Tunable Infrared Plasmon Response of Lithographic Sn‐doped Indium Oxide Nanostructures

Kapetanovic, Viktor; Bicket, Isobel C.; Lazar, S.; Lagos, Maureen J.; Botton, Gianluigi A.

doi:10.1002/adom.202001024

Cited by 11 publications

(9 citation statements)

References 48 publications

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“…Due to the fact that a 30 nanometer-thick silicon nitride (SiN) substrate (TEM grid) was used for conducting this experiment, this activity was identified as a phonon excitation in the SiN film. The energy of the restored phonon peak in this work, is fully aligned with the values reported for SiN phonon excitation in the literature 72 – 74 . Because of the vicinity of the SiN phonon peak to ZLP and the silver nanowire’s SP1 peak (dipole mode), spotting this peak in the raw experimental data would have been practically impossible.…”

Section: Resultssupporting

confidence: 90%

Alignment-invariant signal reality reconstruction in hyperspectral imaging using a deep convolutional neural network architecture

Pofelski

Teimoori

et al. 2022

Sci Rep

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The energy resolution in hyperspectral imaging techniques has always been an important matter in data interpretation. In many cases, spectral information is distorted by elements such as instruments’ broad optical transfer function, and electronic high frequency noises. In the past decades, advances in artificial intelligence methods have provided robust tools to better study sophisticated system artifacts in spectral data and take steps towards removing these artifacts from the experimentally obtained data. This study evaluates the capability of a recently developed deep convolutional neural network script, EELSpecNet, in restoring the reality of a spectral data. The particular strength of the deep neural networks is to remove multiple instrumental artifacts such as random energy jitters of the source, signal convolution by the optical transfer function and high frequency noise at once using a single training data set. Here, EELSpecNet performance in reducing noise, and restoring the original reality of the spectra is evaluated for near zero-loss electron energy loss spectroscopy signals in Scanning Transmission Electron Microscopy. EELSpecNet demonstrates to be more efficient and more robust than the currently widely used Bayesian statistical method, even in harsh conditions (e.g. high signal broadening, intense high frequency noise).

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Section: Resultssupporting

confidence: 90%

Alignment-invariant signal reality reconstruction in hyperspectral imaging using a deep convolutional neural network architecture

Pofelski

Teimoori

et al. 2022

Sci Rep

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“…It is worth noting that the proposed process is generic and might be very efficient for the production of nanostructures of a wide variety of alternative nonmetallic conductors, which are usually grown by sputter deposition, such as molybdenum nitride (MoN), tantalum nitride (TaN), ,, niobium nitride (NbN), In-doped tin oxide (ITO), ,, aluminum- or gallium-doped zinc oxide (AZO, GZO), ,,, niobium-doped titanium oxide (NTO), partly reduced molybdenum oxides MoO x ( x < 3), , and vanadium dioxide (VO 2 ), which exhibits a metal–insulator transition. , All these conductors have been proposed as alternative plasmonic materials, whose plasmonic activity spans the far-ultraviolet to medium-infrared range. ,,,,,− …”

Section: Resultsmentioning

confidence: 99%

Self-Assembled Dichroic Plasmonic Nitride Nanostructures with Broken Centrosymmetry for Second-Harmonic Generation

Babonneau

Camelio

Abadias

et al. 2021

ACS Appl. Nano Mater.

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TiN and ZrN are emerging as important alternative plasmonic materials. In addition to their well-known assets, they can incorporate point defects that break the centrosymmetry of their cubic crystal structure, making them promising candidates as non-linear optical materials and especially for second harmonic generation (SHG). Their refractory character and chemical stability were obstacles for the bottom-up fabrication of TiN and ZrN nanostructures so far. In this work, it is shown that highly directional dichroic nanostructures of TiN and ZrN may be indeed grown by self-assembly using glancing angle deposition on periodic rippled dielectric surfaces. The produced nitride nanostructures exhibit point defects and exceptional photothermal durability. These nanostructures exhibit strong SHG response when probed by a near-infrared laser. It is shown that SHG is strongly associated with the near-field enhancement due to the localized surface plasmon resonance of the nanostructures. Given that such nanostructures can endure extremely high electric fields, they are expected to be able to emit massive SHG signals and be applied in laser technology as optical components such as polarizers and SHG emitters.

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“…This study shows that doped semiconductors can effectively concentrate IR radiation at the nanoscale, leading to strong near electric-field enhancement factors on par with those associated with noble-metal nanoparticles in the visible spectral region. In parallel, other groups have studied the near-field plasmonic responses in nanotriangles and cube-shaped ITO nanocrystals, providing insights to effectively tune plasmonic responses to cover wide spectral regions. Optically dark plasmonic modes can also be accessed via STEM-EELS, providing important information to better understand energy-transfer mechanisms in plasmonic nanosystems. , …”

Section: Infrared Plasmonsmentioning

confidence: 99%

Imaging Vibrational Excitations in the Electron Microscope

Kumar

Camden

2022

J. Phys. Chem. C

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Vibrational spectroscopy is a powerful tool for probing atomic motions in molecules and extended solids. Recent advances in aberration-corrected, monochromated-scanning transmission electron microscopy (STEM) now allow imaging of individual phonon modes at the nanoscale, overcoming the spatial limit imposed by diffraction-limited optical spectroscopy techniques. In this Perspective, we summarize the recent progress in high-resolution electron energy-loss spectroscopy (EELS), which now enables vibrational spectroscopy to be performed in the electron microscope. The high spatial and energy resolution of low-loss EELS can be used to directly image phonons inside or near inorganic and organic materials without considerable sample damage. Monochromated EELS can furthermore resolve isotope specific vibrational signatures and phonon modes arising from single-atom dopants. In parallel with these advances, we highlight the ability of spatial-and momentum-resolved EELS to measure the phonon dispersions at material interfaces, obtaining valuable knowledge about interfacial thermal and electrical transport phenomena. Before concluding, we illustrate how imaging infrared (IR) plasmons at high spatial resolution deepens our understanding of how plasmons interact with molecular vibrations. Taken together, these diverse studies illustrate the capability of monochromated STEM-EELS to image low-energy phonon and plasmon excitations at the nanoscale and the new insights from these studies can be leveraged to engineer the specific material properties needed for next-generation devices.

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Tunable Infrared Plasmon Response of Lithographic Sn‐doped Indium Oxide Nanostructures

Cited by 11 publications

References 48 publications

Alignment-invariant signal reality reconstruction in hyperspectral imaging using a deep convolutional neural network architecture

Alignment-invariant signal reality reconstruction in hyperspectral imaging using a deep convolutional neural network architecture

Self-Assembled Dichroic Plasmonic Nitride Nanostructures with Broken Centrosymmetry for Second-Harmonic Generation

Imaging Vibrational Excitations in the Electron Microscope

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