Mixture Of NO Research Articles

Anesthetic Gases: Environmental Impacts and Mitigation Strategies for Fluranes and Nitrous Oxide

Anesthetic gases represent a small but significant portion of the environmental impact of health care in many countries. These compounds include several fluorocarbons commonly referred to as “fluranes”. The fluranes are greenhouse gases (GHG) with global warming potentials in the hundreds to thousands and are also PFAS compounds (per- and polyfluorinated alkyl substances) according to at least one definition. Nitrous oxide (N2O) is sometimes used as an adjunct in anesthesia, or for sedation, but has a significant stratospheric ozone depletion potential as well as GHG effects. Reducing emissions of these compounds into the environment is, therefore, a growing priority in the health care sector. Elimination or substitution of the highest impact fluranes with alternatives has been pursued with some success but limitations remain. Several emission control strategies have been developed for fluranes including adsorption onto solids, which has shown commercial promise. Catalytic decomposition methods have been pursued for N2O emission control, although mixtures of fluranes and N2O are potentially problematic for this technology. All such emission control technologies require the effective scavenging and containment of the anesthetics during use, but the limited available information suggests that fugitive emissions into the operating room may be a significant route for unmitigated losses of approximately 50% of the used fluranes into the environment. A better understanding and quantification of such fugitive emissions is needed to help minimize these releases. Further cost–benefit and techno-economic analyses are also needed to identify strategies and best practices for the future.

Performance of a novel waste heat-powered ionic liquid-based CO2 capture and liquefaction system for large-scale shipping

In this work, we proposed a novel CO2 capture and liquefaction system for large-scale shipping using ionic liquid as capture solvent. By utilizing the waste heat of the exhaust gas and jacket cooling water from the ship’s engine as well as the residual pressure energy of the N2-O2 mixture from the CO2 absorption and desorption process, the system’s net energy consumption has been significantly reduced. We established the thermodynamic model of the system and investigated the effect of 10 primary system operational parameters on system performance with 3 different ionic liquids as CO2 capture solvent. The results demonstrated that the system with [DEME][TF2N] as the CO2 capture solvent had the best system performance. In addition, we performed a multi-parameter optimization of the system using simulated annealing algorithm with net energy consumption as the optimization objective and the minimal net energy consumption is 0.467 GJ/tCO2. Compared to the CO2 capture system that do not utilize waste heat and residual pressure energy, the net energy consumption was reduced by 57.29 % under optimal operational conditions which proves that the novel system significantly reduces the energy consumption of the CO2 capture and liquefaction process.

Microwave-Assisted Oxidation of N2 into NOx over a La-Ce-Mn-O Perovskite Yielding Plasmas in a Quartz Flow Reactor at Atmospheric Pressure

N2 oxidation to NOx is a challenging reaction, and alternative routes to the industrial Ostwald process are of interest. A perovskite under flowing O2-N2 mixtures at atmospheric pressure in a quartz tube reactor was irradiated by microwaves (MW), leading to the formation of hot spots and plasmas within the catalyst bed. NOx concentrations up to 2.5 vol.% in one pass were obtained at 600 W. Using a lower MW power of 100 W led to a pulsed mode yielding lower NOx concentrations and no noticeable damage to the quartz reactor. The formation of plasma was strongly dependent on the perovskite bed packing. The perovskite acted primarily as a susceptor and likely also as a catalyst, although the proportion of heterogeneous and homogenous reactions could not be determined in the present study. The simple reactor layout allowing operation at atmospheric pressure is promising for the development of practical MW-assisted N2 fixation technologies.

Efficient separation of SO2/NO2 on in-situ synthesized NaA zeolite membrane

SO2 and NO2 mixture widely exists in the desorbed gas from industrial flue gas adsorption purification process, separating the mixture into pure gas provides the key step for success in recycling them into profitable chemicals. However, effective SO2/NO2 separation is challenged due to the similar properties of both gases. In this work, we report the synthesis of an industrially-favored NaA zeolite membrane and the utilization of this membrane for SO2/NO2 separation in order to address the above-mentioned challenge. Various characterizations illustrate that the in-situ synthesis endows the NaA zeolite membrane with well-intergrown crystals, high continuity, and crystal-comparable thickness. The separation measurements at different feed pressure, temperature, and gas composition demonstrate that the NaA zeolite membrane shows superior separation performance (SO2/NO2 separation factor of 40.0, SO2 permeance of 2.93 × 10−7 mol m−2 Pa−1 s−1 at 293 K and 0.2 MPa) with strong stability (more than 7 d) compared to the previous best-performing zeolite membrane. The strong competitiveness of SO2 over NO2 on the low-silica membrane is revealed through molecular simulation, showing that the great affinity of SO2 with highly-polar zeolite structure benefits the SO2 gas preferential adsorption and energetically barrier-free permeation through the eight-membered ring of NaA zeolite. This work not only showcases an efficient strategy for the SO2/NO2 separation, but also expands the gas separation application of zeolite membranes.

