Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Abstract

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature's own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from highinformation content blocks with a focus on stimuli-responsive and "smart" architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

Computational Reverse-Engineering Analysis for Scattering Experiments for Form Factor and Structure Factor Determination (“P(q) and S(q) CREASE”)

“…As CREASE outputs a representative 3D structure of the material and average pair correlation functions between various species in the system, one could conduct additional calculations using these outputs to either understand the interactions in the system that drive that structure or predict a physical property arising from that structure. For example, one could apply relevant domain expertise to elucidate the interactions (or family of interactions) that result in the CREASE-produced real-space spatial arrangement and (averaged) pairwise radial distribution functions. , This could be done using molecular dynamics simulations starting with an appropriate physical representation of the primary particles and an initial guess of pairwise interaction potentials of the particles in the system, followed by optimization approaches ( e.g ., iterative Boltzmann inversion) to identify the interaction potentials that would provide the same radial distribution functions as CREASE outputs. , For structures formed from non-equilibrium processing, identifying the pairwise interactions will be more difficult; however, alternative approaches exist. , …”

“…56,57 For structures formed from non-equilibrium processing, identifying the pairwise interac-tions will be more difficult; however, alternative approaches exist. 56,57 In Sections 2.1 and 2.2, we describe how we adapted the previously developed S(q) CREASE 52 into this "P(q) and S(q) CREASE" to simultaneously solve for the P(q) and S(q) for core−shell type particle solutions. Even though this manuscript is focused on core−shell type particles, to facilitate the application of the presented method to other systems, in SI Section S1, we provide some general guidelines for the prospective user of "P(q) and S(q) CREASE" to consider when they start using this method for their systems.…”

A multi-stimuli-responsive metallosupramolecular gel based on pillararene hierarchical assembly

“…The synthetic procedures for the double-armed pillar [5]arene host SHP5 and the ditopic guest molecule DSPy are provided in the ESI (Schemes S1 and S2 †). All intermediates and target compounds have been fully characterized by 1 H NMR, 13 C NMR, and electrospray ionization mass spectrometry (Fig. S1-S19, ESI †).…”

“…[9][10][11] The integration of hierarchical orthogonal noncovalent interactions is required to endow supramolecular assemblies with tunable topologies, desirable properties, and particular functions. [12][13][14] Moreover, owing to their excellent dynamic reversibility and rich stimulus responsiveness, multi-stimuli responsive supramolecular polymers have been widely used in various fields, including materials science, biomedical research, and environmental sensing. [15][16][17][18] Metallosupramolecular polymer gels, 19 which form through macrocycle-based host-guest assembly favored by the cooperative effect of metal ion coordination and other multiple noncovalent interactions, play a diverse role in the construction of stimuli-responsive supramolecular materials owing to their good processability, excellent adaptive features, high feasibility, stimuli responsiveness, and the metal ions' attractive optical, magnetic, redox, and electronic properties.…”

“…9–11 The integration of hierarchical orthogonal noncovalent interactions is required to endow supramolecular assemblies with tunable topologies, desirable properties, and particular functions. 12–14 Moreover, owing to their excellent dynamic reversibility and rich stimulus responsiveness, multi-stimuli responsive supramolecular polymers have been widely used in various fields, including materials science, biomedical research, and environmental sensing. 15–18…”