Gas Cluster Research Articles

The cooler past of the intracluster medium in TNG-Cluster

Abstract The intracluster medium (ICM) today is comprised largely of hot gas with clouds of cooler gas of unknown origin and lifespan. We analyze the evolution of cool gas (temperatures ≲ 104.5 K) in the ICM of 352 galaxy clusters from the TNG-Cluster simulations, with present-day mass ∼1014.3 − 15.4 M⊙. We follow the main progenitors of these clusters over the past ∼13 billion years (since z ≲ 7) and find that, according to TNG-Cluster, the cool ICM mass increases with redshift at fixed cluster mass, implying that this cooler past of the ICM is due to more than just halo growth. The cool cluster gas at z ≲ 0.5 is mostly located in and around satellite galaxies, while at z ≳ 2 cool gas can also accrete via filaments from the intergalactic medium. Lower-mass and higher-redshift clusters are more susceptible to cooling. The cool ICM mass correlates with the number of gaseous satellites and inversely with the central supermassive black hole (SMBH) mass. The average number of gaseous satellites decreases since z = 2, correlating with the decline in the cool ICM mass over cosmic time, suggesting a link between the two. Concurrently, kinetic SMBH feedback shifts the ICM temperature distribution, decreasing the cool ICM mass inside-out. At z ≈ 0.5, the predicted Mg ii column densities are in the ballpark of recent observations, where satellites and other halos contribute significantly to the total Mg ii column density. Suggestively, a non-negligible amount of the ICM cool gas forms stars in-situ at early times, reaching ∼102 M⊙ yr−1 and an Hα surface brightness of ∼10−17 erg s−1 cm−2 arcsec−2 at z ≈ 2, detectable with Euclid and JWST.

Atomistic insights into salicylic acid treatment on human keratinized skin by XPS combined with argon gas cluster sputtering: a pilot study

Atomistic insights into salicylic acid treatment on human keratinized skin by XPS combined with argon gas cluster sputtering: a pilot study

Analysing a grid-forming storage hub for an offshore platform cluster supplied by wind energy

Abstract This paper performs an analysis of the electrification of an of-the-grid offshore oil and gas cluster of six platforms by means of a wind farm combined with a hydrogen energy hub. The latter, whose model is made publicly available, contains a grid-forming battery system and grid-following electrolysis and fuel cells units. State-of-the-art aerodynamic simulations are used for representing the wind farm power output, which encompasses wake losses and correlated wind fuctuations between turbines arising from farm-scale turbulence. One of the offshore platforms is represented by a detailed publicly available model named LEOGO. The other five platforms are represented as aggregated mixes of constant power and constant impedance loads. The computer simulations presented in the paper provide valuable insights into furthering the design and optimization of the hub concept. These insights include, among others, sizing of batteries depending on maximum ramp rates of fuel cells and electrolysers, identifying and mitigating instabilities induced by interactions among power electronic converters, and evaluating the consequences for the converters when those contribute with voltage support at the hub.

Enhancing Streamflow Prediction in Ungauged Basins Using a Nonlinear Knowledge‐Based Framework and Deep Learning

AbstractIn hydrology, a fundamental task involves enhancing the predictive power of a model in ungagged basins by transferring information on physical attributes and hydroclimate dynamics from gauged basins. Introducing an integrated nonlinear clustering framework, this study aims to develop a comprehensive framework that augments predictive performance in basins where direct measurements are sparse or absent. In this framework, uniform manifold approximation and projection (UMAP) is used as a nonlinear method to extract the essential features embedded in hydro‐climatological attributes and physical properties. Then, the Growing Neural Gas (GNG) clustering model is used to find the basins that potentially share similar hydro‐climatological behaviors. Besides UMAP‐GNG, the integration of Principal Component Analysis (PCA) as a linear method to reduce dimensionality with common clustering methods are also assessed to serve as benchmarks. The results reveal that the combination of clustering algorithms with the PCA method may lead to loss of information while the nonlinear method (UMAP) can extract more informative features. The efficacy of the proposed framework is assessed across the Contiguous United States (CONUS) by training a single Base Model using long short‐term memory (LSTM) for the centroids of all clusters and then, fine‐tuning the model on the centroids of each cluster separately to create a regional model. The results indicate that using the information extracted by the UMAP‐GNG method to guide a Base Model can significantly improve the accuracy in most of the clusters and enhance the median prediction accuracy within different clusters from 0.04 to 0.37 of KGE in ungauged basins.

