Mole Fraction Research Articles

Latent fingerprint detection and identification using yellow-emitting YOF:Pr3+ nanophosphor

In this study, YOF:Pr3+ nanophosphors were synthesized using the microwave-assisted hydrothermal route. The structural and morphological properties of the nanophosphors calcined at different temperatures were studied in detail to optimize the synthesis conditions. The visible region and near-infrared (NIR) photoluminescence (PL) properties of the nanophosphors were obtained. Intense emission bands were observed in the blue and red regions under 250 nm excitation. The CIE chromaticity diagram showed that the color coordinates of the nanophosphors were located in the yellow region. The optimum Pr3+-concentration was found to be 0.002 mole fraction. The application of YOF: 0.002 Pr3+ nanophosphor for latent fingerprint detection was examined and evaluated on different types of surfaces. The nanophosphor demonstrated excellent adherence to the ridge patterns and sufficient sensitivity required for distinguishing between the ridges and the furrows. Different levels of detail were also observed that provided necessary information for the individualization of the fingerprints. The results suggest that the prepared YOF:Pr3+ nanophosphor can be a potential candidate for the rapid visualization and detection of latent fingerprints.

Predicting nickel catalyst deactivation in biogas steam and dry reforming for hydrogen production using machine learning

This study employs Random Forests (RF) and Artificial Neural Networks (ANN) to model the transient behavior of Ni catalyst deactivation during steam and dry reforming of model biogas containing H2S, with a focus on hydrogen production. Deactivation, induced by carbon deposition and sulfur poisoning, is a complex and transient phenomenon demanding precise kinetic mechanisms for accurately predicting Ni catalyst behavior in biogas reforming. Black-box machine learning (ML) models are developed, incorporating catalyst properties, biogas composition, and operating conditions. Encompassing both dry and steam reforming, the ML models aim to predict catalyst behavior, expressed in terms of packed bed reactor exit mole fractions (H2, CO, CH4, and CO2) and conversions (CH4 and CO2). The ML models are trained and tested across a temperature range of 700–900 C with 0–145 ppm of H2S in model biogas (CH4/CO2 ratio varying from 1.0 to 2.0). RF outperforms the ANN across all performance metrics, including overall R2 and root mean squared error (RMSE). The RF achieves a mean overall R2 of 0.979, with training and testing RMSE equal to 6.7×10−3 and 1.47×10−2 respectively. In contrast, the ANN achieves a mean overall R2 of 0.939, with training and testing RMSE equal to 2.6×10−2 and 2.55×10−2 respectively. Moreover, pre-trained RF models are validated with unseen data of dry reforming of biogas containing 30 ppm of H2S (25 data points). It is suggested that 35 % of this unseen experimental data is required to train the RF model for it to predict catalyst deactivation, achieving a validation R sufficiently2> 0.9. The mean overall R2 values attained by the RF fine-tuned on 35 % of the unseen experiment data for both CH4 and CO2 conversions, as well as for all mole fraction predictions, are 0.952 and 0.948, respectively.

Current Density of AlxGa1-xAs/GaAs Superlattice

Theoretically, the AlxGa1-xAs/GaAs superlattice is studied as a function of optical energy with and without bias. The transfer matrix approach has determined the transmission coefficient and resonant tunnelling current density. The number of barriers is estimated at N = 3, and the concentration ratio (the mole fraction value) x at 0.1, 0.2, and 0.3 is fixed. The number of cells in the well is established at (ncw) = 5, while the number of barrier cells (ncb) is changed from 1 to 5 for both biases. This study shows that the change in the number of barrier cells plays a crucial role in the tunnelling of charge carriers and the transmission probability of charge carriers through the depletion regions. Thus, changing the current density is based on the purpose to be applied. In addition, the values ​​of current density at the reverse bias are higher than that in the forward bias, which is explained by the bias controlling the energy levels of the superlattice. It is worth noting that there are many practical applications in which this system can be used, including solar cells, detectors, and light-emitting diodes.

The response of mesophyll conductance to short-term CO2 variation is related to stomatal conductance.

