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Phase-sensitive surface plasmon resonance biosensors are known for their high sensitivity. One of the technology bottle-necks of such sensors is that the phase sensorgram, when measured at fixed angle set-up, can lead to low reproducibility as the signal conveys multiple data. Leveraging the sensitivity, while securing satisfying reproducibility, is therefore is an underdiscussed key issue. One potential solution is to map the phase sensorgram into refractive index unit by the use of sensor calibration data, via a simple non-linear fit. However, basic fitting functions poorly portray the asymmetric phase curve. On the other hand, multi-layer reflectivity calculation based on the Fresnel coefficient can be employed for a precise mapping function. This numerical approach however lacks the explicit mathematical formulation to be used in an optimization process. To this end, we aim to provide a first methodology for the issue, where mapping functions are constructed from Bayesian optimized multi-layer model of the experimental data. The challenge of using multi-layer model as optimization trial function is addressed by meta-modeling via segmented polynomial approximation. A visualization approach is proposed for assessment of the goodness-of-the-fit on the optimized model. Using metastatic cancer exosome sensing, we demonstrate how the present work paves the way toward better plasmonic sensors.

This paper presents the quadrature sinusoidal oscillators for a phase sensitive detection (PSD) system. The proposed oscillators are design by using the commercially available ICs (LT1228). The core oscillator consists of three LT1228s: two grounded capacitors and one resistor. By adding four resistors without the requirement of additional active devices, the amplitudes of two quadrature waveforms become adjustable. The quadrature output nodes are of low impedance, which can be connected to the impedance sensor or other circuits in a phase sensitive detection system without the need of buffer devices. The amplitudes of the quadrature waveform are equal during the frequency of oscillation (FO) tuning. The frequency of oscillation is electronically and linearly controlled by bias current or voltage without affecting the condition of oscillation (CO). Furthermore, the condition of oscillation is electronically controlled without affecting the frequency of oscillation. The performances of the proposed oscillators are experimentally tested with ±5 voltage power supplies. The frequency of the proposed sinusoidal oscillator can be tuned from 8.21 kHz to 1117.51 kHz. The relative frequency error is lower than 3.12% and the relative phase error is lower than 2.96%. The total harmonic distortion is lower than −38 dB (1.259%). The voltage gain of the quadrature waveforms can be tuned from 1.97 to 15.92. The measurement results demonstrate that the proposed oscillators work in a wide frequency range and it is a suitable choice for an instrument-off-the-shelf device

This paper presents a low-power fully integrated quadrature signal generator for system-on-chip (SoC) impedance spectroscopy applications. It has been designed in a 0.18 μm-1.8 V CMOS technology as a self-contained oscillator, without the need for an external reference clock. The frequency can be digitally tuned from 10 to 345 kHz with 12-bit accuracy and a relative mean error below 1.7%, thus supporting a wide range of impedance sensing applications. The proposal is experimentally validated in two impedance spectrometry examples, achieving good magnitude and phase recovery results compared to the results obtained using a commercial LCR-meter. Besides the wide frequency tuning range, the proposed programmable oscillator features a total power consumption lower than 0.77 mW and an active area of 0.129 mm2, thus constituting a highly suitable choice as stimulation module for instrument-on-a-chip devices.