Properties Of Gas Research Articles

Modeling and Experimental Validation of Cell Morphology in Microcellular-Foamed Polycaprolactone.

This study investigates the modeling and experimental validation of cell morphology in microcellular-foamed polycaprolactone (PCL) using supercritical carbon dioxide (scCO2) as the blowing agent. The microcellular foaming process (MCP) was conducted using a solid-state batch foaming process, where PCL was saturated with scCO2 at 6 to 9 MPa and 313 K, followed by depressurization at a rate of -0.3 and -1 MPa/s. This study utilized the Sanchez-Lacombe equation of state and the Peng-Robinson-Stryjek-Vera equation of state to model the solubility and density of the PCL-CO2 mixture. Classical nucleation theory was modified and combined with numerical analysis to predict cell density, incorporating factors such as gas absorption kinetics, the role of scCO2 in promoting nucleation, and the impact of depressurization rate and saturation pressure on cell growth. The validity of the model was confirmed by comparing the theoretical predictions with experimental and reference data, with the cell density determined through field-emission scanning electron microscopy analysis of foamed PCL samples. This study proposes a method for predicting cell density that can be applied to various polymers, with the potential for wide-ranging applications in biomaterials and industrial settings. This research also introduces a Python-based numerical analysis tool that allows for easy calculation of solubility and cell density based on the material properties of polymers and penetrant gases, offering a practical solution for optimizing MCP conditions in different contexts.

Effects of regulating the cathode gas properties on the ammonia-fueled solid oxide fuel cell. Part I. Parasitic power consumption and electrical efficiency after increasing O2 and H2O

This study designed and simulated a kW-scale SOFC system equipped with liquified O2 and NH3 tanks for unmanned underwater vehicles (UUVs). Optimizing the parasitic power consumption and electrical efficiency was performed via using oxygen-enriched cathode gas, in-cell cracking of ammonia and adding steam into cathode gas coupled with phase change of recycle steam. The results show increasing O2 concentration helps improve the net system electrical efficiency from 47.9% at simulate air to 51.7% at pure O2. The use of in-cell cracking increases the net system electrical efficiency by 1.3% on this basis. Interestingly, substitution of O2 to H2O would slightly reduce the net electrical efficiency of the system with O2-enriched cathode gas (e.g., decreased by 0.2% when using 40% H2O); however, substitution of N2 to H2O would help improve the net electrical efficiency of the system with simulated air as cathode gas (e.g., increased by 1.2% when using 40% H2O).

Ne viii in the Warm-hot Circumgalactic Medium of FIRE Simulations and in Observations

The properties of warm-hot gas around ∼L * galaxies can be studied with absorption lines from highly ionized metals. We predict Ne viii column densities from cosmological zoom-in simulations of halos with masses in ∼1012 and ∼1013 M ☉ from the Feedback in Realistic Environments (FIRE) project. Ne viii traces the volume-filling, virial-temperature gas in ∼1012 M ☉ halos. In ∼1013 M ☉ halos the Ne viii gas is clumpier, and biased toward the cooler part of the warm-hot phase. We compare the simulations to observations from the COS Absorption Survey of Baryon Harbors (or CASBaH) and COS Ultraviolet Baryon Survey (or CUBS). We show that when inferring halo masses from stellar masses to compare simulated and observed halos, it is important to account for the scatter in the stellar-mass–halo-mass relation, especially at M ⋆ ≳ 1010.5 M ☉. Median Ne viii columns in the fiducial FIRE-2 model are about as high as observed upper limits allow, while the simulations analyzed do not reproduce the highest observed columns. This suggests that the median Ne viii profiles predicted by the simulations are consistent with observations, but that the simulations may underpredict the scatter. We find similar agreement with analytical models that assume a product of the halo gas fraction and metallicity (relative to solar) ∼0.1, indicating that observations are consistent with plausible circumgalactic medium temperatures, metallicities, and gas masses. Variants of the FIRE simulations with a modified supernova feedback model and/or active galactic nuclei feedback included (as well as some other cosmological simulations from the literature) more systematically underpredict Ne viii columns. The circumgalactic Ne viii observations therefore provide valuable constraints on simulations that otherwise predict realistic galaxy properties.

