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Resistance change under mechanical stimuli arouses mass operational heat, damaging the performance, lifetime, and reliability of stretchable electronic devices, therefore rapid thermal heat dissipating is necessary. Here we report a stretchable strain sensor with outstanding thermal management. Besides a high stretchability and sensitivity testified by human motion monitoring, as well as long-term durability, an enhanced thermal conductivity from the casted thermoplastic polyurethane-boron nitride nanosheets layer helps rapid heat transmission to the environments, while the porous electrospun fibrous thermoplastic polyurethane membrane leads to thermal insulation. A 32% drop of the real time saturated temperature is achieved. For the first time we in-situ investigated the dynamic operational temperature fluctuation of stretchable electronics under repeating stretching-releasing processes. Finally, cytotoxicity test confirms that the nanofillers are tightly restricted in the nanocomposites, making it harmless to human health. All the results prove it an excellent candidate for the next-generation of wearable devices.

Sensing of clinically relevant biomolecules such as neurotransmitters at low concentrations can enable an early detection and treatment of a range of diseases. Several nanostructures are being explored by researchers to detect biomolecules at sensitivities beyond the picomolar range. It is recognized, however, that nanostructuring of surfaces alone is not sufficient to enhance sensor sensitivities down to the femtomolar level. In this paper, we break this barrier/limit by introducing a sensing platform that uses a multi-length-scale electrode architecture consisting of 3D printed silver micropillars decorated with graphene nanoflakes and use it to demonstrate the detection of dopamine at a limit-of-detection of 500 attomoles. The graphene provides a high surface area at nanoscale, while micropillar array accelerates the interaction of diffusing analyte molecules with the electrode at low concentrations. The hierarchical electrode architecture introduced in this work opens the possibility of detecting biomolecules at ultralow concentrations., (© 2021. The Author(s).)

Recent advances in nanomaterials and nano-microfabrication have enabled the development of flexible wearable electronics. However, existing manufacturing methods still rely on a multi-step, error-prone complex process that requires a costly cleanroom facility. Here, we report a new class of additive nanomanufacturing of functional materials that enables a wireless, multilayered, seamlessly interconnected, and flexible hybrid electronic system. All-printed electronics, incorporating machine learning, offers multi-class and versatile human-machine interfaces. One of the key technological advancements is the use of a functionalized conductive graphene with enhanced biocompatibility, anti-oxidation, and solderability, which allows a wireless flexible circuit. The high-aspect ratio graphene offers gel-free, high-fidelity recording of muscle activities. The performance of the printed electronics is demonstrated by using real-time control of external systems via electromyograms. Anatomical study with deep learning-embedded electrophysiology mapping allows for an optimal selection of three channels to capture all finger motions with an accuracy of about 99% for seven classes.

Size selectivity is an important mechanism for molecular recognition based on the size difference between targets and non-targets. However, rational design of an artificial size-selective molecular recognition system for biological targets in living cells remains challenging. Herein, we construct a DNA molecular sieve for size-selective molecular recognition to improve the biosensing selectivity in living cells. The system consists of functional nucleic acid probes (e.g., DNAzymes, aptamers and molecular beacons) encapsulated into the inner cavity of framework nucleic acid. Thus, small target molecules are able to enter the cavity for efficient molecular recognition, while large molecules are prohibited. The system not only effectively protect probes from nuclease degradation and nonspecific proteins binding, but also successfully realize size-selective discrimination between mature microRNA and precursor microRNA in living cells. Therefore, the DNA molecular sieve provides a simple, general, efficient and controllable approach for size-selective molecular recognition in biomedical studies and clinical diagnoses.

Bacteria are an enormous and largely untapped reservoir of biosensing proteins. We describe an approach to identify and isolate bacterial allosteric transcription factors (aTFs) that recognize a target analyte and to develop these TFs into biosensor devices. Our approach utilizes a combination of genomic screens and functional assays to identify and isolate biosensing TFs, and a quantum-dot Förster Resonance Energy Transfer (FRET) strategy for transducing analyte recognition into real-time quantitative measurements. We use this approach to identify a progesterone-sensing bacterial aTF and to develop this TF into an optical sensor for progesterone. The sensor detects progesterone in artificial urine with sufficient sensitivity and specificity for clinical use, while being compatible with an inexpensive and portable electronic reader for point-of-care applications. Our results provide proof-of-concept for a paradigm of microbially-derived biosensors adaptable to inexpensive, real-time sensor devices.

Capabilities for continuous monitoring of pressures and temperatures at critical skin interfaces can help to guide care strategies that minimize the potential for pressure injuries in hospitalized patients or in individuals confined to the bed. This paper introduces a soft, skin-mountable class of sensor system for this purpose. The design includes a pressure-responsive element based on membrane deflection and a battery-free, wireless mode of operation capable of multi-site measurements at strategic locations across the body. Such devices yield continuous, simultaneous readings of pressure and temperature in a sequential readout scheme from a pair of primary antennas mounted under the bedding and connected to a wireless reader and a multiplexer located at the bedside. Experimental evaluation of the sensor and the complete system includes benchtop measurements and numerical simulations of the key features. Clinical trials involving two hemiplegic patients and a tetraplegic patient demonstrate the feasibility, functionality and long-term stability of this technology in operating hospital settings., (© 2021. The Author(s).)

All materials respond heterogeneously at small scales, which limits what a sensor can learn. Although previous studies have characterized measurement noise arising from thermal fluctuations, the limits imposed by structural heterogeneity have remained unclear. In this paper, we find that the least fractional uncertainty with which a sensor can determine a material constant λ 0 of an elastic medium is approximately [Formula: see text] for a ≫ d ≫ ξ, [Formula: see text], and D > 1, where a is the size of the sensor, d is its spatial resolution, ξ is the correlation length of fluctuations in λ 0 , Δ λ is the local variability of λ 0 , and D is the dimension of the medium. Our results reveal how one can construct devices capable of sensing near these limits, e.g. for medical diagnostics. We use our theoretical framework to estimate the limits of mechanosensing in a biopolymer network, a sensory process involved in cellular behavior, medical diagnostics, and material fabrication.