Comparison of carrier gases for the separation and quantification of mineral oil hydrocarbon (MOH) fractions using online coupled high performance liquid chromatography-gas chromatography-flame ionisation detection.

On-line coupled high performance liquid chromatography-gas chromatography-flame ionisation detection (HPLC-GC-FID) was used to compare the effect of hydrogen, helium and nitrogen as carrier gases on the chromatographic characteristics for the quantification of mineral oil hydrocarbon (MOH) traces in food related matrices. After optimisation of chromatographic parameters nitrogen carrier gas exhibited characteristics equivalent to hydrogen and helium regarding requirements set by current guidelines and standardisation such as linear range, quantification limit and carry over. Though nitrogen expectedly led to greater peak widths, all required separations of standard compounds were sufficient and humps of saturated mineral oil hydrocarbons (MOSH) and aromatic mineral oil hydrocarbons (MOAH) were appropriate to enable quantitation similar to situations where hydrogen or helium had been used. Slightly increased peak widths of individual hump components did not affect shapes and widths of the MOSH and MOAH humps were not significantly affected by the use of nitrogen as carrier gas. Notably, nitrogen carrier gas led to less solvent peak tailing and smaller baseline offset. Overall, nitrogen may be regarded as viable alternative to hydrogen or helium and may even extend the range of quantifiable compounds to highly volatile hydrocarbon eluting directly after the solvent peak.

Ultrathin Boundary-Less SnO2 Films with Surface-Activated Two-Dimensional Nanograins Enable Fast and Sensitive Hydrogen Gas Sensing.

Fast and reliable semiconductor hydrogen sensors are crucially important for the large-scale utilization of hydrogen energy. One major challenge that hinders their practical application is the elevated temperature required, arising from undesirable surface passivation and grain-boundary-dominated electron transportation in the conventional nanocrystalline sensing layers. To address this long-standing issue, in the present work, we report a class of highly reactive and boundary-less ultrathin SnO2 films, which are fabricated by the topochemical transformation of 2D SnO transferred from liquid Sn-Bi droplets. The ultrathin SnO2 films are purposely made to consist of well-crystallized quasi-2D nanograins with in-plane grain sizes going beyond 30 nm, whereby the hydroxyl adsorption and grain boundary side-effects are effectively suppressed, giving rise to an activated (101)-dominating dangling-bond surface and a surface-controlled electrical transportation with an exceptional electron mobility of 209 cm2 V-1 s-1. Our work provides a new cost-effective strategy to disruptively improve the gas reception and transduction of SnO2. The proposed chemiresistive sensors exhibit fast, sensitive, and selective hydrogen sensing performance at a much-reduced working temperature of 60 °C. The remarkable sensing performance as well as the simple and scalable fabrication process of the ultrathin SnO2 films render the thus-developed sensors attractive for long awaited practical applications in hydrogen-related industries.

Enhanced gas separation performance for H2 purification using MIL-68(ln)-nh2/PES mixed-matrix membranes.

The growing demand for sustainable and efficient gas separation technologies has prompted the exploration of advanced materials to enhance the gas permeability and selectivity. Polyethersulfone (PES) membranes are widely used in gas separation, gas upgrading, and clean energy production owing to their environmental friendliness and low cost. However, their gas permeability and selectivity can be further improved for commercial application. This study explored the incorporation of 10 wt % of MIL-68(ln)-NH2 into PES membranes using a phase-inversion approach to enhance gas permeability and selectivity. The morphological, structural, and thermal properties of the resulting MOF/PES membrane were characterized using SEM, AFM, BET, XRD, FTIR, and TGA-DTG. Gas permeation experiments were conducted using different gases (CO2, N2, CH4, and H2) under different heating conditions (20-60 °C) to evaluate the gas permeability and selectivity of the MOF/PES membrane. The results showed that the incorporation of MOF into the mixed matrix membrane (MMMs) led to a 9% increase in porosity, 87% reduction in roughness, and 32% decrease in pore size compared to neat PES membranes. Significant changes in the morphology, crystallinity, and thermal stability were observed, with notable improvements of up to 22%. Moreover, the MOF/PES membrane exhibited high gas permeability (CO2 = 124656, N2 = 83650, CH4 = 159298, and H2 = 427075 Barrer) and selectivity (H2/N2 = 5.7, H2/CO2 = 4, CH4/N2 = 2, and CH4/CO2 = 1.7) for flammable gases. The optimal gas separation performance was observed at 20 °C and 60 °C for H2/N2 and H2/CO2 separation, respectively. These findings demonstrate the potential of MOF-based PES membranes for gas separation applications, particularly in H2 purification.

