Effect of ammonium chloride on the morphology of hexagonal boron nitride prepared by magnesium thermal reduction

Hexagonal boron nitride (h-BN) crystals with cylindrical and nanoplate shape were prepared by the magnesium thermal reduction method. A simple and novel strategy successfully controlled the preferred growth direction of h-BN crystal by adding a small amount of ammonium chloride to the reaction system, realized the transformation of the h-BN crystal growth mode from cylindrical to nanoplate, and the thickness of h-BN crystal nanoplates rapidly decreased from 2 μm to 40 nm. XRD results showed that the ammonium chloride content also significantly promoted the crystallinity of the synthesized h-BN nanoplates, and the G.I. index decreased from 2.4 to 1.9. Raman and TEM results showed that the crystallinity of synthesized h-BN was close to the properties of the single crystal.     

Dielectric Environment Sensitivity of Carbon Centers in Hexagonal Boron Nitride

A key advantage of utilizing van-der-Waals (vdW) materials as defect-hosting platforms for quantum applications is the controllable proximity of the defect to the surface or the substrate allowing for improved light extraction, enhanced coupling with photonic elements, or more sensitive metrology. However, this aspect results in a significant challenge for defect identification and characterization, as the defect's properties depend on the the atomic environment. This study explores how the environment can influence the properties of carbon impurity centers in hexagonal boron nitride (hBN). It compares the optical and electronic properties of such defects between bulk-like and few-layer films, showing alteration of the zero-phonon line energies and their phonon sidebands, and enhancements of inhomogeneous broadenings. To disentangle the mechanisms responsible for these changes, including the atomic structure, electronic wavefunctions, and dielectric screening, it combines ab initio calculations with a quantum-embedding approach. By studying various carbon-based defects embedded in monolayer and bulk hBN, it demonstrates that the dominant effect of the change in the environment is the screening of density–density Coulomb interactions between the defect orbitals. The comparative analysis of experimental and theoretical findings paves the way for improved identification of defects in low-dimensional materials and the development of atomic scale sensors for dielectric environments.     

Elaboration of thermophysical performance enhancement mechanism of functionalized boron nitride/graphite hybrid nanofluids

This study mainly investigated the physicochemical characteristics of ethylene glycol/ water (EG/W) based hydroxyl-functionalized boron nitride (BN-OH) and graphite (G) hybrid nanofluids. A novel simple and efficient annealing method was proposed to have hexagonal boron nitride (h-BN) nanoparticles functionalized to improve the synergistic role between hybrid G/BN-OH nanoparticles. Meanwhile, the dispersion stability, thermal stability, and rheological behavior of diverse nanofluids (h-BN, BN-OH, G, G/BN and G/BH-OH) were comprehensively evaluated. The results showed that the G/BN-OH hybrid nanofluids demonstrate both better dispersion stability and thermal stability, as well as a lower increase in viscosity. In addition, the thermal conductivity of G/BN-OH hybrid nanofluids was increased by up to 18.05% with a concentration of 0.2 wt% when compared to the base fluid. Ultimately, the complicated theoretical mechanism of thermophysical performance augment for G/BH-OH hybrid nanofluids was reliably presented. The enhanced thermal conductivity of nanofluids may be attributed to the formation of adsorption layers and the synergistic effect of the thermal conductivity network.     

A Robust n-n Heterojunction: Cu?N and B?N Boosting for Ambient Electrocatalytic Nitrogen Reduction to Ammonia

An n-n type heterojunction comprising with Cu N and B N dual active sites is synthesized via in situ growth of a conductive metal–organic framework (MOF) [Cu₃(HITP)₂] (HITP = 2,3,6,7,10,11-hexaiminotriphenylene) on hexagonal boron nitride (h-BN) nanosheets (hereafter denoted as Cu₃(HITP)₂@h-BN) for the electrocatalytic nitrogen reduction reaction (eNRR). The optimized Cu₃(HITP)₂@h-BN shows the outstanding eNRR performance with the NH₃ production of 146.2 µg h⁻¹ mg_cat⁻¹ and the Faraday efficiency of 42.5% due to high porosity, abundant oxygen vacancies, and Cu N/B N dual active sites. The construction of the n-n heterojunction efficiently modulates the state density of active metal sites toward the Fermi level, facilitating the charge transfer at the interface between the catalyst and reactant intermediates. Additionally, the pathway of NH₃ production catalyzed by the Cu₃(HITP)₂@h-BN heterojunction is illustrated by in situ FT-IR spectroscopy and density functional theory calculation. This work presents an alternative approach to design advanced electrocatalysts based on conductive MOFs.     