The response of mesophyll conductance (gm) to CO2 plays a key role in photosynthesis and ecosystem carbon cycles under climate change. Despite numerous studies, there is still debate about how gm responds to short-term CO2 variations. Here we used multiple methods and looked at the relationship between stomatal conductance to CO2 (gsc) and gm to address this aspect. We measured chlorophyll fluorescence parameters and online carbon isotope discrimination (Δ) at different CO2 mole fractions in sunflower (Helianthus annuus L.), cowpea (Vigna unguiculata L.), and wheat (Triticum aestivum L.) leaves. The variable J and Δ based methods showed that gm decreased with an increase in CO2 mole fraction, and so did stomatal conductance. There were linear relationships between gm and gsc across CO2 mole fractions. gm obtained from A-Ci curve fitting method was higher than that from the variable J method and was not representative of gm under the growth CO2 concentration. gm could be estimated by empirical models analogous to the Ball-Berry model and the USO model for stomatal conductance. Our results suggest that gm and gsc respond in a coordinated manner to short-term variations in CO2, providing new insight into the role of gm in photosynthesis modelling.

Experimental study and correlation of critical parameters for three binary mixtures containing R290 and hydrofluoroolefins

The mixtures of R290 (propane) and R1234yf (2,3,3,3-tetrafluoroprop-1-ene), R1243zf (3,3,3-trifluoropropene), or R1234ze(E) (trans-1,3,3,3-tetrafluoropropene) could be potential alternatives for high global warming potential (GWP) refrigerants hydrofluorocarbons (HFCs) and hydrochlorofluorocarbons (HCFCs). Obtaining the critical parameters of mixtures is crucial for establishing thermodynamic models, evaluating the highest operating temperature of refrigerants, determining the phase envelope, and confirming the starting point of the Widom line. However, few studies have been made on their critical properties. In this work, the critical properties of three binary systems containing R290 + R1234yf / R1243zf / R1234ze(E) are obtained experimentally with a metal-bellows volume apparatus. The critical state is judged by direct visual observation of critical opalescence and the recurrence of the vapor-liquid phase interface. The extended total uncertainties for the mole fraction, critical pressure, critical temperature, and critical density were below 0.004, 21 kPa, 50 mK, and 0.6 % (k = 2, 0.95 confidence coefficient), respectively. Experimentally obtained critical data are correlated by the Modified Wilson method and the Redlich–Kister method. The critical parameters of the R290 + R1234yf, R290 + R1243zf, and R290 + R1234ze(E) mixtures are predicted using the Correlated Modified Wilson (CMW) method, He et al.’s method, and the Modified Extended Chueh–Prausnitz (MECP) method. The correlated curve and predicted outcomes are employed for comparison with this work's experimental results. Meanwhile, the critical parameters data obtained experimentally are contrasted with the value of REFPROP 10.0 and other open literature. The fitting and prediction curves somewhat agree with the experimental results.

Colloidal dispersions of cobalt ferrite nanoparticles in EMIM TFSI, propylene carbonate and their mixtures

Liquid thermocells are promising devices for the recovery of low-grade waste heat and its conversion into electricity. The present study proposes dispersing charged magnetic nanoparticles in liquids to improve thermoelectric conversion, due to their thermodiffusive and magnetic properties. Core@shell cobalt ferrite@maghemite nanoparticles (NPs) of various sizes with three different kinds of coatings are tested for dispersion in EMIM TFSI (ethyl-methylimidazolium bistriflimide), an ionic liquid (IL) of high electrical conductivity. Among the tested ligands, PAC6MIM±Br− (1-(6-hexylphosphonate) 3-methyl imidazolium bromide) emerges as the most efficient due to its phosphonic group. This ligand leads to dispersions of clusters of a few dozen NPs in water and a few NPs in EMIM TFSI. For improving both the viscosity and the electrical conductivity, dispersions in binary mixtures of propylene carbonate (PC), a polar medium, and EMIM-TFSI are further investigated with the sample based on NPs of ∼ 9 nm diameter. Through a pumping and heating procedure, stable dispersions are obtained with a subsequent reduction of the size of the NP clusters, down to 1 to 2 NPs in EMIM TFSI and a few NPs in PC and their binary mixtures. The mixture with an IL mole fraction ∼0.2–0.3 and maximal electrical conductivity is a promising candidate for further thermoelectric investigations.

