###### Abstract
Computational chemistry refers to the application of computational methods to chemistry to solve practical problems, including ab initio algorithms based on simple molecules and kinetic calculations of complex molecules, while computer molecular simulation refers to the general method of constructing actual atomic models to describe large and complex chemical systems and to predict their macroscopic physical properties. When the spatial position of each nucleus in the computational system is determined, the distribution of electron density in space can be determined, and then the energy of the computational system can be represented by a generalized function of electron density. For the computational system, a suitable density generalization method can yield a more accurate solution than the ab initio algorithm, and at the same time take less time. Commonly used density generalization methods include B3 LYP, etc. Due to the limitation of computational resources, the more common 6-31G(d) all-electron basis group is used for light atoms, while the Lanl2 DZ pseudopotential basis group is used for transition metal atoms in order to eliminate relativistic effects. Finally, a more reasonable calculation method was chosen by comparing the errors of the calculated and experimental values of each complex structure. With the development of computer technology and quantum chemistry research theories, computer simulations have been applied to molecular imprinting preparation [23]. [PERSON] et al. [24] used chloramphenicol (CAP) as a template molecule and methacrylic acid (MAA) as a functional binding ligand. All calculations were performed using Gaussian 09 software at the LC-WPBE/6-31g(d, p) level using density generalized function theory [25]. The conformations of the complexes formed by CAP and MAA in different ratios were optimized and the solvation energies of the complexes in the above-mentioned solvents were discussed to check the optimal geometrical conformation and the strength of the interaction between these solvents. Nanomicrospheres prepared by precipitation polymerization can be used as sorbent materials in extraction columns due to their uniform particle size and microporous structure [26]. Guided by the calculation results, molecularly imprinted polymers were synthesized by precipitation polymerization and the adsorption capacity of molecularly imprinted polymers was investigated by equilibrium adsorption experiments. In recent years, more and more researchers have made great progress in order to explore the molecular imprinting process and molecular recognition mechanism, reducing the blindness of preparation, improving the efficiency of molecularly imprinted polymers development, and increasing the adsorption, selectivity, and stability of molecularly imprinted polymers. Many studies have used B3 LYP, M06 ZX, and PBE0 methods to simulate and design molecular imprinting systems by using Gaussian software. [PERSON] et al. [27] used formaldehyde (HCHO) as the imprinting molecule, MAA as the functional binding ligand, divinylbenzene, ethylene glycol dimethacrylate (EGDMA), pentaerythnitol triacrylate and trimethylolpropane as crosslinkers, and water as the solvent to construct the system. Under the condition that the molecular structures of the imprinted molecules and the functional binding ligands of MAA were modeled, the structures of HCHO and MAA were optimized using quantum chemical density flooding theory. After selecting the most stable conformation, the most suitable crosslinker and solvent were selected by calculating the binding energy and hydrogen bond number. Ion imprinted polymers (IIPs) are highly selective synthetic receptors that can recognize metal ions, which also retains all the advantages of molecularly imprinted polymers (MIPs) in this work.