An official website of the United States government
Abstract Alchemical perturbation density functional theory (APDFT) has promise for enabling computational screening of hypothetical catalyst sites. Here, we analyze errors in first order APDFT calculation schemes for binding energies of CHx, NHx, OHx, and OOH adsorbates over a range of different coverages on hypothetical alloys based on a Pt(111) reference system. We then train three different support vector regression machine learning models that correct systematic APDFT prediction errors for each of the three classes of carbon, nitrogen, and oxygen based adsorbates. While uncorrected first order APDFT alone approximates accurate adsorbate binding energies on up to 36 hypothetical alloys based on a single Kohn–Sham DFT calculation on a 3 × 3 unit cell for Pt(111), the machine learning‐corrected APDFT extends this number to more than 20,000 and provides a recipe for developing other machine learning‐based APDFT models.
more »
« less
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.
more »
« less
- 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
More Like this
-
-
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 Abstractmore » « less
-
Abstract Based on the coincident onsets of oxygen evolution reaction (OER) and metal dissolution for many metal‐oxide catalysts it was suggested that OER triggers dissolution. It is believed that both processes share common intermediates, yet exact mechanistic details remain largely unknown. For example, there is still no clear understanding as to why rutile IrO2exhibits such an exquisite stability among water‐splitting electrocatalysts. Here, we employ density functional theory calculations to analyze interactions between water and the (110) surface of rutile RuO2and IrO2as a response to oxygen evolution involving lattice oxygen species. We observe that these oxides display qualitatively different interfacial behavior that should have important implications for their electrochemical stability. Specifically, it is found that IrO2(110) becomes further stabilized under OER conditions due to the tendency to form highly stable low oxidation state Ir(III) species. In contrast, Ru species at RuO2(110) are prone to facile reoxidation by solution water. This should facilitate the formation of high Ru oxidation state intermediates (>IV) accelerating surface restructuring and metal dissolution.more » « less
-
Abstract High‐entropy alloys combine multiple principal elements at a near equal fraction to form vast compositional spaces to achieve outstanding functionalities that are absent in alloys with one or two principal elements. Here, the prediction, synthesis, and multiscale characterization of 2D high‐entropy transition metal dichalcogenide (TMDC) alloys with four/five transition metals is reported. Of these, the electrochemical performance of a five‐component alloy with the highest configurational entropy, (MoWVNbTa)S2, is investigated for CO2conversion to CO, revealing an excellent current density of 0.51 A cm−2and a turnover frequency of 58.3 s−1at ≈ −0.8 V versus reversible hydrogen electrode. First‐principles calculations show that the superior CO2electroreduction is due to a multi‐site catalysis wherein the atomic‐scale disorder optimizes the rate‐limiting step of CO desorption by facilitating isolated transition metal edge sites with weak CO binding. 2D high‐entropy TMDC alloys provide a materials platform to design superior catalysts for many electrochemical systems.more » « less
-
Stability is an important aspect of alloys, and proposed alloys may be unstable due to unfavorable atomic interactions. Segregation of an alloy may occur preferentially at specific exposed surfaces, which could affect the alloy's structure since certain surfaces may become enriched in certain elements. Using density functional theory (DFT), we modeled surface segregation in bimetallic alloys involving all transition metals doped in Pt, Pd, Ir, and Rh. We not only modeled common (111) surfaces of such alloys, but we also modeled (100), (110), and (210) facets of such alloys. Segregation is more preferred for early and late transition metals, with middle transition metals being most stable within the parent metal. We find these general trends in segregation energies for the parent metals: Pt > Rh > Pd > Ir. A comparison of different surfaces suggests no consistent trends across the different parent hosts, but segregation energies can vary up to 2 eV depending on the exposed surface. We also developed a statistical model to predict surface-dependent segregation energies. Our model is able to distinguish segregation at different surfaces (as opposed to generic segregation common in previous models), and agrees well with the DFT data. The present study provides valuable information about surface-dependent segregation and helps explain why certain alloy structures occur ( e.g. core–shell).more » « less
