Equilibrium phase diagrams serve as blueprints for rational design of nanostructured materials of block copolymers, but their construction is time-consuming and requires profound expertise. Herein, by virtue of the knowledge of self-consistent field theory (SCFT), the active-learning method is developed to autonomously construct the phase diagrams of block copolymers. Without human intervention, the SCFT-assisted active-learning method can rapidly search the undetected phases and efficiently reproduce the complicated phase diagrams of diblock copolymers and multiblock terpolymers via decreasing the number of sampling points to about 20%. It is clearly demonstrated that the combined uncertainty sampling/random selection scheme in the active-learning method shows the outperformance in spite of a small amount of initial data set. This work highlights the promising integration of theoretical modeling with machine learning and represents a crucial step toward rational design of nanostructured materials.

Programmable coassembly of multicomponent nanoparticles (NPs) into heterostructures has the capability to build upon nanostructured metamaterials with enhanced complexity and diversity. However, a general understanding of how to manipulate the sequence-defined heterostructures using straightforward concepts and quantitatively predict the coassembly process remains unreached. Drawing inspiration from the synthetic concepts of molecular block copolymers is extremely beneficial to achieve controllable coassembly of NPs and access mesoscale structuring mechanisms. We herein report a general paradigm of kinetic pathway guidance for the controllable coassembly of bivalent DNA-functionalized NPs into regular block-copolymer-like heterostructures via the stepwise polymerization strategy. By quantifying the coassembly kinetics and structural statistics, it is demonstrated that the coassembly of multicomponent NPs, through directing the specific pathways of prepolymer intermediates, follows the step-growth copolymerization mechanism. Meanwhile, a quantitative model is developed to predict the growth kinetics and outcomes of heterostructures, all controlled by the designed elements of the coassembly system. Furthermore, the stepwise polymerization strategy can be generalized to build upon a great variety of regular nanopolymers with complex architectures, such as multiblock terpolymers and ladder copolymers. Our theoretical and simulation results provide fundamental insights on quantitative predictions of the coassembly kinetics and coassembled outcomes, which can aid in realizing a diverse set of supramolecular DNA materials by the rational design of kinetic pathways.

Block copolymer nanocomposites with precise organization of nanorods are promising candidates for construction of orientation-dependent materials. Realizing position- and orientation-controllable coassembly of nanorods in the nanocomposites is thermodynamically challenging due to their slow ordering kinetics and existence of long-lived defects. Regulating the kinetic pathways of a coassembly process offers a convenient alternative to approach the equilibrium configurations of nanostructured composites. Herein, we extend the computational hybrid particle/field method to probe into the coassembly behaviors of block copolymer/nanorod mixtures in the presence of zone annealing. It is found that through regulating coassembly pathways by zone annealing, the nanocomposites have the capability to coassemble into periodically defect-free nanostructures with controllable orientation of nanorods, originating from the epitaxial characteristics of zone-annealed nanocomposites. Meantime, the preferred orientation of nanorods is finely tuned by thermodynamic variables, e.g., incompatibility, aspect ratio, and concentration of nanorods. Furthermore, the minimum free-energy pathways of orientation transition obtained from the string method are used to understand the pathway selection of orientation-controllable nanorods within a nanostructured matrix. In addition, it is revealed that the end-to-end aligned nanorods along the tensile direction are able to enhance the mechanical strength of nanostructured composites. The multiscale modeling study gives insights into how to regulate coassembly pathways to access the targeted nanostructures of nanocomposites with superior mechanical properties through designing manufacture-friendly continuous processing.