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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Housedon-Hill - A ChemCam/RMI mega mosaic to investigate distant features

The ChemCam Remote Microscopic Imager (RMI) onboard Curiosity was originally designed to document the tiny areas analyzed by ChemCam’s laser-induced breakdown spectroscopy (LIBS) technique on rocks at few meters distance around the rover. The RMI produces 1024 x 1024 pixel black and white images directly from ChemCam’s telescope focal plane. Early in the mission, it was recognized that, thanks to its powerful optics, RMI could also play a role as a long-distance reconnaissance tool, complementing other cameras on the remote sensing mast, and taking advantage of its very long 700 mm focal length. Imaging areas several kilometers from the rover provides pictures that are very complementary to orbital observations and gives a more human-like, ground-based perspective. Between sols 2878 and 2921, Curiosity stayed parked at the same place to perform various rock sampling analyses. This opportunity was used to target very distant areas of interest, daily building an RMI mosaic of 216 overlapping images covering an area ranging from the bottom layers of Mount Sharp to the edge of Vera Rubin Ridge. This product is so far the largest RMI mosaic acquired during the entire mission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Quantum criticality and topology in non-equilibrium systems

A key goal of condensed matter physics research is to identify new phases of matter, and to understand the universal features of the phase transitions between them. In the past decade, physicists have uncovered a wealth of new phases with interesting surface properties, exemplified by the theoretical prediction and subsequent experimental discovery of topological insulators and superconductors. Traditional condensed matter systems are usually in a thermal equilibrium state and typically at very low temperature. Very recently, experimental advances have sparked interest in the non-equilibrium setting. Non-equilibrium systems can host new phases and phenomena with no equilibrium counterpart, and could also enable robust ways to build quantum memory devices to store and manipulate quantum information in a coherent manner. These phases and phenomena are inherently “dynamical”: they are described not by changes in the arrangement or structure of the constituent particles, but instead marked by sharp distinctions in how the particles move and exchange energy or quantum information. The discovery of robust non-equilibrium phases raises many fundamental questions: Can we develop a systematic theory of states of matter and of dynamical transitions between such states? How can such states be realized and probed experimentally? The main goal of this project was to explore the emergence of topological phases and quantum criticality (two cornerstones of modern condensed matter physics in equilibrium) in such non-equilibrium quantum systems. Specific goals included (1) using tensor networks to efficiently represent non-equilibrium states of matter and their phase transitions; (2) studying and designing new probes for periodically driven systems; and (3) developing analytic and numerical tools to analyze non-equilibrium topological phase transitions. Advances in these directions were achieved using novel techniques appropriate to study the non-equilibrium dynamics in many-body quantum systems combining strong interactions and randomness. Taken together, these results provide a new conceptual framework for understanding the emergence of quantum critical and topological properties in quantum systems far from thermal equilibrium.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Dynamic fingerprint of fractionalized excitations in single-crystalline Cu3Zn(OH)6FBr

Abstract Beyond the absence of long-range magnetic orders, the most prominent feature of the elusive quantum spin liquid (QSL) state is the existence of fractionalized spin excitations, i.e., spinons. When the system orders, the spin-wave excitation appears as the bound state of the spinon-antispinon pair. Although scarcely reported, a direct comparison between similar compounds illustrates the evolution from spinon to magnon. Here, we perform the Raman scattering on single crystals of two quantum kagome antiferromagnets, of which one is the kagome QSL candidate Cu 3 Zn(OH) 6 FBr, and another is an antiferromagnetically ordered compound EuCu 3 (OH) 6 Cl 3 . In Cu 3 Zn(OH) 6 FBr, we identify a unique one spinon-antispinon pair component in the E 2g magnetic Raman continuum, providing strong evidence for deconfined spinon excitations. In contrast, a sharp magnon peak emerges from the one-pair spinon continuum in the E g magnetic Raman response once EuCu 3 (OH) 6 Cl 3 undergoes the antiferromagnetic order transition. From the comparative Raman studies, we can regard the magnon mode as the spinon-antispinon bound state, and the spinon confinement drives the magnetic ordering.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Asymptotic vacuum solution at tokamak X-point tip