Statistical analysis on branching characteristics of positive streamer discharges in N2–O2 mixtures

Streamers are fast-propagating ionization channels that can usually branch and form complex tree-like structures in dielectric media. In this paper, we perform experiments on positive streamers in different N2–O2 mixtures under varying conditions including voltage, pressure, and electrode geometry, with at least 125 discharge images captured for each condition. We present a statistical analysis on streamer branching characteristics from 3D models that are reconstructed by stereoscopic stroboscopic images and our dedicated semi-automatic 3D reconstruction method.We found that by varying the concentration of O2, the morphology and branching characteristics are greatly changed. Specifically, the average branching angle decrease significantly from 90∘ in air to 66∘ in 1% O2, suggesting that photoionization plays an important role in streamer branching. The branching angles in our work are generally larger than previously reported results due to the resolved 3D structures of discharges by our method. A linear relation between the streamer diameter ratio and the branching direction difference of two daughter branches is found, which intersects the vertical axis almost at unity. It is also found that the average branching angles, streamer velocities and diameters increase as the voltage increases. This is again attributed to stronger photoionization effect under higher voltages. The velocities and diameters are similar at different pressures but at the same reduced electric field. The average branching angle decreases from 90∘ at 133 mbar to 79∘ at 200 mbar. This suggests that stochastic fluctuations become dominant over photoionization effect at higher pressures.

Trapping intermediates of the NO2 hydrolysis reaction on ice.

Using molecular beam methods, a mixture of stable NO2 and O2NNO2 with a considerable relative abundance of t-ONONO2, a potential heterogeneous hydrolysis reaction intermediate, was prepared by heating the quasi-effusive...

Simultaneous Detection of CO and NO2 Gases using Interaction Analysis of SnS2 Sensor Array Response

Developing a multi-analyte gas sensing system that simultaneously detects trace levels of CO and NO2 at low temperatures is necessary for the Internet of Things (IoT) based air quality monitoring applications. Nevertheless, gas sensors operating at low temperatures are nonspecific and rarely detect target gases at lower ppb levels in the air. Herein, an array of two SnS2 sensors with different bias voltages has been developed and characterized upon exposure to individual and binary mixtures of CO and NO2 gases at different concentrations. The developed gas sensors array achieved the lower detection limit of 45 ppb for NO2 and 150 ppb for CO. Further, co-adsorption-induced interaction analysis was carried out to predict the target gas concentration in the binary mixture using the mixed gas response. The mean absolute percentage error of 7.86% is observed in predicting the target gas concentrations in the binary mixture, which indicates the high prediction accuracy of proposed method. As a minimal resource intensive approach, the proposed method can be used in air quality monitoring applications that require low-power and low-cost sensors.

Protocols and procedures for safe administration of nitrous oxide–oxygen inhalational minimal sedation for anxiolysis in pediatric dentistry: A case series

Abstract Fear and anxiety related to dental treatment are the most important causes of avoidance of oral care among pediatric patients. The majority of pediatric dental patients are managed with only behavior management techniques, without any pharmacological intervention. However, several pediatric dental patients, owing to noncooperation or the extent of surgery required may require pharmacological means of management, such as sedation or general anesthesia. Children with mild-to-moderate anxiety are suitable for management with inhalational sedation agents, such as nitrous oxide and oxygen (N2O–O2). An inhalational mixture of N2O–O2 has been used in this setting for over a century and has a high index of safety. With the advent of newer failsafe equipment for the delivery of these agents and the availability of trained dental and anesthesiology teams, this modality of sedation for behavior management of children while rendering dental treatment is gaining more acceptability. Proper case selection, informed consent from parents/guardians before the procedure, preprocedure and preprocedure counseling, and anesthetic evaluation of the child are important steps in the successful administration of sedation. The awareness of guidelines, alertness regarding adverse events, and preemptive preparation to manage any critical incident are essential for the safe administration of this inhalational mixture; thus, providing oral care to pediatric patients with the least amount of discomfort.

