Joseph R. Masiero, Yuna G. Kwon, Elena Selmi
et al.
Polarimetry has the capacity to provide a unique probe of the surface properties of asteroids. Trends in polarization behavior as a function of wavelength trace asteroid regolith mineral properties that are difficult to probe without measurements in situ or on returned samples. We present recent results from our ongoing survey of near-infrared polarimetric properties of asteroids. Our data reveal a mineralogical link between asteroids in the broader M- and K- spectral classes. In particular, M-type objects (16) Psyche, (55) Pandora, (135) Hertha, and (216) Kleopatra show the same polarimetric-phase behavior as K-type objects (89) Julia, (221) Eos, and (233) Asterope from visible through near-infrared light. The near-infrared behavior for these objects is distinct from other classes observed to date, and shows a good match to the polarimetric properties of M-type asteroid (21) Lutetia from the visible to the near-infrared. The best link for these objects from laboratory polarimetric phase curve measurements is to a troilite-rich fine-grained regolith. Our observations indicate that the M- and K-type spectral classes are most likely part of a continuum, with the observed spectral differences due to heterogeneity from partial differentiation, shock darkening of the surface material, or other later evolution of the original parent population. We also provide incidental J- and H-band polarimetric observations of other Main Belt asteroids obtained during our survey.
In order to understand the mineralogy and structure of protoplanetary disks, it is important to analyze them from both an empirical spectrum-based perspective and a radiative transfer image-based perspective. In a prior paper, we set forth an empirical mineralogy mid-IR spectral model that conveyed spatial information and worked in tandem with a radiative transfer model, which formed the EaRTH Disk Model. In this article, we take the empirical portion of that model, the TZTD model, and refine it with a newly derived protoplanetary disk thermal emission formulation which uses a temperature distribution without requiring discrete integration; this simplified model uses an empirical relation between spatial distribution variables, which permits radiative transfer models to directly fit these spatial distribution variables more freely within the provided empirical constraints. We test this model against several $Spitzer~Space~Telescope$ Infrared Spectrograph (IRS) spectra, primarily transition disks, and discuss the mineralogical and structural implications of the fits, including the implications for grain growth and processing within the atmospheric zones of the disks.
Cicero X. Lu, Tushar Mittal, Christine H. Chen
et al.
Debris disks, which consist of dust, planetesimals, planets, and gas, offer a unique window into the mineralogical composition of their parent bodies, especially during the critical phase of terrestrial planet formation spanning 10 to a few hundred million years. Observations from the $\textit{Spitzer}$ Space Telescope have unveiled thousands of debris disks, yet systematic studies remain scarce, let alone those with unsupervised clustering techniques. This study introduces $\texttt{CLUES}$ (CLustering UnsupErvised with Sequencer), a novel, non-parametric, fully-interpretable machine-learning spectral analysis tool designed to analyze and classify the spectral data of debris disks. $\texttt{CLUES}$ combines multiple unsupervised clustering methods with multi-scale distance measures to discern new groupings and trends, offering insights into compositional diversity and geophysical processes within these disks. Our analysis allows us to explore a vast parameter space in debris disk mineralogy and also offers broader applications in fields such as protoplanetary disks and solar system objects. This paper details the methodology, implementation, and initial results of $\texttt{CLUES}$, setting the stage for more detailed follow-up studies focusing on debris disk mineralogy and demographics.
Elnur Baloglanov, Ulviyya Yolchuyeva, Ruslan Akhundov
et al.
Problem statement. This study explores unconventional hydrocarbon resources in East Azerbaijan, focusing on oil-bearing rocks in the Cheyildere and Gyrgyshlag-Girdagh areas. It examines the spatial and temporal distribution of minerals and chemical compositions in Miocene formations. Terrigenous quartz types identified in the Maikop (Lower Miocene), Chokrak (Lower Miocene), and Diatom (Middle to Upper Miocene) formations provide insights into sedimentological maturity. Geochemical classification and tectonic discriminant diagrams help interpret the protoliths of these sediments. The study also evaluates how mineralogy and moisture affect oil-bearing potential, offering useful data for future exploration and resource management.