MXene/Hydrogel-based bioelectronic nose for the direct evaluation of food spoilage in both liquid and gas-phase environments.

Various bioelectronic noses have been recently developed for mimicking human olfactory systems. However, achieving direct monitoring of gas-phase molecules remains a challenge for the development of bioelectronic noses due to the instability of receptor and the limitations of its surrounding microenvironment. Here, we report a MXene/hydrogel-based bioelectronic nose for the sensitive detection of liquid and gaseous hexanal, a signature odorant from spoiled food. In this study, a conducting MXene/hydrogel structure was formed on a sensor via physical adsorption. Then, canine olfactory receptor 5269-embedded nanodiscs (cfOR5269NDs) which could selectively recognize hexanal molecules were embedded in the three-dimensional (3D) MXene/hydrogel structures using glutaraldehyde as a linker. Our MXene/hydrogel-based bioelectronic nose exhibited a high selectivity and sensitivity for monitoring hexanal in both liquid and gas phases. The bioelectronic noses could sensitively detect liquid and gaseous hexanal down to 10-18 M and 6.9 ppm, and they had wide detection ranges of 10-18 - 10-6 M and 6.9-32.9 ppm, respectively. Moreover, our bioelectronic nose allowed us to monitor hexanal levels in fish and milk. In this respect, our MXene/hydrogel-based bioelectronic nose could be a practical strategy for versatile applications such as food spoilage assessments in both liquid and gaseous systems.

Simultaneous and Independent Abaxial and Adaxial Gas Exchange Measurements.

Stomata can be distributed exclusively on the abaxial or adaxial leaf surface, but they are most commonly found on both leaf surfaces. Variations in stomatal arrangement, patterning, and the impact on photosynthesis can be measured using an infrared gas exchange system. However, when using standard gas exchange techniques, both surfaces are measured together and averaged to provide leaf-level values. Employing an innovative gas exchange apparatus with two infrared gas analyzers, separate gaseous flux from both leaf surfaces can be quantified simultaneously and independently. Here, we provide examples of typical measurements that can be performed using a "split chamber" gas exchange system.

Thermodynamically and Kinetically Enhanced Benzene Vapor Sensor Based on the Cu-TCPP-Cu MOF with Extremely Low Limit of Detection.

As a carcinogenic and highly neurotoxic hazardous gas, benzene vapor is particularly difficult to be distinguished in BTEX (benzene, toluene, ethylbenzene, xylene) atmosphere and be detected in low concentrations due to its chemical inertness. Herein, we develop a depth-related pore structure in Cu-TCPP-Cu to thermodynamically and kinetically enhance the adsorption of benzene vapor and realize the detection of ultralow-temperature benzene gas. We find that the in-plane π electronic nature and proper pore sizes in Cu-TCPP-Cu can selectively induce the adsorption and diffusion of BTEX. Interestingly, the theoretical calculations (including density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations) exhibit that benzene molecules are preferred to adsorb and array as a consecutive arrangement mode in the Cu-TCPP-Cu pore, while the TEX (toluene, ethylbenzene, xylene) dominate the jumping arrangement model. The differences in distribution behaviors can allow adsorption and diffusion of more benzene molecules within limited room. Furthermore, the optimal pore-depth range (60-65 nm) of Cu-TCPP-Cu allows more exposure of active sites and hinders the gas-blocking process. The optimized sensor exhibits ultrahigh sensitivity to benzene vapor (155 Hz/µg@1 ppm), fast response time (less than 10 s), extremely low limit of detection (65 ppb), and excellent selectivity (83%). Our research thus provides a fundamental understanding to design and optimize two-dimensional metal-organic framework (MOF)-based gas sensors.