Machine learning-assisted methods for prediction and optimization of oxidative desulfurization of gas condensate via a novel oxidation system

The aim of this study is to predict the efficiency of oxidative desulfurization method (in a gas–liquid oxidation system) for gas condensate using artificial intelligence (AI) systems such as Fuzzy Inference System, Adaptive Neuro-Fuzzy Inference System (ANFIS), Genetic Algorithm (GA)-Fuzzy, and GA-ANFIS. The method utilizes mixtures of H2SO4, HNO3, and NO2 as oxidant agents in various amounts. The optimal parameters of the proposed models were determined using GA, and statistical parameters such as mean absolute error, average relative deviation, and correlation coefficient were used to compare the models. The correlation coefficients for Fuzzy, ANFIS, GA-Fuzzy, and GA-ANFIS models were found to be 0.5899, 0.7831, 0.9693, and 0.9687, respectively. The results indicated that ANFIS-GA and Fuzzy-GA models can effectively predict the desulfurization efficiency of the novel technique. Furthermore, the use of GA improved the performance of the Fuzzy and ANFIS models and enhanced their prediction accuracy. Overall, this study demonstrates the potential of AI systems in predicting the efficiency of novel chemical methods for industrial applications.

Double-pulse streamer simulations for varying interpulse times in air

In this paper, we study how streamer discharges are influenced by a previous voltage pulse using an axisymmetric fluid model. We simulate double-pulse positive streamers in N2–O2 mixtures containing 20% and 10% O2 at 1 bar. By varying the time between the pulses between 5 ns and 10 µs, we observe three regimes during the second pulse: streamer continuation, inhibited growth and streamer repetition. In the streamer continuation regime, a new streamer emerges from the tip of the previous one. In the inhibited regime, the previous channel is partially re-ionized, but there is considerably less field enhancement and almost no light emission. Finally, for the longest interpulse times, a new streamer forms that is similar to the first one. The remaining electron densities at which we observe streamer continuation agree with earlier experimental work. We introduce an estimate which relates streamer continuation to the dielectric relaxation time, the background field and the pulse duration. Furthermore, we show that for interpulse times above 100 ns several electron detachment reactions significantly slow down the decay of the electron density.

O3-assisted NH3-SCR over FeBEA catalyst at low reaction temperature

The injection of O3 upstream to the SCR catalyst, FeBEA zeolite, significantly improves its catalytic performance at 100–200 °C. This improvement is due to the oxidation of NO by O3, which proceeds even at ambient temperature, and to the further reduction of the NO + NO2 mixture as a result of fast SCR, NO2-SCR and accumulation of NH4NO3 on the catalyst surface.

Improving the performance of artificial neural networks trained on synthetic data in gas spectroscopy – a study on two sensing approaches

Abstract Artificial neural networks (ANNs) are used in quantitative infrared gas spectroscopy to predict concentrations on multi-component absorption spectra. Training of ANNs requires vast amounts of labelled training data which may be elaborate and time consuming to obtain. Additional data can be gained by the utilization of synthetically generated spectra, but at the cost of systematic deviations to measured data. Here, we present two approaches to train ANNs with a combination of comparatively small, measured data sets and synthetically generated data. For the first approach a neural network is trained hybridly with synthetically generated infrared absorption spectra of mixtures of N2O and CO and measured zero-gas spectra, taken with a mid-infrared dual comb spectrometer. This improves the mean absolute error (MAE) of the network predictions from 0.46 to 0.01 ppmV and 0.24 to 0.01 ppmV for the concentration predictions of N2O and CO respectively for zero-gas measurements which was previously observed for training with purely synthetic data. At the same time a similar performance on spectra from gas mixtures of 0–100 ppmV N2O and 0 to 60 ppmV CO was achieved. For the second approach an ANN pre-trained on synthetic infrared spectra of mixtures of acetone and ethanol is retrained on a small dataset consisting of 26 spectra taken with a mid-infrared photoacoustic spectrometer. In this case the MAE for the concentration predictions of ethanol and acetone are improved by 45 % and 20 % in comparison to purely synthetic training. This shows the capability of using synthetically generated data to train ANNs in combination with small amounts of measured data to further improve neural networks for gas sensing and the transferability between different sensing approaches.

Classification and concentration estimation of CO and NO2 mixtures under humidity using neural network-assisted pattern recognition analysis

This study addresses the concerns regarding the cross-sensitivity of metal oxide sensors by building an array of sensors and subsequently utilizing machine earning techniques to analyze the data from the sensor arrays. Sensors were built using In2O3, Au-ZnO, Au-SnO2, and Pt-SnO2 and they were operated simultaneously in the presence of 25 different concentrations of nitrogen dioxide (NO2), carbon monoxide (CO), and their mixtures. To investigate the effects of humidity, experiments were conducted to detect 13 distinct CO and NO2 gas combinations in atmospheres with 40% and 90% relative humidity. Principal component analysis was performed for the normalized resistance variation collected for a particular gas atmosphere over a certain period, and the results were used to train deep neural network-based models. The dynamic curves produced by the sensor array were treated as pixelated images and a convolutional neural network was adopted for classification. An accuracy of 100% was achieved using both models during cross-validation and testing. The results indicate that this novel approach can eliminate the time-consuming feature extraction process.

