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The development of efficient and cost-effective catalysts for hydrogen evolution reaction (HER) is crucial for the advancement of electrochemical water splitting technology. Here, we report a novel synthetic method for the preparation of single-crystalline NiCoP nanorods with tunable aspect ratios using a CO-assisted, trioctylphosphine (TOP)-mediated approach. The introduction of CO gas at different temperatures allows for the control of the nanorod growth, resulting in various aspect ratios while maintaining a hexagonal crystal structure and a composition of 1:1 Ni/Co as NiCoP. Our results demonstrate that the NiCoP nanorods with higher aspect ratios exhibit improved HER activity and stability, with the highest aspect ratio nanorods showing the lowest overpotential and Tafel slope in both acidic and alkaline media. This study highlights the importance of controlling the size and morphology of bimetallic phosphide nanoparticles to optimize their catalytic activity for HER, providing new insights into the design and optimization of nanostructured catalysts for electrochemical water splitting applications. 

Abstract Photoconductive emitters for terahertz generation hold promise for highly efficient down-conversion of optical photons because it is not constrained by the Manley-Rowe relation. Existing terahertz photoconductive devices, however, faces limits in efficiency due to the semiconductor properties of commonly used GaAs materials. Here, we demonstrate that large bandgap semiconductor GaN, characterized by its high breakdown electric field, facilitates the highly efficient generation of terahertz waves in a coplanar stripline waveguide. Towards this goal, we investigated the excitonic contribution to the electro-optic response of GaN under static electric field both through experiments and first-principles calculations, revealing a robust excitonic Stark shift. Using this electro-optic effect, we developed a novel ultraviolet pump-probe spectroscopy for in-situ characterization of the terahertz electric field strength generated by the GaN photoconductive emitter. Our findings show that terahertz power scales quadratically with optical excitation power and applied electric field over a broad parameter range. We achieved an optical-to-terahertz conversion efficiency approaching 100% within the 0.03–1 THz bandwidth at the highest bias field (116 kV/cm) in our experiment. Further optimization of GaN-based terahertz generation devices could achieve even greater optical-to-terahertz conversion efficiencies. 

We address a maximally structured case of the question, “Can you hear your location on a manifold,” posed by Wyman and Xi [Can you hear your location on a manifold?, https://arxiv.org/abs/2304.04659, 2023] for dimension $2$. In short, we show that if a compact surface without a boundary sounds the same at every point, then the surface has a transitive action by the isometry group. In the process, we show that you can hear your location on Klein bottles and that you can hear the lengths and multiplicities of looping geodesics on compact hyperbolic quotients. 

Pavement surface distresses are analyzed by transportation agencies to determine section performance across their pavement networks. To efficiently collect and evaluate thousands of lane-miles, automated processes utilizing image-capturing techniques and detection algorithms are applied to perform these tasks. However, the precision of this novel technology often leads to inaccuracies that must be verified by pavement engineers. Developments in artificial intelligence and machine learning (AI/ML) can aid in the progress of more robust and precise detection algorithms. Deep learning models are efficient for visual distress identification of pavement. With the use of 2D/3D pavement images, surface distress analysis can help train models to efficiently detect and classify surface distresses that may be caused by traffic loading, weather, aging, and other environmental factors. The formation of these distresses is developing at a higher rate in coastal regions, where extreme weather phenomena are more frequent and intensive. This study aims to develop a YOLOv5 model with 2D/3D images collected in the states of Louisiana, Mississippi, and Texas in the U.S. to establish a library of data on pavement sections near the Gulf of Mexico. Images with a resolution of 4096 × 2048 are annotated by utilizing bounding boxes based on a class list of nine distress and non-distress objects. Along with emphasis on efforts to detect cracks in the presence of background noise on asphalt pavements, six scenarios for augmentation were made to evaluate the model’s performance based on flip probability in the horizontal and vertical directions. The YOLOv5 models are able to detect defined distresses consistently, with the highest mAP50 scores ranging from 0.437 to 0.462 throughout the training scenarios. 

Abstract Understanding how evolution shapes genetic networks to create new developmental forms is a central question in biology. Flowering shoot (inflorescence) architecture varies significantly across plant families and is a key target of genetic engineering efforts in many crops^1–4. Asteraceae (sunflower family), comprising 10% of flowering plants, all have capitula, a novel inflorescence that mimics a single flower^5,6. Asteraceae capitula are highly diverse but are thought to have evolved once via unknown mechanisms^7,8. During capitulum development, shoot stem cells undergo prolonged proliferation to accommodate the formation of intersecting spirals of flowers (florets) along the disk-shaped head^9,10. Here we show that capitulum evolution paralleled decreases in CLAVATA3 (CLV3) peptide signaling, a conserved repressor of stem cell proliferation. We trace this to novel amino acid changes in the mature CLV3 peptide which decrease receptor binding and downstream transcriptional outputs. Using genetically tractable Asteraceae models, we show that reversion ofCLV3to a more active form impairs Asteraceae stem cell regulation and capitulum development. Additionally, we trace the evolution ofCLV3and its receptors across the Asterales allowing inferences on capitulum evolution within this lineage. Our findings reveal novel mechanisms driving evolutionary innovation in plant reproduction and suggest new approaches for genetic engineering in crop species. 

In this paper, we design and analyze the conforming and nonconforming virtual element methods for the Signorini problem. Under some regularity assumptions, we prove optimal order a priori error estimates in the energy norm for both two numerical schemes. Extensive numerical tests are presented, verifying the theory and exploring unknown features.