Optical Waveguide Theory

A biosensor device is defined by its biological, or bioinspired receptor unit with unique specificities towards corresponding analytes. These analytes are often of biological origin like DNAs or proteins from the immune system (antibodies, antigens) of diseases or infections. Such analytes can also be simple molecules like glucose or pollutants when a biological receptor unit with particular specificity is available. One of many other challenges in biosensor development is the efficient signal capture of the biological recognition event (transduction). Such transducers translate the interaction of the analyte with the biological element into electrochemical, electrochemiluminescent, magnetic, gravimetric, or optical signals. In order to increase sensitivities and to lower detection limits down to even individual molecules, nanomaterials are promising candidates due to the possibility to immobilize an enhanced quantity of bioreceptor units at reduced volumes and even to act itself as transduction element. Among such nanomaterials, gold nanoparticles, semi-conductor quantum dots, polymer nanoparticles, carbon nanotubes, nanodiamonds, and graphene are intensively studied. Due to the vast evolution of this research field, this review summarizes in a non-exhaustive way the advantages of nanomaterials by focusing on nano-objects which provide further beneficial properties than “just” an enhanced surface area.

/pdf/nanomaterials-for-biosensing-applications-a-review-46169riukh.pdf

Nanomaterials for biosensing applications: a review

We review the progress achieved during the recent five years in immunochemical biosensors (immunosensors) combined with nanoparticles for enhanced sensitivity. The initial part introduces antibodies as classic recognition elements. The optical sensing part describes fluorescent, luminescent, and surface plasmon resonance systems. Amperometry, voltammetry, and impedance spectroscopy represent electrochemical transducer methods; electrochemiluminescence with photoelectric conversion constitutes a widely utilized combined method. The transducing options function together with suitable nanoparticles: metallic and metal oxides, including magnetic ones, carbon-based nanotubes, graphene variants, luminescent carbon dots, nanocrystals as quantum dots, and photon up-converting particles. These sources merged together provide extreme variability of existing nanoimmunosensing options. Finally, applications in clinical analysis (markers, tumor cells, and pharmaceuticals) and in the detection of pathogenic microorganisms, toxic agents, and pesticides in the environmental field and food products are summarized.

Nanoparticle-Based Immunochemical Biosensors and Assays: Recent Advances and Challenges

Recent advances in biosensor development for the detection of cancer biomarkers

A biosensor can be defined as a compact analytical device or unit incorporating a biological or biologically derived sensitive recognition element immobilized on a physicochemical transducer to measure one or more analytes. Microfluidic systems, on the other hand, provide throughput processing, enhance transport for controlling the flow conditions, increase the mixing rate of different reagents, reduce sample and reagents volume (down to nanoliter), increase sensitivity of detection, and utilize the same platform for both sample preparation and detection. In view of these advantages, the integration of microfluidic and biosensor technologies provides the ability to merge chemical and biological components into a single platform and offers new opportunities for future biosensing applications including portability, disposability, real-time detection, unprecedented accuracies, and simultaneous analysis of different analytes in a single device. This review aims at representing advances and achievements in the field of microfluidic-based biosensing. The review also presents examples extracted from the literature to demonstrate the advantages of merging microfluidic and biosensing technologies and illustrate the versatility that such integration promises in the future biosensing for emerging areas of biological engineering, biomedical studies, point-of-care diagnostics, environmental monitoring, and precision agriculture.

/pdf/microfluidics-integrated-biosensors-a-leading-technology-2g4gfl0t3n.pdf

Microfluidics Integrated Biosensors: A Leading Technology towards Lab-on-a-Chip and Sensing Applications

Optical Surface plasmon resonance (SPR) biosensors represent the most advanced and developed optical label-free biosensor technology. Optical SPR biosensors are a powerful detection and analysis tool that has vast applications in environmental protection, biotechnology, medical diagnostics, drug screening, food safety and security. This article reviews the recent development of SPR biosensor techniques, including bulk SPR and localized SPR (LSPR) biosensors, for detecting interactions between an analyte of interest in solution and a biomolecular recognition. The concepts of bulk and localized SPs and the working principles of both sensing techniques are introduced. Major sensing advances on biorecognition elements, measurement formats, and sensing platforms are presented. Finally, the discussions on both biosensor techniques as well as comparison of both SPR sensing techniques are made.

