Boron Nitride Monolayer Research Articles

Density Functional Theory Investigation of 2D Phase Separated Graphene/Hexagonal Boron Nitride Monolayers; Band Gap, Band Edge Positions, and Photo Activity

Density Functional Theory Investigation of 2D Phase Separated Graphene/Hexagonal Boron Nitride Monolayers; Band Gap, Band Edge Positions, and Photo Activity

Controllable Epitaxial Growth of Adlayer-Free Hexagonal Boron Nitride Monolayers on Silicon-Incorporated Ni(111) Substrates for Metal–Insulator–Metal Tunneling Devices

Controllable Epitaxial Growth of Adlayer-Free Hexagonal Boron Nitride Monolayers on Silicon-Incorporated Ni(111) Substrates for Metal–Insulator–Metal Tunneling Devices

Adsorption of magnesium porphyrin on Au(111)-supported graphene and hexagonal boron nitride monolayers: A first-principles study

Adsorption of magnesium porphyrin on Au(111)-supported graphene and hexagonal boron nitride monolayers: A first-principles study

Reduction of carbon dioxide to methane and ethanol on the surface of graphyne-like boron nitride (BNyen) monolayer: A DFT study

Recently, scientists have created a novel type of boron nitride material known as BNyen. This material is similar in structure to Graphyne and has a higher N:B ratio than traditional boron nitride due to the addition of boron and nitrogen connecting segments within its units. This material has been studied for its potential as a photocatalyst for reduction of CO2 using DFT approaches. Optical and electronic attributes of BNyen suggest that it has a wider visible-light range and a band gap of 5.69 eV. By adding boron to BNyen, patial distributions of LUMO and HOMO indicate that π network has been extended, resulting in significantly greater photocatalytic efficiency. Upon the adsorption of CO2 on BNyen monolayer, the band gap significantly decreases, indicating a strong interaction between the BNyen and CO2. DFT computations were employed to explore the mechanism of CO2 reduction to a single carbon product catalyzed by BNyen. Based on the ΔG values, the optimized pathway for this reduction is from CO2 to CH4. Additionally, the potential formation of di-carbon products was considered, and based on the free energy values, CH3CH2OH is identified as the final di-carbon product. The Gibbs free energies for potential CO2 reaction pathways on BNyen were calculated, revealing that CO2 can be reduced to CH4 with a low limiting potential of −0.37 V and to CH3CH2OH with a low limiting potential of −0.57 V, both processes being powered by solar energy. In CO2RR, the competing hydrogen evolution reaction (HER) must be considered. The free energy of HER (ΔG = 0.96 eV) is significantly higher than the ΔG of the rate-determining steps for the mono-carbon product (0.37 eV) and the di-carbon product (0.57 eV) on BNyen. Therefore, BNyen effectively suppresses HER during the CO2RR process. This research can serve as a valuable guide for developing novel types of BNyen as appropriate photocatalysts for CO2 reduction reactions (CO2RR).

Quantum mechanical effects in plasmonic sub-nanometer cavities formed by a tip and substrate structure.

Enhancing local field intensity through light field compression is one of the core issues in surface plasmon-enhanced spectroscopy. The theoretical framework for the nanostructure composed of a tip and a substrate has predominantly relied on classical electromagnetic models, ignoring the electron tunneling effect. In this paper, we investigate the plasmonic near-field characteristics in the sub-nanometer cavity formed by the tip and the substrate using a quantum-corrected model. Additionally, we analyze the local electric field and Raman enhancement when hexagonal boron nitride (h-BN) monolayer is used as a decoupling layer for the nanocavity. The results indicate that classical electromagnetic theory fails to accurately describe the plasmonic electric field in smaller sub-nanometer gaps. When the gap is reduced to 0.32 nm, the quantum-corrected model shows that the local electric field in the sub-nanometer cavity is significantly reduced due to the tunneling current, aligning more closely with experimental results. Moreover, adding a high-barrier h-BN layer effectively prevents the occurrence of tunneling current, allowing for a strong local electric field even when the gap is less than 0.32 nm. The calculated maximum Raman enhancement reaches up to 15 orders of magnitude. Our research results provide a deep understanding of quantum mechanical effects in tip-enhanced spectroscopy systems, enabling the potential applications based on quantum plasmons in nanocavity.

