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Abstract The accurate, continuous analysis of healthcare-relevant gases such as nitrogen oxides (NO x ) in a humid environment remains elusive for low-cost, stretchable gas sensing devices. This study presents the design and demonstration of a moisture-resistant, stretchable NO x gas sensor based on laser-induced graphene (LIG). Sandwiched between a soft elastomeric substrate and a moisture-resistant semipermeable encapsulant, the LIG sensing and electrode layer is first optimized by tuning laser processing parameters such as power, image density, and defocus distance. The gas sensor, using a needlelike LIG prepared with optimal laser processing parameters, exhibits a large response of 4.18‰ ppm −1 to NO and 6.66‰ ppm −1 to NO 2 , an ultralow detection limit of 8.3 ppb to NO and 4.0 ppb to NO 2 , fast response/recovery, and excellent selectivity. The design of a stretchable serpentine structure in the LIG electrode and strain isolation from the stiff island allows the gas sensor to be stretched by 30%. Combined with a moisture-resistant property against a relative humidity of 90%, the reported gas sensor has further been demonstrated to monitor the personal local environment during different times of the day and analyze human breath samples to classify patients with respiratory diseases from healthy volunteers. Moisture-resistant, stretchable NO x gas sensors can expand the capability of wearable devices to detect biomarkers from humans and exposed environments for early disease diagnostics. 

We demonstrate a new, to the best of our knowledge, kind of self-pulsation in a microcavity Brillouin laser. This specific self-pulsation is generated by the interplay between the Brillouin lasing and the thermo-optic effect in an optical microcavity. Intriguingly, the self-pulsation behaviors are simultaneously present in both forward input pump and backward Brillouin lasing emission. By developing a coupled-mode theory, our numerical simulations display an excellent agreement with the experimental results.

 

During the COVID-19 pandemic, many urban schools relied on community centers with existing computer labs and high-speed internet that could provide in-person support for a small number of children engaging in online learning. Using a digital storytelling approach, this research report analyzes the mathematics identities of 14 informal adult educators. Situating the stories shared though Critical Race Theory counternarratives, this study enables participants to ground their narratives within their own spaces of power–to tell and forge their own digital mathematics story. Because informal adult educators are not family members nor school-based educators, they often are invisible variables in conceptualizing a child’s mathematics learning. This research seeks to elicit their mathematics stories and understand how to enactment digital mathematics storytelling through listening to how the community positions and visions math. 

A core-removed D-shaped structure with different residual thickness (RT) was manufactured on a single mode silica fiber (SMF) to enhance the sensitivity by using of ultra-precise polishing technology. With six different RTs ranging from ∼55 µm to ∼28 µm, the RT enhancement effect in a D-shaped SMF was researched in detail. The influence of the RT on its transmission spectra was investigated both theoretically and experimentally. Considering a compromise between the multimode interference efficiency and optical power loss, an optimum RT value of 34.09 µm was achieved. The obtained refractive index (RI) sensitivity was 10243 nm/RIU in the RI range of 1.430-1.444, corresponding to a RI resolution of 1.9×10⁻⁶RIU. A high-performance all-fiber sensor was developed to monitor the evaporation process volatile organic compounds (VOCs) based on the RT-enhanced D-shaped SMF. As proof of concept, a 2-hour continuous monitoring was carried to monitor the chloroform and alcohol mixture. As a result, the evaporation of alcohol and chloroform were clearly identified and monitored. The developed RT-enhanced D-shaped fiber sensor provides an alternative way for chemical process monitoring and industrial applications.

 

Soft robots outperform the conventional hard robots on significantly enhanced safety, adaptability, and complex motions. The development of fully soft robots, especially fully from smart soft materials to mimic soft animals, is still nascent. In addition, to date, existing soft robots cannot adapt themselves to the surrounding environment, i.e., sensing and adaptive motion or response, like animals. Here, compliant ultrathin sensing and actuating electronics innervated fully soft robots that can sense the environment and perform soft bodied crawling adaptively, mimicking an inchworm, are reported. The soft robots are constructed with actuators of open‐mesh shaped ultrathin deformable heaters, sensors of single‐crystal Si optoelectronic photodetectors, and thermally responsive artificial muscle of carbon‐black‐doped liquid‐crystal elastomer (LCE‐CB) nanocomposite. The results demonstrate that adaptive crawling locomotion can be realized through the conjugation of sensing and actuation, where the sensors sense the environment and actuators respond correspondingly to control the locomotion autonomously through regulating the deformation of LCE‐CB bimorphs and the locomotion of the robots. The strategy of innervating soft sensing and actuating electronics with artificial muscles paves the way for the development of smart autonomous soft robots.