Circular economy policies and recycling play a pivotal role in fostering sustainable models for the wood industry capable of reducing the environmental impact of our consumption patterns. The production of Particleboard is a good example of industry that uses high quantities of recycled wood. However, it poses risks since wood often have contaminants that compromise compliance of safety standards. Thus, it is necessary to develop methodologies for rapid analysis of chemical contaminants in wood wastes that allow easy detection of these elements.
In this work, the capability of Laser-induced breakdown spectroscopy (LIBS) to detect a set of heavy metals in wood samples was explored. Some advantages of this technique, such as portability, minimal to no sample preparation, and quick analysis are characteristics that make this method one of the most suitable for this purpose of analysis.
In the majority of cases, the contamination comes from the pigments used in paints, varnishes, or coatings. Titanium (Ti) e.g. is a common element in white pigments and Chromium (Cr) in red and green pigments. To ensure the presence or absence of Cr and Ti, a set of 3 lines was analysed. The results revealed the presence of these elements and that 30% of the samples seem to be highly contaminated. The LIBS technique proved to be a powerful methodogy for decision-making purposes.
The application of surface treatments to cork stoppers is presently a common practice in the wine industry, designed to achieve maximum performance and optimal costumer experience of premium products. Unfortunately, current coating techniques lack efficient process control tools, often resulting in faulty products being detected too late, already in use, compromising performance, product quality and mining consumer confidence. In this work a fully automated system equipped with machine vision and automatic feeding of corks, was coupled with an imaging LIBS setup and used to perform a benchmarking against conventional quality control methods. Results clearly demonstrate the capability of the new LIBS system to effectively evaluate in real time the quality of silicone-based surface coatings in cork stoppers, effectively working as a tool for process control providing a route for effective optimization.
Spectral imaging is a powerful technology that uses spatially referenced spectral signatures to create informative visual maps of sample surfaces that can reveal more than what conventional RGB-visual images can show. Indeed, different spectroscopy modalities can provide different information about the same sample: for instance, Laser- Induced Breakdown Spectroscopy (LIBS) imaging can detect the presence of specific elements on the surface, while Raman imaging can identify the molecular structures and compositions of the sample, both of which have potential applications in various industrial processes, from quality control to material sorting. In the path from science to technology, the increasing accessibility to such solutions and the strong market pull have opened a window of opportunity for innovative multimodal imaging solutions, where information from distinct sources is set to be combined in order to enhance the capabilities of the single modality system. However, the practical implementation of multimodal spectral imaging is still a challenge, despite its theoretical potential, and as such, it is yet to be achieved.
In this work, we will go over multimodal spectral knowledge distillation, a disruptive approach to multimodal spectral imaging techniques that tries to explore the combination of two techniques to capitalize on their individual strengths. In specific, this approach allows us to utilize one technique as an autonomous supervisor for the other, leveraging the higher degree of knowledge and interpretability of one of the techniques to increase the performance and transparency of the other. We present some example scenarios with LIBS and HSI and Raman spectroscopy and LIBS, discussing the impact of this new approach for scientific and technological applications.
A low-computational intensive laser control approach is proposed for implementing an embedded control system, using pattern recognition by relevant principal component analysis for laser induced breakdown spectroscopy applications. The laser energy is directly related to the resulting spectral pattern and is determined by iterations in the feature space. Results show that single shot iterations until optimum energy can be significantly reduced by pattern recognition. A performance benchmark with minerals, alloys and pellets from material collected from a drill demonstrated an average of 50% improvement, significantly reducing sample deterioration and improving measurement safety.
A high-resolution advanced laser induced breakdown spectroscopy prototype was used to quantify lithium (Li) in lithiniferous rocks. Samples were collected from Barroso's mine (Portugal), claimed as Western Europe’s largest spodumene Li discovery. 51 samples from a reverse circulation drill were collected, one for each meter interval, dried, milled, pressed into pellets and further analyzed by laser induced breakdown spectroscopy. Quantification was attempted using either linear models based on the intensity of selected Li spectral lines or advanced chemometrics methods. The latter was very successful, with correlation coefficients of 0.97 against certified laboratory results.
A new type of polymer and silica connection is proposed. A tapered SMF-28 silica optical fiber tip is fabricated using a CO2 laser by focusing and stretching the fiber. The tapered silica tip is inserted in one of the holes of a microstructured polymer optical fiber using a 3D alignment system. Using a supercontinuum source, the spectrum is observed after one and after two connections. The polymer fiber is characterized in curvature while using the previous connection.
The possibility of using polymer fiber as a refractive index sensor is presented. The sensor is based on a Fabry-Perot interferometer formed at the tip of the polymer fiber. The interference is granted due to reflections between a fiber Bragg grating and the fiber end-face. The sensor was characterized to refractive index changes at constant temperature using a fast Fourier transform analysis of the interference signal. A sensitivity of −1.94 RIU-1 was achieved with a resolution of 1 × 10-3 RIU and a cross sensitivity to temperature of 1 × 10-4 RIU/°C.
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