Dependence of n-Type Metal-Oxide Gas Sensor Response on the Pressure of Oxygen and Reducing Gases.

The adsorption of oxygen and its reaction with target gases are the basis of the gas detection mechanism by using metal oxides. Here, we present a theoretical analysis of the sensor response, within the ionosorption model, for an n-type polycrystalline semiconductor. Our goal of our work is to reveal the mechanisms of gas sensing from a fundamental point of view. We revisit the existing models in which the sensor response presents a power-law behavior with a reducing gas partial pressure. Then, we show, based on the Wolkenstein theory of chemisorption, that the sensor response depends not only on the reducing gas partial pressure but also on the oxygen partial pressure. We also find that the obtained sensor response does not explicitly depend on the grain size, and if it does, it is exclusively through the rate constants related to the involved reactions.

Comparison of pyrolysis gasification of livestock manure, food wastewater, and their co-digested sludge.

For energy recovery, anaerobic digestion is applied to organic waste, such as livestock manure (LM) and food wastewater (FW). Digested sludge(DS), a residue from the anaerobic co-digestion of LM and FW, is another type of organic waste that can be converted into energy through pyrolysis. This study compared the pyrolysis characteristics of LM, FW, and DS. The product content varied with the pyrolysis temperature, rate of temperature increase, reaction time, and final reaction temperature. Gas production from FW and DS was similar; however, gas production from LM was low. As the pyrolysis temperature increased, the H2 content increased, and the CO2 content decreased, respectively. At 1000 °C, the H2 content of LM increased to 45%, and FW produced the most gas but the lowest H2 content. The H2/CO ratios of LM and FW ranged from 3.5 to 5.2, while those of DS ranged from 5.5 to 12.4, with the highest values. The carbon conversion rate was the highest for the gaseous products of LM (30-54%) and lowest for the gaseous products of digested sludge (26-36%). Conversely, the cold gas efficiency was the highest for the DS and lowest for the LM. Following anaerobic digestion, the DS generated less tar than the untreated LM and FW, showed higher efficiency in gas generation and gas properties, and exhibited a higher value as a char fuel.

A closer look at high-energy X-ray-induced bubble formation during soft tissue imaging.

Improving the scalability of tissue imaging throughput with bright, coherent X-rays requires identifying and mitigating artifacts resulting from the interactions between X-rays and matter. At synchrotron sources, long-term imaging of soft tissues in solution can result in gas bubble formation or cavitation, which dramatically compromises image quality and integrity of the samples. By combining in-line phase-contrast imaging with gas chromatography in real time, we were able to track the onset and evolution of high-energy X-ray-induced gas bubbles in ethanol-embedded soft tissue samples for tens of minutes (two to three times the typical scan times). We demonstrate quantitatively that vacuum degassing of the sample during preparation can significantly delay bubble formation, offering up to a twofold improvement in dose tolerance, depending on the tissue type. However, once nucleated, bubble growth is faster in degassed than undegassed samples, indicating their distinct metastable states at bubble onset. Gas chromatography analysis shows increased solvent vaporization concurrent with bubble formation, yet the quantities of dissolved gasses remain unchanged. By coupling features extracted from the radiographs with computational analysis of bubble characteristics, we uncover dose-controlled kinetics and nucleation site-specific growth. These hallmark signatures provide quantitative constraints on the driving mechanisms of bubble formation and growth. Overall, the observations highlight bubble formation as a critical yet often overlooked hurdle in upscaling X-ray imaging for biological tissues and soft materials and we offer an empirical foundation for their understanding and imaging protocol optimization. More importantly, our approaches establish a top-down scheme to decipher the complex, multiscale radiation-matter interactions in these applications.

Modeling Nonlinear Dynamics of Functionalization Layers: Enhancing Gas Sensor Sensitivity for Piezoelectrically Driven Microcantilever.

