Abstract: The upgrading of the manufacturing industry puts forward higher requirements on the supply and quality of existing lubricants. The demand for lubricants inevitably tends to be individualized, differentiated and diversified. The research and development speed and quality of lubricants in China lag behind market demand. In response to the future market’s requirements for materials, the United States put forward the material genome plan in 2011, and China also put forward its own material genome plan. The main core goal of the Material Genome Project is to shorten the research and development cycle by half and reduce the cost of research and development by half, which will greatly promote the speed and efficiency of the research and development of new materials. It has important strategic significance for China to get out of the predicament of insufficient lubricant research and development. The material gene project will rely on high-throughput computing methods and computing resources to achieve its goals in order to realize the rational design of materials. In recent years, a large number of high-throughput computation studies of materials have been carried out in China, but the high-throughput computation of lubricating materials is still blank.　A high-throughput molecular dynamics computation framework for liquid lubricants is proposed for ionic liquids and ester compounds. Ionic liquids and ester compounds are the two main types of lubricants, so the currently generated molecular model library contains these two types of lubricants, and other types of lubricants can be easily added under the existing framework. The starting point for generating the molecular model library is to obtain the simplified molecular input line entry specification (SMILES) string of the functional groups of the ionic liquid anion, cation and ester compounds. Although there are many ionic liquids and ester compounds with different molecular structures, the number of functional groups is very limited and can be easily obtained from existing chemical libraries. The SMILES string of common carbon chain structure has been built in the program. After entering the SMILES string of the tube energy group, the program will automatically add the carbon chain structure to the functional group, and then combine to generate ionic liquid and ester compounds to quickly obtain the molecular geometric topology of a large number of lubricants Based on graph theory, the optimized potentials for liquid simulations all-atom (OPLS-AA) force field is automatically assigned to lubricant molecules, and finally a molecular model library containing a large number of lubricants is generated. The OPLS-AA force field can accurately describe the liquid phase thermodynamic characteristics and dynamic behavior of the lubricant. The 1.14*CM1A method is used to calculate the partial charge. This method can generate accurate partial charges for both the neutral lubricant molecules and the anions and cations in the non-neutral ionic liquid.　Finally, based on the established lubricant molecular dynamics model library, a two-layer high-throughput parallel computation method of lubricant physical parameters and friction coefficients is carried out. In high-throughput computations, the amount of computation is concentrated in two aspects: first, there are a large number of lubricants in the library, and computations need to be carried out for each; second, the computation of a single lubricant adopts a full-atom scale simulation to ensure the computation accuracy. In order to solve the problem of the amount of computation, a two-layer parallel strategy is adopted to improve the computation efficiency. The first layer divides the lubricant files in the library into blocks, and computes the lubricant in each block concurrently. In a certain block, the lubricants are calculated sequentially. The second level of parallel setting is to use multiple CPUs for parallel molecular dynamics computations for a certain lubricant. The computation method can achieve tens of thousands of concurrent computations. The accuracy of the proposed high-throughput computation method is verified by taking ionic liquid as the object. This high-throughput computation framework points out a feasible direction for realizing the high-throughput rational design of the whole process lubricant, and lays a theoretical foundation for the design of new lubricating materials.