Title: Molecular dynamics simulations for glass transition temperature predictions of polyhydroxyalkanoate biopolymers

Abstract

Polyhydroxyalkanoates (PHAs) represent an emerging class of biosynthetic and biodegradable polyesters that exhibit considerable potential to replace petroleum-based plastics towards a sustainable future. Despite the promise, general structure–property mappings within this class of polymers remain largely unexplored. An efficient exploration of this vast chemical space calls for the development and validation of predictive methods for accurate estimation of a diverse range of properties for PHA-based polymers. Towards this aim, we present and validate in this work the results of our molecular dynamics (MD) simulation based approach aimed at predicting glass transition temperatures (T_g) of PHA-based polymers. Since generally available and widely used polymer forcefields exhibit a relatively poor performance for T_g predictions, we have developed a new forcefield by modifying the polymer consistent force field (PCFF) via refining a selected set of torsion potentials of the polymer backbone using accurate density functional theory (DFT) computations. After carefully assessing the dependence of critical simulation parameters, such as, polymer chain length, number of polymer chains, supercell size, and thermal quenching rate used in the simulation, the applicability and transferability of the modified PCFF (mPCFF) is demonstrated by directly comparing the computed T_g predictions of various polymers with different chemistries, polymer side chainmore » lengths and functional groups forming the polymer side chains against the respective experimentally measured values. Furthermore, the transport properties such as self-diffusion coefficient and viscosity are computationally determined and their well-known correlation with the target properties is demonstrated. Lastly, we have employed the developed approach to predict T_g values for a number of yet-to-be-synthesized PHA-based polymers with a diverse set of functional groups in the polymer side chains. The results are further rationalized by correlating the predicted T_g values with the inter-chain H-bond formation tendencies of the different side chain functional groups. This work represents an important first step towards computationally guided design of PHA-based functional polymers and opens up new directions for a systematic investigation of composition- and configuration-dependent structure–property relationships in more complex binary and ternary copolymer systems.« less

Authors:

Bejagam, Karteek Kumar  ^[1];

• Search DOE PAGES for author "Bejagam, Karteek Kumar"
• Search DOE PAGES for ORCID "0000-0002-8660-9946"

Iverson, Carl Nicholas  ^[1];

• Search DOE PAGES for author "Iverson, Carl Nicholas"
• Search DOE PAGES for ORCID "0000-0002-9854-0026"

Marrone, Babetta Louise  ^[1];

• Search DOE PAGES for author "Marrone, Babetta Louise"
• Search DOE PAGES for ORCID "0000-0001-5002-1289"

Pilania, Ghanshyam  ^[1]

• Search DOE PAGES for author "Pilania, Ghanshyam"
• Search DOE PAGES for ORCID "0000-0003-4460-1572"

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+ Show Author Affiliations

1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Publication Date:

Mon Jul 20 00:00:00 EDT 2020

Research Org.:

Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Org.:

USDOE National Nuclear Security Administration (NNSA); USDOE Laboratory Directed Research and Development (LDRD) Program

OSTI Identifier:

1711395

Alternate Identifier(s):

OSTI ID: 1646927

Report Number(s):

LA-UR-20-23226
Journal ID: ISSN 1463-9076

Grant/Contract Number:  

89233218CNA000001; 20190001DR

Resource Type:

Accepted Manuscript

Journal Name:

Physical Chemistry Chemical Physics. PCCP

Additional Journal Information:

Journal Volume: 22; Journal Issue: 32; Journal ID: ISSN 1463-9076

Publisher:

Royal Society of Chemistry

Country of Publication:

United States

Language:

English

Subject:

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Biopolymers; Molecular Dynamics