Structural and thermoluminescence properties of lithium borate glass matrices under UV and beta radiation.

In the present work, glass samples in the (100 - x)B2O3-xLi2O binary system, with x varying from 30 to 50 mol%, were prepared using the conventional melting and moulding method, with the main objective of evaluating the thermoluminescence response when exposing these materials to ultraviolet (UV) radiation. Complementary analysis based on density, optical absorption on the UV-visible region (UV-vis absorbance), Fourier transform infrared spectroscopy on the medium region, X-ray diffraction, and differential thermal analysis measurements were performed. Thermoluminescence measurements of vitreous samples showed glow curves with at least one peak with a maximum temperature of ~170°C after exposure to UV radiation in the temperature range 50-250°C. Samples were also exposed to beta radiation in the temperature range 25-275°C, also showing single peaks with a maximum temperature of ~150°C.

Modeling microplastic with polyethylene (PE) spherical particles: a differential scanning calorimetry approach for quantification.

Detection, identification, and quantification of microplastics have become increasingly relevant for determining their contribution and role in environmental pollution. Thermal analysis is positioned as one of the alternative techniques employed to quantify microplastics. However, a deeper investigation that explores its capabilities is required, since in techniques such as difference scanning calorimetry (DSC), the result of the melting curve is potentially affected by the size of the micro particles. Therefore, to use this technique in the field of quantitative analysis of microplastics, it is necessary to make an evaluation of how the micro particle size affects the signal obtained. We use spherical polyethylene (PE) particles of different sizes (75-710 µm) as a microplastic model to study the effect of particle size and the mixtures of different particle sizes on the melting curve. The effect of possible interferences on the DSC signal was studied and real microplastics isolated from wastewater were tested. It was found that the DSC signal (both melting temperature and peak shape) is affected by the size of the particles, even in the case of mixtures of particles of different sizes. However, through an appropriate sample preparation, it is possible to identify the signals corresponding to microplastics of different sizes and thus quantify their contribution to the mass of the sample. It was evidenced that factors such as the presence of inorganic materials tend to modify the melting temperature. Also, removal of interferences of organic origin is feasible. In addition, the presence of PP, HDPE and LDPE was evidenced in wastewater samples. Our results represent an important advance in the use of the DSC technique in the field of microplastics, since the existence of particles of different sizes can be evidenced in the same sample allowing for an estimation of the number of microplastic particles. Finally, we show the applicability of DSC study on microplastics in environmental matrices.

Identification and quantitation of semi-crystalline microplastics using image analysis and differential scanning calorimetry.

There are several techniques used to analyze microplastics. These are often based on a combination of visual and spectroscopic techniques. Here we introduce an alternative workflow for identification and mass quantitation through a combination of optical microscopy with image analysis (IA) and differential scanning calorimetry (DSC). We studied four synthetic polymers with environmental concern: low and high density polyethylene (LDPE and HDPE, respectively), polypropylene (PP), and polyethylene terephthalate (PET). Selected experiments were conducted to investigate (i) particle characterization and counting procedures based on image analysis with open-source software, (ii) chemical identification of microplastics based on DSC signal processing, (iii) dependence of particle size on DSC signal, and (iv) quantitation of microplastics mass based on DSC signal. We describe the potential and limitations of these techniques to increase reliability for microplastic analysis. Particle size demonstrated to have particular incidence in the qualitative and quantitative performance of DSC signals. Both, identification (based on characteristic onset temperature) and mass quantitation (based on heat flow) showed to be affected by particle size. As a result, a proper sample treatment which includes sieving of suspended particles is particularly required for this analytical approach.