This article presents a parametrized response model that enhances the limit of detection (LOD) of piezoelectrically driven microcantilever (PD-MC) based gas sensors by accounting for the adsorption-induced variations in elastic properties of the functionalization layer (binder) and the nonlinear motional dynamics of the PD-MC. The developed model is demonstrated for quantifying cadaverine, a volatile biogenic diamine whose concentration is used to assess the freshness of meat. At low concentrations of cadaverine, an increase in the resonance frequency is observed, contrary to the expected reduction due to mass added by adsorption. The study explores the variations in the elastic modulus vis-à-vis the adsorbed mass of cadaverine and derives the resonance frequency to the adsorbed mass response function. We advance a blended technique involving the analysis of atomic force microscopy (AFM) force-distance (f-d) curves and fitting of the quartz crystal microbalance (QCM) impedance response spectrum to deduce the adsorption-induced changes in the viscoelastic properties of the functionalization layer. The findings obtained are subsequently employed in modeling the response function for a structurally nonhomogenous PD-MC, highlighting the significance of the functionalization layer to the global elastic properties. The structural composition of the PD-MC beam adopted herein features a trapezoidal base hosting the actuating piezoelectric stratum and a rectangular free end with a functionalization layer. The Euler-Bernoulli beam theory coupled with Hamilton's principle is used to develop the equation of motion, which is subsequently discretized into a set of nonlinear ordinary differential equations via Galerkin expansion, and the solutions to the first fundamental mode of vibration are determined using the method of multiple scales. The obtained solutions provide a basis for deducing the nonlinear response function model to the adsorbed mass. The derived model is validated by recorded resonance frequency changes resulting from exposure to known concentrations of cadaverine. We demonstrate that the increase in resonance frequency for low concentrations of cadaverine is due to the dominance of the variation of the elastic modulus of the functionalization layer originating from the initial binder-analyte interactions over damping due to added mass. It is concluded that the developed nonlinear response function model can reliably be used to quantify the cadaverine concentration at low concentrations with an elevated Limit of Detection.

Fast-Response and Low-Power Self-Heating Gas Sensor Using Metal/Metal Oxide/Metal (MMOM) Structured Nanowires.

With the escalating global awareness of air quality management, the need for continuous and reliable monitoring of toxic gases by using low-power operating systems has become increasingly important. One of which, semiconductor metal oxide gas sensors have received great attention due to their high/fast response and simple working mechanism. More specifically, self-heating metal oxide gas sensors, wherein direct thermal activation in the sensing material, have been sought for their low power-consuming characteristics. However, previous works have neglected to address the temperature distribution within the sensing material, resulting in inefficient gas response and prolonged response/recovery times, particularly due to the low-temperature regions. Here, we present a unique metal/metal oxide/metal (MMOM) nanowire architecture that conductively confines heat to the sensing material, achieving high uniformity in the temperature distribution. The proposed structure enables uniform thermal activation within the sensing material, allowing the sensor to efficiently react with the toxic gas. As a result, the proposed MMOM gas sensor showed significantly enhanced gas response (from 6.7 to 20.1% at 30 ppm), response time (from 195 to 17 s at 30 ppm), and limit of detection (∼1 ppm) when compared to those of conventional single-material structures upon exposure to carbon monoxide. Furthermore, the proposed work demonstrated low power consumption (2.36 mW) and high thermal durability (1500 on/off cycles), demonstrating its potential for practical applications in reliable and low-power operating gas sensor systems. These results propose a new paradigm for power-efficient and robust self-heating metal oxide gas sensors with potential implications for other fields requiring thermal engineering.

Desulfurization and upgrade of pyrolytic oil and gas during waste tires pyrolysis: The role of metal oxides.

Pyrolysis can effectively convert waste tires into high-value products. However, the sulfur-containing compounds in pyrolysis oil and gas would significantly reduce the environmental and economic feasibility of this technology. Here, the desulfurization and upgrade of waste tire pyrolysis oil and gas were performed by adding different metal oxides (Fe2O3, CuO, and CaO). Results showed that Fe2O3 exhibited the highest removal efficiency of 87.7 % for the sulfur-containing gas at 600 °C with an outstanding removal efficiency of 99.5 % for H2S. CuO and CaO were slightly inferior to Fe2O3, with desulfurization efficiencies of 75.9 % and 45.2 % in the gas when added at 5 %. Fe2O3 also demonstrated a notable efficacy in eliminating benzothiophene, the most abundant sulfur compound in pyrolysis oil, with a removal efficiency of 78.1 %. Molecular dynamics simulations and experiments showed that the desulfurization mechanism of Fe2O3 involved the bonding of Fe-S, the breakage of C-S, dehydrogenation and oxygen migration process, which promoted the conversion of Fe2O3 to FeO, FeS and Fe2(SO4)3. Meanwhile, Fe2O3 enhanced the cyclization and dehydrogenation reaction, facilitating the upgrade of oil and gas (monocyclic aromatics to 57.4 % and H2 to 22.3 %). This study may be helpful for the clean and high-value conversion of waste tires.

