Prediction of real tensile properties using extrapolations
Ranking plasticizers for polymers with atomistic simulations: PVT, mechanical properties, and the role of hydrogen bonding in thermoplastic starch ACS Applied Polymer Materials , 2 ( 5 ) ( 2025 ) , pp. 2016 - 2026
Ranking Plasticizers for Polymers with Atomistic Simulations
DOI: 10.1021/acsapm.0c00191 Corpus ID: 216476927; Ranking Plasticizers for Polymers with Atomistic Simulations: PVT, Mechanical Properties, and the Role of Hydrogen Bonding in Thermoplastic Starch
Ranking Plasticizers for Polymers With Atomistic - Amanote
Ranking Plasticizers for Polymers With Atomistic Simulations; PVT, Mechanical Properties and the Role of Hydrogen Bonding in Thermoplastic Starch ACS Applied Polymer Materials doi 10.1021/acsapm.0c00191
Prediction of real tensile properties using extrapolations
However, molecular dynamics (MD) simulation is a useful tool for investigating plasticization mechanisms in detail (through e.g. hydrogen bond patterns), and ranking plasticizers in a given...
Ranking Plasticizers for Polymers with Atomistic Simulations
The results indicate that molecular simulations can be used to find the optimal plasticizer among a set of candidates or to design/identify better plasticizers in a complex polymer system. Glycerol was the most efficient of the six plasticizers, explained by it forming the least amount of hydrogen bonds, having the shortest hydrogen bond
- Can atomistic simulation predict the plasticizer efficiency of polar hydrogen-bonding polymers?
- This study showed that atomistic (molecular dynamics) simulation is a useful technique for predicting the plasticizer efficiency and the plasticizer concentration needed to obtain sufficient plasticization in polar hydrogen-bonding polymer systems. It has now been shown for two very different polar polymers (starch [ 28] and protein).
- Can molecular simulations be used to find the optimal plasticizer?
- Three polyols (glycerol, sorbitol, and xylitol), two ethanolamines (tri- and diethanolamine), and glucose were investigated. The results indicate that molecular simulations can be used to find the optimal plasticizer among a set of candidates or to design/identify better plasticizers in a complex polymer system.
- Can PVT data from MD simulations be used for plasticizer design?
- Hence, with PVT data from MD simulations it is possible to rank different plasticizer candidates in terms of their plasticizer efficiency (depression in Tg). This also indicates that PVT data from simulations can be used for designing new and better plasticizers for a given polymer system.
- Which plasticizer is the most efficient?
- Glycerol was the most efficient of the six plasticizers, explained by it forming the least amount of hydrogen bonds, having the shortest hydrogen bond lifetimes and low molecular rigidity. Hence, not only was it possible to rank plasticizers, the ranking results could also be explained by the simulations.
- Are glycerol and ethanolamine more effective plasticizers?
- When the mechanical properties were examined (elastic modulus and tensile strength), both the simulations and the experiments ranked glycerol and the two ethanolamines as more effective plasticizers than the other three (glucose, sorbitol, and xylitol).
- Which Ethanolamine is a good plasticizer for polar polymers?
- Two ethanolamines (tri- and diethanolamine) were also included since they are known to be good plasticizers for polar polymers. (1,26,27) Triethanolamine was chosen to reveal the effects of using a “nonlinear” star-shaped molecule with three hydroxyl groups on the plasticization efficiency.
