Programming temporal shapeshifting

Shapeshifting enables a wide range of engineering and biomedical applications, but until now transformations have required external triggers. This prerequisite limits viability in closed or inert systems and puts forward the challenge of developing materials with intrinsically encoded shape evolution. Herein we demonstrate programmable shape-memory materials that perform a sequence of encoded actuations under constant environment conditions without using an external trigger. We employ dual network hydrogels: in the first network, covalent crosslinks are introduced for elastic energy storage, and in the second one, temporary hydrogen-bonds regulate the energy release rate. Through strain-induced and time-dependent reorganization of the reversible hydrogen-bonds, this dual network allows for encoding both the rate and pathway of shape transformations on timescales from seconds to hours. This generic mechanism for programming trigger-free shapeshifting opens new ways to design autonomous actuators, drug-release systems and active implants

Chameleon-like elastomers with molecularly encoded strain-adaptive stiffening and coloration

Active camouflage is widely recognized as a soft-tissue feature, and yet the ability to integrate adaptive coloration and tissuelike mechanical properties into synthetic materials remains elusive. We provide a solution to this problem by uniting these functions in moldable elastomers through the self-assembly of linear-bottlebrush-linear triblock copolymers. Microphase separation of the architecturally distinct blocks results in physically cross-linked networks that display vibrant color, extreme softness, and intense strain stiffening on par with that of skin tissue. Each of these functional properties is regulated by the structure of one macromolecule, without the need for chemical cross-linking or additives. These materials remain stable under conditions characteristic of internal bodily environments and under ambient conditions, neither swelling in bodily fluids nor drying when exposed to air

Universal Coatings Based on Zwitterionic–Dopamine Copolymer Microgels

Multifunctional coatings that adhere to chemically distinct substrates are vital in many industries, including automotive, aerospace, shipbuilding, construction, petrochemical, biomedical, and pharmaceutical. We design well-defined, nearly monodisperse microgels that integrate hydrophobic dopamine methacrylamide monomers and hydrophilic zwitterionic monomers. The dopamine functionalities operate as both intraparticle cross-linkers and interfacial binders, respectively providing mechanical strength of the coatings and their strong adhesion to different substrates. In tandem, the zwitterionic moieties enable surface hydration to empower antifouling and antifogging properties. Drop-casting of microgel suspensions in ambient as well as humid environments facilitates rapid film formation and tunable roughness through regulation of cross-linking density and deposition conditions

Universal Coatings Based on Zwitterionic–Dopamine Copolymer Microgels

Multifunctional coatings that adhere to chemically distinct substrates are vital in many industries, including automotive, aerospace, shipbuilding, construction, petrochemical, biomedical, and pharmaceutical. We design well-defined, nearly monodisperse microgels that integrate hydrophobic dopamine methacrylamide monomers and hydrophilic zwitterionic monomers. The dopamine functionalities operate as both intraparticle cross-linkers and interfacial binders, respectively providing mechanical strength of the coatings and their strong adhesion to different substrates. In tandem, the zwitterionic moieties enable surface hydration to empower antifouling and antifogging properties. Drop-casting of microgel suspensions in ambient as well as humid environments facilitates rapid film formation and tunable roughness through regulation of cross-linking density and deposition conditions

Dynamics of Bottlebrush Networks

The deformation dynamics of bottlebrush networks in a melt state is studied using a combination of theoretical, computational, and experimental techniques. Three main molecular relaxation processes are identified in these systems: (i) relaxation of the side chains, (ii) relaxation of the bottlebrush backbones on length scales shorter than the bottlebrush Kuhn length (<i>b</i>_K), and (iii) relaxation of the bottlebrush network strands between cross-links. The relaxation of side chains having a degree of polymerization (DP), <i>n</i>_sc, dominates the network dynamics on the time scales τ₀ < <i>t</i> ≤ τ_sc, where τ₀ and τ_sc ≈ τ₀(<i>n</i>_sc + 1)² are the characteristic relaxation times of monomeric units and side chains, respectively. In this time interval, the shear modulus at small deformations decays with time as <i>G</i>₀^BB(<i>t</i>) ∼ <i>t</i>^–1/2. On time scales <i>t</i> > τ_sc, bottlebrush elastomers behave as networks of filaments with a shear modulus <i>G</i>₀^BB(<i>t</i>) ∼ (<i>n</i>_sc + 1)^−1/4<i>t</i>^–1/2. Finally, the response of the bottlebrush networks becomes time independent at times scales longer than the Rouse time of the bottlebrush network strands, τ_BB ≈ τ₀<i>N</i>²(<i>n</i>_sc + 1)^3/2, where <i>N</i> is DP of the bottlebrush backbone between cross-links. In this time interval, the network shear modulus depends on the network molecular parameters as <i>G</i>₀^BB(<i>t</i>) ∼ (<i>n</i>_sc + 1)⁻¹<i>N</i>^–1. Analysis of the simulation data shows that the stress evolution in the bottlebrush networks during constant strain-rate deformation can be described by a universal function. The developed scaling model is consistent with the dynamic response of a series of poly­(dimethyl­siloxane) bottlebrush networks (<i>n</i>_sc = 14 and <i>N</i> = 50, 70, 100, 200) measured experimentally

