Components Of Gas Mixture Research Articles

Influence of adsorption and desorption on accurate density measurements of gas mixtures

In measurement science many diverse densimeters are used to measure the density of gas mixtures and the accuracy of such measurements can be significantly influenced by adsorption of gas-mixture components on the internal surfaces of the densimeter. In this context, the major objective of the present study was to investigate the influence of adsorption and desorption on the accurate density measurement of gas mixtures. For this purpose, measurements of the p–ρ–T–x behavior of a 15-component natural-gas mixture were carried out as an example. The densities were measured at T=273.15K with pressures up to 8MPa (which was at least T=25K above the maximum dew-point temperature) using an accurate two-sinker densimeter incorporating a magnetic suspension coupling. Densities at standard conditions (T=273.15K, po=0.101325MPa) were also measured utilizing a special two-sinker densimeter without magnetic suspension coupling. For both instruments, the relative expanded combined uncertainty (k=2) in density was 0.02%. The measurement results are illustrated in diagrams demonstrating the consequence of sorption effects, which is a change of the gas density inside the measuring cell resulting from a change in composition of the measured gas. Due to these sorption effects significant errors in density measurement can occur, up to about 0.1% in case of the typical example investigated within the present study. To avoid a distortion of the measurements by sorption effects, appropriate measurement procedures were undertaken.

Occupation and Release Behavior of Guest Molecules in CH4, CO2, N2, and Acetone Mixture Hydrates: An In Situ Study by Raman Spectroscopy

For practical applications of gas hydration (formation of gas hydrates) in environmental and technological processes, considerable knowledge regarding the thermodynamic stability and structural features of these hydrates, as well as the occupation behavior of specific components of gas mixtures within them, is essential. Herein, the hydrate phase equilibria of a system comprising CH4/CO2/N2 (55/40/5) + aqueous acetone solutions (1, 3, and 5.56 mol %) were determined in the temperature range 273–285 K and under pressures up to 4.5 MPa. Gas compositions in the hydrate phase were also obtained by evaluating the following variables: (1) hydrate-formation temperature and pressure, (2) concentration of acetone, and (3) type of hydrate structure: (a) structure I or (b) structure II. The crystal structures of the gas hydrates formed from the acetone and CH4 + CO2 + N2 mixture gas were also evaluated by both X-ray diffraction and Raman spectroscopy. In addition, structural identification of the CH4 + CO2 + N2 + acetone hydrates formed by varying the concentration of acetone (0, 1, 3, and 5.56 mol %) was performed. Further evaluation of the temperature-dependent occupation behavior of CH4 and CO2 in structure II hydrate cages in the temperature range 150–290 K indicates that CH4 and CO2 gradually escaped from the hydrate frameworks with increasing temperature, up to 255 K, at which point the CH4 + CO2 + N2 + acetone hydrate completely decomposed.

A new kernel discriminant analysis framework for electronic nose recognition

Electronic nose (e-Nose) technology based on metal oxide semiconductor gas sensor array is widely studied for detection of gas components. This paper proposes a new discriminant analysis framework (NDA) for dimension reduction and e-Nose recognition. In a NDA, the between-class and the within-class Laplacian scatter matrix are designed from sample to sample, respectively, to characterize the between-class separability and the within-class compactness by seeking for discriminant matrix to simultaneously maximize the between-class Laplacian scatter and minimize the within-class Laplacian scatter. In terms of the linear separability in high dimensional kernel mapping space and the dimension reduction of principal component analysis (PCA), an effective kernel PCA plus NDA method (KNDA) is proposed for rapid detection of gas mixture components by an e-Nose. The NDA framework is derived in this paper as well as the specific implementations of the proposed KNDA method in training and recognition process. The KNDA is examined on the e-Nose datasets of six kinds of gas components, and compared with state of the art e-Nose classification methods. Experimental results demonstrate that the proposed KNDA method shows the best performance with average recognition rate and total recognition rate as 94.14% and 95.06% which leads to a promising feature extraction and multi-class recognition in e-Nose.

