遗传算法在催化体系的全局结构优化中的应用

对催化体系进行全局结构优化,搜寻基态结构对预测催化剂结构、分析反应物的吸附特性、研究多相催化反应机理、构建实际反应路径等方面至关重要。遗传算法通过交叉、变异和选择等操作,模拟了自然淘汰进化过程,来搜索势能面上的基态结构。作为一种无偏优化算法,遗传算法的优化过程不依赖于输入结构,具有很强的全局搜索能力。对遗传算法在催化体系的全局结构优化问题中的应用进行了综述,介绍了遗传算法在实空间上进行全局结构优化的基本程序框架以及近年来结合并行计算、机器学习等技术发展的改进框架,并讨论了它们在团簇优化、负载型催化剂的结构优化问题上的相关应用,为遗传算法的进一步改进以及更广泛的应用提供理论指导。     

组合化学在催化领域中的应用

组合技术已成为化学研究领域最活跃的前沿之一,是现代催化剂开发的重要手段。     

组合催化的原理、策略与发展

介绍了组合催化的基本原理和催化剂库的高通量筛选方法;讨论了组合催化技术的2个关键因素———催化剂库的合成方法和相应的高通量检测技术在催化研究中的重要作用。综述了组合催化技术在无机、有机以及生物催化领域中的应用进展,指出进一步与计算机相结合,研究新的催化剂体系、开发新的催化剂合成技术和新的筛选技术是今后组合催化的发展方向和趋势。     

组合化学在多相催化领域中的应用

本文系统综述了新近兴起的技术——组合化学在多相催化领域中的研究进展。通过对组合催化研究的两个关键因素催化剂库合成及催化剂高通量筛选技术的评价分析认为,在对已有的催化体系和催化剂优化的同时，如何高效研制新催化材料及开发新筛选检测技术，是组合催化研究的主导思想，对此的深刻理解和运用，将增强实验室的创新能力。     

组合催化在石油化工催化开发中的应用

概述了组合催化的基本原理及实验装置,主要介绍了组合催化在丙烯环氧化制环氧丙烷、甲醇与甲苯侧链烷基化制苯乙烯、丁二烯制四氢呋喃、乙烷/丙烷氧化脱氢制乙烯/丙烯等石油化工过程催化剂研发中的应用,指出组合催化将是未来发现新催化材料及新催化过程的有效手段。     

遗传算法在离散控制系统优化中的应用

利用遗传算法实现对离散控制系统的优化,并给出了离散二阶线性系统的最优控制实例。     

组合化学及其在新农药开发中的应用

结合医药领域的成功经验概述了组合化学的基本概念、化合物库的合成技术与分析、筛选方法，综述了组合化学方法在发现与优化新农药先导化合物中的研究进展，介绍了作者利用互补分子反应活性与分子识别技术优化除草活性原卟啉原氧化酶抑制剂的研究工作，展望了组合化学在新农药创制中的应用前景。     

动态遗传算法在大数据聚类分析中的应用

对于常规聚类方法,聚类结果往往与初始聚类中心数目和数据入次序有关。本文另辟蹊径,提出了一种动态GA来实现样本类别数目由数据本身来确定,避免了聚类数目确定的盲目性等问题。计算结果表明,该方法是一个具有全局最优解的动态聚类方法。     

组合化学及其在新农药创制中的应用

结合医药领域的成功经验概述了组合化学的基本概念、化合物库的合成技术与分析、筛选方法,展望了组合化学在新农药创制中的应用前景。     

高通量筛选技术在多相催化研究中的应用

通过对组合催化研究的关键因素－－催化剂高通量筛选技术的评价分析认为：在对已有的催化体系和催化剂优化的同时，如何高校研制开发新筛选检测技术，诸如反应器设计和检测器的选择，是组合催化研究的主导思想，对此的深刻理解和运用将增强实验室的创新能力。     

An evolutionary approach in the combinatorial selection and optimization of catalytic materials

