Real-space imaging of acoustic plasmons in large-area CVD graphene

An acoustic plasmonic mode in a graphene-dielectric-metal heterostructure has recently been spotlighted as a superior platform for strong light-matter interaction. It originates from the coupling of graphene plasmon with its mirror image and exhibits the largest field confinement in the limit of a nm-thick dielectric. Although recently detected in the far-field regime, optical near-fields of this mode are yet to be observed and characterized. Direct optical probing of the plasmonic fields reflected by the edges of graphene via near-field scattering microscope reveals a relatively small damping rate of the mid-IR acoustic plasmons in our devices, which allows for their real-space mapping even with unprotected, chemically grown, large-area graphene at ambient conditions. We show an acoustic mode that is twice as confined - yet 1.4 times less damped - compared to the graphene surface plasmon under similar conditions. We also image the resonant acoustic Bloch state in a 1D array of gold nanoribbons responsible for the high efficiency of the far-field coupling. Our results highlight the importance of acoustic plasmons as an exceptionally promising platform for large-area graphene-based optoelectronic devices operating in mid-IR

When Are Negative Online Reviews More Helpful Than Positive Reviews? A Multi-method Investigation Into Millions of Online Hotel Reviews

The role and volume of electronic word-of-mouth (e-WOM) online reviews worldwide are increasing rapidly so consumers, particularly in the tourism industry, may suffer from information overload. This, in turn, may impact on driving consumer behaviour. Thus, understanding factors that influence which reviews are perceived as helpful may be important for vendors in the tourism industry particularly in the hotel industry. This thesis suggests negativity bias and loss aversion as a theoretical anchor to illustrate the impact of star ratings on the perceived helpfulness of hotel reviews. Since prior research results appear to be diverse, there is a need to find which systemic moderators elicit different outcomes. This research seeks to provide a significant moderating role of reviews’ differences such as consumer scepticism, and systematic information processing. A quantitative approach via big data consisting of over two million online hotel reviews was adopted to address the inconsistent results. This research offers an enhanced predictive effect instead of small sample sized surveys used in prior studies. By deploying spatial regression discontinuity design between one-sided and two-sided reviews on Booking.com, as well as Agoda.com and Booking.com reviews, I proposed and validated the moderating role of consumer scepticism. This is expressed as ‘too good to be true’. To make the results of the analysis more robust and addressing a small statistical effect size, the effect of the independent variables is not only measured in the statistical methods (regression and PROCESS macro) but also in traditional (bi-logistic regression) and new machine learning techniques (deep-learning). The findings given in this work could offer pivotal implications for academics. They could additionally: (1) provide systemic moderators that elicit different outcomes; (2) illustrate a negative association between the review valence and the perceived helpfulness of the reviews; (3) document that when the level of consumer scepticism and heuristic information processing decreases, then negativity bias and loss aversion also weaken or are eliminated; (4) offer extensions for the broader research stream of e-WOM; and (5) extend the stream of research that utilizes big data with machine learning techniques. Limitations and directions for future research are discussed in the closing chapter

Deep-Learning-Based ADHD Classification Using Children’s Skeleton Data Acquired through the ADHD Screening Game

The identification of attention deficit hyperactivity disorder (ADHD) in children, which is increasing every year worldwide, is very important for early diagnosis and treatment. However, since ADHD is not a simple disease that can be diagnosed with a simple test, doctors require a large period of time and substantial effort for accurate diagnosis and treatment. Currently, ADHD classification studies using various datasets and machine learning or deep learning algorithms are actively being conducted for the screening diagnosis of ADHD. However, there has been no study of ADHD classification using only skeleton data. It was hypothesized that the main symptoms of ADHD, such as distraction, hyperactivity, and impulsivity, could be differentiated through skeleton data. Thus, we devised a game system for the screening and diagnosis of children’s ADHD and acquired children’s skeleton data using five Azure Kinect units equipped with depth sensors, while the game was being played. The game for screening diagnosis involves a robot first travelling on a specific path, after which the child must remember the path the robot took and then follow it. The skeleton data used in this study were divided into two categories: standby data, obtained when a child waits while the robot demonstrates the path; and game data, obtained when a child plays the game. The acquired data were classified using the RNN series of GRU, RNN, and LSTM algorithms; a bidirectional layer; and a weighted cross-entropy loss function. Among these, an LSTM algorithm using a bidirectional layer and a weighted cross-entropy loss function obtained a classification accuracy of 97.82%

