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1. Molecular understanding for large deformations of soft bottlebrush polymer networks

   https://doi.org/10.1039/D0SM00759E  

   Cai, Li-Heng ( July 2020 , Soft Matter)

   null (Ed.)

   Networks formed by crosslinking bottlebrush polymers are a class of soft materials with stiffnesses matching that of ‘watery’ hydrogels and biological tissues but contain no solvents. Because of their extreme softness, bottlebrush polymer networks are often subject to large deformations. However, it is poorly understood how molecular architecture determines the extensibility of the networks. Using a combination of experimental and theoretical approaches, we discover that the yield strain γ y of the network equals the ratio of the contour length L max to the end-to-end distance R of the bottlebrush between two neighboring crosslinks: γ y = L max / R − 1. This relation suggests two regimes: (1) for stiff bottlebrush polymers, γ y is inversely proportional to the network shear modulus G , γ y ∼ G −1 , which represents a previously unrecognized regime; (2) for flexible bottlebrush polymers, γ y ∼ G −1/2 , which recovers the behavior of conventional polymer networks. Our findings provide a new molecular understanding of the nonlinear mechanics for soft bottlebrush polymer networks. 

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2. Adaptive Magnetoactive Soft Composites for Modular and Reconfigurable Actuators

   https://doi.org/10.1002/adfm.202215248  

   Zhang, Zenghao ; Heron, John T. ; Pena‐Francesch, Abdon ( March 2023 , Advanced Functional Materials)

   Magnetoactive soft materials, typically composed of magnetic particles dispersed in a soft polymer matrix, are finding many applications in soft robotics due to their reversible and remote shape transformations under magnetic fields. To achieve complex shape transformations, anisotropic, and heterogeneous magnetization profiles must be programmed in the material. However, once programmed and assembled, magnetic soft actuators cannot be easily reconfigured, repurposed, or repaired, which limits their application, their durability, and versatility in their design. Here, magnetoactive soft composites are developed from squid‐derived biopolymers and NdFeB microparticles with tunable ferromagnetic and thermomechanical properties. By leveraging reversible crosslinking nanostructures in the biopolymer matrix, a healing‐assisted assembly process is developed that allows for on‐demand reconfiguration and magnetic reprogramming of magnetoactive composites. This concept in multi‐material modular actuators is demonstrated with programmable deformation modes, self‐healing properties to recover their function after mechanical damage, and shape‐memory behavior to lock in their preferred configuration and un‐actuated catch states. These dynamic magnetic soft composites can enable the modular design and assembly of new types of magnetic actuators, not only eliminating device vulnerabilities through healing and repair but also by providing adaptive mechanisms to reconfigure their function on demand.

    

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3. Bioinspired cellular sheath-core electrospun non-woven mesh

   https://doi.org/10.1007/s42247-019-00043-7  

   Rizvi, H.R. ; D’Souza, N. ; Ayre, B. ; Ramesh, D. ( January 2019 , Emergent materials)

   Fibers are valuable to biomedical applications. Used as sutures or meshes, there is an increased dual need to provide functionality such as drug delivery. Porosity represents a high surface area to volume architecture. Coaxial fibers with porous and non-porous layers offer a new design framework for fiber design that can resolve dual needs of mechanical robustness with transport phenomena. Using preferential solubility of a polymer in supercritical CO2, we develop a new architecture using biocompatible polymers based on porous core-sheath fiber fabrication technique. Polycaprolactone was selected as the CO2 miscible phase and Poly(butyrate adipate terephthalate)(PBAT) as the immiscible phase. The mechanical performance of the fibers was investigated using quasi static and dynamic loading. SEM images indicate no physical detachment of the two polymer surface after CO2 exposure indicating a successful amalgamation of polymers at the boundary of core and sheath. PCL as a sheath and as a core showed an increase of 650% and 468% in tensile strength compared to pristine PCL and PBAT. Introduction of porosity on the surface of coaxial fiber fPCL(cPBAT) further enhanced the yield strength increases by 40%. Dynamic mechanical analysis was used to analyze the viscoelastic properties of the fibers. The storage and loss modulus for coaxial fibers shows superior modulus throughout the glassy, glass transition and rubbery region as compared to the pristine PCL and PBAT, showing enhancement in both the elastic and viscous response of the material. The results indicate a new approach that is free of volatile organic solvents to manipulate the architecture of the cross-section of the electrospun fiber and tailor mechanical properties to the required application. 