Purpose. This study aims to explore the genesis and potential of oil-bearing deposits of the Miocene age in East Azerbaijan by characterizing the geological, mineralogical, and geochemical proxies of samples collected from outcrops across various regions.
Methods. The mineralogical composition of samples was analyzed using a MiniFlex 600 diffractometer. Chemical composition was determined using S8 TIGER Series 2 and Agilent 7700 Series ICP-MS spectrometers.
Results. The geological characteristics of oil-bearing deposits from the Miocene stratigraphic unit were thoroughly analyzed, providing new insights into the distribution patterns of oil-bearing formations and strata within the studied areas. The mineralogical composition was examined in detail, focusing on the spatial and temporal variations in mineral distribution across different formations of Miocene. The chemical composition reveals significant differences between formations in terms of elemental signatures. The study of the chemical proxies enabled the identification of specific terrigenous quartz types. Additionally, the research assessed the influence of mineralogical composition, moisture and oil content on the oil-bearing capacity. The results demonstrated a clear relationship between the mineralogical characteristics and the oil-bearing potential of the rocks.
Conclusions. The Chokrak Formation is of particular interest due to its significant oil-bearing potential, with total thicknesses of up to 40 meters in Miocene outcrops studied in the areas of Cheyildere and Gyrgyshlag-Girdagh. Compared to other areas, the Chokrak Formation is dominated by quartz minerals (>70%), while the oil-bearing rocks of this formation contain fewer clay minerals and no carbonate minerals. The Upper Maikop deposits are characterized by calcite, and the Diatom deposits by dolomite.
Most oil-bearing rocks of Maikop and Diatom age correlate with greywacke and litharenite, while Chokrak rocks with higher silicon content show a connection with subarkose and sublitharenites. For Diatom oil-bearing rocks, in addition to quartzitic sedimentary sources, some moderate and acidic magmatic rocks can also be considered. Chokrak horizon deposits, rich in quartz, have a more mature mineralogical nature. These deposits, associated with passive continental margins, are typically linked to the interior of cratons or recycled orogenic regions, suggesting long-distance transport.
Relatively moist samples containing clay and carbonate minerals exhibit a significantly higher oil accumulation potential than samples with high quartz content. From this perspective, the marly rocks of the Meotis are of particular interest.
Tchedele Langollo Yannick, Bilkissou Alim, Mohamadou Alpha Ali
et al.
Abstract This study investigates the potential of micro glass powder as a supplementary cementitious material in Belite cement matrices, addressing both environmental concerns and performance optimization. With the cement industry contributing significantly to global CO2 emissions and glass waste posing recycling challenges, this work explores the synergistic recycling of soda-lime glass in cementitious systems. The primary objectives were to evaluate the influence of glass powder on hydration kinetics, mechanical properties, and microstructure, while developing predictive models for strength behavior. Results demonstrate that glass powder addition (5–35% by weight) enhances workability and extends setting times, with optimal mechanical performance observed at 5–20% substitution. The pozzolanic reactivity of glass powder improved compressive strength by up to 23.6% (56 days) and flexural strength by 18.4% (300 days) compared to plain cement mortars. Microstructural analyses confirmed the formation of secondary calcium silicate hydrates (C-S-H) and reduced porosity in modified pastes. Statistical modeling yielded high-accuracy predictive equations (R2 ≥ 0.92) for strength properties as functions of composition, curing time, and microstructure. These findings highlight the dual benefit of glass powder in mitigating waste and enhancing cement performance, supporting its viability as a sustainable construction material.
Safoura Tanbakouei, Rui-Lin Cheng, Binlong Ye
et al.