Lipid redistribution due to a cell-cell fusion pore

We consider the redistribution of lipids comprising the plasma membranes during cell-cell fusion, particularly due to the presence of a fusion pore. Assuming the membranes are of constant thickness, we find that the mole fraction of cholesterol increases in the directly apposed exoplasmic leaflets, and is decreased in the cytoplasmic leaflets. The redistribution of the phospholipids is obtained as well.

Abraham solvation parameter model: experiment-based solute descriptors for (2-nitrophenyl)acetic acid

ABSTRACT Mole fraction solubilities are reported for (2-nitrophenyl)acetic acid dissolved in 1-pentanol, 1-heptanol, 1-octanol, 2-butanol, 3-methyl-1-butanol, 2-pentanol, 4-methyl-2-pentanol, cyclopentanol, 2-ethoxyethanol, 2-propoxyethanol, 2-isopropoxyethanol, 1,4-dioxane, methyl acetate, propyl acetate, isopropyl acetate, butyl acetate, isobutyl acetate, tert-butyl acetate, pentyl acetate, methyl butyrate, dimethyl adipate and propanenitrile at 298.15 K. Solubilities were determined using a spectrophotometric method of chemical analysis. Experiment-based Abraham model solute descriptors are calculated for the molecular, monomeric form of (2-nitrophenyl)acetic acid by combining our experimental values with the published solubility data obtained from the published paper by Zhou and co-workers. The calculated solute descriptors describe the observed solubility data to within an overall standard deviation of 0.10 log units.

Interactions and oil recovery performance of a prepared extended amphoteric surfactant combining with a nonionic surfactant under high salinity condition

The extended amphoteric surfactant (named C12P3E3NS), characterized by FTIR and 1H NMR, was prepared by amination and sulfonation in order to enhance oil recovery (EOR) for the low-permeability oil reservoirs. The surface and interfacial tensions of its combination systems with nonionic surfactant (APG0810, an Alkyl Polyglycoside), obtained by tension meter, were evaluated to obtain an optimized surfactant system for enhancing oil recovery. The compound system (named C12A) with 40 % mole fractions of C12P3E3NS, exhibiting the strongest interaction behavior and highest expansion modulus, possesses the best abilities of reducing the interfacial tension to ultra-low (10-3 mN/m order of magnitude) at a salinity of 10 wt%, and owns certain abilities of emulsifying crude oil. Meanwhile, the contact angle, measured by the contact angle measuring instrument, can be altered from 108.50°to 55.07°by the compound system C12A, confirming its better wetting alteration ability of transforming the capillary force from resistance to driving force. Eventually, displacement efficiency, obtained from core displacement tests, reveals that the compound surfactant system C12A can decrease the pressure by 15.80 % and its corresponding oil recovery factor is 15.25 % after water flooding, demonstrating its favorable displacement performance and potential application in medium or high salinity reservoirs.

Thermal optimization of ivermectin in supercritical carbon dioxide and ethanol to produce nano medicine

The solubility of ivermectin in high pressure carbon dioxide (CO2) at 338, 328, 318, and 308 K temperatures was investigated with and without an ethanol. Several methods were employed to model the data obtained from the experiments. ivermectin exhibited solubility values ranging from 0.130 × 10−5 to 1.760 × 10−4 in the binary system and 1.880 × 10−5 to 1.237 × 10−4 in the ternary system. The outcome indicated that the addition of ethanol significantly increased the mole fraction of ivermectin in CO2. The highest impact of ivermectin solubility was found in the ivermectin -Ethanol- CO2 system at 338 K and 12 MPa, which was about 14.35 times greater than binary system under the same conditions. The models proposed by Jouyban et al. and Sodeifian-Sajadian models showed the best correlation with average absolute relative deviation (AARD%) and Akaike information criterion (AICc) for binary and ternary approaches, respectively. The results confirmed that rapid expansion supercritical solution (RESS) and gas antisolvent (GAS) method can be apply for producing nanoparticles at the suitable ranges of the drug solubility.