A rapid discreteness correction scheme for reproducibility enhancement among a batch of MOS gas sensors

Metal oxide semiconductor (MOS) gas sensors have been widely reported in machine olfaction system (i.e. electronic nose/tongue) for rapid detection of gas mixture components due to their positive characteristics of cross-sensitivity, broad spectrum response and low-cost. However, the discreteness of MOS gas sensors caused by inherent sensor variability during the manufacturing process results in the failure of the batch-oriented applications of MOS gas sensors due to their weak reproducibility. Certainly, it will also cause negative influence to the development of electronic nose/tongue based on MOS gas sensors (e.g. accuracy and consistency during electronic nose/tongue detections). Therefore, the contribution of this paper is to solve the discreteness and improve the reproducibility of sensors by designing an effective and easily realized scheme for large-scale calibration. Experimental results demonstrate that the proposed scheme can effectively and rapidly realize the calibration of the sensors’ discreteness in batch of electronic noses production and the proposed scheme have also been used in industry. Besides, this paper also proves that one sensor's discreteness is constant and keeps unchanged when the sensor is exposed to different kinds of gas components.

A time-of-flight mass spectrometer for monitoring the inhalational anesthesia concentration in the real-time mode

The use of a medical mass spectrometer for measuring the concentration of the gas mixture components in the breathing circuit of an inhalational anesthesia machine in the real-time mode is described. The resolution of the mass spectrometer is M/ΔM = 200, and the detection threshold in terms of the partial pressure of the analyzed gases is 2 × 10−12 mbar. The mass spectrometer is capable of measuring the volumetric content of CO2, O2, and inhalational anesthetic sevoflurane. The respiratory coefficient (CO2/O2) was measured during anesthesia to estimate the patient’s stress reaction to a surgical injury.

Bionanomaterials and Bioinspired Nanostructures for Selective Vapor Sensing

At present, monitoring of air at the workplace, in urban environments, and on battlefields; exhaled air from medical patients; air in packaged food containers; and so forth can be accomplished with different types of analytical instruments. Vapor sensors have their niche in these measurements when an unobtrusive, low-power, and cost-sensitive technical solution is required. Unfortunately, existing vapor sensors often degrade their vapor-quantitation accuracy in the presence of high levels of interferences and cannot quantitate several components in complex gas mixtures. Thus, new sensing approaches with improved sensor selectivity are required. This technological task can be accomplished by the careful design of sensing materials with new performance properties and by coupling these materials with the suitable physical transducers. This review is focused on the assessment of the capabilities of bionanomaterials and bioinspired nanostructures for selective vapor sensing. We demonstrate that these sensing materials can operate with diverse transducers based on electrical, mechanical, and optical readout principles and can provide vapor-response selectivity previously unattainable by using other sensing materials. This ability for selective vapor sensing provides opportunities to significantly impact the major directions in development and application scenarios of vapor sensors.

New calculation method for thermodynamic properties of humid air in humid air turbine cycle – The general model and solutions for saturated humid air

The article proposes a new calculation method for thermodynamic properties (i.e. specific enthalpy, specific entropy and specific volume) of humid air in humid air turbine cycle. The research pressure range is from 0.1 MPa to 5 MPa. The fundamental behaviors of dry air and water vapor in saturated humid air are explored in depth. The new model proposes and verifies the relationship between total gas mixture pressure and gas component pressures. This provides a good explanation of the fundamental behaviors of gas components in gas mixture from a new perspective. Another discovery is that the water vapor component pressure of saturated humid air equals PS, always smaller than its partial pressure (f·PS) which was believed in the past researches. In the new model, “Local Gas Constant” describes the interaction between similar molecules. “Improvement Factor” is proposed for the first time by this article, and it quantitatively describes the magnitude of interaction between dissimilar molecules. They are combined to fully describe the real thermodynamic properties of humid air. The average error of Revised Dalton's Method is within 0.1% compared to experimentally-based data.

Alternative Fuels Based on Biomass: An Investigation of Combustion Properties of Product Gases

Fuels from low quality feedstock such as biomass and biomass residues are currently discussed with respect to their potential to contribute to a more sustainable electrical power supply. In the present work, we report on the study of generic representative gas mixtures stemming from the gasification of different feedstock, from wood and algae. Two major combustion properties—burning velocities and ignition delay times—were measured for different parameters: (i) for two pressures—1 bar and 3 bar—at a constant preheat temperature T0 = 373 K, to determine burning velocities by applying the cone angle method; and (ii) for elevated pressures—up to 16 bar—in the temperature range between about 1000 and 2000 K, at fuel-equivalence ratios φ of 0.5 and 1.0, to obtain ignition delay times by applying the shock tube method. Additional studies performed in our group on gas mixtures of natural gas, methane, and hydrogen were also taken into account as major components of biogenic gas mixtures. It was found that the reaction behavior of the wood gasification product (N2, CO, H2, CO2, CH4) is mainly determined by its H2 content, besides CH4; methane determines the kinetic behavior of the algae fermentation product (CH4, CO2, N2) due to its relatively high amount. Detailed chemical kinetic reaction models were used to predict the measured data. The trends and main features were captured by predictions applying different reaction models. The agreement of the experiments and the predictions is dependent on the pressure range.

