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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Mine Tailings Valorization by Electrochemically Stimulated Mineralization from Mildly Acidic Conditions

This study presents a high-efficiency electrochemical process for the mineralization of calcium carbonate (CaCO 3 ) from mildly acidic mine tailing supernatant water. Electrochemical pH control was used to promote carbonate speciation and precipitation from CO 2 -saturated solutions, achieving >1 mol CaCO 3 precipitated per mol e - at applied potentials between -1.4 and -1.6 V vs Ag/AgCl. Product morphology and polymorph selectivity were tunable via applied potential, yielding calcite and vaterite phases. Experiments using real mine tailings water confirmed selective calcite precipitation, despite the presence of sulfate and other trace elements. These results highlight a viable route for coupling CO 2 utilization with mine tailings valorization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Lime slurry treatment of soils developing on abandoned coal mine spoil: Linking contaminant transport from the micrometer to pedon-scale

Historical and abandoned coal mine spoil continues to generate acid- and metal(loid)-rich porewaters and represents a geographically large and diffuse non-point source of contamination to local watersheds. A potentially inexpensive approach to treat these materials and soils developing on them is through the application of lime slurries, to neutralize acidity and encourage the (co)precipitation of metal(loids) with Fe(III)-(oxy)hydroxides, and potentially other metal-oxides and/or Ca-bearing phases. Here, the efficacy of this approach was evaluated through parallel field application and laboratory-based flow-through column experiments. The field site is Huff Run sub-watershed 25 located in Tuscarawas County, Ohio and was chosen in part because it was previously classified as one of the most highly AMD-impacted sub-watersheds in the region. Two locations with historical spoil were chosen and suction lysimeters were installed at 25 and 75 cm depth to monitor porewater composition on two sides at the base of each pile. Half of each slope received seven lime slurry treatments from June through October of 2017. A suite of aqueous (ICP-OES, IC, and TOC-L) and solid phase geochemical and mineralogical approaches (quantitative SEM-EDS and synchrotron μ-XRF) were used to determine how composition, texture, morphology, and spatial distribution of mineral coatings differ in pre- and post-lime treated soils, and how that impacts the distribution and transport of trace metal(loid)s. Mine spoil porewater at site 1 was slightly less alkaline (pH ranging from 7.04 to 7.37) than at site 2 (ranging from 7.55 to 7.71), and average electrical conductivity values at site 1 (316–405 μS cm —1 ) were slightly lower than at site 2 (358–464 μS cm —1 ), although differences between the sites were not significant. Porewater pH and electrical conductivity in all lysimeters decreased over the course of the field season but there was no obvious response to lime treatment at either site or any depth. At site 1, both treatment and depth were significant factors affecting Ca, K, Ni, SO 4 2— , and DOC concentrations while only treatment effects were significant for dissolved Al and Cu (p < 0.05). For all soils, there were no trends in metal concentration observed over time although DOC and SO 4 2— decreased over the field season. Pedon-scale changes in metal porewater concentrations in response to treatment were linked to micrometer-scale changes in mineral surface coatings; specifically, higher concentrations of Ca, Fe, Mn, and Zn were observed in the coatings and no changes were observed in Fe redox speciation, whereas total S decreased likely due to oxidation of S in coal fragments. In contrast to the field experiment, the column experiments exhibited a much greater response in effluent composition with respect to lime treatment. The untreated columns had approximately an order of magnitude more H + leached over the course of the experiment (p < 0.001) and resulted in greater Ca, Al, Cu, and DIC leached and less Mn, Zn, and SO 4 2— . Soils treated with the lime slurry in the column experiments exhibited larger and thicker secondary Fe-coatings, including the addition of Fe-sulfates. Despite clear trends in the laboratory-based column experiment where the lime-to-soil ratio was higher, the effects were either muted or undetected in the field pilot project, suggesting that a higher application rate of lime in the field is needed to achieve a similar effect. This work provides evidence that a less alkaline lime slurry could be a practical and inexpensive method of treating coal mine spoil-impacted soils and represents an important step in linking laboratory-based remediation studies to implemented field-based studies.

