Hasil untuk "Geology"

Philipp D. Lösel, Aleese Barron, Yulai Zhang et al.

Non-destructive 3D imaging of large multi-particulate samples is essential for quantifying particle-level properties, such as size, shape, and spatial distribution, across applications in mining, materials science, and geology. However, accurate instance segmentation of particles in tomographic data remains challenging due to high morphological variability and frequent particle contact, which limit the effectiveness of classical methods like watershed algorithms. While supervised deep learning approaches offer improved performance, they rely on extensive annotated datasets that are labor-intensive, error-prone, and difficult to scale. In this work, we propose self-validated learning, a novel self-training framework for particle instance segmentation that eliminates the need for manual annotations. Our method leverages implicit boundary detection and iteratively refines the training set by identifying particles that can be consistently matched across reshuffled scans of the same sample. This self-validation mechanism mitigates the impact of noisy pseudo-labels, enabling robust learning from unlabeled data. After just three iterations, our approach accurately segments over 97% of the total particle volume and identifies more than 54,000 individual particles in tomographic scans of quartz fragments. Importantly, the framework also enables fully autonomous model evaluation without the need for ground truth annotations, as confirmed through comparisons with state-of-the-art instance segmentation techniques. The method is integrated into the Biomedisa image analysis platform (https://github.com/biomedisa/biomedisa/).

Ana Maria Jaramillo, Mariana Macedo, Marcos Oliveira et al.

The participation of women in academia has increased in the last few decades across many fields (e.g., Computer Science, History, Medicine). However, this increase in the participation of women has not been the same at all career stages. Here, we study how gender participation within different fields is related to gender representation in top-ranking positions in productivity (number of papers), research impact (number of citations), and co-authorship networks (degree of connectivity). We analyzed over 80 million papers published from 1975 to 2020 in 19 academic fields. Our findings reveal that women remain a minority in all 19 fields, with physics, geology, and mathematics having the lowest percentage of papers authored by women at 14% and psychology having the largest percentage at 39%. Women are significantly underrepresented in top-ranking positions (top 10% or higher) across all fields and metrics (productivity, citations, and degree), indicating that it remains challenging for early researchers (especially women) to reach top-ranking positions, as our results reveal the rankings to be rigid over time. Finally, we show that in most fields, women and men with comparable productivity levels and career age tend to attain different levels of citations, where women tend to benefit more from co-authorships, while men tend to benefit more from productivity, especially in pSTEMs. Our findings highlight that while the participation of women has risen in some fields, they remain under-represented in top-ranking positions. Greater gender participation at entry levels often helps representation, but stronger interventions are still needed to achieve long-lasting careers for women and their participation in top-ranking positions.

Weiwei Wang, Elena Blanc-Betes, Madhu Khanna et al.

Abstract Energy crops will be critical for scaling up production of Sustainable Aviation Fuel in the United States and reducing greenhouse gas emissions. Here we examine the economic incentives for the extent and type of land conversion needed to scale up fuel production from a mix of cellulosic feedstocks and quantify its greenhouse gas intensity. We show that even with the availability of marginal non-cropland, there will be incentives for converting cropland to produce energy crops as the price of sustainable aviation fuel increases. But contrary to expectations, we find that scaling up fuel production by converting more cropland and more non-cropland from existing uses to energy crops lowers its net greenhouse gas intensity, due to high soil carbon sequestration rate of energy crops, even after considering land use change emissions.The potential savings in emissions are larger than the foregone soil carbon accumulation benefits from keeping that land in current uses.

Nikolai Buktukov, Rustem Igizbaev, Gulnaz Moldabayeva et al.

This analytical review is aimed at identifying and analysing a variety of factors affecting the low oil recovery factor. The study covers a wide range of parameters, from the mining and geological conditions of deposits to the physical and mechanical properties of rocks and hydrocarbons. Attention is also paid to such important aspects as geological features, including fracturing of rocks, waterlogging of formations and folding of deposits, which can significantly complicate oil production. Statistical data on current oil recovery rates from different regions and countries were collected and analysed, which helped to identify the most common problems and typical oil recovery rates. The review highlights that, along with well-known factors such as high oil viscosity and low rock permeability, oil recovery factor is significantly influenced by resistance to extraction by gravity, and complex tectonic conditions such as the presence of folds and faults. In addition, the problems related to the modelling and representation of the oil reservoir are considered, which can lead to errors in the assessment of oil reserves and, consequently, to an underestimated oil recovery factor. In conclusion, the review suggests possible areas for the development of oil production technologies that can help to overcome the identified obstacles. Suggestions are given for improving methods of increasing oil recovery, such as the introduction of new technologies, improvement of existing methods, and conducting more accurate geological studies.

