Properties Of Gas Research Articles

First-principles study of the effects of doping B, N, and O on the photoelectric properties of Cr adsorbed GaS.

To lessen the impact of the dangerous metal Cr, this paper applies the first principles to investigate the adsorption behavior and photoelectric properties of GaS on Cr. The effects of doped GaS on Cr adsorption behavior are investigated with four GaS systems, which are pure, boron (B)-doped, nitrogen (N)-doped, and oxygen (O)-doped, in order to maximize the characteristics of GaS for use in novel sectors, to obtain understanding of the impact of doping on the electronic structure and optical properties of GaS adsorption of Cr, as well as to promote the development of the material. Four GaS adsorbed Cr systems, pure, B-doped, N-doped, and O-doped, are optimized, and the optimized results show that the stable adsorption position of Cr on both pure and doped GaS is the top position of Ga atoms, whereas doped elements B, N, and O can promote the adsorption of Cr on GaS, and the order of the strength of this promotion is B > N > O. In this paper, molecular simulation calculations and analyses using the CASTEP module in the software Materials Studio are performed to simulate the structure optimization of GaS-adsorbed Cr materials doped with B, N, and O atoms by using the generalized gradient approximation (GGA) plane-wave pseudopotential approach [1] and the Perdew-Burke-Ernzerhof (PBE) generalized function [2]. From the convergence test, it is reasonable to set the K-point network to 4 × 4 × 1 and the truncation energy to 500eV [3]. In this paper, a 3 × 3 × 1 supercell structure with 18 S atoms and 18Ga atoms is selected. The convergence value of the iterative accuracy is 1.0e - 5eV/atom, and all the atomic forces are less than 0.02eV/Å. A vacuum layer of 16Å is also set in the C direction to avoid interlayer interactions of GaS. First, we optimize the geometry of the model and then analyze the nature of the adsorption energy and electronic structure corresponding to the model.

Gas transport model and numerical solution in roof rock based on the theory of free gas diffusion

Accurately identifying the source of coalbed methane is of great practical significance in preventing gas concentration overruns and improving extraction efficiency. At present, it is widely believed that underground gas mainly comes from coal desorption, and the mechanism of gas flow inside the coal seam is explored in depth, while the gas released inside the rock is often neglected, and there is insufficient understanding of its internal transportation law. In this study, the density gradient theory (FGDGD) in the coal matrix was used as a guide to characterize the adsorption and transport properties of gases within the rock. The anthracite and mudstone from the same roadway in Yuxi mine were selected for the experiments, and coal rock samples with particle sizes of 0.425 mm–0.25 mm were ground. The adsorption constant test and adsorption process experiments were carried out under the constant volume condition, and the transport behavior of gas within the rock was simulated and numerically solved, and the content and flow behavior of gas in the rock were discussed in detail. The results are as follows: (i) The simulation curves based on the density gradient model fit well with the experimental data for both coal and rock downholes, indicating that the gas transport law inside the rock downhole is also in accordance with the density gradient theory, which broadens the scope of application of the theory. (ii) The free gas diffusion coefficients Dks (rock) are smaller than Dks (coal) for the gases in the rock matrix and coal matrix, which may be due to the difference in the pore structure of the rock matrix, resulting in lower adsorption sites than those of the coal. (iii) Although the gas content inside the rock is relatively low compared with that of coal, it is significant for reducing the prediction error of gas influx in engineering practice. Therefore, it is necessary to consider the storage of gas in rocks and its migration behavior when studying the sources of gas emissions in engineering fields.

Acidic Gas Determination Using Indium Tin Oxide-Based Gas Sensors.

This work has presented gas sensors based on indium tin oxide (ITO) for the detection of SO2 and NO2. The ITO gas-sensing material was deposited by radio frequency (RF) magnetron sputtering. The properties of gas sensing could be improved by increasing the ratio of SnO2. The response characteristics of the gas sensor for detecting different concentrations of NO2 and SO2 were investigated. In the detection of NO2, the sensitivity was significantly improved by increasing the SnO2 ratio in ITO by 5%, and the response and recovery time were reduced significantly. However, the sensitivity of the sensor decreased with increasing SO2 concentration. From X-ray photoelectron spectroscopy (XPS) analysis, the gas-sensitive response mechanisms were different in the atmosphere of NO2 and SO2. The NO2 was adsorbed by ITO via physisorption but the SO2 had a chemical reaction with the ITO surface. The gas selectivity, temperature dependence, and environmental humidity of ITO-based gas sensors were systematically analyzed. The high detection sensitivity for acidic gas of the prepared sensor presented great potential for acid rain monitoring.

