Abstract: The use of renewable energy (RE) to transform carbon dioxide into commodities (i.e., CO2 valorization) will pave the way towards a more sustainable economy in the coming years. But how can we efficiently use this energy (mostly available as electricity or solar light) to drive the necessary (catalytic) transformations? This paper presents a review of the technological advances in the transformation of carbon dioxide by means of RE. The socioeconomic implications and chemical basis of the transformation of carbon dioxide with RE are discussed. Then a general view of the use of RE to activate the (catalytic) transformations of carbon dioxide with microwaves, plasmas, and light is presented. The fundamental phenomena involved are introduced from a catalytic and reaction device perspective to present the advantages of this energy form as well as the inherent limitations of the present state-of-the-art. It is shown that efficient use of RE requires the redesign of current catalytic concepts. In this context, a new kind of reaction system, an energy-harvesting device, is proposed as a new conceptual approach for this endeavor. Finally, the challenges that lie ahead for the efficient and economical use of RE for carbon dioxide conversion are exposed.

Abstract: This study investigates the dry reformation of methane (DRM) over Ni/Al2O3 catalysts in a dielectric barrier discharge (DBD) non-thermal plasma reactor. A novel hybrid machine learning (ML) model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data. To address the non-linear and complex nature of the plasma-catalytic DRM process, the hybrid ML model integrates three well-established algorithms: regression trees, support vector regression, and artificial neural networks. A genetic algorithm (GA) is then used to optimize the hyperparameters of each algorithm within the hybrid ML model. The ML model achieved excellent agreement with the experimental data, demonstrating its efficacy in accurately predicting and optimizing the DRM process. The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance. We found that the optimal discharge power (20 W), CO2/CH4 molar ratio (1.5), and Ni loading (7.8 wt%) resulted in the maximum energy yield at a total flow rate of
51 mL/min. Furthermore, we investigated the relative significance of each operating parameter on the performance of the plasmacatalytic DRM process. The results show that the total flow rate had the greatest influence on the conversion, with a significance exceeding 35% for each output, while the Ni loading had the least impact on the overall reaction performance. This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets, enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.

Abstract: Two-dimensional (2D) materials are promising candidates for atomic-scale piezotronics and piezophototronics. Quantum edge states show fascinating fundamental physics such as nontrivial topological behavior and hold promising practical applications for low-power electronic devices. Here, using the tight-binding approach and quantum transport simulations, we investigate the piezotronic effect on the spin polarization of edge states in a zigzag-terminated monolayer MoS2 nanoribbon. We find that the strain-induced piezoelectric potential induces a phase transition of edge states from metal to semiconductor. However, in the presence of exchange field, edge states become semi-metallic with significant spin splitting and polarization that can be tuned by external strain. We show that quantum transport conductance exhibits a 100% spin polarization over a wide range of strain magnitudes. This effect is used in a propose prototype of piezotronic spin transistor. Our results provide a fundamental understanding of the piezotronic effect on edge states in zigzag monolayer MoS2 nanoribbons and are relevant for designing high-performance piezotronic spin devices.