Wafer-Scale Single Crystal Hexagonal Boron Nitride Layers Grown by Submicron-Spacing Vapor Deposition

The direct growth of wafer-scale single crystal two-dimensional (2D) hexagonal boron nitride (h-BN) layer with a controllable thickness is highly desirable for 2D-material-based device applications. Here, for the first time, a facile submicron-spacing vapor deposition (SSVD) method is reported to achieve 2-inch single crystal h-BN layers with controllable thickness from monolayer to tens of nanometers on the dielectric sapphire substrates using a boron film as the solid source. In the SSVD growth, the boron film is fully covered by the same-sized sapphire substrate with a submicron spacing, leading to an efficient vapor diffusion transport. The epitaxial h-BN layer exhibits extremely high crystalline quality, as demonstrated by both a sharp Raman E_2g vibration mode (12 cm⁻¹) and a narrow X-ray rocking curve (0.10°). Furthermore, a deep ultraviolet photodetector and a ZrS₂/h-BN heterostructure fabricated from the h-BN layer demonstrate its fascinating properties and potential applications. This facile method to synthesize wafer-scale single crystal h-BN layers with controllable thickness paves the way to future 2D semiconductor-based electronics and optoelectronics.     

六方氮化硼在防腐涂料中的应用研究进展

六方氮化硼(h-BN)具有优异的热稳定性、阻隔性、耐高温性等性能,日益受到各国研究人员的广泛关注.将h-BN引入到当前防腐涂料体系中,有助于提升防腐涂料的性能,因此成为当前防腐涂料领域的研究热点之一.首先介绍了h-BN及其纳米片(BNNSs)的物化性质.接着对BNNSs的"自上而下"和"自下而上"制备方式进行了介绍,并...     

A tubular solar still integrated with a heat pipe

The aim of this work is to explore the thermal performance of a tracked tubular solar still (TSS) with a parabolic trough concentrator in Baghdad (33.27° N, 44.37° E) in September 2022. The present tubular still is distinguished by its hexagonal glass cover. The effect of integrating the TSS with a heat pipe, the still tilt angle (10°, 15°), and the depth of saline water inside the still partitions on the productivity of freshwater are investigated. The results showed that using heat pipe enhances the freshwater productivity by 25%–40% and the efficiency by 25%. For the still integrated with heat pipe, as the water depth is increased from 5.5 to 6.5 cm the productivity of freshwater is increased by 16% and 20% for tilt angles 10° and 15°, respectively.     

High Proton Conductivity in β-Ba2ScAlO5 Enabled by Octahedral and Intrinsically Oxygen-Deficient Layers

Proton conductors are promising materials for clean energy, but most available materials exhibit sufficient conductivity only when chemically substituted to create oxygen vacancies, which often leads to difficulty in sample preparation and chemical instability. Recently, proton conductors based on hexagonal perovskite-related oxides have been attracting attention as they exhibit high proton conductivity even without the chemical substitutions. However, their conduction mechanism has been elusive so far. Herein, taking three types of oxides with different stacking patterns of oxygen-deficient layers (β-Ba₂ScAlO₅, α-Ba₂Sc_0.83Al_1.17O₅, and BaAl₂O₄) as examples, the roles of close-packed double-octahedral layers and oxygen-deficient layers in proton conduction are shown. It is found that “undoped” β-Ba₂ScAlO₅, which adopts a structure having alternating double-octahedral layer and double-tetrahedral layer with intrinsically oxygen-deficient hexagonal BaO (h') layer, shows high proton conductivity (≈10⁻³ S cm⁻¹ above 300 °C), comparable to representative proton conductors. In contrast, the structurally related oxides α-Ba₂Sc_0.83Al_1.17O₅ and BaAl₂O₄ exhibit lower conductivity. Ab initio molecular dynamics simulations revealed that protons in β-Ba₂ScAlO₅ migrate through the double-octahedral layer, while the h′ layer plays the role of a “proton reservoir” that supplies proton carriers to the proton-conducting double-octahedral layers. The distinct roles of the two layers in proton conduction provide a strategy for developing high-performance proton conductors.     

Position-only planar hexagonal array antenna pattern nulling with simultaneous side lobe reduction at multiple azimuth planes

This article presents a study on the placement of multiple nulls as well as minimization of side lobe level in the radiation pattern using a planar hexagonal antenna array structure in two different vertical planes. The desired null depth is achieved to suppress the interference signal by the position-only control of the uniformly excited isotropic antennas in the array structure. The immediate solution to the mentioned computational problem is reached by various meta-heuristic optimization algorithms such as teaching learning-based optimization (TLBO), symbiotic organism search (SOS), and moth fly optimization (MFO) within a considerably reduced processing time with a control over the design constrains. Various examples for diversified scenarios are demonstrated to place multiple deep nulls in the radiation pattern without compromising the pattern constraints and all other radiation pattern characteristics. This experiment sought to illustrate and quantify the unique benefits and limitations of proposed technique using three considered meta-heuristic optimization algorithm.