Sea urchin inspired ultrafast response low humidity sensor based on ionic liquid modified UiO-66 with advanced applications.

Numerous applications require low humidity sensors that not only sensitive but also stable, small hysteresis, high resolution and fast response. However, most reported low humidity sensors cannot possess these properties at the same time. In this work, inspired by sea urchin, we developed an ionic liquid (IL) modified metal organic framework (UiO-66) based low humidity sensor. Owing to the synergistic effect of the hydrophilicity and ionic conductivity of IL and the steric hindrance effects of UiO-66, the optimized low humidity sensor simultaneously exhibits high response (47.5), small hysteresis (0.3 % RH), ultrafast response speed (0.2 s), high resolution (1 % RH), and excellent long-term stability (>120 days). In particular, the sensor has been proved to have potential applications in visual humidity detection and water source location. This work provides a preliminary design principle that will contribute to the preparation of high-performance low humidity sensing materials.

Pt Loading of Phosphorus-Doped Carbon Nanotube Aerogels in Fuel Cell-Type Gas Sensors for Ultrasensitive H2 Detection.

A phosphorus-doped carbon nanotube (CNT) aerogel as the support material was loaded with Pt nanoparticles in fuel cell-type gas sensors for ultrasensitive H2 detection. The high surface area of the CNT scaffold is favorable to providing abundant active sites, and the high electrical conductivity facilitates the transport of carriers generated by electrochemical reactions. In addition, the CNT aerogel was doped with phosphorus (P) to further enhance the conductivity and electrochemical catalytic activity. As a result, the fuel cell-type gas sensor using the Pt/CNT aerogel doped with the optimal P content as the sensing material shows considerable performance for H2 detection at room temperature. The sensor exhibits an ultrahigh response of -921.9 µA to 15,000 ppm of H2. The sensitivity is -0.063 µA/ppm, which is 21 times higher than that of the conventional Pt/CF counterpart. The sensor also exhibits excellent repeatability and humidity resistance, as well as fast response/recovery; the response/recovery times are 31 and 4 s to 3000 ppm of H2, respectively. The modulation of the structure and catalytic properties of the support material is responsible for the improvement of the sensor performance, thus providing a feasible solution for optimizing the performance of fuel cell-type gas sensors.

Reply to the Comment on "Understanding the Increasing Trend of Sensor Signal with Decreasing Oxygen Partial Pressure by a Sensing-Reaction Model Based on O2- Species".

In our recent work (ACS Sens.2022, 7, 1095-1104), Mirabella et al. provided comments on our publication, mainly focusing on the controversy between the oxygen vacancy model and the ionosorbed model and the related derivation based on the law of mass action. Herein we explain the correlation between the ionosorption model and the oxygen vacancy model and provide a brief introduction of our view on these two models. Moreover, a more detailed derivation about the law of mass action is provided to explain the relationship between surface electron concentration, oxygen partial pressure, adsorbed oxygen density, and oxygen vacancy density.

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.

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.

Understanding the Increasing Trend of Sensor Signal with Decreasing Oxygen Partial Pressure by a Sensing-Reaction Model Based on O2- Species.

Although the increasing trend of sensor signal with decreasing oxygen partial pressure was observed quite early, the underlying mechanism is still elusive, which is a hindrance to accurate gas detection under varying oxygen partial pressure. In this work, a sensing model based on previous experimental and theoretical results is proposed, in which the O2- species is determined to be the main oxygen species because O- species has not been observed by direct spectroscopic studies. On this basis, combined with the band bending of SnO2 at different oxygen partial pressures, the functional relationship between the surface electron concentration, oxygen partial pressure, and reducing gas concentration is established, which includes three forms corresponding to the depletion layer, accumulation layer, and flat band. In the depletion layer case, the variation of the sensor resistance to different concentrations of CO and oxygen can be well fitted with our function model. Besides, this model predicts that the response of sensors will no longer maintain the increasing trend in an extremely hypoxic atmosphere but will decrease and approach 1 with the background oxygen content further going down to 0.