Gas sensing characteristics of MEMS gas sensor arrays in binary mixed-gas system

MOS gas sensor arrays based on MEMS gas sensor platforms were developed for the detection of carbon monoxide (CO), nitrogen oxides (NOx) and ammonia (NH3), and their gas sensing characteristics in binary mixed-gas system were investigated. Three gas sensing materials with nano-sized particles for these target gases, Pd–SnO2 for CO, In2O3 for NOx and Ru–WO3 for NH3 were synthesized using a sol–gel method. All the sensors showed good properties for their target gases at the optimum points for micro-heater operation. From the experimental data in MEMS gas sensor arrays in a binary mixed system, the gas sensing behavior and sensor response in mixed gas systems were scrutinized. The gas sensing behaviors to the mixed gas systems suggested that specific adsorption and selective activation of adsorption sites might occur in gas mixtures and offer the priority for the adsorption of specific gas. Thorough analysis of the sensing performance of the sensor arrays will make it possible to discriminate the components in gas mixtures as well as their concentrations.

Steam solubilities of solid MoO3, ZnO and Cu2O, calculated on a basis of a thermodynamic model

The solubilities of solid oxides in the vapor phase of water are considered as the gas phase chemical reactions of metal oxides and water with the formation of hydroxides of metals and their hydrates. The necessary thermodynamic properties of hydroxides and their hydrates in the ideal gas state are obtained by quantum chemical calculations or in a few cases are evaluated from available experimental data. The values of the fugacity coefficients (ϕ2∞) of components of gas mixtures are estimated by the empirical relation ln ϕ2∞=k⋅ln ϕ1*, where ϕ1* stands for the fugacity coefficient of pure water and the parameter k is evaluated by counting the groups (OH, H2O, O) of the molecule of a dissolved compound, which can form hydrogen bonds with water molecules. Considered examples include the calculations of the steam solubility of MoO3(s), ZnO(s), and Cu2O(s) at 573–1273K and up to water density of 300kgm−3 in comparison with available experimental data. It was found that the speciation of Mo(VI) is absolutely dominated by a single form MoO2(OH)2, while in the Zn(II) and Cu(I) steam mixtures both hydroxides and their hydrates contribute appreciably to the material balance of metals. There is a clear tendency to the dehydration of dominating forms with an increase of temperature. The agreement of the experimental and calculated solubility values can be termed satisfactory (for Cu2O(s)–H2O at least for temperatures of 623.2 and 673.2K), considering the difficulties of gas-phase solubility experiments, uncertainties of the data based on quantum chemical calculations, and the simplicity of the model to predict ϕ2∞ values.

Optical absorption method of natural gas component analysis in real time. Part II. Analysis of mixtures of arbitrary composition

The present paper continues the presentation of the results of studies started in [1]. The referred paper reports the development of the optical method for component analysis of natural gas mixtures with different compositions, allowing conducting measurements in real time. The method is based on the measurement of the absorption coefficients for the analyzed gas mixture at several wavelengths within the infrared region of the spectrum (7–14 μm), with the selected number and values of wavelengths depending on the category of the gas mixture. The resulting accuracy of the determination of the main components of gas mixtures including methane, ethane, propane, butane, pentane and carbon dioxide is sufficient for the use of the developed method for the monitoring of the component composition of natural gas in pipelines.

Computational Study of Adsorption and Separation of CO2, CH4, and N2 by an rht-Type Metal–Organic Framework

In this work, a computational study is performed to evaluate the adsorption-based separation of CO(2) from flue gas (mixtures of CO(2) and N(2)) and natural gas (mixtures of CO(2) and CH(4)) using microporous metal organic framework Cu-TDPAT as a sorbent material. The results show that electrostatic interactions can greatly enhance the separation efficiency of this MOF for gas mixtures of different components. Furthermore, the study also suggests that Cu-TDPAT is a promising material for the separation of CO(2) from N(2) and CH(4), and its macroscopic separation behavior can be elucidated on a molecular level to give insight into the underlying mechanisms. On the basis of the single-component CO(2), N(2), and CH(4) isotherms, binary mixture adsorption (CO(2)/N(2) and CO(2)/CH(4)) and ternary mixture adsorption (CO(2)/N(2)/CH(4)) were predicted using the ideal adsorbed solution theory (IAST). The effect of H(2)O vapor on the CO(2) adsorption selectivity and capacity was also examined. The applicability of IAST to this system was validated by performing GCMC simulations for both single-component and mixture adsorption processes.

