In this work, we explore the manifestation of optical nonlinearities in silicon, given illumination by radiation with wavelengths in the optical communication (C-band) spectrum, near 1550 nm, and extreme intensities, spanning 100-1000 GW/cm2. We photoexcite a silicon photodiode with femtosecond-duration 1550-nm laser pulses and observe the resulting optical autocorrelations as a function of the peak pulse intensity. Such measurements in silicon reveal (i) negligible single-photon absorption, suggesting that there are few defect (trap) states in the bandgap that can assist below-bandgap photoexcitation, (ii) significant two-photon absorption at intensities above 100 GW/cm2, (iii) growing three-photon absorption at intensities rising above a threshold of 300 GW/cm2, and (iv) increasing saturation at intensities rising above a threshold of 650 GW/cm2. We attribute this saturation to the extremely high density of charge carriers brought about by three-photon absorption—as this depletes the available electrons in the valence band and the available states in the conduction band. We hope that this work will be a foundation for the future integration of telecom (C-band) technologies and silicon nanostructures.
Kalman filtering (KF) is a widely used filtering technique in highly predictable temporal-mechanical systems where system noise can be modelled with a gaussian function. Improving the signal quality during acquisition is conventionally accomplished by increasing integration time in acquisition. However, this increases the signal acquisition time in photonic systems. In high noise applications, acquisition time is low, and this post-process filtering technique can be applied to increase signal quality. This work explores the comparison of the KF, and nonlinear filtering methods to a simulated blackbody radiation signal where gaussian noise is added to mimic electrical interference. Three filters are selected for comparison on the ability to improve the root mean square error (RMSE) of a simulated measured signal with respect to a simulated actual signal. The filters that are compared in this work are the Extended Kalman Filter (EKF), the Unscented Kalman (UKF), and the Extended Sliding Innovation Filter (ESIF). The filters use a calibration temperature that the filter model uses to determine expected values. To compare the filters, the RMSE is evaluated when error is introduced to the simulation by changing the actual temperature to values equal, below, and above the calibration temperature. Two additional scenarios were considered to test filter robustness. The first scenario uses changes in model temperature occurring as a function of wavelength (i.e., temperature change mid-scan). The second scenario introduces impurities with different emission values. The ESIF demonstrated favorable performance over the other considered filters, showing promise in optical applications.
Microfluidic technologies and on-chip optical components have advanced such that on-chip sensing of minute chemical and molecular compounds is possible, e.g., detection of gases, pathogens, and DNA. Such DNA analyses require purification and amplification to maximize sensitivity. A common method for amplification of a DNA segment is polymerase chain reaction (PCR), which amplifies DNA segments through temperature changes in an assay process. As such, there is great interest in optofluidic lab-on-a-chip PCR methods. However, developments are limited due to challenges in optically driven temperature fluctuations. These challenges arise when the microfluidic samples are smaller than the optical penetration depth of the incident light and only minimal absorption is achieved. To overcome these challenges, this work presents a bio-photonic approach to the PCR method which utilizes infrared (IR) radiation with whispering gallery mode (WGM) waves. The WGM waves greatly increase the interaction length in the microdroplet, allowing smaller (and scalable) dimensions. This improved interaction length occurs because the applied IR radiation is confined along the perimeter of the microdroplet and its surrounding medium. The operation is modelled with finite-different time-domain electromagnetic simulations, comparing current optical heating with the presented technique. These simulations are validated through an experimental analysis with a thermal camera measuring temperature fluctuations. Ultimately, the presented approach is shown to greatly increase scalability in PCR lab-on-a-chip systems.
Advancements in continuous and digital microfluidics (DMF) for integrated optics technologies are improving the feasibility of biophotonic sensors within lab-on-a-chip devices. Lab-on-a-chip diagnostic devices are achieving unprecedented high levels of throughput. Digital microfluidics, with its reconfigurable nature, is often utilized over continuous microfluidic systems due to reagent economy, precision, potential for scalability, and independent fluid actuation. However, scalability within DMF systems is currently inhibited by the DMF sensing architectures that are presently used, being capacitance and resistance sensing. These electrical-based sensing architectures probe each microdroplet location and this is difficult to scale. In this work, a fibre-optic sensing architecture is developed to improve scalability and achieve independent sensing of microdroplets. The sensing architecture utilizes an m × n (column and row) perpendicular overlap grid structure of embedded fibre-optic cables that yields m × n sensing positions with m + n measurement points. To evaluate both localized and practical scalability of the system, actuation contact time and differentiation of multiple microdroplets are assessed. The embedded fibre-optic cables will distribute light proportional to the number of microdroplets in contact along the column or row. Differentiation of multiple microdroplets is assessed with a theoretical model and through experimental measurements. The DMF sensing architecture is demonstrated for a three by three grid with multiple microdroplets present. The results show compatibility with high-speed DMF operation (due to fast contact times) and demonstrate scalable sensing of multiple microdroplets.
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