F. P. Giest, F. P. Giest, M. Jenrich et al.

<p>Climate warming in the Arctic results in thawing permafrost and associated processes like thermokarst, especially in ice-rich permafrost regions. Since permafrost soils are one of the largest organic carbon reservoirs of the world, their thawing leads to the release of greenhouse gases due to increasing microbial activity with rising soil temperature, further exacerbating climate warming. To enhance the predictions of potential future impacts of permafrost thaw, a detailed assessment of changes in soil characteristics in response to thermokarst processes in permafrost landscapes is needed, which we investigated in this study in an Arctic coastal lowland. We analysed six sediment cores from the Arctic Coastal Plain of northern Alaska, each representing a different landscape feature along a gradient from upland to thermokarst lake and drained basin to thermokarst lagoon in various development stages. For the analysis, a multiproxy approach was used, including sedimentological (grain size, bulk density, ice content), biogeochemical (total organic carbon (TOC), TOC density (<span class="inline-formula">TOC_vol</span>), total nitrogen (TN), stable carbon isotopes (<span class="inline-formula"><i>δ</i>¹³C</span>), TOC<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="e653eaf840568ee76bb20ba3bf368ae0"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bg-22-2871-2025-ie00001.svg" width="8pt" height="14pt" src="bg-22-2871-2025-ie00001.png"/></svg:svg></span></span>TN ratio, mercury (Hg)), and lipid biomarker (<span class="inline-formula"><i>n</i></span>-alkanes, <span class="inline-formula"><i>n</i></span>-alkanols, and their ratios) parameters. We found that a semi-drained state of thermokarst lakes features the lowest OC content, and TOC and TN are generally higher in unfrozen deposits, hinting at a more intact state of organic matter. Indicated by the average chain length (ACL), <span class="inline-formula"><i>δ</i>¹³C</span>, <span class="inline-formula"><i>P</i>_aq</span>, and <span class="inline-formula"><i>P</i>_wax</span>, we found a stronger influence of aquatic organic matter (OM) in the OM composition in the soils covered by water compared to those not covered by water. Moreover, the results of the <span class="inline-formula"><i>δ</i>¹³C</span>, TOC<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="3af55808dad7e355d8e0b0b2a0272ce7"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bg-22-2871-2025-ie00002.svg" width="8pt" height="14pt" src="bg-22-2871-2025-ie00002.png"/></svg:svg></span></span>TN ratio, and CPI indicate that the saline deposits contain stronger degraded OM than the deposits not influenced by saltwater. Additionally, we found positive correlations between the TOC and <span class="inline-formula">TOC_vol</span> and the Hg content in the deposits. The results indicate that thermokarst-influenced deposits tend to accumulate Hg during thawed periods and thus contain more Hg than the upland permafrost deposits that have not been impacted by lake formation. Our findings offer valuable insights into the dynamics of carbon storage and vulnerability to decomposition in coastal permafrost landscapes, reflecting the interplay of environmental factors, landform characteristics, and climate change impacts on Arctic permafrost environments.</p>

Fanny Lehmann, Filippo Gatti, Didier Clouteau

Numerical simulations are essential tools to evaluate the solution of the wave equation in complex settings, such as three-dimensional (3D) domains with heterogeneous properties. However, their application is limited by high computational costs and existing surrogate models lack the flexibility of numerical solvers. This work introduces the Multiple-Input Fourier Neural Operator (MIFNO) to deal with structured 3D fields representing material properties as well as vectors describing the source characteristics. The MIFNO is applied to the problem of elastic wave propagation in the Earth's crust. It is trained on the HEMEW^S-3D database containing 30000 earthquake simulations in different heterogeneous domains with random source positions and orientations. Outputs are time- and space-dependent surface wavefields. The MIFNO predictions are assessed as good to excellent based on Goodness-Of-Fit (GOF) criteria. Wave arrival times and wave fronts' propagation are very accurate since 80% of the predictions have an excellent phase GOF. The fluctuations amplitudes are good for 87% of the predictions. The envelope score is hindered by the small-scale fluctuations that are challenging to capture due to the complex physical phenomena associated with high-frequency features. Nevertheless, the MIFNO can generalize to sources located outside the training domain and it shows good generalization ability to a real complex overthrust geology. When focusing on a region of interest, transfer learning improves the accuracy with limited additional costs, since GOF scores improved by more than 1 GOF unit with only 500 additional specific samples. The MIFNO is the first surrogate model offering the flexibility of an earthquake simulator with varying sources and material properties. Its good accuracy and massive speed-up offer new perspectives to replace numerical simulations in many-query problems.