Hypobaric type oxygenators - physics and physiology.

Brain injury is still a serious complication after cardiac surgery. Gaseous microemboli (GME) are known to contribute to both short and longer-term brain injury after cardiac surgery. Hypobaric and novel dual-chamber oxygenators use the physical behaviors and properties of gases to reduce GME. The aim of this review was to present the basic physics of the gases, the mechanism in which the hypobaric and dual-chamber oxygenators reduce GME, their technical performance, the preclinical studies, and future directions. The gas laws are reviewed as an aid to understanding the mechanisms of action of oxygenators. Hypobaric-type oxygenators employ a high oxygen, no nitrogen environment creating a steep concentration gradient of nitrogen out of the blood and into the oxygenator, reducing the risk of GMEs forming. Adequately powered clinical studies have never been carried out with a hypobaric or dual-chamber oxygenator. These are required before such technology can be recommended for widespread clinical use.

Multiline molecular tagging velocimetry of nitric oxide at 100 kHz using an injection-seeded burst-mode OPO.

An injection-seeded, burst-mode optical parametric oscillator (OPO) operating at a repetition rate of 100 kHz is used to demonstrate the multiline molecular tagging velocimetry of an underexpanded jet using nitric oxide fluorescence. The very narrow linewidth of the OPO system, along with the relatively high pulse energies of the burst-mode system, enables efficient single-photon excitation of nitric oxide along multiple laser beam lines at a high repetition rate. Simultaneous one-dimensional velocity profile measurements were obtained of an underexpanded jet system at six different locations using a reference initial image and single-shot delayed images. A methodology for calculating the uncertainty of single-shot velocity is also described. Mean and root-mean-square velocity profiles are obtained at multiple locations simultaneously over a sampling time of 1 ms. The high-repetition-rate velocity measurements also appear to capture the onset of velocity oscillations and has the potential to reveal velocity frequency content occurring in the tens of kHz. The demonstrated velocimetry technique could be paired with other emerging burst-mode laser capabilities for a quantitative multiparameter gas property or multicomponent gas velocity measurements for supersonic and hypersonic flows, especially within ground test facilities that are limited to very short run durations.

An Artificial Neural Network-Based Fault Diagnostics Approach for Hydrogen-Fueled Micro Gas Turbines

The utilization of hydrogen fuel in gas turbines brings significant changes to the thermophysical properties of flue gas, including higher specific heat capacities and an enhanced steam content. Therefore, hydrogen-fueled gas turbines are susceptible to health degradation in the form of steam-induced corrosion and erosion in the hot gas path. In this context, the fault diagnosis of hydrogen-fueled gas turbines becomes indispensable. To the authors’ knowledge, there is a scarcity of fault diagnosis studies for retrofitted gas turbines considering hydrogen as a potential fuel. The present study, however, develops an artificial neural network (ANN)-based fault diagnosis model using the MATLAB environment. Prior to the fault detection, isolation, and identification modules, physics-based performance data of a 100 kW micro gas turbine (MGT) were synthesized using the GasTurb tool. An ANN-based classification algorithm showed a 96.2% classification accuracy for the fault detection and isolation. Moreover, the feedforward neural network-based regression algorithm showed quite good training, testing, and validation accuracies in terms of the root mean square error (RMSE). The study revealed that the presence of hydrogen-induced corrosion faults (both as a single corrosion fault or as simultaneous fouling and corrosion) led to false alarms, thereby prompting other incorrect faults during the fault detection and isolation modules. Additionally, the performance of the fault identification module for the hydrogen fuel scenario was found to be marginally lower than that of the natural gas case due to assumption of small magnitudes of faults arising from hydrogen-induced corrosion.

