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1903. Dataset used for the paper »Surface modification of magnesium for biomedical applications: comparative analysis of plasma treatment, laser texturing and sandblasting«Marjetka Conradi, zaključena znanstvena zbirka raziskovalnih podatkov Povzetek: Magnesium and its alloys have emerged as promising materials for biomedical applications due to their light weight, mechanical compatibility with bone, biodegradability, and excellent biocompatibility. However, their rapid degradation in physiological environments remains a critical challenge. To address this, a range of surface-modification techniques have been explored to tailor the surface properties while preserving the bulk characteristics of magnesium. This paper provides an overview of surface-engineering methods aimed at enhancing the corrosion resistance, mechanical performance and bioactivity of magnesium. Three key surface-modification approaches are presented: plasma treatment, laser texturing and sandblasting. Plasma treatment resulted in the formation of a stable, protective oxide layer with significantly improved corrosion resistance and hydrophilicity. Laser texturing generated hierarchical microstructures yielding superhydrophobic surfaces with an enhanced hardness, though slightly reduced corrosion resistance. Sandblasting led to an increased surface roughness and mechanical stiffness, but also introduced microstructural defects that are detrimental to the corrosion stability. Overall, the study demonstrates how tailored surface modifications can effectively balance the mechanical integrity and degradation behavior of magnesium, paving the way for its optimized use in biomedical applications.
Ključne besede: magnesium, surface modification, biomaterial
Objavljeno v DiRROS: 18.06.2025; Ogledov: 554; Prenosov: 260
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1907. Pythagorean linguistic information-based green supplier selection using quantum-based group decision-making methodology and the MULTIMOORA approachPrasenjit Mandal, Leo Mršić, Antonios Kalampakas, Tofigh Allahviranloo, Sovan Samanta, 2025, izvirni znanstveni članek Povzetek: The selection of environmentally sustainable suppliers has been a significant challenge in management decision-making (DM). Multicriteria group decision-making (MCGDM) is a ranking methodology used to select suppliers, but it is complex and influenced by the different opinions of decision-makers. Once again, extensive research on MCGDM has exposed inadequacies in the trustworthiness of experts’ judgements, which profoundly impact the ultimate ranking results. The Pythagorean linguistic number (PLN) concept has been used to address MCGDM by considering experts’ confidence levels and real-world scenarios. This study introduces an extensive technique using a quantum scenario-based Bayesian network (QSBN) and Deng entropy-based belief entropy to account for the interference of beliefs. The goal is to replicate the subjectivity of experts’ opinions during different stages of DM, including the accumulation of experts’ weights and alternative probabilities. The correlation coefficient of PLNs is introduced for determining criterion weights and employing new techniques based on entropy methods for experts’ weights. The MULTIMOORA approach consolidates the probability of alternatives in QSBN among all experts, and the interference value is computed using belief entropy, an index for quantifying the probability of uncertainty. The study provides a numerical example to illustrate the proposed methodology, pecifically focusing on selecting environmentally sustainable suppliers, and demonstrates its applicability and effectiveness
Ključne besede: Pythagorean linguistic set, MULTIMOORA, Quantum probability theory, MCGDM
Objavljeno v DiRROS: 18.06.2025; Ogledov: 414; Prenosov: 216
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