Confinement Enrichment Effect in HoMS-BaTiO3 Microwave Gas Sensors for the Detection of 10 ppb-0.55 v/v% Ammonia at Room Temperature.

The construction of ammonia gas sensors with wide detection ranges is important for exhalation diagnosis and environmental pollution monitoring. To achieve a wide detection range, sensitive materials must possess excellent spatial confinement and large active surfaces to enhance gas adsorption. In this study, an ammonia microwave gas sensor with a wide detection range of 10 ppb-0.55 v/v% at room temperature was fabricated by incorporating hollow multishelled-structured BaTiO3 (HoMS-BaTiO3). The effect of the number of shells and the quantity of the sensitive material on the gas-sensing performance was investigated, and two-layered HoMS-BaTiO3 demonstrated the best response at high concentrations (0.15-0.55 v/v%). Conversely, single-layered HoMS-BaTiO3 displayed outstanding performance at low concentrations (10 ppb-0.15 v/v%). The lower the quantity of the sensitive material, the higher the response. This study offers a method for preparing room-temperature ammonia sensors with a wide detection range and reveals the link between the structure and quantity of sensitive materials and gas-sensing performance.

Pd@Pt Core-Shell Nanocrystal-Decorated ZnO Nanosheets for ppt-Level NO2 Detection.

Bimetallic nanocrystals (NCs) have obtained significant attention due to their unique advantages of the intrinsic properties of individual metals and synergistic enhancements resulting from the electronic coupling between two constituent metals. In this work, Pd@Pt core-shell NCs were prepared through a facile one-pot solution-phase method, which had excellent dispersion and uniform size. Concurrently, ZnO nanosheets were prepared via a hydrothermal method. To explore their potential in nitrogen dioxide (NO2) gas sensing applications, sensitive materials based on ZnO nanosheets with varying mass percentages of Pd@Pt NCs were generated through an impregnation process. The sensor based on 0.3 wt % Pd@Pt-ZnO exhibited remarkable performance, demonstrating a substantial response (Rg/Ra = 60.3) to 50 ppb of NO2 at a low operating temperature of 80 °C. Notably, this sensor reached an outstanding low detection limit of 300 ppt. The enhancement in gas sensing capabilities can be attributed to the sensitization and synergistic effects imparted by the exceptional catalytic activity of Pd@Pt NCs, which significantly promoted the reaction. This research introduces a novel approach for the utilization of core-shell structured bimetallic nanocrystals as modifiers in metal-oxide-semiconductor (MOS) materials for NO2 detection.

Mixed Potential Type Isoprene Sensor for the Application in Real-Time Monitoring of Biomarker Gases.

Monitoring of isoprene in exhaled breath is expected to provide a noninvasive and painless method for dynamic monitoring of physiological and metabolic states during exercise. However, for real-time and portable detection of isoprene, gas sensors have become the best choice for gas detection technology, which are crucial to achieving the goal of anytime, anywhere, human-centered healthcare in the future. Here, we first report a mixed potential type isoprene sensor based on a Gd2Zr2O7 solid electrolyte and a CdSb2O6 sensing electrode, which enables sensitive detection for isoprene with sensitivities of -21.2 mV/ppm and -65.8 mV/decade in the range of 0.05-1 and 1-100 ppm. The sensing behavior of the sensor follows the mixed potential sensing mechanism and was further verified by the electrochemical polarization curves. The significant differentiation between the sensor response to exhaled breath of healthy individuals and simulated breath containing different concentrations of isoprene demonstrates the potential of the sensor for the detection of isoprene in exhaled breath. Simultaneously, monitoring of isoprene during exercise signifies the feasibility of the sensor in dynamic monitoring of physiological indicators, which is not only of great significance for optimizing training and guiding therapeutic exercise intervention in sporting scenarios but also expected to help further reveal the interaction between exercise, muscle, and organ metabolism in medicine.

Ag2S-Decorated One-Dimensional CdS Nanorods for Rapid Detection and Effective Discrimination of n-Butanol.

