fig2

Figure 2. (A) The model architecture of TinNet. The information transits from the graph representation of an adsorption system to the theory module to calculate adsorption energy ΔE, where ρ_a¹…ρ_aⁱ indicates the projected DOS onto the adsorbate frontier orbital(s) and μ₁…μ_j indicates d-band moments; (B-D) DFT-calculated vs. TinNet-predicted. (B) ^*OH adsorption energies of {111}W-TM surfaces, (C) ^*O adsorption energies at the atop the site of {111}-terminated alloy surfaces, (D) ^*N adsorption energies at the hollow site of (100)-terminated alloy surfaces; (E) The model architecture of ACE-GCN; (F and G) Predictions of conformational stability of unrelaxed. (F) NO^* and (G) OH^* using the ACE-GCN model generated by SurfGraph. Reproduced with permission from refs^[74,75], licensed under Creative Commons CC BY. DOS: Density of states; DFT: density-functional theory; TM: transition metal; ACE-GCN: adsorbate chemical environment-based graph convolution neural network.