High-mobility junction field-effect transistor via graphene/MoS2 heterointerface

© 2020, The Author(s).Monolayer molybdenum disulfide (MoS2) possesses a desirable direct bandgap with moderate carrier mobility, whereas graphene (Gr) exhibits a zero bandgap and excellent carrier mobility. Numerous approaches have been suggested for concomitantly realizing high on/off current ratio and high carrier mobility in field-effect transistors, but little is known to date about the effect of two-dimensional layered materials. Herein, we propose a Gr/MoS2 heterojunction platform, i.e., junction field-effect transistor (JFET), that enhances the carrier mobility by a factor of ~ 10 (~ 100 cm2 V−1 s−1) compared to that of monolayer MoS2, while retaining a high on/off current ratio of ~ 108 at room temperature. The Fermi level of Gr can be tuned by the wide back-gate bias (VBG) to modulate the effective Schottky barrier height (SBH) at the Gr/MoS2 heterointerface from 528 meV (n-MoS2/p-Gr) to 116 meV (n-MoS2/n-Gr), consequently enhancing the carrier mobility. The double humps in the transconductance derivative profile clearly reveal the carrier transport mechanism of Gr/MoS2, where the barrier height is controlled by electrostatic doping11sci

Time Evolution Studies on Strain and Doping of Graphene Grown on a Copper Substrate Using Raman Spectroscopy

© 2019 American Chemical Society.The enhanced growth of Cu oxides underneath graphene grown on a Cu substrate has been of great interest to many groups. In this work, the strain and doping status of graphene, based on the gradual growth of Cu oxides from underneath, were systematically studied using time evolution Raman spectroscopy. The compressive strain to graphene, due to the thermal expansion coefficient difference between graphene and the Cu substrate, was almost released by the nonuniform Cu2O growth; however, slight tensile strain was exerted. This induced p-doping in the graphene with a carrier density up to 1.7 × 1013 cm-2 when it was exposed to air for up to 30 days. With longer exposure to ambient conditions (>1 year), we observed that graphene/Cu2O hybrid structures significantly slow down the oxidation compared to that using a bare Cu substrate. The thickness of the CuO layer on the bare Cu substrate was increased to approximately 270 nm. These findings were confirmed through white light interference measurements and scanning electron microscop

Charge Transport in MoS2/WSe2 van der Waals Heterostructure with Tunable Inversion Layer

Despite numerous studies on two-dimensional van der Waals heterostructures, a full understanding of the charge transport and photoinduced current mechanisms in these structures, in particular, associated with charge depletion/inversion layers at the interface remains elusive. Here, we investigate transport properties of a prototype multilayer MoS2/WSe2 heterojunction via a tunable charge inversion/depletion layer. A charge inversion layer was constructed at the surface of WSe2 due to its relatively low doping concentration compared to that of MoS2, which can be tuned by the back-gate bias. The depletion region was limited within a few nanometers in the MoS2 side, while charges are fully depleted on the whole WSe2 side, which are determined by Raman spectroscopy and transport measurements. Charge transport through the heterojunction was influenced by the presence of the inversion layer and involves two regimes of tunneling and recombination. Furthermore, photocurrent measurements clearly revealed recombination and space-charge-limited behaviors, similar to those of the heterostructures built from organic semiconductors. This contributes to research of various other types of heterostructures and can be further applied for electronic and optoelectronic devices. © 2017 American Chemical Society126281sciescopu

Subsentence Extraction from Text Using Coverage-Based Deep Learning Language Models

