Sulfur (S) is a central element in global biogeochemical cycling and Earth's redox evolution. Minerals that contain S are an important record of local environmental conditions at the time of their formation based on chemical speciation and redox. However, the oxidation state of S for hundreds of different S-containing minerals and thousands of S-containing mineral localities is unknown, largely sulfides and sulfosalts, and the redox state alone does not fully capture mineral chemistry diversity, thus limiting understanding of S redox evolution. Here, we use mineral chemistry network analysis and the weighted Mineral Element Electronegativity Coefficient of Variation (wMEE(CV)) metric to investigate the element interactions and localities of S-containing minerals from the Mineral Evolution Database (MED) to infer the redox state of S in minerals where the redox state is unknown (S-U). Louvain community detection of the S mineral chemistry redox network reveals that there are three main network communities that are separated by redox state. The S6+ community includes minerals that contain the S6+ redox state and a small number of S4+ and S2+ minerals, the S2- community includes S2--containing minerals, and the S-U community includes minerals in which the redox state of S is unknown. The wMEE(CV) values of the S-U community closely overlap with the wMEE(CV) values of the S2- community, and do not overlap with the wMEE(CV) values of the S6+ community, indicating the S-U community minerals contain predominately reduced S. Assuming that S-U community minerals contain reduced S, as supported by their network chemical associations and wMEE(CV) values, then reduced S-containing minerals make up approximately 81 % of S-containing mineral localities in the S mineral chemistry network, even though the majority of all mineral localities (S-containing and non-S-containing) are oxygen (O)-containing minerals. Additionally, reduced S-containing minerals make up the majority (similar to 75 %) of all non-O containing mineral localities in the MED, representing the importance of reduced S as an electron source and substrate in the evolution of microbial metabolic networks. The range wMEE(CV) values of S6+ community minerals expands through time due primarily to formation of chemically diverse sulfate minerals, coinciding with crustal oxidation from the late Proterozoic to Phanerozoic and the expansion of the marine sulfate reservoir. The intersection of shared constituent elements among reduced and oxidized S in the mineral chemistry network represents redox convergence of weathered S in the geosphere that was crucial in the formation of natural resource deposits and the evolution of biogeochemical cycles.

Abstract Uranium (U) is an important global energy resource and a redox sensitive trace element that reflects changing environmental conditions and geochemical cycling. The redox evolution of U mineral chemistry can be interrogated to understand the formation and distribution of U deposits and the redox processes involved in U geochemistry throughout Earth history. In this study, geochemical modeling using thermodynamic data, and mineral chemistry network analysis are used to investigate U geochemistry and deposition through time. The number of U6+ mineral localities surpasses the number of U4+ mineral localities in the Paleoproterozoic. Moreover, the number of sedimentary U6+ mineral localities increases earlier in the Phanerozoic than the number of U4+ sedimentary mineral localities, likely due to the necessity of sufficient sedimentary organic matter to reduce U6+–U4+. Indeed, modeling calculations indicate that increased oxidative weathering due to surface oxygenation limited U4+ uraninite (UO2) formation from weathered granite and basalt. Louvain network community detection shows that U6+ forms minerals with many more shared elements and redox states than U4+. The range of weighted Mineral Element Electronegativity Coefficient of Variation (wMEECV) values of U6+ minerals increases through time, particularly during the Phanerozoic. Conversely, the range of wMEECV values of U4+ minerals is consistent through time due to the relative abundance of uraninite, coffinite, and brannerite. The late oxidation and formation of U6+ minerals compared to S6+ minerals illustrates the importance of the development of land plants, organic matter deposition, and redox‐controlled U deposition from ground water in continental sediments during this time‐period.

Characterizing the types of crystalline structures that form in different environments helps us to better interpret the geologic record and deepens our understanding of mineral stability. To this end, the Dolivo – Dobrovol’sky symmetry index provides a convenient way to quantify the statistical trends in the symmetry of minerals over time (Bermanec et al. 2022). Behavior of the Dolivo - Dobrovol’sky symmetry index was investigated for different paragenetic modes of minerals (Hazen and Morrison 2022). Two datasets were used and compared (code and datasets are available on https://github.com/NoaVidovic/pgm-mineral-pairs-pg). The first one used only minerals, and each mineral was considered just once. In contrast, in the mineral–paragenetic mode pair dataset, minerals were counted once for each of the paragenetic modes in which they occurred.The paragenetic mode dataset incorporates a number of properties associated with each of more than 60 modes of formation, including relative age and order of that mode’s first appearance, estimated minimum and maximum temperature and pressure of formation, and duration. Paragenetic mode order does not substantially affect the symmetry index of minerals. However, some trends are evident when inspecting the properties of given paragenetic modes. The symmetry indices show a strong correlation with the maximum temperature, maximum pressure, and minimum pressure of paragenetic modes they belong to (Hazen et al. 2022) with correlation coefficients of 69%, 84% and 95%, respectively when using the mineral dataset. These trends show that minerals formed at higher temperature display higher overall symmetry. Trends for pressure are enigmatic: correlations show that minerals formed at higher minimum pressure tend to favor lower symmetry, whereas minerals formed at higher maximum pressure tend to favor higher symmetry.When using the mineral–paragenetic mode dataset, the correlation coefficients are significantly lower at 42%, 30% and 89% for maximum temperature, maximum pressure, and minimum pressure, respectively. The lower correlation coefficients obtained using the mineral–paragenetic mode pairs might indicate that the paragenetic mode is not as important in terms of trends in symmetry as initially thought. On the other hand, considering a much higher correlation coefficient for the mineral dataset, perhaps there is a more dominant effect where certain P-T conditions tend to favor certain types of symmetry at equilibrium.