امیر فضلی اله آبادی, مجید عطایی پور

برای بررسی ارتباط میان اجزای نظارتی و اجرایی معدن و به منظور بهبود سطح ایمنی سیستم، این مقاله روش جدیدی را برای ارزیابی و مدیریت ایمنی سیستم معادن معرفی می‌کند. بدین منظور در این مقاله از کاربرد نظریه بازی‌ها برای حل مسایل ایمنی معادن استفاده شده است. نظریه بازی‌ها ابزار ساختاریافته‌ای است که تعاملات بین دو یا چند بازیکن را بررسی می‌کند تا اقدامات آن‌ها را در شرایط معین درک کند. در این مقاله از بازی تکاملی به دلیل بیان پویایی روابط میان بازیکنان، استفاده شده است. مدل معرفی شده تعاملات بین دولت، مدیران و معدنچیان را تحت شرایط مختلف شبیه‌سازی می‌کند و تأثیر عوامل نظارتی بر آن‌ها در سیستم ارزیابی می‌شود. نتایج نشان می‌دهد که تاثیر هر عامل بر ایمنی سیستم متفاوت است و بازیکنان، متناسب با هر عامل نظارتی بر ایمنی سیستم تاثیر می‌گذارند. از جمله این عوامل، تاثیرگذاری جریمه‌های اعمالی ناظر بازی بر رفتار مدیریت معدن و کارگران معدن در بیشترین میزان بود. به طوری که با افزایش جریمه‌ها، بازیکنان در زمان کوتاهی استراتژی‌های همسو با تولید ایمن را در پیش گرفتند. در ادامه تاثیر مشوق‌های دولتی نیز بررسی و مشخص شد که به ازای افزایش ضریب پاداش به مدیریت و کارگران معدن تغییر استراتژی و تولید ایمن در معدن برقرار خواهد شد.

Hanchen Wang, Yinpeng Chen, Tariq Alkhalifah et al.

The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection serve as indispensable tools, offering vital insights into subsurface structures and fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high-quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, DeFault, specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain-adaptation, DeFault allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using DeFault, the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of DeFault on a field case study involving CO2 injection related microseismic data from the Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and aided in the prevention of potential geological hazards. Our results highlight the potential of DeFault as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning's capacity to refine these methods. Ultimately, our work bear significant implications for CCUS technology deployment, an essential strategy in combating climate change.

J. Lustig-Yaeger, N. R. Izenberg, M. S. Gilmore et al.

Parker Solar Probe (PSP) conducted several flybys of Venus while using Venus' gravity for orbital adjustments to enable its daring passes of the Sun. During these flybys, PSP turned to image the nightside of Venus using the Wide-field Imager for Solar PRobe (WISPR) optical telescopes, which unexpectedly observed Venus' surface through its thick and cloudy atmosphere in a theorized, but until-then unobserved near-visible spectral window below 0.8 $μ$m. We use observations taken during PSP's fourth Venus gravity assist flyby to examine the origin of the Venus nightside flux and confirm the presence of this new atmospheric window through which to observe the surface geology of Venus. The WISPR images are well explained by emission from the hot Venus surface escaping through a new atmospheric window in the optical with an overlying emission component from the atmosphere at the limb that is consistent with O$_2$ nightglow. The surface thermal emission correlates strongly with surface elevation (via temperature) and emission angle. Tessera and plains units have distinct WISPR brightness values. Controlling for elevation, Ovda Regio tessera is brighter than Thetis Regio; likewise, the volcanic plains of Sogolon Planitia are brighter than the surrounding regional plains units. WISPR brightness at 0.8 $μ$m is predicted to be positively correlated to FeO content in minerals; thus, the brighter units may have a different starting composition, be less weathered, or have larger particle sizes.

Zhiguo He, Yingzhong Lou, Haoyang Zhang et al.