Non-parametric reconstruction of the fine structure constant with galaxy clusters

Testing possible variations in fundamental constants of nature is a crucial endeavor in observational cosmology. This paper investigates potential cosmological variations in the fine structure constant (α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document}) through a non-parametric approach, using galaxy cluster observations as the primary cosmological probe. We employ two methodologies based on galaxy cluster gas mass fraction measurements derived from X-ray and Sunyaev–Zeldovich observations, along with luminosity distances from type Ia supernovae. We also explore how different values of the Hubble constant (H0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$H_0$$\\end{document}) impact the variation of α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} across cosmic history. When using the Planck satellite’s H0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$H_0$$\\end{document} observations, a constant α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} is ruled out at approximately the 3σ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma $$\\end{document} confidence level for z≲0.5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$z \\lesssim 0.5$$\\end{document}. Conversely, employing local estimates of H0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$H_0$$\\end{document} restores agreement with a constant α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document}.

2M NaCl by XPS using monochromatic Al K α x rays

Cryo-XPS enables the study of many substances that are unsuitable for standard XPS analysis, such as moderately volatile liquids, biological samples, porous materials, and polymeric materials that may outgas significantly under ultrahigh vacuum conditions. In this article, XPS spectra of a 50 μl frozen droplet of 2M sodium chloride solution (NaCl) in Millipore water purified to 18.2 MΩ cm at 25 °C were obtained using an Al Kα (1486.6 eV) source with a quartz (1010) crystal monochromator through first order diffraction and irradiating the sample at 54.7° to the surface normal. The sample was sputter cleaned using a Gas Cluster Ion Source pre-acquisition to remove the minor layer of adventitious carbon contamination on the surface. Spectra of the principal lines include Na 1s, O 1s, and Cl 2p. Spectra of O KLL, Na KLL, Cl 2s, Na 2s, Na 2p, O 2s, and valence band were also acquired.

Two-Dimensional Hydration and Triple-Interlayer Lattice Structures in Sulfate-Intercalated Graphene Oxide Nanosheets

Sulfate anions (SO42−) are pivotal in various scientific and industrial domains, including mineralogy, biology, and materials science. While extensive research has elucidated sulfate hydration in bulk solids, liquids, and gaseous clusters, a significant gap persists in understanding sulfate interactions within two-dimensional materials, particularly graphene oxide (GO) nanosheets. This study investigates the intricate hydration phenomena and novel triple-interlayer lattice configurations that emerge from sulfate intercalation in GO nanosheets. Utilizing a straightforward methodology for obtaining precise X-ray measurements of confined nanospaces, we analyzed the temperature-dependent behavior and structural characteristics of these systems. Our findings reveal how sulfate ions modulate interlayer spacing, the dynamics of GO layers, and phase transitions. This research offers an atomic-scale understanding of hybrid hydration behaviors within confined SO4-H2O nano-environments, advancing our knowledge of sulfate interactions in two-dimensional materials.

Quantifying the impact of AGN feedback on the large-scale matter distribution using two- and three-point statistics

Abstract Feedback from active galactic nuclei (AGN) plays a critical role in shaping the matter distribution on scales comparable to and larger than individual galaxies. Upcoming surveys such as Euclid and LSST aim to precisely quantify the matter distribution on cosmological scales, making a detailed understanding of AGN feedback effects essential. Hydrodynamical simulations provide an informative framework for studying these effects, in particular by allowing us to vary the parameters that determine the strength of these feedback processes and, consequently, to predict their corresponding impact on the large-scale matter distribution. We use the EAGLE simulations to explore how changes in subgrid viscosity and AGN heating temperature affect the matter distribution, quantified via 2- and 3-point correlation functions, as well as higher order cumulants of the matter distribution. We find that varying viscosity has a small impact ($\approx 10~{{\%}}$) on scales larger than 1h−1 Mpc, while changes to the AGN heating temperature lead to substantial differences, with up to 70% variation in gas clustering on small scales (≲ 1h−1 Mpc). By examining the suppression of the power spectrum as a function of time, we identify the redshift range z = 1.5 − 1 as a key epoch where AGN feedback begins to dominate in these simulations. The 3-point function provides complementary insight to the more familiar 2-point statistics, and shows more pronounced variations between models on the scale of individual haloes. On the other hand, we find that effects on even larger scales are largely comparable.