Surface plasmon resonance based biosensor technique: a review

Reservoir computing (RC) is a potential neuromorphic paradigm for physically realizing artificial intelligence systems in the Internet of Things society, owing to its well-known low training cost and compatibility with nonlinear devices. Micro-electro-mechanical system (MEMS) resonators exhibiting rich nonlinear dynamics and fading behaviors are promising candidates for high-performance hardware RC. Previously, we presented a non-delay-based RC using one single micromechanical resonator with hybrid nonlinear dynamics. Here, we innovatively introduce a nonlinear tuning strategy to analyze the computing properties (the processing speed and recognition accuracy) of the presented RC. Meanwhile, we numerically and experimentally analyze the influence of the hybrid nonlinear dynamics using the image classification task. Specifically, we study the transient nonlinear saturation phenomenon by fitting quality factors under different vacuums, as well as searching the optimal operating point (the edge of chaos) by the static bifurcation analysis and dynamic vibration numerical models of the Duffing nonlinearity. Our results in the optimal operation conditions experimentally achieved a high classification accuracy of (93 ± 1)% and several times faster than previous work on the handwritten digits recognition benchmark, profit from the perfect high signal-to-noise ratios (quality factor) and the nonlinearity of the dynamical variables.

/pdf/enhancing-the-recognition-task-performance-of-mems-resonator-119gdpwd.pdf

Enhancing the Recognition Task Performance of MEMS Resonator-Based Reservoir Computing System via Nonlinearity Tuning

An MEMS resonant accelerometer is a temperature-sensitive device because temperature change affects the intrinsic resonant frequency of the inner silicon beam. Most classic temperature compensation methods, such as algorithm modeling and structure design, have large errors under rapid temperature changing due to the hysteresis of the temperature response of the accelerometer. To address this issue, we propose a novel reservoir computing (RC) structure based on a nonlinear silicon resonator, which is specifically improved for predicting dynamic information that is referred to as the input–output-improved reservoir computing (IOI-RC) algorithm. It combines the polynomial fitting with the RC on the input data mapping ensuring that the system always resides in the rich nonlinear state. Meanwhile, the output layer is also optimized by vector concatenation operation for higher memory capacity. Therefore, the new system has better performance in dynamic temperature compensation. In addition, the method is real-time, with easy hardware implementation that can be integrated with MEMS sensors. The experiment’s result showed a 93% improvement in IOI-RC compared to raw data in a temperature range of −20–60 °C. The study confirmed the feasibility of RC in realizing dynamic temperature compensation precisely, which provides a potential real-time online temperature compensation method and a sensor system with edge computing.

/pdf/input-output-improved-reservoir-computing-based-on-duffing-34yvyrz1.pdf

Input–Output-Improved Reservoir Computing Based on Duffing Resonator Processing Dynamic Temperature Compensation for MEMS Resonant Accelerometer

Current conductive polymers win wide applications in smart strain/stress sensors, bioinspired actuators, and wearable electronics. This paper investigates a novel strain sensor by using conductive polypyrrole (PPy) nanoparticles coated polyvinyl alcohol (PVA) fibers as matrix. The flexible, water-resistant PVA fibers are initially prepared by combined electrospinning and annealing techniques, and then are coated with PPy nanoparticles through in situ polymerization. The resultant PPy@PVA fibers exhibit stable, favorable electrical conductivities due to the uniform point-to-point connections among PPy nanoparticles, e.g. after three-time' polymerizations, the PPy@PVA3 fiber film presents a sheet resistance of ∼840 Ω/sq and a bulk conductivity of ∼32.1 mS/cm. Cyclic sensing tests reveal that, PPy@PVA sensors show linear relationships between the relative resistance variations and the applied strains, e.g. the linear deviation of PPy@PVA3 is only 0.9 % within 33 % strain. After long-term stretching/releasing cycles, the PPy@PVA sensor exhibits stable, durable, and reversible sensing behaviors, no evident "drift" is observed over 1,000 cycles (5,000 seconds). This article is protected by copyright. All rights reserved.

Xiaowei Guo

Papers

Surface plasmon resonance based biosensor technique: a review

Enhancing the Recognition Task Performance of MEMS Resonator-Based Reservoir Computing System via Nonlinearity Tuning

Input–Output-Improved Reservoir Computing Based on Duffing Resonator Processing Dynamic Temperature Compensation for MEMS Resonant Accelerometer

PVA electrospun fibers coated with PPy nanoparticles for wearable strain sensors.