Solubility measurement of Ceftriaxone sodium in SC-CO2 and thermodynamic modeling using PR-KM EoS and vdW mixing rules with semi-empirical models

The complete investigation of the solubility of Ceftriaxone sodium drug has not yet been conducted. This communication investigates the solubility of Ceftriaxone sodium drug in supercritical CO2 (SC-CO2) for the first time. The drug solubility measurements were performed using utilizing UV–vis analysis under different operation conditions (at P (bar) = 120–270 and T (K) = 308–338). The results demonstrated that the solubility of Ceftriaxone sodium ranged from 0.90 × 10−6 to 8.01 × 10−6. The mole fraction solubility of Ceftriaxone sodium increases proportionally with an increase in the pressure, while maintaining a constant temperature. However, a crossover was noted. The solubility behavior of Ceftriaxone sodium drug in SC-CO2 was modeled by Peng-Robinson equation of state (PR EoS) with Kwak-Mansoori and van der Waals mixing rules and seven semi-empirical correlations (Bian et al., Kumar-Johnston, Chrastil, Garlapati-Madras, Bartle et al., Sung-Shim and Sodeifian et al.,). The vaporization, total and solvation enthalpies of the Ceftriaxone sodium/SC-carbon dioxide system were obtained by KJ, Chrastil, and Bartle et al. correlations. The evaluation of two methods was performed by absolute average relative deviation (AARD%). Both models exhibited a satisfactory level of agreement with the experimental data. Finally, PR/KM EoS and the Chrastil models, with AARD% values of 8.70 % and 8.10 % respectively, showed superior precision in accurately fitting the solubility data.

Mutual and Thermal Diffusivities in Binary Mixtures of Polystyrene with Dissolved N2 or CO2 by Dynamic Light Scattering

In physical foaming processes of thermoplastics, a liquid mixture consisting of a molten polymer with a dissolved blowing agent is extruded through a die or injected into a mold. The morphology of the foam matrix strongly depends on the mutual diffusion coefficient D11 of the liquid polymer-blowing agent mixture. For a better understanding of the underlying physical mechanisms during the foaming process and the development of corresponding models, accurate knowledge of D11 is needed. This work reports on the simultaneous measurement of D11 and the thermal diffusivity a of liquid mixtures consisting of polystyrene melts with dissolved nitrogen (N2) or carbon dioxide (CO2) at mass fractions wsolute up to 0.003 or 0.02 and temperatures T between (433 and 533) K using dynamic light scattering (DLS). The determined D11 range is between (1 and 4) × 109 m2⋅s−1 and are slightly larger for the mixtures containing N2 at a given T and wsolute. D11 could be determined with an average expanded relative uncertainty of 18%. Considering all investigated state points and the achieved experimental uncertainties, both D11 and a are independent on the amount of dissolved gas, despite relatively large mole fractions of the dissolved blowing agents xsolute of 0.997 and 0.93.

FLIM nanoscopy resolves the structure and preferential adsorption in the co-nonsolvency of PNIPAM microgels in methanol-water

Polymer microgels are swollen macromolecular networks with a typical size of hundred of nanometers to several microns that show an extraordinary open and responsive architecture to different external stimuli, being therefore important candidates for nanobiotechnology and nanomedical applications such as biocatalysis, sensing and drug delivery. It is therefore crucial to understand the delicate balance of physical-chemical interactions between the polymer backbone and solvent molecules that to a high extent determine their responsivity.In particular, the co-nonsolvency effect of poly(N-isopropylacrylamide) in aqueous alcohols is highly discussed, and there is a disagreement between molecular dynamics (MD) simulations (from literature) of the preferential adsorption of alcohol on the polymer chains and the values obtained by several empirical methods that mostly probe the bulk solvent properties.It is our contention that the most efficacious method for addressing this problem requires a nanoscopic method that can be combined with spectroscopy and record fluorescence spectra and super-resolved fluorescence lifetime images of microgels labeled covalently with the solvatochromic dye Nile Red. By employing this approach, we could simultaneously resolve the structure of sub-micron size objects in the swollen and in the collapsed state and estimate the solvent composition inside of them in ▪–▪ mixtures for two very different polymer architectures. We found an outstanding agreement between the MD simulations and our results that estimate a co-solvent molar fraction excess of approximately 3 with a very flat profile in the lateral direction of the microgel.

