Title: Epitaxial hexagonal boron nitride with high quantum efficiency
Two-dimensional (2D) hexagonal boron nitride (h-BN) is one of the few materials showing great promise for light emission in the far ultraviolet (UV)-C wavelength, which is more effective and safer in containing the transmission of microbial diseases than traditional UV light. In this report, we observed that h-BN, despite having an indirect energy bandgap, exhibits a remarkably high room-temperature quantum efficiency (∼60%), which is orders of magnitude higher than that of other indirect bandgap material, and is enabled by strong excitonic effects and efficient exciton-phonon interactions. This study offers a new approach for the design and development of far UV-C optoelectronic devices as well as quantum photonic devices employing 2D semiconductor active regions. more »« less
Aldalbahi, Ali; Velázquez, Rafael; Zhou, Andrew F.; Rahaman, Mostafizur; Feng, Peter X.
(, Nanomaterials)
null
(Ed.)
This study presents a fast and effective method to synthesize 2D boron nitride/tungsten nitride (BN–WN) nanocomposites for tunable bandgap structures and devices. A few minutes of synthesis yielded a large quantity of high-quality 2D nanocomposites, with which a simple, low-cost deep UV photo-detector (DUV-PD) was fabricated and tested. The new device was demonstrated to have very good performance. High responsivity up to 1.17 A/W, fast response-time of lower than two milliseconds and highly stable repeatability were obtained. Furthermore, the influences of operating temperature and applied bias voltage on the properties of DUV-PD as well as its band structure shift were investigated.
Biswas, Abhijit; Alvarez, Gustavo A; Tripathi, Manoj; Lee, Jonghoon; Pieshkov, Tymofii S; Li, Chenxi; Gao, Bin; Puthirath, Anand B; Zhang, Xiang; Gray, Tia; et al
(, Journal of Materials Chemistry C)
We used temperature-dependent spark plasma sintering to induce phase transformations of metastable 3D c-BN to mixed-phase 3D/2D c-BN/h-BN and ultimately to the stable 2D h-BN phase at high temperature, useful for extreme-temperature technology.
2D materials have attracted broad attention from researchers for their unique electronic proper-ties, which may be been further enhanced by combining 2D layers into vertically stacked van der Waals heterostructures. Among the superlative properties of 2D systems, thermoelectric energy (TE) conversion promises to enable targeted energy conversion, localized thermal management, and thermal sensing. However, TE conversion efficiency remains limited by the inherent tradeoff between conductivity and thermopower. In this paper, we use first-principles calculation to study graphene-based van der Waals heterostructures (vdWHs) composed of graphene layers and hexagonal boron nitride (h-BN). We compute the electronic band structures of heterostructured systems using Quantum Espresso and their thermoelectric (TE) properties using BoltzTrap2. Our results have shown that stacking layers of these 2D materials opens a bandgap, increasing it with the number of h-BN interlayers, which significantly improves the power factor (PF). We predict a PF of ~1.0x10 11 W/K 2 .m.s for the vdWHs, nearly double compared to 5x10 10 W/K 2 .m.s that we obtained for single-layer graphene. This study gives important information on the effect of stacking layers of 2D materials and points toward new avenues to optimize the TE properties of vdWHs.
Abstract Reliable and controllable growth of two-dimensional (2D) hexagonal boron nitride (h-BN) is essential for its wide range of applications. Substrate engineering is one of the critical factors that influence the growth of the epitaxial h-BN films. Here, we report the growth of monolayer h-BN on Ni (111) substrates incorporated with oxygen atoms via molecular beam epitaxy. It was found that the increase of incorporated oxygen concentration in the Ni substrate through a pretreatment process prior to the h-BN growth step would have an adverse effect on the morphology and growth rate of 2D h-BN. Under the same growth condition, h-BN monolayer coverage decreases exponentially as the amount of oxygen incorporated into Ni (111) increases. Density functional theory calculations and climbing image nudged elastic band (CI-NEB) method reveal that the substitutional oxygen atoms can increase the diffusion energy barrier of B and N atoms on Ni (111) thereby inhibiting the growth of h-BN films. As-grown large-area h-BN monolayer films and fabricated Al/h-BN/Ni (MIM) nanodevices were comprehensively characterized to evaluate the structural, optical and electrical properties of high-quality monolayers. Direct tunneling mechanism and high breakdown strength of ∼11.2 MV cm−1are demonstrated for the h-BN monolayers grown on oxygen-incorporated Ni (111) substrates, indicating that these films have high quality. This study provides a unique example that heterogeneous catalysis principles can be applied to the epitaxy of 2D crystals in solid state field. Similar strategies can be used to grow other 2D crystalline materials, and are expected to facilitate the development of next generation devices based on 2D crystals.
Xie, Jing; Afshari, Sahra; Sanchez_Esqueda, Ivan
(, npj 2D Materials and Applications)
Abstract Recent studies of resistive switching devices with hexagonal boron nitride (h-BN) as the switching layer have shown the potential of two-dimensional (2D) materials for memory and neuromorphic computing applications. The use of 2D materials allows scaling the resistive switching layer thickness to sub-nanometer dimensions enabling devices to operate with low switching voltages and high programming speeds, offering large improvements in efficiency and performance as well as ultra-dense integration. These characteristics are of interest for the implementation of neuromorphic computing and machine learning hardware based on memristor crossbars. However, existing demonstrations of h-BN memristors focus on single isolated device switching properties and lack attention to fundamental machine learning functions. This paper demonstrates the hardware implementation of dot product operations, a basic analog function ubiquitous in machine learning, using h-BN memristor arrays. Moreover, we demonstrate the hardware implementation of a linear regression algorithm on h-BN memristor arrays.
Laleyan, David_Arto, Lee, Woncheol, Zhao, Ying, Wu, Yuanpeng, Wang, Ping, Song, Jun, Kioupakis, Emmanouil, and Mi, Zetian.
"Epitaxial hexagonal boron nitride with high quantum efficiency". APL Materials 11 (5). Country unknown/Code not available: American Institute of Physics. https://doi.org/10.1063/5.0142242.https://par.nsf.gov/biblio/10595058.
@article{osti_10595058,
place = {Country unknown/Code not available},
title = {Epitaxial hexagonal boron nitride with high quantum efficiency},
url = {https://par.nsf.gov/biblio/10595058},
DOI = {10.1063/5.0142242},
abstractNote = {Two-dimensional (2D) hexagonal boron nitride (h-BN) is one of the few materials showing great promise for light emission in the far ultraviolet (UV)-C wavelength, which is more effective and safer in containing the transmission of microbial diseases than traditional UV light. In this report, we observed that h-BN, despite having an indirect energy bandgap, exhibits a remarkably high room-temperature quantum efficiency (∼60%), which is orders of magnitude higher than that of other indirect bandgap material, and is enabled by strong excitonic effects and efficient exciton-phonon interactions. This study offers a new approach for the design and development of far UV-C optoelectronic devices as well as quantum photonic devices employing 2D semiconductor active regions.},
journal = {APL Materials},
volume = {11},
number = {5},
publisher = {American Institute of Physics},
author = {Laleyan, David_Arto and Lee, Woncheol and Zhao, Ying and Wu, Yuanpeng and Wang, Ping and Song, Jun and Kioupakis, Emmanouil and Mi, Zetian},
}
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