Cristian Udrea

Micro- and nanoplastics are plastic particles with sizes below 1 or 5 mm for microplastics and 1 µm for nanoplastics. These particles can enter the environment through various pathways and subsequently affect all components of ecosystems. However, research on nanoplastics remains particularly limited, primarily due to challenges in isolating these particles from complex environmental matrices and producing them in controlled laboratory settings, especially in terms of size, shape, and purity. This study addresses the urgent need for standardized nanoplastic test materials by comparing various bottom-up and top-down laboratory methods for the preparation of polyethylene terephthalate (PET) micro- and nanoplastics, with a focus on their potential applications in environmental research. Chemical methods based on dissolution and recoagulation (using solvents such as 1,1,1,3,3,3-hexafluoro-2-propanol, trifluoroacetic acid, and chlorobenzene) and physical methods (including cryomilling and laser ablation) were evaluated. The resulting PET particles were characterized in terms of their size, polydispersity, morphology, and surface structure. For chemical methods, the presence of residual solvents was also analyzed. Chemical methods exhibited significant limitations, such as low reproducibility, polydisperse particles (PDI up to 11.4), strong aggregation tendencies, and the presence of potentially toxic solvent residues which make them unsuitable for standardized toxicity testing. From this point of view, physical methods represent solvent-free approaches. Cryomilling, however, proved ineffective due to surface melting of the particles during the process. Laser ablation produced highly monodisperse particles with regular spherical shapes, a median size of 340 nm, a size range of 193 to 9.5 µm, and a very low polydispersity index (PDI = 1.003 ± 0.002). These particles fall within the nanoplastic domain and showed no detectable contamination, making them especially suitable for environmental toxicity studies. Moreover, the method demonstrated consistent repeatability across replicates and is highly promising for producing standardized test materials for environmental fate, transport, and toxicity research. Graphical abstract

In lieu of the traditional method of data encryption using Hadamard matrices we here propose a method which change in the encryption part mathematical with physical means, namely the mathematical Hadamard transform with the physical Fourier transform using a lens. The Fourier transform has a lower power of compression, but the advantage of using physical encoding compensated for this disadvantage. Our approach has two parts, an encryption-compression stage, and a decryption-decompression stage, which are supposed to be complementary and are coupled by means of a computer which controls both experiments and uses the output of the encryption-compression stage as input for the decryption-decompression stage.

Single Pixel Camera (SPC) is an alternative architecture for imaging systems that emerged as an application of Compressive Sensing theory. The SPC distinctive feature is the single detector that measures linear combinations of pixels instead of pixels as in imaging array cameras. The measurements are obtained by projecting the scene on a Spatial Light Modulator (SLM), the other distinctive component of the SPC architecture. This paper discusses the problem of resolution in SPC. We show that in terms of Point Spread Function (PSF), the resolution model is similar to that of an imaging array camera except the fact that the role of the imaging array is taken over by the SLM. This reduces the contribution of the optics to the SPC resolution comparing with the CCD cameras. Relying on an existing method, we develop a procedure that uses a circular chart to measure the camera PSF. Our procedure has as additional facilities the correction of chart tilt and the capability to work with non-circular apertures. At low noise, tilts up to 15 degrees are practically removed.

Compressive Sensing refers to the acquisition in compressed form of sparse signals. One of the CS applications is the Single Pixel Camera that rethinks the conventional imaging systems. The key part of the camera is a Spatial Light Modulator (SLM), which provides the mechanism for taking arbitrary measurements of the scene. The non-uniform sampling (NUS) scenario offers a simple procedure to select random samples from the scene, instead of taking random projections. This paper analyses the Single Pixel Camera performance using NUS in the case of two categories of samples: randomly distributed over the scene and selected from the contours vicinity. The NUS is compared, in terms of reconstructed images, with measurements obtained by projection on a random selection from the S-Transform basis. The results are given on simulated data and on real images obtained with the experimental model of a Single Pixel Camera. The comparison of reconstructed images in the three cases of measurements shows that, in terms of PSNR, the NUS with contour pixels is equivalent with the S-transform based measurement.

A simple way to make physical encoding of data is to use some common Fourier optics tools, like lenses and some more sophisticated ones like a digital matrix detector (CCD, Charged Coupled Devices), as in Fig. 1. Except now the encoding and the compacting of the data is not made using Hadamard transform but a Fourier transform, which has less compacting power. There is however the big advantage of physically encrypting the data instead of manually or digitally doing the computation. The input data may be anything, a note, a picture, a diagram, anything at all. It may come at a moment notice and does not require any special preparation on the part of the operator. One can accomplish real-time encoding. It may require, however that the message data to be made available in a specific format, independent of the contents of the message. For instance it may have to be inscribed on a transparency and to have certain dimensions.

A grating interferometer that uses the high diffraction orders in conjunction with a Twyman–Green commercial interferometer is used for the measurement of in plane movement of gratings. The high diffraction orders ensures the amplification of the measurement precision with a factor equal to the diffraction order of the measurement in principle, because no imaging of features marking the beginning and the end of the measured length feature is necessary, and therefore the resolution limits associated with microscope imaging are eliminated.