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纳米红外光谱 (nano-infrared spectroscopy, 简记为nano-IR) 技术能够突破光的衍射极限,实现 ~ 10 nm空间分辨率的红外光谱检测,是研究纳米尺度物质化学成分和结构的重要技术手段. 然而,由于纳米物质的尺寸与红外光的波长存在较大失配,导致其红外吸收信号微弱. 在这里,我们理论提出了一种基于纳米腔室的声学型石墨烯等离激元 (nanocavity-Acoustic graphene plasmon, 简记为n-AGP) 可调谐增强nano-IR检测平台. 该平台可实现超高光场压缩 (模式体积Vn-AGP ≈ 10-7λ03,λ0 = 6.25 μm) 和约50倍电场增强的n-AGP激发. 通过调控金纳米腔室结构和石墨烯费米能级,我们实现了n-AGP的宽频段动态调控 (1290-2124 cm-1). 此外,由于n-AGP的电磁场高度局域在纳米腔室内,具有高的探测灵敏度,可实现单个蛋白质颗粒酰胺I带和酰胺II带振动指纹特征的探测 (灵敏度提高15倍). 这一基于n-AGP的增强结构拓展了nano-IR技术在单分子尺度的表征能力,可广泛应用于生物、催化等领域.Nano-infrared spectroscopy (nano-IR) technology can surpass the diffraction limit of light, achieving infrared spectroscopic detection with a spatial resolution of ~ 10 nm, which is an important technical means for studying the chemical composition and structure of molecules at the nanoscale. However, the weak infrared absorption signals of nanoscale materials pose a significant challenge due to the large mismatch between their dimensions and the wavelength of infrared light. The infrared absorption signals of molecular vibrational modes are proportional to the square of the electromagnetic field intensity at their location, meaning that higher electromagnetic field intensity can significantly enhance molecular detection sensitivity. Acoustic graphene plasmons (AGP), excited by the interaction between free charges in graphene and image charges in metals, exhibit strong optical field localization and electromagnetic field enhancement. These properties make AGP an effective platform for enhancing nano-IR detection sensitivity. However, the fabrication of graphene nanostructures often introduces numerous edge defects due to the limitations of nanofabrication techniques, significantly reducing the electromagnetic field enhancement observed in experiments. Here, using finite element simulation, we theoretically propose a tunable enhanced nano-IR detection platform based on nanocavity-acoustic graphene plasmon (n-AGP), utilizing a graphene/air gap/gold nanocavity structure. This platform avoids the need for nanofabrication of graphene, thereby preventing defects and contamination introduced by processes such as electron beam exposure and plasma etching. By plotting the dispersion of n-AGP, we found that n-AGP has a high wavelength compression capability comparable to AGP (λ0/λAGP = 48). Additionally, due to the introduction of the gold nanocavity structure, n-AGP possess an extremely small mode volume (Vn-AGP ≈ 10-7λ03, λ0 = 6.25 μm). By calculating the electric field intensity distribution (|Enorm|) and the normalized electric field intensity spectrum (i.e., the relationship between frequency and (|Ez|/|E0|) of the n-AGP structure, it is evident that due to the high electron density on the gold surface, electromagnetic waves can reflect at the boundaries of the gold nanocavity and be resonantly enhanced within the nanocavity. At the resonant frequency of n-AGP (1800 cm-1), the electric field enhancement within the cavity is about 50 times. In contrast, at similar resonant frequencies, the electric field enhancement