Highly Selective Mixed Potential Methanol Gas Sensor Based on a Ce0.8Gd0.2O1.95 Solid Electrolyte and Au Sensing Electrode.

A Ce0.8Gd0.2O1.95-based mixed potential type sensor attached with a commercially available Au paste sensing electrode material was fabricated to detect methanol. The optimum working temperature of the sensor was 545 °C, and the response value to 100 ppm methanol was -53 mV. The selectivity of the sensor was poor. The addition of a 4A molecular sieve filter layer and the method of pattern recognition were combined to improve it. Only gas molecules smaller than the pore diameter of the 4A molecular sieve were able to pass through the zeolite channel, and the selectivity coefficient of the sensor to methanol was improved by adding the filter layer. Meanwhile, there was an obvious distinction between the response and recovery times of the sensor toward methanol, ethanol, acetone, n-butanol, and n-pentanol. Next, the pattern recognition method was adopted. The relationship between the response value and the logarithm of gas concentration and the relationship between the maximum rate of the response process and the gas concentration were plotted separately. By comprehensively considering the two characteristic parameters of the response value and the maximum value of the differential response signal, the purpose of qualitative identification of gas types and quantitative analysis of gas concentrations was hopefully achieved.

Room-Temperature Mixed-Potential Type ppb-Level NO Sensors Based on K2Fe4O7 Electrolyte and Ni/Fe-MOF Sensing Electrodes.

Portable and sensitive mixed-potential type solid-state electrolyte (MPSE) gas sensors can detect exhaled biomarkers in a noninvasive and inexpensive way, which is significant for convenient disease diagnosis and saving medical resources. However, high working temperature is still one of the main bottlenecks for hindering MPSE gas sensors' applications in disease diagnosis. Here, we, for the first time, developed and fabricated new room-temperature MPSE gas sensors utilizing K2Fe4O7 electrolyte and Ni/Fe-MOF (Ni/Fe clusters are coordinated with 1,4-H2BDC) sensing electrodes (SEs) for the detection of ppb-level NO. Among different MOF SEs, the sensor attached with the Ni-MOF SE presents the highest NO sensitivities. This is attributed to a reducing oxygen reduction reaction activity and enhancing NO electrochemical catalytic reaction activity, verified by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) tests. In addition, the presented sensor also shows a low detection limit (20 ppb), fast response/recovery characteristic (17 s/6 s to 50 ppb NO), excellent selectivity, acceptable repeatability, and long-term stability of 34 days to NO at 25 °C and 60%RH. Simultaneously, the mechanism of humidity effect on the sensing performance was investigated by EIS and CV tests. Our work provides new insight into the development of room-temperature solid-state electrolyte gas sensors based on the mixed-potential mechanism and enlarges the potential application domain.

Machine Learning-Assisted Development of Sensitive Electrode Materials for Mixed Potential-Type NO2 Gas Sensors.

Yttrium-stabilized zirconia (YSZ)-based mixed potential-type NOx sensors have broad application prospects in automotive exhaust gas detection. Great efforts continue to be made in developing high-performance sensitive electrode materials for mixed potential-type NO2 gas sensors. However, only five kinds of new sensing electrode materials have been developed for this type of gas sensor in the last 3 years. In this work, four different tree-based machine learning models were trained to find potentially sensitive electrode materials for NO2 detection. More than 400 materials were selected from 8000 materials by the above machine learning models. To further verify the reliability of the model, 13 of these materials containing unexploited elements were selected as sensitive electrode materials for making sensors and testing their gas-sensing performances. The experimental results showed that all 13 materials exhibited good gas-sensing performance for NO2. More interestingly, an electrode material BPO4, which does not contain any metal elements, was also screened out and showed good sensing properties to NO2. In a short period of time, 13 new sensitive electrode materials for NO2 detection were targeted and screened, which was difficult to achieve by a trial-and-error procedure.

Highly sensitive detection of Pb2+ and Cu2+ based on ZIF-67/MWCNT/Nafion-modified glassy carbon electrode.