N-butanol (C4H9OH) is a volatile organic compound (VOC) that is susceptible to industrial explosions. It has become imperative to develop n-butanol sensors with high selectivity and fast response and recovery kinetics. CdS/Ag2S composite nanomaterials were designed and prepared by the solvothermal method. The incorporation of Ag2S engendered a notable augmentation in specific surface area and a consequential narrow band gap. The CdS/Ag2S-based sensor with 3% molar ratio of Ag2S, operating at 200 °C, demonstrated a remarkably elevated response (S = Ra/Rg = 24.5) when exposed to 100 ppm n-butanol, surpassing the pristine CdS by a factor of approximately four. Furthermore, this sensor exhibited notably shortened response and recovery times, at a mere 4 s and 1 s, respectively. These improvements were ascribed to the one-dimensional single-crystal nanorod structure of CdS, which provided an effective path for expedited electron transport along its axial dimension. Additionally, the electron and chemical sensitization effects resulting from the modification with precious metal sulfides Ag2S were the primary reasons for enhancing the sensor response. This work can contribute to mitigating the safety risks associated with the use of n-butanol in industrial processes.

Imparting Chemiresistor with Humidity-Independent Sensitivity toward Trace-Level Formaldehyde via Substitutional Doping Platinum Single Atom.

The modification of metal oxides with noble metals is one of the most effective means of improving gas-sensing performance of chemiresistors, but it is often accompanied by unintended side effects such as sensor resistance increases up to unmeasurable levels. Herein, a carbonization-oxidation method is demonstrated using ultrasonic spray pyrolysis technique to realize platinum (Pt) single atom (SA) substitutional doping into SnO2 (named PtSA-SnO2 ). The substitutional doping strategy can obviously enhance gas-sensing properties, and meanwhile decrease sensor resistance by two orders of magnitude (decreased from ≈850 to ≈2 MΩ), which are attributed to the tuning of band gap and fermi-level position, efficient single atom catalysis, and the raising of adsorption capability of formaldehyde, as validated by the state-of-the-art characterizations, such as spherical aberration-corrected scanning transmission electron microscopy (Cs -corrected STEM), in situ diffuse reflectance infrared Fourier transformed spectra (in situ DRIFT), CO temperature-programmed reduction (CO-TPR), and theoretical calculations. As a proof of concept, the developed PtSA-SnO2 sensor shows humidity-independent (30-70% relative humidity) gas-sensing performance in the selective detection of formaldehyde with high response, distinguishable selectivity (8< Sformaldehyde /Sinterferant <14), and ultra-low detection limit (10 ppb). This work presents a generalized and facile method to design high-performance metal oxides for chemical sensing of volatile organic compounds (VOCs).

Zeolitic Imidazolate-Framework-Engineered Heterointerface Catalysis for the Construction of Plant-Wearable Sensors.

Plant-wearable sensors provide real-time information that enables pesticide inputs to be finely tuned and play critical roles in precision agriculture. However, tracking pesticide information in living plants remains a formidable challenge owing to inadequate shape adaptabilities and low in-field sensor sensitivities. In this study, plant-wearable hydrogel discs are designed by embedding a dual-shelled upconversion-nanoparticles@zeolitic-imidazolate-framework@polydopamine (UCNPs@ZIF@PDA) composite in double-network hydrogels to deliver on-site pesticide-residue information. Benefiting from the enzyme-mimetic catalytic activity of ZIFs and enzyme triggered-responsive property of PDA shell, the hydrogel discs are endowed with high sensing sensitivity toward 2,4-dichlorophenoxyacetic acid pesticide at the nanogram per milliliter level via boosting fluorescence quenching efficiency. Notably, hydrogel discs mounted on tomato plants exhibit sufficient adaptability to profile dynamic pesticide degradation when used in conjunction with an ImageJ processing algorithm, which is practically applicable. Such hydrogel discs form a noninvasive and low-cost toolkit for the on-site acquisition of pesticide information, thereby contributing to the precise management of the health status of a plant and the judicious development of precision agriculture.

Self-ratiometric fluorescent platform based on upconversion nanoparticles for on-site detection of chlorpyrifos.