Theoretical designing of Ni-doped PtSTe monolayer as a promising gas sensor upon thermal runaway gases in the Li-ion battery

This study proposes Ni-doped Janus PtSTe (Ni-PtSTe) as a novel sensing material for detecting three critical gases (CO, CO2, and C2H4), with potential applications in gas sensors and Li-ion battery monitoring. The Ni-doping favors the Te surface of the PtSTe monolayer, with a formation energy of -1.19 eV. The adsorption capacity follows the order: CO > C2H4 > CO2, with chemisorption in CO and C2H4 systems and physisorption in CO2 system. The analysis of electronic properties in gas adsorbed Ni-PtSTe systems indicate a reduced bandgap in CO and C2H4 systems, resulting in the sensing response of 99.25% and 97.71%, respectively. The work function increases significantly in the presence of CO and C2H4, suggesting its suitability as a work function-based sensor. These results highlight the promising sensing capabilities of Ni-PtSTe monolayer, expanding the horizon for PtSTe-based materials and inspiring cutting-edge research.

Non-invasive ultrasonic sensing of internal conditions on a partial full-scale spent nuclear fuel canister mock-up

The safe storage of spent nuclear fuel (SNF) in dry cask storage systems (DCSSs) is critical to the nuclear fuel cycle and the future of nuclear energy. A critical component of DCSSs is the SNF canister. The canister is a sealed stainless-steel structure, which is first vacuum dried and then backfilled with helium. The structural deterioration within a canister can be monitored through its internal gas properties. This monitoring serves as the driving force behind the non-invasive ultrasonic sensing approach in this paper. A major challenge in collecting gas-borne signals using ultrasonic sensing is the impedance mismatch between the stainless-steel canister and the helium gas inside. Only a small fraction of the ultrasonic signal makes its way from the transmitter to the receiver through the gas medium. In this paper, experimental studies on a partial full-scale canister mock-up were carried out to capture the gas-borne signals. Damping materials were applied on the outside, and blocking and unblocking tests were conducted to identify the gas-borne signal. The research results showed that the excitation frequency played an important role in maximizing the gas-borne signals. The gas-borne signal was successfully detected at around the theoretical time-of-flight (TOF) at 225 kHz. A high signal-to-noise ratio (SNR) was achieved in the measurements. Next, acoustic impedance matching (AIM) layers were added, and it was found that the gas signal energy was improved by 160.4% compared with that of no AIM layers. Subsequently, the relative humidity (RH) level and temperature of the gas were varied to simulate abnormal internal conditions of the canister. The non-invasive testing system demonstrated reliability and sensitivity in detecting gas temperature and RH variations. Theoretical calculations demonstrated the potential for detecting low-level xenon and air within an actual SNF canister filled with helium. Last, an active noise cancellation (ANC) method, previously developed by the authors, was verified on the canister mock-up for the first time. The results showed that the SNR of the gas signal was improved by 213.6% compared with that of no ANC.

Bridging gas and aerosol properties between the northeastern US and Bermuda: analysis of eight transit flights

Abstract. The western North Atlantic Ocean is strongly influenced by continental outflow, making it an ideal region to study the atmospheric transition from a polluted coastline to the marine environment. Utilizing eight transit flights between the NASA Langley Research Center (LaRC) in Hampton, Virginia, and the remote island of Bermuda from NASA's Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE), we examine the evolution of trace gas and aerosol properties off the US East Coast. The first pair of flights flew along the wind trajectory of continental outflow, while the other flights captured a mix of marine and continental air mass sources. For measurements within the boundary layer (BL), there was an offshore decline in particle N<100 nm, N>100 nm, CH4, CO, and CO2 concentrations, all leveling off around ∼900 km offshore from the LaRC. These trends are strongest for the first pair of flights. In the BL, offshore declines in organic mass fraction and increases in sulfate mass fraction coincide with increasing hygroscopicity based on f(RH) measurements. Free troposphere measurements show a decline in N<100 nm, but other measured parameters are more variable when compared to the prominent offshore gradients seen in the BL. Pollution layers exist in the free troposphere, such as smoke plumes, that can potentially entrain into the BL. This work provides detailed case studies with a broad set of high-resolution measurements to further our understanding of the transition between continental and marine environments.