Sentiment prediction remains a challenging and unresolved task in various research fields, including psychology, neuroscience, and computer science. This stems from its high degree of subjectivity and limited input sources that can effectively capture the actual sentiment. This can be even more challenging with only text-based input. Meanwhile, the rise of deep learning and an unprecedented large volume of data have paved the way for artificial intelligence to perform impressively accurate predictions or even human-level reasoning. Drawing inspiration from this, we propose a coverage-based sentiment and subsentence extraction system that estimates a span of input text and recursively feeds this information back to the networks. The predicted subsentence consists of auxiliary information expressing a sentiment. This is an important building block for enabling vivid and epic sentiment delivery (within the scope of this paper) and for other natural language processing tasks such as text summarisation and Q&A. Our approach outperforms the state-of-the-art approaches by a large margin in subsentence prediction (i.e., Average Jaccard scores from 0.72 to 0.89). For the evaluation, we designed rigorous experiments consisting of 24 ablation studies. Finally, our learned lessons are returned to the community by sharing software packages and a public dataset that can reproduce the results presented in this paper

Observation of an exceptional point in a non-Hermitian metasurface

© 2020 Mark Lawrence, Teun-Teun Kim et al., published by De Gruyter, Berlin/Boston 2020.Exceptional points (EPs), also known as non-Hermitian degeneracies, have been observed in parity-time symmetric metasurfaces as parity-time symmetry breaking points. However, the parity-time symmetry condition puts constraints on the metasurface parameter space, excluding the full examination of unique properties that stem from an EP. Here, we thus design a general non-Hermitian metasurface with a unit cell containing two orthogonally oriented split-ring resonators (SRRs) with overlapping resonance but different scattering rates and radiation efficiencies. Such a design grants us full access to the parameter space around the EP. The parameter space around the EP is first examined by varying the incident radiation frequency and coupling between SRRs. We further demonstrate that the EP is also observable by varying the incident radiation frequency along with the incident angle. Through both methods, we validate the existence of an EP by observing unique level crossing behavior, eigenstate swapping under encirclement, and asymmetric transmission of circularly polarized light11sciescopu

Observation of an exceptional point in a non-Hermitian metasurface

Exceptional points (EPs), also known as non-Hermitian degeneracies, have been observed in parity-time symmetric metasurfaces as parity-time symmetry breaking points. However, the parity-time symmetry condition puts constraints on the metasurface parameter space, excluding the full examination of unique properties that stem from an EP. Here, we thus design a general non-Hermitian metasurface with a unit cell containing two orthogonally oriented split-ring resonators (SRRs) with overlapping resonance but different scattering rates and radiation efficiencies. Such a design grants us full access to the parameter space around the EP. The parameter space around the EP is first examined by varying the incident radiation frequency and coupling between SRRs. We further demonstrate that the EP is also observable by varying the incident radiation frequency along with the incident angle. Through both methods, we validate the existence of an EP by observing unique level crossing behavior, eigenstate swapping under encirclement, and asymmetric transmission of circularly polarized light

Tunable Negative Differential Resistance in van der Waals Heterostructures at Room Temperature by Tailoring the Interface

© 2019 American Chemical Society.Vertically stacked two-dimensional van der Waals (vdW) heterostructures, used to obtain homogeneity and band steepness at interfaces, exhibit promising performance for band-to-band tunneling (BTBT) devices. Esaki tunnel diodes based on vdW heterostructures, however, yield poor current density and peak-to-valley ratio, inferior to those of three-dimensional materials. Here, we report the negative differential resistance (NDR) behavior in a WSe2/SnSe2 heterostructure system at room temperature and demonstrate that heterointerface control is one of the keys to achieving high device performance by constructing WSe2/SnSe2 heterostructures in inert gas environments. While devices fabricated in ambient conditions show poor device performance due to the observed oxidation layer at the interface, devices fabricated in inert gas exhibit extremely high peak current density up to 1460 mA/mm2, 3-4 orders of magnitude higher than reported vdW heterostructure-based tunnel diodes, with a peak-to-valley ratio of more than 4 at room temperature. Besides, Pd/WSe2 contact in our device possesses a much higher Schottky barrier than previously reported Cr/WSe2 contact in the WSe2/SnSe2 device, which suppresses the thermionic emission current to less than the BTBT current level, enabling the observation of NDR at room temperature. Diode behavior can be further modulated by controlling the electrostatic doping and the tunneling barrier as well11sciescopu