Monitoring organophosphorus pesticides is significant for food safety assessment. Herein, we developed upconversion nanoparticles (UCNPs)-based self-ratiometric fluorescent platform for the detection of chlorpyrifos. The UCNPs have the ability to confine the detection and reference functions in one nanoparticle. Specifically, the blue upconversion (UC) emission (448 nm) in the shell layer of UCNPs is quenched by the product of the acetylcholinesterase-mediated reaction, while the red UC emission (652 nm) from the core remains constant as a self-calibrated reference signal. Employing the inhibition property of chlorpyrifos, self-proportional fluorescence is employed to detect chlorpyrifos. As proof-of-concept, test strips are fabricated by loading the UCNPs onto filter paper. Combined with the smartphone and image-processing algorithm, chlorpyrifos quantitative testing is achieved with a detection limit of 14.4843 ng mL-1. This portable platform displays anti-interference capability and high stability in the complicated matrix, making it an effective candidate for on-site application.

Self-Healing, Laminated, and Low Resistance NH3 Sensor Based on 6,6',6″-(Nitrilotris(benzene-4,1-diyl))tris(5-phenylpyrazine-2,3-dicarbonitrile) Sensing Material Operating at Room Temperature.

With the rapid development of the concept of the Internet of Things (IoT), gas sensors with the function of simulating the human sense of smell became irreplaceable as a key element. Among them, ammonia (NH3) sensors played an important role in respiration tests, environmental monitoring, safety, and other fields. However, the fabrication of the high-performance device with high stability and resistance to mechanical damages was still a challenge. In this work, polyurethane (PU) with excellent self-healing ability was applied as the substrate, and the sensor was designed from new sensitive material design and device structure optimization, through applying the organic molecule with groups which could absorb NH3 and the laminated structure to shorten the electronic transmission path to achieve a low resistance state and favorable sensing properties. Accordingly, a room temperature flexible NH3 sensor based on 6,6',6″-(nitrilotris(benzene-4,1-diyl))tris(5-phenylpyrazine-2,3-dicarbonitrile) (TPA-3DCNPZ) was successfully developed. The device could self-heal by means of a thermal evaporation assisted method. It exhibited a detection limit of 1 ppm at 98% relative humidity (RH), as well as great stability, selectivity, bending flexibility, and self-healing properties. The improved NH3 sensing performance under high RH was further investigated by complex impedance plots (CIPs) and density functional theory (DFT), attributing to the enhanced adsorption of NH3. The TPA-3DCNPZ based NH3 sensors proved to have great potential for application on simulated exhaled breath to determine the severity of kidney diseases and the progress of treatment. This work also provided new ideas for the construction of high-performance room temperature NH3 sensors.

Mixed Potential Type Acetone Sensor with Ultralow Detection Limit for Diabetic Ketosis Breath Analysis.

Breath analysis using gas sensors is an emerging method for disease screening and diagnosis. Since it is closely related to the lipid metabolism and blood ketone concentration of the body, the detection of acetone content in exhaled breath is helpful for the screening and monitoring of diabetes and ketosis. The development of an acetone sensor with high selectivity, stability, and low detection limit has been the research focus for this purpose. Here, we developed a mixed potential type acetone sensor based on Gd2Zr2O7 solid electrolyte and CoSb2O6 sensing electrode. The developed sensor exhibits an extremely low detection limit of 10 ppb, enabling linear detection for acetone in an extremely wide range of 10 ppb-100 ppm. The good results of systematic evaluation on selectivity, repeatability, and stability prove the superior reliability of the sensor, which is a prerequisite for the application in actual breath detection. The ability of the sensor to distinguish healthy people from diabetic ketosis patients was confirmed by using the sensor to detect the breath of healthy people and diabetic patients, proving the feasibility of the sensor in the diagnosis and monitoring of diabetic ketosis.

A highly efficient open-shell singlet luminescent diradical with strong magnetoluminescence properties.

Developing open-shell singlet (OS) diradicals with high luminescent properties and exceptional single-molecule magnetoluminescence (ML) performance is extremely challenging. Herein, we propose a concept to enhance luminescent efficiency by adjusting the donor conjugation of OS diradicals, thereby achieving a highly luminescent diradical, DR1, with outstanding stability and making it a viable option for use in the emitting layer of organic light-emitting diodes (OLEDs). More importantly, the 0.5 wt%-DR1 doped film demonstrates significant single-molecule magnetoluminescence (ML) properties. A giant ML value of 210% is achieved at a magnetic field of 7 T, showing the great potential of DR1 in magneto-optoelectronic devices.

Wearable Gas Sensor Based on Reticular Antimony-Doped SnO2/PANI Nanocomposite Realizing Intelligent Detection of Ammonia within a Wide Range of Humidity.

