Surfactant effect on energy storage performance of hydrothermally synthesized Ni3V2O8.

We report a study to improve the ternary oxide Ni3V2O8's electrochemical energy storage capabilities through correct surfactanization during hydrothermal synthesis. In this study, Ni3V2O8nanomaterials were synthesized in three different forms: one with a cationic surfactant (CTAB), one with an anionic surfactant (SLS), and one without any surfactant. FESEM study reveals that all the synthesized Ni3V2O8nanomaterials had a small stone-like morphology. The electrochemical study showed that anionic surfactant-assisted Ni3V2O8(NVSLS) had a maximum of 972 F g-1specific capacitance at 1 A g-1current density, whereas cationic surfactant-assisted Ni3V2O8(NVCTAB) had the lowest specific capacitance of 162 F g-1. The specific capacitance and the capacitance retention of the NVSLS(85% after 4000 cycles) based electrode was much better than that of the NVCTAB(76% after 4000 cycles) based electrode. The improved energy storage properties of the NVSLSelectrode are attributed to its high diffusion coefficient, high surface area, and enriched elemental nickel, as compared to the NVCTABelectrode. All these excellent electrochemical properties of NVSLSelectrode indicates their potential usage in asymmetric supercapacitor application.

Assessment of fish adulteration using SnO2 nanopetal-based gas sensor and machine learning.

The work presents the identification of fish adulteration and quality assessment by incorporating a chemiresistive gas sensor and machine learning (ML) techniques. Highly sensitive SnO2 nanopetals were synthesized chemically and integrated with interdigitated electrodes to fabricate a sensor device. The sensor was calibrated with formaldehyde (37 %) with a theoretical detection limit of 75 ppb and further utilized to detect the vapors emitted from fresh and formalin-adulterated fish. An extensive sensing investigation was conducted with freshly caught Rohu fish samples. The sensing behavior was examined for all the samples at different time intervals to estimate the spoilage level. The classification between fresh and adulterated fish samples was obtained with 100 % accuracy by employing ML tools. Moreover, the storage duration and spoilage level of fish samples were quantified using regression models. This work emphasizes the potential of nanomaterials combined with machine learning for the accurate detection of adulteration in food systems.

Ni6Se5, an unexplored transition metal chalcogenide of formula M(n+1)Xn(2 ≤n≤ 8), for high-performance hybrid supercapacitor and Li-ion battery application.

This work reports anin situ, one-step hydrothermal preparation procedure of a binder-free electrode growth of Ni6Se5on nickel foam (Ni6Se5/NF) with a rod-like structure. Ni6Se5is an enveloped transition metal chalcogenides of formula M(n+1)Xn(where 2 ≤n≤ 8, M is a transition metal and X is chalcogen) of the nickel selenide family. The Ni6Se5/NF electrode described here demonstrates an exceptional lifetime of 81% capacitance retention over 20000 cycles and a high specific capacitance of 473.5 Fg-1at a current density of 4 Ag-1. The Ni6Se5/NF/activated carbon asymmetric supercapacitor (SC) exhibits a remarkable 97.3 Whkg-1energy density and a 2325 Wkg-1power density. Ni6Se5served as an active electrode material in SC applications and offered exceptional power density and long cycle life. Ni6Se5/NF, used as an anode for Li-ion batteries, has a lithium storage capacity of 939.7 mAhg-1at 100 mAg-1current density. Ni6Se5's (active electrode material) excellent energy storage capability, which was previously unreported, is particularly beneficial for electrochemical energy storage device applications.

MOF-Assimilated High-Sensitive Organic Field-Effect Transistors for Rapid Detection of a Chemical Warfare Agent.

