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Rational Design of 3d-Transition Metal Phthalocyanine Sheet Electrocatalysts for Overall Water Splitting and Metal–Air Batteries: A DFT Investigation

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Rational_Design_of_3d-Transition_Metal_Phthalocyanine_Sheet_Electrocatalysts_for_Overall_Water_Splitting_and_Metal_Air_Batteries_A_DFT_Investigation/31956645
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The development of efficient, stable, and cost-effective single-atom catalysts (SACs) is crucial for advancing sustainable energy technologies such as water splitting and metal–air batteries. Two-dimensional (2D) metal phthalocyanine sheets (s-MPc) present a promising platform with their well-defined, high-density active sites, but comprehensive screening for their bifunctional catalytic activity and electrochemical stability is lacking. Herein, we conducted a systematic first-principles density functional theory (DFT) study to screen a series of s-MPc (M = Sc to Zn) as trifunctional electrocatalysts for the hydrogen evolution reaction (HER), oxygen evolution reaction (OER), and oxygen reduction reaction (ORR). Our stability analysis, based on formation energy, dissolution potential, and surface Pourbaix diagrams, identifies s-VPc, s-MnPc, s-FePc, s-CoPc, s-NiPc, and s-CuPc as electrochemically stable across all pH conditions. Catalysts’ performance evaluation reveals distinct optimal candidates: s-MnPc and s-VPc exhibit superior HER activity with near-optimal hydrogen adsorption energies (ΔGH*), while s-VPc and s-CuPc demonstrated outstanding OER performance with low overpotentials of 0.41 and 0.49 V, respectively, rivaling IrO2. For the ORR, s-CoPc and s-MnPc emerge as the most active, with low overpotentials comparable to those of the Pt(111) surface. Consequently, we identify s-VPc as an excellent bifunctional catalyst for the HER/OER and s-CoPc and s-CuPc for the OER/ORR. Supervised machine learning (ML) is employed on a set of atomic and electronic descriptors to classify the efficiency of s-MPc sheets for the HER/OER/ORR, with the KNN model demonstrating superior predictive performance. This work not only highlights specific high-performance s-MPc candidates but also establishes a robust computational framework for the design and screening of durable, high-activity single-atom electrocatalysts.
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2026-04-07
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