Identification of Polymers by Means of LIBS

Anzano, Jesús; Bello-Gálvez, C.; Lasheras, Roberto

doi:10.1007/978-3-642-45085-3_15

Cited by 7 publications

(2 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As LIBS has already been used for (spatially resolved) polymer classification 36,46,47 , it is a promising tool for the dectection of polymer degradation. LIBS inherently enables analysis of oxygen and should therefore also be able to detect oxidation of polymers.…”

Section: Depth Profiling Of Polymer Degradation and Oxidation Using Lmentioning

confidence: 99%

Combined LA-ICP-MS/LIBS: powerful analytical tools for the investigation of polymer alteration after treatment under corrosive conditions

Brunnbauer

Mayr

Larisegger

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Polymers are used in a variety of different areas, including applications in food packaging, automotive and the semiconductor industry. information about degradation of these materials during application, but also uptake of pollutants from the surrounding environment is therefore of great interest. conventional techniques used for polymer characterization such as ft-iR or Raman spectroscopy, but also thermo-analytical techniques offer insights into degradation processes but lack the possibility to detect uptake of inorganic species. Moreover, these techniques do not allow the measurement of depth profiles, thus information about degradation or pollutant uptake with sample depth is not accessible. in this work, we propose LA-icp-MS and LiBS as powerful analytical tools for polymer characterization, overcoming the limitations of conventional analytical techniques used for polymer analysis. Applicability of the developed procedures is demonstrated by the analysis of artificially weathered polyimides and modern art materials, indicating that the degradation of the polymer but also the uptake of corrosive gases is not limited to the sample surface. finally, a tandem LA-icp-MS/ LiBS approach is employed, which combines the advantages of both laser-based procedures, enabling the simultaneous analysis of polymer degradation and cadmium uptake of polystyrene after exposure to UV radiation and treatment with artificial sea water. Synthetic polymers and plastics are among the most commonly used materials in our modern world 1. They are mainly employed as packaging materials for consumer goods such as food and cosmetics and also bottles and boxes, but also frequently applied for construction materials 2. Polymers are also used as passivation or encapsulation materials in the semiconductor industry 3,4 or, in combination with pigments, as paints in the fields of art and cultural heritage 5,6. In general, the applied synthetic polymers are composed of an organic-carbon-chain polymer and different additives that give the materials the intended chemical and physical properties. Commonly applied additives include plasticizers, antioxidants, antistatic agents, lubricants, flame retardants or inorganic pigments. During application, polymers are often exposed to harmful environmental conditions, causing changes in their chemical composition. In this context, the negative influences of sunlight but also contact with ambient gases and environmental liquids have to be mentioned. Whereas UV light and oxidative gases are known to promote degradation 7-9 , corrosive gases or metals dissolved in rain, snow and river or seawater are susceptible for uptake into the polymer network, resulting in increased concentrations of inorganic constituents in aged materials. All of these possible interactions contribute to unwanted changes in the polymer composition, which finally lead to altered material properties (e.g. bleaching of colors, reduced thermal stability, increased brittleness, etc.). A comprehensive characterization of aged polymers is th...

show abstract

Section: Depth Profiling Of Polymer Degradation and Oxidation Using Lmentioning

confidence: 99%

Combined LA-ICP-MS/LIBS: powerful analytical tools for the investigation of polymer alteration after treatment under corrosive conditions

Brunnbauer

Mayr

Larisegger

et al. 2020

Sci Rep

View full text Add to dashboard Cite

show abstract

“…In the case of organic compounds such as polymers, the amount of useful information provided by the LIBS analysis is restricted by two phenomena: the partial loss of information about the molecular connectivity due to the sample atomization and the high similarity of the LIBS spectra caused by the similar elemental composition of polymers [ 20 ]. Nevertheless, subtle variations of the signal intensities related to the different stoichiometric ratios of the polymeric compounds exist and can be detected by means of various chemometric tools, which opens up the possibility of their discrimination [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Identification of 20 polymer types by means of laser-induced breakdown spectroscopy (LIBS) and chemometrics

et al. 2021

View full text Add to dashboard Cite

Over the past few years, laser-induced breakdown spectroscopy (LIBS) has earned a lot of attention in the field of online polymer identification. Unlike the well-established near-infrared spectroscopy (NIR), LIBS analysis is not limited by the sample thickness or color and therefore seems to be a promising candidate for this task. Nevertheless, the similar elemental composition of most polymers results in high similarity of their LIBS spectra, which makes their discrimination challenging. To address this problem, we developed a novel chemometric strategy based on a systematic optimization of two factors influencing the discrimination ability: the set of experimental conditions (laser energy, gate delay, and atmosphere) employed for the LIBS analysis and the set of spectral variables used as a basis for the polymer discrimination. In the process, a novel concept of spectral descriptors was used to extract chemically relevant information from the polymer spectra, cluster purity based on the k-nearest neighbors (k-NN) was established as a suitable tool for monitoring the extent of cluster overlaps and an in-house designed random forest (RDF) experiment combined with a cluster purity–governed forward selection algorithm was employed to identify spectral variables with the greatest relevance for polymer identification. Using this approach, it was possible to discriminate among 20 virgin polymer types, which is the highest number reported in the literature so far. Additionally, using the optimized experimental conditions and data evaluation, robust discrimination performance could be achieved even with polymer samples containing carbon black or other common additives, which hints at an applicability of the developed approach to real-life samples. Graphical abstract

show abstract