Nanosensors from Logistics and Supply Chain Perspective: A Literature Review

Introduction: Nanosensors are one of the most recent technologies obtained from the nanoworld. They have enhanced properties with potential applications in a wide spectrum of sectors. They exhibit exceptional properties in temperature monitoring, hazardous gas and vapor detection, humidity detection, as well as pathogens, toxins, and chemical contaminant detection. Among various nanosensor applications, one of the most recent usages of nanosensor technology is in logistics and supply chain management (SCM). Aim: This study aims at investigating the potential of nanosensor technology from logistics & SCM perspective, and specifically questions how can this technology contribute to food supply chains. Method: A systematic comprehensive literature review was conducted with the keywords: nanosensors & logistics, nanosensors & supply chain, nanosensors & smart packaging, and nanosensors & food logistics for the date range 2001-2022, covering a broad set of references. Findings revealed that nanosensors have significant potential in providing smart packaging, and improving traceability and visibility across all the logistics and SCM processes including end-to-end transportation and storage activities Result: Hybrids of different types of nanosensors with the existing material identification systems provide new levels of traceability and visibility in SCM, enabling accurate tracking of a variety of parameters. The study has shown that the intersection of nanotechnology and logistics & SCM domains is still immature. Conclusion: This intersection is especially critical for food supply chains for meeting their special traceability requirements, and for serving food safety and organic food traceability across all stages of logistics.

Flowing Bottomhole Pressure during Gas Lift in Unconventional Oil Wells

Summary We present artificial neural network (ANN) models for predicting the flowing bottomhole pressure (FBHP) of unconventional oil wells under gas lift operations. Well parameters, fluid properties, production/injection data, and bottomhole gauge pressures from 16 shale oil wells in Permian Basin, Texas, USA, are analyzed to determine key parameters affecting FBHP during the gas lift operation. For the reservoir fluid properties, several pressure-volume-temperature (PVT) models, such as Benedict-Webb-Rubin (BWR); Lee, Gonzalez, and Eakin; and Standing, among others, are examined against experimentally tuned fluid properties (i.e., viscosity, formation volume factor, and solution gas-oil ratio) to identify representative fluid (PVT) models for oil and gas properties. Pipe flow models (i.e., Hagedorn and Brown; Gray, Begs and Brill; and Petalas and Aziz) are also examined by comparing calculated FBHP against the bottomhole gauge pressures to identify a representative pipe flow model. Training and test data sets are then generated using the representative PVT and pipe flow models to develop a physics-based ANN model. The physics-based ANN model inputs are hydrocarbon fluid properties, liquid flow rate (qL), gas-liquid ratio (GLR), water-oil ratio (WOR), well true vertical depth (TVD), wellhead pressure (Pwh), wellhead temperature (Twh), and temperature gradient (dT/dh). A data-based ANN model is also developed based on only TVD, Pwh, qL, GLR, and WOR. Both physics- and data-based ANN models are trained through hyperparameter optimization using genetic algorithm and K-fold validation and then tested against the gauge FBHP. The results reveal that both models perform well with the FBHP prediction from field data with a normalized mean absolute error (NMAE) of around 10%. However, a comparison between results from the physics- and data-based ANN models shows that the accuracy of the physics-based model is higher at the later phase of the gas lift operation when the steady-state pipe flow is well established. On the contrary, the data-based model performs better for the early phase of gas lift operation when transient flow behavior is dominant. Developed ANN models and workflows can be applied to optimize gas lift operations under different fluid and well conditions.

Defect sensitivity and high-cycle fatigue resistance of arc-welded 2219 aluminum alloy at 77 K

This study investigated the tensile and high-cycle fatigue (HCF) properties of a tungsten inert gas (TIG)-welded 2219 aluminum alloy at room temperature (RT) and 77 K for the first time. Defect-sensitivity-based fatigue strength and life prediction models were proposed to link welding defects with fatigue properties at cryogenic temperatures. The findings revealed that the yield strength, ultimate tensile strength, and fatigue strength of 2219 welded joints at 77 K were significantly improved by 29.7 %, 34.1 %, and 60.4 %, respectively, compared to those at RT. The largest possible pore defects near the weld surface were predicted using a combination of laboratory X-ray computed microtomography and the extreme value statistics (EVS) method. Furthermore, the fatigue strength was predicted by considering the maximum defect size in terms of the El-Haddad-based Kitagawa–Takahashi (K–T) diagram. The predicted fatigue strength was 95.5 MPa with an error of 5.4 % at RT, whereas at 77 K, the predicted value was 144.5 MPa with an error of 10.8 %. Finally, a fatigue life prediction model at both RT and 77 K was proposed based on a modified K–T diagram and Murakami’s S-N prediction model. The combination of the fatigue life prediction model and the maximum possible defect size based on EVS can provide slightly conservative predictions of the fatigue life without conducting a large number of HCF tests.

