Dr. Stefano Di Frischia Profile

Dr. Stefano Di Frischia

at ENEA

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Author

Publications (2)

Proceedings Article | 7 October 2019 Presentation + Paper

Maximization of Raman signal in standoff detection under eye-safe conditions

F. Angelini, S. di Frischia, A. Chiuri, F. Colao

Proceedings Volume 11166, 1116609 (2019) https://doi.org/10.1117/12.2524467

KEYWORDS: Signal to noise ratio, Raman spectroscopy, Photons, Signal detection, Charge-coupled devices, Interference (communication), Sensors, Pulsed laser operation, Skin, Standoff detection

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Proceedings Article | 7 October 2019 Paper

Standardized characterization of inkjet-printed explosive trace samples

Frank Schnürer, Christian Ulrich, Roberto Chirico, Stefano Di Frischia, Raphael Moon, Kevin Hung

Proceedings Volume 11166, 111660W (2019) https://doi.org/10.1117/12.2533029

KEYWORDS: Particles, Image processing, Explosives, Printing, Standards development, Image segmentation, Statistical analysis, Inkjet technology, Microscopes, Image quality

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Detection systems for explosives have to be tested and validated with realistic samples. However, at present, well defined and characterized and homogeneous test materials for the development and validation of trace detection systems are still missing. Drop-on-demand and inkjet printing technology has become a promising method of producing standardized chemically contaminated test materials with high precision, accuracy, scalability, and flexibility to allow for the inexpensive, high throughput production. Especially for the preparation of samples for optical stand-off technologies the drop-on-demand technique leads to samples of higher quality. Test samples with contaminations ranging from nanograms to micrograms have been prepared and analysed over several weeks of storage. The influence of plot parameters on the morphology and durability of printed samples of various common explosives have been investigated on different substrates. Our results show that this technique leads to samples of higher quality compared to already existing preparation methods of reference samples. For the evaluation of deposition uniformity, quantity and reproducibility samples on several different surfaces, with different solvents and areal density distributions were prepared and analysed. HPLC measurements were used to quantitatively evaluate the durability of printed samples. The morphology of the test samples has been characterized by optical microscopy and confocal Raman-microscopy. This poster focuses on the development of a proposed standardized methodology for the characterization of particulate trace explosive samples of all types. Micrographs were processed with ImageJ (National Institutes of Health), an open source image processing program designed for scientific multidimensional images, which has already been applied to the shape analysis of particles in various research areas and for different materials. The main problem is to find the right threshold to apply to segment the image into features of interest (particles) and background. It is certainly a goal of digital image processing to establish protocols that eliminate variability, but currently it is not possible to use only one threshold with a fixed value for a set of images of samples of various explosives. Manual methods have several limitations like reduced reproducibility, high user bias, tedious and time-consuming fiddling-around finding an "appropriate" cut-off value, etc. The open source software that is in use to process the images provides several methods to automatically apply a threshold. Based on the morphology of the particles and the applied threshold, the obtained results can be really different and, an incorrect selection of the automatic threshold could provide either an overestimation or an underestimation of the parameters to be evaluated, particle size distribution and area coverage.

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