Integrated silicon-based suspended racetrack micro-resonator for biological solution sensing with high-order mode

A biological sensing structure with a high-order mode(E^(y)_(21))is designed,which is composed of a suspended racetrack micro-resonator(SRTMR)and a microfluidic channel.The mode characteristics,coupling properties,and sensing performances are simulated by using the finite element method(FEM).To analyze the mode confinement property,the confinement factors in the core and cladding of the suspended waveguide for the E^(x)_(11),E^(y)_(11),and E^(y)_(21) are calculated.The simulation results show that the refractive index(RI)sensitivity of the proposed sensing structure can be improved by using the high-order mode(Ey 21).The RI sensitivity for the E^(y)_(21) mode is~201 nm/RIU,which is twice to thrice higher than those for the E^(x)_(11) mode and the E^(y)_(11) mode.Considering a commercial spectrometer,the proposed sensing structure based on the SRTMR achieves a limit of detection(LOD)of -4.7×10^(-6) RIU.Combined with the microfluidic channel,the SRTMR can possess wide applications in the clinical diagnostic assays and biochemical detections.

A Review on Surface Stress-Based Miniaturized Piezoresistive SU-8 Polymeric Cantilever Sensors

In the last decade, microelectromechanical systems(MEMS) SU-8 polymeric cantilevers with piezoresistive readout combined with the advances in molecular recognition techniques have found versatile applications,especially in the field of chemical and biological sensing.Compared to conventional solid-state semiconductor-based piezoresistive cantilever sensors, SU-8 polymeric cantilevers have advantages in terms of better sensitivity along with reduced material and fabrication cost. In recent times,numerous researchers have investigated their potential as a sensing platform due to high performance-to-cost ratio of SU-8 polymer-based cantilever sensors. In this article, we critically review the design, fabrication, and performance aspects of surface stress-based piezoresistive SU-8 polymeric cantilever sensors. The evolution of surface stress-based piezoresistive cantilever sensors from solid-state semiconductor materials to polymers, especially SU-8 polymer, is discussed in detail. Theoretical principles of surface stress generation and their application in cantilever sensing technology are also devised. Variants of SU-8 polymeric cantilevers with different composition of materials in cantilever stacks are explained. Furthermore, the interdependence of the material selection, geometrical design parameters, and fabrication process of piezoresistive SU-8 polymeric cantilever sensors and their cumulative impact on the sensor response are also explained in detail.In addition to the design-, fabrication-, and performancerelated factors, this article also describes various challenges in engineering SU-8 polymeric cantilevers as a universal sensing platform such as temperature and moisture vulnerability. This review article would serve as a guideline for researchers to understand specifics and functionality of surface stress-based piezoresistive SU-8 cantilever sensors.

Biologically Enabled Syntheses of Nanostructured 3-D Sensor Materials:the Potential for 3-D Genetically Engineered Microdevices (3-D GEMs)

Three-dimensional (3-D)self-assembly of nanos- tructures and nanodevices on a large scale remains a grand quest for mankind.Freestanding nanostructured assemblies with controlled 3-D shapes can exhibit attractive properties for sensor and other applications. Protocols for 3-D self-assembly that can be scaled up for mass production on a large up to tonnage)scale, while preserving morphological features on a small (down to nanometer)scale,are needed to allow for widespread use of 3-D nanostructures in advanced devices.However,these often conflicting requirements of scalability and precision pose a difficult challenge for synthetic (man-made)processing routes.

Tunable multiple plasmon resonances and local field enhancement of nanocrescent/nanoring structure

According to the plasmon hybridization theory, the plasmon resonance characteristics of the gold nanocrescent/nanoring(NCNR) structure are systematically investigated by the finite element method. It is found that the extinction spectra of NCNR structure exhibit multiple plasmon resonance peaks, which could be attributed to the result of the plasmon couplings between the multipolar plasmon modes of nanocrescent and the dipolar, quadrupolar, hexapolar, octupolar,decapolar plasmon modes of nanoring. By changing the geometric parameters, the intense and separate multiple plasmon resonance peaks are obtained and can be tuned in a wide wavelength range. It is further found that the plasmon coupling induces giant multipole electric field enhancements around the tips of the nanocrescent. The tunable and intense multiple plasmon resonances of NCNR structure may provide effective applications in multiplex biological sensing.

