TY - JOUR A1 - Wohlschläger, Maximilian A1 - Versen, Martin A1 - Löder, Martin G. J. A1 - Laforsch, Christian T1 - A promising method for fast identification of microplastic particles in environmental samples: A pilot study using fluorescence lifetime imaging microscopy JF - Heliyon N2 - Microplastic pollution of the environment has been extensively studied, with recent studies focusing on the prevalence of microplastics in the environment and their effects on various organisms. Identification methods that simplify the extraction and analysis process to the point where the extraction can be omitted are being investigated, thus enabling the direct identification of microplastic particles. Currently, microplastic samples from environmental matrices can only be identified using time-consuming extraction, sample processing, and analytical methods. Various spectroscopic methods are currently employed, such as micro Fourier-transform infrared, attenuated total reflectance, and micro Raman spectroscopy. However, microplastics in environmental matrices cannot be directly identified using these spectroscopic methods. Investigations using frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) to identify and differentiate plastics from environmental materials have yielded promising results for directly identifying microplastics in an environmental matrix. Herein, two artificially prepared environmental matrices that included natural soil, grass, wood, and high-density polyethylene were investigated using FD-FLIM. Our first results showed that we successfully identified one plastic type in the two artificially prepared matrices using FD-FLIM. However, further research must be conducted to improve the FD-FLIM method and explore its limitations for directly identifying microplastics in environmental samples. KW - FD-FLIM KW - Fluorescence lifetime KW - Environmental science KW - Fluorescence microscopy KW - Material identification KW - Microplastics Y1 - 2024 U6 - https://doi.org/10.1016/j.heliyon.2024.e25133 VL - 10 IS - 3 ER - TY - JOUR A1 - Wohlschläger, Maximilian A1 - Versen, Martin A1 - Löder, Martin G. J. A1 - Laforsch, Christian T1 - Identification of different plastic types and natural materials from terrestrial environments using fluorescence lifetime imaging microscopy. JF - Analytical and Bioanalytical Chemistry N2 - Environmental pollution by plastics is a global issue of increasing concern. However, microplastic analysis in complex environmental matrices, such as soil samples, remains an analytical challenge. Destructive mass-based methods for microplastic analysis do not determine plastics’ shape and size, which are essential parameters for reliable ecological risk assessment. By contrast, nondestructive particle-based methods produce such data but require elaborate, time-consuming sample preparation. Thus, time-efficient and reliable methods for microplastic analysis are needed. The present study explored the potential of frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) for rapidly and reliably identifying as well as differentiating plastics and natural materials from terrestrial environments. We investigated the fluorescence spectra of ten natural materials from terrestrial environments, tire wear particles, and eleven different transparent plastic granulates <5 mm to determine the optimal excitation wavelength for identification and differentiation via FD-FLIM under laboratory conditions. Our comparison of different excitation wavelengths showed that 445 nm excitation exhibited the highest fluorescence intensities. 445 nm excitation was also superior for identifying plastic types and distinguishing them from natural materials from terrestrial environments with a high probability using FD-FLIM. We could demonstrate that FD-FLIM analysis has the potential to contribute to a streamlined and time-efficient direct analysis of microplastic contamination. However, further investigations on size-, shape-, color-, and material-type detection limitations are necessary to evaluate if the direct identification of terrestrial environmental samples of relatively low complexity, such as a surface inspection soil, is possible. KW - FD-FLIM KW - Fluorescence lifetime KW - Microplastic contamination KW - Microplastic in soils KW - Plastic identification KW - Terrestrial pollution Y1 - 2024 U6 - https://doi.org/10.1007/s00216-024-05305-w ER - TY - CHAP A1 - Heitzmann, Sebastian A1 - Wohlschläger, Maximilian A1 - Leiter, Nina A1 - Löder, Martin G. J. A1 - Versen, Martin A1 - Laforsch, Christian T1 - Classification of Foods and Plastics using FD-FLIM and Neural Networks T2 - 2024 IEEE Sensors Applications Symposium (SAS) N2 - Plastics and foods can be differentiated by their material characteristic fluorescence properties, especially their fluorescence lifetimes. An areal measurement of fluorescent lifetimes of these materials can be done using Frequency-Domain Fluorescence Lifetime Imaging Microscopy (FD-FLIM). Up until now, most plastic detection is done using NIR or X-ray, while most applications of FD-FLIM are in biomedicalfields. The application of FD-FLIM in a food safety setting presents a promising approach to the detection of plastic contaminants. A Multilayer Perceptron (MLP) based neural network is developed to reliably identify the presence of plastic in a food/plastic sample via FD-FLIM. Features like the mean, median, standard deviation, variance, range, and interquartile range are calculated from the intensity image, the phase shift and modulation index along with the according phase- and modulation-dependent fluorescence lifetimes from the FD-FLIM data. For training, test and validation, a total of 3520 FD-FLIM measurements have been taken at 445nm excitation of sixteen samples with the labels food and plastic. To rank the performance of the 3888 trained networks, Fl-score, accuracy, precision, and recall are used as metrics. The best performing network reaches a Fl-score of 98.86% proving that a differentiation of foods and plastics using a MLP classification based on FD- FLIM data is possible with a low error rate. KW - fluorescence KW - foods KW - FLIM KW - MLP KW - neural networks Y1 - 2024 U6 - https://doi.org/10.1109/SAS60918.2024.10636453 SP - 1 EP - 6 PB - IEEE ER - TY - CHAP A1 - Leiter, Nina A1 - Schwarz, Jonas A1 - Versen, Martin A1 - Risse, Michael A1 - Löder, Martin G.J. A1 - Laforsch, Christian T1 - A non-destructive approach to wood origin differentiation using FD-FLIM T2 - 2024 IEEE Sensors Applications Symposium (SAS) N2 - Wood auto-fluorescence, primarily attributed to lignin, presents a distinctive feature. Different wood species exhibit variations in lignin distribution. Frequency-Domain Fluorescence Lifetime Imaging Microscopy is effective in distinguishing wood species based on their fluorescence characteristics. This study investigates the potential to differentiate the origins of beech, spruce, and larch through phase-dependent fluorescence decay times. Therefore the zero hypothesis H0 is tested: The phase dependent fluorescence lifetimes of samples from the same species but varying in origin are equal. To determine the fluorescence characteristics of woods of different origins, wood samples of the species Fagus sylvatica L. (beech), Larix decidua Mill. (larch), and Picea abies (L.) H. Karst. (spruce) from Germany, Austria, the Netherlands, Spain, Sweden, New Zealand and Romania were analyzed. The wood samples were analyzed with a FD-FLIM camera setup, including a laser source emitting at an excitation wavelength of 445 nm. Employing Analysis-of-Variance hypothesis testing on fluorescence lifetime data for each wood species, the results indicate that 23 out of 35 origin pairs could be distinguished at a 5% significance level. While acknowledging the challenges of origin-based differentiation, the findings emphasize the promising potential of fluorescence lifetime imaging microscope as a valuable tool in this context. Moving forward, a more intricate approach to sample differentiation should involve acquiring detailed information about the samples, including associated temperature and precipitation profiles, and soil composition. KW - wood KW - fluorescence KW - FLIM KW - origin KW - species Y1 - 2024 U6 - https://doi.org/10.1109/SAS60918.2024.10636550 SP - 1 EP - 6 PB - IEEE ER -