The CM chondrites are characterized as primary accretionary rocks which originate from primitive water-rich asteroids formed during the early Solar System. Here, we study the mineralogy and organic characteristics of right CM and one ungrouped chondrite to better understand their alteration history; Queen Alexandra Range 93005 (QUE 93005), Murchison, LaPaz Icefield 02333 (LAP 02333), Miller Range (MIL 13005), Mackay Glacier 05231 (MCY 05231), Northwest Africa 8534 (NWA 8534), Northwest Africa 3340 (NWA 3340), Yamato 86695 (Y-86695), and the ungrouped carbonaceous chondrite Belgica 7904 (B-7904). Raman spectroscopy has been employed to detect the presence of organic carbon in the samples, specifically through the G band at approximately 1580 cm-1 and D band at around 1350 cm-1. The properties of organic matter in meteorites serve as valuable indicators for characterizing the structure and crystallinity of carbonaceous materials and estimating their thermal metamorphism degree. The R1 parameter, defined as the peak height ratio of the D and G bands, provides a quantifiable measure of this structural organization. Raman spectra are used to show the general mineralogy, thermal history and heating stage of CM and ungrouped chondrites. X-ray diffraction patterns further indicate the mineralogical compositions of the samples. Visible to near-infrared (VNIR) and attenuated total reflection (ATR) reflectance spectra illustrate the trends related to their mineralogy and furthermore infer aqueous alteration, thermal history of CM carbonaceous chondrites, formation and evolution of their parent bodies.
Samuel D. Crossley, Colby L. Donner, Josh Magnus
et al.
We greatly expand the application of multiphoton microscopy to geological investigations by using a tightly focused femtosecond laser beam to excite fluorescent emissions among minimally prepared rock and mineral samples. This new finding provides a tool for spatially resolving UV-visible fluorescent sources in minerals. Using a unique combination of harmonic generation and fluorescence, we explore applications to mineralogical investigations of terrestrial rocks and astromaterials. We report first-order demonstrations for 3D imaging of fluid inclusions in minerals and radiation-induced luminescence in meteorites. Nonlinear optical mineralogy, enabled by multiphoton microscopy, provides unique insights in mineralogic samples and holds the potential to revolutionize the analysis of geologic and astromaterials samples in the coming years.
The Carboniferous-Permian coal measure strata in the Qinshui Basin exhibit highly lithium (Li) enrichment, with substantial exploitation potential. To further explore the enrichment mechanism of lithium in coal measure strata, the No. 15 coal of the Taiyuan Formation from the Gaoping mine is taken as the research object, and its mineralogical and geochemistry characteristics are evaluated using optical microscopy, X-ray diffraction, scanning electron microscopy, inductively coupled plasma mass spectrometry, X-ray fluorescence, and infrared spectral. The results show that the No. 15 coal is semi-anthracite coal with low moisture, low ash, low volatility, and high sulfur. Organic macerals are primarily vitrinite, followed by inertinite, and liptinite is rare; the inorganic macerals (ash) are dominated by clay minerals (predominantly kaolinite, cookeite, illite, and NH<sub>4</sub>-illite), calcite, pyrite, quartz, siderite, gypsum, and zircon. The average Li content in the coal is 66.59 μg/g, with higher content in the coal parting (566.00 μg/g) and floor (396.00 μg/g). Lithium in coal occurs primarily in kaolinite, illite, cookeite, and is closely related to titanium-bearing minerals. In addition, Li in organic maceral may occur in liptinite. The No. 15 coal was formed in the coastal depositional system, and the deposition palaeoenvironment is primarily a wet–shallow water covered environment in open swamp facies; the plant tissue preservation index is poor, and aquatic or herbaceous plants dominate the plant type. The reducing environment with more terrestrial detritus, an arid climate, and strong hydrodynamic effects is favorable for Li enrichment in coal. The results have important theoretical significance for exploring the enrichment and metallogenic mechanisms of Li in coal.
