Amino acids as plasticizers - II. Use of quantitative structure-property relationships to predict the behavior of monoammoniummonocarboxylate plasticizers in starch-glycerol blends
被引:17
|
作者:
Stein, TM
论文数: 0引用数: 0
h-index: 0
机构:
ARS, Biopolymer Res Unit, Natl Ctr Agr Utilizat Res, USDA, Peoria, IL 61604 USAARS, Biopolymer Res Unit, Natl Ctr Agr Utilizat Res, USDA, Peoria, IL 61604 USA
Stein, TM
[1
]
Gordon, SH
论文数: 0引用数: 0
h-index: 0
机构:
ARS, Biopolymer Res Unit, Natl Ctr Agr Utilizat Res, USDA, Peoria, IL 61604 USAARS, Biopolymer Res Unit, Natl Ctr Agr Utilizat Res, USDA, Peoria, IL 61604 USA
Gordon, SH
[1
]
Greene, RV
论文数: 0引用数: 0
h-index: 0
机构:
ARS, Biopolymer Res Unit, Natl Ctr Agr Utilizat Res, USDA, Peoria, IL 61604 USAARS, Biopolymer Res Unit, Natl Ctr Agr Utilizat Res, USDA, Peoria, IL 61604 USA
Greene, RV
[1
]
机构:
[1] ARS, Biopolymer Res Unit, Natl Ctr Agr Utilizat Res, USDA, Peoria, IL 61604 USA
Twenty natural and synthetic amino acids (5 cyclic and 15 acyclic) were blended with a standard starch-glycerol mixture and extruded as ribbons. Glycerol was present in all blends as a co-plasticizer, permitting observation of both increase and decrease in sample flexibility resulting from amino acids. Mechanical testing of the ribbons revealed that amino acids had a dramatic effect on the percent elongation at break (%E) which varied from 13% to 379%. Tensile strength (TS) of the ribbons also varied considerably from 0.96 to 6.29 MPa. In general, samples displaying the greatest elongation had the lowest TS. FT-Raman spectroscopy indicated that the amino acids in these blends existed predominately as zwitterions. Computational models of all test compounds were therefore generated as zwitterions, and the global minimum-energy conformation of each test compound was used as the basis for calculating molecular descriptors. Surprisingly, only two (sum of absolute values of atomic charges and maximum positive charge on the molecule) of the 17 descriptors evaluated were needed to generate predictive quantitative structure-property relationships (QSPR) for both %E and TS data. By calculating these two descriptors from computer models, %E and TS can be predicted for blends with unknown or new monoamine-monocarboxyl compounds. (C) 1999 Elsevier Science Ltd. All rights reserved.