Research on microscopic structure–activity relationship of AP particle–matrix interface in HTPB propellant

Abstract The matrix and particle interface of hydroxyl-terminated polybutadiene (HTPB) propellant is the weakest part of its mechanical properties, making it prone to dewetting damage and destroying the structural integrity of the propellant. This article uses nano-indentation, gas cluster ion beam etching, and X-ray photoelectron spectroscopy experimental analyses to study the physicochemical properties of the interface and subsequently construct a microscopic model for the HTPB matrix and ammonium perchlorate particle interface. The model fully considers the existing forms of curing agent toluene diisocyanate, bonding agent Tris (2-methyl-aziridine) phosphine oxide (MAPO), and the aging products of the propellant in the interface structure. Meanwhile, the physicochemical properties, mechanical properties, and adhesive properties of the interface under different tensile loading conditions were analyzed. The results indicate that the bonding agent MAPO significantly enhances the mechanical and adhesive properties of the interface. The interface is sensitive to changes in temperature and tensile rate, and the aged interface is more fragile.

A Multiwavelength Approach to Constraining the Merger Properties of ACT-CL J0034.4+0225

ACT-CL J0034.4+0225 is a previously unrecognized merging galaxy cluster at z = 0.38588 ± 0.00068. Our primary evidence is provided by a 21 ks Chandra image that shows two surface brightness peaks separated by ∼49″ (259 kpc) surrounded by an extended cluster gas distribution. Each gas peak contains a brightest cluster galaxy, offset from the gas peak. We collect new South African Large Telescope optical spectra that, when augmented by archival data, yield redshifts for the two BGCs and 58 other cluster members. Archival Giant Metrewave Radio Telescope and MeerKAT data reveal a radio halo that encompasses the X-ray peaks. We provide and compare three X-ray-based mass estimates (5.0 × 1014 M ⊙, 6.4 × 1014 M ⊙, and 8.6 × 1014 M ⊙). The Planck and ACT Sunyaev–Zel’dovich masses are ≈5.8 × 1014 M ⊙. We constrain the merger state and properties by comparing them to an existing suite of N-body/hydrodynamical models using the measured gas peak separation (259 kpc, projected) and radial velocity difference (0–1000 km s−1). This constrains the epoch of the merger to be within ∼100 Myr of first pericenter passage. A strong lensing analysis constrains the mass ratio to be in the range 1:1–1:20, while the cluster morphology prefers values near the equal-mass range.

Intelligent Fire Suppression Devices Based on Microcapsules Linked to Sensor Internet of Things

Most fire spread is caused by the absence of suppression means at the beginning of the fire. This results in the missed golden time. There are various factors that cause initial fires, such as electrical outlets, general distribution circuits, and oil–vapor–gas cluster spaces. In most cases, these places are out of reach of human hands or they lose the initial suppression time when a fire occurs, causing the spread of fire. This study implements an intelligent fire suppression device that connects sensor IoT based on microcapsules to secure initial fire suppression and golden time in the event of a fire in blind spots that cannot be seen by humans or at a time when it is difficult to recognize a fire. The microcapsule is a micro-collection unit that collects Novec 1230 gas generated in the semiconductor production process. The microcapsule is molded into a form with a fire suppression function and, when a fire occurs, the molded body explodes and absorbs ambient oxygen to suppress the fire. The complex-sensor IoT executes smoke and heat detection generated when a fire is suppressed within 10 s, which ensures the reliability of the detector by notifying of the fire and detecting the ignition point through communication linkages such as Ieee 485 and WiFi or LoRa.