The mineral record contains chemical signatures that reflect the evolving redox conditions of Earth's crust, and reveal trends in the bioavailability of life's critical elements. In particular, shifting redox states of transition metal elements that are used as co-factors by enzymes across all domains of life can be tracked in preserved mineral chemistry. The transition metal iron (Fe) is one of the most abundant elements in Earth's core, mantle, and crust, and is commonly a major constituent of rock-forming minerals. Additionally, Fe is the most widely used metal in biology, and Earth's redox history has profoundly impacted the chemical speciation and availability of Fe in aqueous systems. The diverse mineral chemistry of Fe can therefore reveal new insights into the redox evolution of Earth's crust and subsequent biological impacts. Here, we apply a new mineral chemistry network analysis platform, dragon, to investigate the mineral chemistry of iron (Fe) over geologic-time. We present bipartite network graphs of iron minerals linked to their constituent elements or ions for several geological time intervals. These graphs illustrate the increasing importance of oxygen (O) abundance in the atmosphere from the Paleoarchean to the Mesoproterozoic in regard to the the emergence of new Fe minerals, as well as the influence of free O on trends in element electronegativity in mineral formation and electron transfer processes. The proportion of oxygen containing Fe minerals had the sharpest increase during the time periods of the Kenorland and Columbia supercontinent assembly events. Indeed, the rise of O is associated with O becoming more centralized in the network as well as with an increase through time in the number of Fe minerals containing combinations of high and low electronegativity elements. The importance of oxygen in the expansion of Fe mineral chemical diversity, and its influence on the bioavailability of Fe in the environment, is illustrated clearly in the Fe mineral chemistry network.

Analysis of manganese mineral occurrences and valence states demonstrate oxidation of Earth's crust through time. Changes in crustal redox state are critical to Earth's evolution, but few methods exist for evaluating spatially averaged crustal redox state through time. Manganese (Mn) is a redox-sensitive metal whose variable oxidation states and abundance in crustal minerals make it a useful tracer of crustal oxidation. We find that the average oxidation state of crustal Mn occurrences has risen in the last 1 billion years in response to atmospheric oxygenation following a 66 ± 1 million-year time lag. We interpret this lag as the average time necessary to equilibrate the shallow crust to atmospheric oxygen fugacity. This study employs large mineralogical databases to evaluate geochemical conditions through Earth's history, and we propose that this and other mineral data sets form an important class of proxies that constrain the evolving redox state of various Earth reservoirs.

Crystallographic data from 5289 IMA-approved mineral species in the RRUFF database were used to examine the distribution of species among the 32 crystallographic point groups. It is found that within each crystal system, minerals strongly prefer point groups with higher group orders. Within a crystal system, the abundance of minerals belonging to each point group approximately obeys a power law with respect to group order, the same mathematical formalism that describes objects with fractal geometry. In this framework, each crystal system has its own fractal dimension; crystal systems possessing threefold (or sixfold) symmetry elements (i.e., trigonal, hexagonal, isometric) have significantly lower fractal dimension (<2), while those with only one-, two-, or fourfold symmetry elements (triclinic, monoclinic, orthorhombic, tetragonal) have higher fractal dimension (>2). While higher symmetry is preferred within a crystal system, the opposite trend is observed when comparing between crystal systems, with more species preferring crystals systems with lower order symmetry elements than those with higher order symmetry elements at constant group order. The combination of these two competing trends leads to a complex distribution of minerals among the crystal systems, and to the monoclinic group 2/m, the orthorhombic group 2/m2/m2/m, and the triclinic group 1 being the three most popular point groups, respectively. The fractal behavior of symmetry distribution among minerals points toward universal scaling patterns not just in physical, geometric objects but also in the way that symmetry is incorporated into natural periodic structures.