First principles study of BN triphenylene-graphdiyne monolayer and bilayer structures with varying C-chain lengths: insights into optical behavior

First-principles calculations engaging density functional theory (DFT) are employed to systematically study the optical characteristics of monolayer and bilayer boron nitride (BN) triphenylene-graphdiyne (Tp-BNyne) structures featuring varying lengths of C-chains. The thermal stability of Tp-BNyne structures at temperatures up to 1000 K is verified. The weak van der Waals interactions due to the small binding energies and significant interlayer distances maintain the cohesion between the layers. The investigation revealed that all Tp-BNyne structures under examination exhibit semiconductor behavior with a band gap in the range of 0.97–2.74 eV. The bilayer configurations demonstrated a narrower energy band gap in comparison to the monolayer ones. Increasing the length of C-chains leads to a reduction in the energy band gap. Delving into the optical behavior of Tp-BNyne structures under photon incidence with parallel and perpendicular polarizations, a distinct anisotropy in the optical characteristics of Tp-BNyne is revealed. The static dielectric constant increases and the optical band gap decreases with increasing C-chain length. The absorption coefficients of monolayer and bilayer Tp-BNyne structures, on the order of 107/m, demonstrate that these sheets can effectively absorb light in the visible and ultraviolet regions. These findings present Tp-BNyne sheets as promising candidates for use in photovoltaic devices to convert sunlight into electrical current, as well as for designing optical devices for ultraviolet protection. Additionally, Tp-BNyne structures are transparent materials, especially in the high-energy range.

QRCODE: Massively parallelized real-time time-dependent density functional theory for periodic systems

We present a new software module, QRCODE (Quantum Research for Calculating Optically Driven Excitations), for massively parallelized real-time time-dependent density functional theory (RT-TDDFT) calculations of periodic systems in the open-source Qbox software package. Our approach utilizes a custom implementation of a fast Fourier transformation scheme that significantly reduces inter-node message passing interface (MPI) communication of the major computational kernel and shows impressive scaling up to 16,344 CPU cores. In addition to improving computational performance, QRCODE contains a suite of various time propagators for accurate RT-TDDFT calculations. As benchmark applications of QRCODE, we calculate the current density and optical absorption spectra of hexagonal boron nitride (h-BN) and photo-driven reaction dynamics of the ozone-oxygen reaction. We also calculate the second and higher harmonic generation of monolayer and multi-layer boron nitride structures as examples of large material systems. Our optimized implementation of RT-TDDFT in QRCODE enables large-scale calculations of real-time electron dynamics of chemical and material systems with enhanced computational performance and impressive scaling across several thousand CPU cores.

Bilayer C60 Polymer/h-BN Heterostructures: A DFT Study of Electronic and Optic Properties.

Interest in fullerene-based polymer structures has renewed due to the development of synthesis technologies using thin C60 polymers. Fullerene networks are good semiconductors. In this paper, heterostructure complexes composed of C60 polymer networks on atomically thin dielectric substrates are modeled. Small tensile and compressive deformations make it possible to ensure appropriate placement of monolayer boron nitride with fullerene networks. The choice of a piezoelectric boron nitride substrate was dictated by interest in their applicability in mechanoelectric, photoelectronic, and electro-optical devices with the ability to control their properties. The results we obtained show that C60 polymer/h-BN heterostructures are stable compounds. The van der Waals interaction that arises between them affects their electronic and optical properties.

Role of carbon substitutional and vacancy in tailoring the H2 adsorption energy over a hexagonal boron nitride monolayer: an ab initio study

The effect of the substitutional and vacancy type defects on the H2 adsorption energy over a monolayer hexagonal boron nitride (h-BN) substrate has been studied by using the van der Waals density functional theory calculations. Carbon doping at the boron site or formation of boron vacancy can be an effective way to increase the adsorption energy value of a pristine h-BN substrate. The repulsive lateral interaction present in between the two H2 molecules plays a vital role in case of multiple H2 molecule adsorption over the substrate. Also, the carbon cluster formation during doping can have a favorable effect in the overall storage capacity of the h-BN substrate.

