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Enhanced singlet oxygen production under nanoconfinement using silica nanocomposites towards improving the photooxygenation’s conversion

Tamtaji, M ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1007/s11051-022-05553-w
  3. Publisher: Springer Science and Business Media B.V , 2022
  4. Abstract:
  5. In this contribution, the effect of physical immobilization of methylene blue (MB) into silica nanocomposites was investigated on the conversion and selectivity of the photooxygenation of anthracene and dihydroartemisinic acid (DHAA). Physically immobilized photocatalysts were synthesized through a developed Stöber method and were thoroughly characterized by UV–Vis, FTIR, XRD, XPS, SEM, TEM, HR-TEM, BET-BJH, and EDX analyses. Based on the TEM and UV–Vis results, it was determined that enhancement of the MB concentration as an organocatalyst for the Stöber reaction led to an increase in the size of the nanoparticles from 54 to 183 nm and a 21 nm blue shift in their UV–Vis spectra. Moreover, utilizing an immobilized MB as a photocatalyst for photooxygenation reactions under visible light led to a remarkable enhancement of 9% (i.e., from 89 to 98%) in the reaction conversion of anthracene photooxygenation compared to those using the same amount of homogenous MB. Nonetheless, a 5% reduction (i.e., 83 to 78%) in the selectivity of photooxygenation of DHAA was observed. These behaviors were rationalized through the nanoconfinement effects of pores with a narrow size distribution of 3.1 nm obtained through the HR-TEM and BET-BJH analyses, which led to a controlled aggregation of the MB molecules. Deep neural networks (DNNs) were applied to accurately predict the UV–Vis spectra and aggregation of the MB molecules. The results from time-dependent density functional theory (TD-DFT) calculations suggested that aggregation of the MB led to decreasing in intersystem crossing energy gap; hence, an increase in the 1O2 generation became possible. Finally, the finite element method (FEM) simulation revealed a 300 nm penetration depth of 1O2 around synthesized photocatalysts. Graphical abstract: [Figure not available: see fulltext.] © 2022, The Author(s), under exclusive licence to Springer Nature B.V
  6. Keywords:
  7. Machine learning ; Methylene blue ; Anthracene ; Deep neural networks ; Density functional theory ; Fourier transform infrared spectroscopy ; Iridium compounds ; Molecules ; Nanocomposites ; Oxygen ; Silica ; DFT ; Dihydroartemisinic acid ; Machine-learning ; Organocatalysts ; Photooxygenations ; Silica nanocomposites ; Singlet oxygen production ; Synthesised ; UV-Vis spectrum ; Organocatalyst ; Artemisinic acid ; Methylene blue ; Nanocomposite ; Silicon dioxide ; Singlet oxygen ; Binding affinity ; Chemical reaction ; Chemical reaction kinetics ; Deep neural network ; Energy ; Energy dispersive X ray spectroscopy ; Finite element analysis ; Immobilization ; Mathematical phenomena ; Photocatalysis ; Photooxidation ; Proton nuclear magnetic resonance ; Scanning electron microscopy ; Transmission electron microscopy ; Ultraviolet visible spectroscopy ; X ray diffraction ; X ray photoemission spectroscopy
  8. Source: Journal of Nanoparticle Research ; Volume 24, Issue 9 , 2022 ; 13880764 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s11051-022-05553-w