Indicator minerals have special physical and chemical properties that can be analyzed to glean information concerning the composition of host rocks and formational (or altering) fluids. Clay, zeolite, and tourmaline mineral groups are all ubiquitous at the Earth’s surface and shallow crust and distributed through a wide variety of sedimentary, igneous, metamorphic, and hydrothermal systems. Traditional studies of indicator mineral-bearing deposits have provided a wealth of data that could be integral to discovering new insights into the formation and evolution of naturally occurring systems. This study evaluates the relationships that exist between different environmental indicator mineral groups through the implementation of machine learning algorithms and network diagrams. Mineral occurrence data for thousands of localities hosting clay, zeolite, and tourmaline minerals were retrieved from mineral databases. Clustering techniques (e.g., agglomerative hierarchical clustering and density based spatial clustering of applications with noise) combined with network analyses were used to analyze the compiled dataset in an effort to characterize and identify geological processes operating at different localities across the United States. Ultimately, this study evaluates the ability of machine learning algorithms to act as supplementary diagnostic and interpretive tools in geoscientific studies.

The flow of energy and elements between the geosphere and biosphere can be traced through the changing redox chemistry of Earth’s surface. Deep-time trends in the mineral record, including mineral age and elemental composition, reveal a dynamic history of changing redox states and chemical speciation. We present a user-friendly exploratory network analysis platform called dragon (Deep-time Redox Analysis of the Geobiology Ontology Network) to facilitate investigation of the expanding redox chemical network preserved in the mineral record throughout Earth’s history and beyond. The utility of dragon is demonstrated by showing that as oxygen became more central in the Fe mineral chemistry network, the number of combinations of high and low electronegativity elements increased in Fe minerals through time, thus illustrating the importance of oxygen in expanding the chemical diversity of Fe minerals and influencing the bioavailability of Fe in the environment. Dragon opens up many possibilities for the investigation chemical linkages between minerals and biology.

Abstract Minerals contain important clues to understanding the complex geologic history of Earth and other planetary bodies. Therefore, geologists have been collecting mineral samples and compiling data about these samples for centuries. These data have been used to better understand the movement of continental plates, the oxidation of Earth's atmosphere and the water regime of ancient martian landscapes. Datasets found at ‘RRUFF.info/Evolution’ and ‘mindat.org’ have documented a wealth of mineral occurrences around the world. One of the main goals in geoinformatics has been to facilitate discovery by creating and merging datasets from various scientific fields and using statistical methods and visualization tools to inspire and test hypotheses applicable to modelling Earth's past environments. To help achieve this goal, we have compiled physical, chemical and geological properties of minerals and linked them to the above‐mentioned mineral occurrence datasets. As a part of the Deep Time Data Infrastructure, funded by the W.M. Keck Foundation, with significant support from the Deep Carbon Observatory (DCO) and the A.P. Sloan Foundation, GEMI (‘Global Earth Mineral Inventory’) was developed from the need of researchers to have all of the required mineral data visible in a single portal, connected by a robust, yet easy to understand schema. Our data legacy integrates these resources into a digestible format for exploration and analysis and has allowed researchers to gain valuable insights from mineralogical data. GEMI can be considered a network, with every node representing some feature of the datasets, for example, a node can represent geological parameters like colour, hardness or lustre. Exploring subnetworks gives the researcher a specific view of the data required for the task at hand. GEMI is accessible through the DCO Data Portal (https://dx.deepcarbon.net/11121/6200‐6954‐6634‐8243‐CC). We describe our efforts in compiling GEMI, the Data Policies for usage and sharing, and the evaluation metrics for this data legacy.

18 Crystallographic data from 5289 IMA-approved mineral species in the RRUFF database 19 were used to examine the distribution of species among the 32 crystallographic point groups. It is 20 found that within each crystal system, minerals strongly prefer point groups with higher group 21 orders. Within a crystal system, the abundance of minerals belonging to each point group 22 approximately obeys a power law with respect to group order, the same mathematical formalism 23 that describes objects with fractal geometry. In this framework, each crystal system has its own 24 fractal dimension; crystal systems possessing 3 (or 6)-fold symmetry elements (i.e., trigonal, 25 hexagonal, isometric) have significantly lower fractal dimension (< 2), while those with only 1, 2, 26 or 4-fold symmetry elements (triclinic, monoclinic, orthorhombic, tetragonal) have higher fractal 27 dimension (> 2). While higher symmetry is preferred within a crystal system, the opposite trend is 28 observed when comparing between crystal systems, with more species preferring crystals systems 29 with lower order symmetry elements than those with higher order symmetry elements at constant 30 group order. The combination of these two competing trends leads to a complex distribution of 31 minerals among the crystal systems, and to the monoclinic group 2/m, the orthorhombic group 32 2/m2/m2/m, and the triclinic group ̅1 being the three most popular point groups, respectively. The 33 fractal behavior of symmetry distribution among minerals points toward universal scaling patterns 34 not just in physical, geometric objects, but also in the way that symmetry is incorporated into 35 natural periodic structures. 36