Efficient mixing in stirred tanks is essential for chemical and biochemical processes. Tubular baffles offer potential energy savings and multifunctionality (e.g., as heat exchangers); however, their interaction with common impeller types is not well understood. This study uses computational fluid dynamics (CFD) simulations to evaluate the hydrodynamic performance of a novel tubular baffle design compared to conventional flat baffles with three impellers: a Rushton turbine (RT), a pitched blade turbine (PBT), and a hydrofoil (HE3). Dimensionless analysis (power number, N_P; and pumping number, N_Q), flow visualization, and vorticity dynamics were employed. The results show that, by attenuating large-scale recirculation, tubular baffles reduce power consumption by 64%, 13%, and 23% for the HE3, PBT, and RT, respectively. However, the HE3 impeller experienced a 30% decrease in pumping capacity, which confined the flow to the lower tank. The PBT showed a 10% increase in N_Q and intensified bottom circulation. The RT uniquely generated distributed, high-intensity turbulence along the baffle height while maintaining its characteristic dual-loop structure. The analysis critiques the local pumping efficiency metric and advocates for a global flow assessment. The HE3 is optimal for efficient bulk blending at low power; the PBT is optimal for strong bottom circulation processes; and the RT is optimal for applications requiring enhanced interfacial processes, where baffles serve a dual function. This work provides a framework for selecting energy-efficient agitation systems by coupling impeller performance with global tank hydrodynamics.

The intensive use of generative AI tools in higher education raises questions about their impact on students' cognitive autonomy. This study compares students' interaction with these tools and examines factors potentially associated with differences in cognitive autonomy between students in the early semesters (2nd to 4th) and final semesters (8th to 10th) of STEM programs. Using a cross-sectional comparative mixed-methods design, cognitive autonomy is assessed with the self-regulation subscale of the Motivated Learning Strategies Questionnaire (MSLQ) and a prompt coding system measuring complexity, critical iteration, and cognitive delegation. Semi-structured interviews identified factors associated with the observed differences between groups. A sample of 188 STEM students participated (116 in early and 72 in final semesters). The results reveal distinct profiles of interaction with AI according to academic progress, with a delegative prompt profile predominating among early-semester students (75.9 %) compared to final-semester students (19.4 %), and a higher overall interaction-autonomy index among the latter (d = 3.92). These findings are consistent with an association, rather than a causal or developmental effect, given the cross-sectional design, between academic trajectory and a more critical, epistemically reflective use of this technology. The results indicate potential risks of technological dependence and a possible weakening of autonomous thinking among students with less disciplinary maturity.

The photocatalysts of TiO₂ doped with carbon, boron, nitrogen, and sulfur were synthesized and evaluated, with the aim of improving their efficiency in dye degradation under UV and visible light irradiation. The samples were structurally and optically characterized using X-ray diffraction (XRD), Raman spectroscopy, and UV-Vis spectroscopy. All materials retained the anatase phase, although doping affected their crystallinity and optical properties. C–TiO₂ and N–TiO₂ stood out due to their enhanced absorption in the visible region. The photocatalytic activity was evaluated using the dyes Acid Orange 7 and Reactive Black 5 under both UV and visible light irradiation. C–TiO₂ exhibited the highest efficiency under both conditions, especially under visible light, outperforming undoped TiO₂. N–TiO₂ also showed improved performance in the degradation of Reactive Black 5. These results confirm that doping with non-metallic elements, particularly carbon enhances the performance of TiO₂ under visible light irradiation, highlighting its potential for the treatment of dye-contaminated wastewater.