Direct Deoxygenation of Phenol over Fe-based Bimetallic Surfaces using On-the-fly Surrogate Models

TL;DR

This work develops and validates a GPR-NEB framework that couples on-the-fly Gaussian process surrogates with DFT to accelerate minimum energy pathway calculations for complex surface reactions. The method is first benchmarked on phenol deoxygenation (DDO) on pristine Fe(110), achieving close agreement with DFT barriers while delivering up to ~3× speedup, thanks to uncertainty-guided model updates. The approach is then applied to Fe(110) modified by Co or Ni in top- or subsurface layers, revealing that subsurface substitutions retain DDO energetics similar to Fe(110) and can even enhance C–H formation, whereas top-layer substitutions raise C–O cleavage barriers and favor reverse reactions, reducing DDO viability. The results provide mechanistic insight and design guidelines for earth-abundant, bimetallic catalysts in selective hydrodeoxygenation, and demonstrate the practical utility of GPR-based surrogate models for efficient exploration of large, flexible molecular reactions on surfaces.

Abstract

We present an accelerated nudged elastic band (NEB) study of phenol direct deoxygenation (DDO) on Fe-based bimetallic surfaces using a recently developed Gaussian process regression (GPR) calculator. Our test calculations demonstrate that the GPR calculator achieves up to 3x speedup compared to conventional density functional theory (DFT) calculations while maintaining high accuracy, with energy barrier errors below 0.015 eV. Using GPR-NEB, we systematically examine the DDO mechanism on pristine Fe(110) and surfaces modified with Co and Ni in both top and subsurface layers. Our results show that subsurface Co and Ni substitutions preserve favorable thermodynamics and kinetics for both C-O bond cleavage and C-H bond formation, comparable to those on the pristine Fe(110) surface. In contrast, top-layer substitutions generally increase the C-O bond cleavage barrier, render the step endothermic, and result in significantly higher reverse reaction rates, making DDO unfavorable on these surfaces. This work demonstrates both the effectiveness of GRR-accelerated transition state searches for complex surface reactions and provides insights into rational design of bimetallic catalysts for selective deoxygenation.

Figures (6)

• Figure 1: The simulated MEP of deoxygenation of phenol on the Fe(110) surface from both the GPR and pure VASP calculators. The representative structures along the transition path are also shown in the inset. Brown, white and red spheres represent Fe, O and C atoms, respectively.
• Figure 2: The usage of GPR and base calls during the MEP optimization associated with the GPR-NEB simulation mentioned in Fig. \ref{['fig1']}. In this simulation, each NEB iteration includes 7 consecutive images.
• Figure 3: The simulated MEP of deoxygenation of phenol on the Fe(110) surface from both the GPR and pure VASP calculators. The representative structures along the transition path are also shown in the inset. Brown, white and red spheres represent Fe, O and C atoms, respectively.
• Figure 4: The simulated MEPs of the deoxygenation and hydrogenation steps on the pure Fe(110) surfaces. The initial, transition state (TS) and final structures the elementary steps are shown below the MEPs. Brown, white and red spheres represent Fe, O and C atoms, respectively.
• Figure 5: The simulated MEPS of the deoxygenation and hydrogenation steps on Co and Ni top-layer substitution surfaces. (b) The initial, transition state (TS) and final structures for the C-O bond cleavage (top row) and C-H formation (bottom row) steps on the Ni top-surface. (c) The initial, transition state (TS) and final structures for the same steps for the Co top-surface. Brown, green, gray, white and red spheres represent Fe, Ni, Co, O and C atoms, respectively.