The selective and rapid detection of trace amounts of highly toxic chemical warfare agents has become imperative for efficiently using military and civilian defense. Metal-organic frameworks (MOFs) are a class of inorganic-organic hybrid porous material that could be potential next-generation toxic gas sensors. However, the growth of a MOF thin film for efficiently utilizing the material properties for fabricating electronic devices has been challenging. Herein, we report a new approach to efficiently integrate MOF as a receptor through diffusion-induced ingress into the grain boundaries of the pentacene semiconducting film in the place of the most adaptive chemical functionalization method for sensor fabrication. We used bilayer conducting channel-based organic field-effect transistors (OFETs) as a sensing platform comprising CPO-27-Ni as the sensing layer, coated on the pentacene layer, showed a strong response toward sensing of diethyl sulfide, which is one of the stimulants of bis (2-chloroethyl) sulfide, a highly toxic sulfur mustard (HD). Using OFET as a sensing platform, these sensors can be a potential candidate for trace amounts of sulfur mustard detection below 10 ppm in real time as wearable devices for onsite uses.

A simple chemical reduction approach to dope ß-FeSi2 with boron and its comprehensive characterization.

ß-FeSi2 has been doped with Boron via a novel and cost-effective chemical reduction of the glassy phase of [(Fe2O3 + 4SiO2 + B2O3 + FeBO3 + Fe2SiO4)] using Mg metal at 800 °C. Doped ß-FeSi2 has been investigated via extensive characterization and detailed analysis using first-principles calculations. The reduction in the d-spacing as can be observed from the XRD peak shift as well as the blue shift of the ß-Raman line along with the right shift of Si and Fe 2p peaks indicate the B doping. The Hall investigation basically demonstrates p-type conductivity. Hall parameters were also analyzed using thermal mobility and dual-band model. The temperature profile of RH demonstrates the contribution of shallow acceptor levels at low temperatures, whereas the deep acceptor level contributes at high temperatures. Dual-band investigation reveals a substantial increase in the Hall concentration with B doping due to the cumulative contribution of both deep and shallow acceptor levels. The low-temperature mobility profile exhibits phonon and ionized impurity scattering just above and below 75 K, respectively. Moreover, it demonstrates that holes in low-doped samples can be transported more easily than at higher B doping. From density functional theory (DFT) calculations, the origin of the dual-band model has been validated from the electronic structure of ß-FeSi2. Further, the effects of Si and Fe vacancies and B doping on the electronic structure of ß-FeSi2 have also been demonstrated. The charge transfer to the system due to B doping has indicated that an increase in doping leads to higher p-type characteristics.

Nanoinspired Biocompatible Chemosensors: Progress toward Efficient Prognosis of Arsenic Poisoning.

Diagnosing heavy metals poisoning in human beings is of paramount importance. In this work, we present the design of a biocompatible FexNi(1-x)O hierarchical nanostructure-based sensor for ultraselective detection of arsenate (As(V)) ions in biological environments (e.g., body fluids, blood plasma, etc.). A novel iron doping technique was employed to fabricate the nanostructures rich with Fe cores to induce ultraselectivity toward arsenates. These nanostructures were used as dispersed markers and thin films deposited on Si/SiO2 substrates to support in vivo and in vitro detection of As(V) ions. The device demonstrated excellent sensitivity with a maximum response of 64.7% (for 1000 ppm As(V) ions) with a limit of detection of 1 ppb in blood plasma. The sensor's response time (τr) was 5 s with 95.48% recovery with a maximum error of ±0.549% after three washes. The device showed excellent response stability for 63 days with a maximum error of ±1.27%. The sensor devices were highly reproducible, with a maximum variation of ±0.6% in response for a batch of four devices. Due to Fe doping, the nanostructures in suspension demonstrated as arsenate markers with excellent cytocompatibility (with dosage up to 1 mg/mL) for human umbilical vein endothelial cells and 3T3 fibroblasts (LDH < 120 and cell viability ∼80%) till 48 h of incubation. The sensing mechanism suggested that the nanostructures not only detect arsenates but also prevent their substantial reduction to arsenites under anoxic environments. Thus, the sensors may show considerable progress toward early arsenate detection in living systems.

Ultra-selective tin oxide-based chemiresistive gas sensor employing signal transform and machine learning techniques.