Modeling and simulation of laser-ignited Al-PTFE reactive material in vacuum

Despite extensive investigations elucidating the initial response behavior of Al-PTFE (aluminized polytetrafluoroethylene) under atmospheric pressure, research on their response in lean-oxygen environments pertinent to propulsion and explosion scenarios is still lacking. This paper theoretically analyzes the multi-physical processes of laser-ignited Al-PTFE, identifying the initial response, main chemical reaction paths, and gas-phase product flow mechanisms. A dynamic reaction model of Al-PTFE considering material moving front, chemical reactions, gas-phase product dynamics, and variations in thermophysical properties, was developed. The robust coupling scheme in the model addresses nonlinear equations and fluid-solid coupling boundary conditions. Validation was achieved by comparing the ablation depth and plume number density field calculated by the model with the experimental results in the literature. The model reveals a positive correlation between laser fluence and both temperature growth rate and ablation depth of Al-PTFE, with the effects mainly observed in the FWHM of the pulsed laser due to the thermal decomposition of the PTFE matrix. Simulations of the equilibrium constants and molar fractions of 19 components in the Al-PTFE ablation plume within the temperature range of 2000 K to 30,000 K at 0.001 Pa indicate that the equilibrium constants for dissociative reactions exceed those for ionization reactions, primarily in the early plume formation stages. Analysis of kinetic parameters and ambient pressure effects shows that during laser ablation, the maximum temperature of the plume initially appears near the ablation surface, shifting to the front, where the maximum velocity is always located. An elliptical shock wave forms due to adiabatic expansion of the plume, creating a cavity inside the plume. Lower ambient pressure increases plume expansion velocity, temperature, and size.

Chemical kinetic study of methane blended with ammonia cracked gas at elevated temperature and pressure

Ammonia (NH3) on-line cracking to produce hydrogen (H2) can avoid direct ammonia combustion and is an important method to enhance combustion performance and control nitrogen oxide (NOx) emissions. This work aims to study the effects of various ammonia energy ratios (ENH3) and cracking ratios (CNH3) on the combustion and NO emission characteristics of methane (CH4) blended with ammonia cracked gas under lean-burn condition. The results showed that methane co-combustion and ammonia cracking significantly enhance the laminar burning velocity (LBV). The chemical effect plays a dominant role in the enhancement of LBV, but its relative contribution gradually decreases with increasing ENH3 and CNH3. A linear relationship between LBV and (O+H+OH+NH2 + CH3)max was observed, with both the slope and intercept being functions of CNH3. At an ENH3 of 20 %, NO emission decrease with increasing CNH3. At an ENH3 of 80 %, NO emission first increase and then decrease. The percentage of thermal NO is less than 1 % under ambient condition and could increase to as much as 22 % under elevated condition (500 K, 10 atm). Additionally, there was a quadratic polynomial relationship between (O+H+OH+NH2)max and the final NO mole fraction within an equivalence ratio range from 0.4 to 0.8. The second-order coefficient exhibits a linear correlation with CNH3, while the first-order and constant coefficient show a quadratic polynomial correlation with CNH3.

Interface properties and applications in laundry of the BS12-SAS mixed systems

In the BS12/SAS mixed systems, the solution exhibits acidity. BS12 can act as a cationic surfactant to form anionic-cationic complexes with SAS. In this study, the surface properties and application characteristics of the BS12/SAS mixed systems were investigated. The static surface tension, dynamic surface tension, and contact angle of BS12, SAS, and their different mixed molar ratios were measured at 25 °C to evaluate interaction parameters, activity coefficient, molar fraction, and thermodynamic variables of surfactants in the mixed micelles. The results demonstrated that the BS12/SAS mixed systems deviated from the ideal state due to the strong molecular attraction between the two components, resulting in a synergistic effect. The mixed systems exhibited higher surface activity and lower critical micelle concentration. Thermodynamic analysis indicated that the spontaneous micellization of binary mixtures of BS12 and SAS occurred through both enthalpy-driven and entropy-driven processes. The adsorption kinetics data revealed that the mixed systems followed a diffusion-adsorption process. Contact angle measurements demonstrated that BS12/SAS possesses superior ability to reduce surface tension, which facilitated rapid droplet diffusion and efficient wetting of the matrix within a short time period. Furthermore, the aggregation behavior of individual surfactants and the two composite systems in aqueous solutions was analyzed using DLS and TEM to investigate their effects on the wetting, emulsification stability, foaming stability, and decontamination capability of liquid paraffin.