factors of Graphene plasmon (resonant frequency 1770 cm-1) and AGP (resonant frequency 1843 cm-1) are approximately 3 and 2 times, respectively, significantly lower than that of n-AGP. Furthermore, by placing a protein film (60 nm wide and 10 nm high) under the graphene, we calculated the spectral dip depths caused by Fano resonance between n-AGP and AGP with the vibrational modes of protein molecules, thereby validating the enhancement factors of different modes for protein vibrational mode infrared absorption. For the amide I band of proteins, the detection sensitivity of n-AGP is about 60 times higher than that of AGP. Additionally, we discovered that by adjusting the structural parameters of the gold nanocavity, including cavity depth, width, and surface roughness, the response frequency band of n-AGP can be modulated (from 1290 to 2124 cm-1). Specifically, as the cavity depth increases, the electric field enhancement of n-AGP improves, and the wavelength compression capability of n-AGP decreases, causing the resonant frequency to blue-shift (from 1793 cm-1 to 2124 cm-1). As the cavity width increases, the resonant frequency of n-AGP red-shift (from 1793 cm-1 to 1290 cm-1), and the effectiveness of the gold nanocavity boundary in reflecting the resonant electric field within the cavity diminishes, resulting in a decrease in the electric field enhancement factor. With the gradual increase in the roughness of the gold nanocavity bottom, the effective depth of the gold nanocavity increases, causing a blue shift in the n-AGP resonant frequency (from 1793 cm-1 to 1861 cm-1) and an increase in the electric field enhancement factor. Moreover, by adjusting the Fermi level of graphene (from 0.3 eV to 0.6 eV), we achieved dynamic tuning of n-AGP (from 1355 to 1973 cm-1). As the Fermi level of graphene increases, the wavelength compression capability of n-AGP decreases, resulting in a blue-shift in the resonant frequency. Finally, by optimizing the structural parameters and Fermi level of n-AGP, and placing protein particles of different sizes (20 nm, 15 nm, and 10 nm wide, all 10 nm high) into the graphene/gold nanocavity structure, we verified the protein detection capability of n-AGP-enhanced nano-IR. We found that n-AGP can detect the vibrational fingerprint features of the amide I and amide II bands of a single protein particle (10×10 nm) with a 15-fold increase in sensitivity. This n-AGP-based enhanced structure holds promise for providing an important detection platform for nanoscale material characterization and single-molecule detection, with broad application potential in biomedicine, materials science, and geology.
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Keywords:
- graphene /
- nanocavity /
- plasmon /
- surface enhanced infrared spectroscopy
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[1] Yao Z, Xu S, Hu D, Chen X, Dai Q, Liu M 2020 Adv. Opt. Mater. 8 1901042
[2] Chen X, Hu D, Mescall R, You G, Basov D N, Dai Q, Liu M 2019 Adv. Mater. 31 1804774
[3] Lahiri B, Holland G, Centrone A 2013 Small 9 439
[4] Centrone A 2015 Annu. Rev. Anal. Chem. 8 101