58 GEOSCIENCES↗
DOE OSTI2023

Upcycling and urban mining for nanomaterial synthesis

Responsible processing of complex waste streams, especially through resource recovery and upgrading, is essential to lessen the environmental and societal impacts of materials production and disposal. Upcycling waste into materials that have higher value than their original form, and urban mining, the recovery of metals from electronic waste, are two recent strategies in waste management. Sustainable cradle-to-grave manufacturing means recovering resources that would otherwise contaminate the planet. Here, we discuss upcycling of plastic, rubber, and related carbon waste streams into graphene, as well as the recovery of precious metals and rare earth elements, while removing toxic heavy metals, all using flash Joule heating. Furthermore, this article provides a brief overview of the current state of upcycling and urban mining as it applies to materials conversion, recovery, or nanomaterial synthesis, with a concluding perspective highlighting the considerations, opportunities, and challenges that accompany upcycling and urban mining research.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Process design for recovering rare-earth elements from mine tailings with low rare-earth concentrations via sequential leaching and solvent extraction

Rare earth elements (REEs) are essential for advanced technologies and yet face significant supply chain risks due to their concentrated global production and limited domestic availability. Addressing this challenge requires efficient processes capable of upgrading low-grade secondary resources such as mine tailings. In this study, we developed a novel separation flowsheet that integrates sequential leaching and 2-stage solvent extraction (SX) processes to recover high-purity heavy REEs (HREEs) and light REEs (LREEs) from a simulated mine-tailing concentrate containing 2.4 wt% total REEs (TREEs; 0.6 wt% LREEs and 1.8 wt% HREEs). Sequential leaching with controlled pH adjustment selectively precipitated REEs while retaining the large amount of impurities in the solution, producing an REE-enriched leachate by following leaching processes with roughly twice the REE concentration and half the impurity concentration compared to that of single-step leaching. The optimized SX flowsheet employed Cyanex 572 to extract HREEs and Fe over LREEs, followed by Fe removal using tributyl phosphate (TBP), while the raffinate stream was processed by SX with di(2-ethylhexyl)phosphoric acid (D2EHPA) to recover LREEs under optimized conditions balancing both extraction efficiency and purity. Although increased extractant availability in the organic phase improved LREE recovery, it also increased co-extraction of Ca, underscoring trade-offs in process optimization. Both HREE- and LREE-rich solutions were subsequently precipitated into solid products via oxalate precipitation, resulting in high-purity REE solids containing ∼92.0 wt% HREEs (∼95.7 wt% TREEs) and ∼92.8 wt% LREEs (∼94.0 wt% TREEs). In conclusion, this proof-of-concept study using simulated mine tailings demonstrates a promising approach for upgrading low-grade REE resources, while highlighting the need for future validation with real materials.

Mine tailings↗
DOE OSTI2021

Urban mining by flash Joule heating

Abstract Precious metal recovery from electronic waste, termed urban mining, is important for a circular economy. Present methods for urban mining, mainly smelting and leaching, suffer from lengthy purification processes and negative environmental impacts. Here, a solvent-free and sustainable process by flash Joule heating is disclosed to recover precious metals and remove hazardous heavy metals in electronic waste within one second. The sample temperature ramps to ~3400 K in milliseconds by the ultrafast electrical thermal process. Such a high temperature enables the evaporative separation of precious metals from the supporting matrices, with the recovery yields >80% for Rh, Pd, Ag, and >60% for Au. The heavy metals in electronic waste, some of which are highly toxic including Cr, As, Cd, Hg, and Pb, are also removed, leaving a final waste with minimal metal content, acceptable even for agriculture soil levels. Urban mining by flash Joule heating would be 80× to 500× less energy consumptive than using traditional smelting furnaces for metal-component recovery and more environmentally friendly.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

NEWTS Coal Mine Drainage Dataset from Cravotta Brady (2015)

Data from Cravotta, Brady, "Priority pollutants and associated constituents in untreated and treated discharges from coal mining or processing facilities in Pennsylvania, USA". Applied Geochemistry, 2015. https://doi.org/10.1016/j.apgeochem.2015.03.001 Dataset includes information on water quality composition including inorganic compounds from untreated and treated streams of coal-mine discharge from coal mining and coal processing locations. Data is provided in the original version as well as in a summarized version for easy input into aqueous chemistry modeling software.