Enhancement of mass transfer through under-rib convection in polymer electrolyte fuel cell with dimensionless moduli analysis

The significance of under-rib convection in the flow field development of polymer electrolyte fuel cells (PEFCs) is increasingly recognized. This study quantitatively evaluates the interplay between mass transfer and reaction processes in adjacent channels, affected by under-rib convection. A comprehensive analysis identifies that oxygen mole fraction and current density profiles in the channel-rib direction are governed by five dimensionless moduli. The effectiveness factor, defined as the ratio of the integral average under-rib current density to that without mass transfer resistance, elucidates the potential for current density enhancement due to under-rib convection. Experimental results demonstrate a significant increase in the under-rib current density from 0.15 to 0.32 A cm⁻2 as the pressure difference between adjacent channels rises from 0 to 929 Pa at 0.60 V and 0.52 relative humidity. This corresponds to an increase in the effectiveness factor from 0.37 to 0.77 and a Péclet number increase from 0 to 34.8. Model predictions indicate that the maximum net power density is achieved at a Péclet number of 60, balancing under-rib convection benefits and pumping pressure. Validated by experimental results, the model aids in reaction kinetics analysis and polarization prediction, offering significant insights and practical guidelines for electrochemical reactor optimization.

Mapping high-resolution XCO2 concentrations in China from 2015 to 2020 based on spatiotemporal ensemble learning model

High-resolution column-averaged dry air mole fraction of CO2 (XCO2) data is crucial for understanding the spatiotemporal patterns of XCO2 and for mitigating carbon emissions. Due to the limited scanning range of sensors and strict inversion conditions, satellite-retrieved XCO2 data are often significantly incomplete. Machine learning models are widely used to fill these gaps in satellite XCO2 data. However, the limitations of individual machine learning models and the complexity of the spatial distribution of XCO₂ mean that the accuracy of XCO2 predictions still needs improvement. In this study, a new spatiotemporal stacked ensemble learning model (STEL) was developed by combining random forest (RF), extremely randomized trees (ERT), extreme gradient boosting (XGBoost), optical gradient boosting (LightGBM), and categorical boosting (CatBoost) using the stacking ensemble learning methodology. Considering the spatiotemporal heterogeneity of XCO2, a novel spatiotemporal weighting feature was constructed as part of the model's input parameters. Finally, the XCO2 observed by Orbiting Carbon Observatory 2 (OCO-2) was reconstructed using STEL, and a monthly mean XCO2 dataset covering China from 2015 to 2020 was generated at a spatial resolution of 0.1°. The results show that STEL exhibits superior performance and generalization capabilities compared to individual machine-learning models. R2 RMSE and MAPE were 0.9624, 1.0023 ppm, and 0.1583 % on the test set, and 0.8970, 1.4213 ppm, and 0.2475 % for R2, RMSE, and MAPE in ground validation, respectively. In 10-fold cross-validation, STEL's RMSE was reduced by 9.52 % compared to the best-performing single model (RF). The spatiotemporal trend of CO2 in China from 2015 to 2020 was analyzed using STEL XCO2 data. The results indicate that this dataset accurately reflects the spatiotemporal heterogeneity of XCO2 distribution at a fine scale. Overall, XCO2 exhibited a spatiotemporal pattern of “high in the east and low in the west” and “high in spring and low in summer.” Except in summer, high XCO₂ values were mainly distributed in the North China Plain. XCO2 trends and hotspots showed considerable spatial variation. The Pearl River Delta and Yangtze River Delta urban agglomerations have the fastest XCO2 growth rates, and the distribution of XCO2 hotspots is consistent with the distribution of population and economic centers. In the sparsely populated northwest of China, XCO2 is growing rapidly due to increased thermal power generation and coal mining. XCO2 hotspots in Northwest China are mainly located in Xinjiang, Ningxia, and Inner Mongolia. The methodology and data presented are useful for further research on carbon emissions, carbon sinks, and climate change.