Development of toxic gas sensor from anthocyanin-embedded polycaprolactone-co-polylactic acid nanofibrous mat.

The colorless ammonia gas has been a significant intermediate in the industrial sector. However, prolonged exposure to ammonia causes harmful effects to organs or even death. Herein, an environmentally friendly solid-state ammonia sensor was developed utilizing colorimetric polycaprolactone-co-polylactic acid nanofibrous membrane. Pomegranate (Punica granatum L.) peel contains anthocyanin (ACN) as a naturally occurring spectroscopic probe. A mordant (potassium aluminum sulfate) is used to immobilize the anthocyanin direct dyestuff inside nanofibers, generating mordant/anthocyanin (M/ACN) coordinated complex nanoparticles. When exposed to ammonia, the color change of anthocyanin-encapsulated polycaprolactone-co-polylactic acid nanofibrous membrane from purple to transparent was examined by absorbance spectra and CIE Lab color parameters. With a quick colorimetric shift, the polycaprolactone-co-polylactic acid fabric exhibits a detection limit of 5-150 mg/L. The absorbance spectra showed a hypsochromic shift when exposed to ammonia, displaying an absorption shift from 559 nm to 391 nm with an isosbestic point of 448 nm. Scanning electron microscopy (SEM) images revealed that the polycaprolactone-co-polylactic acid nanofibers had a diameter of 75-125 nm, whereas transmission electron microscopy (TEM) images revealed that M/ACN nanoparticles exhibited diameters of 10-20 nm.

Gas-Phase Functionalization of Phytoglycogen Nanoparticles and the Role of Reagent Structure in the Formation of Self-Limiting Hydrophobic Shells.

A suite of acyl chloride structural isomers (C6H11OCl) was used to effect gas-phase esterification of starch-based phytoglycogen nanoparticles (PhG NPs). The surface degree of substitution (DS) was quantified using X-ray photoelectron spectroscopy, while the overall DS was quantified using 1H NMR spectroscopy. Gas-phase modification initiates at the NP surface, with the extent of surface and overall esterification determined by both the reaction time and the steric footprint of the acyl chloride reagent. The less sterically hindered acyl chlorides diffuse fully into the NP interior, while the branched isomers are restricted to the near-surface region and form self-limiting hydrophobic shells, with shell thicknesses decreasing with increasing steric footprint. These differences in substitution were also reflected in the solubility of the NPs, with water solubility systematically decreasing with increasing DS. The ability to separately control both the surface and overall degree of functionalization and thereby form thin hydrophobic shells has significant implications for the development of polysaccharide-based biopolymers as nanocarrier delivery systems.

Solution and gaseous phase sensing of formaldehyde with economical triphenylmethane based sensors: a tool to estimate formaldehyde content in stored fish samples.

The use of formalin to preserve raw food items such as fish, meat, vegetables etc. is very commonly practiced in the present day. Also, formaldehyde (FA), which is the main constituent of formalin solution, is known to cause serious health issues on exposure. Considering the ill effects of formaldehyde, herein we report synthesis of highly sensitive triphenylmethane based formaldehyde (FA) sensors from a single step reaction of inexpensive reagents namely 4-hydroxy benzaldehyde and 2,6-dimethyl phenol. The synthetic method also provides highly pure product in bulk quantity. The analytical activity of the triphenylmethane sensor 1 with a limit of detection (LOD) value of 2.31 × 10-6 M for FA was significantly enhanced through induced deprotonation and thereafter a LOD value of 1.82 × 10-8 M could be achieved. To the best of our knowledge, the LOD value of the deprotonated form (sensor 2) for FA was superior to those of all the FA optical sensors reported so far. The mechanism of sensing was demonstrated by 1H-NMR titration and recording mass spectra before and after addition of FA to a solution of sensor 2. Both sensor 1 and sensor 2 exhibit quenching in emission upon addition of FA. A fluorescence study also demonstrates enhancement in analytical activity of the sensor upon induced deprotonation. Then the sensor was effectively immobilized into a hydrophilic and biocompatible starch-PVA polymer matrix which enabled detection of FA in a 100% aqueous system reversibly. Again, quick and effective sensing of FA in real food samples (stored fish) with the help of a computational application was demonstrated. The sensors have significant practical applicability as they effectively detect FA in real food samples qualitatively and quantitatively.

