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Abstract Technology disposal poses increasing pressure on the environment, society and economy. Scientists and engineers are seeking sustainable alternative solutions to meet these challenges, for example, through the development of sustainable soft robotics. Compared to conventional robotics, sustainable soft robotics can degrade into nothing at the end of their functional lives, leaving zero footprint in their surrounding environment. This is of paramount importance, especially in the push toward the ubiquity of robotic technology through advanced design and manufacturing techniques. Additive manufacturing (AM) describes the creation of 3D objects through the consecutive addition of material layers, enabling the fast prototyping of complex structures and devices, thereby reducing the financial and temporal cost in advanced robot development. The marriage of smart materials and AM can significantly promote the advancement of sustainable soft robotics technologies. In this roadmap, leading experts overview the status and development of sustainable soft robotics and provide insights into the exciting challenges and potential opportunities of sustainable actuators and sensors, AM technologies, functional materials, and robotic components across a wide range of application fields. This roadmap also serves as a vital compass for experts and enthusiasts in the field of sustainable soft robotics. 

Composites printed using material extrusion additive manufacturing (AM) typically exhibit alignment of high- aspect-ratio reinforcements parallel to the print direction. This alignment leads to highly anisotropic stiffness, strength, and transport properties. In many cases, it would be desirable to increase mechanical and transport properties transverse to the print direction, for example, in 3D-printed heat sinks or heat exchangers where heat must be moved efficiently between printed roads or layers. Rotational direct ink writing (RDIW), where the deposition nozzle simultaneously rotates and translates during deposition, provides a method to reorient fibers transverse to the print direction during the printing process. In the present work, carbon fiber-reinforced epoxy composites were printed by RDIW with a range of nozzle rotation rates and the in-plane and through-thickness thermal conductivity was measured. In addition, the orientation of carbon fiber (CF) in the composites was measured using optical microscopy and image analysis, from which second-order fiber orientation tensors were calculated. These results showed that the orientation of CF became less anisotropic as nozzle rotation rate increased, leading to increased through-thickness thermal conductivity, which increased by 40% at the highest rotation rate. The orientation tensors also showed that RDIW was more effective at reorienting fibers within the in-plane transverse direction compared to the through-thickness transverse direction. The results presented here demonstrate that a current weakness of material extrusion AM composites—poor thermal conductivity in the through-thickness direction—can be significantly improved with RDIW. 

In tissues and organs, the extracellular matrix (ECM) helps maintain inter- and intracellular architectures that sustain the structure–function relationships defining physiological homeostasis. Combining fiber scaffolds and cells to form engineered tissues is a means of replicating these relationships. Engineered tissues' fiber scaffolds are designed to mimic the topology and chemical composition of the ECM network. Here, we asked how cells found in the heart compare in their propensity to align their cytoskeleton and self-organize in response to topological cues in fibrous scaffolds. We studied cardiomyocytes, valvular interstitial cells, and vascular endothelial cells as they adapted their inter- and intracellular architectures to the extracellular space. We used focused rotary jet spinning to manufacture aligned fibrous scaffolds to mimic the length scale and three-dimensional (3D) nature of the native ECM in the muscular, valvular, and vascular tissues of the heart. The representative cardiovascular cell types were seeded onto fiber scaffolds and infiltrated the fibrous network. We measured different cell types' propensity for cytoskeletal alignment in response to fiber scaffolds with differing levels of anisotropy. The results indicated that valvular interstitial cells on moderately anisotropic substrates have a higher propensity for cytoskeletal alignment than cardiomyocytes and vascular endothelial cells. However, all cell types displayed similar levels of alignment on more extreme (isotropic and highly anisotropic) fiber scaffold organizations. These data suggest that in the hierarchy of signals that dictate the spatiotemporal organization of a tissue, geometric cues within the ECM and cellular networks may homogenize behaviors across cell populations and demographics. 

Clinical diagnosis typically incorporates physical examination, patient history, various laboratory tests, and imaging studies but makes limited use of the human immune system’s own record of antigen exposures encoded by receptors on B cells and T cells. We analyzed immune receptor datasets from 593 individuals to develop MAchine Learning for Immunological Diagnosis, an interpretive framework to screen for multiple illnesses simultaneously or precisely test for one condition. This approach detects specific infections, autoimmune disorders, vaccine responses, and disease severity differences. Human-interpretable features of the model recapitulate known immune responses to severe acute respiratory syndromecoronavirus2, influenza, and human immunodeficiency virus, highlight antigen-specific receptors, and reveal distinct characteristics of systemic lupus erythematosus and type-1 diabetes autoreactivity. This analysis framework has broad potential for scientific and clinical interpretation of immune responses.