Controllable terahertz cross-shaped three-dimensional graphene intrinsically chiral metastructure and its biosensing application

Asgari, Somayyeh; Granpayeh, Nosrat; Fabritius, Tapio

doi:10.1016/j.optcom.2020.126080

Cited by 64 publications

(35 citation statements)

References 67 publications

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“…MMPAs have significant applications, including sensors [27], [28], absorption filtering [29], etc. The design of the MMPAs can be such that absorption occurs at various frequency ranges including GHz [30], THz [31]- [33], IR and optical frequencies [34].…”

Section: Introductionmentioning

confidence: 99%

The Potential of Refractive Index Nanobiosensing Using a Multi-Band Optically Tuned Perfect Light Metamaterial Absorber

et al. 2021

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An optically tunable perfect light absorber as a refractive index (RI) metamaterial (MM) nanobiosensor (NBS) is designed for sensing chemicals, monitoring the concentration of water-soluble glucose, and detecting viruses. This plasmon induced tunable metasurface works based on multiband super-absorption in the infrared frequency regime. It consists of a metal mirror that facilitates the MM to work as an absorber where the metal pattern at the top layer creates an enhanced evanescent wave that facilitates the metasurface to work as a RI optical sensor. The modelling and numerical analysis are carried out using Finite Difference Time Domain (FDTD) method-based software, CST microwave studio where a genetic algorithm (GA) is used to optimize the geometric parameters. We demonstrate multiband super-absorption spectra having maximum absorption of more than 99%. Furthermore, we show how the multiband super-absorber nanostructure can be used as a RI NBS, where the resonance frequency shifts with the RI of the surrounding medium. The achieved opto-chemical sensitivity is approximately 65nm/RIU RIU, the bio-optical sensitivity to detect viruses is approximately 76 nm / RIU; and the optical sensitivity of the water-soluble glucose concentration is about 300nm/RIU; all sensitivities are comparable in comparison with the reported values in the literature.

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Section: Introductionmentioning

confidence: 99%

The Potential of Refractive Index Nanobiosensing Using a Multi-Band Optically Tuned Perfect Light Metamaterial Absorber

et al. 2021

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“…Recent advances in biosensor technologies [ 40 , 41 ] and consumer electronics have led to precise physiological monitoring and more specifically accurate activity recognition. Activity recognition based on wearable device is one of the most rapidly growing research areas in personalization of analyses.…”

Section: Discussionmentioning

confidence: 99%

Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors

Bahador¹,

Ferreira²,

Tamminen³

et al. 2021

JMIR Mhealth Uhealth

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Background Multimodal wearable technologies have brought forward wide possibilities in human activity recognition, and more specifically personalized monitoring of eating habits. The emerging challenge now is the selection of most discriminative information from high-dimensional data collected from multiple sources. The available fusion algorithms with their complex structure are poorly adopted to the computationally constrained environment which requires integrating information directly at the source. As a result, more simple low-level fusion methods are needed. Objective In the absence of a data combining process, the cost of directly applying high-dimensional raw data to a deep classifier would be computationally expensive with regard to the response time, energy consumption, and memory requirement. Taking this into account, we aimed to develop a data fusion technique in a computationally efficient way to achieve a more comprehensive insight of human activity dynamics in a lower dimension. The major objective was considering statistical dependency of multisensory data and exploring intermodality correlation patterns for different activities. Methods In this technique, the information in time (regardless of the number of sources) is transformed into a 2D space that facilitates classification of eating episodes from others. This is based on a hypothesis that data captured by various sensors are statistically associated with each other and the covariance matrix of all these signals has a unique distribution correlated with each activity which can be encoded on a contour representation. These representations are then used as input of a deep model to learn specific patterns associated with specific activity. Results In order to show the generalizability of the proposed fusion algorithm, 2 different scenarios were taken into account. These scenarios were different in terms of temporal segment size, type of activity, wearable device, subjects, and deep learning architecture. The first scenario used a data set in which a single participant performed a limited number of activities while wearing the Empatica E4 wristband. In the second scenario, a data set related to the activities of daily living was used where 10 different participants wore inertial measurement units while performing a more complex set of activities. The precision metric obtained from leave-one-subject-out cross-validation for the second scenario reached 0.803. The impact of missing data on performance degradation was also evaluated. Conclusions To conclude, the proposed fusion technique provides the possibility of embedding joint variability information over different modalities in just a single 2D representation which results in obtaining a more global view of different aspects of daily human activities at hand, and yet preserving the desired performance level in activity recognition.

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“…The conductivity of the gold layer is 4.56 × 10 7 S/m 34 . Simulations were performed using the CST Microwave Studio Software 4 . The device works as a broadband and multiband metamirrors when it is illuminated by TE and TM waves respectively.…”

Section: Metastructure Material and Equivalent Circuit Modelmentioning

confidence: 99%

“…For the upper graphene, μ c = 1 eV and for the bottom graphene, μ c = 0.95 eV are considered. The relative permittivity of graphene, by assumption of the incident electromagnetic wave as e jωt , is 4 : in which σ , ω, ε 0 , and Δ are respectively the graphene surface conductivity, angular frequency, vacuum permittivity, and graphene thickness. Δ is considered to be 0.335 nm 7 .…”

Section: Metastructure Material and Equivalent Circuit Modelmentioning

confidence: 99%

Graphene-based dual-functional chiral metamirror composed of complementary 90° rotated U-shaped resonator arrays and its equivalent circuit model

Asgari

Fabritius

2021

Sci Rep

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An equivalent circuit model (ECM) using a MATLAB code to analyze a tunable two-layered graphene-based chiral dual-function metamirror, is proposed in this work. The investigated metastructure is composed of complementary U-shaped graphene resonator arrays in the terahertz (THz) region. The ECM analysis could be used for any two-layered chiral metastructure for any frequencies, containing resonators with a thickness less than λ/50. The characteristics of the proposed tunable metamirror were analyzed numerically using the finite element method (FEM) in CST Software to verify the ECM analysis. The proposed metamirror can be used in polarization-sensitive devices in the THz region with simpler biasing without a need for ion gels or similar. It works as a broadband TE and multiband (four bands) TM mirror in the 0.3–4.5 THz bandwidth with a strong linear dichroism (LD) response (up to 96%). The designed mirror is a dynamically tunable, dual-functional structure, requiring only 90° rotation of the incident electromagnetic fields to switch between broadband and multiband spectral behavior making it a promising candidate for future THz intelligent systems. The proposed ECM is in agreement with the FEM results. The ECM analysis provides a simple, fast, and effective way to understand the metamirror’s behavior and guides for the design and analysis of graphene-based chiral metastructures in the THz region.

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Controllable terahertz cross-shaped three-dimensional graphene intrinsically chiral metastructure and its biosensing application

Cited by 64 publications

References 67 publications

The Potential of Refractive Index Nanobiosensing Using a Multi-Band Optically Tuned Perfect Light Metamaterial Absorber

The Potential of Refractive Index Nanobiosensing Using a Multi-Band Optically Tuned Perfect Light Metamaterial Absorber

Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors

Graphene-based dual-functional chiral metamirror composed of complementary 90° rotated U-shaped resonator arrays and its equivalent circuit model

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