MRS Communications最新文献

Nanoparticle diffusion is a fundamental process that ubiquitously exists in life science and engineering technology. Recent studies demonstrate the potential of harnessing mechanical deformation to program nanoparticle diffusion in hydrogels, offering an expanded spectrum of nanoparticle diffusivities with precise and on-demand control. Here, we develop a mechano-diffusion characterization platform (MDCP) that integrates a mechanical system to apply controlled tension and torsion loads to deformable mediums, and an imaging system to capture spatiotemporal diffusion profiles of nanoparticles. Employing the MDCP, we study the impact of mechanical deformation on nanoparticle diffusion in hydrogels subjected to controlled stress states and loading rates.

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Metal oxide nanostructures (MONSTRs) have become popular in various fields. This study investigates the durability of MONSTRs synthesized through hot water treatment (HWT) using copper, aluminum, and zinc as the source metals of choice. The physical durability tests include pressure, scratch, and scotch tape adhesion tests, and chemical durability tests such as corrosion resistance tests, heat resistance, and solar exposure tests. Results showed that MONSTRs synthesized from HWT are highly durable under the tested conditions except for NaOH and HCl immersion tests for copper oxide and zinc oxide. The study concluded that HWT is a sustainable synthesis method for MONSTRs.

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In this study, the experiment and molecular dynamic simulations were used to show how oxygen plasma etching works on diamond-like carbon (DLC) for micro-texturing. On the experimental side, C–C bonds on the DLC were dissociated by the irradiated oxygen. The physical bombardment of reactive oxygen ions selectively removes the carbon atoms in the unmasked area via the generation and desorption of gaseous carbon monoxide and carbon dioxide molecules. Molecular dynamic simulation exhibits the reactivity of O₂ molecules with C atoms in the DLC. The quantity of O₂ molecules and the formation of new molecules (CO) were proven in this simulation.

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Aircraft in both the commercial and defense sectors undergo significant disassembly in order to access and inspect critical structures and components. To limit the extent of disassembly needed and thus increase system availability, the concept of mobile robotic inspection has been notionally discussed for over 20 years. Notably this interest in mobile robotic inspection extends beyond aircraft to include civil infrastructure, pipelines, and nuclear plants where some robotic platforms are currently in use. However, the unique challenges associated with complex aircraft systems and structures remain to be addressed. With advancements in the fields of durable polymers, autonomous materials, flexible electronics, tailorable actuation, and others, soft robotics are an increasingly viable solution to the challenge of inspection in access-limited spaces. This perspective article will overview key advancements in pertinent technical areas and highlight scientific barriers to wide-spread use and acceptance of soft robotics for aircraft inspection.

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The effect of randomly distributed Ca dopants within the BaTiO₃ lattice was investigated using first principle calculations. We examined electronic properties to understand how different orbitals contribute to the conduction and valence bands in doped materials. Our findings indicate that the valence band is primarily composed of Ti-3d and O-2p orbital states, while the conduction band is influenced by the collective contributions of Ba-4d, Ti-3d, and Ca-3d orbital states. Additionally, our results demonstrate a reduction in the bandgap due to Ca doping, with the extent of variation depending on the substituted sites of the Ca atoms. Furthermore, we investigated modifications in optical properties such as absorption, conductivity, dielectric function, refractive index, extinction coefficient, loss function, and reflectivity in the energy range from 0 to 40 eV. The findings reveal the stability of these characteristics in the infrared and visible light regions, and they also depend on the site substitution of Ca cations within the BaTiO₃ lattice. We expected that our findings would deepen the understanding of the mechanism and site effect of Ca dopant on the properties of BaTiO₃ materials, thereby contributing to the development of lead-free ferroelectric materials with enhanced properties for multifunctional applications.

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Stereolithography (SLA) is a highly versatile additive manufacturing technique that utilizes various ink formulations to fabricate 3D-printed nanocomposite structures with desired properties. Zinc oxide (ZnO) is a promising candidate due to its excellent mechanical and thermal stability, and compatibility with various polymeric matrices. In this work, varying ink formulations containing ZnO nanoparticles, along with employing appropriate post-printing curing parameters to fabricate SLA 3D-printed acrylate-based nanocomposites with improved mechanical and thermal properties, were reported. This study can significantly contribute to expanding its potential use in practical applications such as biomedical and structural applications.

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Artificial intelligence and machine learning (ML) continue to see increasing interest in science and engineering every year. Polymer science is no different, though implementation of data-driven algorithms in this subfield has unique challenges barring widespread application of these techniques to the study of polymer systems. In this Prospective, we discuss several critical challenges to implementation of ML in polymer science, including polymer structure and representation, high-throughput techniques and limitations, and limited data availability. Promising studies targeting resolution of these issues are explored, and contemporary research demonstrating the potential of ML in polymer science despite existing obstacles are discussed. Finally, we present an outlook for ML in polymer science moving forward.

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The design of electrode architecture plays a crucial role in advancing the development of next generation energy storage devices, such as lithium-ion batteries and supercapacitors. Nevertheless, existing literature lacks a comprehensive examination of the property tradeoffs stemming from different electrode architectures. This prospective seeks to bridge this gap by focusing on the diverse nanocomposite electrode architectures. Furthermore, the challenges related to designing well-defined electrode architectures for enhanced energy storage are discussed. Finally, this review addresses the interdisciplinary nature of this field by examining the integration of advanced characterization and fabrication techniques, and machine learning methodologies for electrode optimization.

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Designing electrodes with controlled architecture and leveraging emerging tools such as in situ characterization, additive manufacturing methods, and machine learning facilitates the advancement of energy storage systems.

This study presents the synthesis and characterization of the Co supported on CeO₂ nanorods (NR) catalyst to investigate catalytic performance towards efficient hydrogen production. The catalyst was characterized by transmission electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction. Temperature-programmed reduction measurements showed that the Co/CeO₂-NR active phase was reduced below 500°C. Adding Co to CeO₂-NR enhances the basicity of the raw CeO₂-NR and greatly improves the conversion to 70% for CO₂ and 55% for CH₄. In addition, density functional theory calculations using Halgren–Lipscomb indicate electron donation from Co to CeO₂-NR promotes feasible breaking of C–H bonds.

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Extracellular vesicles (EVs) have been explored as promising drug delivery platforms and cell-free therapies for a range of diseases. Despite their therapeutic potential, challenges persist in achieving sustained EV delivery. Here, we integrate EVs into a supramolecular and injectable hydrogel-based drug delivery system based on dodecyl- or octadecyl-modified hydroxypropyl methylcellulose (HPMC-C12 or -C18) that form non-covalent crosslinks with liposomes. Hydrogel mechanics and EV-release kinetics were tunable by varying liposome concentrations. Using mesenchymal stem cell-derived EVs (MSC-EVs), we confirm effective, hydrogel-mediated sustained EV delivery and uptake and a ~ 20% greater anti-inflammatory response in pathogenic vascular smooth muscle cells than bolus EV-only treatment.

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