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991.
Mei Li Krzysztof Matyjaszewski 《Journal of polymer science. Part A, Polymer chemistry》2003,41(22):3606-3614
An improved atom transfer radical polymerization (ATRP) process was developed for use in a waterborne miniemulsion system. To conduct a successful ATRP in a heterogeneous waterborne system, it is of great importance to ensure control over the polymerization process while preserving colloidal stability. Efforts devoted to optimization of reaction conditions and improvement in the overall productivity of the process allowed the development of a novel, practical initiation system for ATRP suitable for use in a miniemulsion procedure that can provide copolymers of well-defined composition (e.g., block copolymers) and topologies (e.g., multiarm polymer). © 2003 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 41: 3606–3614, 2003 相似文献
992.
XingZhouLI KeMeiWU LiangHUANG 《中国化学快报》2003,14(4):338-340
Synthesis of the optically active metabolite of clausenamide cm2(3,5-dihydroxy-5-(α-hydroxylbenzyl)-1-methyl-4-benzylpyrrolidin-2-one)from 3-O-acetyl-clausenamide was described. 相似文献
993.
本文用ESR方法考察了Cp2ZrH) Cl与RNCSR=C6H5,c-C6H11,n-C4H9)的反应的过程,结果表明,在这类反应过程中,Zr-H键发生均裂,中心金属锆经过+4-→+3-→+4的价态变化,反应通过自由基机理进行. 相似文献
994.
对硝基苯乙酮在0.025mol·L-1乙二胺-0.010mol·L-1EDTA底液中,产生一灵敏的极谱峰电流.峰电位为-0.35V(vs.SCE).对硝基苯乙酮浓度在3.00×10-8~1.00×10-4mol·L-1范围内,浓度与峰电流成线性关系.检测限为3.00×10-8mol·L-1.本方法用于氯霉素制药厂废水中的对硝基苯乙酮的测定,取得满意的结果 相似文献
995.
4,4'-Oxybis(benzoic acid)(Ⅰ)is an important monomer for making synthetic resin,heat resistant filmand liquid crystal fiber,etc.It has been synthesized either by the oxidation of 4,4'-dimethyl diphenylether,or by the electrophilic substitution of diphenyl ether,these substituents introduced into thebenzene ring can be further transformed into carboxylic groups.Diphenyl ethers are usually prepared fromphenols and halobenzenes through Ullmann resction.Due to the high reaction temerature(usually above200℃),long time heating and the formation of isomers,it is difficult to obtain pure products in highyields. 相似文献
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998.
Hoi-Ming Chi Okan K. Ersoy Herbert Moskowitz Jim Ward 《European Journal of Operational Research》2007
Using a supply chain network, we demonstrate the feasibility, viability, and robustness of applying machine learning and genetic algorithms to respectively model, understand, and optimize such data intensive environments. Deployment of these algorithms, which learn from and optimize data, can obviate the need to perform more complex, expensive, and time consuming design of experiments (DOE), which usually disrupt system operations. We apply and compare the behavior and performance of the proposed machine learning algorithms to that obtained via DOE in a simulated Vendor Managed Replenishment system, developed for an actual firm. The results show that the models resulting from the proposed algorithms had strong explanatory and predictive power, comparable to that of DOE. The optimal system settings and profit were also similar to that obtained from DOE. The virtues of using machine learning and evolutionary algorithms to model and optimize data rich environments thus seem promising because they are automatic, involving little human intervention and expertise. We believe and are exploring how they can be made adaptive to improve parameter estimates with increasing data, as well as seamlessly detecting system (and therefore model) changes, thus being capable of recursively updating and reoptimizing a modified or new model. 相似文献
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