Rational Design of 3d-Transition Metal Phthalocyanine Sheet Electrocatalysts for Overall Water Splitting and Metal–Air Batteries: A DFT Investigation
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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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资源简介:
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.
创建时间:
2026-04-07



