The Antielectrostatic Effect of N-Alkanol-N-alkoxymethyl-N,N-dimethylammonium Chlorides and Their Ester Derivatives

• Autorzy: Pernak, J. , Chwała, P. , Syguda, A. , Poźniak, R.
• Języki publikacji: EN

Abstrakty

EN

Several new quaternary ammonium chlorides, analogues of choline, were prepared by reaction of 2-(dimethylamino)ethanol and its derivatives with chloromethyl alkyl ethers. The obtained chlorides were examined in respect to their antielectrostatic effects: the surface resistance and half decay time on polyethylene film were measured. Application of rough set theory permitted to perform a comprehensive analysis of data and detection of structural-activity relationships. The obtained chlorides showed high antielectrostatic properties. The most active were quaternary ammonium chlorides with 11 and 12 carbon atoms in alkyl chain.

Słowa kluczowe

EN

quaternary ammonium salts; antielectrostatic effect; rough set theory; SAR

• Czasopismo: Polish Journal of Chemistry
• Rocznik: 2003
• Tom: Vol. 77 / nr 10
• Strony: 1263-1274
• Opis fizyczny: Bibliogr. 12 poz., rys.

Twórcy

autor

Pernak, J.

• Poznan University of Technology, 60-965 Poznań, pl. Skłodowskiej-Curie 2, Poland

autor

Chwała, P.

• Poznan University of Technology, 60-965 Poznań, pl. Skłodowskiej-Curie 2, Poland

autor

Syguda, A.

• Poznan University of Technology, 60-965 Poznań, pl. Skłodowskiej-Curie 2, Poland

autor

Poźniak, R.

• Wrocław University of Technology, 50-370 Wrocław, Poland

Bibliografia

• 1. Stahl P.H. and Wermuth C.G., Handbook of Pharmaceutical Salts Properties, Selection and Use, Verlag Helvetica Chimica Acta, Zürich 2002.
• 2. Pawlak Z. and Słowiński R., Int. Trans. Opl. Res., 1, 107 (1994).
• 3.Prędki B., Słowiński R., Stefanowski J., Susmaga R. and Wilk S., Bull. Intern. Rough Sets Soc. 2, 31 (1998).
• 4. Krysiński J., Skrzypczak A., Demski G. and Prędki B., Quant. Struct.-Act. Relat., 20, 395 (2002).
• 5. Krysiński J., “Analysis of Structure-Activity Relationships of Quaternary Ammonium Compound", in Intelligent Decision Support. Handbook of Applications and Advances of Rough Set Theory., (Ed: R. Słowiński), Dordrecht, Boston, London: Kluwer Acad. Pub., pp. 119-136, 1992.
• 6. Wiktorowicz W., Krysiński J., Skrzypczak A. and Kaliszan R., STP Pharma Sci., 12, 181 (2002).
• 7. Pernak J., Pożniak R., Krejcio Z. and Skrzypczak A., Acta Polymer, 38, 299 (1987).
• 8. Bukala M., Pasternak A., Pożniak R. and Rospond W., Polimery, 20,530 (1975). CA: 84,165443 (1976).
• 9. Pernak J., Arndt A. and Poźniak R., Polymer, 39, 605 (1998).
• 10. Program ROSE2 Lite available at web site of the Laboratory of Intelligent Decision Ssa Systems, the Institute of Computing Science, Poznań University of Technology, Poznań, Poland, http://www-idss.cs.put.poznan.pl/rose/(Feb. 15, 2003).
• 11. Program ROSSETA available at web site of the Knowledge Systems Group, Dept, of CosjH and Information Science, Norwegian University of Science and Technology, Trondheim, Norway, http://www.idi.ntnu.no/~aleks/rosetta/(Feb. 15, 2003).
• 12. Grzymała-Busse J. W., “LERS a System for Learning for Examples Based on Rough Sets”, in Intielligent Decision Support. Handbook ofApplications and Advances of Rough Set Theory, (Ed: R. Słowiński), Dordrecht, Boston: Kluwer Acad. Pub., pp. 3-18, 1992.