In the H-mode regime of diverted tokamaks, the presence of strong pressure gradients in the pedestal gives rise to a sizable bootstrap current, together with the Ohmic and Pfirsch–Schlueter currents, close to the separatrix. For such equilibria, the presence of finite current density close to the separatrix requires the reexamination of equilibrium properties. It is almost universally assumed that the two branches of the separatrix (the stable and unstable manifolds) are straight as they cross at the X-point. However, the opposite angles of the plasma-filled segment and vacuum one cannot be equal if the current density does not vanish at the separatrix on the plasma side. We solve this difficulty by chipping off a thin layer of plasma edge so that the sharp corner of the plasma-filled segment becomes a hyperbola. Using the conformal transformation, we found that in the assumption of a hyperbolic boundary, the X point moves beyond the plasma boundary to fall in the vacuum region. An acute angle of the plasma-filled segment leads to an obtuse opposite angle of vacuum segment and vice versa. In the case of an acute angle of the plasma-filled segment, the new X point shifts inside the X point formed by the asymptotes of a hyperbolic boundary; in the case of an obtuse angle of the plasma-filled segment, the new X point shifts outside the X point formed by the asymptotes of a hyperbolic plasma boundary. Furthermore, the results are important for understanding the X point features, which affect the tokamak edge stability and transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Don't cross the streams: caustics from fuzzy dark matter

Here we study how tidal streams from globular clusters may be used to constrain the mass of ultra-light dark matter particles, called `fuzzy' dark matter (FDM). A general feature of FDM models is the presence of ubiquitous density fluctuations in bound, virialized dark matter structures, on the scale of the de Broglie wavelength, arising from wave interference in the evolving dark matter distribution. These time-varying fluctuations can disturb the motions of stars, leading to potentially observable signatures in cold thin tidal streams in our own Galaxy. The study of this effect has been hindered by the difficulty in simulating the FDM wavefunction in Milky Way-sized systems. We present a simple method to evolve realistic wavefunctions in nearly static potentials, that should provide an accurate estimate of this granulation effect. We quantify the impact of FDM perturbations on tidal streams, and show that initially, while stream perturbations are small in amplitude, their power spectra exhibit a sharp cutoff corresponding to the de Broglie wavelength of the FDM potential fluctuations. Eventually, when stream perturbations become nonlinear, fold caustics generically arise that lead to density fluctuations with universal behavior. This erases the signature of the de Broglie wavelength in the stream density power spectrum, but we show that it will still be possible to determine the FDM mass in this regime, by considering the fluctuations in quantities like angular momenta or actions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

A Simplified Approach Based on Cellular Automata for Describing Direct Reduced Iron Production in Different Reducing Conditions

A quick computation approach based on cellular automata is developed and implemented to describe the reduction of iron ore pellets by a mixture of reducing agents featured by different H 2 /CO ratios. The evolution of oxygen concentration inside the pellet is followed from the beginning to the end of contact between reducing agent and pellet. The variation of thermal state of pellets and gas mixture is computed based on their initial temperature, considering the heat involved and the convective heat exchange between pellet and gas mixture. The use of cellular automata and finite‐difference method to solve the diffusion equation point out the absence of any diffusion coefficient value, allowing to make the model fit the experimental trial, because the problem is that it is not ruled just by diffusion but also by the concentration variation of reducing agent inside the pellet due to porosity increasing during reduction. The updating of the reducing agents concentration implies a sharp decrease of oxygen concentration that the cellular automata model considers. The developed model is able to provide the in‐line control of reduction process and could be used to adjust the chemical concentration and temperature of injected reducing agents.

Metallurgy & Metallurgical Engineering↗
DOE OSTI2021

Expansion of Machine-Learning Method for Classifying Neutron Resonances

The understanding of astrophysics processes and the performance of nuclear reactors and other nuclear systems depend on a precise description of the neutron interaction cross sections for materials and nuclei present in these environments. At low neutron energies, these cross sections exhibit resonance structure represented by sharp enhancements when the neutron energy is sufficiently close to excited levels in a compound nucleus. Such resonances can be characterized by their quantum numbers relative to angular momenta, which are often deduced in an ad hoc and irreproducible manner from the shape of the cross sections. The correct assignment of the quantum numbers of neutron resonances is therefore of paramount importance. To address this we have developed a machine-learning method to automate the identification and correction of these spin assignments. The algorithm is trained from simulated data, generated from statistical properties of resonance data for a given nucleus, to mimic the errors found in real data. In this project we describe five independent approaches to further develop and expand the applicability of the machine-learning spin classifier: i) Feature impact; ii) Integration with the Atlas; iii) Training optimization; iv) Spacings systematics; and v) Validation with polarized data. The premises, methods, results, and future perspectives are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Observed and Bin Model Simulated Evolution of Drop Size Distributions in High-Based Cumulus Congestus Over the United Arab Emirates