Active hydrothermal vents provide the surrounding submarine environment with substantial amounts of matter and energy, thus serving as important habitats for diverse megabenthic communities in the deep ocean and constituting a unique, highly productive chemosynthetic ecosystem on Earth. Vent-endemic biological communities gather near the venting site and are usually not found beyond a distance of the order of 100 m from the vent. This is surprising because one would actually expect matter ejected from high-temperature vents, which generate highly turbulent buoyancy plumes, to be suspended and carried far away by the plume flows and deep-sea currents. Here, we study this problem from a fluid dynamics perspective by simulating the vent hydrodynamics using a numerical model that couples the plume flow with induced matter and energy transport. We find that both low- and high-temperature vents deposit most vent matter relatively close to the plume. In particular, the tendency of turbulent buoyancy plumes to carry matter far away is strongly counteracted by generated entrainment flows back into the plume stem. The deposition ranges of organic and inorganic hydrothermal particles obtained from the simulations for various natural high-temperature vents are consistent with the observed maximum spatial extent of biological communities, evidencing that plume hydrodynamics exercises strong control over the spatial distribution of vent-endemic fauna. While other factors affecting the spatial distribution of vent-endemic fauna, such as geology and geochemistry, are site-specific, the main physical features of plume hydrodynamics unraveled in this study are largely site-unspecific and therefore universal across vent sites on Earth.

Gaetano Falcone, Gaetano Elia, Annamaria di Lernia

The assessment of slope susceptibility to seismically-induced displacements receives wide attention in the geotechnical earthquake engineering field, but the alteration of the seismic wave inside the slope and at the ground surface due to the presence of a shear band confining a quiescent landslide body is rarely investigated. This paper describes the preliminary results of the numerical analysis of two step-like FE models, reproducing a gentle slope and steep cutting subjected to weak earthquakes, thus focusing on seismic wave amplification processes only. The results show that the higher the thickness of the weakened zone, the higher the maximum value of the amplification factors predicted at the ground surface. For gentle slopes affected by a landslide body confined by a thick shear band, the highest amplification factors are expected in the longer period range of 0.7–1.1 s, while the highest level of amplification is achieved in the intermediate period interval of 0.4–0.8 s in the case of steep slopes. In addition, the parasitic vertical component of acceleration can be considerably amplified beyond the crest and at the toe of the slope for increasing band thickness, especially in the case of steep topography, for which the effects of the shear band morphology enhance those related to the topographic profile. Finally, the fundamental frequency of the sloping deposit is not particularly affected by the presence of the shear band, while the amplitude of the amplification function at the fundamental frequency is clearly related to its thickness.

Jinpeng Zhang, Michal Tomczak, Andrzej Witkowski et al.

Marine transgressions-regressions have profoundly shaped marginal seas following global sea-level fluctuations driven by climate change. This study on a sedimentary core profile SO219/31-4 from the Beibu Gulf, northwestern South China Sea (SCS), reveals information about paleoenvironment, paleoceanography and paleoclimate changes through fossil diatom assemblages and grain size distributions during the last ca. 12900 cal. yr. BP. Eight local diatom assemblage zones were distinguished and assigned to paleoenvironmental fluctuations recording sea-level and depositional environment changes in eight stages, ca. 12900–11700 (stage 1), ca. 11700–9500 (stage 2), ca. 9500–7200 (stage 3), ca. 7200–5800 (stage 4), ca. 5800–3800 (stage 5), ca. 3800–2400 (stage 6), ca. 2400–800 (stage 7) and ca. 800–0 (stage 8), cal. yr. BP. After the low sea level of stage 1 within the last deglaciation, rapid increases in sea level in stages 2 and 3 were recorded as meltwater events pulse-1B and pulse-1C resulting in marine transgression rates of ca. 16 m/kyr and 8 m/kyr, respectively. The high sea level, above the present level, in stages 4 and 5, in the Middle Holocene Climatic Optimum period, was clearly documented by more significant open sea/tropical diatom species and coastal planktonic species percentages, respectively. The late Holocene regression of sea levels was marked by a pronounced reversion of diatom taphocoenosis, responding to neoglacial climate. Fossil diatom assemblages outlined responded to paleoclimate of global warming in the deglacial and early Holocene. This study provides additional insights into the late Pleistocene and Post-glacial history of a tropical-subtropical shallow water gulf, in the NW-SCS.