As a result of studying new ore samples from the Ukonik deposit, new data on the composition of pyrite was obtained, the composition of electrum was studied for the first time and plattnerite, hessite, jalpaite, silver-bearing covellite and greigite were identified, and the sequence of their formation was determined. It was determined that a significant part of the pyrite (48%) contains arsenic in the amount of 0.82 - 2.28 wt.%, which is typical for the upper parts of many gold deposits. This is also evidenced by an insignificant admixture of cobalt (0.5 – 0.55 wt.%) in only two samples. The bulk of gold in the ore is associated with electrum, containing from 41.26 to 63.11 wt.% gold. Mercury electrum was found to contain up to 3.29 wt.% Hg. For the first time in Transbaikalia, plattnerite, which usually belongs to the minerals of the supergenesis zone, has been identified and studied in the ores of the upper part of the Ukonik deposit. In this case, it is one of the last products of the evolution of the hydrothermal mineral-forming system, preceding the formation of dolomite. Hessite containing variable amounts of copper, lead and antimony was discovered for the first time. This hessite-like telluride is of interest for further research.
This article presents tangible geological evidence for coexistence of porphyry copper and epithermal gold systems within single polygenic deposits and provides a paleothermophysical model for their origins. Brief metallogenic analysis of the Southern Caucasus and Northern Iran has shown that such deposits are confined to long-living calc-alkaline island arcs and were formed during their orogenesis. Examples of complex Sonajil (Iran), Gharta, and Merisi (Georgia) deposits are considered. Investigation has shown that for combined porphyry and epithermal ore formation some preconditions are suggested to exist: (i) Source of anomalous energy, which exceeds thermodynamics of the enclosing environment; (ii) Existence of temperature gradient, which determines conventional flows of fluids composed of endogenous and meteoric constituents (proven by rhythmical zoning of ore lodes); (iii) Stability of such conditions for a period of sulfide ore formation. However, such a process of sulfide ore formation cannot explain formation of high sulfidation gold deposits. Mass precipitation of free gold requires phreatic collapse in the ore conduit channel already after formation of hydrothermally altered rocks, and this event results in creation of either hydrothermal breccias, often with jigsaw-fit texture or brecciated vuggy silica where host rocks and hydrothermally altered rocks are cemented by a gold-bearing quartz matrix.
Computed tomography (CT) can capture volumes large enough to measure a statistically meaningful number of micron-sized particles with a sufficiently good resolution to allow for the analysis of individual particles. However, the development of methods to efficiently investigate such image data and interpretably model the observed particle features is still an active field of research. When image data of particles exhibiting a wide range of shapes and sizes is considered, traditional image segmentation methods, such as the classic watershed algorithm, struggle to recognize particles with satisfying accuracy. Thus, more advanced methods of machine learning must be utilized for image segmentation to improve the validity of subsequent analyzes. Moreover, CT data does not include information about the mineralogical composition of particles and, therefore, additional SEM-EDS image data has to be acquired. In this paper, micro-CT image data of a particle system mostly consisting of zinnwaldite-quartz composites is considered. First, an image segmentation method is applied which uses deep convolutional neural networks, in particular an adaptation of the U-net architecture. This has the advantage of requiring less hand-labeling than other machine learning methods, while also being more flexible with the possibility of transfer learning. Then, fully parameterized models based on vine copulas are designed to determine multivariate probability distributions of descriptor vectors for the size, shape, texture and composition of particles -- allowing for the estimation and interpretable characterization of interdependencies between particle descriptors. For model fitting, the segmented three-dimensional CT data and co-registered two-dimensional SEM-EDS data are used.
Lucille Le Corre, Juan A. Sanchez, Vishnu Reddy
et al.