This study examines microphysical processes in developing high-based cumulus congestus over the United Arab Emirates using aircraft observations and a large-eddy-simulation model with bin microphysics. A notable feature of this case is the lack of mm-sized drops despite having a liquid cloud layer >3.5 km deep, contrasting with copious large drops observed in maritime tropical cumulus congestus having a similar vertical extent. Modeled drop size distributions are similar to observations at various temperatures between 9.5 and –12°C, including the lack of mm-sized drops. Cloud dilution leads to low-to-moderate liquid water contents (~0.5–1.5 g m –3 ) in most of the cloud core, several times smaller than adiabatic values. Dilution is enhanced in the inflowing branch of the toroidal circulations associated with individual cloud thermals, which are favored regions for secondary droplet activation (activation above cloud base). Secondary activation in general contributes substantially to the droplet population. Turning it off leads to a sharp decrease in droplet concentration and increase in mean size aloft, but does little to increase rain drop production. Warm rain generation (or lack thereof) in this case is therefore determined more by the sub-cloud aerosol and the cloud base droplet size distribution (DSD) than DSD evolution aloft from secondary droplet activation. Decreasing the aerosol concentration by a factor of 10 greatly increases production of large drops via collision-coalescence. Thus, despite its high base (low temperatures) and substantial dilution, the simulated cloud is thermodynamically and dynamically capable of rapidly producing copious mm-sized drops from collision-coalescence under pristine aerosol conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Anharmonic phonons, thermal expansion, and nuclear quantum effects in Zn

The anharmonic behavior of phonons and thermal expansion of hexagonal zinc were studied from 15 to 690 K by inelastic neutron scattering (INS) and ab initio simulations. Phonon spectra were measured for Q-points covering the full Brillouin zone, giving the phonon density of states (DOS) and dispersions along high-symmetry directions. The dispersions were sharp at 15 K, but diffuse intensity was observed at energies above them. The dispersions broadened with temperature T and the diffuse intensity became stronger. This diffuse intensity appeared in all INS measurements and simulations, except for classical molecular dynamics at 15 K. The temperature-dependent effective potential (TDEP) method, which included the nuclear quantum effect from zero-point vibrational dynamics, was used to calculate the free energy and thermal expansion. For T < 100 K nuclear quantum effects were important for obtaining the correct negative thermal expansion, and path integral molecular dynamics (PIMD) was particularly effective for obtaining the negative thermal expansion in the basal plane. A Heisenberg-Langevin model for interacting phonons coupled to a thermal bath was able to reproduce the shape and intensity of the diffuse spectral features.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Kinetics of charged particles in a high-voltage gas discharge in a nonuniform electrostatic field

A high-voltage gas discharge is of interest as a possible means of generating directed flows of low-temperature plasma in the off-electrode space distinguished by its original features [1–4]. We propose a model for calculating the trajectories of charges particles in a high-voltage gas discharge in nitrogen at a pressure of 0.15 Torr existing in a nonuniform electrostatic field and the strength of this field. Based on the results of our calculations, we supplement and refine the extensive experimental data concerning the investigation of such a discharge published in [1, 2, 5–8]; good agreement between the theory and experiment has been achieved. The discharge burning is initiated and maintained through bulk electron-impact ionization and ion–electron emission. We have determined the sizes of the cathode surface regions responsible for these processes, including the sizes of the axial zone involved in the discharge generation. The main effect determining the kinetics of charged particles consists in a sharp decrease in the strength of the field under consideration outside the interelectrode space, which allows a free motion of charges with specific energies and trajectories to be generated in it. The simulation results confirm that complex electrode systems that allow directed plasma flows to be generated at a discharge current of hundreds or thousands of milliamperes and a voltage on the electrodes of 0.3–1 kV can be implemented in practice [3, 9, 10].

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

ProbabilisticRecalibration of Forecasts

In this work, we present a scheme by which a probabilistic forecasting system whose predictions have a poor probabilistic calibration may be recalibrated through the incorporation of past performance information in order to produce a new forecasting system that is demonstrably superior to the original, inasmuch as one may use it to win wagers consistently against someone who is using the original system. The scheme utilizes Gaussian process (GP) modeling to estimate a probability distribution over the probability integral transform (PIT) of a scalar predictand. The GP density estimate gives closed-form access to information entropy measures that are associated with the estimated distribution, which allows the prediction of winnings in wagers against the base forecasting system. A separate consequence of the procedure is that the recalibrated forecast has a uniform expected PIT distribution. One distinguishing feature of the procedure is that it is appropriate even if the PIT values are not i.i.d. The recalibration scheme is formulated in a framework that exploits the deep connections among information theory, forecasting, and betting. We demonstrate the effectiveness of the scheme in two case studies: a laboratory experiment with a nonlinear circuit and seasonal forecasts of the intensity of the El Nino-Southern Oscillation phenomenon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Adsorption and reaction of methanol on Fe 3 O 4 (001)