A Thermal Model for a Hybrid Gas Bearing System in Oil-Free Turbochargers

Abstract With little drag friction, gas bearings operate at high rotor speed and high temperature and thus enable long operating life along with material damping for mechanical energy dissipation. However, most computational tools for modeling gas bearings are not accessible to bearing manufacturers or potential end-users, and the models are restricted to specific geometries and operating conditions or are missing important features, thus limiting their utility. This paper presents the thermal energy transport in a hybrid gas bearing for oil-free turbochargers with integrated heat and fluid flow models to produce a comprehensive thermo-hydrodynamic analysis predictive tool, and to design and evaluate air-lubricated gas bearings by predictions and experiments. An efficient algorithm couples the solution of the Reynolds equations and the thermal energy transport equations in the film between the rotor and a pad of the hybrid gas bearing, and updates the temperature-dependent viscosity and film thicknesses during the iterative process. The test repeats and averaged for each rotor speed from 2 krpm to 22 krpm at intervals of 2 krpm, for supply pressure varying along 25 psi to 100 psi and predicted film temperature matches well with the measured one. The parameters of interest in this analysis include the gas supply condition, bearing configuration, and the gas properties at high altitudes and high rotation speeds. The parametric study results show the density and kinematic viscosity are the most dominant properties of the gas lubrication for the film temperature.

Teaching Aero-Engine Performance: From Analytics to Hands-On Exercises Using Gas Turbine Performance Software

Abstract In this paper, we present an approach for teaching turbojet engine performance that combines mathematical analysis with the use of performance software to provide students with a comprehensive and in-depth understanding of engine performance and how it is affected by design parameter choices. In the first part, we present the derivation of a universally valid analytical model for turbojet engine cycle design, which is the basis of the propulsion courses at RWTH Aachen University. The analytical model allows for the calculation of specific thrust as well as thermal and propulsive efficiencies as a function of pressure ratios and burner exit temperature. These are all expressed as differentiable functions. Their mathematical extremes form a basis for examining the intricate relationships in turbojet engine design. In the second part, we move from theory to practice. We utilize the GasTurb software, computing turbojet engine cycles for a wide range of cycle design parameters. The analytically derived trends are validated and errors introduced by simplifications are assessed. Differences between the analytical approach and software-based performance simulations of real engines, like temperature-dependent gas properties and secondary air systems, are emphasized and discussed, thus providing a bridge to real-world applications. In summary, this paper describes a two-step approach to teaching turbojet engine design using analytics and performance software. Each approach alone can be used to enrich and extend existing performance courses. Combining the approaches has significant benefits, improving understanding and inspiring students to pursue further research in the field of propulsion.

A coarse-grained approach to modeling gas transport in swelling porous media

In many engineering applications, understanding gas adsorption and its induced swelling in nanoporous materials is crucial. In this study, we propose a novel coarse-grained molecular dynamics (CGMD) model with gas-gas, solid-solid, and gas-solid interactions explicitly controlled to achieve the coupling between gas transport and solid deformation at the microscale. The CGMD model has the capability to recover solid and gas properties, including density, Young's modulus of the solid, and viscosity of the gas to generate a broad range of swelling ratios relevant to nanostructures by using the innovative bead-spring chain networks. A comparison is made between gas transport through deformable and non-deformable nanochannels of varying sizes (35.4–123.9 nm), which is also compared with the macroscopic Hagen-Poiseuille equation. The proposed model has been further tested in a simplified nanoporous medium composed of four randomly distributed spherical solids. The Kozeny-Carman equation can generally describe the relationship between permeability and porosity, but small deviations are observed in the case of swelling porous media. Our results justify the effect of swelling on reducing gas permeability and provide a new approach to modeling gas transport in swelling porous media at the microscale within the framework of CGMD, with potential applications spanning nanofluidics, energy storage technologies, and environmental nanotechnology.