Wearable gas sensors demonstrate broad potential for environmental monitoring and breath analysis applications. Typically, they require a highly stable and high-performance flexible gas sensing unit that can work with a small, flexible circuit to enable real-time accurate concentration analysis and prediction. This work proposes a flexible gas sensor using antimony-doped tin dioxide composite polyaniline as the sensing material for room-temperature ammonia detection over a wide humidity range. The sensor exhibits high sensitivity (response value at 33.1 toward 100 ppm ammonia at 70% relative humidity), excellent selectivity, and good long-term and mechanical stability. The increased sensitivity is due to a reduction in the hole concentration of polyaniline in air, achieved through compositing and doping. Subsequently, regression analysis equations are developed to establish the relationship between the gas concentration and sensor response under varying environmental humidity conditions. The sensor was integrated with a small, low-power circuit module to form a wearable smart bracelet with signal acquisition, processing, and wireless transmission functions, which could achieve early and remote warning of gas leakage in different humidity environments. This research demonstrates a promising approach to designing high-performance, high-stability, and flexible gas sensors and their corresponding wireless sensing systems.

Pattern Recognition with Temperature Regulation: A Single YSZ-Based Mixed Potential Sensor Classifies Multiple Mixtures of Isoprene, n-Propanol, and Acetone.

Gas sensors integrated with machine learning algorithms have aroused keen interest in pattern recognition, which ameliorates the drawback of poor selectivity on a sensor. Among various kinds of gas sensors, the yttria-stabilized zirconia (YSZ)-based mixed potential-type sensor possesses advantages of low cost, simple structure, high sensitivity, and superior stability. However, as the number of sensors increases, the increased power consumption and more complicated integration technology may impede their extensive application. Herein, we focus on the development of a single YSZ-based mixed potential sensor from sensing material to machine learning for effective detection and discrimination of unary, binary, and ternary gas mixtures. The sensor that is sensitive to isoprene, n-propanol, and acetone is manufactured with the MgSb2O6 sensing electrode prepared by a simple sol-gel method. Unique response patterns for specific gas mixtures could be generated with temperature regulation. We chose seven algorithm models to be separately trained for discrimination. In order to realize more accurate discrimination, we further discuss the selection of suitable feature parameters and its reasons. With temperature regulation coefficients which are easily available as feature input to model, a single sensor is verified to achieve elevated accuracy rates of 95 and 99% for the discrimination of seven gases (three unary gases, three binary gas mixtures, and one ternary gas mixture) and redefined six gas mixtures. This article provides a potential new approach via a mixed potential sensor instead of a sensor array that could provide a wide application prospect in the field of electronic nose and artificial olfaction.

Ultrabright organic fluorescent probe for quantifying the dynamics of cytosolic/nuclear lipid droplets.

Lipid droplets (LDs) are extremely active organelles that play a crucial role in energy metabolism, membrane formation, and the production of lipid-derived signaling molecules by regulating lipid storage and release. Nevertheless, directly limited by the lack of superior fluorescent probes, studies of LDs dynamic motion velocity have been rarely reported, especially for nuclear LDs. Herein, a novel organic fluorescent probe Lipi-Bright has been rationally developed based on bridged cyclization of distyrylbenzene. The fully ring-fused molecule structure endows the probe with high photostability. Moreover, this new fluorescent probe displays the features of excellent LDs staining specificity as well as ultrahigh fluorescence brightness. Lipi-Bright labeled LDs was dozens of times brighter than representative probes BODIPY 493/503 or Nile Red. Consequently, by in-situ time-lapse fluorescence imaging, the dynamics of LDs have been quantitatively studied. For instance, the velocities of cytosolic LDs (37 ± 15 nm/s) are found to be obviously faster than those of nuclear LDs (24 ± 4 nm/s), and both the cytosolic LDs and the nuclear LDs would be moved faster or slower depend on the various stimulations. Overall, this work providing plentiful information on LDs dynamics will greatly facilitate the in-depth investigation of lipid metabolism.

Gas Sensor Array Fault Diagnosis Based on Multi-Dimensional Fusion, an Attention Mechanism, and Multi-Task Learning.