Optimized Binary Interaction Parameters for VLE Calculations of Natural Gas Mixtures via Cubic and Molecular-Based Equations of State

The objective of this study is to analyze the performance of a selected collection of equations of state (EOS) for the prediction of vapor–liquid equilibrium of the components of a typical natural gas mixture. In this work, 13 biparametric, triparametric, and tetraparametric, widely used simple-cubic-type EOS and three complex, but state-of-the-art, molecular-based EOS are used. A simple, one-fluid-based mixing rule was applied for the extension to mixtures of the models. Binary interaction parameters for the different equations were calculated by correlation of available binary vapor–liquid equilibria data in the experimental literature, in wide temperature–pressure ranges, for the key binary systems relevant to natural gases. The results allow one to infer the performance of the different EOS commonly used for phase equilibria analysis in the natural gas industry, and to study how the different complexity of the studied EOS does (or does not) lead to an improvement in the quality of the predictions.

Performance analysis of neuro swarm optimization algorithm applied on detecting proportion of components in manhole gas mixture

The article presents performance analysis of the neuro swarm optimization algorithm applied for the detection of proportion of the component gases found in manhole gas mixture. The hybrid neuro swarm optimization technique is used for implementing an intelligent sensory system for the detection of component gases present in manhole gas mixture. The manhole gas mixture typically contains toxic gases such as Hydrogen Sulfide, Ammonia, Methane, Carbon Dioxide, Nitrogen Oxide, and Carbon Monoxide. A semiconductor based gas sensor array used for sensing the gas components consists of many sensor elements, where each sensor element is responsible for sensing particular gas component. Presence of multiple gas sensors for detecting multiple gases results in cross-sensitivity. The central theme of this article is the performance analysis of the algorithm which offers solution to multiple gas detection issue. The article also presents study on the computational cost incurred by the algorithm.

Nonempirical simulation of chemical deposition of silicon nitride films in CVD reactors

This work is devoted to the atomistic simulation of chemical vapor deposition (CVD) of thin silicon nitride films from the mixture of dichlorosilane (DCS) and ammonia in CVD reactors. The earlier developed chemical mechanism is substantially extended by including the reactions of catalytic decomposition of DCS, and a self-consistent atomistic model of a CVD process is developed. An extended chemical mechanism is constructed and analyzed that allows one to adequately describe kinetic processes in a gas phase within the ranges of temperature, pressure, and the DCS: NH3 ratio of original reactants, that are characteristic of silicon nitride deposition. An effective kinetic model is developed that involves the calculation of the rate constants and the concentrations of the gas mixture components. A thermodynamic analysis of the surface coverage by various chemisorbed groups is carried out, and equilibrium surface concentrations are obtained for the main chemisorbed groups. Practically significant conclusions are made about the character of the deposition process and, in particular, about the role of the extended chemical mechanism.

Performance comparison of the mass transfer models with internal reforming for solid oxide fuel cell anodes

In this work, models describing multicomponent gas diffusion process in an electrode of a porous solid oxide fuel cell (SOFC) anode coupled with internal reforming reactions were developed. The performances of three different types of models, the dusty-gas model (DGM), the binary-friction model (BFM) and the cylindrical pore interpolation model (CPIM), were compared in 1D. All these models take into account Knudsen diffusion and molecule–molecule diffusion can be used in transition region which is generally the case in a SOFC electrode. The developed models are able to predict the fuel components’ molar fraction distributions in the anode electrode, and the concentration overpotential. They are capable of simulating the internal reforming process for hydrocarbon fuel, such as natural gas, with kinetic models considering both methane-steam reforming (MSR), and water–gas shift reaction (WSR). The effects of pressure gradient, pore size, current density, are studied. It was found that three models give similar results in difference cases using the same “tuned” tortuosity factor (τ2). The difference caused using the isobaric assumption is negligible for the H2–H2O–Ar and CO–CO2 system, expect at small pore sizes (under 1μm) and high current density (above 1A/cm2). For a system fed with hydrocarbon fuel, the isobaric assumption will change the molar fraction distribution by up to 10% for different gas mixture components for the CPIM and the BFM, and up to 25% for the DGM at small pore sizes. However, the reaction rates for both MSR and WSR remain the same when the pressure variation is neglected.

