A Systematic Progressive Infusion of Computational ChemistryThroughout an Undergraduate Chemistry Curriculum

计算方法是实验和理论方法的补充，是提高化学知识的一种手段。因此，本科化学课程必须包含有意义的计算成分。在一般化学中，学生们使用软件包来增强他们对微观性质以及微观和宏观性质之间关系的理解。在计算化学入门课程中，学生将接触到不同的计算方法和电子结构方法的实际应用。在有机化学中，这些技巧被应用于研究反应性和电子结构之间的关系。计算方法的光谱应用在物理化学中被强调，而无机和生物化学课程的学生正在进行更复杂的、多方面的项目，包括基于dft梯度优化的结构预测、晶体结构可视化和药物与活性位点的结合亲和力。

Computational methods complement experimental and theoretical methods as a means for advancing chemical knowledge. Therefore, it is essential that the undergraduate chemistry curriculum include a meaningful computational component. In general chemistry, students are using software packages to enhance their understanding of microscopic properties and the relationship between microscopic and macroscopic properties. In an introductory computational chemistry course, students are being exposed to different computational methods and the practical applications of electronic structure methods. In organic chemistry, these skills are being applied to studies of the relationship between reactivity and electronic structure. The spectroscopic applications of computational methods are being emphasized in physical chemistry, while students in inorganic and biochemistry courses are undertaking more complex, multifaceted projects involving structural predictions based on DFT-gradient optimizations, crystal structure visualizations, and drug binding affinity to active sites.