Aqueous Chemistry↗
DOE OSTI2023

Advanced Processing of Rare Earth Elements and Critical Minerals from Acid Mine Drainage Feedstocks

Ongoing work by the project team identified a process for extracting rare earths and critical mineral (REE/CM) concentrates from acid mine drainage from coal mines, a major stream pollutant. The process removes harmful metals and separates REE/CM into economically attractive concentrates. This project explored the processing of those concentrates into individually separated, high purity metals, suitable for domestic manufacturers. The team brought unique experience in working with AMD-based feedstocks since the inception of USDOE’s coal-based REE/CM program in 2016. The project team has pioneered the recovery of rare earth/critical minerals (REE/CM) from acid mine drainage (AMD). This environmentally beneficial strategy will incentivize AMD treatment while recovering materials critical to the Nation’s defense and advanced manufacturing industries. In addition, the project will investigate the co-production of five high purity CMs from AMD, namely Co, Mn, Li, Cr, Ge. This team’s upstream and midstream recovery and processing technology has been demonstrated at the continuous, small scale pilot scale. In conjunction with the West Virginia Department of Environmental Protection, the team is constructing a full-scale, integrated, 500 gpm AMD treatment plant coupled with an REE/CM facility that will produce 21 tons REE/CM per year. Commissioning is scheduled for September 2021. This will provide feedstock for the team’s proprietary downstream processes that met the project objective: production of individually separated, high purity (ISHP) REE/CM oxides and their further processing to elemental metals (REM). To facilitate entry into the U.S. market, we have teamed up with companies that would use our products to strengthen their domestic supply chains and grow REE/CM based manufacturing in the U.S. They include Rockwell Automation, Rivian, Endress+Hauser, Inc., Northrop Grumman and Hela Novel Metals.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Development of Leaching Processes for the Recovery of Rare Earth Elements from Acid Mine Drainage Precipitates

Acid mine drainage (AMD) has been a challenge for mine operators to address and has had significant environmental impacts when there is a failure to address it. Fortunately, there is a regulation in the US that requires the treatment of AMD before water can be discharged into the environment. AMD is generated when sulfide minerals are exposed to water and air from mining. The acidic water then leaches metals from the surrounding rock, creating the potential for environmental contamination of this acidic water containing dissolved metals. AMD can contain high concentrations of metals like iron, aluminum, and manganese and also have been shown to contain trace concentrations of critical minerals, including rare earth elements (REEs). This environmental waste stream is now being researched as a potential source for REEs. There is a patented process for processing and extracting REEs from AMD which produces rare earth oxide preconcentrate (REOP) from AMD treatment precipitates and a final stage mixed rare earth oxide (MREO) product. This body of research examines a selective leaching process for each of these products and determines the activation energy associated with the leaching processes. Acid leaching with HCl was examined to selectively leach REEs from REOP while contaminant metals remained in the solid residue. The maximum leaching recovery of the REEs from the REOP was approximately 90% and an activation energy of 6.4 kJ/mol at pH 3.0. Ammonium chloride leaching was examined to selectively remove contaminant metals from a MREO product. The ammonium chloride process successfully leached major contaminant metals in excess of 85% recovery and had a maximum activation energy of 40.0 kJ/mol.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Mobilizing mine lands for biobased decarbonization strategies

