near solid surfaces with three different curvatures (a flat surface and NPs with two radii) to study the static conformation of the polymer bound layer near the surface and the dynamic chain adsorption process. Additionally, we find that the bulk polymer concentration at which the wetting transition in the poor solvent system occurs is not affected by the difference in surface–fluid interactions; however, a threshold value of surface–fluid interaction is needed to observe the wetting transition. We also find that with good solvent, increasing the chain length or the difference in the surface–polymer interaction relative to the surface–solvent interaction increases the surface coverage of polymer segments and independent chains for all surface curvatures. Finally, we demonstrate that the polymer segmental adsorption times are heavily influenced only by the surface–fluid interactions, although polymers desorb more quickly from highly curved surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Paper-based gold nanoparticles decorated SWCNTs chemiresistive sensor for sensitive detection of As(III) based on electrochemical doping

A paper-based chemiresistive sensor consisting of a single-walled carbon nanotubes network with electrodeposited gold nanoparticles (AuNPs-SWCNTs) was developed for the sensitive detection of As(III). A new sensing strategy was also proposed combined with a paper-based device for As(III) chemiresistive detection based on the electrochemical doping of As(0) on the AuNPs-SWCNTs channel. Here, the proposed paper-based chemiresistive sensor was manufactured by wax printing and vacuum deposition using a water-based SWCNTs ink. The sensor sensitivity was enhanced by optimizing the volume of SWCNTs ink used in the formation of the sensing network in the paper and the sweep segment of cyclic voltammetry used for the electrochemical deposition of AuNPs. Additionally, the mechanism of the sensing strategy based on the electrochemical n-doping of As(0) to the AuNPs-SWCNTs sensing channel was investigated using a liquid-ion gated FET system. The As(III) concentration detected by the as-fabricated chemiresistive sensor is as low as 1.35 × 10 -5 μM which is even lower than the maximum permissible concentration in drinking water defined by the WHO. In this paper, we provide a simple strategy for developing paper-based chemiresistive sensors with unique properties for practical As(III) determination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Correlation between backbone and pyridine dynamics in poly(2-vinyl pyridine)/silica polymer nanocomposites

Polymer segmental dynamics in polymer nanocomposites (PNCs) can be significantly perturbed from bulk and underly macroscopic material properties such as mechanical enhancements and improved small molecule transport, but fundamental studies are necessary to further understand this concept. To elucidate a mechanistic description of this perturbation and isolate different molecular motions, we present quasi-elastic neutron scattering (QENS) measurements on PNCs with attractive interactions comprised of colloidal silica nanoparticles (NPs) uniformly dispersed in poly(2-vinyl pyridine) (P2VP) with and without backbone deuteration. Measurements of fully-protonated P2VP probe the dynamics of both the polymer backbone and pyridine pendant group, whereas measurements of backbone deuterated P2VP isolate the dynamics of only the pyridine ring. On the small length scales (~1 nm) and fast time scales (~1 ns) captured by QENS, we show that the backbone and pyridine ring dynamics are highly coupled at high temperature and both are slowed by about 35% relative to neat polymer in 25 vol% PNCs. This observation implies that the backbone and pendant interfacial dynamics are perturbed similarly in PNCs, which further develops our fundamental understanding of microscopic properties in PNCs.

36 MATERIALS SCIENCE↗

Extreme Nanoconfinement Dramatically Enhances Small Molecule Solubility in Nonpolar Polymers

Elucidating gas solubility in confined polymer systems addresses a fundamental gap in polymer physics and has important implications for gas barrier and separation technologies and polymer upcycling reactions. In this study, we examine the solubility of methanol and n-hexane in polystyrene and low-density polyethylene confined within the interstitial pores of disordered silica nanoparticle packings. Using capillary rise infiltration, these polymers are infiltrated into the nanoparticle packings. Gas solubility in these confined polymers is measured using a quartz crystal microbalance. Remarkably, confinement leads to a 10- to ∼100-fold increase in gas solubility. Systematic experiments reveal that pore size plays a dominant role in increasing solubility. In contrast, the molecular weight of the polymer and the surface wetting characteristics of the nanoparticles, achieved by hydrophobically modifying the nanoparticles, have minimal effects. By systematically varying penetrant polarity, polymer crystallinity, pore size, and nanopore surface chemistry, this study isolates geometric nanoconfinement as the dominant factor governing solubility enhancement in confined polymers. Atomistic simulations revealed that confinement and surface−polymer interactions both contribute to enhanced solubility, with polymer packing playing a significant role in modulating gas uptake. Here, these results suggest that the changes in the molecular arrangements of polymer segments underlie the observed trends. This study highlights the potential of confined polymers in engineering the separation performance of membranes and heterogeneously catalyzed polymer upcycling reactions.

alcohols↗

Amplifying Nanoparticle Reinforcement through Low Volume Topologically Controlled Chemical Coupling

Here, we present a streamlined method to covalently bond hydroxylated carbon nanotubes (CNOH) within a polyphenol matrix, all achieved through a direct, solvent-free process. Employing an extremely small concentration of CNOH (0.01% w/w) along with topologically contrasting linkers led to a maximum of 5-fold increase in modulus and a 25% enhancement in tensile strength compared to the unaltered matrix, an order of magnitude greater reinforcement (w/w) compared to state-of-the-art melt-processed nanocomposites. Through dynamic mechanical analysis, low field solid-state nuclear magnetic resonance spectroscopy, and molecular dynamics simulations, we uncovered the profound influence of linker’s conformational degrees of freedom on the segmental dynamics and therefore the material’s properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