This work presents innovative findings on the weld overlay cladding of a 9
Electrochemical water splitting is a promising strategy for sustainable hydrogen production; however, it requires efficient and durable non-noble metal electrocatalysts. In this work, we report the controlled synthesis of two-dimensional (2D) CuCo₂O₄ nanosheets (CC-NS) via a Triton X-100-assisted hydrothermal method, highlighting a morphology-engineering approach for enhanced bifunctional catalysis. The surfactant-directed growth enables the formation of a porous, ultrathin spinel architecture composed of nanocrystalline domains with uniformly distributed Cu and Co species. Structural and surface analyses (XRD, FESEM, TEM, EDS, and XPS) confirm a phase-pure cubic spinel structure with mixed-valence Co²⁺/Co³⁺ and Cu²⁺ states, which contribute to improved interfacial charge transfer and catalytic activity. In 1 M KOH, the CC-NS electrode delivers overpotentials of 280 mV for HER and 530 mV for OER at 50 mA cm⁻², demonstrating competitive bifunctional performance at relatively high current densities. The enhanced activity is attributed to the synergistic interplay between nanosheet morphology, porous structure, and mixed-metal redox chemistry. This study provides a rational design strategy for developing morphology-controlled spinel oxides as cost-effective electrocatalysts for alkaline water splitting.
The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) aims to detect the coherent scattering (CE nu NS) of reactor antineutrinos off silicon nuclei using thick fully depleted high-resistivity silicon CCDs. Two Skipper-CCD sensors with subelectron readout noise capability were installed at the experiment next to the Angra-2 reactor in 2021, making CONNIE the first experiment to employ Skipper-CCDs for reactor neutrino detection. We report on the performance of the Skipper-CCDs, the new data processing, data quality, and event selection for CE nu NS interactions, which enable CONNIE to reach a record low detection threshold of 15 eV. The data were collected over 300 days in 2021-2022 and correspond to exposures of 14.9 g-days with the reactor-on and 3.5 g-days with the reactor-off. The difference between the reactor-on and off event rates shows no excess and yields upper limits for the neutrino interaction rates, comparable with previous CONNIE limits from standard CCDs and higher exposures. Searches for new neutrino interactions beyond the Standard Model improve the previous CONNIE limit on a simplified model with light vector mediators. A first dark matter (DM) search by diurnal modulation by CONNIE obtains the best limits on the DM-electron scattering cross section by a surface-level experiment. These promising results, obtained using a very small-mass sensor, illustrate the potential of Skipper-CCDs to probe rare neutrino interactions and motivate the plans to increase the detector mass in the near future.
This work integrates computational simulations with a hybrid machine learning framework to investigate the nonlinear relationships between plasmonic layer geometry, refractive index variations, and spectral response in a photonic crystal fiber (PCF) surface plasmon resonance (SPR) sensor. The proposed approach achieves reliable detection of small refrative index chances from a simple yet optimized PCF SPR sensing structure, reaching competitive sensitivity levels in the refractive index range of 1.33–1.39. Accurate predictions were obtained with R^2> 0.99 and minimal error ( ϵ < 0.1 ). A central contribution of this work is the simultaneous optimization of multiple optical metrics. Beyond maximizing wavelength sensitivity, the methodology balances sensitivity, figure of merit, Q-factor, and FWHM. This multiobjective strategy enables precise tailoring of the plasmonic layer geometry, producing sharp resonances, high-quality factors, and robust performance. Overall, the results demonstrate how plasmonic engineering in photonic crystal fibers can drive high-performance SPR sensing platforms. The methodology provides valuable insights into the geometry–plasmonics interplay while opening avenues for practical implementations in biochemical detection, environmental monitoring, and chemical sensing.
This study investigated the enhancement of photovoltaic efficiency of dye-sensitized solar cells (DSSCs) through titanium dioxide (TiO2) anodes composite with iron oxide (Fe2O3). TiO2 with Fe2O3 at different weight percentages (0–30 wt
