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Organisationseinheit der BAM
A facile yet robust synthesis is reported herein to simultaneously incorporate atomically dispersed Co-Nₓ sites with graphitic layer-protected Co₉S₈ nanoparticles (denoted as Co SACs+Co₉S₈) as an efficient electrocatalyst for oxygen reduction in acidic solution. The Co SACs+Co₉S₈ catalyst shows low H₂O₂ selectivity (∼5 %) with high half-wave potential (E1/2) of ∼0.78 V(RHE) in 0.5 M H₂SO₄. The atomic sites of the catalyst were quantified by a nitrite stripping method and the corresponding site density of the catalyst is calculated to be 3.2×10¹⁸ sites g⁻¹. Besides, we also found the presence of a reasonable amount of Co₉S₈ nanoparticles is beneficial for the oxygen electrocatalysis. Finally, the catalyst was assembled into a membrane electrode assembly (MEA) for evaluating its performance under more practical conditions in proton exchange membrane fuel cell (PEMFC) system.
Optimizing the properties of next-generation high-temperature and corrosion-resistant alloys is rooted in balancing structure-property relationships and phase chemistry. Here, we implement a complementary approach based on transmission electron microscopy (TEM) and atom probe tomography (APT) to ascertain aspects of hierarchical phase separation behavior, by understanding the microstructural evolution and the three-dimensional (3D) nanochemistry of a single crystal Fe79.5Si15.5V5.0 (at%) alloy. A maze-like hierarchical microstructure forms, in which a complex network of metastable disordered α plates (A2 phase) emerges within ordered α1 precipitates (D03 phase). The supersaturation in α1 (D03) precipitates with Fe and V drives the formation of α (A2) plates. The morphology of α (A2) plates is discussed concerning crystal structure, lattice misfit, and elastic strain. Phase compositions and a ternary phase diagram aid the thermodynamic assessment of the hierarchical phase separation mechanism via the Gibbs energy of mixing. A perspective on the stabilization of hierarchical microstructures beyond Fe79.5Si15.5V5.0 is elaborated by comparing hierarchical alloys. We find that the ratio of elastic anisotropy (Zener ratio) serves as a predictor of the hierarchical particles’ morphology. We suggest that the strengthening effect of hierarchical microstructures can be harnessed by improving the temporal and thermal stability of hierarchical particles. This can be achieved through phase-targeted alloying aiming at the hierarchical particles phase by considering the constituents partitioning behavior. Beyond Fe79.5Si15.5V5.0, our results demonstrate a potential pathway for improving the properties of high-temperature structural materials.
The core−shell NaYF4:Yb3+/Tm3+@NaYF4:Yb3+ upconversion nanoparticles were successfully prepared by a solvothermal method, and a layer of mesoporous silica (mSiO2) was successfully coated on the periphery of the core−shell nanoparticles to transform their surface from lipophilic to hydrophilic, further expanding their applications in biological tissues. The physical phase, morphology, structure, and fluorescence properties were characterized by X-ray diffraction (XRD), field emission transmission electron microscopy (TEM), Fourier infrared spectroscopy (FT-IR), ζ potential analysis, and fluorescence spectroscopy. It was found that the material has a hexagonal structure with good hydrophilicity and emits intense fluorescence under 980 nm pump laser excitation. The non-contact temperature sensing performance of nanoparticles was evaluated by analyzing the upconversion fluorescence of Tm3+ (1G4 → 3F4 and 3F3 → 3H6) in the temperature range of 284−344 K. The absolute and relative sensitivities were found to be 0.0067 K−1 and 1.08 % K−1, respectively, with high-temperature measurement reliability and good temperature cycling performance. More importantly, its temperature measurement in phosphate-buffered saline (PBS) solution is accurate. In addition, the temperature of the cells can be increased by adjusting the laser power density and laser irradiation time. Therefore, an optical temperature sensing platform was built to realize the application of real-time monitoring of cancer cell temperature and the dual function of photothermal therapy.
The NaYF4: Yb3+/Tm3+@NaYF4@β-CD upconversion nanoparticles were successfully prepared by the solvothermal method, and the samples were pure hexagonal phase with good crystallinity and homogeneous size, asevidenced by XRD and TEM analysis. The FT-IR analysis shows that β-CD is successfully encapsulated on the surface of NaYF4: Yb3+/Tm3+@NaYF4 nanoparticles. The fluorescence intensity 3and lifetime were significantly increased after coating the inert layer on the surface of core nanoparticles. After further surface modification of β-CD, the fluorescence intensity and fluorescence lifetime were reduced, but the overall fluorescence was stronger. Temperature measurements using the fluorescence intensity ratio technique were found to have relatively low reliability and absolute sensitivity for temperature measurements using thermally coupled energy levels. However, the reliability of temperature measurements using non-thermally coupled energy levels is significantly higher and the absolute sensitivity is much higher than for measurements at thermally coupled levels. Since the maximum absolute sensitivity, maximum relative sensitivity and minimum temperature resolution are determined to be 0.1179 K-1, 2.19 %K 1 and 0.00019 K, respectively, NaYF4: Yb3+/Tm3+@NaYF4@β-CD upconversion nanoparticles are expected to be widely used in the biomedical field due to their feasibility, reliability, non-toxicity and harmlessness.
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.