A series of different facile modification layers (MLs) was designed to gradually increase the electrochemical sensing performance of glassy carbon electrode (GCE) for simultaneously detecting Pb2+ and Cu2+. ML designs were mainly a different combination of ZIF-67, MWCNT and Nafion, and their different electrochemical sensing performances were investigated by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), square wave stripping voltammetry (SWSV) and chronocoulometry. The fabricated sensor, which modified with ZIF-67/MWCNT and Nafion layer, exhibited the biggest response peak current to Pb2+ and Cu2+. In addition, it displayed a wide linear detection range of 1.38 nM-5 µM for Pb2+ and 1.26 nM-5 µM for Cu2+, a detection accuracy of about 1 nM for both Pb2+ and Cu2+, and an excellent stability for both Pb2+ and Cu2+. We also analyzed the real water sample taken from Changchun's Sanjia Lake and Yan Lake. We believe this ML design provides instruction for building high-performance electrochemical sensing systems.

Insight into the effect of the continuous testing and aging on the SO2 sensing characteristics of a YSZ (Yttria-stabilized Zirconia)-based sensor utilizing ZnGa2O4 and Pt electrodes.

In this paper, YSZ-based mixed potential SO2 sensor with ZnGa2O4 and Pt electrodes was developed and the effect of the continuous testing and aging process on the sensing characteristics was discussed. The results showed that with this process the response of the sensor to SO2 performed an opposite direction to that in the sensor's initial state. The reason might be that the PtS produced at the Pt electrode increased the electrochemical catalytic activity of the Pt electrode, leading to the mixed potential of the Pt electrode higher than that of the ZnGa2O4 electrode. XPS and EDS results proved that a lot of Pt2+ and S2- were produced at Pt electrode after this process. Moreover, vulcanized sensor also performed similar sensing properties to the above aging sensor, which indicated that the produced PtS should be the reason that the sensor performed reverse deflection on sensing properties. In addition, the sensor after sulfuration can detect 0.05-500 ppm SO2 with the sensitivity being 5 mV/decade to 0.05-1 ppm and 41 mV/decade to 1-500 ppm. The sensor also had a reliable stability during the continuous measurement.

Fluorescent hydrogel test kit coordination with smartphone: Robust performance for on-site dimethoate analysis.

Precise monitoring of pesticide with portable device was challenging because it required high sensitivity, short response time, strong stability and excellent selectivity. Herein, we newly constructed a stimuli-responsive hydrogel (SRHg)-based portable kit by embedding copper nanoparticles (CuNPs) in agarose hydrogel. In this work, dimethoate as inhibitor of urease restrained the generation of ammonia, which reduced in-situ etching of CuNPs, resulting in the fluorescence color response of test kit under ultraviolet illumination. Interestingly, by means of smartphone-based nanocolorimetry, the photo image of portable kit could be translated into digital information using ImageJ software, achieving a direct quantitative tool for dimethoate identification. The simplicity of SRHg-based portable kit combined with smartphone-based color recognition not only improved the analysis sensitivity (detection limit of 1.0 µg L-1), accuracy and stability, but also simplified operation process and shortened sample-to-answer analysis time (55 min), demonstrating that the methodology met the needs of daily testing and provided a new sight for on-site monitoring of food safety and human health.

Enhanced resistive acetone sensing by using hollow spherical composites prepared from MoO3 and In2O3.

Hollow sphere composites were synthesized by a template-free hydrothermal method from MoO3 and In2O3. The spheres have a typical size of 800 ± 50 nm and were characterized by XRD, FESEM, TEM, XPS. Gas sensors based on samples with different Mo/In composite ratios were fabricated and their gas sensing properties were studied. The results show that a Mo:In ratio of 1:1 in the composite gives the highest response, typically at a working temperature of 250 °C. The response increases to 38 when exposed to 100 ppm acetone at 250 °C. This is 13.6 times better than when using pure MoO3. The sensor shows improved selectivity, response, repeatability and long-term stability. Typical features include a large specific surface area, and high levels of chemisorbed oxygen and defective oxygen sites. The N-N heterojunction theory was used to explain the improvement of gas sensing performance. Graphical abstract Schematic presentation of MoO3 and In2O3 composites and response test graph for 100 ppm acetone. The sensor based on this composite exhibits a very high response (38) to acetone at 250 °C and very fast response time (2 s).