Effect of hydrogen concentration, initial pressure and temperature on mechanisms of hydrogen explosion in confined spaces

Hydrogen as a renewable clean energy raises industrial safety and environmental issues. Studying the mechanism of hydrogen explosion in confined space is significant for guiding the risk assessment and efficient use of hydrogen energy. This paper used a 20 L explosion chamber to explore the effect of initial concentration changes on the hydrogen explosion and verify the model, the CHEMKIN simulation software was used to qualitatively and quantitatively evaluate the dynamic behavior characteristics of hydrogen explosion in confined space under different initial conditions, and the variation law of physical process of hydrogen explosion under different influencing factors in confined space was revealed from macro-micro perspectives. This study shows that the maximum explosion temperature and pressure under fuel-rich conditions are generally higher than those under fuel-lean conditions. The induction period of the hydrogen explosion reaction gradually shortens as the initial pressure increases, there is a negative temperature coefficient effect of ignition delay at the initial temperature of 800 K. In addition, compared with the initial pressure, higher explosion temperature and faster reactant mixing speed significantly affect the gas explosion reaction rate. The molar fractions of free radicals H, O, and OH show an inverted V-shaped relationship with the initial hydrogen concentration, and there is a hysteresis phenomenon in the final molar fraction peak of H free radicals; Sensitivity analysis indicates that free radicals are mainly responsive to the intermediate reaction R16 (forward direction) and R9 (reverse direction), thereby affecting parameters such as explosion pressure and temperature. These research findings can provide theoretical support for developing hydrogen explosion suppression technology.

A quantitative theory for heterogeneous combustion of nonvolatile metal particles in the diffusion-limited regime

The paper presents an analytical theory quantitatively describing the heterogeneous combustion of nonvolatile (metal) particles in the diffusion-limited regime. It is assumed that the particle is suspended in an unconfined, isobaric, quiescent gaseous mixture and the chemisorption of the oxygen takes place evenly on the particle surface. The analytical solution of the particle burn time is derived from the conservation equations of the gas-phase described in a spherical coordinate system with the utilization of constant thermophysical properties, evaluated at a reference film layer. This solution inherently takes the Stefan flow into account. The approximate expression of the time-dependent particle temperature is solved from the conservation of the particle enthalpy by neglecting the higher order terms in the Taylor expansion of the product of the transient particle density and diameter squared. Coupling the solutions for the burn time and time-dependent particle temperature provides quantitative results when initial and boundary conditions are specified. The theory is employed to predict the burn time and temperature of 10–100 μm iron particles, which are then compared with measurements, as the first validation case. The theoretical burn time agrees with the experiments almost perfectly at both low and high oxygen levels. The calculated particle temperature matches the measurements fairly well at relatively low oxygen mole fractions, whereas the theory overpredict the particle peak temperature due to the neglect of evaporation and the possible transition of the combustion regime.Novelty and significance statementFor the first time, we present a comprehensive and quantitative analytical theory elucidating the heterogeneous combustion of nonvolatile (metal) particles in the diffusion-limited regime. This novel theoretical model exhibits a remarkable capacity for quantitative prediction, obviating the need for supplementary information from numerical simulations or experimental data. The derivation process of analytical solutions for burn time and time-dependent particle temperature from conservation equations is elaborated, offering transparency and insight into the model’s foundations. To demonstrate the practical utility of the theory, we apply it to analyze the combustion of iron particles, providing valuable mathematical perspectives on the underlying processes. The model’s predictions for burn time and temperature align closely with experimental results, offering a partial validation of the theory within the realm of its applicable assumptions. This pioneering work contributes a robust and versatile analytical framework, advancing our understanding of diffusion-limited combustion phenomena of nonvolatile particles.