Structural and mechanical properties of monolayer amorphous carbon and boron nitride

Structural and mechanical properties of monolayer amorphous carbon and boron nitride

First-principles study of CH2O, CH4, Cl2, HCN, and CNCl gas adsorption behavior by h-BN boron site modification

The potential application of metallic boron bit-doped hexagonal boron nitride monolayers (h-BN@M, M = Fe, Sn, Cu, Zn) as materials for the detection of hazardous gases (CH2O, CH4, Cl2, HCN, and CNCl) has been investigated based on the first nature principle. h-BN@Fe exhibits chemisorptive properties for the adsorption of HCN and CNCl and h-BN@Sn exhibits chemisorption and appropriate humidity resistance. The recovery time of HCN on the h-BN@Fe surface and CNCl on the h-BN@Sn surface was significantly shortened under the 392 K ultraviolet light attempt frequency. In the presence of an applied electric field, HCN and CNCl on the h-BN@Fe surface and CNCl on the h-BN@Sn surface showed adjustable recovery times. This suggests that it is possible to design gas sensing devices with good adsorption characteristics on metallic boron bit-doped hexagonal boron nitride monolayers. In the future, the performance of these materials for the detection of hazardous gases will be improved by changing their structure and composition.

Investigation of hexagonal boron nitride monolayer with pores as an anode material for sodium-ion batteries

The hexagonal boron nitride monolayer (h-BNML) used as an anode material for metal-ion batteries was assumed pristine form. However, inspired by the imperfections in natural materials, this study investigates the effect of defects on the electrochemical properties of h-BNML. Within the current piece of research, h-BNML with pores is introduced to develop an anode material for sodium ion battery (SIBs) by undertaking density-functional theory (DFT) computations. During the diffusion and storage process of Na ions, the pores effect was thoroughly investigated. The boron atoms were removed from the structure of the pure h-BNML in order to form the h-BNML with pores, which mimicked the pore formation. Based on the DFT results, after the pore formation, the h-BNML retained its planarity. Following the introduction of vacancies, significant alterations occurred in the electronic structure characteristics of h-BNML within the pores, facilitating the effective adsorption of Na ions within the pore. The results of quantum theory of atoms in molecules indicated that there were interactions between the pores and Na ions through an electrostatic-type attraction. The h-BNML with pores was capable of retaining a large number of Na ions at its surface without any change in its planar structure. This led to an increase in its theoretical specific capacity, which increased with porosity. Hence, unlike the pure h-BNML, the pore formation improved the diffusion of Na ions. This can be promising to designing highly efficient anodes for SIBs. The methodological approach in this study can be used for tailoring porous BN materials for SIBs.

Light-wave-controlled Haldane model in monolayer hexagonal boron nitride

In recent years, the stacking and twisting of atom-thin structures with matching crystal symmetry has provided a unique way to create new superlattice structures in which new properties emerge1,2. In parallel, control over the temporal characteristics of strong light fields has allowed researchers to manipulate coherent electron transport in such atom-thin structures on sublaser-cycle timescales3,4. Here we demonstrate a tailored light-wave-driven analogue to twisted layer stacking. Tailoring the spatial symmetry of the light waveform to that of the lattice of a hexagonal boron nitride monolayer and then twisting this waveform result in optical control of time-reversal symmetry breaking5 and the realization of the topological Haldane model6 in a laser-dressed two-dimensional insulating crystal. Further, the parameters of the effective Haldane-type Hamiltonian can be controlled by rotating the light waveform, thus enabling ultrafast switching between band structure configurations and allowing unprecedented control over the magnitude, location and curvature of the bandgap. This results in an asymmetric population between complementary quantum valleys that leads to a measurable valley Hall current7, which can be detected by optical harmonic polarimetry. The universality and robustness of our scheme paves the way to valley-selective bandgap engineering on the fly and unlocks the possibility of creating few-femtosecond switches with quantum degrees of freedom.