Effect of fluorine tin oxide substrate on the deposited SnO2: Ni thin films properties for gas sensing

This study explores the deposition of Tin Oxide and Ni-doped SnO2 thin films (NSO) via spray pyrolysis from aqueous solutions. The deposition process was conducted under uniform conditions on two substrates, namely glass and fluorine tin oxide (FTO), with varying Ni percentages. The aim was to evaluate their potential for gas sensing applications. The as-deposited thin films exhibit diverse properties influenced by both Ni content and substrate type. X-Ray Diffraction (XRD) measurements reveal polycrystalline structures characterized by broad SnO2 diffraction lines, with the emergence of a NiO phase, particularly evident at higher Ni content. Notably, thin films deposited on FTO show the appearance of a secondary phase of SnO and enhanced crystallinity. Furthermore, lattice parameters and crystallite size decrease with increasing Ni percentage. The Field Emission Scanning Electron Microscopy (FE-SEM) analysis highlights significant alterations in surface nanostructures based on nickel content and substrate type. Higher nickel concentrations result in the formation of cauliflower-like structures, varying in size and density. This structural divergence significantly impacts the sensitivity of NSO-based NO2 gas sensors. Particularly, thin films with 20 % Ni, especially those deposited on FTO, exhibit optimal configurations for gas sensor applications, display sensitivity of 501 % at 100 ppm for nanocrystalline NSO/FTO compared to 436 % for glass-deposited samples. Our findings highlight the crucial role of Ni content and substrate type in modifying the structural and sensing properties of NSO thin films, for enhanced gas sensing applications.

Density distributions, magnetic field structures, and fragmentation in high-mass star formation

Context. The fragmentation of high-mass star-forming regions depends on a variety of physical parameters, including density, the magnetic field, and turbulent gas properties. Aims. We evaluate the importance of the density and magnetic field structures in relation to the fragmentation properties during high-mass star formation. Methods. Observing the large parsec-scale Stokes I millimeter dust continuum emission with the IRAM 30 m telescope and the intermediate-scale (<0.1 pc) polarized submillimeter dust emission with the Submillimeter Array toward a sample of 20 high-mass star-forming regions allows us to quantify the dependence of the fragmentation behavior of these regions on the density and magnetic field structures. Results. Based on the IRAM 30 m data, we infer density distributions n ∝ r−p of the regions with typical power-law slopes p around ~1.5. There is no obvious correlation between the power-law slopes of the density structures on larger clump scales (~1 pc) and the number of fragments on smaller core scales (<0.1 pc). Comparing the large-scale single-dish density profiles to those derived earlier from interferometric observations at smaller spatial scales, we find that the smaller-scale power-law slopes are steeper, typically around ~2.0. The flattening toward larger scales is consistent with the star-forming regions being embedded in larger cloud structures that do not decrease in density away from a particular core. The magnetic fields of several regions appear to be aligned with filamentary structures that lead toward the densest central cores. Furthermore, we find different polarization structures; some regions exhibit central polarization holes, whereas other regions show polarized emission also toward the central peak positions. Nevertheless, the polarized intensities are inversely related to the Stokes I intensities, following roughly a power-law slope of ∝ SI−0.62. We estimate magnetic field strengths between ~0.2 and ~4.5 mG, and we find no clear correlation between magnetic field strength and the fragmentation level of the regions. A comparison of the turbulent to magnetic energies shows that they are of roughly equal importance in this sample. The mass-to-flux ratios range between ~2 and ~7, consistent with collapsing star-forming regions. Conclusions. Finding no clear correlations between the present-day large-scale density structure, the magnetic field strength, and the smaller-scale fragmentation properties of the regions, indicates that the fragmentation of high-mass star-forming regions may not be affected strongly by the initial density profiles and magnetic field properties. However, considering the limited evolutionary range and spatial scales of the presented CORE analysis, future research directions should include density structure analysis of younger regions that better resemble the initial conditions, as well as connecting the observed intermediate-scale magnetic field structure with the larger-scale magnetic fields of the parental molecular clouds.