Study of the efficiency of ozone synthesis in a point‐to‐plain discharge in N2–O2 mixtures

AbstractThe experimental results of the ozone synthesis and electrodynamic characteristics of the point‐to‐plane DC voltage corona discharge in N2–O2 mixtures at atmospheric pressure are presented. Four different modes of DC corona discharge were investigated: stationary mode of positive point‐to‐plane discharge, two non‐stationary (streamers) modes of positive point‐to‐plane discharge, and mode of negative point‐to‐plane discharge. It was shown that ozone synthesis highly depends on discharge modes and correlates with discharge conditions appropriated to dissociative attachment processes. In the case of positive point‐to‐plane discharge, ozone synthesis behavior is similar to that of the pulse component of the discharge current. It was shown that the mode with secondary streamers propagation is the most effective for ozone production among the four different modes of the point‐to‐plane DC corona discharge.

Thermodynamic analysis of an efficient pressure-swing CO2 capture system based on ionic liquid with residual pressure energy recovery

In this work, an efficient pressure-swing ionic liquid-based CO2 capture system with residual pressure energy recovery is proposed. In this system, the N2–O2 mixture from flue gas which is not absorbed by the ionic liquid in the absorber flows into the turbine to recover the energy for the purpose of reducing energy consumption. 1-butyl-3-methylimidazolium tetrafluoroborate ([Bmim][BF4]) and 1-butyl-3-methylimidazolium hexafluorophosphate ([Bmim][PF6]) are selected as the capture solvent and a comprehensive thermodynamic analysis is performed. The total energy consumption of the new system is 1.770 GJ/tCO2 under design conditions which is 28.45% lower than the conventional system for [Bmim][BF4] and 1.737GJ/tCO2 which is 28.84% lower than the conventional system for [Bmim][PF6]. The effect of absorption pressure, desorption temperature, heat storage fluid flow rate, distribution ratio of heat storage fluid in the intercooler, flue gas composition and type of heat storage fluid on system thermodynamic performance were analyzed. The result shows that relatively lower capture pressure, the lower desorption temperature, the lower heat storage fluid flow rate, the more heat storage fluid distributed in the first intercooler and the higher CO2 fraction in flue gas can improve the thermodynamic performance of the system. Also, the exergy analysis represents that cold tank and the capture module are the two components with maximum exergy destruction. And the comparison results with the conventional system show that the new system has significantly lower energy consumption and capture cost.

Inhaled nitrous oxide for painful procedures in children and youth: a systematic review and meta-analysis.

The objective of this study was to synthesize indication-based evidence for N2O for distress and pain in children. We included trials of N2O in participants 0-21years, reporting distress or pain for emergency department procedures. The primary outcome was procedural distress. Where meta-analysis was not possible, we used Tricco et al.'s classification of "neutral" (p ≥ 0.05), "favorable," or "unfavorable" (p < 0.05, supporting N2O or comparator, respectively). We used the Cochrane Collaboration's Risk of Bias tool and the Grading of Recommendations Assessment, Development, and Evaluation system to evaluate risk of bias and quality of evidence, respectively. We included 30 trials. For pain using the Visual Analog Scale (0-100mm) during IV insertion, 70% N2O (delta:-16.5; 95%CI:-28.6 to -4.4; p = 0.008; three trials; I2 = 0%) and 50% N2O plus eutectic mixture of local anesthetics (EMLA) (delta:-1.2; 95%CI:-2.1 to -0.3; p = 0.007; two trials; I2 = 43%) were superior to EMLA. 50% N2O was not superior to EMLA (delta:-0.4; 95%CI:-1.2 to 0.3; p = 0.26; two trials; I2 = 15%). For distress and pain during laceration repair, N2O was "favorable" versus each of SC lidocaine, oxygen, and oral midazolam but "neutral" versus IV ketamine (five trials). For distress and pain during fracture reduction (three trials), N2O was "neutral" versus each of IM meperidine plus promethazine, regional anesthesia, and IV ketamine plus midazolam. For distress and pain during lumbar puncture (one trial), N2O was "favorable" versus oxygen. For distress and pain during urethral catheterization (one trial), N2O was "neutral" versus oral midazolam. For pain during intramuscular injection (one trial), N2O plus EMLA was "favorable" versus N2O and EMLA alone. Common adverse effects of N2O included nausea (4.4%), agitation (3.7%), and vomiting (3.6%) AEs were less frequent with N2O alone (278/1147 (24.2%)) versus N2O plus midazolam (48/52 (92.3%)) and N2O plus fentanyl (123/201 (61.2%)). There is sufficient evidence to recommend N2O plus topical anesthetic for IV insertion and laceration repair. Adverse effects are greater when combined with other sedating agents.