Kinetic and thermodynamic treatments of a neutral binary gas mixture affected by a nonlinear thermal radiation field

In the present study, the kinetic and the irreversible thermodynamic properties of a binary gas mixture, under the influence of a thermal radiation field, are presented from the molecular viewpoint. In a frame comoving with the fluid, the Bhatnagar–Gross–Krook model of the kinetic equation is analytically applied, using the Liu–Lees model. We apply the moment method to follow the behavior of the macroscopic properties of the binary gas mixture, such as the temperature and the concentration. The distinction and comparisons between the perturbed and equilibrium distribution functions are illustrated for each gas mixture component. From the viewpoint of the linear theory of irreversible thermodynamics we obtain the entropy, entropy flux, entropy production, thermodynamic forces, and kinetic coefficients. We verify the second law of thermodynamics and celebrated Onsager’s reciprocity relation for the system. The ratios between the different contributions of the internal energy changes, based upon the total derivatives of the extensive parameters, are estimated via Gibbs’ formula. The results are applied to the argon–neon binary gas mixture, for various values of both the molar fraction parameters and radiation field intensity. Graphics illustrating the calculated variables are drawn to predict their behavior and the results are discussed.

Molecular insight into the high selectivity of double-walled carbon nanotubes

Combining experimental knowledge with molecular simulations, we investigated the adsorption and separation properties of double-walled carbon nanotubes (DWNTs) against flue/synthetic gas mixture components (e.g. CO(2), CO, N(2), H(2), O(2), and CH(4)) at 300 K. Except molecular H(2), all studied nonpolar adsorbates assemble into single-file chain structures inside DWNTs at operating pressures below 1 MPa. Molecular wires of adsorbed molecules are stabilized by the strong solid-fluid potential generated from the cylindrical carbon walls. CO(2) assembly is formed at very low operating pressures in comparison to all other studied nonpolar adsorbates. The adsorption lock-and-key mechanism results from perfect fitting of rod-shaped CO(2) molecules into the cylindrical carbon pores. The enthalpy of CO(2) adsorption in DWNTs is very high and reaches 50 kJ mol(-1) at 300 K and low pore concentrations. In contrast, adsorption enthalpy at zero coverage is significantly lower for all other studied nonpolar adsorbates, for instance: 35 kJ mol(-1) for CH(4), and 14 kJ mol(-1) for H(2). Applying the ideal adsorption solution theory, we predicted that the internal pores of DWNTs have unusual ability to differentiate CO(2) molecules from other flue/synthetic gas mixture components (e.g. CO, N(2), H(2), O(2), and CH(4)) at ambient operating conditions. Computed equilibrium selectivity for equimolar CO(2)-X binary mixtures (where X: CO, N(2), H(2), O(2), and CH(4)) is very high at low mixture pressures. With an increase in binary mixture pressure, we predicted a decrease in equilibrium separation factor because of the competitive adsorption of the X binary mixture component. We showed that at 300 K and equimolar mixture pressures up to 1 MPa, the CO(2)-X equilibrium separation factor is higher than 10 for all studied binary mixtures, indicating strong preference for CO(2) adsorption. The overall selective properties of DWNTs seem to be superior, which may be beneficial for potential industrial applications of these novel carbon nanostructures.

Dissemination of units of mole fraction and mass concentration of gas components by means of first-grade working standards based on dynamic gas mixture generators

A comparison of static and dynamic methods of preparing gas mixtures is presented and requirements that working standards based on dynamic generators must satisfy are formulated. The basic sources of errors in the reproduction of mole fraction and mass concentration of components in gas mixtures are analyzed by a dynamic method and results from a study of methods of increasing the stability and precision of dynamic generators are presented. A new complex of first-grade working standards is described. Data of an experimental study of the metrological characteristics of dynamic generators based on the results gained from their use in international key comparisons are presented.

Analytical approximation of the thermal and caloric equations of state for real gases over a wide density and temperature range

The thermal and caloric equations of state of the main components of gas mixtures normally used in calculations of gas dynamic processes, including combustion and detonation, as well as in problems of internal ballistics, are presented in an analytical form. The formulas obtained for the equations of state contain a relatively small number of parameters and provide an average error of approximation of less than 1% at temperatures from 500 to 2000–2500 K and densities up to the critical.