Synthesis of Polymeric Janus Superstructures via a Facile Synthesis Method

Lim, Yi Guang Jerome; Low, Jessalyn; Loo, Say Chye Joachim

doi:10.1002/marc.202000140

Cited by 2 publications

(1 citation statement)

References 35 publications

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“…Although the SC model gives relatively acceptable results, it is associated with some complexities affecting its precision. The model’s major drawback is neglecting the role of the blend composition by ignoring the interfacial surface area between the two polymer phases. , In order to consider the role of blend composition,, instead of using solid-polymer data, the surface tension (ST) data for each polymer solution must be calculated at the phase-separation threshold using the pendant drop method . Although this technique improves the predictability of the SC model, it can be costly and time-consuming as it requires measurements of interfacial tension for each mixture.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Prediction of Janus/Core–Shell Morphology in Polymer Particles: A Machine-Learning Approach

2023

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The majority of research on Janus particles prepared by solvent evaporation-induced phase separation technique uses models based on interfacial tension or free energy to predict Janus/core−shell morphology. Data-driven predictions, in contrast, utilize multiple samples to identify patterns and outliers. Using machine-learning algorithms and explainable artificial intelligence (XAI) analysis, we developed a model based on a 200-instance data set to predict particle morphology. As model features, simplified molecular input line entry system syntax identifies explanatory variables, including cohesive energy density, molar volume, the Flory−Huggins interaction parameter of polymers, and the solvent solubility parameter. Our most accurate ensemble classifiers predict morphology with an accuracy of 90%. In addition, we employ innovative XAI tools to interpret system behavior, suggesting phase-separated morphology to be most affected by solvent solubility, polymer cohesive energy difference, and blend composition. While polymers with cohesive energy densities above a certain threshold favor the core−shell structure, systems with weak intermolecular interactions favor the Janus structure. The correlation between molar volume and morphology suggests that increasing the size of polymer repeating units favors Janus particles. Additionally, the Janus structure is preferred when the Flory−Huggins interaction parameter exceeds 0.4. XAI analysis introduces feature values that generate the thermodynamically low driving force of phase separation, resulting in kinetically stable morphologies as opposed to thermodynamically stable ones. The Shapley plots of this study also reveal novel methods for creating Janus or core−shell particles based on solvent evaporation-induced phase separation by selecting feature values that strongly favor a given morphology.

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Section: Introductionmentioning

confidence: 99%

Data-Driven Prediction of Janus/Core–Shell Morphology in Polymer Particles: A Machine-Learning Approach

2023

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Electroinduced Reconfiguration of Complex Emulsions for Fabrication of Polymer Particles with Tunable Morphology

Guo

Fang

Jia

et al. 2021

Macromol. Rapid Commun.

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Continuous morphological control of anisotropic particles is always an important challenge in the field of materials. In this study, a new strategy for continuous fabrication of polymer particles with various morphologies induced by electricity is reported using complex emulsions as template. A synthetic electro‐responsive surfactant containing ferrocene group is used to prepare complex emulsions, which contain a polymerizable monomer as inner phase. With the increasing time of electrical stimulation on the complex emulsions, hollow, hemispherical, mushroom‐like, and spherical particles are constructed successively after photopolymerization. The Marangoni effect caused by the heterogeneity in the interfacial tension at the droplet surface is the reason for the reconfigurable morphology of the complex emulsion. The controllable complex emulsions by electricity present a versatile platform for constructing fine control of the microstructure and shape anisotropy of particles having customized shapes and functionalities, opening a new possibility for designing sophisticated architectures.

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Synthesis of Polymeric Janus Superstructures via a Facile Synthesis Method

Cited by 2 publications

References 35 publications

Data-Driven Prediction of Janus/Core–Shell Morphology in Polymer Particles: A Machine-Learning Approach

Data-Driven Prediction of Janus/Core–Shell Morphology in Polymer Particles: A Machine-Learning Approach

Electroinduced Reconfiguration of Complex Emulsions for Fabrication of Polymer Particles with Tunable Morphology

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