A fiber Bragg grating (FBG) interrogator is a scientific instrument that converts the wavelength change of FBG sensors into readable electrical signals. To achieve miniaturization and integration of FBG interrogator, we designed and fabricated a 36-channel array waveguide grating (AWG) on silica-based planar lightwave circuits (PLC) as a key device in a built FBG interrogation system. It is used to achieve continuous demodulation in C-band, while maintaining high resolution. This AWG has a 1.6 nm channel spacing, 3-dB bandwidth of 1.76 nm, non-adjacent channel crosstalk of −29.76 dB, and insertion loss of 3.46 dB. The dynamic range of the FBG interrogation system we built was tested to be 1522.4–1578.4 nm, with an interrogation resolution of 1 pm and accuracy of less than 1 pm in the dynamic range of 1523.16–1523.2 nm. The test results show that the FBG interrogation technology, based on AWG, can realize FBG wavelengths accurately demodulated, which has high application value in aerospace, deep sea exploration, and environmental monitoring, as well as other fields.

A novel method for the detection of triacylglycerides was reported with a pure, stable, label-free enzyme functionalized optical fiber detector. This method has been accomplished by immobilizing Zeolitic imidazolate framework-8 (ZIF-8) packaged lipase on the tapered optical fiber. The evanescent field is generated by tapering the optical fiber birefringent interferometer (BFI). Usage of ZIF-8/lipase as a biosensing film on optical fiber has not previously been reported. 4-nitrophenyl palmitate (4-NP) is used to determine the stability of the lipase encapsulated in ZIF-8. Tapered BFI works at a refractive index (RI), which matches the turning point to provide high sensitivity. The wavelength shift has a quadratic polynomial response relationship with the concentration of triacylglycerol, showing enhanced sensitivity and bio-selectivity. LOD (Limit of detection) of 0.17 μM and 0.23 nM is obtained with diameters of 10 μm and 7 μm, respectively. This sensor can be applied to triacylglycerides detection, requiring a low volume of blood for each sample.

The convolution neural network (CNN) is a classical neural network with advantages in image processing. The use of multiport optical interferometric linear structures in neural networks has recently attracted a great deal of attention. Here, we use three 3 × 3 reconfigurable optical processors, based on Mach-Zehnder interferometers (MZIs), to implement a two-layer CNN. To circumvent the random phase errors originating from the fabrication process, MZIs are calibrated before the classification experiment. The MNIST datasets and Fashion-MNIST datasets are used to verify the classification accuracy. The optical processor achieves 86.9% accuracy on the MNIST datasets and 79.3% accuracy on the Fashion-MNIST datasets. Experiments show that we can improve the classification accuracy by reducing phase errors of MZIs and photodetector (PD) noises. In the future, our work provides a way to embed the optical processor in CNN to compute matrix multiplication.

Fano resonance has an asymmetric and sharp resonance peak near the resonance wavelength, enhancing optical modulation performance. Here, a Fano resonant silicon optical modulator with a micro-ring resonator (MRR) coupled with a T-shaped waveguide is designed. Compared with an MRR modulator, a Fano resonance-based modulator has a smaller wavelength range of changes in optical intensity (from 0 a.u. to 1 a.u.). Under the condition of achieving the same light intensity change, Fano resonance only needs to shift the wavelength by 0.07 times compared with MRR. By optimizing the doping section and the Fano resonance line shape, the modulation depth of the Fano modulator is 12.44 dB, and an insertion loss of 0.41 dB is obtained. Moreover, it improves the modulation linearity. This modulator provides a new idea, to the best of our knowledge, for the single-cavity Fano resonance modulator.

Silicon photonics has shown great potential in integrated biochemical sensing. However, it is challenging to detect ions selectively, which is crucial in several biochemical application. In this paper, we propose and demonstrate a newly designed ion sensor by combining two-dimensional (2D) plasmonic and sub-nanoporous K _x MoO ₃ with a silicon waveguide. A T-shaped waveguide coupled with a microring resonator (MRR) generates Fano resonance at all resonance modes. Sharp Fano-like spectra were optimized by numerically simulating the structure of the waveguide in terms of the coupling coefficients, phase factor, and MRR power loss. In our design, a Fano resonance wavelength shift is caused by a refractive index change based on the interaction between 2D near-infrared plasmonic K _x MoO ₃ and K ⁺ . Moreover, the alteration in plasmonic absorption leads to a variation in transmission power. This dual-sensing output method is unique compared with existing methods that utilize optical ion sensors. Our results demonstrate that the micro-scale silicon waveguide combined with a 2D plasmonic material exhibits excellent potential as a chemical sensor.