# Wafer-scale AA-stacked hexagonal boron nitride grown on a GaN substrate https://mdr.nims.go.jp/datasets/a57dc597-9d11-4364-9242-d42d82b48553 ## File - [2025A01135G_87948_3_merged_1738752664.pdf](https://mdr.nims.go.jp/filesets/617cbde1-8169-4f72-a5c0-9d50911ccc38/download) ([Detail](https://mdr.nims.go.jp/filesets/617cbde1-8169-4f72-a5c0-9d50911ccc38.md)) ## Id a57dc597-9d11-4364-9242-d42d82b48553 ## Local identifier ## Visibility open_to_public ## State published ## Created at 2026-08-31T05:29:28.421060Z ## Updated at 2026-08-31T05:53:07.457913Z ## Published at 2026-08-31T07:27:56.538743Z ## Doi ## First published url https://doi.org/10.1038/s41563-025-02173-2 ## Date published 2025-03-19 ## Recorded date published 2025-6 ## Resource type journal_article ## Manuscript type accepted_manuscript ## Collection ## Title - title: Wafer-scale AA-stacked hexagonal boron nitride grown on a GaN substrate title_type: original lang: en ## Description - description: The stacking sequence of two-dimensional hexagonal boron nitride (hBN) is a critical factor that determines its polytypes and its distinct physical properties. Although most hBN layers adopt the thermodynamically stable AA′ stacking sequence, achieving alternative stacking configurations has remained a long-standing challenge. Here we demonstrate the scalable synthesis of hBN featuring unprecedented AA stacking, where atomic monolayers align along the c axis without any translation or rotation. This previously considered thermodynamically unfavourable hBN polytype is achieved through epitaxial growth on a two-inch single-crystalline gallium nitride wafer, using a metal–organic chemical vapour deposition technique. Comprehensive structural and optical characterizations, complemented by theoretical modelling, evidence the formation of AA-stacked multilayer hBN and reveal that hBN nucleation on the vicinal gallium nitride surface drives the unidirectional alignment of layers. Here electron doping plays a central role in stabilizing the AA stacking configuration. Our findings provide further insights into the scalable synthesis of engineered hBN polytypes, characterized by unique properties such as large optical nonlinearity. description_type: abstract lang: en ## Creator - name: Seokho Moon role: author - name: Odongo Francis Ngome Okello role: author - name: Adrien Rousseau role: author - name: Chang-Won Choi role: author - name: Youngjae Kim role: author - name: Yunjae Park role: author - name: Jiye Kim role: author - name: Jaewon Kim role: author - name: Minhyuk Kim role: author - name: Pierre Valvin role: author - name: Jaehee Cho role: author - name: Kenji Watanabe role: author orcid: https://orcid.org/0000-0003-3701-8119 organization: National Institute for Materials Science - name: Takashi Taniguchi role: author orcid: https://orcid.org/0000-0002-1467-3105 organization: National Institute for Materials Science - name: Hu Young Jeong role: author - name: Giorgia Fugallo role: author - name: Wilfried Desrat role: author - name: Feng Ding role: author - name: JaeDong Lee role: author - name: Bernard Gil role: author - name: Guillaume Cassabois role: author - name: Si-Young Choi role: author - name: Jong Kyu Kim role: author ## Contact agent ## Publisher organization: Springer Science and Business Media LLC ## Managing organization ## Keyword - subject: Hexagonal boron nitride (hBN) schema: not_defined - subject: Stacking sequence (polytype) schema: not_defined - subject: Metal-organic chemical vapor deposition (MOCVD) schema: not_defined ## Rights - description: 'This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1038/s41563-025-02173-2' identifier: http://rightsstatements.org/vocab/InC/1.0/ ## Other identifier(s) ## Data origin - data_origin_type: other ## Embargo start_date: 2025-03-19 end_date: 2025-09-19 ## Journal - title: Nature Materials issn: '14764660' volume: '24' issue: '6' start_page: 843 end_page: 851 ## Conference ## Related item ## Funding - identifier: NRF-2021M3C1C3097673 funder_name: National Research Foundation of Korea - identifier: RS-2024-00344690 funder_name: National Research Foundation of Korea - identifier: RS-2022-NR068223 funder_name: National Research Foundation of Korea - identifier: NRF-2021M3C1C3097673 funder_name: National Research Foundation of Korea - identifier: 2018H1A2A1060392 funder_name: National Research Foundation of Korea - identifier: RS-2024-00344690 funder_name: National Research Foundation of Korea - identifier: RS-2022-NR068223 funder_name: National Research Foundation of Korea - identifier: RS-2024-00355591 funder_name: National Research Foundation of Korea - identifier: RS-2024-00355591 funder_name: National Research Foundation of Korea - identifier: '20016290' funder_name: Ministry of Trade, Industry and Energy - identifier: '20016290' funder_name: Ministry of Trade, Industry and Energy - identifier: 25YH1100 funder_name: Electronics and Telecommunications Research Institute - identifier: 25YH1100 funder_name: Electronics and Telecommunications Research Institute - identifier: SRFC-MA1401-10 funder_name: Samsung - identifier: IO201215-08185-01 funder_name: Samsung - identifier: SRFC-MA1401-10 funder_name: Samsung - identifier: IO201215-08185-01 funder_name: Samsung - identifier: SRFC-MA1401-10 funder_name: Samsung - identifier: IO201215-08185-01 funder_name: Samsung - identifier: SRFC-MA1401-10 funder_name: Samsung - identifier: IO201215-08185-01 funder_name: Samsung - identifier: 2020R1A6C101A202 funder_name: Korea Basic Science Institute - identifier: 2020R1A6C101A202 funder_name: Korea Basic Science Institute - identifier: 2020R1A6C101A202 funder_name: Korea Basic Science Institute ## Instrument ## Instrument operator ## Instrument managing organization ## Measurement method ## Specimen ## Chemical composition ## Structure for specimen ## Structural feature for specimen ## Specific property for specimen ## Process for specimen treatment ## Computational method ## Energy level/transition state ## Software ## Custom property ## Fileset - id: 617cbde1-8169-4f72-a5c0-9d50911ccc38 filename: 2025A01135G_87948_3_merged_1738752664.pdf content_type: application/pdf size: 49452998 md5: 0cebf429d494dc05cdeddcfa936fc9fa ## Thumbnail fileset_id: 617cbde1-8169-4f72-a5c0-9d50911ccc38 filename: 2025A01135G_87948_3_merged_1738752664.pdf