Protein-Inorganic Hybrid Nanoflower-Rooted Agarose Hydrogel Platform for Point-of-Care Detection of Acetylcholine.

Rapid and precise profiling of acetylcholine (ACh) has become important for diagnosing diseases and safeguarding health care because of its pivotal role in the central nervous system. Herein, we developed a new colorimetric sensor based on protein-inorganic hybrid nanoflowers as artificial peroxidase, comprising a test kit and a smartphone reader, which sensitively quantifies ACh in human serum. In this sensor, ACh indirectly triggered the substrate reaction with the help of a multienzyme system including acetylcholinesterase, choline oxidase, and mimic peroxidase (nanoflowers), accompanying the enhancement of absorbance intensity at 652 nm. Therefore, the multienzyme platform can be used to detect ACh via monitoring the change of the absorbance in a range from 0.0005 to 6.0 mmol L-1. It is worth mentioning that the platform was used to prepare a portable agarose gel-based kit for rapid qualitative monitoring of ACh. Coupling with ImageJ program, the image information of test kits can be transduced into the hue parameter, which provides a directly quantitative tool to identify ACh. Based on the advantages of simple operation, good selectivity, and low cost, the availability of a portable kit for point-of-care testing will achieve the needs of frequent screening and diagnostic tracking.

Sensitive colorimetric sensor for point-of-care detection of acetylcholinesterase using cobalt oxyhydroxide nanoflakes.

Point-of-care monitoring of acetylcholinesterase (AChE) is of significant importance for pesticide poisoning and disease diagnosis because it plays a pivotal role in biological nerve conduction systems. Herein, we designed a colorimetric strategy for the facile and accurate detection of AChE based on tandem catalysis with a multi-enzyme system, which is constituted by cobalt oxyhydroxide nanoflakes (CoOOH NFs) and choline oxidase (CHO). In this sensor, AChE catalytically hydrolyzed acetylcholine (ACh) to produce choline, which was further efficiently oxidized by CHO to yield H2O2. CoOOH NFs, as a nanozyme, efficiently catalyzed 3,3',5,5'-tetramethylbenzidine (TMB) into blue oxTMB with the help of H2O2, accompanied by an enhancement of absorbance intensity. The resulting intensity could be employed as the signal output of the CHO/CoOOH/ACh system in monitoring AChE. Under optimal conditions, the developed sensor possessed a sensitive response to AChE with a detection limit of 33 µU mL-1. Interestingly, the proposed platform was applied to fabricate a paper-based sensor for rapidly recognizing AChE by direct observation with the naked eyes. Combined with a smartphone and ImageJ software, we further developed an image-processing algorithm for the quantitative detection of AChE with highly promising results, which validated the outstanding potential of on-site application in clinical diagnostics and pesticide poisoning.

Preparation of silver-loaded titanium dioxide hedgehog-like architecture composed of hundreds of nanorods and its fast response to xylene.

Hedgehog-like titanium dioxide (TiO2) architectures composed of hundreds of one-dimensional (1D) nanorods and silver (Ag) loaded TiO2 with different amounts (0.2 at%, 0.5 at% and 1 at%) were successfully prepared by facile hydrothermal process and simple isometric impregnation route. The high electron mobility of 1D nanorods on the surface of TiO2 and the high porosity of Ag loaded hedgehog-like TiO2 architectures enable the sensor with fast responsive and recovered properties. TiO2 loaded with 0.5 at% Ag exhibited the highest response to xylene with low response/recovery time at the operating temperature of 375 °C. In addition, the sensitivity and selectivity of the TiO2 sensor were enhanced markedly with Ag loading.

Gas sensor based on samarium oxide loaded mulberry-shaped tin oxide for highly selective and sub ppm-level acetone detection.