Deep learning the intergalactic medium using lyman-alpha forest at 4 ≤ z ≤ 5

Abstract Unveiling the thermal history of the intergalactic medium (IGM) at 4 ≤ z ≤ 5 holds the potential to reveal early onset He ii reionization or lingering thermal fluctuations from H i reionization. We set out to reconstruct the IGM gas properties along simulated Lyman-alpha forest data on pixel-by-pixel basis, employing deep neural networks. Our approach leverages the Sherwood-Relics simulation suite, consisting of diverse thermal histories, to generate mock spectra. Our convolutional and residual networks with likelihood metric predicts the Lyα optical depth-weighted density or temperature for each pixel in the Lyα forest skewer. We find that our network can successfully reproduce IGM conditions with high fidelity across range of instrumental signal-to-noise. These predictions are subsequently translated into the temperature-density plane, facilitating the derivation of reliable constraints on thermal parameters. This allows us to estimate temperature at mean cosmic density, T0 , with one sigma confidence, $\delta {\rm T_{\rm 0}}\,$≲ 1000K, using only one 20h−1cMpc sightline (Δz ≃ 0.04) with a typical reionization history. Existing studies utilize redshift pathlength comparable to Δz ≃ 4 for similar constraints. We can also provide more stringent constraints on the slope (1σ confidence interval, δγ ≲ 0.1) of the IGM temperature-density relation as compared to other traditional approaches. We test the reconstruction on a single high signal-to-noise observed spectrum (20h−1cMpc segment), and recover thermal parameters consistent with current measurements. This machine learning approach has the potential to provide accurate yet robust measurements of IGM thermal history at the redshifts in question.

Impact of Al profile in high-Al content AlGaN/GaN HEMTs on the 2DEG properties

Ultra-thin high-Al content barrier layers can enable improved gate control and high-frequency operation of AlGaN/GaN high electron mobility transistors (HEMTs) but the precise composition control is very challenging. In this work, we investigate the compositional profiles of AlxGa1−xN/GaN HEMT structures with targeted Al content in the barrier layer, x = 0.50, 0.70, and 1, and thickness in the sub-10 nm range in correlation with the two-dimensional electron gas (2DEG) properties. The HEMT structures are grown by metal-organic chemical vapor deposition on SiC. The maximum Al content in the barrier layer, experimentally determined by scanning transmission electron microscopy combined with energy-dispersive x-ray spectroscopy, is found to be lower than that intended and the deviations from the designed structures increase progressively with increasing x. Compositionally sharp interface between GaN and Al0.46Ga0.54N and box-like Al profile is achieved for intended x∼0.50 while pronounced Al grading is found in the samples with intended x of 0.70 and 1, with a maximum Al content of 0.78 reached for the HEMT structure with intended AlN barrier layer. The impact of the experimentally determined Al profiles on the 2DEG properties, obtained by contactless and electrical Hall effect measurements and coupled with self-consistent solution of the Poisson–Schrödinger equation, is evaluated and discussed. It is shown that the observed deviations from the intended Al profiles have a negative effect on the 2DEG confinement and result in reduced mobility parameters, which have significant implications for the implementation of high-Al content AlGaN/GaN structures in high-frequency devices.

Decoupling and predicting natural gas deviation factor using machine learning methods

Accurately predicting the deviation factor (Z-factor) of natural gas is crucial for the estimation of natural gas reserves, evaluation of gas reservoir recovery, and assessment of natural gas transport in pipelines. Traditional machine learning algorithms, such as Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Artificial Neural Network (ANN) and Bidirectional Long Short-Term Memory Neural Networks (BiLSTM), often lack accuracy and robustness in various situations due to their inability to generalize across different gas components and temperature-pressure conditions. To address this limitation, we propose a novel and efficient machine learning framework for predicting natural gas Z-factor. Our approach first utilizes a signal decomposition algorithm like Variational Mode Decomposition (VMD), Empirical Fourier Decomposition (EFD) and Ensemble Empirical Mode Decomposition (EEMD) to decouple the Z-factor into multiple components. Subsequently, traditional machine learning algorithms is employed to predict each decomposed Z-factor component, where combination of SVM and VMD achieved the best performance. Decoupling the Z-factors firstly and then predicting the decoupled components can significantly improve prediction accuracy of all traditional machine learning algorithms. We thoroughly evaluate the impact of the decoupling method and the number of decomposed components on the model’s performance. Compared to traditional machine learning models without decomposition, our framework achieves an average correlation coefficient exceeding 0.99 and an average mean absolute percentage error below 0.83% on 10 datasets with different natural gas components, high temperatures, and pressures. These results indicate that hybrid model effectively learns the patterns of Z-factor variations and can be applied to the prediction of natural gas Z-factors under various conditions. This study significantly advances methodologies for predicting natural gas properties, offering a unified and robust solution for precise estimations, thereby benefiting the natural gas industry in resource estimation and reservoir management.

