Prediction on the configuration of CSMA–PCL amphiphilic copolymers by coarse-grained molecular dynamics simulations
碩士 === 國立中山大學 === 機械與機電工程學系研究所 === 102 === In this study, we use molecular dynamics and coarse-grained molecular dynamics simulations which are used to analyze the properties of the conformations of micelle, and also compare with the experiment results. The probability distributions from the fully a...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2014
|
Online Access: | http://ndltd.ncl.edu.tw/handle/5u94sg |
id |
ndltd-TW-102NSYS5490053 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-102NSYS54900532018-05-09T05:10:29Z http://ndltd.ncl.edu.tw/handle/5u94sg Prediction on the configuration of CSMA–PCL amphiphilic copolymers by coarse-grained molecular dynamics simulations 利用粗殼粒子動力學預測兩性共聚物硫酸軟骨素接枝聚己內酯之結構 Chien-Chia Chen 陳建嘉 碩士 國立中山大學 機械與機電工程學系研究所 102 In this study, we use molecular dynamics and coarse-grained molecular dynamics simulations which are used to analyze the properties of the conformations of micelle, and also compare with the experiment results. The probability distributions from the fully atomic simulation are transferred by iterative Boltzmann inversion method to obtain the required potential parameters, and then conduct the simulation of the CS-PCL (Chondroitin sulfate graft Polycaprolactone) copolymers self-assembling in the water with different molecular grafting weight in aqueous. This study can help engineers clarify the characteristics and phenomena of carrier of drug molecules, as well as contributing to the application of recent technology. Shin-Pon Ju 朱訓鵬 2014 學位論文 ; thesis 79 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 國立中山大學 === 機械與機電工程學系研究所 === 102 === In this study, we use molecular dynamics and coarse-grained molecular dynamics simulations which are used to analyze the properties of the conformations of micelle, and also compare with the experiment results. The probability distributions from the fully atomic simulation are transferred by iterative Boltzmann inversion method to obtain the required potential parameters, and then conduct the simulation of the CS-PCL (Chondroitin sulfate graft Polycaprolactone) copolymers self-assembling in the water with different molecular grafting weight in aqueous. This study can help engineers clarify the characteristics and phenomena of carrier of drug molecules, as well as contributing to the application of recent technology.
|
author2 |
Shin-Pon Ju |
author_facet |
Shin-Pon Ju Chien-Chia Chen 陳建嘉 |
author |
Chien-Chia Chen 陳建嘉 |
spellingShingle |
Chien-Chia Chen 陳建嘉 Prediction on the configuration of CSMA–PCL amphiphilic copolymers by coarse-grained molecular dynamics simulations |
author_sort |
Chien-Chia Chen |
title |
Prediction on the configuration of CSMA–PCL amphiphilic copolymers by coarse-grained molecular dynamics simulations |
title_short |
Prediction on the configuration of CSMA–PCL amphiphilic copolymers by coarse-grained molecular dynamics simulations |
title_full |
Prediction on the configuration of CSMA–PCL amphiphilic copolymers by coarse-grained molecular dynamics simulations |
title_fullStr |
Prediction on the configuration of CSMA–PCL amphiphilic copolymers by coarse-grained molecular dynamics simulations |
title_full_unstemmed |
Prediction on the configuration of CSMA–PCL amphiphilic copolymers by coarse-grained molecular dynamics simulations |
title_sort |
prediction on the configuration of csma–pcl amphiphilic copolymers by coarse-grained molecular dynamics simulations |
publishDate |
2014 |
url |
http://ndltd.ncl.edu.tw/handle/5u94sg |
work_keys_str_mv |
AT chienchiachen predictionontheconfigurationofcsmapclamphiphiliccopolymersbycoarsegrainedmoleculardynamicssimulations AT chénjiànjiā predictionontheconfigurationofcsmapclamphiphiliccopolymersbycoarsegrainedmoleculardynamicssimulations AT chienchiachen lìyòngcūkélìzidònglìxuéyùcèliǎngxìnggòngjùwùliúsuānruǎngǔsùjiēzhījùjǐnèizhǐzhījiégòu AT chénjiànjiā lìyòngcūkélìzidònglìxuéyùcèliǎngxìnggòngjùwùliúsuānruǎngǔsùjiēzhījùjǐnèizhǐzhījiégòu |
_version_ |
1718635108408229888 |