Self‐Validated Machine Learning Study of Graphdiyne‐Based Dual Atomic Catalyst

Abstract

Although the atomic catalyst has attracted intensive attention in the past few years, the current progress of this field is still limited to a single atomic catalyst (SAC). With very few successful cases of dual atomic catalysts (DACs), the most challenging part of experimental synthesis still lies in two main directions: the thermodynamic stability of the synthesis and the optimal combination of metals. To address such challenges, comprehensive theoretical investigations on graphdiyne (GDY)‐based DAC are proposed by considering both, the formation stability and the d‐band center modifications. Unexpectedly, it is proven that the introduction of selected lanthanide metals to the transition metals contributes to the optimized stability and electroactivity. With further verification by machine learning, the potential f–d orbital coupling is unraveled as the pivotal factor in modulating the d‐band center with enhanced stability by less orbital repulsive forces. These findings supply the delicate explanations of the atomic interactions and screen out the most promising DAC to surpass the limitations of conventional trial and error synthesis. This work has supplied an insightful understanding of DAC, which opens up a brand new direction to advance the research in atomic catalysts for broad applications.

Stepping Out of Transition Metals: Activating the Dual Atomic Catalyst through Main Group Elements

“…Depending on our previous work, we continued to develop the use of Gaussian Process regression (GPR) due to its relatively low computation cost on smaller data sets [ 44 ] and previous success at giving promising results on our target dataset. [ 30 ] Our previous work has confirmed that machine learning is an effective tool to predict the thermodynamic stability and electronic structures of GDY‐based electronic structures. To evaluate the influences of introducing p orbitals, we have also introduced the GPR algorithm method to predict both the energetic trend and electronic structures of GDY‐DAC in this work.…”

“…Meanwhile, there were three possible anchoring sites in each unit of GDY based on the previous works. [ 16–18,30 ] The two different elements were placed between the C2 and C3 sites of the alkyl chain in GDY, which were proved to be the most stable position. To guarantee full relaxations, 15 Å vacuum space was introduced in the z ‐direction.…”

“…Recently, dual atomic catalysts (DAC) have been reported, where the introduction of the second metal atom enables the simultaneous adsorptions of different reactants, promotes the intermediate conversions, optimizes the binding strength, and supplies ensemble effects, improving the catalytic performances significantly. [ 24–30 ] Currently, the utilizations of TMs metals are the mainstream selections in DAC. In comparison, the main group elements including alkaline/alkaline earth metals (AAEM), post‐transition metals (Post‐TM), and metalloids are rarely discussed.…”

Supercritical CO2‐assisted Fabrication of Two‐dimensional Graphdiyne Oxide Nanosheets for Enhanced Photothermal Conversion

“…As an emerging 2D carbon‐network material, graphdiyne (GDY) has attracted great attention from theory to experiment, because of possessing natural semiconductor band gap and superior electrical properties, differing from carbon nanotube and graphene [1–3] . GDY has a planar and conjugate structure with homogeneous nanopores, resulting from the benzene ring and the butadiyne linkage, [4–8] which are composed of sp and sp 2 carbon atoms [9–10] . Graphdiyne has been reported for promising practical applications in catalysis, [11] electrics, [12] detection, [13] energy storage [14] and biomedicine [15] .…”

Low‐dimensional material supported single‐atom catalysts for electrochemical CO2 reduction

“…In contrast, Ni/Fe DMS structure with adsorbed CO reduces the barrier for *COOH formation and the *CO desorption simultaneously, which extremely promotes CO formation (Figure 8I). Huang et al 160 used the DFT and machine learning techniques to propose the Ln–transition metal (TM) DMS systems as the promising electrocatalyst candidates with expected high electroactivity and durability in the long‐term applications. They further experimented with verifying that a Zn/Ln DMS catalyst was highly effective for ECR to produce CO/H 2 syngas with a tunable ratio 159 .…”