The lateral-flow immunoassay (LFA) has proven to be an effective point-of-care (POC) diagnostic for the rapid detection of target analytes in patient samples. However, due to its reliance on a binary, visual output, the LFA cannot be used to quantify target analyte concentrations, nor is it accessible to blind or visually impaired patients. To address these limitations, we developed the quantitative LFA interpretation device (qLFAID), which operates on the Raspberry Pi 4 Model B. The qLFAID uses a trained neural network in conjunction with a nonlinear regression model to analyze the test line intensity of any LFA to determine the target analyte concentration. In addition, qLFAID’s electronic components provide auditory and tactile signals for blind and visually impaired users to interpret their results. As a proof of concept, the device was applied to analyze an LFA we designed to detect for digoxin in human serum. Our device successfully correlated the LFA test line intensity to the sample digoxin concentration, providing a quantitative output. Overall, qLFAID has the potential to be robust in POC settings and, to our knowledge, is the first assistive technology that can both enable the quantitative capability of all LFAs and increase diagnostic accessibility for blind or visually impaired individuals.

We are the first to combine the lateral-flow immunoassay (LFA) with gold nanorod (GNR) etching to achieve a multicolor readout where the color produced was correlated with digoxin concentrations in human serum in the relevant range for therapeutic drug monitoring of 0.5-3.0 ng mL-1.

Nano-wrinkled polymeric membranes have received tremendous attention for their broad applications in tunable optics, biomedicine, surface wettability, and flexible electronics. However, achieveing a low-cost and scalable synthesis routine remains highly desirable. Here, we invent a simple, bottom-up, polymer engineering strategy by introducing water molecules into the polymerization process. Water evaporation induces intermolecular forces that build a crosslinking reaction gradient from the material surface to its interior, which buckles the surface-forming wrinkles. The shape, geometry, size, orientation, and arrangement of the wrinkles on the polymer surface can be designed accordingly. Moreover, the as-fabricated nano-wrinkled, polymeric membranes display outstanding performance in energy and sensing applications, boosting output current and sensing sensitivity by 611% and 164%, respectively, compared to their flat counterparts. This work may contribute to a low-cost, scalable, and environmentally friendly strategy to engineer polymer surfaces with controllable wrinkles, showing great potential for the development of various soft-matter technologies.

With the rapid development of the Internet of Things (IoT) and the ongoing Fourth Industrial Revolution, the effective conversion of wasted ambient mechanical energy from the environment to generate electricity is regarded as one of the most pivotal technologies for powering widely distributed electronics in the era of the Internet of Things. Although the triboelectric nanogenerator (TENG), based on the coupling effect of contact electrification and electrostatic induction, has recently undergone a tremendous evolution with the development of various features such as flexibility, conformability, and user-friendliness, further improvement of the output performance is still required for usage toward practical applications for the next-generation of IoT devices. In this review article, surface nanostructure modification methods for high-performance triboelectric nanogenerators are systematically summarized. The field is deeply reviewed, with the methods classified into four categories: templating method, appending method, etching method, and crumpling method. Finally, an in-depth discussion of the existing challenges and the direction of future efforts for enhancing TENG output performance are clearly stated, which can contribute to promoting further development of the field.

Carbon is a fascinating element that can be found in a wide spectrum of materials and plays a significant role in diverse disciplines across the scientific community. Carbon nanomaterials take many forms with numerous applications. Controllably tailoring carbon nanomaterials at the molecular scale can be considered as a basic innovation yet remains a significant challenge because of carbon's intrinsic structural and chemical stability. Herein, we report a molecular scissor to efficiently tailor carbon nanomaterials of different dimensions at a molecular level. By using the Mg/Zn bimetallic effect and CO2 molecules, a molecular scissor was invented to engineer the surface of carbon nanomaterials with highly interconnected graphene pillared superstructures. The molecular scissor redesigned the carbon materials with improved surface properties for use in various applications. For energy storage application, both ultrahigh surface area and conductivity can be achieved concurrently with substantial ion-reserved accommodation and rapid mass -transfer expressway. As a demonstration, a flexible solid-state supercapacitor based on the surface -tailored carbon fiber was developed with Polyvinyl alcohol(PVA)/Na2SO4 gel electrolytes. It delivered a remarkably high energy density of 4.63 mW h cm-3 at a power density of 3520 mW cm-3. This work paves a new way to reinvent carbon materials at the molecular scale and promote their applications for energy storage, sensing, environmental remediation, and healthcare. (C) 2020 Elsevier Ltd. All rights reserved.

With the rapid development of the Internet of Things (IoT) and the ongoing Fourth Industrial Revolution, the effective conversion of wasted ambient mechanical energy from the environment to generate electricity is regarded as one of the most pivotal technologies for powering widely distributed electronics in the era of the Internet of Things. Although the triboelectric nanogenerator (TENG), based on the coupling effect of contact electrification and electrostatic induction, has recently undergone a tremendous evolution with the development of various features such as flexibility, conformability, and user-friendliness, further improvement of the output performance is still required for usage toward practical applications for the next-generation of IoT devices. In this review article, surface nanostructure modification methods for high-performance triboelectric nanogenerators are systematically summarized. The field is deeply reviewed, with the methods classified into four categories: templating method, appending method, etching method, and crumpling method. Finally, an in-depth discussion of the existing challenges and the direction of future efforts for enhancing TENG output performance are clearly stated, which can contribute to promoting further development of the field.

