The paper presents a comprehensive analysis of the elastic properties of polystyrene-based nanocomposites filled with different types of inclusions: small spherical particles (SiO₂ and Al₂O₃), alumosilicates (montmorillonite, halloysite natural tubules and mica), and carbon nanofillers (carbon black and multi-walled carbon nanotubes). Block samples of composites with different filler concentrations were fabricated by melt technology, and their linear and non-linear elastic properties were studied. The introduction of more rigid particles led to a more profound increase in the elastic modulus of a composite, with the highest rise of about 80% obtained with carbon fillers. Non-linear elastic moduli of composites were shown to be more sensitive to addition of filler particles to the polymer matrix than linear ones. A non-linearity modulus β_s comprising the combination of linear and non-linear elastic moduli of a material demonstrated considerable changes correlating with those of the Young’s modulus. The changes in non-linear elasticity of fabricated composites were compared with parameters of bulk non-linear strain waves propagating in them. Variations of wave velocity and decay decrement correlated with the observed enhancement of materials’ non-linearity.

In this paper, we present a novel numerical approach for increasing the resolution of retrieved images of objects after their diffraction patterns are recorded via terahertz pulse time-domain holography (THz PTDH). THz PTDH allows for spectrally resolved imaging with high spatial resolution and does not require the fine alignment of complex optics in the THz path. The proposed data post-processing method opens up the possibility to reconstruct holograms recorded with spatially restricted THz detectors, and overcome the diffraction limit even for the lower-frequency spectral components. The method involves an iterative procedure of backward-forward wavefront propagation to simulate the field distribution beyond the initially recorded hologram area. We show significant improvement in both the object reconstruction and contrast across the whole spectrum, with qualitative resolution enhancement at lower frequency spectral components.

In this report, we present implementation and validation of machine-learning classifiers for distinguishing between cell types (HeLa, A549, 3T3 cell lines) and states (live, necrosis, apoptosis) based on the analysis of optical parameters derived from cell phase images. Validation of the developed classifier shows the accuracy for distinguishing between the three cell types of about 93% and between different cell states of the same cell line of about 89%. In the field test of the developed algorithm, we demonstrate successful evaluation of the temporal dynamics of relative amounts of live, apoptotic and necrotic cells after photodynamic treatment at different doses.

The paper presents a novel algorithm based on digital holographic interferometry and being promising for evaluation of phase variations from highly noisy or modulated by speckle-structures digital holograms. The suggested algorithm simulates an interferogram in finite width fringes, by analogy with classical double exposure holographic interferometry. Thus obtained interferogram is then processed as a digital hologram. The advantages of the suggested approach are demonstrated in numerical experiments on calculations of differences in phase distributions of wave fronts modulated by speckle structure, as well as in a physical experiment on the analysis of laser-induced heating dynamics of an aqueous solution of a photosensitizer. It is shown that owing to the inherent capability of the approach to perform adjustable smoothing of compared wave fronts, the resulting difference undergoes noise filtering. This capability of adjustable smoothing may be used to minimize losses in spatial resolution. Since the method allows to vary an observation angle of compared wave fields, an opportunity to compensate misalignment of optical axes of these wave fronts arises. This feature can be required, for example, when using two different setups in comparative digital holography or for compensation of recording system displacements during a set of exposures in studies of dynamic processes.

Digital holographic microscopy supplemented with the developed cell segmentation and machine learning and classification algorithms is implemented for quantitative description of the dynamics of cellular necrosis induced by photodynamic treatment in vitro. It is demonstrated that the developed algorithms operating with a set of optical, morphological, and physiological parameters of cells, obtained from their phase images, can be used for automatic distinction between live and necrotic cells. The developed classifier provides high accuracy of about 95.5% and allows for calculation of survival rates in the course of cell death.

Numerous studies have been performed on different aspects of the mechanical behavior of polymer nanocomposites; however, the results obtained still lack a comprehensive comparative analysis of the mechanical properties of composites containing nanofillers of different shapes and concentrations and subjected to different static and dynamic loads. Carbon nanofillers were shown to provide the most significant improvement in the elastic properties of polymer composites. In this paper, we present a comparative analysis of the mechanical properties of polystyrene-based nanocomposites filled with carbon allotropes of different shapes: spherical fullerene particles, filamentary multi-walled nanotubes, and graphene platelets, fabricated by the same technology. The influence of shape and concentration of dispersed carbon fillers on mechanical and viscoelastic properties of composites in different stress–strain states was evaluated based on the results of tensile and three-point bending tests, and ultrasonic and dynamic mechanical analysis. Comparison of the static and dynamic elastic properties of nanocomposites allowed us to analyze their variations with frequency. At low concentrations of 0.1 wt% and 0.5 wt% all nanofillers did not provide significant improvement of elastic characteristics of composites. More efficient reinforcement was observed at the concentration of 5 wt%. Among the filler types, some increase in composite rigidity was observed with the addition of filamentary particles. The introduction of the layered filler provided the most pronounced rise in the composite rigidity. The weak frequency dependence of the mechanical loss tangent, which is characteristic of amorphous thermoplastics, was demonstrated for all the samples.