Ab initio quality neural-network potential for sodium

Article

关键词: EMBEDDED-ATOM METHOD;    MOLECULAR-DYNAMICS SIMULATION;    ELASTIC-CONSTANTS;    ENERGY SURFACES;    1ST PRINCIPLES;    LIQUID-SODIUM;    CUBIC METALS;    ALKALI-METALS;    BCC METALS;    PRESSURE;   

DOI  :  10.1103/PhysRevB.81.184107

来源: SCIE

【 摘 要 】

An interatomic potential for high-pressure high-temperature (HPHT) crystalline and liquid phases of sodium is created using a neural-network (NN) representation of the ab initio potential-energy surface. It is demonstrated that the NN potential provides an ab initio quality description of multiple properties of liquid sodium and bcc, fcc, and cI16 crystal phases in the P-T region up to 120 GPa and 1200 K. The unique combination of computational efficiency of the NN potential and its ability to reproduce quantitatively experimental properties of sodium in the wide P-T range enables molecular-dynamics simulations of physicochemical processes in HPHT sodium of unprecedented quality.

【 授权许可】

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