With the development of gas sensor arrays and computational technology, machine olfactory systems have been widely used in environmental monitoring, medical diagnosis, and other fields. The reliable and stable operation of gas sensing systems depends heavily on the accuracy of the sensors outputs. Therefore, the realization of accurate gas sensor array fault diagnosis is essential to monitor the working status of sensor arrays and ensure the normal operation of the whole system. The existing methods extract features from a single dimension and require the separate training of models for multiple diagnosis tasks, which limits diagnostic accuracy and efficiency. To address these limitations, for this study, a novel fault diagnosis network based on multi-dimensional feature fusion, an attention mechanism, and multi-task learning, MAM-Net, was developed and applied to gas sensor arrays. First, feature fusion models were applied to extract deep and comprehensive features from the original data in multiple dimensions. A residual network equipped with convolutional block attention modules and a Bi-LSTM network were designed for two-dimensional and one-dimensional signals to capture spatial and temporal features simultaneously. Subsequently, a concatenation layer was constructed using feature stitching to integrate the fault details of different dimensions and avoid ignoring useful information. Finally, a multi-task learning module was designed for the parallel learning of the sensor fault diagnosis to effectively improve the diagnosis capability. The experimental results derived from using the proposed framework on gas sensor datasets across different amounts of data, balanced and unbalanced datasets, and different experimental settings show that the proposed framework outperforms the other available methods and demonstrates good recognition accuracy and robustness.

Super-resolution dynamic tracking of cellular lipid droplets employing with a photostable deep red fluorogenic probe.

Lipid droplets (LDs) are critical organelles involved in many physiological processes in eukaryotic cells. To visualize and study LDs, particular the small/nascent LDs, the emerging super-resolution fluorescence imaging techniques with nanoscale resolution would be much more powerful in comparison to the conventional confocal/wide-field imaging techniques. However, directly limited by the availability of advanced LDs probes, super-resolution fluorescence imaging of LDs is a practically challenging task. In this context, a superior LDs fluorescent probe named Lipi-Deep Red is newly developed for structured illumination microscopy (SIM) super-resolution imaging. This fluorescent probe features with the advantages of strong deep red/NIR emission, fluorogenic character, high LDs specificity, and outstanding photostability. These advantages enable the fluorescent probe to be finely applied in SIM super-resolution imaging, e.g. time-lapse imaging (up to 1000 frames) to monitor the LDs dynamics at nanoscale (159 nm), two-color time-lapse imaging to discover the nearby contact/interaction between LDs and mitochondria. Consequently, the fusion processes of LDs are impressively visualized at a high spatial and temporal resolution. Two kinds of contact models between LDs and mitochondria (dynamic contact and stable contact) newly proposed in the recent literatures are successfully revealed.

A biocompatible and fully erodible conducting polymer enables implanted rechargeable Zn batteries.

Implanted rechargeable batteries that can provide energy over a sufficient lifetime and ultimately degrade into non-toxic byproducts are highly desirable. However, their advancement is significantly impeded by the limited toolbox of electrode materials with a known biodegradation profile and high cycling stability. Here we report biocompatible, erodible poly(3,4-ethylenedioxythiophene) (PEDOT) grafted with hydrolyzable carboxylic acid pendants. This molecular arrangement combines the pseudocapacitive charge storage from the conjugated backbones and dissolution via hydrolyzable side chains. It demonstrates complete erosion under aqueous conditions in a pH-dependent manner with a predetermined lifetime. The compact rechargeable Zn battery with a gel electrolyte offers a specific capacity of 31.8 mA h g-1 (57% of theoretical capacity) and outstanding cycling stability (78% capacity retention over 4000 cycles at 0.5 A g-1). Subcutaneous implantation of this Zn battery into Sprague-Dawley (SD) rats demonstrates complete biodegradation in vivo and biocompatibility. This molecular engineering strategy presents a viable avenue for developing implantable conducting polymers with a predetermined degradation profile and high energy storage capability.

Zeolites as a Class of Semiconductors for High-Performance Electrically Transduced Sensing.