A Neural Network Method for Characterizing Particle Clusters in Gas–Solid Fluidized Beds

A Neural Network Method for Characterizing Particle Clusters in Gas–Solid Fluidized Beds

Reactive Gas Cluster Ion Beams for Enhanced Drug Analysis by Secondary Ion Mass Spectrometry.

In this study, we investigate the formation and composition of Gas Cluster Ion Beams (GCIBs) and their application in Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) analysis. We focus on altering the carrier gas composition, leading to the formation of (Ar/CO2)n or (H2O)n GCIBs. Our results demonstrate that the addition of a reactive species (CO2) to water GCIBs significantly enhances the secondary ion yield of small pharmaceutical compounds in the positive ion mode. In negative ion mode, the addition of CO2 resulted in either a positive enhancement or no effect, depending on the sample. However, an excess of CO2 in the carrier gas leads to the formation of carbon dioxide clusters, resulting in reduced yields compared to that of water cluster beams. Cluster size also plays a crucial role in overall yields. In a simple two-drug system, CO2-doped water clusters prove effective in mitigating matrix effects in positive ion mode compared to pure water cluster, while in negative ion mode, this effect is limited. These clusters are also applied to the analysis of drugs in a biological matrix, leading to more quantitative measurements as shown by a better fitting calibration curve. Overall, the doping of water clusters with small amounts of a reactive gas demonstrates promising benefits for higher sensitivity, higher resolution molecular analysis, and imaging using ToF-SIMS. The effectiveness of these reactive cluster beams varies depending on the experimental parameters and sample type.

Characterization of silicon-based chromium (VI) replacement coatings by using time-of-flight secondary ion mass spectrometry and salt spray tests

This paper proposes an innovative approach in characterization of silicon-based chromium (VI) replacement coatings on an Al substrate by using, salt spray tests and time-of-flight secondary ion mass spectrometry (ToF-SIMS) performed in profile mode by a gas cluster ion beam source (GCIB). While salt spray tests highlight the difference in anticorrosion behaviour, ToF-SIMS provides molecular information on the entire coating and even down to the interface with the Al substrate. ToF-SIMS revealed Si2O2+ and SiOAl + fragments which both contribute to understanding the differences in the anticorrosion performance which are found in the salt spray tests. Si2O2+ moieties relate to the cross-linking density of the coating and subsequently determines the barrier properties. SiOAl+ originates from the interface and characterizes the actual “conversion” of Al at the interface by the deposited layer. The differences in the profile of Si2O2+ and SiOAl + explained the respective anticorrosion performance. From the tested coatings PCT161 showed the highest intensity for both Si2O2+ and SiOAl + while simultaneously performing the best results in the salt spray test. These observations highlight that Si2O2+ and SiOAl + fragments are good indicators of anticorrosion performance and are confirmed by salt spray tests. Moreover, PCT161 and PCT146 are true conversion coatings capable of replacing chromium-based systems.

Unveiling the Hubble constant through galaxy cluster gas mass fractions

In this work, we obtain Hubble constant (H0) estimates by using two galaxy cluster gas mass fraction measurement samples, Type Ia supernovae luminosity distances, and the validity of the cosmic distance duality relation. Notably, the angular diameter distance (ADD) to each galaxy cluster in the samples is determined by combining its gas mass fraction measurement with galaxy clustering observations, more precisely, the Ωb/Ωm ratio. Such a combination results in a H0 estimate that is independent of a specific cosmological framework. In one of the samples, the gas fraction measurements were calculated in spherical shells at radii near r2500 (44 data points), while in the other (103 data points) the measurements were calculated within r500. We find H0=72.7−5.6+6.3 km/s/Mpc at 68% CL for the joint analysis of these data sets. We also investigate the impact on the H0 determination by exploring the precision and number of gas mass fraction data by performing a data Monte Carlo simulation. Our simulations show that future measurements could achieve a precision of up to 5% for H0.