Dimethyl sulfoxide as a gas phase charge-reducing agent for the determination of PEGylated proteins' intact mass.

Determination of PEGylated proteins' intact mass by mass spectrometry is challenging due to the molecules' large size, excessive charges, and instrument limitations. Previous efforts have been reported. However, signal variability, ion coalescence, and a generally low degree of robustness have been observed. In this work, we have explored the capabilities of post-column infusion of dimethyl sulfoxide (DMSO) following reversed-phase liquid chromatography-mass spectrometry (RP-LCMS) to determine PEG-filgrastim' intact mass, and to characterize its PEG moiety. The method was optimized around reproducibility (six preparations, and three injection replicates) with an in-house prepared PEG-filgrastim standard. The method showed a mass accuracy of ≤1.2 Da. The average molecular weight (MWEO=483) was 40 147.9 Da. The number average molecular weight (Mn) and the weight average molecular weight (Mw) were observed to be 40 101.1 and 40 113.9 Da, respectively, both with an RSD of 0.03%. The molecular weight distribution of ethylene oxide (EO), the polydispersity index (PDI), was 1.0003 for all preparations with a minimum and maximum number of EO units of 448 ± 2 and 516 ± 2, respectively. The method was finally applied to commercially available Neulasta® lots where the Mn and Mw were 39 995.8 and 40 008.8 Da, respectively, both with an RSD of 0.1%. The minimum and maximum EO units across the lots were observed to be 444.5 ± 1.5 and 514 ± 3, respectively. The PDI for all Neulasta® lots was 1.0003. This study provides an insightful characterization of Neulasta® and describes a robust LC-MS methodology for the characterization of the PEGylated proteins.

Wireless Gas Sensor Based on the Mesoporous ZnO-SnO2 Heterostructure Enables Ultrasensitive and Rapid Detection of 3-Methylbutyraldehyde.

Achieving ultrasensitive and rapid detection of 3-methylbutyraldehyde is crucial for monitoring chemical intermediate leakage in pharmaceutical and chemical industries as well as diagnosing ventilator-associated pneumonia by monitoring exhaled gas. However, developing a sensitive and rapid method for detecting 3-methylbutyraldehyde poses challenges. Herein, a wireless chemiresistive gas sensor based on a mesoporous ZnO-SnO2 heterostructure is fabricated to enable the ultrasensitive and rapid detection of 3-methylbutyraldehyde for the first time. The mesoporous ZnO-SnO2 heterostructure exhibits a uniform spherical shape (∼79 nm in diameter), a high specific surface area (54.8 m2 g-1), a small crystal size (∼4 nm), and a large pore size (6.7 nm). The gas sensor demonstrates high response (18.98@20 ppm), short response/recovery times (13/13 s), and a low detection limit (0.48 ppm) toward 3-methylbutyraldehyde. Furthermore, a real-time monitoring system is developed utilizing microelectromechanical systems gas sensors. The modification of amorphous ZnO on the mesoporous SnO2 pore wall can effectively increase the chemisorbed oxygen content and the thickness of the electron depletion layer at the gas-solid interface, which facilitates the interface redox reaction and enhances the sensing performance. This work presents an initial example of semiconductor metal oxide gas sensors for efficient detection of 3-methylbutyraldehyde that holds great potential for ensuring safety during chemical production and disease diagnosis.

General Model for Predicting Response of Gas-Sensitive Materials to Target Gas Based on Machine Learning.

