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(a∼b): Morphologies of large-area uniform sapphire-based Ag/Au hybrid coupled nanoarrays (SA-Ag/Au HCNAs) with low (a) and high (b) magnifications. c: The plasmonic photocatalysis for PNTP based on SA-Ag/Au HCNAs substrate. d: Raman mapping characterization results at the 1162 cm-1 position of CV molecule with a scanning accuracy of 0.02 mm over 1 mm * 1 mm. [Display omitted] • Sapphire-based Ag/Au hybrid coupled nanoarrays with high SERS activity and plasmonic photocatalytic properties were obtained. • "Droplet funnel" method was employed for large-area uniform assembly of Au nanoparticles. • The prepared substrates showed excellent photocatalytic properties for PNTP molecules. • The synergistic electromagnetic enhancement effect of Ag-Au hybrid coupling is 26.661 times higher than that of pure AuNP. The regulation of surface plasmon properties of noble metal nanostructure has been a hot topic in the field of nanomaterials preparation and its applications. Surface-enhanced Raman Scattering (SERS), as a sensitive surface-interface trace molecule detection tool, strongly depends on the localized surface plasmonic characteristics. However, how to prepare highly sensitive and reproducible SERS substrates is still under difficult. Herein, Ag/Au hybrid coupled films were attached to the sapphire array by chemical method and interface assembly. Sapphire-based Ag/Au hybrid coupled nanoarrays (SA-Ag/Au HCNAs) with high SERS activity and plasmonic photocatalytic properties were obtained. By monitoring the catalytic reaction of PNTP on the substrate, we found that the prepared SA-Ag/Au HCNAs had significant plasmonic photocatalytic properties. The results show that the synergistic enhancement effect of Ag/Au hybrid coupling is 26.661 times higher than that of pure Au and 9.522 times higher than that of pure Ag. Furthermore, crystal violet (CV), Rhodamine 6G (R6G) and malachite green (MG) were selected as probe molecules, exhibiting good SERS stability and sensitivity of SA-Ag/Au HCNAs substrates. This work provides a simple, low-cost and scalable method for the preparation of hybrid coupled nanoarrays, showing good prospect in photocatalytic dye degradation, environmental monitoring and biomedical analysis. [ABSTRACT FROM AUTHOR]

[Display omitted] • Double transition metal atoms on GDY break the scaling relationship. • Machine learning speeds up the screening catalysts and reveals the descriptors. • Relations of intermediate adsorption energies aid catalyst selection in deep CO 2 RR. • GDY-based catalysts with strong CO binding exhibit high selectivity towards CH 4. Electrochemical CO 2 reduction reaction (CO 2 RR) has become a promising application in addressing energy challenges and environmental crises. However, the scaling relationship between the reaction intermediates constrains the successful deep reduction of CO 2. Dual-metal-site catalysts (DMSCs) have emerged as potential electrocatalysts for CO 2 RR by breaking the scaling relationship due to their more adaptable active sites. Herein, this study aims to investigate the correlation between the adsorption energies of essential intermediates in CO 2 RR catalysis with double transition metal atoms anchored on graphdiyne monolayer (TM 1 -TM 2 @GDY) through machine-learning (ML) assisted density functional theory (DFT) calculations. The results reveal the important descriptors of CO 2 RR catalyzed by TM 1 -TM 2 @GDY, and demonstrate that the heteronuclear TM 1 -TM 2 @GDY have great potential for deep CO 2 reduction. Especially, Co-Mo@GDY and Co-W@GDY show low limiting potential (-0.60 V and −0.39 V, respectively) and high selectivity on the reaction from CO 2 to CH 4 based on the free energy diagrams. This study indicates that the two TM atoms on GDY act cooperatively for the catalysis of CO 2 RR. Notably, utilizing ML eliminates the need to calculate all transition metal combinations by DFT, which is a great boost in quickly investigating catalytic performance and high screening for excellent catalysts. [ABSTRACT FROM AUTHOR]