The enormous increase of Raman signal in the vicinity of metal nanoparticles allows surface-enhanced Raman spectroscopy (SERS) to be employed for label-free detection of substances at extremely low concentrations. However, the ultimate potential of label-free SERS to identify pharmaceutical compounds at low concentrations, especially in relation to biofluid sensing, is far from being fully realized. Opioids are a particular challenge for rapid clinical identification because their molecular structural similarities prevent their differentiation with immunolabeling approaches. In this paper, we report a new method called quantitative label-free SERS (QLF-SERS) which involves the formation of halide-conjugated gold nanoclusters trapping the analyte of interest near the SERS hot spots, and we demonstrate that it yields a 105 fold improvement in the detection limit over previously reported results for the entire class of clinically-relevant opioids and their metabolites. Measurements of opioid concentrations in multi-component mixtures are also demonstrated. QLF-SERS has comparable detection limits as currently existing laboratory urine drug testing techniques but is significantly faster and inexpensive and, therefore, could be easily adapted as part of a rapid clinical laboratory routine.
Pancreatic cancers are usually detected at an advanced stage and have poor prognosis. About one fifth of these arise from pancreatic cystic lesions. Yet not all lesions are precancerous, and imaging tools lack adequate accuracy for distinguishing precancerous from benign cysts. Therefore, decisions on surgical resection usually rely on endoscopic ultrasound-guided fine needle aspiration (EUS-FNA). Unfortunately, cyst fluid often contains few cells, and fluid chemical analysis lacks accuracy, resulting in dire consequences, including unnecessary pancreatic surgery for benign cysts and the development of cancer. Here, we report an optical spectroscopic technique, based on a spatial gating fibre-optic probe, that predicts the malignant potential of pancreatic cystic lesions during routine diagnostic EUS-FNA procedures. In a double-blind prospective study in 25 patients, with 14 cysts measured in vivo and 13 postoperatively, the technique achieved an overall accuracy of 95%, with a 95%confidence interval of 78–99%, in cysts with definitive diagnosis.
We experimentally demonstrate extraction of silicon waveguide geometry with subnanometer accuracy using optical measurements. Effective and group indices of silicon-on-insulator (SOI) waveguides are extracted from the optical measurements. An accurate model linking the geometry of an SOI waveguide to its effective and group indices is used to extract the linewidths and thicknesses within respective errors of 0.37 and 0.26 nm on a die fabricated by IMEC multiproject wafer services. A detailed analysis of the setting of the bounds for the effective and group indices is presented to get the right extraction with improved accuracy.
Programmable photonic integrated circuits are emerging as an attractive platform for applications such as quantum information processing and artificial neural networks. However, current programmable circuits are limited in scalability by the lack of low-power and low-loss phase shifters in commercial foundries. Here, we demonstrate a compact phase shifter with low-power photonic MEMS (micro-electro-mechanical systems) actuation on a silicon photonics foundry platform (IMEC's iSiPP50G). The device attains (2.9π ± π) phase shift at 1550 nm, with an insertion loss of (0.33 + 0.15 − 0.10 ) dB, a V π of (10.7 + 2.2 − 1.4 ) V, and an L π of (17.2 + 8.8 − 4.3 ) µm. We also measured an actuation bandwidth f -3dB of 1.03 MHz in air. We believe that our demonstration of a low-loss and low-power photonic MEMS phase shifter implemented in silicon photonics foundry compatible technology lifts a main roadblock towards the scale-up of programmable photonic integrated circuits.
We present a simulation framework for evaluating the effect of location-dependent variability in photonic integrated circuits. The framework combines a fast circuit simulator with circuit layout information and wafer maps of waveguide width and layer thickness variations to estimate the statistics of the circuit performance through Monte Carlo simulations. We illustrate this with ring resonator filters, a design sweep of Mach-Zehnder lattice filters, and the tolerance optimization of a Mach-Zehnder interferometer, and show how variability aware design can be essential for future photonic circuit design, especially in a fabless ecosystem where details of the foundry processes are not available to the designers.
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