Spatially-resolved UV-C emission in epitaxial monolayer boron nitride

We report hyperspectral imaging in the UV-C spectral domain in epitaxial monolayers of hexagonal boron nitride (hBN). Under quasi-resonant laser excitation, the UV-C emission of monolayer hBN consists in resonant Raman scattering and photoluminescence, which appear to be spatially uncorrelated. Systematic measurements as a function of the excitation energy bring evidence of a photoluminescence singlet at ∼6.045 eV. The spatial variations of the photoluminescence energy are found to be around ∼10 meV, revealing that the inhomogeneous broadening is lower than the average photoluminescence linewidth of ∼25 meV, a value close to the radiative limit in monolayer hBN. Our methodology provides an accurate framework for assessing the opto-electronic properties of hBN in the prospect of scalable hBN-based devices fabricated by epitaxy.

Hexagonal boron nitride nanosheets: Fabrication, thermal properties and application in polymers

Traditional thermally conductive materials are gradually losing their advantages as the electronics industry develops rapidly. Polymers are in urgent need of a material with high thermal conductivity, stable structure, good mechanical properties and oxidation resistance, which makes hexagonal boron nitride (h-BN) an excellent heat transfer filler for polymer composites. Boron nitride nanosheets (BNNS) are monolayers of hexagonal boron nitride, and theoretical studies have shown that BNNS have a higher thermal conductivity than h-BN (up to 400 Wm−1K−1, in-plane). This paper provides a comprehensive review of various methods for preparing BNNS, including mechanical exfoliation, liquid phase sonication exfoliation and chemical vapor deposition (CVD). In addition, various factors affecting the thermal conductivity of BNNS, including grain boundary, grain size and defects, are also discussed. Then, the influence of BNNS as filler on the thermal conductivity of the polymer was further discussed. Finally, this paper summarizes the existing BNNS applications and lists the application scenarios of BNNS in various fields. The purpose of this review is to summarize the previous work and put forward the prospect and future development direction of preparing high thermal conductivity BNNS-included polymer composites, so as to stimulate the research and improvement of new preparation methods for BNNS and promote its practical application as heat transfer materials.

Adsorption and evolution of hydrogen molecules on hexagonal boron nitride monolayer: a combined DFT and kinetic monte-carlo simulations study

Density functional theory (DFT) and kinetic Monte-Carlo (kMC) simulation code has been combinedly used to study the adsorption and evolution dynamics of hydrogen molecules over a hexagonal boron nitride (h-BN) monolayer. Maximum adsorption energy from van der Waals curve is predicted to be around 60 to 70 meV using two different DFT functionals. Repulsive lateral interaction between two hydrogen molecules plays a key role in determining the maximum number of adsorptions inside one unit cell of h-BN. Bader charge analysis, electron localization function (ELF), total and partial density of states (DOS) plots have been included to understand the weak interaction going on between the adsorbent and substrate. The input energy parameters from the DFT calculation has been used to perform the kMC simulation for describing the adsorption, desorption and the diffusion pattern of hydrogen molecules with a given time of exposure to an empty h-BN substrate along with the overall surface coverage.

Reinforcement learning for in silico determination of adsorbate-substrate structures.

Reinforcement learning (RL) methods have helped to define the state of the art in the field of modern artificial intelligence, mostly after the breakthrough involving AlphaGo and the discovery of novel algorithms. In this work, we present a RL method, based on Q-learning, for the structural determination of adsorbate@substrate models in silico, where the minimization of the energy landscape resulting from adsorbate interactions with a substrate is made by actions on states (translations and rotations) chosen from an agent's policy. The proposed RL method is implemented in an early version of the reinforcement learning software for materials design and discovery (RLMaterial), developed in Python3.x. RLMaterial interfaces with deMon2k, DFTB+, ORCA, and Quantum Espresso codes to compute the adsorbate@substrate energies. The RL method was applied for the structural determination of (i) the amino acid glycine and (ii) 2-amino-acetaldehyde, both interacting with a boron nitride (BN) monolayer, (iii) host-guest interactions between phenylboronic acid and β-cyclodextrin and (iv) ammonia on naphthalene. Density functional tight binding calculations were used to build the complex search surfaces with a reasonably low computational cost for systems (i)-(iii) and DFT for system (iv). Artificial neural network and gradient boosting regression techniques were employed to approximate the Q-matrix or Q-table for better decision making (policy) on next actions. Finally, we have developed a transfer-learning protocol within the RL framework that allows learning from one chemical system and transferring the experience to another, as well as from different DFT or DFTB levels.

