Design and Analysis of a Microwave-Optical Dual Modality Biomolecular Sensing Platform

Zhang, Luya; Niknejad, Ali M.

doi:10.1109/jssc.2019.2946817

Cited by 10 publications

(2 citation statements)

References 44 publications

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“…As a next step, the presented approach can be combined with a high-performance BiCMOS electronic-PIC (EPIC) technology [150]. In addition to these optical elements, the abovementioned EPIC technology also features high-frequency bipolar transistors, which can pave the way for future monolithic electro-optical multimodal sensor platforms [151] at an unprecedented degree of integration and functionality. VI.…”

Section: B Sensor Functionalizationmentioning

confidence: 99%

Integrated Millimeter-Wave and Terahertz Analyzers for Biomedical Applications

Kissinger

Kaynak

Mai

2022

IEEE Trans. Microwave Theory Techn.

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Section: B Sensor Functionalizationmentioning

confidence: 99%

Integrated Millimeter-Wave and Terahertz Analyzers for Biomedical Applications

Kissinger

Kaynak

Mai

2022

IEEE Trans. Microwave Theory Techn.

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“…A common target of measurement is added mass deposited on the mechanism [22] resulting in a shift in the resonance frequency [17] or amplitude ratio at resonance [26]. Similar phenomenology is used in [28] to detect the presence of specific biomolecules through their effect on the dielectric properties of the surrounding medium. In [19], a network of Colpitts oscillators is proposed as a potential threshold color sensor.…”

Section: Introductionmentioning

confidence: 99%

Design of active network filters as hysteretic sensors

Mao,

Dankowicz

2021

Preprint

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This work aims to propose and design a class of networks of coupled linear and nonlinear oscillators, in which short bursts of exogenous excitation result in sustained endogenous network activity that returns to a quiescent state only after a characteristic time and along a different path than when originally excited. The desired hysteretic behavior is obtained through the coupling of self-excited oscillations with purposely designed rate laws for slowly-varying nodal parameters, governed only by local interactions in the network. The proposed architecture and the sought dynamics take inspiration from complex biological systems that combine endogenous energy sources with a paradigm for distributed sensing and information processing. In this paper, the network design problem considers arbitrary topologies and investigates the dependence of the desired response on model parameters, as well as on the placement of a single nonlinear node in an otherwise linear network. Perturbation analysis in various asymptotic parameter limits is used to define the proposed internal dynamics. Parameter continuation techniques validate the asymptotic results numerically and demonstrate their robustness over finite ranges of parameter values. Both approaches suggest a nontrivial dependence of the optimal distribution of nonlinearity on the network topology.

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