Kai Gong, Elsa Olivetti

Density is one of the most commonly measured or estimated materials properties, especially for glasses and melts that are of significant interest to many fields, including metallurgy, geology, materials science and sustainable cements. Here, two types of machine learning (ML) models (i.e., random forest (RF) and artificial neural network (ANN)) have been developed to predict the room-temperature density of glasses in the compositional space of CaO-MgO-Al2O3-SiO2-TiO2-FeO-Fe2O3-Na2O-K2O-MnO (CMASTFNKM), based on ~2100 data points mined from ~140 literature studies. The results show that the RF and ANN models give accurate predictions of glass density with R2 values, RMSE, and MAPE of ~0.96-0.98, ~0.02-0.03 g/cm3 and ~0.59-0.79%, respectively, for the 15% testing set, which are more accurate compared with empirical density models based on ionic packing ratio (with R2 values, RMSE, and MAPE of ~0.28-0.91, ~0.05-0.15 g/cm3, and ~1.40-4.61%, respectively). Furthermore, glass density is shown to be a reliable reactivity indicator for a range of CaO-Al2O3-SiO2 (CAS) and volcanic glasses due to its strong correlation (R2 values above ~0.90) with the average metal-oxygen dissociation energy (a structural descriptor) of these glasses. Analysis of the predicted density-composition relationships from these models (for selected compositional subspaces) suggests that the ANN model exhibits a certain level of transferability (i.e., ability to extrapolate to compositional space not (or less) covered in the database) and captures known features including the mixed alkaline earth effects for (CaO-MgO)0.5-(Al2O3-SiO2)0.5 glasses.

Rami N Khushaba, Arman Melkumyan, Andrew J Hill

Understanding the structure and mineralogical composition of a region is an essential step in mining, both during exploration (before mining) and in the mining process. During exploration, sparse but high-quality data are gathered to assess the overall orebody. During the mining process, boundary positions and material properties are refined as the mine progresses. This refinement is facilitated through drilling, material logging, and chemical assaying. Material type logging suffers from a high degree of variability due to factors such as the diversity in mineralization and geology, the subjective nature of human measurement even by experts, and human error in manually recording results. While laboratory-based chemical assaying is much more precise, it is time-consuming and costly and does not always capture or correlate boundary positions between all material types. This leads to significant challenges and financial implications for the industry, as the accuracy of production blasthole logging and assaying processes is essential for resource evaluation, planning, and execution of mine plans. To overcome these challenges, this work reports on a pilot study to automate the process of material logging and chemical assaying. A machine learning approach has been trained on features extracted from measurement-while-drilling (MWD) data, logged from autonomous drilling systems (ADS). MWD data facilitate the construction of profiles of physical drilling parameters as a function of hole depth. A hypothesis is formed to link these drilling parameters to the underlying mineral composition. The results of the pilot study discussed in this paper demonstrate the feasibility of this process, with correlation coefficients of up to 0.92 for chemical assays and 93% accuracy for material detection, depending on the material or assay type and their generalization across the different spatial regions.

Loizeau Damien, Pilorget Cédric, Poulet François et al.

The PTAL (Planetary Terrestrial Analogues Library) project aims at building and exploiting a database involving several analytical techniques, to help characterizing the mineralogical evolution of terrestrial bodies, starting with Mars. Around 100 natural Earth rock samples have been collected from selected locations to gather a variety of analogues for Martian geology, from volcanic to sedimentary origin with different levels of alteration. All samples are to be characterized within the PTAL project with different mineralogical and elemental analysis techniques, including techniques brought on actual and future instruments at the surface of Mars (Near InfraRed spectroscopy, Raman spectroscopy and Laser Induced Breakdown Spectroscopy). This paper presents the NIR measurements and interpretations acquired with the ExoMars MicrOmega spare instrument. MicrOmega is a NIR hyperspectral microscope, mounted in the analytical laboratory of the ExoMars rover Rosalind Franklin. All PTAL samples have been observed at least once with MicrOmega using a dedicated setup. For all PTAL samples data description and interpretation are presented. For some chosen examples, RGB images and spectra are presented a well. A comparison with characterizations by NIR and Raman spectrometry is discussed for some of the samples. In particular, the spectral imaging capacity of MicrOmega allows detections of mineral components and potential organic molecules that were not possible with other one-spot techniques. Additionally, it enables to estimate heterogeneities in the spatial distribution of various mineral species. The MicrOmega/PTAL data shall support the future observations and analyses performed by MicrOmega/Rosalind Franklin instrument.

Philippa Liggins, Sean Jordan, Paul B. Rimmer et al.

The geology of Earth and super-Earth sized planets will, in many cases, only be observable via their atmospheres. Here, we investigate secondary volcanic atmospheres as a key base case of how atmospheres may reflect planetary geochemistry. We couple volcanic outgassing with atmospheric chemistry models to simulate the growth of C-O-H-S-N atmospheres in thermochemical equilibrium, focusing on what information about a planet's mantle fO$_2$ and bulk silicate H/C ratio could be determined by atmospheric observation. 800K volcanic atmospheres develop distinct compositional groups as the mantle fO$_2$ is varied, which can be identified using sets of (often minor) indicator species: Class O, representing an oxidised mantle and containing SO$_2$ and sulfur allotropes; Class I, formed by intermediate mantle fO$_2$'s and containing CO$_2$, CH$_4$, CO and COS; and Class R, produced by reduced mantles, containing H$_2$, NH$_3$ and CH$_4$. These atmospheric classes are robust to a wide range of bulk silicate H/C ratios. However, the H/C ratio does affect the dominant atmospheric constituent, which can vary between H$_2$, H$_2$O and CO$_2$ once the chemical composition has stabilised to a point where it no longer changes substantially with time. This final atmospheric state is dependent on the mantle fO$_2$, the H/C ratio, and time since the onset of volcanism. The atmospheric classes we present are appropriate for the closed-system growth of hot exoplanets, and may be used as a simple base for future research exploring the effects of other open-system processes on secondary volcanic atmospheres.

Duncan V. Mifsud, Zuzana Kanuchova, Peter Herczku et al.

Sulfur is the tenth most abundant element in the universe and is known to play a significant role in biological systems. Accordingly, in recent years there has been increased interest in the role of sulfur in astrochemical reactions and planetary geology and geochemistry. Among the many avenues of research currently being explored is the laboratory processing of astrophysical ice analogues. Such research involves the synthesis of an ice of specific morphology and chemical composition at temperatures and pressures relevant to a selected astrophysical setting (such as the interstellar medium or the surfaces of icy moons). Subsequent processing of the ice under conditions that simulate the selected astrophysical setting commonly involves radiolysis, photolysis, thermal processing, neutral-neutral fragment chemistry, or any combination of these, and has been the subject of several studies. The in-situ changes in ice morphology and chemistry occurring during such processing has been monitored via spectroscopic or spectrometric techniques. In this paper, we have reviewed the results of laboratory investigations concerned with sulfur chemistry in several astrophysical ice analogues. Specifically, we review (i) the spectroscopy of sulfur-containing astrochemical molecules in the condensed phase, (ii) atom and radical addition reactions, (iii) the thermal processing of sulfur-bearing ices, (iv) photochemical experiments, (v) the non-reactive charged particle radiolysis of sulfur-bearing ices, and (vi) sulfur ion bombardment of and implantation in ice analogues. Potential future studies in the field of solid phase sulfur astrochemistry are also discussed in the context of forthcoming space missions, such as the NASA James Webb Space Telescope and the ESA Jupiter Icy Moons Explorer mission.

Andrew M. Buchan, Amy Bonsor, Oliver Shorttle et al.

Polluted white dwarfs that have accreted planetary material provide a unique opportunity to probe the geology of exoplanetary systems. However, the nature of the bodies which pollute white dwarfs is not well understood: are they small asteroids, minor planets, or even terrestrial planets? We present a novel method to infer pollutant masses from detections of Ni, Cr and Si. During core--mantle differentiation, these elements exhibit variable preference for metal and silicate at different pressures (i.e., object masses), affecting their abundances in the core and mantle. We model core--mantle differentiation self-consistently using data from metal--silicate partitioning experiments. We place statistical constraints on the differentiation pressures, and hence masses, of bodies which pollute white dwarfs by incorporating this calculation into a Bayesian framework. We show that Ni observations are best suited to constraining pressure when pollution is mantle-like, while Cr and Si are better for core-like pollution. We find 3 systems (WD0449-259, WD1350-162 and WD2105-820) whose abundances are best explained by the accretion of fragments of small parent bodies ($<0.2M_\oplus$). For 2 systems (GD61 and WD0446-255), the best model suggests the accretion of fragments of Earth-sized bodies, although the observed abundances remain consistent ($<3σ$) with the accretion of undifferentiated material. This suggests that polluted white dwarfs potentially accrete planetary bodies of a range of masses. However, our results are subject to inevitable degeneracies and limitations given current data. To constrain pressure more confidently, we require serendipitous observation of (nearly) pure core and/or mantle material.

