Subwavelength Terahertz Imaging of Graphene Photoconductivity

Hornett, Samuel M.; Stantchev, Rayko I.; Vardaki, Martha Z.; Beckerleg, Chris; Hendry, Euan

doi:10.1021/acs.nanolett.6b03168

Cited by 34 publications

(28 citation statements)

References 49 publications

(131 reference statements)

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“…Δσ is the temporal photoexcitation dynamics and Δ E represents the photoconductivity. Comparison of photoconductivity maps with Raman maps also suggested eliminating spatial inhomogeneities in optoelectronic fabrication . This study provided both experimental and theoretical basis for the potential application of graphene devices in optoelectronics.…”

Section: Microscale Spectral Mapping and Optical‐property Studiesmentioning

confidence: 78%

“…Due to the wide optical and optoelectronic applications in photoconductive detector, terahertz emitters, and modulators within terahertz range, THz transmission imaging of graphene on Si substrate was conducted using local free carrier dynamic analysis in a sub‐mm resolution in a large area . Other studies mainly focused on the conductivity imaging of graphene using THz conductivity spectroscopic imaging to assess electrical parameters such as charge carrier mobility, ionized dopant density, charge carrier lifetime, and surface recombination velocity of graphene . The transmission properties of large‐area graphene films have been studied through time‐domain THz and FTIR spectroscopy in a frequency range from 10 to 10 000 cm −1 .…”

Section: Microscale Spectral Mapping and Optical‐property Studiesmentioning

confidence: 99%

Section: Microscale Spectral Mapping and Optical‐property Studiesmentioning

confidence: 99%

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Microscale Spectroscopic Mapping of 2D Optical Materials

Dong

Yetisen

Köhler

et al. 2019

Advanced Optical Materials

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be used for flexible touch screens and displays, printable electronics, and thinfilm photovoltaics, [4] while FETs made of graphene can be used for highly sensitive biosensors. [5] Another 2D material MoS 2 , a direct-bandgap semiconductor, has applications in ultrasensitive photodetectors, transistors, and gas-sensing devices. [6][7][8][9] Other 2D materials have also shown potential in photovoltaic devices, memory, and light-emitting diodes (LEDs). [10,11] Broad application potential of 2D materials in optoelectronic devices, photonic devices, and optical sensors is mainly based on their unique optical performances. [12] 2D materials can be fabricated based on their layered structure. In the molecular structures of these materials, the atoms are bonded hard in the same plane, but the bond effect between two lateral layers is weak due to van der Waals forces. [13] 2D materials can be roughly categorized as semimetal like graphene, semiconductor like transition metal dichalcogenides (TMDs), and insulator like hexagonal boron nitride (hBN) from the aspect of bandgap differences. [14] Due to the experimentally practical manipulation of monolayer and multilayer 2D materials, remarkable optical performances can be realized for a wide range of optical applications. For example, the number of layers of 2D materials can strongly influence the photoluminescence performance. [15] The unconventional optical performances including adsorption and emission, light sensitivity, as well as plasmonic effects of 2D materials are closely related to their inner physical properties such as carrier mobility, density of states, and band structure based on the interaction of atoms, structural symmetry, and stacking patterns. [16,17] Through the control of layer number which could influence the bandgap value, 2D materials could react to different spectrum ranging from ultraviolet to infrared light. [18] Doping strategies are also effective to modify intrinsic 2D semiconductors and improve the response with respect to an extended range of spectrum. [19,20] The assessment of the optical properties of 2D materials is indispensable for device and sensor development. [21] Based on detailed surface mapping and spectral information, the suitability of 2D materials for optical devices or sensor applications can be thoroughly studied. [22,23] Microscopy, direct 2D mapping of materials, can provide basic spatial information, [24] while spectroscopy can offer one more dimensional spectral information which is 2D materials have unique optical properties due to their ultrathin layered structures, and are emerging as promising materials for optoelectronic devices. To characterize and evaluate these properties, diffraction-limited spectroscopic mapping, also known as microscale spectroscopic imaging, has been developed to provide abundant spatial and spectral information. The usefulness of microscale spectroscopic mapping for unique property study of 2D optical materials is addressed. Advances in both mature and growing microscale spectroscopic mapping...

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Section: Microscale Spectral Mapping and Optical‐property Studiesmentioning

confidence: 78%

Section: Microscale Spectral Mapping and Optical‐property Studiesmentioning

confidence: 99%

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Microscale Spectroscopic Mapping of 2D Optical Materials

Dong

Yetisen

Köhler

et al. 2019

Advanced Optical Materials

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“…In Ref. 65 , the same group investigated the conductivity of a graphene monolayer, by depositing it on the surface of the silicon modulator. Conductivity maps with a resolution down to 75 μm were obtained.…”

Section: Near-field Imagingmentioning

confidence: 99%

Single-pixel terahertz imaging: a review

Zanotto

Piccoli

Morandotti

et al. 2020

Opto-Electronic Advances

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This paper is devoted to reviewing the results achieved so far in the application of the single-pixel imaging technique to terahertz (THz) systems. The use of THz radiation for imaging purposes has been largely explored in the last twenty years, due to the unique capabilities of this kind of radiation in interrogating material properties. However, THz imaging systems are still limited by the long acquisition time required to reconstruct the object image and significant efforts have been recently directed to overcome this drawback. One of the most promising approaches in this sense is the so-called "single-pixel" imaging, which in general enables image reconstruction by patterning the beam probing the object and measuring the total transmission (or reflection) with a single-pixel detector (i.e., with no spatial resolution). The main advantages of such technique are that i) no bulky moving parts are required to raster-scan the object and ii) compressed sensing (CS) algorithms, which allow an appropriate reconstruction of the image with an incomplete set of measurements, can be successfully implemented. Overall, this can result in a reduction of the acquisition time. In this review, we cover the experimental solutions proposed to implement such imaging technique at THz frequencies, as well as some practical uses for typical THz applications.

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“…AFM is a versatile method used to measure the thickness of 2D materials; however, the materials are easily destroyed due to the sliding of the tip on the sample surface when working on contact mode, while the tapping mode takes a relatively long time to measure even a small area [20,21]. Time-domain terahertz spectroscopy is an emerging technique for imaging 2D materials, but the comparatively large spot size hinders the identification of laterally small flakes [22]. In such a situation, an accurate, versatile and nondestructive method is highly desirable not only in fundamental research but also for practical applications.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Analysis of Raman Spectra of MoS2

et al. 2020

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Defects introduced during the growth process greatly affect the device performance of two-dimensional (2D) materials. Here we demonstrate the applicability of employing machine-learning-based analysis to distinguish the monolayer continuous film and defect areas of molybdenum disulfide (MoS2) using position-dependent information extracted from its Raman spectra. The random forest method can analyze multiple Raman features to identify samples, making up for the problem of not being able to effectively identify by using just one certain variable with high recognition accuracy. Even some dispersed nucleation site defects can be predicted, which would commonly be ignored under an optical microscope because of the lower optical contrast. The successful application for classification and analysis highlights the potential for implementing machine learning to tap the depth of classical methods in 2D materials research.

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Subwavelength Terahertz Imaging of Graphene Photoconductivity

Cited by 34 publications

References 49 publications

Microscale Spectroscopic Mapping of 2D Optical Materials

Microscale Spectroscopic Mapping of 2D Optical Materials

Single-pixel terahertz imaging: a review

Machine Learning Analysis of Raman Spectra of MoS2

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