Volatile and Nonvolatile Resistive Switching Coexistence in Conductive Point Hexagonal Boron Nitride Monolayer.

Recently, we demonstrated the nonvolatile resistive switching effects of metal-insulator-metal (MIM) atomristor structures based on two-dimensional (2D) monolayers. However, there are many remaining combinations between 2D monolayers and metal electrodes; hence, there is a need to further explore 2D resistance switching devices from material selections to future perspectives. This study investigated the volatile and nonvolatile switching coexistence of monolayer hexagonal boron nitride (h-BN) atomristors using top and bottom silver (Ag) metal electrodes. Utilizing an h-BN monolayer and Ag electrodes, we found that the transition between volatile and nonvolatile switching is attributed to the thickness/stiffness of chain-like conductive bridges between h-BN and Ag surfaces based on the current compliance and atomristor area. Computations indicate a "weak" bridge is responsible for volatile switching, while a "strong" bridge is formed for nonvolatile switching. The current compliance determines the number of Ag atoms that undergo dissociation at the electrode, while the atomristor area determines the degree of electric field localization that forms more stable conductive bridges. The findings of this study suggest that the h-BN atomristor using Ag electrodes shows promise as a potential solution to integrate both volatile neurons and nonvolatile synapses in a single neuromorphic crossbar array structure through electrical and dimensional designs.

Defects in <i>h</i>-BN: computer simulation of size effects

The influence of size effects on the properties of a hexagonal boron nitride (h-BN) monolayer containing CBVN, NBVN, and OBOBVN defects has been studied by first principles methods. These defects are potentially capable of generating single photons in quantum optics and quantum information devices. Size effects here mean the dependence of the studied model properties on the simulated fragment size of the 2D structure under periodic boundary conditions. Physically, this means that the properties of a monolayer depend on the distance between defects. This dependence allows us to judge how strongly the defects interact with each other and whether they interact at all. For technical applications, the characteristics of the band structure (band gap, spectrum and density of electron states induced by the defect in the band gap) and the atomic structure of the defect (defect formation energy, geometry in the equilibrium configuration), which form this band pattern, are important. In this work, these properties are studied by using the density functional theory with the basis of atom-like functions (SIESTA package) and plane waves (VASP package). The results obtained using both packages are consistent with each other. It has been established that the defects can be considered non-interacting, when the distance between them is ten unit cell parameters.

Dirac t-Boron Nitride Monolayer as an Appealing Binder-Free Anode for Alkali Metal Ion Batteries.

The development of universal anode materials with superlative electrochemical performance poses a great challenge for rechargeable alkali metal (AM) ion battery technologies. In the present work, the viability of the gapless Dirac t-BN (tetragonal boron nitride) monolayer as a lightweight binder-free anode has been systematically evaluated via comprehensive first-principles calculations. Aside from the desirable electronic conductivity, the t-BN monolayer exhibits an excellent ionic conductivity as well due to its moderate affinity for Li, Na, and K atoms with favorable in-plane barriers of 0.36, 0.18, and 0.19 eV, respectively. Meanwhile, the presence of B4N4 octagons allows the AM atoms to penetrate through the t-BN monolayer. Excitingly, the host material delivers an ultrahigh specific capacity up to 1080 mA h g-1 for Li, 5400 mA h g-1 for Na, and 2160 mA h g-1 for K in the wake of low mean open-circuit voltages of 0.033, 0.203, and 0.300 V at the half-cell level. According to the standard hydrogen electrode methodology, the energy densities are forecasted to be as large as 3240, 13500, and 5680 mW h g-1 for Li, Na, and K ion batteries, respectively, with robust thermal stability up to at least 400 K. The safety and cycling durability of the t-BN monolayer are jointly corroborated via the moderate mechanical strengths and ab initio molecular dynamics simulations at the maximum intercalated states, as well as via the small lattice changes and its ultrahigh tolerable ultimate tensile strain. These findings unambiguously promise that the t-BN monolayer can serve as an appealing candidate for anode applications in AM ion batteries.