Structural Analysis of Polymer Composites Using Spectral Domain Optical Coherence Tomography

An Efficient Method for Laser Welding Depth Determination Using Optical Coherence Tomography

Online monitoring of laser welding depth is increasingly important, with the growing demand for the precise welding depth in the field of power battery manufacturing for new energy vehicles. The indirect methods of welding depth measurement based on optical radiation, visual image and acoustic signals in the process zone have low accuracy in the continuous monitoring. Optical coherence tomography (OCT) provides a direct welding depth measurement during laser welding and shows high achievable accuracy in continuous monitoring. Statistical evaluation approach accurately extracts the welding depth from OCT data but suffers from complexity in noise removal. In this paper, an efficient method coupled DBSCAN (Density-Based Spatial Clustering of Application with Noise) and percentile filter for laser welding depth determination was proposed. The noise of the OCT data were viewed as outliers and detected by DBSCAN. After eliminating the noise, the percentile filter was used to extract the welding depth. By comparing the welding depth determined by this approach and the actual weld depth of longitudinal cross section, an average error of less than 5% was obtained. The precise laser welding depth can be efficiently achieved by the method.

Fast and accurate spectral-estimation axial super-resolution optical coherence tomography

Spectral-estimation OCT (SE-OCT) is a computational method to enhance the axial resolution beyond the traditional bandwidth limit. However, it has not yet been used widely due to its high computational load, dependency on user-optimized parameters, and inaccuracy in intensity reconstruction. In this study, we implement SE-OCT using a fast implementation of the iterative adaptive approach (IAA). This non-parametric spectral estimation method is optimized for use on OCT data. Both in simulations and experiments we show an axial resolution improvement with a factor between 2 and 10 compared to standard discrete Fourier transform. Contrary to parametric methods, IAA gives consistent peak intensity and speckle statistics. Using a recursive and fast reconstruction scheme the computation time is brought to the sub-second level for a 2D scan. Our work shows that SE-OCT can be used for volumetric OCT imaging in a reasonable computation time, thus paving the way for wide-scale implementation of super-resolution OCT.

Patterned Photonic Array Based on an Intertwined Polymer Network Functionalized with a Nonenzymatic Moiety for the Visual Detection of Glucose

A patterned photonic array chip based on an intertwined polymer network (IPN) is proposed for the visual detection of glucose. The IPN networks are composed of photonic and poly(acrylic acid) (PAA) networks. Aminophenylboronic acid, as a nonenzymatic glucose-responsive moiety that can covalently bond to glucose at alkaline pH, forming tetragonal complexes, is immobilized in the PAA network; in hydrogels, this bonding generates Donnan osmotic pressure, resulting in a volumetric increase of the photonic IPN and reflected color change. The photonic band gap wavelength linearly increases with the glucose concentration (in the 1-12 mM range), with a limit of detection of 0.35 mM. The dots of the photonic IPN array respond independently, with high sensitivity and stability, to glucose via color changes; different glucose levels, from hypo- to hyperglycemia, can be visually detected in this way. Serum samples spiked with different glucose concentrations were tested for practical evaluation of the chip. The proposed chip could be utilized as a new biosensor platform for cost-effective and easy visual detection in remote areas, without the need of advanced instruments or technology.

In Vivo Non-Destructive Monitoring of Capsicum Annuum Seed Growth with Diverse NaCl Concentrations Using Optical Detection Technique

We demonstrate that optical coherence tomography (OCT) is a plausible optical tool for in vivo detection of plant seeds and its morphological changes during growth. To investigate the direct impact of salt stress on seed germination, the experiment was conducted using Capsicum annuum seeds that were treated with different molar concentrations of NaCl. To determine the optimal concentration for the seed growth, the seeds were monitored for nine consecutive days. In vivo two-dimensional OCT images of the treated seeds were obtained and compared with the images of seeds that were grown using sterile distilled water. The obtained results confirm the feasibility of using OCT for the proposed application. Normalized depth profile analysis was utilized to support the conclusions.