Strained Bottlebrushes in Super-Soft Physical Networks

International audienceABA triblock copolymers composed of a poly(dimethylsiloxane) (PDMS) bottlebrush central block and linear poly(methyl methacrylate) (PMMA) terminal blocks self-assemble into a physical network of PDMS bottlebrush strands connected by PMMA spherical domains. A combination of small- and ultrasmall-angle X-ray scattering techniques was used to concurrently examine dimensions of PMMA spherical domains and PDMS bottlebrush strands both in the bulk and at the PMMA–PDMS interface. In agreement with scaling model predictions, the degrees of polymerization of the bottlebrush backbone (nbb) and PMMA block (nA) correlate with the measured PMMA domain size and area per molecule at the PMMA–PDMS interface as DA ∝ (nbbnA)1/3 and S ∝ nA2/3nbb–1/3, respectively. In the bulk, bottlebrush strands are extended due to steric repulsion between the side chains and unfavorable interactions between the different blocks. At the PMMA–PDMS interface with large curvature, packing constraints require additional bottlebrush backbone extension and alignment of side chains along the backbone in the direction perpendicular to the interface

Sticky Architecture: Encoding Pressure Sensitive Adhesion in Polymer Networks

Pressure sensitive adhesives (PSAs) are ubiquitous materials within a spectrum that span from office supplies to biomedical devices. Currently, the ability of PSAs to meet the needs of these diverse applications relies on trial-and-error mixing of assorted chemicals and polymers, which inherently entails property imprecision and variance over time due to component migration and leaching. Herein, we develop a precise additive-free PSA design platform that predictably leverages polymer network architecture to empower comprehensive control over adhesive performance. Utilizing the chemical universality of brush-like elastomers, we encode work of adhesion ranging 5 orders of magnitude with a single polymer chemistry by coordinating brush architectural parameters–side chain length and grafting density. Lessons from this design-by-architecture approach are essential for future implementation of AI machinery in molecular engineering of both cured and thermoplastic PSAs incorporated into everyday use

Sticky Architecture: Encoding Pressure Sensitive Adhesion in Polymer Networks

Pressure sensitive adhesives (PSAs) are ubiquitous materials within a spectrum that span from office supplies to biomedical devices. Currently, the ability of PSAs to meet the needs of these diverse applications relies on trial-and-error mixing of assorted chemicals and polymers, which inherently entails property imprecision and variance over time due to component migration and leaching. Herein, we develop a precise additive-free PSA design platform that predictably leverages polymer network architecture to empower comprehensive control over adhesive performance. Utilizing the chemical universality of brush-like elastomers, we encode work of adhesion ranging 5 orders of magnitude with a single polymer chemistry by coordinating brush architectural parameters–side chain length and grafting density. Lessons from this design-by-architecture approach are essential for future implementation of AI machinery in molecular engineering of both cured and thermoplastic PSAs incorporated into everyday use

Sticky Architecture: Encoding Pressure Sensitive Adhesion in Polymer Networks

Pressure sensitive adhesives (PSAs) are ubiquitous materials within a spectrum that span from office supplies to biomedical devices. Currently, the ability of PSAs to meet the needs of these diverse applications relies on trial-and-error mixing of assorted chemicals and polymers, which inherently entails property imprecision and variance over time due to component migration and leaching. Herein, we develop a precise additive-free PSA design platform that predictably leverages polymer network architecture to empower comprehensive control over adhesive performance. Utilizing the chemical universality of brush-like elastomers, we encode work of adhesion ranging 5 orders of magnitude with a single polymer chemistry by coordinating brush architectural parameters–side chain length and grafting density. Lessons from this design-by-architecture approach are essential for future implementation of AI machinery in molecular engineering of both cured and thermoplastic PSAs incorporated into everyday use

Sticky Architecture: Encoding Pressure Sensitive Adhesion in Polymer Networks

Pressure sensitive adhesives (PSAs) are ubiquitous materials within a spectrum that span from office supplies to biomedical devices. Currently, the ability of PSAs to meet the needs of these diverse applications relies on trial-and-error mixing of assorted chemicals and polymers, which inherently entails property imprecision and variance over time due to component migration and leaching. Herein, we develop a precise additive-free PSA design platform that predictably leverages polymer network architecture to empower comprehensive control over adhesive performance. Utilizing the chemical universality of brush-like elastomers, we encode work of adhesion ranging 5 orders of magnitude with a single polymer chemistry by coordinating brush architectural parameters–side chain length and grafting density. Lessons from this design-by-architecture approach are essential for future implementation of AI machinery in molecular engineering of both cured and thermoplastic PSAs incorporated into everyday use