The molecular oxygen 118-GHz line intensity revision

The intensity of the atmospheric diagnostic fine-structure line of the O2 molecule at 118.75 GHz is revised based on multiple measurements with a resonator spectrometer in pure O2 and O2–N2 mixture at pressures ranging from 250 to 1500 Torr and temperatures within 278–327 K. The resulting intensity of 1.000(3)⋅10−25 cm/molec confirms the earlier measurements and allows decreasing the uncertainty down to ∼0.3%. An excellent agreement with the result of calculations presented in HITRAN is demonstrated, suggesting that the 10%–20% uncertainty recommended by the database for all fine structure lines is too large.

Mixed gas concentration inversion based on the hierarchical feature fusion convolutional neural network

Recently, the detection of gas mixtures has attracted considerable attention due to its promising application in disease diagnosis, environmental monitoring and so on. However, the detection of gas mixtures is inevitably subject to the cross-interference between different components. Herein, we propose a hierarchical feature fusion convolutional neural network (CNN) model for mixed gas concentration inversion. In our experiment, mixtures of SO2, NO2 and NH3 were analyzed. SO2 and NO2 were the detected gases while NH3 was the interfering gas. The proposed model can be applied to low-resolution spectra. Compared with the model without hierarchical structure and feature fusion, the mean absolute errors of SO2 and NO2 decreased by 80.3% and 87.0% in the simulated spectral samples. The experimental results also demonstrate that the proposed model could effectively reduce the cross-interference and improve the accuracy of gas concentration inversion. This model would have a promising application in the field of gas detection and low-resolution spectra.

Enhanced sensitivity towards LPG with selectivity between LPG, NO2, and NH3 by novel CoFe2O4/SiC/BaTiO3 nanocomposites

In this paper, the enhanced sensitivity and selectivity between LPG, NO2, and NH3 by novel CoFe2O4/SiC/BaTiO3 (CFO/SiC/BTO) ternary nanocomposites synthesized by chemical coprecipitation and solid-state methods have been reported. The structural and morphological properties of nanocomposites were analysed using XRD, SEM and EDS respectively. The highest dielectric permittivity ∼665 at 8 kHz for 30 wt% BTO with lowest dielectric loss at high temperature was achieved using LCR meter. Moreover, the maximum response (%) was obtained towards LPG ∼84%, while it was found to be ∼11% for NH3 and ∼23% for NO2 at 220 ppm, whilst it was achieved more than 95% above 150 °C for all the gases. Furthermore, the selectivity ∼95% at room temperature was acquired for LPG in presence of NH3. The excellent response (%) ∼ 99.68% and 99.85% was obtained for mixture of LPG-NO2 and LPG-NH3 at 300 °C for 30 wt% BTO, which was also confirmed by obtained activation energy. Accordingly, 30 wt% BTO of CFO/SiC/BTO nanocomposites is providing excellent sensitivity and selectivity towards LPG in the mixture of NO2 and NH3.

Study on the concentration retrieval of SO2 and NO2 in mixed gases based on the improved DOAS method.

NO2 and SO2 are important components of air pollutants, and their absorption spectra are superimposed at 193-253 nm. The superposed spectra affect the gas concentration retrieval based on the ultraviolet differential optical absorption spectroscopy (DOAS) method. In this study, a suitable wavelength band was chosen for concentration retrieval, moreover, the characteristics of the quasi-periodic variation of absorption cross-section with wavelength was given sufficient attention and then the superposed spectra were separated by the Fast Fourier transform (FFT) method. The concentration of the gases to be measured was calculated according to the relationship between the amplitude of absorbance after FFT and the gas concentration. The experimental results prove that by using an absorption cell with a 700 mm optical path, the relative deviation absolute value of the retrieval concentration of SO2 in a NO2 and SO2 gas mixture is less than 1.471%, and that of NO2 in a NO2 and SO2 gas mixture is less than 7.207%. The method has good adaptability, high detection precision, whether single SO2, NO2 or a mixture of both, and important reference value for the development of DOAS and future research on the high-precision detection of more types of mixed gases in the ultraviolet band, such as gas mixtures of NO2, SO2 and NO in flue gas.