The interaction of methanol with iron oxide surfaces is of interest due to its potential in hydrogen storage, and from a fundamental perspective as a chemical probe of the reactivity. We present here a study examining the adsorption and reaction of methanol on magnetite Fe 3 O 4 (001) at cryogenic temperatures using a combination of temperature programmed desorption, x-ray photoelectron spectroscopy, and scanning tunneling microscopy. We report the methanol desorption profile from Fe 3 O 4 (001) is complex, exhibiting peaks at 145, 175, 238, and 273 K, corresponding to the desorption of intact methanol, as well as peaks at 350 and 500 K due to the reaction of methoxy intermediates. The saturation of a monolayer of methanol corresponds to ~5 molecules/unit cell (u.c.), which is slightly higher than the number of surface octahedral iron atoms of 4/u.c. We probe the kinetics and thermodynamics of the desorption of molecular methanol using inversion analysis. The deconvolution of the complex desorption profile into individual peaks allows for calculations of both the desorption energy and the prefactor of each feature. The initial 0.7 methanol/u.c. reacts to form a methoxy and hydroxy intermediates by 180 K, which remains on the surface above room temperature after intact methanol has desorbed. The methoxy species react via one of two channels, a recombination reaction with surface hydroxyls to form additional methanol at ~350 K, and a disproportionation reaction to form methanol and formaldehyde at ~500 K. Only 20% of the methoxy species undergo the disproportionation reaction, with most of them reacting via the 350 K pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Signatures of low-dimensional magnetism and short-range spin fluctuations in Co-based trirutiles

Features of low dimensional magnetism resulting from a square-net arrangement of Co atoms in trirutile CoTa2O6 is studied in the present work by means of density functional theory and is compared with the experimental results of specific heat and neutron diffraction. The small total energy differences between the ferromagnetic (FM) and antiferromagnetic (AFM) configuration of CoTa2O6 shows that competing magnetic ground states exist, with the possibility of transition from FM to AFM phase at low temperature. Our calculation further suggests the semi-conducting behavior for CoTa2O6 with a band gap of ~0.41 eV. The calculated magnetic anisotropy energy is ~2.5 meV with its easy axis along the [100] (in-plane) direction. Studying the evolution of magnetism in Co1-xMgxTa2O6 (x = 0, 0.1, 0.3, 0.5, 0.7 and 1). it is found that the sharp AFM transition exhibited by CoTa2O6 at TN = 6.2 K in it’s heat capacity vanishes with Mg-dilution, indicating the obvious effect of weakening the superexchange pathways of Co. The current specific heat study reveals the robust nature of TN for CoTa2O6 in applied magnetic fields. Clear indication of short-range magnetism is obtained from the magnetic entropy, however, diffuse components are absent in neutron diffraction data. At TN , CoTa2O6 enters a long-range ordered magnetic state which can be described using a propagation vector, ( 1 1 0). Upon Mg-dilution at x =0.1, the long-range ordered magnetism is destroyed. The present results should motivate an investigation of magnetic excitations in this low-dimensional anisotropic magnet.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Low-temperature spin dynamics in the TmFeO 3 orthoferrite with a non-Kramers ion

We investigate the magnetic dynamics of the orthorhombic perovskite TmFeO 3 at low temperatures, below the spin reorientation transition at TSR≈80 K, by means of time-of-flight neutron spectroscopy. We find that the magnetic excitation spectrum combines two emergent collective modes associated with different magnetic sublattices. The Fe subsystem orders below TN~632 K into a canted antiferromagnetic structure and exhibits sharp, high-energy magnon excitations. We describe them using linear spin-wave theory, and reveal a pronounced anisotropy between in- and out-of-plane exchange interactions, which was mainly neglected in previous reports on the spin dynamics in orthoferrites. At lower energies, we find two crystalline electrical field (CEF) excitations of Tm3+ ions at energies of ~2 and 5 meV. In contrast to the sister compound YbFeO 3 , where the Yb 3+ ions form quasi-one-dimensional chains along the c axis, the Tm excitations show dispersion along both directions in the (0KL) scattering plane. Analysis of the neutron scattering polarization factor reveals a longitudinal polarization of the 2 meV excitation. To evaluate the effect of the CEF on the Tm 3+ ions, we perform point-charge model calculations, and their results quantitatively capture the main features of Tm single-ion physics, such as energies, intensities, and polarization of the CEF transitions, and the type of magnetic anisotropy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Analysis of ionizing radiation induced DNA damage response in human adult stem cells and differentiated neurons

