浅谈用“终态分析法”解化学计算题

化学计算是中学化学中的一个重要组成部分,它基本上渗透到了教材的每一个章节,学生在做题过程中往往只按自己已有的方法求得正确解就了事.很少对化学计算方法进行总结.这样一旦遇上难度稍大的题目或自己的思维行不通时将会束手无策,导致失败.解化学计算题的方法很多,下面重点谈一下用"终态分析法"解化学计算题.     

计算化学辅助大学有机化学教学的探讨

计算化学作为化学的一门独立分支已经渗透到有机化学的各个方面.借助于计算化学,可以将有机化学中抽象的分子结构、反应机理等直观化,从而使得相关有机化学知识更容易被理解和掌握.以有机化学中的化学、反应机理以及红外光谱等概念为例,探讨了计算化学在有机化学教学中的应用,为大学有机化学的教学提供一些有益的尝试.     

计算化学在化学化工中的应用(下)

计算化学在最近十年中是发展最快的化学研究领域之一,通过对具体的分子系统进行理论分析和计算,能比较准确地回答有关稳定性、反应机理等基本化学问题。如今计算化学已被广泛用于材料、催化和生物化学等研究领域。主要就计算化学的背景、计算化学常用的方法及其在化学化工中的应用等几个方面作一简单介绍。     

计算化学在化学化工中的应用（上）

计算化学在最近十年中是发展最快的化学研究领域之一,通过对具体的分子系统进行理论分析和计算,能比较准确地回答有关稳定性、反应机理等基本化学问题。如今计算化学已被广泛用于材料、催化和生物化学等研究领域。主要就计算化学的背景、计算化学常用的方法及其在化学化工中的应用等几个方面作一简单介绍。     

有限元方法求解化学气相淀积反应器模型(Ⅰ)——冷壁反应器模型及有限元解

建立了冷壁化学气相淀积反应器的数学模型,用Galerkin有限元方法对模型予以求解.计算中考虑了温度对物性参数的影响及自然对流因素,计算值和实验结果基本上一致.     

计算化学和虚拟仿真技术在制药工程专业有机化学教学中的应用实践

随着现代科技的迅速发展,计算化学和虚拟仿真技术在基础化学教学中的应用越来越广泛.借助于计算化学和虚拟仿真技术,可将有机化学中抽象的分子结构、分子轨道、反应机理等直观化,从而使相关知识点更容易理解和掌握.本文以绝对构型的判断、构型与构象的区分、反应机理的动态演示为例,对计算化学和虚拟仿真技术在制药工程专业有机化学课程教学...     

计算化学的应用研究进展

随着计算化学方法的不断改进和计算机技术的飞速发展,计算化学在科学研究中起着更加重要的作用。本文从计算化学快速发展的原因、分类及其在化学教育、生命科学和材料等方面的应用进行了简要论述,并论述了最新的研究进展。     

有限元方法求解化学气相淀积反应器模型(Ⅰ)——冷壁反应器模型及有限元解

建立了冷壁化学气相淀积反应器的数学模型,用Galerkin有限元方法对模型予以求解.计算中考虑了温度对物性参数的影响及自然对流因素,计算值和实验结果基本上一致.     

计算化学的应用研究进展

随着计算化学方法的不断改进和计算机技术的飞速发展,计算化学在科学研究中起着更加重要的作用。本文从计算化学快速发展的原因、分类及其在化学教育、生命科学和材料等方面的应用进行了简要论述,并论述了最新的研究进展。     

对多重平衡现象理解及解决方法

多重平衡现象蕴含着丰富的内涵,可以灵活地运用于多种化学问题解释和化学计算.本文探讨多重平衡的应用.     

Computational Chemistry in the Pharmaceutical Industry: From Childhood to Adolescence

Computational chemistry within the pharmaceutical industry has grown into a field that proactively contributes to many aspects of drug design, including target selection and lead identification and optimization. While methodological advancements have been key to this development, organizational developments have been crucial to our success as well. In particular, the interaction between computational and medicinal chemistry and the integration of computational chemistry into the entire drug discovery process have been invaluable. Over the past ten years we have shaped and developed a highly efficient computational chemistry group for small‐molecule drug discovery at Bayer HealthCare that has significantly impacted the clinical development pipeline. In this article we describe the setup and tasks of the computational group and discuss external collaborations. We explain what we have found to be the most valuable and productive methods and discuss future directions for computational chemistry method development. We share this information with the hope of igniting interesting discussions around this topic.     