Semi-Analytical Reservoir Modeling of Non-Linear Gas Diffusion with Gas Desorption Applied to the Horn River Basin Shale Gas Play, British Columbia (Canada)

Adsorbed gas may account for a significant part of the gas resources in shale gas and coalbed methane plays. Understanding gas sorption behaviors and integrating gas desorption into analytical reservoir modeling and an associated transient performance analysis are important for evaluating a system’s gas desorption ability and further analyzing its CO2 injectability, utilization, and storage capacity. However, gas desorption, along with other pressure-dominated gas properties, increases a system’s non-linearity in theoretical studies. Few studies on analytical modeling have integrated the gas desorption feature into a non-linear system and validated the model’s accuracy. In this study, the desorbed gas due to pressure decay was treated as an additional source/sink term in the source-and-sink function methods. This method was combined with the integral image method in a semi-analytical manner to determine the amount of gas desorption. Fundamental reservoir and gas properties from the Horn River Basin shale gas play were chosen to evaluate the methodology and the performance of the associated production well. The results were compared with the commercial fine-gridding numerical simulation software, and good matches were achieved. The results showed that the desorbed gas released from rock will supply free-gas flow when the pressure significantly decreases due to gas production. The production wellbore pressure can be maintained at a higher level, and the production rate was higher than in cases where gas desorption was not considered, depending on the operating conditions.

A case study of an early galaxy cluster with the Athena X-IFU

Context. Observations of the hot gas in distant clusters of galaxies, though challenging, are key to understanding the role of intense galaxy activity, supermassive black hole feedback, and chemical enrichment in the process of massive halo assembly. Aims. Using X-ray hyperspectral data alone, we assess the feasibility of retrieving the thermodynamical hot gas properties and chemical abundances of a z = 2 galaxy cluster of mass M500 = 7 × 1013 M⊙, extracted from the Hydrangea hydrodynamical simulations. Methods. We created mock X-ray observations of the future X-ray Integral Field Unit (X-IFU) on board the Athena mission. By forward-modelling the measured 0.4 − 1 keV surface brightness, the projected gas temperature and abundance profiles, we reconstructed the three-dimensional distribution for the gas density, pressure, temperature, and entropy. Results. Thanks to its large field of view, high throughput, and exquisite spectral resolution, one X-IFU exposure lasting 100 ks enabled the reconstruction of density and pressure profiles with 20% precision out to a characteristic radius of R500, accounting for each quantity’s intrinsic dispersion in the Hydrangea simulations. Reconstruction of abundance profiles requires both higher signal-to-noise ratios and specific binning schemes. We assess the enhancement brought by longer exposures and by observing the same object at later evolutionary stages (at z = 1 and 1.5). Conclusions. Our analysis highlights the importance of scatter in the radially binned gas properties, which induces significant effects on the observed projected quantities. The fidelity of the reconstruction of gas profiles is sensitive to the degree of mixing of the gas components along the line of sight. Future analyses should aim to involve dedicated hyper-spectral models and fitting methods that are able to grasp the complexity of such three-dimensional, multi-phase, diffuse gas structures.

Combining a noble gas with radiotherapy: glutamate receptor antagonist xenon may act as a radiosensitizer in glioblastoma

