Heteroatom doping in hexagonal boron nitride (h-BN) films has been regarded as an effective solution to adjust their electrical and optical properties for realizing applications in various technologies. A high-temperature annealing process is routinely utilized to enhance the doping efficiency following film growth, which is, however, accompanied by other unexpected effects. Thus, understanding the dopant behavior induced by temperature is crucial for unlocking unprecedented development of h-BN. Here, we report the thermally induced mutual diffusion in Si-doped h-BN films grown on sapphire substrates, which can facilitate the transition from the hexagonal to the cubic phase. Spectral analysis indicates that as the annealing temperature increases, the doped films undergo a phase transition from hexagonal to cubic BN phases via an intermediate of explosive BN. Combined x-ray photoelectron spectroscopy and secondary ion mass spectrometry reveal that the thermal annealing above 1000 °C induces the interdiffusion of Si and Al through the interface, where the latter originates from the decomposition of the sapphire substrate. First-principles calculations reveal that the substitution of Si within BN reduces the energy barrier from sp2 to sp3 phase transformation by supplying electrons to adjacent N atoms. This work provides novel insights into understanding the doping behavior in h-BN films and the development of h-BN based devices.

Two-dimensional boron–carbon–nitrogen (BCN) materials represent a versatile class of layered compounds that bridge the electronic and structural characteristics of graphene and hexagonal boron nitride. Among these, the BC 2 N stoichiometry offers highly tunable properties but remains unexplored. We report a first-principles investigation of monolayer BC 2 N, exploring eleven possible atomic configurations. Phonon and ab initio molecular dynamics simulations reveal six dynamically and thermally stable structures. The stable monolayers display high in-plane stiffness with elastic constants of 252–305 N/m and Young’s moduli between 743 and 844 GPa, achieving ultimate strengths up to 104 GPa. Electronic band structures calculated with the HSE06 functional show that, while one configuration exhibits metallic behavior, the others possess direct band gaps ranging from 0.29 to 2.71 eV. Furthermore, exciton binding energies obtained via the Bethe–Salpeter equation vary from 134 to 471 meV. The spectroscopic limited maximum efficiency (SLME) analysis reveals promising photovoltaic performance, with specific structural phases achieving efficiencies of 20.5% and 31.5%. These findings demonstrate the tunable mechanical, electronic, and optical properties of BC 2 N monolayers and their potential for next-generation optoelectronic and solar energy harvesting devices.

Polytetrafluoroethylene composites with enhanced thermal conductivity and low dielectric constant enabled by hexagonal boron nitride and hollow silica@nanodiamond fillers

High-temperature solar selective absorption coatings based on high-entropy boron nitride TaNbZrCrTiBN

Integrated synthesis, theoretical modelling and experimental assessment of boron nitride nanosheets- SnO2 nanocomposites for high-performance photodetector applications

Z-scheme heterojunction nanozyme comprising a porphyrin-based metal-organic framework on defect-enriched porous boron nitride for simultaneous detection and elimination of pollutants

Boron nitride meeting Fe: defect-induced interfacial electronic tuning for enhanced Fenton-like reaction

Synergistic Fe Cu dual-metal sites on boron nitride for boosted redox cycling in Fenton-like reactions

Research on single photon sources in layered materials has been limited so far to transition metal dichalcogenides (TMDs) and hexagonal boron nitride (hBN) as hosting platforms. These quantum emitters exhibit advantages due to the distinct semiconducting and insulating characteristics of the two classes of materials, which enable their integration with van der Waals heterostructures and devices. Here, we report single photon emission in ZnPS3, which belongs to the MPX3 family characterized by stronger electronic correlations than those observed intrinsically in TMDs or hBN. We provide a comprehensive characterization of the vibrational and optical properties of nonmagnetic ZnPS3 crystals, focusing on unraveling the mechanisms responsible for the single photon emission. Using polarization-resolved Raman scattering spectroscopy, we identify key phonon modes and uncover strong metal-ligand interactions that influence both phonon dynamics and defect-bound excitonic states. Low-temperature photoluminescence spectroscopy reveals stable and narrow optical transitions localized at defect sites, while second-order correlation measurements confirm the quantum nature of the emission. We complement our experimental analysis with ab initio density functional and GW many-body perturbation theory calculations to investigate the characteristics of the bulk and defect-related electronic structure. Our theoretical analysis reveals that phosphorus vacancies introduce midgap states, enabling optical transitions occurring at the energy range consistent with the experimentally observed emission lines. This joint approach identifies P-vacancies as the likely origin of single photon emitters in ZnPS3. Furthermore, we anticipate that similar behavior should be present in other MPX3 compounds, offering a framework for exploring defect-based quantum emitters with intrinsic magnetic tunability.

