In this research, eco-friendly PLA filaments were 3D-printed using FDM. Three geometric shapes with different orders of rotational symmetry were selected to create infill patterns: an equilateral triangle, a square, and a regular hexagon. Additionally, each of these three infill patterns was modified by rotating the basic shape used to form the infill pattern by 0°, 15°, and 30°. The objective of this study was to analyze how the order of rotational symmetry within the infill pattern affects the mechanical properties of the printed specimens. To ensure consistency, infill density was kept as uniform as possible across all samples produced. DMA and tensile tests were performed on the produced specimens. The obtained mean values in the tensile measurements were compared using the Kruskal–Wallis test. Dunn’s test was used for post hoc pairwise multiple comparisons. DMA showed that when comparing different infill patterns, the specimens with an order of rotational symmetry of 3 (triangle) showed the highest modulus of elasticity, and the specimens with a 15° rotation regardless of shape generally had the highest storage modulus. Statistical analysis showed that the maximum force of the infill pattern with an order of rotational symmetry of 3 (triangle) was the least affected by the rotation angle, while the infill pattern with an order of rotational symmetry of 4 (square) and a 0° rotation displayed a significantly higher value of the maximum force than other patterns. The infill pattern with an order of rotational symmetry of 6 (hexagon) was moderately affected by the angle of rotation. Given the numerous infill patterns utilized in FDM, the results of this research offered a new viewpoint and insights into optimizing the mechanical properties of 3D-printed infill patterns.

This study aims to investigate the feasibility of using paper made from eco-friendly recycled and non-woody plants in graphic technology, particularly in offset printing. Instead of changing the composition or modifying the surface properties of the paper, the focus was on enhancing the print quality by modifying the printing ink. By modifying the printing inks, the quality of the prints on recycled and non-woody paper can be optimized, which in turn reduces the need for paper made from primary fibers. This approach can expand the use of alternative materials in graphic technology and design. The objective was to optimize the print quality on these sustainable materials. Five types of uncoated paper were used, with high-quality uncoated offset paper based on virgin fibers serving as a reference. Laboratory tests of the basic and surface properties were carried out to measure the paper quality parameters that are important for offset printing. The influence of the paper composition on its optical and colorimetric properties was also investigated. The interaction between the selected papers and offset inks was examined through measurements of adhesion parameters and ink transfer, i.e., the paper’s ability to accept the ink. To enhance the applicability of the investigated papers as printing substrates in the graphic industry, SiO₂ and TiO₂ nanoparticles were added to the offset inks. The influence of the paper composition on the colorimetric properties of the prints was also investigated. The print uniformity, as an important quality characteristic, was determined by measuring the mottling index. The research findings indicate that incorporating SiO₂ and TiO₂ nanoparticles into offset inks can enhance the interaction between the paper and ink, leading to improved print quality. This study provides new perspectives on the possibilities of using recycled and non-woody plant paper in offset printing without significantly compromising the quality of the print.

In this study, the surface modification of thin ink films with added nanoparticles was used to improve the functional properties of ink applied on paperboard substrates. The surface modification was performed by additional exposure of the samples to xenon radiation. Anatase TiO₂, rutile TiO₂ and ZnO were added to the base ink. The effect of surface modification on the surface, structural, and mechanical properties of the printed ink films was determined by FTIR-ATR spectroscopy, calculating the surface free energy and adhesion parameters, performing the rub resistance test of the printed samples, and by measuring the resistance to bending. Color measurements on the ink films were performed in order to observe the optical properties of unmodified and modified samples. The results showed that surface modification significantly improved the adhesion properties of the thin ink films and the mechanical properties of the samples. The results obtained on uncoated and coated paperboard showed that the addition of rutile TiO₂ and ZnO nanoparticles had the greatest effect on the rub resistance of the ink films. The results of the color analysis showed that the addition of nanoparticles did not change the optical properties of the modified ink films and that rutile TiO₂ and ZnO nanoparticles improved the lightfastness of the applied ink films.

In this work, three types of photopolymer printing plates for packaging printing were subjected to varied UV (ultraviolet radiation) post-treatments, and their surface free energy (SFE) components were calculated. SFE of the photopolymer printing plate is crucial in the process of transferring the ink from the printing plate to the substrate. Calculated polar and dispersive SFE components were used to build and optimize artificial neural networks for the prediction of the surface properties of different photopolymer materials after the performed UVA and UVC post-treatments. In this way, the production of printing plates with tailored SFE components could be automated and optimized. Consequently, products with improved qualitative properties could be printed. Results of the research have shown that the choice of the neural network’s activation function is most significant for the minimization of the mean squared error (MSE), while the number of neurons and hidden layers in neural networks has less influence on MSE. The optimized neural networks applied for common photopolymer materials in this work have the potential to be applied for the automation of the printing plates’ post-treatment process and the production of printing plates with surface properties tailored to specific printing systems.