BackgroundIonotropic glutamate receptors α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) and N-methyl-D-aspartate receptor (NMDAR) modulate proliferation, invasion and radioresistance in glioblastoma (GB). Pharmacological targeting is difficult as many in vitro-effective agents are not suitable for in patient applications. We aimed to develop a method to test the well tolerated AMPAR- and NMDAR-antagonist xenon gas as a radiosensitizer in GB.MethodsWe designed a diffusion-based system to perform the colony formation assay (CFA), the radiobiological gold standard, under xenon exposure. Stable and reproducible gas atmosphere was validated with oxygen and carbon dioxide as tracer gases. After checking for AMPAR and NMDAR expression via immunofluorescence staining we performed the CFA with the glioblastoma cell lines U87 and U251 as well as the non-glioblastoma derived cell line HeLa. Xenon was applied after irradiation and additionally tested in combination with NMDAR antagonist memantine.ResultsThe gas exposure system proved compatible with the CFA and resulted in a stable atmosphere of 50% xenon. Indications for the presence of glutamate receptor subunits were present in glioblastoma-derived and HeLa cells. Significantly reduced clonogenic survival by xenon was shown in U87 and U251 at irradiation doses of 4–8 Gy and 2, 6 and 8 Gy, respectively (p < 0.05). Clonogenic survival was further reduced by the addition of memantine, showing a significant effect at 2–8 Gy for both glioblastoma cell lines (p < 0.05). Xenon did not significantly reduce the surviving fraction of HeLa cells until a radiation dose of 8 Gy.ConclusionThe developed system allows for testing of gaseous agents with CFA. As a proof of concept, we have, for the first time, unveiled indications of radiosensitizing properties of xenon gas in glioblastoma.

A φ-divergence based finite element moment method for the polyatomic ES-BGK Boltzmann equation

Bonafide numerical simulations of transport phenomena in rarefied gases are becoming increasingly important in science and engineering. To enhance the accuracy of the rarefied-gas model, it is important to account for the internal structure of the gas molecules and exceed the standard monatomic description. A suitable model for polyatomic rarefied-gas flows that balances between accuracy and complexity is the polyatomic ES-BGK Boltzmann equation. In this work we consider numerical approximation of the ES-BGK Boltzmann equation based on a Method of Moments (MoM) approximation in the velocity/internal-energy dependence, and DGFEM approximation in the spatial dependence. In the MoM setting, only two moments have to be considered in internal-energy dependence to capture the correct macroscopic gas properties, viz. the thermal conductivity, the adiabatic coefficient and the shear and dilational viscosity. In the presentation of the method, we focus specifically on the evaluation of the integrals in the velocity and intrinsic-variable dependence appearing in the MoM formulation and on linearization of the formulation. We present numerical results for the heat flux between two parallel heated plates, mass flow in a micro-channel, a poly-atomic lid-driven cavity problem, and rarefied-gas flow around a sphere. The computed results are compared with corresponding theoretical and experimental results. The results support the suitability of the FEM-MoM approximation of the ES-BGK Boltzmann equations as a model for predicting transport phenomena in rarefied-gas flows.

Enhanced capturing of acidic components (CO2/SO2) from Flue gas by MAF-66 produced by a facile and one pot synthetic procedure: Experimental, isotherms and modeling

This study focuses on the synthesis and characterization of MAF-66, a metal-organic framework with excellent adsorption properties for the flue gases containing carbon dioxide (CO2) and sulfur dioxide (SO2) impurities. The sol-gel method was employed using various sources of zinc to approach to the qualified product with the highest yield. The best results were achieved by mixing zinc nitrate solution, ammonia, and amitrol at room temperature, followed by washing the product with methanol at 40 °C and drying it under vacuum conditions at 200 °C. The characterization analyses, confirmed the desired crystalline phase structure of MAF-66, with the specific surface area of 1226 m2/g and pore volume of 0.65 cm3/g. The synthesized material exhibited the presence of N-H functional groups on the surface. Equilibrium adsorption measurements at the two temperatures of 35 and 45 °C showed high loading and selectivity of CO2 and SO2 over nitrogen, at low and moderate pressures. The ideal selectivities of CO2/N2 and SO2/N2 were obtained 194 and 357, respectively, at 35 °C. The isosteric heats of adsorptions were determined as − 25.4 kJ/mol for CO2 and − 36.1 kJ/mol for SO2. The synthesized material demonstrated good stability and reliability during regeneration and reuse, making it suitable for cyclic adsorption-desorption processes in flue gas refining.

