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Field-based simulations can be challenging in multi-component polymer systems and are highly sensitive to the choice of relaxation coefficients (λ) used in the field update algorithms. Judiciously chosen relaxation coefficients are critical for both the stability and convergence of field-based simulations, yet their selection is challenging when the number of unique chemical species in the system is large. In this work, we develop a new method to automatically and efficiently locate optimal relaxation coefficients in systems with large numbers of species. We begin by analyzing the effects of relaxation coefficients in two- and three-species systems and demonstrate that regions of high-performance are both narrow and system-specific. Based on these findings, we next develop a method based on Bayesian optimization that automatically locates relaxation coefficients that are stable and exhibit good performance. We demonstrate that our method is considerably faster than naive search methods and becomes particularly efficient as the system complexity increases. This work demonstrates that Bayesian optimization can be used to stabilize and accelerate field-based simulations that contain many different chemical species. 

This study investigates the role of chain architecture and block asymmetry on the morphology of AB2 miktoarm star block copolymers (AB2 BCPs) in the strongly segregated regime using molecular dynamics simulations. Notably, the cylindrical morphology in AB2 BCPs persists across a broad compositional range, extending close to fA ≈ 0.5, in agreement with both theoretical and experimental findings. The lamellar morphology observed up to fA ≈ 0.8 matches predictions; however, beyond this point, AB2 BCPs continue to exhibit lamellar structures (disk-like micelles), deviating from the expected transitions to cylindrical or spherical morphologies. This behavior, corroborated by dissipative particle dynamics simulations, is attributed to the B arms’ preference to occupying the outer regions of curved interfaces, which hinders the formation of cylindrical or spherical morphologies. Furthermore, domain spacing results exhibit remarkable agreement with strong-stretching theory (SST) across different morphologies, reinforcing the predictive power of SST. Finally, shape parameter analysis, including metrics like asphericity and acylindricity, underscores the significant impact of chain architecture on these morphological transitions. These findings provide molecular-level insights into how chain architecture and block asymmetry dictate phase behavior and morphological stability in linear and miktoarm BCPs. 

The self-assembly of block polymers into well-ordered nanostructures underpins their utility across fundamental and applied polymer science, yet only a handful of equilibrium morphologies are known with the simplest AB-type materials. Here, we report the discovery of the A15 sphere phase in single-component diblock copolymer melts comprising poly(dodecyl acrylate)− block −poly(lactide). A systematic exploration of phase space revealed that A15 forms across a substantial range of minority lactide block volume fractions ( f L = 0.25 − 0.33) situated between the σ-sphere phase and hexagonally close-packed cylinders. Self-consistent field theory rationalizes the thermodynamic stability of A15 as a consequence of extreme conformational asymmetry. The experimentally observed A15−disorder phase transition is not captured using mean-field approximations but instead arises due to composition fluctuations as evidenced by fully fluctuating field-theoretic simulations. This combination of experiments and field-theoretic simulations provides rational design rules that can be used to generate unique, polymer-based mesophases through self-assembly.