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Functional properties of nanomaterials strongly depend on their surfaceatomic structure, but they often become largely different from their bulkstructure, exhibiting surface reconstructions and relaxations. However, most ofthe surface characterization methods are either limited to 2-dimensionalmeasurements or not reaching to true 3D atomic-scale resolution, andsingle-atom level determination of the 3D surface atomic structure for general3D nanomaterials still remains elusive. Here we show the measurement of 3Datomic structure of a Pt nanoparticle at 15 pm precision, aided by a deeplearning-based missing data retrieval. The surface atomic structure wasreliably measured, and we find that <100> and <111> facets contributedifferently to the surface strain, resulting in anisotropic strain distributionas well as compressive support boundary effect. The capability of single-atomlevel surface characterization will not only deepen our understanding of thefunctional properties of nanomaterials but also open a new door for finetailoring of their performance.

Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography