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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Effect of Sequential Heat Impacts on the Formation of a Stable State of the xLPM–(1 – x)PT Multiferroic Composites

The effect of thermal cycling and sintering temperature on the chemical and thermodynamic stability of the bulk multiferroic xLa{sub 0.7}Pb{sub 0.3}MnO{sub 3}–(1 – x)PbTiO{sub 3} quasi-ceramic and ceramic composites has been experimentally investigated. It is shown that the limiting temperature of the long-term sample firing should not exceed 1070 K. It has been found that sintering at this temperature and/or short-term exposure of the samples at higher temperatures (up to 1220 K) significantly increase the sample compactness, stabilize the thermal expansion, and enhance the quality of the composites. It has been established that the component grain integrity is violated by shrinkage of the samples and a sharp change in their volume during the phase transition of a ferroelectric component.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Monitoring Aqueous Reprocessing Systems for Detection of Facility Misuse

Traditional approaches to material control and accounting at used nuclear fuel reprocessing facilities relies in large part on laboratory-based destructive assay of periodic samples taken from key stages. These techniques are highly accurate, but limited inspection frequency may limit the size and operation of a reprocessing facility. Online monitoring techniques using inline detectors can be applied to fuel reprocessing systems to improve the situational awareness as the facility is operating to provide additional indicators of the evolving state of the facility between normal inspection periods, potentially alerting regulators to the need for additional inspection. The Multi-Isotope Process (MIP) Monitor combines medium-resolution gamma detectors with statistical data analysis techniques to monitor reprocessing systems for anomalous conditions resulting from process control issues or malfeasance. Gamma spectra collected from the H-Canyon reprocessing facility were modeled using principal component analysis to demonstrate the efficacy of the MIP Monitor for detecting notional diversion scenarios.

safeguards, nuclear fuel reprocessing, gamma spect↗
DOE OSTI2018

Synthesis and High-Temperature Heat Capacity of Pb{sub 8}La{sub 2}(GeO{sub 4}){sub 4}(VO{sub 4}){sub 2} and Pb{sub 8}Nd{sub 2}(GeO{sub 4}){sub 4}(VO{sub 4}){sub 2} with the Apatite Structure

The Pb{sub 8}La{sub 2}(GeO{sub 4}){sub 4}(VO{sub 4}){sub 2} and Pb{sub 8}Nd{sub 2}(GeO{sub 4}){sub 4}(VO{sub 4}){sub 2} germanatovanadates with the apatite structure have been prepared by solid-state reactions, by sequentially firing stoichiometric mixtures of PbO, La{sub 2}O{sub 3} (Nd{sub 2}O{sub 3}), GeO{sub 2}, and V{sub 2}O{sub 5} in air at temperatures of 773, 873, 973, and 1073 K. The effect of temperature on the heat capacity of the resultant polycrystalline samples has been studied by differential scanning calorimetry at temperatures from 350 to 950 K using polycrystalline samples. The experimental C{sub p}(T) data have been used to evaluate the thermodynamic functions of the lead lanthanum and lead neodymium germanatovanadates.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Synchrotron resolved microscale mineralogy and elemental composition of individual plinthic and manganiferous nodules from agricultural soils

Iron and manganese oxides are strong sorbents and elemental scavengers in the environment that can form macroscopic nodules in soils. Despite their importance in the geochemical cycling of nutrients and contaminants, nodules are rarely characterized. When analyzed, they are often combined into bulk samples, obscuring individual characteristics. This study investigates the composition and mineralogy of individual plinthic and manganiferous nodules in soil from cropping systems in the Farming Systems Project in Beltsville, Maryland. Elemental composition indicates the accumulation of contaminants and nutrients, including copper in all nodules and high levels of phosphorus in select nodules. Sequential extractions determine that highly crystalline minerals comprise the nodules, locking away these nutrients and contaminants. Bulk X-ray diffraction (XRD) demonstrated distinct mineralogies in the plinthic and manganiferous nodules, with the former comprised of quartz, goethite, and kaolinite, and the latter consisting of quartz, Mn 2 O 3 , and hematite. Synchrotron and laboratory-based X-ray fluorescence (XRF) mapping gives critical insight into the elemental distribution within the nodules and elucidates spatial elemental associations, including the coupling of manganese and iron in the manganiferous nodules. XRF maps paired with µXRD provide microscale spatial resolution in mineralogy, which resolved several phases not apparent in bulk XRD, manganese’s association with goethite, and minerals indicative of redox transformations, including magnetite and maghemite. These novel results provide critical insight into the microscale mineralogy and individual elemental composition of plinthic and manganiferous nodules, as well as how they alter bulk soil geochemistry in ways largely unaccounted for in research on soil systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimal experimental design: Formulations and computations

Questions of ‘how best to acquire data’ are essential to modelling and prediction in the natural and social sciences, engineering applications, and beyond. Optimal experimental design (OED) formalizes these questions and creates computational methods to answer them. This article presents a systematic survey of modern OED, from its foundations in classical design theory to current research involving OED for complex models. We begin by reviewing criteria used to formulate an OED problem and thus to encode the goal of performing an experiment. We emphasize the flexibility of the Bayesian and decision-theoretic approach, which encompasses information-based criteria that are well-suited to nonlinear and non-Gaussian statistical models. We then discuss methods for estimating or bounding the values of these design criteria; this endeavour can be quite challenging due to strong nonlinearities, high parameter dimension, large per-sample costs, or settings where the model is implicit. A complementary set of computational issues involves optimization methods used to find a design; we discuss such methods in the discrete (combinatorial) setting of observation selection and in settings where an exact design can be continuously parametrized. Finally we present emerging methods for sequential OED that build non-myopic design policies, rather than explicit designs; these methods naturally adapt to the outcomes of past experiments in proposing new experiments, while seeking coordination among all experiments to be performed. Throughout, we highlight important open questions and challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Uncovering multiscale structure-property correlations via active learning in scanning tunneling microscopy

Atomic arrangements and local sub-structures fundamentally influence emergent material functionalities. These structures are conventionally probed using spatially resolved studies and the property correlations are deciphered by a researcher based on sequential explorations, thereby limiting the efficiency and scope. Here we demonstrate a multi-scale Bayesian deep-learning based framework that automatically correlates material structure with its electronic properties using scanning tunneling microscopy (STM) measurements in real-time. Its predictions are used to autonomously direct exploration toward regions of the sample that optimize a given material property. This method is deployed on a low-temperature ultra-high vacuum STM to understand the structure-property relationship in a europium-based semimetal, EuZn 2 As 2 , a promising candidate relevant to magnetism-driven topological phenomena. The framework employs a sparse-sampling approach to efficiently construct the scalar-property space using minimal measurements, about 1–10% of the data required in standard hyperspectral methods. Moreover, we formulate the problem hierarchically across length scales, implementing autonomous workflow to locate mesoscopic and atomic structures that correspond to a target material property. This framework offers the choice to design scalar-property from the spectroscopic data to steer sample exploration. Our findings reveal correlations of the electronic properties unique to surface terminations, local defect density, and point defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Why natural monazite never becomes amorphous: Experimental evidence for alpha self-healing

Monazite, a common accessory rare-earth orthophosphate mineral in the continental crust widely used in U-Pb geochronology, holds promise for (U-Th)/He thermochronology and for the immobilization of Pu and minor actinides (MA) coming from spent nuclear fuel reprocessing. Previous results obtained on natural and plutonium-doped monazite have demonstrated the ability of this structure to maintain a crystalline state despite high radiation damage levels. However, the low critical temperature (180 °C), above which amorphization cannot be achieved in natural monazite under ion irradiation, does not explain this old and unsolved paradox: why do natural monazites, independent of their geological history, remain crystalline even when they did not experience any thermal event that could heal the defects? This is what the present study aims to address. Synthetic polycrystals of LaPO 4 -monazite were irradiated sequentially and simultaneously with α particles (He) and gold (Au) ions. Here, our results demonstrate experimentally for the first time in monazite, the existence of the defect recovery mechanism, called α-healing, acting in this structure due to electronic energy loss of α particles, which explains the absence of amorphization in natural monazite samples. This mechanism is critically important for monazite geo- and thermochronology and to design and predictively model the long-term behavior of ceramic matrices for nuclear waste conditioning.

36 MATERIALS SCIENCE↗
NASA NTRS2011

High-Throughput, Adaptive FFT Architecture for FPGA-Based Spaceborne Data Processors

Exponential growth in microelectronics technology such as field-programmable gate arrays (FPGAs) has enabled high-performance spaceborne instruments with increasing onboard data processing capabilities. As a commonly used digital signal processing (DSP) building block, fast Fourier transform (FFT) has been of great interest in onboard data processing applications, which needs to strike a reasonable balance between high-performance (throughput, block size, etc.) and low resource usage (power, silicon footprint, etc.). It is also desirable to be designed so that a single design can be reused and adapted into instruments with different requirements. The Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture was developed, in which the high-throughput benefits of the parallel FFT structure and the low resource usage of Singleton s single butterfly method is exploited. The result is a wide-kernel, multipass, adaptive FFT architecture. The 32K-point MPWK-FFT architecture includes 32 radix-2 butterflies, 64 FIFOs to store the real inputs, 64 FIFOs to store the imaginary inputs, complex twiddle factor storage, and FIFO logic to route the outputs to the correct FIFO. The inputs are stored in sequential fashion into the FIFOs, and the outputs of each butterfly are sequentially written first into the even FIFO, then the odd FIFO. Because of the order of the outputs written into the FIFOs, the depth of the even FIFOs, which are 768 each, are 1.5 times larger than the odd FIFOs, which are 512 each. The total memory needed for data storage, assuming that each sample is 36 bits, is 2.95 Mbits. The twiddle factors are stored in internal ROM inside the FPGA for fast access time. The total memory size to store the twiddle factors is 589.9Kbits. This FFT structure combines the benefits of high throughput from the parallel FFT kernels and low resource usage from the multi-pass FFT kernels with desired adaptability. Space instrument missions that need onboard FFT capabilities such as the proposed DESDynl, SWOT (Surface Water Ocean Topography), and Europa sounding radar missions would greatly benefit from this technology with significant reductions in non-recurring cost and risk.

NguyenKobayashi, Kayla↗
DOE OSTI2025

In Situ Diffraction and Ex Situ Transmission X‐Ray Microscopy Studies of Solid‐State Upcycling for NMC Cathodes

Upcycling of recycled LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) cathodes offers an economical route to produce cathode materials with increased energy density (i.e., LiNi 0.8 Mn 0.1 Co 0.1 O 2 , NMC811) that meet the performance needs of present-day electric vehicles. In this work, solid-state upcycling of NMC622 via calcination with Ni(OH) 2 and LiOH was monitored using in situ synchrotron powder X-ray diffraction measurements. Sequential Rietveld refinements indicate that the calcination proceeds by initially converting Ni(OH) 2 to a rocksalt NiO phase followed by lithiation of NiO to form LiNiO 2 (LNO), with both NMC and LNO phases present in nearly equal proportions at the calcination endpoint. Variable-energy transmission X-ray microscopy tomograms of upcycled samples reveal that the NMC and LNO domains are intermixed at sub-micron length scales. Depth-dependent analysis of multi-elemental fitting maps matches the expected NMC811 composition at the secondary particle level and indicates that transition metal diffusion is not limited by the secondary particle size.

cathode upcycling↗
DOE OSTI2021

Optical properties of differing nanolayered structures of divalent europium doped barium fluoride thin films synthesized by pulsed laser deposition

Optically-active thin films are employed in a variety of applications, such as LEDs and photovoltaics, due to their ability to act as up- or down-photon energy converters. Their performance depends critically on their composition and structure; thus, the use of novel synthesis techniques that allow for their control at the nanoscale level can result in improved efficiency and practicality. Here, layered thin films consisting of Eu 2+ - doped BaF 2 nanocrystalline layers separated by amorphous Al 2 O 3 were synthesized via sequential pulsed laser deposition using three separate targets for the different components; this synthesis technique provides precise control of layer thickness at the nanoscale along with dopant distribution within the film. Cross-sectional transmission electron microscopy analysis verified the desired nano-layering. Post-deposition heat treatments in a nitrogen atmosphere resulted in samples exhibiting steady emission with a broad peak ranging from 400 to 600 nm and a shoulder at 410 nm. The CIE 1931 chromaticity coordinates are x = 0.26-0.29 and y = 0.32-0.35 and vary as a function of the sample configuration. Because the chromaticity coordinates are close to those of a pure white light (x = 0.33, y = 0.33), these films demonstrate advantageous properties for applications with UV-pumped white light LEDs.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Multilevel sequential Monte Carlo: Mean square error bounds under verifiable conditions

We consider the multilevel sequential Monte Carlo (MLSMC) method of Beskos et al. (Stoch. Proc. Appl. [to appear]). This technique is designed to approximate expectations w.r.t. probability laws associated to a discretization. For instance, in the context of inverse problems, where one discretizes the solution of a partial differential equation. The MLSMC approach is especially useful when independent, coupled sampling is not possible. Beskos et al. show that for MLSMC the computational effort to achieve a given error, can be less than independent sampling. In this article we significantly weaken the assumptions of Beskos et al., extending the proofs to non-compact state-spaces. The assumptions are based upon multiplicative drift conditions as in Kontoyiannis and Meyn (Electron. J. Probab. 10 [2005]: 61–123). The assumptions are verified for an example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Improvement of the thermal stability of nickel silicide using a ruthenium interlayer deposited via remote plasma atomic layer deposition

In this study, the effects of a thin Ru interlayer on the thermal and morphological stability of NiSi have been investigated. Ru and Ni thin films were deposited sequentially to form a Ni/Ru/Si bilayered structure, without breaking the vacuum, by remote plasma atomic layer deposition (RPALD) on a p-type Si wafer. After annealing at various temperatures, the thermal stabilities of the Ni/Ru/Si and Ni/Si structures were investigated by various analysis techniques. The results showed that the sheet resistance of the Ni/Ru/Si sample was consistently lower compared to the Ni/Si sample over the entire temperature range. Although both samples exhibited the formation of NiSi{sub 2} phases at an annealing temperature of 800 °C, as seen with glancing angle x-ray diffraction, the peaks of the Ni/Ru/Si sample were observed to have much weaker intensities than those obtained for the Ni/Si sample. Moreover, the NiSi film with a Ru interlayer exhibited a better interface and improved surface morphologies compared to the NiSi film without a Ru interlayer. These results show that the phase transformation of NiSi to NiSi{sub 2} was retarded and that the smooth NiSi/Si interface was retained due to the activation energy increment for NiSi{sub 2} nucleation that is caused by adding a Ru interlayer. Hence, it can be said that the Ru interlayer deposited by RPALD can be used to control the phase transformation and physical properties of nickel silicide phases.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Simultaneous beam sampling and aperture shape optimization for SPORT

Purpose: Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: The authors build a mathematical model with the fundamental station point parameters as the decision variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution. Results: A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and neck and a prostate case. It significantly improved the target conformality and at the same time critical structure sparing compared with conventional intensity modulated radiation therapy (IMRT). In the head and neck case, for example, the average PTV coverage D99% for two PTVs, cord and brainstem max doses, and right parotid gland mean dose were improved, respectively, by about 7%, 37%, 12%, and 16%. Conclusions: The proposed method automatically determines the number of the stations required to generate a satisfactory plan and optimizes simultaneously the involved station parameters, leading to improved quality of the resultant treatment plans as compared with the conventional IMRT plans.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2014

Revised (Mixed-Effects) Estimation for Forest Burning Emissions of Gases and Smoke, Fire/Emission Factor Typology, and Potential Remote Sensing Classification of Types for Ozone and Black-Carbon Simulation

We summarize recent progress (a) in correcting biomass burning emissions factors deduced from airborne sampling of forest fire plumes, (b) in understanding the variability in reactivity of the fresh plumes sampled in ARCTAS (2008), DC3 (2012), and SEAC4RS (2013) airborne missions, and (c) in a consequent search for remotely sensed quantities that help classify forest-fire plumes. Particle properties, chemical speciation, and smoke radiative properties are related and mutually informative, as pictures below suggest (slopes of lines of same color are similar). (a) Mixed-effects (random-effects) statistical modeling provides estimates of both emission factors and a reasonable description of carbon-burned simultaneously. Different fire plumes will have very different contributions to volatile organic carbon reactivity; this may help explain differences of free NOx(both gas- and particle-phase), and also of ozone production, that have been noted for forest-fire plumes in California. Our evaluations check or correct emission factors based on sequential measurements (e.g., the Normalized Ratio Enhancement and similar methods). We stress the dangers of methods relying on emission-ratios to CO. (b) This work confirms and extends many reports of great situational variability in emissions factors. VOCs vary in OH reactivity and NOx-binding. Reasons for variability are not only fuel composition, fuel condition, etc., but are confused somewhat by rapid transformation and mixing of emissions. We use "unmixing" (distinct from mixed-effects) statistics and compare briefly to approaches like neural nets. We focus on one particularly intense fire the notorious Yosemite Rim Fire of 2013. In some samples, NOx activity was not so suppressed by binding into nitrates as in other fires. While our fire-typing is evolving and subject to debate, the carbon-burned delta(CO2+CO) estimates that arise from mixed effects models, free of confusion by background-CO2 variation, should provide a solid base for discussion. (c) We report progress using promising links we find between emissions-related "fire types" and promising features deducible from remote observations of plumes, e.g., single scatter albedo, Angstrom exponent of scattering, Angstrom exponent of absorption, (CO column density)/(aerosol optical depth).

Remote sensing↗
DOE OSTI2017

Revisiting the Anionic Polymerization of Methyl Ethacrylate

Synthesis of poly(methyl ethacrylate), (PMEA), in tetrahydrofuran at -78 °C using anionic polymerization techniques results in high molar mass (>30 kg mol-1), low dispersity (1.3), and high conversion (>81%). The molar masses of a series of samples are consistent with values anticipated by the monomer-to-initiator ratio and conversion. These results represent a significant improvement to earlier reported attempts to prepare PMEA using anionic methods. Successful diblock polymerization of polystyrene-block-PMEA, (PS-PMEA), and poly(4-tert-butylstyrene)-block-PMEA, (PtBS-PMEA), is achieved through sequential anionic polymerization techniques with dispersities as low as 1.06 and segment molar fractions close to those targeted. Broad principal scattering peaks observed by small-angle X-ray scattering (SAXS) for symmetric PS-PMEA at relatively high molar mass (39 kg mol-1) suggests an effective interaction parameter (χeff) that is smaller than for PS-block-poly(methyl methacrylate). On the other hand, PtBS-PMEA block polymers form a well-ordered morphology based on SAXS measurements and is attributable to the more hydrophobic PtBS segment. These results confirm the viability of PMEA as a new constituent in the expanding suite of polymers suitable for preparing nanostructured block polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Phosphorus chemistry in plant charcoal: interplay between biomass composition and thermal condition

Background Vegetation fire may change Phosphorus (P) cycling in terrestrial ecosystems through converting biomass into fire residues. Aim The aim of this study was to understand the chemistry and mobility of P in fire residues to help reveal P thermochemistry during biomass burning and post-fire P cycling. Methods A combination of sequential extraction, liquid 31P NMR and P K-edge XANES was used to obtain quantitative P speciation and explain P solubilisation behaviours of charcoal. Key results Despite varying diverse P species existing in raw biomass, only two P structural moieties – orthophosphate and pyrophosphate – were identified in charcoal. However, relative abundance of pyrophosphate differs greatly among charcoal samples from different biomass types, ranging between 0 and 40% of total extractable P. Although P K-edge XANES data indicates abundant soluble phosphate minerals, most P (70–90%) is likely occluded physically in the charcoal. The bicarbonate-extractable P (the Olsen-P) varies significantly and cannot be explained by surface P concentration or elemental stoichiometry alone. Conclusion and implications The results suggest the importance of starting biomass P speciation (i.e. molecular structure and complexation environment) and thermal conditions in controlling P speciation and availability in charcoal. The different P chemistry between charcoal and ash suggests the importance of fire types and severity in disturbing the P cycle.

Forestry↗
NASA NTRS1978

User's Guide for a Modular Flutter Analysis Software System (Fast Version 1.0)

The use and operation of a group of computer programs to perform a flutter analysis of a single planar wing are described. This system of programs is called FAST for Flutter Analysis System, and consists of five programs. Each program performs certain portions of a flutter analysis and can be run sequentially as a job step or individually. FAST uses natural vibration modes as input data and performs a conventional V-g type of solution. The unsteady aerodynamics programs in FAST are based on the subsonic kernel function lifting-surface theory although other aerodynamic programs can be used. Application of the programs is illustrated by a sample case of a complete flutter calculation that exercises each program.

Desmarais, R. N.↗
DOE OSTI2024

Physics-inspired spatiotemporal-graph AI ensemble for the detection of higher order wave mode signals of spinning binary black hole mergers

We present a new class of AI models for the detection of quasi-circular, spinning, non-precessing binary black hole mergers whose waveforms include the higher order gravitational wave modes ($\ell$, |m|) = {(2,2), (2,1), (3,3), (3,2), (4,4)}, and mode mixing effects in the $\ell$ = 3, |m| = 2 harmonics. These AI models combine hybrid dilated convolution neural networks to accurately model both short- and long-range temporal sequential information of gravitational waves; and graph neural networks to capture spatial correlations among gravitational wave observatories to consistently describe and identify the presence of a signal in a three detector network encompassing the Advanced LIGO and Virgo detectors. We first trained these spatiotemporal-graph AI models using synthetic noise, using 1.2 million modeled waveforms to densely sample this signal manifold, within 1.7 h using 256 NVIDIA A100 GPUs in the Polaris supercomputer at the Argonne Leadership Computing Facility. This distributed training approach exhibited optimal classification performance, and strong scaling up to 512 NVIDIA A100 GPUs. With these AI ensembles we processed data from a three detector network, and found that an ensemble of 4 AI models achieves state-of-the-art performance for signal detection, and reports two misclassifications for every decade of searched data. We distributed AI inference over 128 GPUs in the Polaris supercomputer and 128 nodes in the Theta supercomputer, and completed the processing of a decade of gravitational wave data from a three detector network within 3.5 h. Finally, we fine-tuned these AI ensembles to process the entire month of February 2020, which is part of the O3b LIGO/Virgo observation run, and found 6 gravitational waves, concurrently identified in Advanced LIGO and Advanced Virgo data, and zero false positives. This analysis was completed in one hour using one NVIDIA A100 GPU.

79 ASTRONOMY AND ASTROPHYSICS↗