Abstract

Single-atom catalysts with particular electronic structures and precisely regulated coordination environments delivering excellent activity for oxygen-evolution reaction (OER) and oxygen-reduction reaction (ORR) are highly desirable for renewable energy applications. In this work, a novel tetragonal carbon nitride T-C2N monolayer with remarkable stability was predicted by using the RG2 method. Inspired by the well-defined atomic structures and just right N4 aperture of T-C2N substrate, the electrocatalytic performance of a series of transition metal single-atoms anchored on porous T-C2N matrix (TM@C2N) have been systematically investigated. In addition, machine learning (ML) method was employed with the gradient boosting regression GBR model to deeply explore the complex controlling factors and offer direct guidance for rational discovery of desirable catalysts. On this basis, the coordination environment of the central TM active sites has been tailored by incorporating heteroatoms. Impressively, the Co@C2N/B-C, Rh@C2N/SC and Rh@C2N/SN exhibit significantly enhanced OER/ORR activity with notably low ηOER/ηORR of 0.39/0.32, 0.26/0.35 and 0.37/0.27 V, respectively. Our work provides insights into the rational design, data-driven, performance regulation, mechanism analysis and practical application of TMNC catalysts. Such a systematic theoretical framework can also be expanded to many other kinds of catalysts for energy storage and conversion.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call