Regulating star formation in a magnetized disc galaxy

ABSTRACT We use high-resolution magnetohydrodynamic simulations of isolated disc galaxies to investigate the co-evolution of magnetic fields with a self-regulated, star-forming interstellar medium (ISM). The simulations are conducted using the ramses adaptive mesh refinement code on the standard agora initial condition, with gas cooling, star formation, and feedback. We run galaxies with a variety of initial magnetic field strengths. The fields evolve and achieve approximate saturation within 500 Myr, but at different levels. The galaxies reach a quasi-steady state, with slowly declining star formation due to both gas consumption and increase in the field strength at intermediate ISM densities. We connect this behaviour to differences in the gas properties and overall structure of the galaxies. Stronger magnetic fields limit supernova bubble sizes. Different cases support the ISM using varying combinations of magnetic pressure, turbulence, and thermal energy. Initially, $\gtrsim\!\! 1\ \mu \mathrm{ G}$ magnetic fields evolve modestly and dominate support at all radii. Conversely, initially weaker fields grow through feedback and turbulence but never dominate the support. This is reflected in the stability of the gas disc. This interplay determines the overall distribution of star formation in each case. We conclude that an initially weak field can grow to produce a realistic model of a local disc galaxy, but starting with typically assumed field strengths ($\gtrsim\!\! 1\ \mu \mathrm{ G}$) will not.

Recent Developments on the Hi Gas of Low-Redshift Galaxies Seen by the 21cm Emission Lines

Abstract As a major interstellar medium, the atomic neutral hydrogen (Hi) plays an important role in the galaxy evolution. It provides the ingredient for star formation, and sensitively traces the internal processes and external perturbations influencing the galaxy. With the beginning of many new radio telescopes and surveys, Hi may make a more significant contribution to the understanding of galaxies in the near future. This review discusses the major development of the 21 cm emission-line Hi observations and studies in the past few years, including its scaling relations with other galaxy properties, its kinematics and structures, its role in environmental studies, and its constraints on hydrodynamical simulations. The local-Universe Hi scaling relations of stellar-mass-selected samples extend smoothly to 109M⊙ stellar mass, with a tentative evolution to the redshift of ~0.1. The development of measurement techniques enables better estimations of Hi non-circular motion, dispersion, and thickness, and new observations revealed extended or extra-planar Hi structures, both helpfully constraining the gas accretion, stellar feedback, and star formation processes of galaxy evolution models. Hi is very useful for tracing the satellite evolution in dense environments, the studies of which would benefit from ongoing blind Hi surveys. Although simulations still cannot fully reproduce Hi gas properties, they help to understand the role of possible factors in regulating Hi properties.

Supercritical hydrothermal combustion and enhanced degradation characteristics of phenol

Supercritical hydrothermal combustion is a green combustion technology that produces flames in supercritical water (SCW), which can realize efficient disposal of aqueous wastes. In this study, the typical pollutant phenol is investigated through tubular reactor experiments and mechanism analysis to explore its hydrothermal combustion properties and enhanced degradation effects on refractory species. The results show that 3.06 and 3.41 wt% phenol can be self-ignited in the tubular reactor with a critical preheating temperature of 460 °C. Methanol could improve the ignition and burnout characteristics of phenol. As the COD ratio of methanol was greater than 0.35, the ignition temperature of phenol was reduced to 420 °C, with TOC removal rate achieving 99.9%. At 460 °C, phenol positively influenced the heat release during combustion of phenol/methanol. In oxidation of phenol/ammonia, 1.61 wt% phenol resulted in the reaction temperature rising by around 62.0 °C, allowing a NH4-N removal rate of 92.8% through its synergistic kinetic and thermal effects. Whereas, the nitrogen-containing intermediates from ammonia inhibited phenol oxidation. Finally, a mechanism-based kinetics model for oxidation of phenol in SCW was developed by means of real gas properties and sensitive reaction step modifications, which was viable for simulating the ring-opening path of phenol.

