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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. 

Abstract Precipitation plays an important role in cloud and aerosol processes over the Southern Ocean (SO). The main objective of this study is to characterize SO precipitation properties associated with SO stratocumulus clouds. We use data from the Southern Ocean Clouds Radiation Aerosol Transport Experimental Study (SOCRATES), and leverage observations from airborne radar, lidar, and in situ probes. We find that for the cold‐topped clouds (cloud‐top‐temperature <0°C), the phase of precipitation with reflectivity >0 dBZ is predominantly ice, while reflectivity < −10 dBZ is predominantly liquid. Liquid‐phase precipitation properties are retrieved where radar and lidar are zenith‐pointing. Power‐law relationships between reflectivity (Z) and rain rate (R) are developed, and the derived Z–R relationships show vertical dependence and sensitivity to the presence of droplets with diameters between 10 and 40 μm. Using derived Z–R relationships, a reflectivity‐velocity (ZV) retrieval method, and a radar‐lidar retrieval method, we derive rain rate and other precipitation properties. The retrieved rain rate from all three methods shows good agreement with in‐situ aircraft estimates, with rain rates typically being quite light (<0.1 mm hr⁻¹). We examine the vertical distribution of precipitation properties, and find that rain rate, precipitation number concentration, and precipitation liquid water all decrease as one gets closer to the surface, while precipitation size and distribution width increases. We also examine how cloud base rain rate (R_CB) depends on cloud depth (H) and aerosol concentration (N_a) for particles with a diameter greater than 70 nm, and find thatR_CBis proportional to . 

This engineering curriculum is designed for students in 6-8 grade where they learn about the concept of polarity and mixing through the phenomenon of oil separating from water by simulating an oil spill that demonstrates the impact of these molecular qualities on the environment. In the first part of the activity, students get familiar with the concept of polarity and how it causes oil to float on water through molecular models and demonstrations. The second part entails a simulation of an oil spill in the ocean, where students are given a variety of tools and will engineer their own solutions to clean up the spill through trial and testing. Finally, they discuss the real-world methods used to clean up oil spills, and their impact on the environment. This engineering curriculum aligns to Next Generation Science Standards. 

The Arctic is warming at almost four times the global rate. Cooling caused by anthropogenic aerosols has been estimated to offset sixty percent of greenhouse-gas-induced Arctic warming, but the contribution of aerosols to radiative forcing (RF) represents the largest uncertainty in estimating total RF, largely due to unknown preindustrial aerosol abundance. Here, sulfur isotope measurements in a Greenland ice core show that passive volcanic degassing contributes up to 66 ± 10% of preindustrial ice core sulfate in years without major eruptions. A state-of-the-art model indicates passive volcanic sulfur emissions influencing the Arctic are underestimated by up to a factor of three, possibly because many volcanic inventories do not include hydrogen sulfide emissions. Higher preindustrial volcanic sulfur emissions reduce modeled anthropogenic Arctic aerosol cooling by up to a factor of two (+0.11 to +0.29 W m-2), suggesting that underestimating passive volcanic sulfur emissions has significant implications for anthropogenic-induced Arctic climate change. 

Abstract The Arctic is warming at almost four times the global rate. An estimated sixty percent of greenhouse‐gas‐induced Arctic warming has been offset by anthropogenic aerosols, but the contribution of aerosols to radiative forcing (RF) represents the largest uncertainty in estimating total RF, largely due to unknown preindustrial aerosol abundance. Here, sulfur isotope measurements in a Greenland ice core show that passive volcanic degassing contributes up to 66 ± 10% of preindustrial ice core sulfate in years without major eruptions. A state‐of‐the‐art model indicates passive volcanic sulfur emissions influencing the Arctic are underestimated by up to a factor of three, possibly because many volcanic inventories do not include hydrogen sulfide emissions. Higher preindustrial volcanic sulfur emissions reduce modeled anthropogenic Arctic aerosol cooling by up to a factor of two (+0.11 to +0.29 W m⁻²), suggesting that underestimating passive volcanic sulfur emissions has significant implications for anthropogenic‐induced Arctic climate change. 

Abstract Ultrafast movements propelled by springs and released by latches are thought limited to energetic adjustments prior to movement, and seemingly cannot adjust once movement begins. Even so, across the tree of life, ultrafast organisms navigate dynamic environments and generate a range of movements, suggesting unrecognized capabilities for control. We develop a framework of control pathways leveraging the non-linear dynamics of spring-propelled, latch-released systems. We analytically model spring dynamics and develop reduced-parameter models of latch dynamics to quantify how they can be tuned internally or through changing external environments. Using Lagrangian mechanics, we test feedforward and feedback control implementation via spring and latch dynamics. We establish through empirically-informed modeling that ultrafast movement can be controllably varied during latch release and spring propulsion. A deeper understanding of the interconnection between multiple control pathways, and the tunability of each control pathway, in ultrafast biomechanical systems presented here has the potential to expand the capabilities of synthetic ultra-fast systems and provides a new framework to understand the behaviors of fast organisms subject to perturbations and environmental non-idealities.