Density Functional Theory and Machine Learning Description and Prediction of Oxygen Atom Chemisorption on Platinum Surfaces and Nanoparticles

Abstract

Elucidating chemical interactions between catalyst surfaces and adsorbates is crucial for understanding surface chemical reactivity. Herein, interactions between O atoms and Pt surfaces and nanoparticles are described as a linear combination of the properties of pristine surfaces and isolated nanoparticles. The energetics of O chemisorption onto Pt surfaces were described using only two descriptors related to surface geometrical features. The relatively high coefficient of determination and low mean absolute error between the density functional theory-calculated and predicted O binding energies indicate good accuracy of the model. For Pt nanoparticles, O binding is described by the geometrical features and electronic properties of isolated nanoparticles. Using a linear combination of five descriptors and accounting for nanoparticle size effects and adsorption site types, the O binding energy was estimated with a higher accuracy than with conventional single-descriptor models. Finally, these five descriptors were used in a general model that decomposes O binding energetics on Pt surfaces and nanoparticles. Good correlation was achieved between the calculated and predicted O binding energies, and model validation confirmed its accuracy. This is the first model that considers the nanoparticle size effect and all possible adsorption sites on Pt nanoparticles and surfaces.

Exploring Structure-Sensitive Relations for Small Species Adsorption Using Machine Learning

“…On-top binding gives excellent correlations but the other-site-type binding does not; mixed site types break these correlations. When all of the Pt surface adsorption sites are considered, the GCN model does not hold even for O* (see Figure S3), consistent with the findings of the Koyama group . The ability to account for the site type is essential for accurate scalings.…”

Magnesium-Induced Strain and Immobilized Radical Generation on the Boron Oxide Surface Enhances the Oxidation Rate of Boron Particles: A DFTB-MD Study

“…It is well known that the interstitial diffusional flux ( J ) of a particular species scales linearly with the product of the diffusivity ( D ) and the interstitial volume increment relative to the volume of the diffusing atom ( v 0 , J ≈ Dν 0 ), given that the gradient in strain remains constant . Neglecting the fact that D is also influenced by the lattice strain to avoid complication, a bond length extension from 1.3 to 2.0 Å resulting in an ∼20 Å 3 volume increment should increase the flux of O atoms (radius ∼152 pm) by 4×. Apart from the intrinsic reaction kinetics, the rate of oxidation of solid particles in gas-phase oxygen depends on (i) the rate of adsorption of gas-phase oxygen to the particle surface and (ii) the rate of diffusion of the adsorbed oxygen through the oxide shell to the particle interior .…”

Combustion‐Assisted Polyol Reduction Method to Prepare Highly Transparent and Efficient Pt Counter Electrodes for Bifacial Dye‐Sensitized Solar Cells

“…We may speculate that the following steps occur in the polyol reduction: (i) the rapid conversion of the Pt complexes to the oxides or hydroxides, and the chemical reduction to metallic Pt. [40] Unfortunately, although Pt(IV) state disappeared, Pt(II) state still existed because low-coordinated sites on tiny Pt nanoparticles can strongly bind with oxygen-containing species, such as O, OH and CO. [41,42] Importantly, the addition of Hacac engendered more metallic Pt during the polyol reduction reaction. The ratio of 1 : 16 produced the largest portion of metallic Pt, which has highly electrocatalytic Pt (100) and ( 111) facets.…”