Gas Morphology of Milky Way–like Galaxies in the TNG50 Simulation: Signals of Twisting and Stretching

We present an in-depth analysis of gas morphologies for a sample of 25 Milky Way–like galaxies from the IllustrisTNG TNG50 simulation. We constrain the morphology of cold, warm, hot gas, and gas particles as a whole using a local shell iterative method and explore its observational implications by computing the hard-to-soft X-ray ratio, which ranges between 10−3 and 10−2 in the inner ∼50 kpc of the distribution and 10−5–10−4 at the outer portion of the hot gas distribution. We group galaxies into three main categories: simple, stretched, and twisted. These categories are based on the radial reorientation of the principal axes of the reduced inertia tensor. We find that a vast majority (77%) of the galaxies in our sample exhibit twisting patterns in their radial profiles. Additionally, we present detailed comparisons between (i) the gaseous distributions belonging to individual temperature regimes, (ii) the cold gas distributions and stellar distributions, and (iii) the gaseous distributions and dark matter (DM) halos. We find a strong correlation between the morphological properties of the cold gas and stellar distributions. Furthermore, we find a correlation between gaseous distributions with a DM halo that increases with gas temperature, implying that we may use the warm–hot gaseous morphology as a tracer to probe the DM morphology. Finally, we show gaseous distributions exhibit significantly more prolate morphologies than the stellar distributions and DM halos, which we hypothesize is due to stellar and active galactic nucleus feedback.

Retracted: Study on Rheological Properties of Coal Rock Containing Gas under Disturbance Conditions

Retracted: Study on Rheological Properties of Coal Rock Containing Gas under Disturbance Conditions

Multiwavelength exploration of Extreme Emission Line Galaxies detected in miniJPAS survey

ABSTRACT Extreme Emission Line Galaxies (EELGs) stand as remarkable objects due to their extremely metal poor environment and intense star formation. Considered as local analogues of high-redshift galaxies in the peak of their star-forming activity, they offer insights into conditions prevalent during the early Universe. Assessment of their stellar and gas properties is therefore of critical importance, which requires the assembly of a considerable sample, comprehending a broad redshift range. The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (JPAS) plays a significant role in assembling such a sample, encompassing ∼8000 $\rm deg^2$ and employing 54 narrow-band optical filters. The present work describes the development and subsequent application of the tools that will be employed in the forthcoming JPAS spectrophotometric data, allowing for the massive and automated characterization of EELGs that are expected to be identified. This fully automated pipeline (requiring only the object coordinates from users) constructs Spectral Energy Distributions (SEDs) by retrieving virtually all the available multiwavelength photometric data archives, employs SED fitting tools, and identifies optical emission lines. It was applied to the sample of extreme line emitters identified in the miniJPAS Survey, and its derived physical properties such as stellar mass and age, coupled with fundamental relations, mirror results obtained through spectral modelling of SDSS spectra. Thorough testing using galaxies with documented photometric measurements across different wavelengths confirmed the pipeline’s accuracy, demonstrating its capability for automated analysis of sources with varying characteristics, spanning brightness, morphology, and redshifts. The modular nature of this pipeline facilitates any addition from the user.

A cooling flow around the low-redshift quasar H1821+643

ABSTRACT H1821+643 is the nearest quasar hosted by a galaxy cluster. The energy output by the quasar, in the form of intense radiation and radio jets, is captured by the surrounding hot atmosphere. Here, we present a new deep Chandra observation of H1821+643 and extract the hot gas properties into the region where Compton cooling by the quasar radiation is expected to dominate. Using detailed simulations to subtract the quasar light, we show that the soft-band surface brightness of the hot atmosphere increases rapidly by a factor of ∼30 within the central $\sim\!{10}\ \rm kpc$. The gas temperature drops precipitously to $\lt 0.4\rm \,\, keV$ and the density increases by over an order of magnitude. The remarkably low metallicity here is likely due to photoionization by the quasar emission. The variations in temperature and density are consistent with hydrostatic compression of the hot atmosphere. The extended soft-band peak cannot be explained by an undersubtraction of the quasar or scattered quasar light and is instead due to thermal interstellar medium. The radiative cooling time of the gas falls to only $12\pm 1\rm \,\, Myr$, below the free fall time, and we resolve the sonic radius. H1821+643 is therefore embedded in a cooling flow with a mass deposition rate of up to $3000\ {\rm M}_{\odot}\,{\rm yr}^{-1}$. Multiwavelength observations probing the star-formation rate and cold gas mass are consistent with a cooling flow. We show that the cooling flow extends to much larger radii than can be explained by Compton cooling. Instead, the active galactic nucleus appears to be underheating the core of this cluster.