Detection and Classification of Diabetic Retinopathy Using DCNN and BSN Models

Diabetes is associated with many complications that could lead to death.Diabetic retinopathy,a complication of diabetes,is difficult to diagnose and may lead to vision loss.Visual identification of micro features in fundus images for the diagnosis of DR is a complex and challenging task for clinicians.Because clinical testing involves complex procedures and is timeconsuming,an automated system would help ophthalmologists to detect DR and administer treatment in a timelymanner so that blindness can be avoided.Previous research works have focused on image processing algorithms,or neural networks,or signal processing techniques alone to detect diabetic retinopathy.Therefore,we aimed to develop a novel integrated approach to increase the accuracy of detection.This approach utilized both convolutional neural networks and signal processing techniques.In this proposed method,the biological electro retinogram(ERG)sensor network(BSN)and deep convolution neural network(DCNN)were developed to detect and classify DR.In the BSN system,electrodes were used to record ERGsignal,which was preprocessed to be noise-free.Processing was performed in the frequency domain by the application of fast Fourier transform(FFT)and mel frequency cepstral coefficients(MFCCs)were extracted.Artificial neural network(ANN)classifier was used to classify the signals of eyes with DR and normal eye.Additionally,fundus images were captured using a fundus camera,and these were used as the input for DCNN-based analysis.The DCNN consisted of many layers to facilitate the extraction of features and classification of fundus images into normal images,non-proliferative DR(NPDR)or earlystage DR images,and proliferative DR(PDR)or advanced-stage DR images.Furthermore,it classifiedNPDRaccording tomicroaneurysms,hemorrhages,cotton wool spots,and exudates,and the presence of new blood vessels indicated PDR.The accuracy,sensitivity,and specificity of the ANNclassifier were found to be 94%,95%,and 93%,respectively.Both the accuracy rate and sensitivity rate of theDCNNclassifierwas 96.5%for the images acquired from various hospitals as well as databases.A comparison between the accuracy rates of BSN andDCNN approaches showed thatDCNNwith fundus images decreased the error rate to 4%.

Two-Channel Highly Sensitive Sensors Based on 4 × 4 Multimode Interference Couplers

We propose a new kind of microring resonators （MRR） based on 4 × 4 multimode interference （MMI） couplers for multichannel and highly sensitive chemical and biological sensors. The proposed sensor structure has advantages of compactness and high sensitivity compared with the reported sensing structures. By using the transfer matrix method （TMM） and numerical simulations, the designs of the sensor based on silicon waveguides are optimized and demonstrated in detail. We apply our structure to detect glucose and ethanol concentrations simultaneously. A high sensitivity of 9000 nm/RIU, detection limit of 2 × 10^-4 for glucose sensing and sensitivity of 6000 nm/RIU, detection limit of 1.3 × 10^-5 for ethanol sensing are achieved.

Single-waveguide-based microresonators for optical sensing

Optical biosensors with a high sensitivity and a low detection limit play a highly significant role in extensive scenarios related to our daily life. Combined with a specific numerical simulation based on the transfer matrix and resonance condition, the idea of novel single-waveguide-based microresonators with a double-spiral-race- track （DSR） shape is proposed and their geometry optimizations and sensing characteristics are also investigated based on the Vernier effect. The devices show good sensing performances, such as a high quality factor of 1.23 x 105, a wide wavelength range of over 120 nm, a high extinction ratio （ER） over 62.1 dB, a high sensitivity of 698.5 nm/RIU, and a low detection limit of 1.8 × 10^-5. Furthermore, single-waveguide-based resonators can also be built by cascading two DSR structures in series, called twin-DSRs, and the results show that the sensing properties are enhanced in terms of quasi free spectral range （FSR） and ER due to the double Vernier effect. Excellent features indicate that our novel single-waveguide-based resonators have the potential for future compact and highly integrated biosensors.