Polyethylenes are the most widely used polymers and are gaining more and more interest due to their easy processability, relatively good mechanical properties and excellent chemical resistance. The disadvantage is their low temperature stability, which excludes particular high-density polyethylenes (HDPEs) for use in engineering applications where the temperature exceeds 100 °C for a long time. One of the possibilities of improving the temperature stability of HDPE is a modification by accelerated electrons when HDPE is cross-linked by this process and it is no longer possible to process it like a classic thermoplastic, e.g., by injection technology. The HDPE modified in this way was thermally stressed five times at temperatures of 110 and 160 °C, and then the dynamic tensile behavior was determined. The deformation and surface temperature of the specimens were recorded by a high-speed infrared camera. Furthermore, two thermal methods of specimen evaluation were used: differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The result of the measurement is that the modification of HDPE by accelerated electrons had a positive effect on the dynamic tensile behavior of these materials.

Biodiesel is a renewable fuel mainly produced by methylation of triglycerides of vegetable oils or animal fats. The production processes nowadays are particularly based on the utilization of inorganic alkali catalysts. However, it has been proved that an organic alkali – tetramethylammonium hydroxide (TMAH) – can also be used as a very efficient transesterification catalyst. The work presented herein is focused on mathematical modeling of the kinetics of TMAH-catalyzed transesterification of triglycerides at different reaction conditions, specifically at varying reaction temperature with the aim to understand the reaction mechanism and identify the key variables for optimization of the production process. The main kinetic parameters were calculated based on the mathematical- statistical processing of experimental kinetic data. The reaction rate constants for individual consecutive and reversible reactions and the corresponding activation energies were calculated.

As the demand for biodiesel continues to rise, there is a pressing need for efficient and continuous monitoring of the transesterification reaction at the industrial level. However, there is a lack of straightforward online monitoring methods capable of accurately following the course of ethanolysis under various reaction conditions. In this work, simple linear regression (SLR) and multiple linear regression (MLR) models were developed to assess Fourier transform infrared spectroscopy (FTIR) data from a continuous flow cell, enabling real-time ethanolysis monitoring without sample pretreatment. Gas chromatography (GC) was utilised as the reference method to accurately characterise the reaction mixture’s composition during ethanolysis. Extensive correlation analysis was performed to identify spectra regions where the reaction system’s state changes are observable. The gained regions were subsequently applied in the linear regression model’s development. This novel approach resulted in the performance of simple linear regression comparable to complex partial least squares (PLS) regression model (RMSEP = 2.11). The developed online monitoring system was validated in a wide range of reaction conditions (40–60 °C; 0.25–1.0% w/w NaOH); it effectively identifies dynamic changes in the ethanolysis process and confirms achieving the threshold value of ester content set by EU regulation directly in the production process.

Biostimulants are increasingly used in agriculture to promote plant growth, improve stress tolerance, and support sustainable farming practices. One common method of production is chemical hydrolysis of protein‐rich waste, such as tannery by‐products, offering an economical and eco‐friendly alternative to conventional raw materials. This approach aligns with the principles of the circular economy by transforming industrial waste into valuable agricultural inputs. This study investigates the first stage of biostimulant production, alkaline hydrolysis at elevated temperatures, by analyzing the interplay between reaction kinetics, conversion efficiency, and operational costs. Through experimental data and kinetic modelling using a first‐order reaction and the Arrhenius equation, key parameters such as activation energy and frequency factor were established. A techno‐economic evaluation was conducted to determine optimal operating conditions, emphasizing the importance of the cost ratio between the reactor and evaporator. The results show that higher conversion rates and shorter reaction times are achievable with optimized temperature and cost parameters. Pilot‐scale validation (100 L) confirmed process scalability, and preliminary field trials on maize demonstrated effects comparable to those of commercial products. These insights contribute to the advancement of scalable and cost‐effective hydrolysis methods for producing biostimulants from waste protein sources.