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The utilization of renewable materials has raised worldwide interest regarding biodegradable polymers, proving important scientific, ecological, and economic relevance. Biopolymers are versatile materials used in various applications due to their high strength, low weight, and minimal environmental impact. However, their characterization for understanding their properties requires extensive experimental measurement. In this context, conventional research is improved by the integration of artificial intelligence (A...

The paper presents the research and results obtained by authors concerning the reactor modeling of the catalytic cracking process using two methods: artificial neural network (ANN) and multiple linear regression (MLR). This study is structured in four parts. The first part presents the process description, and the existing models in the literature. The second part presents the multiple linear regression method, the reactor model obtained with this method, and the comparison between the output experimental data of ...

Biochar can be used as an alternative and efficient adsorbent for organic and inorganic pollutants. Therefore, based on previous study in which, a biochar loaded with mixed metal oxides of iron, tin or titanium catalysts results as a by-product of levulinic esters synthesis from biomass carbohydrates, this paper aim was to test this residue as biochar for the retention of phosphate from water samples. The obtained adsorbents based on Fe2O3-SnO2 and Fe2O3-La2O3-TiO2 were characterized by FT-IR and TGA analyses. The...

The presence of nitrate concentration in drinking water can cause high toxicity to the human body, being considered among the most important pollutant in the environment. Among the many methods available such as biological treatment, electrodialysis, reverse osmosis, adsorption, ion exchange, adsorption is the most used technique due to its low cost and simplistic design. Therefore, the aim of this paper was to study the retention of nitrate anion from high concentration aqueous solutions on a novel magnetic adsor...

Reservoir description is rapidly increasing with the help of advancing computing possibilities. Although machines become more efficient, it is necessary to have accurate input data and plenty of data points to achieve reliable results. However, in the case of both old Romanian hydrocarbon reservoirs and some of the new ones, not too many data points are available. In this situation, no matter the computing power of the machine or the computing algorithm, detailed reservoir description is limited. This paper extend...

Reservoir heterogeneity creates difficulties for every stage of production, the effects being more pronounced when little data is available. This is the case for many old and abandoned Romanian oil reservoirs that have very poor reservoir characterization. This paper discusses the efficiency of two prediction methods, ordinary kriging and artificial neural networks, for porosity as an routine core analysis parameter, with the hope of improving reservoir characterization by creating more accurate distribution maps....