PCA, PC-CVA, and Random Forest of GCIB-SIMS Data for the Elucidation of Bacterial Envelope Differences in Antibiotic Resistance Research.

Antibiotic resistance can rapidly spread through bacterial populations via bacterial conjugation. The bacterial membrane has an important role in facilitating conjugation, thus investigating the effects on the bacterial membrane caused by conjugative plasmids, antibiotic resistance, and genes involved in conjugation is of interest. Analysis of bacterial membranes was conducted using gas cluster ion beam-secondary ion mass spectrometry (GCIB-SIMS). The complexity of the data means that data analysis is important for the identification of changes in the membrane composition. Preprocessing of data and several analytical methods for identification of changes in bacterial membranes have been investigated. GCIB-SIMS data from Escherichia coli samples were subjected to principal components analysis (PCA), principal components-canonical variate analysis (PC-CVA), and Random Forests (RF) data analysis with the aim of extracting the maximum biological information. The influence of increasing replicate data was assessed, and the effect of diminishing biological variation was studied. Optimized m/z region-specific scaling provided improved clustering, with an increase in biologically significant peaks contributing to the loadings. PC-CVA improved clustering, provided clearer loadings, and benefited from larger data sets collected over several months. RF required larger sample numbers and while showing overlap with the PC-CVA, produced additional peaks of interest. The combination of PC-CVA and RF allowed very subtle differences between bacterial strains and growth conditions to be elucidated for the first time. Specifically, comparative analysis of an E. coli strain with and without the F-plasmid revealed changes in cyclopropanation of fatty acids, where the addition of the F-plasmid led to a reduction in cyclopropanation.

Towards a better understanding of the surface smoothing effect in gas cluster ion beam processing with molecular dynamics simulation and experiment

In recent years, the application of gas cluster ion beam (GCIB) technology has made great progress. Due to the similar essence of a monoatomic ion beam, the GCIB also shows flashes of brilliance in material processing. It has been reported that smoothness can be greatly improved after the rough surface is bombarded by the GCIB. This indicates that the GCIB processing has great potential in optical fabrication. Although the surface smoothing effect has been investigated, there is still a lack of dynamic micro-analysis for GCIB processing, which is limited for better understanding the mechanism of smoothing effect. In this paper, the surface smoothing effect in GCIB processing is explicitly investigated with molecular dynamics (MD) simulation and experiment. The principle of GCIB processing is compared with the traditional monoatomic ion-beam based processing, and details of the MD simulation procedure are introduced. Based on this, the dynamic micro-analysis of GCIB processing is conducted under different processing conditions. The simulations reveal the phenomena of atomic removal and migration in GCIB processing, which plays an important role in explaining the mechanism of surface smoothing effect. The experiment was performed on the silicon substrate with the in-house GCIB processing machine. The results indicate that the initial rough surface with dense protrusions can be greatly smoothed, and the root mean square (RMS) value is reduced from 0.586 nm to 0.191 nm. Both simulation and experiment can provide a better understanding of smoothing effect mechanism in GCIB processing.

Re-investigation on effect of equivalent diameter of the conical nozzle on cluster size

Based on the Hagena scaling law, the cluster size in a gas jet is dependent on the equivalent diameter of a conical nozzle. In this work, the effect of the equivalent diameter deq of a conical nozzle on cluster size is separated into the individual effects of the throat diameter d and the half-opening angle α by comparing the Rayleigh scattering signals from gas jets. Nine types of conical nozzles with three different throat diameters (0.3, 0.5, and 0.7 mm) and three different half-opening angles (8.5°, 14.0°, and 24.2°) are used to produce argon gas jets at gas backing pressures from 10 up to 80 bar. The experimental results show that the effect of the throat diameter d is almost the same as that expected by the scaling law. However, the scaling law overestimates the effect of the half-opening angle α. The result is helpful for the precise characterization of cluster size and further understanding the interaction between intense laser and gas clusters.