Ground-based characterization of spacecraft targets prior to mission operations is critical to properly plan and execute measurements. Understanding surface properties, like mineralogical composition and phase curves (expected brightness at different viewing geometries) informs data acquisition during the flybys. Binary near-Earth asteroids (NEA) (35107) 1991 VH and (175706) 1996 FG3 were selected as potential targets of the National Aeronautics and Space Administration's (NASA) dual spacecraft Janus mission. We observed 1991 VH using the 3-m NASA Infrared Telescope Facility (IRTF) on Mauna Kea, Hawaii, on July 26, 2008. 1996 FG3 was observed with the IRTF for seven nights during the spring of 2022. Compositional analysis of 1991 VH revealed that this NEA is classified as an Sq-type in the Bus-DeMeo taxonomy classification, with a composition consistent with LL ordinary chondrites. Using thermal modeling, we computed the thermally corrected spectra for 1996 FG3 and the corresponding best fit albedo of about 2-3% for the best spectra averaged for each night. Our spectral analysis indicates that this NEA is a Ch-type. The best possible meteorite analogs for 1996 FG3, based on curve matching, are two carbonaceous chondrites, Y-86789 and Murchison. No rotational variation was detected in the spectra of 1996 FG3, which means there may not be any heterogeneities on the surface of the primary. However, a clear phase reddening effect was observed in our data, confirming findings from previous ground-based studies.
Muhammad Zubair Khan, Oleg E. Peil, Apoorva Sharma
et al.
In the rapidly expanding field of two-dimensional materials, magnetic monolayers show great promise for the future applications in nanoelectronics, data storage, and sensing. The research in intrinsically magnetic two-dimensional materials mainly focuses on synthetic iodide and telluride based compounds, which inherently suffer from the lack of ambient stability. So far, naturally occurring layered magnetic materials have been vastly overlooked. These minerals offer a unique opportunity to explore air-stable complex layered systems with high concentration of local moment bearing ions. We demonstrate magnetic ordering in iron-rich two-dimensional phyllosilicates, focusing on mineral species of minnesotaite, annite, and biotite. These are naturally occurring van der Waals magnetic materials which integrate local moment baring ions of iron via magnesium/aluminium substitution in their octahedral sites. Due to self-inherent capping by silicate/aluminate tetrahedral groups, ultra-thin layers are air-stable. Chemical characterization, quantitative elemental analysis, and iron oxidation states were determined via Raman spectroscopy, wavelength disperse X-ray spectroscopy, X-ray absorption spectroscopy, and X-ray photoelectron spectroscopy. Superconducting quantum interference device magnetometry measurements were performed to examine the magnetic ordering. These layered materials exhibit paramagnetic or superparamagnetic characteristics at room temperature. At low temperature ferrimagnetic or antiferromagnetic ordering occurs, with the critical ordering temperature of 38.7 K for minnesotaite, 36.1 K for annite, and 4.9 K for biotite. In-field magnetic force microscopy on iron bearing phyllosilicates confirmed the paramagnetic response at room temperature, present down to monolayers.
Geochemical data are compositional in nature and are subject to the problems typically associated with data that are restricted to the real non-negative number space with constant-sum constraint, that is, the simplex. Geochemistry can be considered a proxy for mineralogy, comprised of atomically ordered structures that define the placement and abundance of elements in the mineral lattice structure. Based on the innovative contributions of John Aitchison, who introduced the logratio transformation into compositional data analysis, this contribution provides a systematic workflow for assessing geochemical data in a simple and efficient way, such that significant geochemical (mineralogical) processes can be recognized and validated. This workflow, called GeoCoDA and presented here in the form of a tutorial, enables the recognition of processes from which models can be constructed based on the associations of elements that reflect mineralogy. Both the original compositional values and their transformation to logratios are considered. These models can reflect rock-forming processes, metamorphism, alteration and ore mineralization. Moreover, machine learning methods, both unsupervised and supervised, applied to an optimized set of subcompositions of the data, provide a systematic, accurate, efficient and defensible approach to geochemical data analysis. The workflow is illustrated on lithogeochemical data from exploration of the Star kimberlite, consisting of a series of eruptions with five recognized phases.