María Lidia Sánchez, J. Rossi, S. Morra et al.

Se estudió una sucesión sedimentaria que aflora en el sudeste de la Cuenca Neuquina, en el departamento El Cuy (Río Negro). La misma incluye a las formaciones Huincul y Lisandro que integran el Subgrupo Río Limay (Grupo Neuquén), y han sido asignadas al Cenomaniano- Turoniano. Se identificaron once litofacies de origen fluvial, tres litofacies de naturaleza eólica y dos litofacies volcaniclásticas. A partir de los agrupamientos en unidades genéticamente relacionadas se definieron siete elementos fluviales de intracanal, cuatro de planicie de inundación y cuatro eólicos. La distribución espacial y relaciones entre los elementos arquitecturales ha permitido reconocer sistemas fluviales agradantes de alta sinuosidad (SF-I y II), un sistema de abanico terminal (SAT) y campos de médanos barjanoides (SE). El análisis estratigráfico-secuencial permitió definir cinco Secuencias a partir de las relaciones espaciales y temporales de los elementos arquitecturales mayores y de la determinación de superficies estratigráficamente significativas. La base de la Formación Huincul está representada por el SF-I, caracterizado por un sistema de alta sinuosidad, con baja relación canales/planicie de inundación y abundantes depósitos de desbordes. Este tramo de la secuencia se interpreta como el Cortejo de Alta Acomodación (AA) de la Secuencia I (S-I). El sector cuspidal de la unidad está integrado por un sistema similar pero con una alta relación canal/planicie de inundación y constituye el Cortejo de Baja Acomodación (BA) de la Secuencia II (S-II). Se propone que la depositación de la Formación Huincul tuvo lugar bajo condiciones climáticas cálidas con un régimen de estacionalidad marcado. La Formación Lisandro se inicia con depósitos de un sistema distributario proximal de abanico terminal (SAT) que representan el Cortejo AA de S-II. De aquí en adelante es notoria la recurrencia de SE, caracterizando los Cortejos BA y una sucesión desde cuenca de inundación a distributarios proximales de SAT, integrando los Cortejos AA de las secuencias S-II, III, IV y V. La unidad se depositó bajo condiciones climáticas semiáridas permanentes. Las unidades estratigráficas estudiadas se consideran de carácter sinorogénico, con un control tectónico significativo en la definición del espacio de acomodación y un volcanismo principalmente activo durante la sedimentación de la Formación Huincul. La Formación Lisandro corresponde a un período de abrupto incremento en la tasa de subsidencia en la Cuenca Neuquina.

S. B. Luthcke, T. C. Thomas, T. A. Pennington et al.

Abstract ICESat‐2 science requirements are dependent on the accurate real‐time pointing control (i.e., geolocation control) and postprocessed geolocation knowledge of the laser altimeter surface returns. Prelaunch pointing alignment errors and postlaunch pointing alignment variation result in large geolocation errors that must be calibrated on orbit. In addition, the changing sun‐orbit geometry causes thermal‐mechanical forced laser frame alignment variations at the orbit period and trends from days, weeks, and months. Early mission analysis computed precise postlaunch laser beam alignment calibration. The alignment calibration was uploaded to the spacecraft and enabled the pointing control performance to achieve 4.4 ± 6.0 m, a significant improvement over the 45 m (1 σ) mission requirement. Laser frame alignment calibrations are used to reduce the alignment bias and time variation, as well as the orbital variation contributions to geolocation knowledge error from 6 to 1.7 m (1 σ). Relative beam alignment of the six beams is calibrated and shown to contribute between 0.5 ± 0.1 m and 2.4 ± 0.2 m of remaining geolocation knowledge error. Independent geolocation assessment based on comparison to high‐resolution digital elevation models agrees well with the calibration geolocation error estimates. The analysis demonstrates the ICESat‐2 mission is performing far better than its geolocation knowledge requirement of 6.5 m (1 σ) after the laser frame alignment bias variation and orbital variation calibrations have been applied. Remaining geolocation error is beam dependent and ranges from 2.5 m for beam 6 to 4.4 m for beam 2 (mean + 1 σ).