Controlling and reducing the developed region initiated by photoexposure is one of the fundamental goals of optical lithography. Here, we demonstrate a two-color irradiation scheme whereby initiating species are generated by single-photon absorption at one wavelength while inhibiting species are generated by single-photon absorption at a second, independent wavelength. Co-irradiation at the second wavelength thus reduces the polymerization rate, delaying gelation of the material and facilitating enhanced spatial control over the polymerization. Appropriate overlapping of the two beams produces structures with both feature sizes and monomer conversions otherwise unobtainable with use of single- or two-photon absorption photopolymerization. Additionally, the generated inhibiting species rapidly recombine when irradiation with the second wavelength ceases, allowing for fast sequential exposures not limited by memory effects in the material and thus enabling fabrication of complex two- or three-dimensional structures.

Liquid crystalline elastomers (LCEs) are soft, anisotropic materials that exhibit large shape transformations when subjected to various stimuli. Here we demonstrate a facile approach to enhance the out-of-plane work capacity of these materials by an order of magnitude, to nearly 20 J/kg. The enhancement in force output is enabled by the development of a room temperature polymerizable composition used both to prepare individual films, organized via directed self-assembly to retain arrays of topological defect profiles, as well as act as an adhesive to combine the LCE layers. The material actuator is shown to displace a load >2500× heavier than its own weight nearly 0.5 mm.

Experimental search for high-temperature ferroelectric perovskites is a challenging task due to the vast chemical space and lack of predictive guidelines. Here, we demonstrate a two-step machine learning approach to guide experiments in search of xBiO3–(1 − x)PbTiO3-based perovskites with high ferroelectric Curie temperature. These involve classification learning to screen for compositions in the perovskite structures, and regression coupled to active learning to identify promising perovskites for synthesis and feedback. The problem is challenging because the search space is vast, spanning ~61,500 compositions and only 167 are experimentally studied. Furthermore, not every composition can be synthesized in the perovskite phase. In this work, we predict x, y, Me′, and Me″ such that the resulting compositions have both high Curie temperature and form in the perovskite structure. Outcomes from both successful and failed experiments then iteratively refine the machine learning models via an active learning loop. Our approach finds six perovskites out of ten compositions synthesized, including three previously unexplored {Me′Me″} pairs, with 0.2Bi(Fe0.12Co0.88)O3–0.8PbTiO3 showing the highest measured Curie temperature of 898 K among them.

Orthogonal, sequential “click” reactions were implemented to yield novel polymeric substrates with the ability to record holographic data. The base-catalyzed thiol–acrylate Michael “click” reaction was implemented to yield a writable, stage 1 polymeric substrate with glass transition temperatures (T g) ranging from 0 to −26 °C and rubbery storage moduli (E′) from 11.1 to 0.3 MPa. The loosely cross-linked matrix also contained a novel high refractive index monomer 9-(2,3-bis(allyloxy)propyl)-9H-carbazole (BAPC) that did not participate in the thiol–Michael reaction but allowed for large index gradients to be developed within the network upon subsequent exposure to coherent laser beams and initiation of the radical-mediated thiol–ene reaction. The holographic gratings were recorded with 96% diffraction efficiency and ca. 2.4 cm/mJ of light sensitivity in 2 s under a 405 nm exposure with an intensity of 20 mW/cm2. Subsequent to pattern formation, via a thiol–allyl radical “click” photopolymerization initiated by flood illumination of the sample, holographic materials with high T g, high modulus, diffraction efficiency as high as 82%, and refractive index modulation of 0.004 were obtained. Graded rainbow holograms that displayed colors from blue to red at a single viewing angle were readily formed through this new technique.

Materials capable of complex shape changes have broad reaching applications spanning biomimetic devices, componentless actuators, artificial muscles, and haptic displays. Liquid crystal elastomers (LCE) are a class of shape programmable materials which display anisotropic mechanical deformations in response external stimuli. This work details a synthetic strategy to quickly and efficiently prepare LCEs through the usage of chain transfer agents (CTA). The polyacrylate materials described herein exhibit large, reversible shape changes with strains greater 475%, rivalling properties observed in polysiloxane-based networks. The approach reported here is distinguished in that the materials chemistry is readily amenable to surface alignment techniques. The facile nature of the materials chemistry and the compatibility of these materials with directed self-assembly methods could further enable paradigm shifting end uses as designer substrates for flexible electronics or as actuating surfaces.