Selective detection of gases has been a major concern among metal-oxide based chemiresistive gas sensors due to their intrinsic cross-sensitivity. In this endeavor, we report integration of single metal-oxide based chemiresistive sensor with different soft computing tools to obtain perfect recognition of tested analyte molecules by means of signal processing, feature extraction and machine learning. The fabricated sensor device consists of SnO2 hollow-spheres as the sensing material, which was synthesized chemically. A remarkable gas sensing performance has been observed towards every target volatile organic compound (VOC); which exhibits the sensor having cross-sensitivity. The transient response curves obtained from the sensor were processed using fast Fourier transform (FFT) and discrete wavelet transform (DWT) to squeeze out distinct characteristic features associated with each tested VOC. The signal transform tools were taken in a comparative fashion to examine their credibility in terms of feature extraction and assistance for pattern recognition. The extracted features were assigned as input information to the machine learning algorithms in a supervised manner to discriminate among the tested VOCs qualitatively. Moreover, a quantitative estimation of concentration for corresponding VOCs was also obtained with acceptable accuracy. The main highlight of the paper is the vigilant and efficient selection of features from the transformed signal which adequately allows the machine learning algorithms to achieve excellent classification (best average accuracy: 96.84%) and quantification. The collective results promote a step towards the realization of an automated and real-time detection.

Structurally modified V2O5based extrinsic pseudocapacitor.

Rapidly changing demand on energy storage systems makes it essential to redesign the device architecture and materials required to fabricate the devices. It is crucial to introduce capacitive behaviour in a conventional energy storage device (batteries) to improve the lifetime and power efficiency of the hole energy storage system. The charge storing nature of electrode material primarily depends on particle size, grain size, the electrode's chemical structure, and effective diffusion lengths for electrolytes within the electrode. Here V2O5based Li-ion battery electrode is transformed into a Li-ion pseudocapacitive electrode by structural modifications. The modified structures are achieved by optimizing reaction pressure to obtain larger, medium and smaller V2O5particles (namely, V2O5-L, V2O5-M and V2O5-S). As a result, the plateau regions in galvanostatic charge-discharge plots and highly intense redox peaks in the CV plots of V2O5-L get flattened for V2O5-S. Also, the lucrative improvement in rate capabilities and stability for V2O5-S indicates induced pseudocapacitance in V2O5. Some devices are fabricated with the extrinsic pseudocapacitive material (V2O5-S), providing 4.36 mWh cm-3volumetric energy density with 125 mW cm-3volumetric power density. The device retains around 95% of its initial capacitance after 10k cycles and holds up to 63% after 25k stability cycles.

Substitutional Doping of MoS2 for Superior Gas-Sensing Applications: A Proof of Concept.

Two-dimensional layered materials (like MoS2 and WS2) those are being used as sensing layers in chemoresistive gas sensors suffer from poor sensitivity and selectivity. Mere surface functionalization (decorating of material surface) with metal nanoparticles (NPs) might not improve the sensor performance significantly. In this respect, doping of the layered material can play a significant role. Here, we report a simple yet effective substitutional doping technique to dope MoS2 with noble metals. Through various material characterization techniques like X-ray diffraction, scanning tunneling spectroscopy images, and selected area electron diffraction pattern, we were able to put forward the difference between surface decoration and substitutional doping by Au at S-vacancy sites of MoS2. Lattice strain was found to exist in the Au-doped MoS2 samples, while being absent in the Au NP-decorated samples. Surface chemistry studies performed using X-ray photoelectron spectroscopy showed a shift of Mo 3d peaks to lower binding energies, thus realizing p-type doping due to Au. The blue shift of the peaks as observed in Raman spectroscopy further confirmed the p-type doping. We found that gold-doped MoS2 was more sensitive and selective toward ammonia (with a response of 150% for 500 ppm of ammonia at 90 °C) as compared to gold NP-decorated MoS2. The advantages of substitutional doping and the gas-sensing mechanism were also explained by the density functional theory study. From the first principles study, it was found that the adsorption of Au atoms on the S-vacancy site of a monolayer of the MoS2 sheet was thermodynamically favorable with the adsorption energy of 2.39 eV. We also successfully doped MoS2 with Pt using the same technique. It was found that Pt-doped MoS2 gives huge response toward humidity (60,000% at 80% relative humidity). Thus, various noble metal doping of MoS2 selectively improved the sensing response toward specific analytes. From this work, we believe that this method could also be useful to dope other layered nanomaterials to design gas sensors with improved selectivity.

