Monte Carlo Study of Symmetric Diblock Copolymers in Nonselective Solvents

1994 ◽  
Vol 27 (5) ◽  
pp. 1160-1165 ◽  
Author(s):  
Luis A. Molina ◽  
Antonio Lopez Rodriguez ◽  
Juan J. Freire
1995 ◽  
Vol 60 (5) ◽  
pp. 736-750
Author(s):  
Tereza Vrbová ◽  
Zuzana Limpouchová ◽  
Karel Procházka

Conformations of symmetric diblock copolymers AB in dilute solutions in good and selective solvents were studied by Monte Carlo simulations on a simple cubic lattice. Individual chain conformations were created by the self-avoiding walk algorithm. A modified thermal equilibration of the system based on the Metropolis acceptance criteria for energies of the system and the Rosenbluth weights of chain conformations was applied. Interactions of the nearest neighbours (r = l), where l is the lattice distance, and interactions for r = sqrt(2l) and r = sqrt(3l) were considered. Various structural characteristics of the whole copolymer chain and individual blocks A, B were obtained in the course of computer simulations. It was found that a moderate contraction of the worse soluble block B and a certain segregation of blocks occurs in dilute solutions in selective solvents for the block A, however neither that contraction, nor the segregation of blocks are extensive.


1995 ◽  
Vol 28 (8) ◽  
pp. 2705-2713 ◽  
Author(s):  
Luis A. Molina ◽  
Juan J. Freire

1993 ◽  
Vol 3 (12) ◽  
pp. 2387-2395 ◽  
Author(s):  
Kevin E. Bassler ◽  
Monica Olvera de la Cruz

Methodology ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Holger Steinmetz

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.


2011 ◽  
Author(s):  
Patrick J. Rosopa ◽  
Amber N. Schroeder ◽  
Jessica Doll

1993 ◽  
Vol 3 (9) ◽  
pp. 1719-1728
Author(s):  
P. Dollfus ◽  
P. Hesto ◽  
S. Galdin ◽  
C. Brisset

1987 ◽  
Vol 48 (C5) ◽  
pp. C5-199-C5-202
Author(s):  
T. MIYASAKI ◽  
K. AIZAWA ◽  
H. AOKI ◽  
C. ITOH ◽  
M. OKAZAKI

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