Adaptation of the Low Dissipation Low Dispersion Scheme for Reactive Multicomponent Flows on Unstructured Grids Using Density-Based Solvers

Abstract The low dissipation low dispersion (LD2) second-order accurate scheme is effective for scale-resolving simulations in finite volume computational fluid dynamics (CFD) solvers, thanks to its combination of a skew-symmetric split form for convective terms and matrix-valued artificial dissipation fluxes. However, reactive flow simulations face challenges due to steep gradients and varying gas properties. This study replaces the skew-symmetric scheme with the kinetic energy and entropy preserving (KEEP) scheme, utilizing quadratic and cubic split forms for convective terms, enhancing stability. The nonsmooth fluid interfaces in reactive flow simulations necessitate upwind fluxes for reactive scalars to limit total variation (TV), also requiring upwind fluxes for the mixture-dependent internal energy fluxes. Other convective terms use central discretizations from the KEEP scheme, leveraging LD2’s spatial reconstruction to minimize dispersive errors. Numerical assessments show this approach reduces spurious pressure oscillations in single and multicomponent flows. The absolute flux Jacobian for dissipation flux calculation is efficiently computed using an expanded Turkel’s approach for thermally perfect gas mixtures. Partial pressure derivatives are approximated when using the flamelet generated manifolds (FGM) combustion model. The proposed scheme is evaluated through scale-resolving simulations of the Cambridge burner flame SWB1 on an unstructured grid using the density-based solver TRACE, employing both finite rate chemistry (FRC) and FGM combustion models. Comparative analysis with the all-speed SLAU2 scheme shows the superior performance of the proposed scheme in handling turbulent reactive multicomponent flows.

ENSURING ECOLOGICAL AND FIRE SAFETY DURING THE OPERATION OF MOTOR VEHICLES WITH PISTON PNEUMATIC AND CRYO ENGINES WHICH USING THE NITROGEN AS WORKING BODY

In the study, the purpose of which is to improve the mathematical apparatus based on the modified thermodynamic theory of disturbances for describing the thermophysical characteristics of nitrogen in the gaseous and liquid states as the working fluid of fire-safe and environmentally safe motor vehicles with piston pneumatic or cryoengines, a mathematical model was suggested to describe for describing the thermodynamic properties of gaseous and liquid of nitrogen, which is intended for the development of a new type of fire-safe and environmentally efficient vehicle with a piston pneumo- or cryoengine and its application is illustrated. The object of the study is the thermophysical characteristics of nitrogen in a liquid or gaseous aggregate state, as a working fluid of fire-safe and eco-safe motor vehicles with a piston pneumatic or cryoengine. The subject of the research is a mathematical apparatus based on the modified perturbation theory for describing the thermophysical characteristics of nitrogen in gaseous and liquid states. The scientific novelty of the research results is that a mathematical apparatus based on a modified thermodynamic theory of disturbances has been improved for a comprehensive description of all thermophysical characteristics of nitrogen, which is in both liquid and gaseous aggregate state, in terms of reducing calculation time and reducing the error of obtaining thermophysical characteristics compared to reference and experimental data. The practical significance of the research results is that the improved mathematical apparatus is marketable for providing accurate information to the composition of the initial data set in studies on the use of nitrogen in various aggregate states as the working fluid of fire-safe and eco-safe motor vehicles with a piston pneumatic or cryoengine.

Mathematical formulation of the physical properties of Hydrocarbon Gases and the determination of these parameters in a Gas-Condensate field in Albania

Abstract The physic-chemical properties of fluids that saturate a bed have been followed throughout the course of resource exploitation through different analyses. Fluids released from the formation over time of exploitation change due to the change in the phase state of the fluids, their material balance and energy. Determining the type of reservoir fluid and its properties, including physical properties and chemical properties, play a key role in reservoir engineering for many decisions made in the development of an oil and gas field. In this manuscript, the properties of gases are analyzed step by step in both their physical and mathematical contexts, as well as that of gas. In this context, a gas-condensate field located in Albania was taken into consideration, determining its properties through the relevant correlations and the use of different graphs both for the measured value of the initial pressure of the formation and for the different values of the pressure taken into consideration.