[5] Katzenmeyer A M, Holland G, Kjoller K, Centrone A 2015 Anal. Chem. 87 3154
[6] Dazzi A, Glotin F, Carminati R 2010 J. Appl. Phys. 107 124519
[7] Schwartz J J, Jakob D S, Centrone A 2022 Chem. Soc. Rev. 51 5248
[8] Wang L, Wang H, Xu X G 2022 Chem. Soc. Rev. 51 5268
[9] Wang L, Wang H, Wagner M, Yan Y, Jakob D S, Xu X G 2017 Sci. Adv. 3 e1700255
[10] Wang H, Gonzalez-Fialkowski J M, Li W, Xie Q, Yu Y, Xu X G 2021 Anal. Chem. 93 3567
[11] Davies-Jones J A, Davies P R 2022 Mater. Chem. Front. 6 1552
[12] Rajapaksa I, Uenal K, Wickramasinghe H K 2010 Appl. Phys. Lett. 97, 073121
[13] Jahng J, Fishman D A, Park S, Nowak D B, Morrison W A, Wickramasinghe H K, Potma E O 2015 Acc. Chem. Res. 48, 2671
[14] Xue M, Ye S, Ma X, Ye F, Wang C, Zhu L, Yang Y, Chen J 2022 J. Am. Chem. Soc. 144 20278
[15] Gamage S, Howard M, Makita H, Cross B, Hastings G, Luo M, Abate Y 2018 PLoS One 13 e0199112
[16] Kim S Y, Khanal D, Kalionis B, Chrzanowski W 2019 Nat. Protoc. 14 576
[17] Goikoetxea M, Amenabar I, Chimenti S, Paulis M, Leiza J R, Hillenbrand R 2021 Macromolecules 54 995
[18] Tri P N, Prud’homme R E 2018 Macromolecules 51 181
[19] Morsch S, Liu Y, Lyon S B, Gibbon S R 2016 ACS Appl. Mater. Interfaces 8 959
[20] Yang J, Hatcherian J, Hackley P C, Pomerantz A E 2017 Nat. Commun. 8 2179
[21] Hassenkam T, Andersson M P, Dalby K N, Mackenzie D M A, Rosing M T 2017 Nature 548 78
[22] Kebukawa Y, Kobayashi H, Urayama N, Baden N, Kondo M, Zolensky M E, Kobayashi K 2019 Proc. Natl. Acad. Sci. 116 753
[23] Nishida J, Otomo A, Koitaya T, Shiotari A, Minato T, Iino R, Kumagai T 2024 Nano Lett. 24 836
[24] Tang F, Bao P, Su Z 2016 Anal. Chem. 88 4926
[25] Patabendigedara S, Nowak D, Nancarrow M J B, Clark S M 2021 Rev. Sci. Instrum. 92 023103
[26] Yang X, Sun Z, Low T, Hu H, Guo X, Garcia de Abajo F J, Avouris P, Dai Q 2018 Adv. Mater. 30 e1704896
[27] Hu H, Yang X, Zhai F, Hu D, Liu R, Liu K, Sun Z, Dai Q 2016 Nat. Commun. 7 12334
[28] Wu C, Guo X, Duan Y, Lyu W, Hu H, Hu D, Chen K, Sun Z, Gao T, Yang X, Dai Q 2022 Adv. Mater. 34 2110525
[29] Rodrigo D, Limaj O, Janner D, Etezadi D, García de Abajo F J, Pruneri V, Altug H 2015 Science 349 165
[30] Hu H, Yang X, Guo X, Khaliji K, Biswas S R, García de Abajo F J, Low T, Sun Z, Dai Q 2019 Nat. Commun. 10 1131
[31] Bareza N, Jr., Gopalan K K, Alani R, Paulillo B, Pruneri V 2020 ACS Photonics 7 879
[32] Alonso-González P, Nikitin A Y, Gao Y, Woessner A, Lundeberg M B, Principi A, Forcellini N, Yan W, Vélez S, Huber A J, Watanabe K, Taniguchi T, Casanova F, Hueso L E, Polini M, Hone J, Koppens F H L, Hillenbrand R 2017 Nat. Nanotechnol. 12 31
[33] Menabde S G, Lee I-H, Lee S, Ha H, Heiden J T, Yoo D, Kim T-T, Low T, Lee Y H, Oh S-H, Jang M S 2021 Nat. Commun. 12 938
[34] Epstein I, Alcaraz D, Huang Z, Pusapati V-V, Hugonin J-P, Kumar A, Deputy X M, Khodkov T, Rappoport T G, Hong J-Y, Peres N M R, Kong J, Smith D R, Koppens F H L 2020 Science 368 1219
[35] Lundeberg M B, Gao Y, Asgari R, Tan C, Van Duppen B, Autore M, Alonso-González P, Woessner A, Watanabe K, Taniguchi T, Hillenbrand R, Hone J, Polini M, Koppens F H L 2017 Science 357 187