Zeolites are widely used as catalysts and adsorbents in the chemical industry, but their potential for electronic devices has been stunted to date, as they are commonly recognized as electronic insulators. Here, we have for the first time demonstrated that Na-type ZSM-5 zeolites are ultrawide-direct-band-gap semiconductors based on optical spectroscopy, variable-temperature current-voltage characteristics, and photoelectric effect as well as electronic structure theoretical calculations and further unraveled the band-like charge transport mechanism in electrically conductive zeolites. The increase in charge-compensating Na+ cations in Na-ZSM-5 decreases the band gap and affects its density of states, shifting the Fermi level close to the conduction band. Remarkably, the semiconducting Na-ZSM-5 zeolites have been first applied for constructing electrically transduced sensors that can sense trace-level (77 ppb) ammonia with unprecedentedly high sensitivity, negligible cross-sensitivity, and high stability under moisture ambient conditions compared with conventional semiconducting materials and conductive metal-organic frameworks (MOFs). The charge density difference shows that the massive electron transfer between NH3 molecules and Na+ cations ascribed to Lewis acid sites enables electrically transduced chemical sensing. This work opens a new era of zeolites in applications of sensing, optics, and electronics.

Machine Learning-Assisted Volatile Organic Compound Gas Classification Based on Polarized Mixed-Potential Gas Sensors.

The performance of electrochemical gas sensors depends on the reactions at the three-phase boundary. In this work, a mixed-potential gas sensor containing a counter electrode, a reference electrode, and a sensitive electrode was constructed. By applying a bias voltage to the counter electrode, the three-phase boundary can be polarized. The polarization state of the three-phase boundary determined the gas-sensitive performance. Taking 100 ppm ethanol vapor as an example, by regulating the polarization state of the three-phase boundary, the response value of the sensor can be adjusted from -170 to 40 mV, and the sensitivity can be controlled from -126.4 to 42.6 mV/decade. The working temperature of the sensor can be reduced after polarizing the three-phase boundary, lowering the power consumption from 1.14 to 0.625 W. The sensor also showed good stability and short response-recovery time (3 s). Based on this sensor, the Random Forest algorithm reached 99% accuracy in identifying the kind of VOC vapors. This accuracy was made possible by the ability to generate several signals concurrently. The above gas-sensitive performance improvements were due to the polarized three-phase boundary.

A new organic molecular probe as a powerful tool for fluorescence imaging and biological study of lipid droplets.

Background: Lipid droplets (LDs) are critical organelles associated with many physiological processes in eukaryotic cells. To visualize and study LDs, fluorescence imaging techniques including the confocal imaging as well as the emerging super-resolution imaging of stimulated emission depletion (STED), have been regarded as the most useful methods. However, directly limited by the availability of advanced LDs fluorescent probes, the performances of LDs fluorescence imaging are increasingly unsatisfied with respect to the fast research progress of LDs. Methods: We herein newly developed a superior LDs fluorescent probe named Lipi-QA as a powerful tool for LDs fluorescence imaging and biological study. Colocalization imaging of Lipi-QA and LDs fluorescent probe Ph-Red was conducted in four cell lines. The LDs staining selectivity and the photostability of Lipi-QA were also evaluated by comparing with the commercial LDs probe Nile Red. The in-situ fluorescence lifetime of Lipi-QA in LDs was determined by time-gated detection. The cytotoxicity of Lipi-QA was assessed by MTT assay. The STED saturation intensity as well as the power- and gate time-dependent resolution were tested by Leica SP8 STED super-resolution nanoscopy. The time-lapse 3D confocal imaging and time-lapse STED super-resolution imaging were then designed to study the complex physiological functions of LDs. Results: Featuring with the advantages of the super-photostability, high LDs selectivity, long fluorescence lifetime and low STED saturation intensity, the fluorescent probe Lipi-QA was capable of the long-term time-lapse three-dimensional (3D) confocal imaging to in-situ monitor LDs in 3D space and the time-lapse STED super-resolution imaging (up to 500 STED frames) to track the dynamics of LDs with nanoscale resolution (37 nm). Conclusions: Based on the state-of-the-art fluorescence imaging results, some new biological insights into LDs have been successfully provided. For instance, the long-term time-lapse 3D confocal imaging has surely answered an important and controversial question that the number of LDs would significantly decrease rather than increase upon starvation stimulation; the time-lapse STED super-resolution imaging with the highest resolution has impressively uncovered the fission process of nanoscale LDs for the first time; the starvation-induced change of LDs in size and in speed has been further revealed at nanoscale by the STED super-resolution imaging. All of these results not only highlight the utility of the newly developed fluorescent probe but also significantly promote the biological study of LDs.