Mulberry-shaped tin oxide (SnO2) hierarchical architectures and samarium oxide (Sm2O3) loaded tin oxide with different amounts (0.5, 1, 2.5, and 4 mol% Sm2O3) were successfully synthesized by facile hydrothermal synthesis method and simple isometric impregnation method. The gas sensing performance of the sensors based on pure SnO2 and Sm2O3 loaded SnO2 materials were systematically investigated. The results indicated that Sm2O3 loading considerably affected the improvement of the sensing performance of the SnO2 sensor. The 2.5 mol% Sm2O3/SnO2 exhibited the highest response (41.14) to 100 ppm acetone, the response was 2.29 times higher than that of pure SnO2 (18). In addition, with 2.5 mol% Sm2O3 loading, the low detection threshold of the sensor dropped from 500 ppb to 100 ppb. The enhanced gas sensing performance was mainly bacause of the increased oxygen vacancies created by the substitution of samarium in the SnO2 lattice, which enhanced the adsorption of oxygen and the exceptional catalytic effect of Sm2O3.

Metal-organic frameworks derived tin-doped cobalt oxide yolk-shell nanostructures and their gas sensing properties.

Yolk-shell nanomaterials with controlled morphology have received great attention because of their promising applications in gas sensing. Here, we reported the facile synthesis of pure and 1-5 mol% Sn doped Co3O4 yolk-shell nanostructures by calcinating the Co based metal-organic framework (MOF, ZIF-67) prepared from hydrothermal method. The morphologies of the as-obtained samples were characterized by various experimental techniques. Furthermore, the gas sensing properties were systematically measured. Gas sensors based on 3 mol% Sn doped Co3O4 yolk-shell nanostructures exhibited extremely enhanced response to ethanol at 200 °C (Rg/Ra = 13.4-100 ppm at 200 °C) and low detection limit (Rg/Ra = 1.3-1 ppm ethanol at 200 °C). Most importantly, the gas response to 100 ppm ethanol is still maintained well after continuous measurement for 20 days.

Flower-like In2O3 modified by reduced graphene oxide sheets serving as a highly sensitive gas sensor for trace NO2 detection.

In this work, we described gas sensors based on the materials composed of hierarchical flower-likeIn2O3 and reduced graphene oxide (rGO), which were fabricated by a facile one-step hydrothermal method. The rGO-In2O3 composites exhibited enhanced sensing performance towards NO2 through comparison with the pure In2O3 sample. The operating temperature can be tuned by the percentage of rGO in the composites. The sensor based on 5wt% rGO-In2O3 could work at room temperature with a high response value to 1ppm NO2. 3wt% rGO-In2O3 composite was adopted for the ultra-sensitivity gas sensor owing to its extremely low limit of detection of 10ppb with rapid response time to NO2. The sensor also exhibited excellent selectivity and stability. The ultra-sensitivity of rGO-In2O3 should be related to synergistic effect of the hierarchical structure of In2O3 and the presence of rGO in the composites, which provided enhanced surface area and local p-n heterojunctions in rGO/In2O3 composites.

Acetone gas sensor based on NiO/ZnO hollow spheres: Fast response and recovery, and low (ppb) detection limit.

NiO/ZnO composites were synthesized by decorating numerous NiO nanoparticles on the surfaces of well dispersed ZnO hollow spheres using a facile solvothermal method. Various kinds of characterization methods were utilized to investigate the structures and morphologies of the hybrid materials. The results revealed that the NiO nanoparticles with a size of ∼10nm were successfully distributed on the surfaces of ZnO hollow spheres in a discrete manner. As expected, the NiO/ZnO composites demonstrated dramatic improvements in sensing performances compared with pure ZnO hollow spheres. For example, the response of NiO/ZnO composites to 100ppm acetone was ∼29.8, which was nearly 4.6 times higher than that of primary ZnO at 275°C, and the response/recovery time were 1/20s, respectively. Meanwhile, the detection limit could extend down to ppb level. The likely reason for the improved gas sensing properties was also proposed.