Single‐atom catalysts (SACs) have become the forefront of energy conversion studies, but unfortunately, the origin of their activity and the interpretation of the synchrotron spectrograms of these materials remain ambiguous. Here, systematic density functional theory computations reveal that the edge sites—zigzag and armchair—are responsible for the activity of the graphene‐based Co (cobalt) SACs toward hydrogen evolution reaction (HER). Then, edge‐rich (E)‐Co single atoms (SAs) were rationally synthesized guided by theoretical results. Supervised learning techniques are applied to interpret the measured synchrotron spectrum of E‐Co SAs. The obtained local environments of Co SAs, 65.49% of Co‐4N‐plane, 13.64% in Co‐2N‐armchair, and 20.86% in Co‐2N‐zigzag, are consistent with Athena fitting. Remarkably, E‐Co SAs show even better HER electrocatalytic performance than commercial Pt/C at high current density. Using the joint effort of theoretical modeling, thorough characterization of the catalysts aided by supervised learning, and catalytic performance evaluations, this study not only uncovers the activity origin of Co SACs for HER but also lays the cornerstone for the rational design and structural analysis of nanocatalysts.

Atomic simulations provide an effective means to understand the underlying physics of structural phase transformations. However, this remains a challenge for certain allotropic metals due to the failure of classical interatomic potentials to represent the multitude of bonding. Based on machine-learning (ML) techniques, we develop a hybrid method in which interatomic potentials describing martensitic transformations can be learned with a high degree of fidelity from ab initio molecular dynamics simulations (AIMD). Using zirconium as a model system, for which an adequate semiempirical potential describing the phase transformation process is lacking, we demonstrate the feasibility and effectiveness of our approach. Specifically, the ML-AIMD interatomic potential correctly captures the energetics and structural transformation properties of zirconium as compared to experimental and density-functional data for phonons, elastic constants, as well as stacking fault energies. Molecular dynamics simulations successfully reproduce the transformation mechanisms and reasonably map out the pressure-temperature phase diagram of zirconium.

Multitudinous topological configurations spawn oases of many physical properties and phenomena in condensed-matter physics. Nano-sized ferroelectric bubble domains with various polar topologies (e.g., vortices, skyrmions) achieved in ferroelectric films present great potential for valuable physical properties. However, experimentally manipulating bubble domains has remained elusive especially in the bulk form. Here, in any bulk material, we achieve self-confined bubble domains with multiple polar topologies in bulk Bi0.5Na0.5TiO3 ferroelectrics, especially skyrmions, as validated by direct Z-contrast imaging. This phenomenon is driven by the interplay of bulk, elastic and electrostatic energies of coexisting modulated phases with strong and weak spontaneous polarizations. We demonstrate reversable and tip-voltage magnitude/time-dependent donut-like domain morphology evolution towards continuously and reversibly modulated high-density nonvolatile ferroelectric memories.

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