Physical properties of strong 1 < z < 3 Balmer and Paschen line emitters observed with JWST

Context. The ultraviolet continuum traces young stars while the near-infrared unveils older stellar populations and dust-obscured regions. Balmer emission lines provide insights into gas properties and young stellar objects but are highly affected by dust attenuation. The near-infrared Paschen lines suffer less dust attenuation and can be used to measure star formation rates (SFRs) in star-forming regions obscured by dust clouds. Aims. We present a new way of combining spectro-photometric data in order to test the robustness of the SFRs and stellar mass estimates of star-forming sources observed with JWST. We also aim to quantify the amount of differential attenuation between the interstellar medium and the birth clouds with the use of Paschen emission lines. Methods. We select 13 sources between redshifts 1 and 3 observed with HST, JWST/NIRCam and NIRSpec based on the availability of at least one Balmer and one Paschen line with S/N ≥ 5. With a newly developed version of CIGALE, we fit their hydrogen line equivalent widths (EWs) and photometric data. We assess the impacts of the removal of spectroscopic data by comparing the quality of the fits of the spectro-photometric data to those with photometric data only. We compare the single (BC03) vs binary (BPASS) stellar population models in the fitting process of spectro-photometric data. We derive the differential attenuation and explore different attenuation recipes by fitting spectro-photometric data with BC03. For each stellar model and for each input dataset (with and without EWs), we quantify the deviation on the SFRs and stellar masses from the “standard” choice. Results. The combination of spectro-photometric data provides robust constraints on the physical properties of galaxies, with a significant reduction in the uncertainties compared to using only photometric data. On average, the SFRs are overestimated and the stellar masses are underestimated when EWs are not included as input data. We find a major contribution of the Hα emission line to the broadband photometric measurements of our sources, and a trend of increasing contribution with specific SFR. Using the BPASS models has a significant impact on the derived SFRs and stellar masses, with SFRs being higher by an average of 0.13 dex and stellar masses being lower by an average of 0.18 dex compared to BC03. We show that a flexible attenuation recipe provides more accurate estimates of the dust attenuation parameters, especially the differential attenuation. Finally, we reconstruct the total effective attenuation curves of the most dust-obscured galaxies in our sample.

The properties and kinematics of HCN emission across the closest starburst galaxy NGC 253 observed with ALMA

Context. Investigating molecular gas tracers, such as hydrogen cyanide (HCN), to probe higher densities than CO emission across nearby galaxies remains challenging. This is due to the large observing times required to detect HCN at a high sensitivity and spatial resolution. Although approximate kiloparsec scales of HCN maps are available for tens of galaxies, higher-resolution maps still need to be available. Aims. We aim to study the properties of molecular gas, the contrast in intensity between two tracers that probe different density regimes (the HCN(1–0)/CO(2–1) ratio), and their kinematics across NGC 253, one of the closest starburst galaxies. With its advanced capabilities, the Atacama Large Millimeter/submillimeter Array (ALMA) can map these features at a high resolution across a large field of view and uncover the nature of such dense gas in extragalactic systems. Methods. We present new ALMA Atacama Compact Array and Total Power (ACA+TP) observations of the HCN emission across NGC 253. The observations cover the inner 8.6′ of the galaxy disk at a spatial resolution of 300 pc. Our study examines the distribution and kinematics of the HCN-traced gas and its relationship with the bulk molecular gas traced by CO(2–1). We analyze the integrated intensity and mean velocity of HCN and CO along each line of sight. We also used the SCOUSE software to perform spectral decomposition, which considers each velocity component separately. Results. We find that the denser molecular gas traced by HCN piles up in a ring-like structure at a radius of 2 kpc. The HCN emission is enhanced by two orders of magnitude in the central 2 kpc regions, beyond which its intensity decreases with increasing galactocentric distance. The number of components in the HCN spectra shows a robust environmental dependence, with multiple velocity features across the center and bar. The HCN spectra exhibit multiple velocity features across the center and bar, which shows a robust environmental dependence. We have identified an increase in the HCN/CO ratio in these regions, corresponding to a velocity component likely associated with a molecular outflow. We have also discovered that the ratio between the total infrared luminosity and dense gas mass, which is an indicator of the star formation efficiency of dense gas, is anticorrelated with the molecular gas surface density up to approximately 200 M⊙ pc−2. However, beyond this point, the ratio starts to increase. Conclusions. We argue that using information about spectroscopic features of molecular emission is an important aspect of understanding molecular properties in galaxies.