Double-Atom Catalysts Featuring Inverse Sandwich Structure for CO₂ Reduction Reaction: A Synergetic First-Principles and Machine Learning Investigation

Abstract

Electrocatalytic CO2 reduction reactions (CO2RR) based on scalable and highly efficient catalysis provide an attractive strategy for reducing CO2 emissions. In this work, we combined first-principles density functional theory (DFT) and machine learning (ML) to comprehensively explore the potential of double-atom catalysts (DACs) featuring an inverse sandwich structure anchored on defective graphene (gra) to catalyze CO2RR to generate C1 products. We started with five homonuclear M2⊥gra (M = Co, Ni, Rh, Ir, and Pt), followed by 127 heteronuclear MM′⊥gra (M = Co, Ni, Rh, Ir, and Pt, M′ = Sc–Au). Stable DACs were screened by evaluating their binding energy, formation energy, and dissolution potential of metal atoms, as well as conducting first-principles molecular dynamics simulations with and without solvent water molecules. Based on DFT calculations, Rh2⊥gra DAC was found to outperform the other four homonuclear DACs and the Rh-based single- and double-atom catalysts of noninverse sandwich structures. Out of the 127 heteronuclear DACs, 14 were found to be stable and have good catalytic performance. An ML approach was adopted to correlate key factors with the activity and stability of the DACs, including the sum of radii of metal and ligand atoms (d M–M′, d M–C, and d M′–C), the sum and difference of electronegativity of two metal atoms (P M + P M′, P M – P M′), the sum and difference of first ionization energy of two metal atoms (I M + I M′, I M – I M′), the sum and difference of electron affinity of two metal atoms (A M + A M′, A M – A M′), and the number of d-electrons of the two metal atoms (N d). The obtained ML models were further used to predict 154 potential electrocatalysts out of 784 possible DACs featuring the same inverse sandwich configuration. Overall, this work not only identified promising CO2RR DACs featuring the reported inverse sandwich structure but also provided insights into key atomic characteristics associated with high CO2RR activity.

High-Throughput Screening of Effective Dual Atom Catalysts for the Nitric Oxide Reduction Reaction

“…Interestingly, 2D expanded phthalocyanine (Pc) Cr 2 -Pc reaches an extremely low energy input of 0.02 V for the production of ammonia, which means that the homonuclear metal catalysts may also show excellent catalytic activities . In addition, an inverse sandwich homonuclear or heteronuclear metal structure anchored on defective graphene was also designed for the carbon dioxide reduction reaction . With regard to the development of DACs, the combination of computational predictions and experimental verifications has also attracted widespread interest due to its high efficiency .…”

“…27 In addition, an inverse sandwich homonuclear or heteronuclear metal structure anchored on defective graphene was also designed for the carbon dioxide reduction reaction. 28 With regard to the development of DACs, the combination of computational predictions and experimental verifications has also attracted widespread interest due to its high efficiency. 29 At present, the experimental preparation of DACs can be successfully achieved.…”

Three-Dimensional Dual-Site Catalysts for Industrial Ammonia Synthesis at Dramatically Decreased Temperatures and Pressures

“…In addition, it is reasonable to expect that DPD motifs with the formation energies ( E f ) < 0 eV are experimentally accessible. As summarized in Figure S1c and Table S2, the Δ E b and E f of all DPD configurations are comparable to or even more negative than those of single-atom catalysts ,,− and dual-atom catalysts, ,− where some widely discussed single-atom alloys have been implemented to various reactions operating at temperatures above 500 °C. − In this regard, the negative Δ E b and extremely high diffusion barriers of isolated metal atoms could preserve the original single atom sites and prevent metal aggregation on these DPD motifs.…”

Identifying hexagonal 2D planar electrocatalysts with strong OCHO* binding for selective CO2 reduction

“…Fortunately, theoretical calculations have emerged as a powerful tool for the cost-effective and swift prediction of catalyst performance, which can steer experimental endeavors toward the acquisition of superior catalysts. 7–10 Nevertheless, a key oversight in catalyst design has been the disregard of the surface states ( i.e ., the electrochemistry-induced surface coverage) under reaction conditions, 11 which sometimes can lead to a significant deviation between theoretical and experimental observations. 12 To circumvent this bottleneck, the surface Pourbaix diagram, as a function of operating potential and pH, can be a valuable tool to describe the occupation state of the catalyst surface under realistic working conditions.…”