This study explores the integration of nanomaterials and machine learning (ML) in enhancing atomization and combustion behavior of nanofuels. Nanoparticles such as TiO2, Al2O3, and graphene derivatives improve fuel atomization, thermal conductivity, and emission reduction. A systematic review (2021–2025) and meta-analysis reveal short-term gains in brake thermal efficiency (+12.5%) and emission reduction (CO −12%, HC −25%, NOx −19%), though long-term stability remains limited by agglomeration and injector fouling. ML-models, including Bayesian-Ridge and Random-Forest, predict efficiency metrics effectively but underperform for emissions. The findings highlight the need for atomization descriptors and hybrid ML–CFD models for robust predictive combustion design.
This study investigates pure and Ag-doped SrMoO4 powders (Sr1−xAgxMoO4, x = 0, 0.01, 0.07), focusing on structural, optical, and functional properties. We evaluate its photocatalytic performance, capacitance response in lactate solution and water, and antimicrobial activity in textiles. The diffraction patterns could be indexed to the pure tetragonal phase SrMoO4. The doping of SrMoO4 with Ag+ ions affects the morphology and particle size of the samples designed by co-precipitation. SrMoO4 pure and Ag+-doped samples exhibited promising results in detecting water and lactate solutions, as well as photocatalysis. Pure SrMoO4 was more efficient in the photodegradation of methylene blue (MB) than the sample doped with Ag+. Among the bactericidal test results, sample SMO:0.01-P4, without light, in S. aureus, and SMO:0.07-P3, with light in E. coli, showed a slight distance from the inhibition halo. These results suggest that the treated textile may possess a characteristic bactericidal capacity that deserves further exploration. This comprehensive analysis offers insights into the structure–function relationship of SrMoO4:Ag and advances the development of multifunctional materials.
With Zr-doped ceria (Ce0.6Zr0.4O2, CZ40) discovered as a promising redox material, metal oxide (MO)-based thermochemical cycles offer a feasible technique for CO2 splitting (CDS) at lower temperatures. There are currently few thorough thermodynamic efficiency evaluations available, despite experimental validation of its redox efficacy. The two-step CZ40-driven CDS cycle is modeled in this study, and experimental data are used to perform the efficiency analysis. Solar-to-fuel efficiency increases from 0.74% to 1.00% as a result of reducing solar heat demand from 434.05 kW to 322.17 kW by boosting gas-to-gas heat recuperation from 0.0 to 0.3.