Gas sensors play a crucial role in various industries and applications. In recent years, there has been an increasing demand for gas sensors in society. However, the current method for screening gas-sensitive materials is time-, energy-, and cost-consuming. Consequently, an imperative exists to enhance the screening efficiency. In this study, we proposed a collaborative screening strategy through integration of density functional theory and machine learning. Taking zinc oxide (ZnO) as an example, the responsiveness of ZnO to the target gas was determined quickly on the basis of the changes in the electronic state and structure before and after gas adsorption. In this work, the adsorption energy and electronic and structural characteristics of ZnO after adsorbing 24 kinds of gases were calculated. These computed features served as the basis for training a machine learning model. Subsequently, various machine learning and evaluation algorithms were utilized to train the fast screening model. The importance of feature values was evaluated by the AdaBoost, Random Forest, and Extra Trees models. Specifically, charge transfer was assigned importance values of 0.160, 0.127, and 0.122, respectively, ranking as the highest among the 11 features. Following closely was the d-band center, which was presumed to exert influence on electrical conductivity and, consequently, adsorption properties. With 5-fold cross-validation using the Extra Tree accuracy, the 24-sample data set achieved an accuracy of 88%. The 72-sample data set achieved an accuracy of 78% using multilayer perceptron after 5-fold cross-validation, with both data sets exhibiting low standard deviations. This verified the accuracy and reliability of the strategy, showcasing its potential for rapidly screening a material's responsiveness to the target gas.

Mechanism of Interfacial Molecular Interactions Reveals the Intrinsic Factors for the Highly Enhanced Sensing Performance of Ag-Loaded Co3O4.

The noble metal-loaded strategy can effectively improve the gas-sensing performances of metal oxide sensors. However, the gas-solid interfacial interactions between noble metal-loaded sensing materials and gaseous species remain unclear, posing a significant challenge in correlating the physical and chemical processes during gas sensing. In this study, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and in situ Raman spectroscopy were conducted to collaboratively investigate the interfacial interactions involved in the ethanol gas-sensing processes over Co3O4 and Ag-loaded Co3O4 sensors. In situ DRIFTS revealed differences in the compositions and quantities of sensing reaction products, as well as in the adsorption-desorption interactions of surface species, among Co3O4 and Ag-loaded Co3O4 materials. In parallel, in situ Raman spectroscopy demonstrated that the ethanol atmosphere can modulate the electron scattering of Ag-loaded Co3O4 materials but not of raw Co3O4. In situ experimental results revealed the intrinsic reason for the highly enhanced sensing performances of the Ag-loaded Co3O4 sensors toward ethanol gas, including a decreased optimal working temperature (from 250 to 150 °C), an improved gas response level (from 24 to 257), and accelerated gas recovery dynamics. This work provides an effective platform to investigate the interfacial interactions of sensing processes at the molecular level and further advances the development of high-performance gas sensors.

Synthesis of lignin-based carbon/graphene oxide foam and its application as sensors for ammonia gas detection.

The present study highlights the integration of lignin with graphene oxide (GO) and its reduced form (rGO) as a significant advancement within the bio-based products industry. Lignin-phenol-formaldehyde (LPF) resin is used as a carbon source in polyurethane foams, with the addition of 1 %, 2 %, and 4 % of GO and rGO to produce carbon structures thus producing carbon foams (CFs). Two conversion routes are assessed: (i) direct addition with rGO solution, and (ii) GO reduction by heat treatment. Carbon foams are characterized by thermal, structural, and morphological analysis, alongside an assessment of their electrochemical behavior. The thermal decomposition of samples with GO is like those having rGO, indicating the effective removal of oxygen groups in GO by carbonization. The addition of GO and rGO significantly improved the electrochemical properties of CF, with the GO2% sensors displaying 39 % and 62 % larger electroactive area than control and rGO2% sensors, respectively. Furthermore, there is a significant electron transfer improvement in GO sensors, demonstrating a promising potential for ammonia detection. Detailed structural and performance analysis highlights the significant enhancement in electrochemical properties, paving the way for the development of advanced sensors for gas detection, particularly ammonia, with the prospective market demands for durable, simple, cost-effective, and efficient devices.