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Abstract Elephant trunks are capable of complex, multimodal deformations, allowing them to perform task‐oriented high‐degree‐of‐freedom (DOF) movements pertinent to the field of soft actuators. Despite recent advances, most soft actuators can only achieve one or two deformation modes, limiting their motion range and applications. Inspired by the elephant trunk musculature, a liquid crystal elastomer (LCE)‐based multi‐fiber design strategy is proposed for soft robotic arms in which a discrete number of artificial muscle fibers can be selectively actuated, achieving multimodal deformations and transitions between modes for continuous movements. Through experiments, finite element analysis (FEA), and a theoretical model, the influence of LCE fiber design on the achievable deformations, movements, and reachability of trunk‐inspired robotic arms is studied. Fiber geometry is parametrically investigated for 2‐fiber robotic arms and the tilting and bending of these arms is characterized. A 3‐fiber robotic arm is additionally studied with a simplified fiber arrangement analogous to that of an actual elephant trunk. The remarkably broad range of deformations and the reachability of the arm are discussed, alongside transitions between deformation modes for functional movements. It is anticipated that this design and actuation strategy will serve as a robust method to realize high‐DOF soft actuators for various engineering applications. 

With the rapid growth of emerging point-of-use (POU)/point-of-care (POC) detection technologies, miniaturized sensors for the real-time detection of gases and airborne pathogens have become essential to fight pollution, emerging contaminants, and pandemics. However, the low-cost development of miniaturized gas sensors without compromising selectivity, sensitivity, and response time remains challenging. Microfluidics is a promising technology that has been exploited for decades to overcome such limitations, making it an excellent candidate for POU/POC. However, microfluidic-based gas sensors remain a nascent field. In this review, the evolution of microfluidic gas sensors from basic electronic techniques to more advanced optical techniques such as surface-enhanced Raman spectroscopy to detect analytes is documented in detail. This paper focuses on the various detection methodologies used in microfluidic-based devices for detecting gases and airborne pathogens. Non-continuous microfluidic devices such as bubble/droplet-based microfluidics technology that have been employed to detect gases and airborne pathogens are also discussed. The selectivity, sensitivity, advantages/disadvantages vis-a-vis response time, and fabrication costs for all the microfluidic sensors are tabulated. The microfluidic sensors are grouped based on the target moiety, such as air pollutants such as carbon monoxide and nitrogen oxides, and airborne pathogens such as E. coli and SARS-CoV-2. The possible application scenarios for the various microfluidic devices are critically examined.