Negatively charged boron vacancies (VB-) in hexagonal boron nitride (hBN) comprise a promising quantum sensing platform, optically addressable at room temperature and transferable onto samples. However, broad hyperfine-split spin transitions of the ensemble pose challenges for quantum sensing with conventional resonant excitation due to limited spectral coverage. While VB- in isotopically enriched hBN using 10B and 15N isotopes (h10B15N) exhibits sharper spectral features, significant inhomogeneous broadening persists. We demonstrate that, implemented via frequency modulation on an FPGA, a frequency-ramped microwave pulse achieves around 4-fold greater |0⟩→|-1⟩ spin-state population transfer and thus contrast than resonant microwave excitation and thus 16-fold shorter measurement time for spin relaxation-based quantum sensing. Quantum dynamics simulations reveal that an effective two-state Landau-Zener model captures the complex relationship between population inversion and pulse length with relaxations incorporated. Our approach is robust and valuable for quantum relaxometry with spin defects in hBN, especially in noisy environments.

Single-atom catalysts are often framed as isolated reactive sites that maximize atom efficiency in chemical transformations. A less explored role is their function as growth directors, viz., atomic-scale agents that bias nucleation pathways, steer incorporation events, and shape early-stage morphologies with precision beyond that of nanoparticles. The strongest experimental evidence comes from graphene, where advanced scanning tunneling and scanning/transmission electron microscopies enable direct tracking of atoms at growth edges and kinks, linking configurations to stepwise growth. First-principles studies on Rh(111) propose that transition-metal single atoms, particularly Mo, can promote productive feeding species such as diatomic carbon and boron nitride (BN) dimers, lower kinetic barriers during early h-BN-graphene lateral heterostructure growth, and influence boundary chemistry. This perspective reframes single atoms as growth directors, distills the mechanistic insights established for graphene, extends them to emerging heterostructures, and outlines criteria for identifying single-atom-directed growth, providing a basis for the rational design of atomically precise 2D interfaces.

The role of nickel substrate thickness in determining the thickness of CVD-grown boron nitride films

Ion adsorption on the surfaces of 2D materials is crucial for applications in ion sieving, electrochemical sensing, and synthesis of abnormal 2D crystals. However, achieving tunable cation adsorption on 2D materials remains challenging. Using first principles calculations, we reveal that electrostatic potentials enable tunable adsorption of alkali metal cations on graphene and hexagonal boron nitride (hBN) surfaces. Negative potentials markedly strengthen the adsorption for all three cations on both substrates, whereas positive potentials weaken the adsorption. Remarkably, the adsorption enhancement under negative potentials is larger on hBN than on graphene, which is attributed to the much greater charge transfer from hBN to cations. Molecular orbital analysis indicates that in cation@hBN system the HOMO is mainly localized on the N atoms and LUMO centers on the adsorbed cation, making cations on hBN more prone to reduction, while the delocalized HOMO and LUMO in cation@graphene systems hinder the π electron departure from graphene. Moreover, electrostatic potentials can modulate interlayer spacing in cation-intercalated graphene and hBN bilayers: negative potentials contract the spacing and positive potentials expand it. These findings illuminate ion adsorption on 2D material surfaces and offer a feasible strategy to regulate ion adsorption and interlayer spacing in 2D layered membranes.