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4. Photothermally and magnetically controlled reconfiguration of polymer composites for soft robotics

   https://doi.org/10.1126/sciadv.aaw2897  

   Liu, Jessica A.-C. ; Gillen, Jonathan H. ; Mishra, Sumeet R. ; Evans, Benjamin A. ; Tracy, Joseph B. ( August 2019 , Science Advances)

   New materials are advancing the field of soft robotics. Composite films of magnetic iron microparticles dispersed in a shape memory polymer matrix are demonstrated for reconfigurable, remotely actuated soft robots. The composite films simultaneously respond to magnetic fields and light. Temporary shapes obtained through combined magnetic actuation and photothermal heating can be locked by switching off the light and magnetic field. Subsequent illumination in the absence of the magnetic field drives recovery of the permanent shape. In cantilevers and flowers, multiple cycles of locking and unlocking are demonstrated. Scrolls show that the permanent shape of the film can be programmed, and they can be frozen in intermediate configurations. Bistable snappers can be magnetically and optically actuated, as well as biased, by controlling the permanent shape. Grabbers can pick up and release objects repeatedly. Simulations of combined photothermal heating and magnetic actuation are useful for guiding the design of new devices. 

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5. Multi-Objective Optimization of Predicted Magnetic Properties From Multifield Processing Conditions in Polymer Matrix Particle Composites

   https://doi.org/10.1115/SMASIS2022-91175  

   Widdowson, Denise ; Erol, Anil ; Papula, Dashiell ; Ounaies, Zoubeida ; von Lockette, Paris ( September 2022 , Proceedings of the ASME 2022 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASME 2022 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Dearborn, Michigan, USA. September 12–14, 2022. V001T02A008. ASME.)

   Additive manufacturing, no longer reserved exclusively for prototyping components, can create parts with complex geometries and locally tailored properties. For example, multiple homogenous material sources can be used in different regions of a print or be mixed during printing to define properties locally. Additionally, heterogeneous composites provide an opportunity for another level of tuning properties through processing. For example, within particulate-filled polymer matrix composites before curing, the presence of an applied electric and/or magnetic fields can reorient filler particles and form hierarchical structures depending on the fields applied. Control of particle organization is important because effective material properties are highly dependent on the distribution of filler material within composites once cured. While previous work in homogenization and effective medium theories have determined properties based upon ideal analytic distributions of particle orientations and spatial location, this work expands upon these methods generating discrete distributions from quasi-Monte Carlo simulations of the electromagnetic processing event. Results of simulations provide predicted microarchitectures from which effective properties are determined via computational homogenization.

   These particle dynamics simulations account for dielectric and magnetic forces and torques in addition to hydrodynamic forces and hard particle separation. As such, the distributions generated are processing field dependent. The effective properties for a composite represented by this distribution are determined via computational homogenization using finite element analysis (FEA). This provides a path from constituents, through processing parameters to effective material properties. In this work, we use these simulations in conjunction with a multi-objective optimization scheme to resolve the relationships between processing conditions and effective properties, to inform field-assisted additive manufacturing processes.

   The constituent set providing the largest range of properties can be found using optimization techniques applied to the aforementioned simulation framework. This key information provides a recipe for tailoring properties for additive manufacturing design and production. For example, our simulation results show that stiffness for a 10% filler volume fraction can increase by 34% when aligned by an electric field as compared to a randomly distributed composite. The stiffness of this aligned sample is also 29% higher in the direction of the alignment than perpendicular to it, which only differs by 5% from the random case [1]. Understanding this behavior and accurately predicting composite properties is key to producing field processed composites and prints. Material property predictions compare favorably to effective medium theory and experimentation with trends in elastic and magnetic effective properties demonstrating the same anisotropic behavior as a result of applied field processing. This work will address the high computational expense of physics simulation based objective functions by using efficient algorithms and data structures. We will present an optimization framework using nested gradient searches for micro barium hexaferrite particles in a PDMS matrix, optimizing on composite magnetization to determine the volume fraction of filler that will provide the largest range of properties by varying the applied electric and magnetic fields.

    

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