The SRG/eROSITA All-Sky Survey

Galaxy cluster gas temperatures (T) play a crucial role in many cosmological and astrophysical studies. However, it has been shown that T measurements can significantly vary between different X-ray telescopes. These T biases can propagate to several cluster applications in which T can be used, such as measuring hydrostatic cluster masses and constraining the angular variation of cosmological parameters. Thus, it is important to accurately cross-calibrate X-ray instruments to account for systematic biases. In this work, we present the cross-calibration between Spectrum Roentgen Gamma/eROSITA (SRG/eROSITA) and Chandra/ACIS and between SRG/eROSITA and XMM-Newton/EPIC using for the first time a large sample of galaxy cluster T. To do so, we used the first eROSITA All-Sky Survey data and the preliminary extremely expanded HIgh FLUx Galaxy Cluster Sample, a large X-ray flux-limited cluster catalog. We spectroscopically measured X-ray T for 186 independent cluster regions with both SRG/eROSITA and Chandra/ACIS in a self-consistent way for three energy bands: 0.7–7 keV (full), 0.5–4 keV (soft), and 1.5–7 keV (hard). We did the same with SRG/eROSITA and XMM-Newton/EPIC for 71 different cluster regions and all three bands. We find that SRG/eROSITA measures systematically lower T than the other two instruments, with hotter clusters deviating more than cooler ones. For the full band, SRG/eROSITA returns 20% and 14% lower T than Chandra/ACIS and XMM-Newton/EPIC, respectively, when the two other instruments each measure kBT ≈ 3 keV. The discrepancy respectively increases to 38% and 32% when Chandra/ACIS and XMM-Newton/EPIC each measure kBT ≈ 10 keV. On the other hand, the discrepancy becomes milder for low-T galaxy groups. Moreover, a broken power law fit demonstrated that there is a break at the SRG/eROSITA-Chandra/ACIS scaling relation at kBT ≈ 1.7 − 2.7 keV, depending on the energy band. The soft band shows a marginally lower discrepancy compared to the full band. In the hard band, the cross-calibration of SRG/eROSITA and the other instruments show very strong differences. We tested several possible systematic biases (such as multiphase cluster gas, Galactic absorption, non-Gaussian scatter, and selection effects) to identify the reason behind the cross-calibration discrepancies, but none could significantly alleviate the tension. For now, it is most likely that the systematically lower SRG/eROSITA T can be attributed to systematic effective area calibration uncertainties; however, the exact role of multiphase cluster gas in the observed T discrepancies needs to be further investigated. Furthermore, we provide conversion factors between SRG/eROSITA, Chandra/ACIS, and XMM-Newton/EPIC T that will be beneficial for future cluster studies that combine SRG/eROSITA T with data from other X-ray instruments. Finally, we also provide conversion functions between the official eRASS1 cluster catalog T and the equivalent core and core-excised Chandra/ACIS and XMM-Newton/EPIC T.

The PARSEC view of star formation in galaxy centres: from protoclusters to star clusters in an early-type spiral

ABSTRACT Understanding star formation in galaxies requires resolving the physical scale on which star formation often occurs: the scale of star clusters. We present a multiwavelength, eight-parsec resolution study of star formation in the circumnuclear star cluster and molecular gas rings of the early-type spiral NGC 1386. The cluster ring formed simultaneously ∼4 Myr ago. The clusters have similar properties in terms of mass and star formation rate, resembling those of H ii regions in the Milky Way disc. The molecular CO gas resolves into long filaments, which define a secondary ring detached from the cluster ring. Most clusters are in CO voids. Their separation with respect to the CO filaments is reminiscent of that seen in galaxy spiral arms. By analogy, we propose that a density wave through the disc of this galaxy may have produced this gap in the central kpc. The CO filaments fragment into strings of dense, unresolved clouds with no evidence of a stellar counterpart. These clouds may be the sites of a future population of clusters in the ring. The free-fall time of these clouds, ∼10 Myr, is close to the orbital time of the CO ring. This coincidence could lead to a synchronous bursting ring, as is the case for the current ring. The inward spiralling morphology of the CO filaments and co-spatiality with equivalent kpc-scale dust filaments are suggestive of their role as matter carriers from the galaxy outskirts to feed the molecular ring and a moderately active nucleus.