计算化学在多孔储氢材料研究中的应用

计算化学方法在多孔储氢材料的应用主要有4个方面:1)研究多孔材料的储氢性能;2)研究多孔材料对氢气的吸附热;3)研究储氢机理;4)设计新型多孔储氢材料。综述了计算化学方法在多孔储氢材料研究中取得的成果和最新进展,展望了计算化学方法在储氢领域的应用前景。     

Prioritizing Small Sets of Molecules for Synthesis through in-silico Tools: A Comparison of Common Ranking Methods

Prioritizing molecules for synthesis is a key role of computational methods within medicinal chemistry. Multiple tools exist for ranking molecules, from the cheap and popular molecular docking methods to more computationally expensive molecular-dynamics (MD)-based methods. It is often questioned whether the accuracy of the more rigorous methods justifies the higher computational cost and associated calculation time. Here, we compared the performance on ranking the binding of small molecules for seven scoring functions from five docking programs, one end-point method (MM/GBSA), and two MD-based free energy methods (PMX, FEP+). We investigated 16 pharmaceutically relevant targets with a total of 423 known binders. The performance of docking methods for ligand ranking was strongly system dependent. We observed that MD-based methods predominantly outperformed docking algorithms and MM/GBSA calculations. Based on our results, we recommend the application of MD-based free energy methods for prioritization of molecules for synthesis in lead optimization, whenever feasible.     

Design of new catalysts for ecological high-quality transportation fuels by combinatorial computational chemistry and tight-binding quantum chemical molecular dynamics approaches

Recently, we introduced a concept of combinatorial chemistry to computational chemistry and proposed a new method called “combinatorial computational chemistry”, which enables us to perform a theoretical high-throughput screening of catalysts. In the present paper, we reviewed our recent application of our combinatorial computational chemistry approach to the design of new catalysts for high-quality transportation fuels. By using our combinatorial computational chemistry techniques, we succeeded to predict new catalysts for methanol synthesis and Fischer–Tropsch synthesis. Moreover, we have succeeded in the development of chemical reaction dynamics simulator based on our original tight-binding quantum chemical molecular dynamics method. This program realizes more than 5000 times acceleration compared to the regular first-principles molecular dynamics method. Electronic- and atomic-level information on the catalytic reaction dynamics at reaction temperatures significantly contributes the catalyst design and development. Hence, we also summarized our recent applications of the above quantum chemical molecular dynamics method to the clarification of the methanol synthesis dynamics in this review.     

Surface and interfacial chemistry

Based on a molecular approach combining controlled surface chemistry, advanced spectroscopic methods, in particular solid-state NMR, and computational chemistry, it is possible to develop single-site species and to control the growth of nanoparticles on supports. This allows the generation of highly efficient catalysts combining the advantages of both homogeneous and heterogeneous catalysts and function materials with defined properties.     

金属-有机骨架材料在气体膜分离中的研究进展

金属-有机骨架材料(metal-organic frameworks,MOF)由于具有高比表面积、大孔隙率、功能性孔道结构以及种类多样性等特征,在储气、分离、催化、载药和光学等领域受到重视。其中,制备纯MOF膜或基于MOF的混合基质膜(mixed matrix membranes,MMMs)并用于气体分离,被认为具有潜在的应用前景。目前为止,实验合成的MOF材料种类已有两万种,为了快速筛选出合适的MOF材料作为膜材料,计算化学的方法可以极大地缩减MOF膜的研究周期,并有助于指导实验合成高效膜分离材料。本文分别从计算和实验两方面介绍了MOF膜在气体分离中的研究进展,分析表明,MOF膜的研究总体上向功能性更强、稳定性更高的方向发展,但是利用计算方法建立MOF膜的构效关系还存在一定的难度。因此,建立MOF膜的结构与性能表征的新概念、新方法,并利用MOF膜的结构-性能关系指导实验合成高稳定性、低成本的膜材料将是未来MOF膜的发展方向。     

抗肿瘤有效成分靛玉红作用机理的研究进展

靛玉红具有副作用小,临床疗效好等优点。由于靛玉红具有独特的研究价值和潜在的应用前景,越来越受到人们的重视。综述了靛玉红的量子化学研究和药理作用,并对其今后的发展动态进行了展望。量子化学研究方法有CNDO分子轨道法、密度泛函DFT法和CNDO／2量子化学法等;靛玉红具有抗菌、消炎、增强免疫、抗肿瘤等药理作用。     

Towards multiscale modelling in product engineering

A concept of multiscale modelling of product manufacturing based on integration of three modelling methods currently applied at different scales of length and time: process system modelling, computational fluid dynamics and computational chemistry was presented. Major features of the three key types of modelling in the chemical and process industries were briefly described. The first applications and mutual benefits of joint use of two of the three approaches were presented along with the perspectives for the full integration of all three methods. The crucial role of a universal interface, such as the CAPE-OPEN standard, was emphasized.