Selective Discrimination of VOCs Applying Gas Sensing Kinetic Analysis over a Metal Oxide-Based Chemiresistive Gas Sensor.

Semiconducting metal oxide-based gas sensors have inadequate selectivity as they are responsive toward a variety of gases. Here, we report the implementation of gas sensing kinetic analysis of the sensor to identify the tested volatile organic compounds (VOCs) (2-propanol, formaldehyde, methanol, and toluene) precisely. A single chemiresistive sensor was employed having tin oxide-based hollow spheres as the sensing material, which were obtained by chemical synthesis. The gas sensing measurements were conducted in a dynamic manner where the sensor displayed excellent response with high sensitivity. Eley-Rideal model was adopted to obtain the kinetic properties of the gas sensing phenomenon through theoretical fitting of response transient curves and their corresponding kinetic parameters. The calculated characteristic kinetic properties were further examined to discriminate among different VOCs. The approach of using gas sensing kinetic analysis for multiple gas discrimination is an attractive solution to mitigate the problem of cross-sensitivity for resistive gas sensors.

Voltage-controlled NiO/ZnO p-n heterojunction diode: a new approach towards selective VOC sensing.

Metal oxide resistive gas sensors suffer from poor selectivity that restricts their practical applicability. Conventional sensor arrays are used to improve selectivity which increased the system complexity. Here, we have proposed a novel NiO/ZnO-based p-n junction single-diode device for selective sensing of several volatile organic compounds (VOCs) simultaneously by tuning bias voltage. The operating voltage was varied between 3 and 5 volts to achieve selective sensing of 2-propanol (19.1 times for 95 ppm with response and recovery times of 70 s and 55 s respectively' at 3 volts), toluene (20.1 times for 95 ppm with response and recovery times of 100 s and 60 s respectively, at 4 volts), and formaldehyde (11.2 times for 95 ppm with response and recovery times of 88 s and 54 s respectively, at 5 volts). A probable mechanism of the tunable selectivity with operating bias voltage due to increase in surface carriers with increasing voltage was hence put forth. Thus, this device may play an important role to develop future selective multiple VOC sensor thereby replacing standard sensor arrays.

Quantum capacitance tuned flexible supercapacitor by UV-ozone treated defect engineered reduced graphene oxide forest.

A forest like 3D carbon structure formed by reduced graphene oxide (RGO) was prepared to use as an electrode material for a highly power efficient supercapacitor. To improve the specific energy of the electrode, pore like defects were incorporated on the RGO forests by atomic oxygen etching, during the UV-ozone treatment. The modified surface helps to increase the net capacitance by permitting the electrolyte to the inner core of the active material and improving the minimal quantum capacitance. Density functional theory based first principle studies were carried out to find DOS at the Fermi level of defect induced RGO sheet and hence to validate the effect of quantum capacitance on net capacitance. Specific capacitance of RGO forest was increased by almost 150% after introduction of the defects. The best performing material exhibits 18.87 mF cm-2 areal capacitance at 2 mA cm-2 current density which is equivalent to 70 F cm-3 at 3.7 A cm-3 current density, and it was used to fabricate the supercapacitor. Two supercapacitors were fabricated, (i) on graphite sheet (non-flexible) and (ii) on scotch tape (flexible). Here PVA-KOH gel soaked filter paper was used as electrolyte-separator. Both the prepared supercapacitors on graphite sheet and scotch tape are able to transfer electrical energy with ultra high specific power (656.25 mW cm-3 and 164.06 mW cm-3 respectively) while maintaining moderate energy densities. The first device can withstand its primary capacitance by 90% even after 10 K charge-discharge cycles and the flexible device was able to hold 96% of its capacitance after 1 K bending cycles.

