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Abstract Titanium dioxide (TiO2) has been used in numerous paintings since its creation in the early 1920s. However, due to this relatively recent adoption by the art world, we have limited knowledge about the nature and risk of degradation in museum environments. This study expands on the existing understanding of TiO2facilitated degradation of linseed oil, by examining the effect of visible light and crystallographic phase (either anatase or rutile) on the reactivity of TiO2. The present approach is based on a combination of experimental chemical characterization with computational calculation through Density Functional Theory (DFT) modeling of the TiO2-oil system. Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR-FT-IR) enabled the identification of characteristic degradation products during UV and visible light aging of both rutile and anatase based paints in comparison to BaSO4and linseed oil controls. In addition, cratering and cracking of the paint surface in TiO2based paints, aged under visible and UV–vis illumination, were observed through Scanning Electron Microscopy (SEM). Finally, Density Functional Theory (DFT) modeling of interactions between anatase TiO2and oleic acid, a fatty acid component of linseed oil, to form a charge transfer complex explains one possible mechanism for the visible light activity observed in artificial aging. Visible light excitation of this complex sensitizes TiO2by injecting an electron into the conduction band of TiO2to generate reactive oxygen species and subsequent degradation of the oil binder by various mechanisms (e.g., formation of an oleic acid cation radical and other oxidation products). Graphical Abstract
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Benchmarking Computational Alchemy for Carbide, Nitride, and Oxide Catalysts
Abstract Kohn–Sham density functional theory (DFT)‐based searches for hypothetical catalysts are too computationally demanding for wide searches through diverse materials space. Here, the accuracy of computational alchemy schemes on carbides, nitrides, and oxides is assessed. With a single set of reference DFT calculations, computational alchemy approximates adsorbate binding energies (BEs) on a large number of hypothetical catalysts surfaces with negligible computational cost. Analogous to previous studies on metal alloys, computational alchemy predicts adsorbate BEs on rocksalt TiC(111), TiN(100), and TiO(100) materials, which have no bandgap, in close agreement with DFT results (with mean unsigned errors up to 0.33 eV). In contrast, it is found that semiconducting systems such as rutile TiO2(110), rutile SnO2(110), and rocksalt ZnO(100) can present more significant challenges. This work identifies these challenges being linked to the density of states at the Fermi level and by adding Pt dopants in the surface layer of TiO2, it is shown that computational alchemy can become more reliable with non‐transition metal systems. This remedy provides insight that promotes computational alchemy for broad searches for catalyst active sites through materials space beyond transition metal alloys.
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- Award ID(s):
- 1653392
- PAR ID:
- 10079211
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Theory and Simulations
- Volume:
- 2
- Issue:
- 4
- ISSN:
- 2513-0390
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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