FEIT Research Project Database

Soft matter informatics: inverse design engine for block co-polymers

Project Leader: Ellie Hajizadeh
Primary Contact: Ellie Hajizadeh (ellie.hajizadeh@unimelb.edu.au)
Keywords: artificial intelligence; computational materials science; polymeric materials; rheology
Disciplines: Chemical & Biomolecular Engineering,Mechanical Engineering

Multiblock polymers (MBPs) show great promise as a platform for synthesising materials with highly customised nanostructures. In these systems, the subtle balance of chain configurational entropy and interactions between dissimilar block chemistries emerge a rich palette of self-assembled structural motifs that may be leveraged to impart novel functional, mechanical, or optical properties to the final material. Unfortunately, extensive study of MBP self-assembly has yielded few reliable heuristics for intuitively navigating the enormous molecular design space made available by modern polymer synthesis techniques. In order to make progress, new methods must be developed that allow researchers to efficiently screen molecular designs for achieving a desired state of self-assembly.

Here, we introduce a platform for the automated discovery of tailored MBP formulations based on the Particle Swarm Optimization (PSO) method and a linear multiblock chain parametrisation that enables continuous optimisation of chain architecture. We apply the method to thin-film blends of linear ABC triblock polymers subject to lateral confinement, allowing all polymer and blend parameters to freely optimise in search of a prespecified, non-trivial target morphology. While we focus on pattern selection as a proof of principle, any computable equilibrium property can be optimised using the methods described here.

Related articles on methodologies

[1] Elnaz Hajizadeh, Shi Yu, Shihu Wang, and Ronald G. Larson, “A novel hybrid population balance—Brownian dynamics method for simulating the dynamics of polymer-bridged colloidal latex particle suspensions”, J. Rheol. 62, 235–247 (2018).

[2] Elnaz Hajizadeh, Billy Todd, Peter Daivis, Journal of Rheology, 58, 281-305 (2014)

[3] Elnaz Hajizadeh, Billy Todd, Peter Daivis, J. Chem. Phys, 142, 174911 (2015)

[4] Elnaz Hajizadeh, Billy Todd, Peter Daivis, J. Chem. Phys, 141, 194904 (2014)

[5] Guorui Zhu, Hossein Rezvantalab, Elnaz Hajizadeh, Xiaoyi Wang, Ronald G Larson, Journal of Rheology, 60, 327–343 (2016)

[6] Elnaz Hajizadeh, Ronald G Larson, Soft Matter, 13, 5942–5949 (2017)

[7] Zakiya Shireen, Elnaz Hajizadeh, Peter Daivis, Christian Brandl, Computational Materials Science, 216111824 (2023)