Devin J. Roach

An analytical continuum framework maps the attainable equilibrium states of liquid crystalline elastomers across stretch, temperature, and stress, defining an operational envelope for comparing actuator performance across studies.

Fused filament fabrication (FFF) printed polyetherimide (PEI), commercially available as ULTEM 9085, is qualified by the Federal Aviation Administration for aerospace structural applications. Its mechanical performance depends strongly on printing parameters, including build orientation, number of contours, raster angle, and air gap, whose nonlinear interactions govern void formation, interlayer bonding, and ultimate strength. Prior work using artificial neural networks (ANNs) predicted ULTEM 9085 properties with under 5% error from a single data split, leaving two questions open: whether that accuracy holds across repeated splits, and whether the model's reasoning can be physically interpreted. This study addresses both gaps. Eight regression algorithms (Ridge, Decision Tree, Random Forest, Extra Trees, Gradient Boosting, XGBoost, K‐Nearest Neighbors, and Support Vector Regression) are benchmarked to jointly predict complete stress–strain curves and three scalar mechanical properties (tensile strength, elastic modulus, yield strength) from the four printing parameters, evaluated across five random data splits. SHAP and LIME are then applied to the best‐performing model to attribute its predictions to individual printing parameters. Extra Trees Regressor achieves the lowest and most stable test mean absolute error (MAE) of 0.162 ± 0.041 in scaled space across five seeds, with scalar property errors of 4.0% (tensile strength), 4.4% (elastic modulus), and 8.5% (yield strength), accuracy comparable to the ANN baseline at a fraction of the computational cost. SHAP and LIME attributions agree that the number of contours and build orientation are the dominant drivers of tensile strength, with air gap acting as a smaller, suppressive factor. These results support Extra Trees with SHAP/LIME explanation as a repeatable, interpretable, and computationally inexpensive surrogate for reducing the physical testing burden in aerospace qualification of 3D‐printed ULTEM 9085.

Contractile actuators are promising candidates for soft robotics, but selecting a suitable actuator for a specific mechanism requires the combination of performance metrics such as free stroke, blocking force, or work density. For a specific elastic actuator, the available stroke is strongly dependent on the force imposed by the intrinsic stiffness of the robot or the external structure. Here, we present a framework for characterizing and selecting contractile actuators typical uses operating in the quasistatic regime. To characterize the actuators, we use the longitudinal force–displacement curves, measured in the passive state via tensile test and in the active state via isometric or isobaric test. The force–displacement curves in these two states define the boundary of the operational range of achievable strokes. We demonstrate the framework on three representative and distinct contractile actuators: electrically stimulated thermal twisted‐and‐coiled polymer actuators, heat‐stimulated liquid crystal elastomer actuators, and McKibben‐type pneumatic actuators. To select actuators, we propose the incidence matrix formulation for actuator groups arranged in series and/or in parallel. We validate the approach experimentally in two design problems: an insect‐scale jumping robot with nonlinear buckling loads, and an antagonistic structure. This framework for actuator characterization and selection replaces trial‐and‐error with a predictive, materials‐agnostic design workflow, providing a foundation for the rational integration of emerging contractile actuators into soft robotics.

Continuous fiber reinforced polymer composites (CFRPC) represent the state of the art in structural materials, yet their manufacturing is constrained by expensive fixed tooling, slow development cycles, and limited geometric complexity. This work introduces Quicksand Molding (QSM), a rapid, low-cost manufacturing method that combines additively manufactured (AM) tooling, sand support, and pneumatic bladder pressure to fabricate CFRPC parts with geometric design freedom not possible through conventional methods. By supporting thin, flexible AM tooling with sand, QSM achieves molding pressures above 700 kPa, seven times the theoretical maximum of vacuum bagging (VB), using thermoplastic tools as thin as 1 mm. This pressure, combined with the tool's flexibility when unsupported, allows QSM to mold geometries with undercuts and compound curvature that conventional rigid tooling cannot achieve. Mechanical, optical, and compositional analysis show QSM outperforms VB, the most common CFRPC manufacturing method, increasing fiber volume by 6%, reducing void content from over 10% to below 0.5%, and improving flexural strength by 38%, with additional gains in tensile and interlaminar shear performance. By pairing low-cost, rapidly manufacturable tooling with freeform geometric design, QSM enables on-demand fabrication of high-performance composites in resource-limited or austere environments.

Multi-photon lithography (MPL) is a nano-scale additive manufacturing technique capable of creating extremely detailed structures with sub-micron 3D resolution, providing a leading platform for innovation in the field of microrobotics. Liquid crystalline elastomers (LCEs) are a class of soft, stimuli-responsive materials that undergo large, reversible shape changes, motivating their extensive study as artificial muscles for soft microrobotic systems. Actuation in LCEs relies on the alignment of their polymer backbone, yet achieving spatially programmable alignment at sub-micrometer scales remains a challenge. In this work, we report a straightforward method for introducing controlled alignment in LCEs 3D printed using MPL. LCE inks containing a non-reactive solvent are printed between fixed constraints and, upon solvent removal, a shrinkage-induced volume change generates internal stresses, leading to alignment of the printed LCE network. Importantly, the direction of alignment and resulting actuation can be programmed along arbitrary axes in a 3D printing coordinate system without substrate pretreatment or external fields. These MPL printed LCE microactuators demonstrate actuation in functional micromechanical systems including a micro-mirror array and gear system, achieving specific work values of up to 212 J/kg. This approach enables simultaneous 3D printing and alignment of LCEs at the microscale, providing a pathway for creating efficient, stimuli-responsive actuators for microrobotic systems.

For semicrystalline polyolefin thermoplastics, the balance between interconnected ordered crystalline and disordered amorphous regions is paramount to their performance and processability. However, contemporary manufacturing strategies, from injection molding to three-dimensional (3D) printing, result in monolithic objects, unable to spatially encode crystallinity. We develop a light-based approach for fabricating mechanically robust polyolefin thermoplastics with microscopic control over crystallinity in 3D space. Light dosage governs polymer stereochemistry giving access to a continuum of materials, from strong rigid plastics, such as high-density polyethylene, to more extensible materials akin to low-density polyethylene, all at the flick of a switch. Leveraging this finding in lithographic grayscale 3D printing enables rapid multimaterial fabrication with voxel-level control over optical and mechanical properties, opening avenues in information storage, soft robotics, and energy damping.

Liquid crystal elastomers (LCEs) are anisotropic polymeric smart materials with promise for soft robotic actuators, dampers, and adhesives. Realizing these applications requires precise 3D alignment of the polymer backbone, yet current manufacturing approaches struggle to produce complex spatial patterns in three dimensions. Here, we introduce a digital light processing (DLP) 3D printing strategy that enables voxel‐level control of LCE alignment domains. By integrating a rotatable magnetic array with DLP photomasking, we achieve spatially tunable structures at voxel resolutions. This approach allows freeform 180° alignment within individual voxels, generating highly nonlinear shape transformations in both 2D films and 3D architectures. Finite element modeling and inverse design guide the creation of multidomain alignment patterns that could achieve targeted nonlinear deformation behaviors. As a demonstration, multidomain LCE smart valves are fabricated that exhibit up to 70% improved flow control compared to monodomain analogues. This technique dramatically expands the design space of 3D programmable matter and establishes a pathway toward complex, application‐ready LCE systems.