Ezra Kwok

Performance of ultra-thin SOI-based resonators for sensing applications

This work presents simulation and experimental results of ultra-thin optical ring resonators, having larger Evanescent Field (EF) penetration depths, and therefore larger sensitivities, as compared to conventional Silicon-on-Insulator (SOI)-based resonator sensors. Having higher sensitivities to the changes in the refractive indices of the cladding media is desirable for sensing applications, as the interactions of interest take place in this region. Using ultra-thin waveguides (<100 nm thick) shows promise to enhance sensitivity for both bulk and surface sensing, due to increased penetration of the EF into the cladding. In this work, the designs and characterization of ultra-thin resonator sensors, within the constraints of a multi-project wafer service that offers three waveguide thicknesses (90 nm, 150 nm, and 220 nm), are presented. These services typically allow efficient integration of biosensors with on-chip detectors, moving towards the implementation of lab-on-chip (LoC) systems. Also, higher temperature stability of ultra-thin resonator sensors were characterized and, in the presence of intentional environmental (temperature) fluctuations, were compared to standard transverse electric SOI-based resonator sensors.

Optical Absorption Glucose Measurements Using 2.3-

Continuous glucose monitoring has been shown to help diabetes mellitus patients stabilize their glucose levels, leading to improved patient health. One promising technique for monitoring blood glucose concentration is to use optical absorption spectroscopy. This letter proposes the use of thermally tunable 2.3-mum vertical-cavity surface-emitting lasers to obtain blood absorption spectra. The partial least squares technique is used to determine the glucose concentration from the spectra obtained in aqueous glucose solutions.

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Perfusion culture optimization in multiple noninstrumented small‐scale flasks allows reduced expense and time associated with process development. These cultures normally use a different process mode because at small scales it is not practical to retain the cells for medium perfusion. In this work, the kinetics of growth, nutrient consumption, metabolite, and product formation were compared in spinner cultures operated in batch, semicontinuous, chemostat, and perfusion modes. Fed‐batch was also included to provide an added comparison. Using logistic fitting for more reliable specific rate estimates in transient conditions, the growth phase of batch cultures predicted similar kinetics to fed‐batch and continuous processes. For daily medium exchange rates up to 50%, the semicontinuous mode also predicted the perfusion process kinetics. Differences between the chemostat and semicontinuous culture results were only observed at higher exchange rates with the greatest daily culture perturbation. Overall, the batch or semicontinuous cultures were shown to readily provide results similar to the far more complex to operate chemostat or perfusion cultures.

m Vertical-Cavity Semiconductor Lasers

Abstract Uncertainties are ubiquitous and unavoidable in process design and modeling. Because they can significantly affect the safety, reliability and economic decisions, it is important to quantify these uncertainties and reflect their propagation effect to process design. This paper proposes the application of generalized polynomial chaos (gPC)-based approach for uncertainty quantification and sensitivity analysis of complex chemical processes. The gPC approach approximates the dependence of a process state or output on the process inputs and parameters through expansion on an orthogonal polynomial basis. All statistical information of the interested quantity (output) can be obtained from the surrogate gPC model. The proposed methodology was compared with the traditional Monte-Carlo and Quasi Monte-Carlo sampling-based approaches to illustrate its advantages in terms of the computational efficiency. The result showed that the gPC method reduces computational effort for uncertainty quantification of complex chemical processes with an acceptable accuracy. Furthermore, Sobol’s sensitivity indices to identify influential random inputs can be obtained directly from the surrogated gPC model, which in turn further reduces the required simulations remarkably. The framework developed in this study can be usefully applied to the robust design of complex processes under uncertainties.

Simpler Noninstrumented Batch and Semicontinuous Cultures Provide Mammalian Cell Kinetic Data Comparable to Continuous and Perfusion Cultures

A biomechanical model of the female pelvic support system was developed to explore the contribution of pelvic floor muscle defect to the development of stress urinary incontinence (SUI). From a pool of 135 patients, clinical data of 26 patients with pelvic muscular defect were used in modelling. The model was employed to estimate the parameters that describe the stiffness properties of the vaginal wall and ligament tissues for individual patients. The parameters were then implemented into the model to evaluate for each patient the impact of pelvic muscular defect on the vaginal apex support and the bladder neck support, a factor that relates to the onset of SUI. For the modelling analysis, the compromise of pelvic muscular support was demonstrated to contribute to vaginal apex prolapse and bladder neck prolapse, a condition commonly seen in SUI patients, while simulated conditions of restored muscular support were shown to help re-establish both vaginal apex and bladder neck supports. The findings illustrate the significance of pelvic muscle strength to vaginal support and urinary continence; therefore, the clinical recommendation of pelvic muscle strengthening, such as Kegel exercises, has been shown to be an effective treatment for patients with SUI symptoms.