A methodical basis of the evolutionary method for selection and optimization of heterogeneous catalytic materials was developed. For validation, the oxidative dehydrogenation of propane was used as a model reaction. Various oxides (V₂O₅, MoO₃, MnO₂, Fe₂O₃, GaO, MgO, B₂O₃, La₂O₃) were chosen as primary components for the generation of catalytic materials. The first generation consisting of 56 catalytic materials was created by combination of the primary components in a stochastic manner. The materials of each preceding generation were selected based on the catalytic results obtained and subjected to an evolutionary procedure applying mutation and crossover operators to create further generations of catalytic materials of different qualitative and quantitative compositions. For illustration, four generations were created with a total number of tested catalytic materials of 224. As a result of the preliminary optimization procedure an increase in the propene yield was achieved with increasing number of generations; the results can be certainly improved by screening further generations of catalytic materials. Under standard conditions used for testing (T=500°C, C₃H₈/O₂=3, p(C₃H₈)=30 Pa), the highest C₃H₆ yield amounted to 9.0% (S=57.4%) in the 3rd generation on V_0.22Mg_0.47Mo_0.11Ga_0.20O_x.     

基于遗传算法的桁架形状优化及最小质量设计

在工程结构的优化设计中,应用遗传算法的基本原理,研究了离散设计变量全局寻优等传统优化方法难于解决的特殊问题。以平面桁架梁作为解析例,选取桁架的节点坐标和杆件的截面特征为设计参数,模拟遗传操作过程中的生物进化机制,对桁架的构成和形状的优化问题进行了解析。得到桁架在不同情况下的形状优化解,并使桁架质量趋于最小。研究结果验证了遗传算法在桁架的形状最优化和最小质量设计中应用的可行性。     

Mass exchange network synthesis using genetic algorithms

Mass Exchange Networks (MENs) are used in the chemical industry to reduce the waste generated by a plant to an acceptable level at the cheapest cost. Finding the optimal network, however, is often difficult due to the non-convexity of the mathematical representation of the problem. This paper describes a novel approach for the synthesis of MENs and MENs with regeneration using Genetic Algorithms (GA), a stochastic optimisation technique based on the concepts of natural evolution. We present an encoding for a genetic algorithm which describes a rich search space, considering both stream splitting and in-series exchangers. For a certain class of problems, all encoded solutions are feasible and require a simple evaluation to yield a cost, resulting in an efficient genetic algorithm. For other problems, the number of infeasible solutions is small, having little effect on the convergence of the genetic algorithm. In comparison with other methods, the GA presented herein is able to find better networks than have been reported elsewhere.     

组合化学及其应用

组合化学是一种快速大量的合成技术。简明地介绍了组合化学的基本原理、化合物库的设计与制备方法、活性分子结构的表征以及组合化学在许多领域里的应用。     

液相组合合成中化合物库的纯化方法研究

综述了近8年来液相组合合成中小分子化合物库的纯化方法，如通过固载化试剂的应用、可溶性聚载物的应用、氟合成技术、液相萃取等达到纯化目的。论述了这些纯化方法的基本原理、使用范围及局限，并列举了一些经典实例。     

Fundamental and combinatorial approaches in the search for and optimisation of catalytic materials for the oxidative dehydrogenation of propane to propene

An evolutionary approach was applied to create five generations of -Al₂O₃-supported multi-metal-oxides to be used as catalytic materials for the oxidative dehydrogenation of propane at 773 K. Each generation consisted of 56 differently composed materials, i.e., a total amount of 280 materials. These catalytic materials were tested in parallel. For the best materials propene yields from 7% (1st generation) to 9% (5th generation) were achieved. Some of these superior catalysts were characterised by XRD, XPS and EPR. A correlation between catalytic performance and the Mg/V ratio on the surface was found. Based on the structural knowledge obtained, from which the requirement of isolated or at least weakly interacting vanadium sites was derived, VO_x (2.8 wt.%)/MCM-48 and VO_x (2.8 wt.%)/MCM-41 catalysts with a high dispersion of vanadia were used as reference giving a maximal propene yield of 17 and 15%, respectively.     

水滑石类材料在氧化还原催化反应中的应用

综述了水滑石类材料在氧化还原催化反应中应用的最新研究进展,重点讨论了类水滑石及以类水滑石为前驱体衍生得到的复合氧化物在精细合成中的绿色催化应用。水滑石类材料必将在环境友好催化工业体系中扮演越来越重要的角色。