Pt decorated MoS2 nanoflakes for ultrasensitive resistive humidity sensor.

In this work, we report the fabrication of a low power, humidity sensor where platinum nanoparticles (NPs) decorated few-layered molybdenum disulphide (MoS2) nanoflakes have been used as the sensing layer. A mixed solvent was used to exfoliate the nanoflakes from the bulk powder. Then the Pt/MoS2 composites were prepared by reducing Pt NPs from chloroplatinic acid hexahydrate using a novel reduction technique using sulphide salt. The successful reduction and composite preparation were confirmed using various material characterization tools like scanning electron microscopy, atomic force microscopy, transmission electron microscopy, x-ray diffraction, x-ray photoelectron spectroscopy, Raman spectroscopy and UV-visible spectroscopy. The humidity sensors were prepared by drop-coating the Pt-decorated MoS2 on gold interdigitated electrodes and then exposed to various levels of relative humidity (RH). Composites with different weight ratios of Pt were tested and the best response was shown by the Pt/MoS2 (0.25:1) sample with a record high response of ∼4000 times at 85% RH. The response and recovery times were ∼92 s and ∼154 s respectively with repeatable behaviour. The sensor performance was found to be stable when tested over a few months. The underlying sensing mechanisms along with detailed characterization of the various composites have been discussed.

Liquid exfoliated pristine WS2 nanosheets for ultrasensitive and highly stable chemiresistive humidity sensors.

WS2 nanosheets have been synthesized by ultrasonication in a binary mixture of acetone and 2-propanol, with a volume ratio of 80:20. Hansen solubility parameters were taken into consideration as part of the process. These nanosheets have been characterized by electron microscopy, atomic force microscopy, and x-ray diffraction, along with spectroscopy such as ultraviolet-visible spectroscopy, Raman spectroscopy, and x-ray photoelectron spectroscopy. The nanosheets were further used as a sensing material to fabricate a humidity sensor on interdigitated aluminum electrodes, realized over Si/SiO2 substrate using a conventional photolithography technique. The response for our sensor varied from 11.9 for 40% RH to as high as 37.5 for 80% RH. Response and recovery time were found to be 13 ± 2 s and 17 ± 2 s respectively. The suspended nanosheets were also treated with UV light in a nitrogen environment. The response for UV treated nanosheets shows better linearity, however its response decreases in the presence of humidity. This is due to a decrease in oxygen content of the UV treated sample. Furthermore, the effect of sonication time has been investigated, and it was found that samples with 10 h sonication are better than others due to their high surface-to-volume ratio. The repeatability and stability of the sensor have been investigated and found to be excellent. The hysteresis in the sensors was also explored. The mechanism of humidity sensing has been discussed in detail.

Hierarchical nanostructured WO3-SnO2 for selective sensing of volatile organic compounds.

It remains a challenge to find a suitable gas sensing material that shows a high response and shows selectivity towards various gases simultaneously. Here, we report a mixed metal oxide WO3-SnO2 nanostructured material synthesized in situ by a simple, single-step, one-pot hydrothermal method at 200 °C in 12 h, and demonstrate its superior sensing behavior towards volatile organic compounds (VOCs) such as ammonia, ethanol and acetone. SnO2 nanoparticles with controlled size and density were uniformly grown on WO3 nanoplates by varying the tin precursor. The density of the SnO2 nanoparticles on the WO3 nanoplates plays a crucial role in the VOC selectivity. The responses of the present mixed metal oxides are found to be much higher than the previously reported results based on single/mixed oxides and noble metal-doped oxides. In addition, the VOC selectivity is found to be highly temperature-dependent, with optimum performance obtained at 200 °C, 300 °C and 350 °C for ammonia, ethanol and acetone, respectively. The present results on the cost-effective noble metal-free WO3-SnO2 sensor could find potential application in human breath analysis by non-invasive detection.