[36] Alcaraz Iranzo D, Nanot S, Dias E J C, Epstein I, Peng C, Efetov D K, Lundeberg M B, Parret R, Osmond J, Hong J-Y, Kong J, Englund D R, Peres N M R, Koppens F H L 2018 Science 360 291
[37] Chen S, Autore M, Li J, Li P, Alonso-Gonzalez P, Yang Z, Martin-Moreno L, Hillenbrand R, Nikitin A Y 2017 ACS Photonics 4 3089
[38] Olmon R L, Raschke M B 2012 Nanotechnology 23 444001
[39] Low T, Avouris P 2014 ACS Nano 8 1086
[40] Adato R, Altug H 2013 Nat. Commun. 4 2154
[41] Du X, Skachko I, Barker A, Andrei E Y 2008 Nat. Nanotechnol. 3 491
[42] Rickhaus P, Maurand R, Liu M-H, Weiss M, Richter K, Schönenberger C 2013 Nat. Commun. 4 2342
[43] Dorgan V E, Behnam A, Conley H J, Bolotin K I, Pop E 2013 Nano Lett. 13 4581
[44] Hu H, Yu R, Teng H, Hu D, Chen N, Qu Y, Yang X, Chen X, McLeod A S, Alonso-González P, Guo X, Li C, Yao Z, Li Z, Chen J, Sun Z, Liu M, García de Abajo F J, Dai Q 2022 Nat. Commun. 13 1465
[45] Lu Y-H, Morales C, Zhao X, van Spronsen M A, Baskin A, Prendergast D, Yang P, Bechtel H A, Barnard E S, Ogletree D F, Altoe V, Soriano L, Schwartzberg A M, Salmeron M 2020 Nano Lett. 20 6364
[46] Farmer D B, Rodrigo D, Low T, Avouris P 2015 Nano Lett. 15 2582
[47] Zhuang B, Li S, Li S, Yin J 2021 Carbon 173 609
[48] Dregely D, Neubrech F, Duan H, Vogelgesang R, Giessen H 2013 Nat. Commun. 4 2237
[49] Kawata S 2001 Near-field optics and surface plasmon polaritons (Vol. 81) (Springer Science & Business Media) p163
[50] Miao X, Luk T S, Liu P Q 2022 Adv. Mater. 34 2107950
[51] Guo Q, Li C, Deng B, Yuan S, Guinea F, Xia F 2017 ACS Photonics 4 2989
[52] Schwaighofer A, Montemurro M, Freitag S, Kristament C, Culzoni M J, Lendl B 2018 Anal. Chem. 90 7072
[53] Jahng J, Fishman D A, Park S, Nowak D B, Morrison W A, Wickramasinghe H K, Potma E O 2015 Acc. Chem. Res. 48 2671
[54] Kavungal D, Magalhães P, Kumar S T, Kolla R, Lashuel H A, Altug H 2023 Sci. Adv. 9 eadg9644
[55] López-Lorente Á I, Mizaikoff B 2016 Anal. Bioanal. Chem. 408 2875
[56] Zhang W, Chen L, Chen J, Wang L, Gui X, Ran J, Xu G, Zhao H, Zeng M, Ji J, Qian L, Zhou J, Ouyang H, Zou X 2017 Adv. Healthcare Mater. 6 1700121
[57] Hoarau M, Badieyan S, Marsh E N G 2017 Org. Biomol. Chem. 15 9539
[58] Talari A C S, Martinez M A G, Movasaghi Z, Rehman S, Rehman I U 2017 Appl. Spectrosc. Rev. 52 456
[59] Araki K, Yagi N, Ikemoto Y, Yagi H, Choong C-J, Hayakawa H, Beck G, Sumi H, Fujimura H, Moriwaki T, Nagai Y, Goto Y, Mochizuki H 2015 Sci. Rep. 5 17625
[60] Nabers A, Ollesch J, Schartner J, Kötting C, Genius J, Haußmann U, Klafki H, Wiltfang J, Gerwert K 2016 J. Biophotonics 9 224
[61] Nabers A, Ollesch J, Schartner J, Kötting C, Genius J, Hafermann H, Klafki H, Gerwert K, Wiltfang J 2016 Anal. Chem. 88 2755
[62] Lashuel H A, Overk C R, Oueslati A, Masliah E 2013 Nat. Rev. Neurosci. 14 38
[63] Conway K A, Lee S-J, Rochet J-C, Ding T T, Williamson R E, Lansbury P T 2000 Proc. Natl. Acad. Sci. 97 571
[64] Hardy J A, Higgins G A 1992 Science 256 184
[65] Ballatore C, Lee V M Y, Trojanowski J Q 2007 Nat. Rev. Neurosci. 8 663
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