Nanoconfined water plays a key role in nanofluidics, electrochemistry, and catalysis, yet its reactivity remains a matter of debate. Prior studies have reported both enhanced and suppressed water self-dissociation relative to the bulk, but without a consistent explanation. Here, using enhanced sampling molecular dynamics with machine-learned potentials trained at first-principles accuracy, we investigate dissociation behavior in water confined within two-dimensional slit pores and nanodroplets, using graphene and hexagonal boron nitride as model materials. We find that reactivity is extremely sensitive to water density, geometry, and surface chemistry, among other factors. Despite this complexity, we show that chemical potential, together with interfacial interactions, governs dissociation trends and explains the variability observed in prior studies. Within this framework, when confined water is compared to the bulk at equivalent chemical potential, corresponding to thermodynamic equilibrium with a bulk reservoir, its reactivity remains essentially unchanged; rather, differences arise when the systems are compared at different chemical potentials or under distinct interfacial conditions. This thermodynamic perspective reconciles previous contradictions and reveals how nanoscale environments can drastically shift water reactivity. Our findings provide molecular-level insight and offer a design lever for modulating water chemistry at the nanoscale.

Inelastic electron tunneling (IET) provides an efficient route for electroluminescence (EL) in van der Waals (vdW) heterostructures, yet the microscopic origin of its bias-polarity dependence remains elusive due to structural asymmetry in prior devices. Here, we report a pronounced bias-polarity-selective EL in structurally symmetric graphene/hexagonal boron nitride (h-BN)/graphene tunneling junctions coupled to CrSBr; light emission is observed exclusively under positive bias and is fully quenched under negative bias. We demonstrate that strong interfacial charge transfer between CrSBr and the adjacent graphene electrode induces Fermi-level pinning and asymmetric band alignment, which enhances both the IET probability and energy transfer efficiency under positive bias while suppressing them under negative bias. The control device based on monolayer WSe2 exhibits nearly symmetric EL, confirming this mechanism. Our results establish interfacial charge transfer as a pivotal and tunable parameter governing IET-driven light emission and provide a general framework for engineering bias-polarity-selective optoelectronic functionalities in vdW heterostructures.

Cubic boron nitride (c-BN) is a promising catalyst or catalyst substrate with good thermal, chemical, and mechanical stability. However, the large bandgap (Eg) limits its photocatalytic activity under visible light, but it is able to work in the UV region or can be used as a composite with other narrow Eg semiconductors. In this theoretical study, we investigate the structural, electronic, optical, and thermodynamic properties of c-BN nanoparticles using density functional theory (DFT) calculations within the CASTEP and Dmol3 frameworks. The computed Raman, FTIR, and XRD spectra confirm a cubic zinc-blende-like structure of c-BN. Electronic structure calculations using generalized gradient approximations (GGA), B3LYP, and HSE06 functionals show a direct bandgap of 4.533 eV (GGA/PBE), 4.381 eV (B3LYP), and 4.507 eV (HSE06), consistent with UV-limited absorption, and illustrate its limited visible-light absorption. Density of states and electron localization function analyses highlight the polar covalent B─N bonding and charge distribution, revealing that boron p-orbital states are dominant in the conduction band (CB) while nitrogen p-orbital states are mostly available in the valance band (VB), and this inequality of state distribution makes B atoms good electron acceptors and N atoms good donors during the catalysis process. Thermodynamic properties also indicate thermal stability and suitability for high-temperature catalysis. Phonon dispersion analysis also confirms dynamical stability, with no imaginary frequencies. Optical property analysis shows a broad and intense absorption peak, high dielectric response, and low reflectivity, which suggests a favorable electron-hole separation. A wide band edge alignment of c-BN relative to water redox potentials suggests that c-BN can drive the generation of reactive oxygen species, which support its potential in photocatalysis, such as water splitting and pollutant degradation.

Thermal interfaces for wearable thermoelectric generators must efficiently transfer heat from the skin while remaining comfortable, yet conventional materials sacrifice breathability for higher thermal conductivity. Here, we develop a breathable thermal interface using electrohydrodynamic printing of liquid metal (LM)-boron nitride (BN)-thermoplastic polyurethane (TPU) composites. The resulting microscale lattice creates localized contact points with the skin, enabling air and moisture transport while maintaining continuous thermal pathways. The composite incorporates thermally conductive, electrically insulating fillers, yielding a through-plane thermal conductivity of 0.37 W·m-1·K-1. When integrated into wearable thermoelectric generators, the printed interface acts as both a compliant thermal interface and a patterned heatsink, supporting heat transfer while preserving skin compatibility. Guided by multiphysics modeling, the device generates a power density of 0.43 μW·cm-2 at thermal equilibrium from an initial temperature difference of 10 °C. The device can be disassembled to recover and reuse both composite constituents and thermoelectric elements without measurable performance loss. This work highlights an interface design approach that prioritizes breathability and skin compatibility in flexible thermoelectric devices, with further improvements in power output and mechanical robustness needed for practical deployment.