Uncertainty quantification and global sensitivity analysis of complex chemical process using a generalized polynomial chaos approach

Diabetes Mellitus is a common chronic disease that has become a public health issue. Continuous glucose monitoring improves patient health by stabilizing the glucose levels. Optical methods are one of the painless and promising methods that can be used for blood glucose predictions. However, having accuracies lower than what is acceptable clinically has been a major concern. Using lasers along with multivariate techniques such as Partial Least Square (PLS) can improve glucose predictions. This research involves investigations for developing a novel optical system for accurate glucose predictions, which leads to the development of a small, low power, implantable optical sensor for diabetes patients.

A biomechanical model to assess the contribution of pelvic musculature weakness to the development of stress urinary incontinence.

Evanescent field sensors have shown promise for biological sensing applications. In particular, Silicon-on-Insulator (SOI)-nano-photonic based resonator sensors have many advantages for lab-on-chip diagnostics, including high sensitivity for molecular detection and compatibility with CMOS foundries for high volume manufacturing. We have investigated the optimum design parameters within the fabrication constraints of Multi-Project Wafer (MPW) foundries that result in the highest sensitivity for a resonator sensor. We have demonstrated the optimum waveguide thickness needed to achieve the maximum bulk sensitivity with SOI-based resonator sensors to be 165 nm using the quasi-TM guided mode. The closest thickness offered by MPW foundry services is 150 nm. Therefore, resonators with 150 nm thick silicon waveguides were fabricated resulting in sensitivities as high as 270 nm/RIU, whereas a similar resonator sensor with a 220 nm thick waveguide demonstrated sensitivities of approximately 200 nm/RIU.

Optical glucose monitoring using vertical cavity surface emitting lasers (VCSELs)

Metformin is an antihyperglycemic agent commonly used for the treatment of Type II diabetes mellitus. However, its effects on patients are derived usually from clinical experiments. In this study, a dynamic model of Type II diabetes mellitus with the treatment of metformin is proposed. The Type II diabetic model is a modification of an existing compartmental diabetic model. The dynamic simulation of the metformin effect for a Type II diabetic patient is based on the pharmacokinetic and pharmacodynamic relationship with a human body. The corresponding model parameters are estimated by optimization using clinical data from published reports. Then, the effect of metformin in both intravenous and oral administration on a Type II diabetes mellitus model are compared. The combination treatment of insulin infusion plus oral metformin is shown to be superior than the monotherapy with oral metformin only. These results are consistent with the clinical understanding of the use of metformin. For further work, the model can be analyzed for evaluating the treatment of diabetes mellitus with different pharmacological agents.

Optimized sensitivity of Silicon-on-Insulator (SOI) strip waveguide resonator sensor

A resonance-enhanced, defect-mediated, ring resonator photodetector has been implemented as a single unit biosensor on a silicon-on-insulator platform, providing a cost effective means of integrating ring resonator sensors with photodetectors for lab-on-chip applications. This method overcomes the challenge of integrating hybrid photodetectors on the chip. The demonstrated responsivity of the photodetector-sensor was 90 mA/W. Devices were characterized using refractive index modified solutions and showed sensitivities of 30 nm/RIU.

Pharmacokinetic-Pharmacodynamic Modeling of Metformin for the Treatment of Type II Diabetes Mellitus

Optical methods are one of the painless and promising techniques that can be used for blood glucose predictions for diabetes patients. The use of thermally tunable vertical cavity surface-emitting lasers (VCSELs) as the light source to obtain blood absorption spectra, along with the multivariate technique partial least squares for analysis and glucose estimation, has been demonstrated. With further improvements by using data preprocessing and two VCSELs, we have achieved a clinically acceptable level in the physiological range in buffered solutions. The results of previous experiments conducted using white light showed that increasing the number of wavelength intervals used in the analysis improves the accuracy of prediction. The average prediction error, using absorption spectra from one VCSEL in aqueous solution, is about 1.2 mM. This error is reduced to 0.8 mM using absorption spectra from two VCSELs. This result confirms that increasing the number of VCSELs improves the accuracy of prediction.