Signed languages are not as pervasive a conversational medium as spoken languages due to the history of institutional suppression of the former and the linguistic hegemony of the latter. This has led to a communication barrier between signers and non-signers that could be mitigated by technology-mediated approaches. Here, we show that a wearable sign-to-speech translation system, assisted by machine learning, can accurately translate the hand gestures of American Sign Language into speech. The wearable sign-to-speech translation system is composed of yarn-based stretchable sensor arrays and a wireless printed circuit board, and offers a high sensitivity and fast response time, allowing real-time translation of signs into spoken words to be performed. By analysing 660 acquired sign language hand gesture recognition patterns, we demonstrate a recognition rate of up to 98.63% and a recognition time of less than 1 s.

Ammonia (NH3) is mainly produced through the traditional Haber-Bosch process under harsh conditions with huge energy consumption and massive carbon dioxide (CO2) emission. The nitrogen electroreduction reaction (NERR), as an energy-efficient and environment-friendly process of converting nitrogen (N2) to NH3 under ambient conditions, has been regarded as a promising alternative to the Haber-Bosch process and has received enormous interest in recent years. Although some exciting progress has been made, considerable scientific and technical challenges still exist in improving the NH3 yield rate and Faradic efficiency, understanding the mechanism of the reaction and promoting the wide commercialization of NERR. Single-atom catalysts (SACs) have emerged as promising catalysts because of its atomically dispersed activity sites and maximized atom efficiency, unsaturated coordination environment, and its unique electronic structure, which could significantly improve the rate of reaction and yield rate of NH3. In this review we briefly introduce the unique structural and electronic features of SACs, which contributes to comprehensively understand the reaction mechanism owing to their structural simplicity and diversity, and in turn expedite the rational design of fantastic catalysts at the atomic scale. Then, we summarize the most recent experimental and computational efforts on developing novel SACs with excellent NERR performance, including precious metal-, nonprecious metal- and nonmetal-based SACs. Finally, we present challenges and perspectives of SACs on NERR, as well as some potential means for advanced NERR catalyst.

Approximately 22% of the 86 million people in the United States living with prediabetes are unaware of their condition. Detection of acetone in human respiration offers an effective and painless approach for the diagnosis of prediabetes. In this work, a wearable active acetone biosensor employing chitosan and reduced graphene oxide (RGO) as sensitive materials was developed to non-invasively diagnose prediabetes. When operated under 97.3% relative humidity at room temperature, the prepared chitosan and RGO composite film-based sensor exhibited a good sensing response of 27.89% under 10 ppm acetone in respiratory gases, which is about 5 times higher than the sensing response of pure chitosan film-based devices. In addition, finite element analysis and phase-field simulation were conducted to provide theoretical support for the active sensing mechanism. This work not only presents a wirelessly powered wearable active acetone biosensor, but also paves the way for a new method of non-invasive prediabetes diagnosis.

Gas sensors are an important part of smart homes in the era of the Internet of Things. In this work, we studied Ti-doped P-type WO3 thin films for liquefied petroleum gas (LPG) sensors. Ti-doped tungsten oxide films were deposited on glass substrates by direct current reactive magnetron sputtering from a W-Ti alloy target at room temperature. After annealing at 450 °C in N2 ambient for 60 min, p-type Ti-doped WO3 was achieved for the first time. The measurement of the room temperature Hall-effect shows that the film has a resistivity of 5.223 × 103 Ωcm, a hole concentration of 9.227 × 1012 cm−3, and mobility of 1.295 × 102 cm2V−1s−1. X-Ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) analyses reveal that the substitution of W6+ with Ti4+ resulted in p-type conductance. The scanning electron microscope (SEM) images show that the films consist of densely packed nanoparticles. The transmittance of the p-type films is between 72% and 84% in the visible spectra and the optical bandgap is 3.28 eV. The resistance increased when the films were exposed to the reducing gas of liquefied petroleum gas, further confirming the p-type conduction of the films. The p-type films have a quick response and recovery behavior to LPG.

Efficient heat removal and recovery are two conflicting processes that are difficult to achieve simultaneously. Here, in this work, we pave a new way to achieve this through the use of a smart thermogalvanic hydrogel film, in which the ions and water undergo two separate thermodynamic cycles: thermogalvanic reaction and water-to-vapor phase transition. When the hydrogel is attached to a heat source, it can achieve efficient evaporative cooling while simultaneously converting a portion of the waste heat into electricity. Moreover, the hydrogel can absorb water from the surrounding air to regenerate its water content later on. This reversibility can be finely designed. As an applicative demonstration, the hydrogel film with a thickness of 2 mm was attached to a cell phone battery while operating. It successfully decreased the temperature of the battery by 20 °C and retrieved electricity of 5 μW at the discharging rate of 2.2 C.