The exponential demand for energy-efficient and adaptive computing architectures drives the evolution of artificial intelligence (AI) and machine learning (ML). Neuromorphic computing, inspired by biological neural networks, overcomes the limitations of traditional von Neumann architectures, including high energy consumption and limited scalability. The introduction of two-dimensional (2D) materials, such as transition metal dichalcogenides, hexagonal boron nitride, black phosphorus, and tellurene, enables neuromorphic devices with unprecedented control over electronic and optoelectronic properties. These materials exhibit atomic-scale thickness, high carrier mobility, and tunable bandgaps, facilitating synaptic behaviours such as spike-timing-dependent plasticity and paired-pulse facilitation. This review describes the integration of 2D materials into neuromorphic systems, highlighting applications in wearable electronics, brain-machine interfaces, and quantum neuromorphic platforms. In wearable and edge computing, 2D-based devices enable localized, ultra-low-power data processing. In brain-machine interfaces, they enhance signal transduction and neural interfacing. Quantum effects in 2D materials further enable hybrid quantum-classical neuromorphic architectures for high-dimensional computational tasks. Despite significant advances, challenges in reproducibility, scalability, and stability remain. Addressing these limitations through innovations in synthesis and defect passivation is essential for practical application. This review underscores the transformative potential of 2D-material-based neuromorphic computing for energy-efficient AI. Integration of 2D materials into neuromorphic computing architectures offers a promising pathway toward energy-efficient and adaptive systems that bridge biological learning mechanisms with machine intelligence.

The development of high-power-density equipment necessitates efficient thermal management. Phase change materials (PCMs), despite their high latent heat and isothermal operation, face application challenges due to low thermal conductivity, leakage, and poor flexibility. In this study, a flexible phase change film was successfully prepared by electrospinning meta-aramid nanofibers (PMIA) and poly(ethylene glycol) (PEG). The introduction of a small amount of boron nitride nanosheets (BNNS) as thermal conductive fillers constructed a continuous network within the fibers, which significantly enhanced the heat transfer capability of the composite. The composite film could achieve a relatively high thermal conductivity of 1.96 W/(m·K) and a phase transition enthalpy value of 59.5 J·g-1 with the addition of extremely low boron nitride (9 wt %). After 50 melt-curing cycles, the melting enthalpy and crystallization enthalpy only decreased by 1.2%, demonstrating promising cycle stability. Meanwhile, this composite film featured notable flexibility, with an elongation at break of 83%, and possessed good mechanical adaptability. This composite material shows promise for thermal management in high-power-density electronic devices and thermoelectric conversion systems.

In situ detection of paramagnetic ions, including ions and biological macromolecules, is critical for fundamental research and applications in biology, chemistry, and medicine. The negatively charged boron vacancy (VB-) defects in hexagonal boron nitride (hBN) have emerged as versatile, highly sensitive quantum sensors for detecting various physical quantities. To further extend the scope and make practical applications of the quantum sensing, in this work, we demonstrate in situ quantum detection of the paramagnetic Mn2+ ions and ferritin in both solution and dry states using VB- defects in hBN. The experiments show that the optically detected magnetic resonance (ODMR) contrasts of VB- defects decrease with increasing concentrations of Mn2+ and ferritin in solution states; however, the ODMR contrasts remain unchanged in the case of dry states. This phenomenon is attributed to magnetic-noise-induced depopulation and modulated solution conductivity by solution paramagnetic ions. At the same time, the spin longitudinal relaxation rates monotonically increase with concentration in both solution and dried states as a function of ions concentration due to the magnetic noise from paramagnetic ions. Moreover, VB- defects can also distinguish different ionic species based on their distinct relaxation rates, requiring no prior knowledge. Finally, the all-optical relaxation method is also adopted to efficiently detect ferritin and paramagnetic ions. Collectively, our work establishes VB- defects in hBN-based sensors as a versatile quantum sensing platform for different species of paramagnetic ions in biology and chemistry, offering dual-modal detection methods including ODMR and T1 relaxation with operational flexibility and high sensitivity.