Multifunctional electronic textiles (e-textiles) incorporating miniaturized electronic devices will pave the way toward a new generation of wearable devices and human-machine interfaces. Unfortunately, the development of e-textiles is subject to critical challenges, such as battery dependence, breathability, satisfactory washability, and compatibility with mass production techniques. This work describes a simple and cost-effective method to transform conventional garments and textiles into waterproof, breathable, and antibacterial e-textiles for self-powered human-machine interfacing. Combining embroidery with the spray-based deposition of fluoroalkylated organosilanes and highly networked nanoflakes, omniphobic triboelectric nanogenerators (R F -TENGs) can be incorporated into any fiber-based textile to power wearable devices using energy harvested from human motion. R F -TENGs are thin, flexible, breathable (air permeability 90.5 mm s −1 ), inexpensive to fabricate (<0.04$ cm −2 ), and capable of producing a high power density (600 µW cm −2 ). E-textiles based on R F -TENGs repel water, stains, and bacterial growth, and show excellent stability under mechanical deformations and remarkable washing durability under standard machine-washing tests. Moreover, e-textiles based on R F -TENGs are compatible with large-scale production processes and exhibit high sensitivity to touch, enabling the cost-effective manufacturing of wearable human-machine interfaces.

Traditional manufacturing methods and materials used to fabricate epidermal electronics for physiological monitoring, transdermal stimulation, and therapeutics are complex and expensive, preventing their adoption as single-use medical devices. This work describes the fabrication of epidermal, paper-based electronic devices (EPEDs) for wearable and implantable applications by combining the spray-based deposition of silanizing agents, highly conductive nanoparticles, and encapsulating polymers with laser micromachining. EPEDs are inexpensive, stretchable, easy to apply, and disposable by burning. The omniphobic character and fibrous structure of EPEDs make them breathable, mechanically stable upon stretching, and facilitate their use as electrophysiological sensors to record electrocardiograms, electromyograms, and electrooculograms, even under water. EPEDs can also be used to provide thermotherapeutic treatments to joints, map temperature spatially, and as wirelessly powered implantable devices for stimulation and therapeutics. This work makes epidermal electronic devices accessible to high-throughput manufacturing technologies and will enable the fabrication of a variety of wearable medical devices at a low cost.

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This work describes the detection of anti-T. cruzi antibodies in whole blood solutions using magnetic levitating microbeads (MLμBs). This simple diagnostic method can be easily performed by minimally trained personnel using an inexpensive and portable magnetic stage that requires no electricity. A multiphase test tube containing the MLμBs facilitates the sequential incubation, filtering, and reading of the immunoassays. The diagnostic method starts by adding a blood sample to the top phase of the test tube where the anti-T. cruzi antibodies present in the blood attach to the T. cruzi antigens on the surface of the MLμBs. Shaking the test tube after incubation mixes the top layer with a paramagnetic medium loaded with SiO microcrystals. The attachment of SiO microcrystals to those MLμBs bound to T. cruzi antibodies decreases their levitation height once the tube is placed between two antialigned permanent magnets. Measuring the levitation height of MLμBs enables the accurate detection and quantification of anti-T. cruzi antibodies in the blood across the clinically relevant range, with a detection limit of 5 μg mL. The small size of the test tubes facilitates the simultaneous analysis of over 50 different samples. MLμBs act as partial collimators for non-polarized light, facilitating their visual identification by the naked eye or by projecting incident light on a thin paper screen. A machine-vision algorithm was created to automatically interpret the results of the MLμB tests from a digital image, resulting in a rapid, accurate, and user-friendly assay for Chagas disease that can be used in resource-limited settings.