Findings of neurodegenerative features associated with human radiosensitive syndromes such as Ataxia telangiectasia suggest that DNA repair efficiency is crucial for maintaining the functional integrity of central nervous system. To gain a better understanding of ionizing radiation (IR) induced DNA damage response in undifferentiated and differentiated neural cell types and to evaluate the role of ATM in DNA double strand break (DSB) repair, an in vitro human neural cell differentiation model system was utilized in this study. As compared to adult stem cells, differentiated neurons displayed an attenuated DSB repair response (as judged by the persistence of 53BP1 foci) after IR exposure and the attenuation was even more pronounced in stem cells and neurons after suppression of ATM (Ataxia Telangiectasia Mutated) gene product suggesting the importance of ATM for an optimal DSB repair efficiency in human neural cell types. In corroboration with an attenuated DNA damage response, a sharp decline in the expression levels of several DSB repair genes was observed in neurons. Furthermore, our results suggest that cellular differentiation modulates the expression of several genes thereby compromising the DSB repair fidelity in post mitotic neurons. Further studies are required to verify whether or not ATM mediated exacerbation of DNA repair deficiency in differentiated neurons leads to neurodegeneration.

53 binding protein 1↗
DOE OSTI2020

Organismic materials for beyond von Neumann machines

The elementary basis of intelligence in organisms with a central nervous system includes neurons and synapses and their complex interconnections forming neural circuits. In non-neural organisms such as slime mold with gel-like media, viscosity modulation enables adaptation to changing environments. At a larger scale, collective intelligence emerges via social interactions and feedback in animal colonies. Learning and memory are therefore multi-scale features that evolve as a result of constant interactions with the environment. There is growing interest in emulating such features of intelligence in computing machines and autonomous systems. Materials that can respond to their environment in a manner similar to organisms (referred to as "organismic materials") therefore may be of interest as hardware components in artificial intelligence machines. In this brief review, we present a class of semiconductors called correlated oxides as candidates for learning machines. The term "correlated" refers to the fact that electrons in such lattices strongly interact and the ground state is not what is predicted by classical band theory. Such materials can undergo insulator-metal transitions at near ambient conditions under external stimuli such as thermal or electrical fields, strain, and chemical doping. Depending on the mechanism driving the transition, intermediate states can be metastable with different volatilities, and the time scales of phase change can be controlled over many orders of magnitude. The change in electronic properties can be sharp or gradual, leading to digital or analog behavior. These properties enable the realization of artificial neurons and synapses and emulate the associative and non-associative learning characteristics found in various organisms. We examine microscopic properties concerning electronic and structural transitions leading to collective behavior and theoretical treatments of the ground state and dynamical response, showcasing VO 2 as a model system. Next, we briefly review algorithms designed from the plasticity demonstrated by phase changing systems. Finally, we conclude the brief review with suggestions for future research toward realizing non-von Neumann machines.

42 ENGINEERING↗
DOE OSTI2022

B/PS bulges in DESI Legacy edge-on galaxies – I. Sample building

ABSTRACT We present the biggest up-to-date sample of edge-on galaxies with boxy/peanut-shaped (B/PS) bulges and X-structures. The sample was prepared using images from the Dark Energy Spectroscopic Instrument (DESI) Legacy catalogue and contains about 2000 galaxies. To find suitable candidates in catalogue, we made the assumption that the residues (original images minus model) of galaxies with B/PS bulges should exhibit a characteristic X-shape. Galaxies with such features were selected by eye and then used as input data for a neural network training, which was applied to a bigger sample of edge-on galaxies. Using the available data and the photometric models from the literature, we investigated the observational and statistical properties of the sample created. Comparing the B/D ratios for galaxies with and without B/PS bulges, we found that the B/D ratio for galaxies from our sample is statistically higher, with typical values in the range ≈0.2–0.5 depending on the decomposition procedure. We studied how the opening angles φ of the X-structure and the length of its rays are distributed in the formed sample and found them to be consistent with previous measurements and predictions from N-body models, e.g. $\varphi \gtrsim 25{^\circ }$, but measured here for a much larger number of galaxies. We found a sharp increase in the B/PS bulge fraction for stellar masses log M⋆ ≳ 10.4, but for edge-on galaxies, which complements the results of previous works. The sample can be used in future work to test various bar models and their relationship with B/PS bulges, as well as to study their stability and evolution.

79 ASTRONOMY AND ASTROPHYSICS↗