Over 163 000 ha of mine lands in Pennsylvania (PA) have the potential to produce willow as a feedstock for renewable energy generation. Each year these lands could produce between 454 000 and 907 000 dry Mg of willow, which can be a feedstock for bioenergy (i.e., biopower) with carbon capture and sequestration (BECCS) or sustainable aviation fuel (SAF) production. We used a spatially explicit model to explore cost-minimized allocation of willow biomass from abandoned mine lands (AML) to be used for BECCS or SAF production and to abate carbon dioxide. The results suggest that between 454 000 and 907 000 dry Mg of biomass can be produced on AML in PA at costs from $94 to $250 per dry Mg. This AML willow biomass could be combined with other available biomass and aggregated to ten facilities to produce 17.9 TWh of power; alternatively, it could produce 958 million liters of jet fuel, 638 million liters of renewable diesel, and 1.289 billion liters of naphtha, along with 0.735 TWh of electricity. From this analysis, in PA, under the BECCS pathway, up to 36 million Mg per year of CO2 could be abated at costs of up to $134 per Mg; under the SAF pathway, up to 17.5 million Mg per year of CO2 could be abated at costs up to $150 per Mg of CO2. The use of mine land willow as a supplemental feedstock for SAF and BECCS would need strong incentive programs if costs of production are to be comparable with production on agricultural land.

Wahlstrom, Mallory [Pennsylvania State University]↗
DOE OSTI2024

The Data Mine model for accessible partnerships in data science

Abstract The Data Mine at Purdue University is a pioneering experiential learning community for undergraduate and graduate students of any background to learn data science. The first data‐intensive experience embedded in a large learning community, The Data Mine had nearly 1300 students in academic year (AY) 2022–2023 and nearly 1700 students for AY 2023–2024. The Data Mine embodies data‐infused education, research, and collaboration. Students learn Python, R, SQL, and shell‐scripting, while working on weekly projects within a high‐performance computing (HPC) cluster. In the Corporate Partners cohort, students work on teams of 5–15 students, led by a paid student team leader. Each cohort follows an Agile approach, working on data‐intensive projects provided by industry partners and mentored by company employees. Students develop professional and data skills throughout the academic year, from August through April. Many students return in subsequent years to the program, increasing their tenure with a Corporate Partner. Student teams are inherently interdisciplinary; students from 133 different majors are involved in the program, ranging from new incoming students through PhD level students. These interdisciplinary teams of students bring new perspectives to challenging problems in which data science is a key part of the solution. The interdisciplinary teams foster an environment of synthesis with ideas and solutions. Students come together with different life experiences, different levels of technical skill, but also varying ways they navigate paths to solutions because of the variety of majors represented, resulting in a more creative and robust solution than a traditional data science program. This article is categorized under: Applications of Computational Statistics > Education in Computational Statistics

Betz, Margaret A.↗
DOE OSTI2021

Chemical-damage MINE: A database of curated and predicted spontaneous metabolic reactions

Spontaneous reactions between metabolites are often neglected in favor of emphasizing enzyme-catalyzed chemistry because spontaneous reaction rates are assumed to be insignificant under physiological conditions. However, synthetic biology and engineering efforts can raise natural metabolites' levels or introduce unnatural ones, so that previously innocuous or nonexistent spontaneous reactions become an issue. Problems arise when spontaneous reaction rates exceed the capacity of a platform organism to dispose of toxic or chemically active reaction products. While various reliable sources list competing or toxic enzymatic pathways' side-reactions, no corresponding compilation of spontaneous side-reactions exists, nor is it possible to predict their occurrence. We addressed this deficiency by creating the Chemical Damage (CD)-MINE resource. First, we used literature data to construct a comprehensive database of metabolite reactions that occur spontaneously in physiological conditions. We then leveraged this data to construct 148 reaction rules describing the known spontaneous chemistry in a substrate-generic way. We applied these rules to all compounds in the ModelSEED database, predicting 180,891 spontaneous reactions. The resulting (CD)-MINE is available at https://minedatabase.mcs.anl. gov/cdmine/#/home and through developer tools. We also demonstrate how damage-prone intermediates and end products are widely distributed among metabolic pathways, and how predicting spontaneous chemical damage helps rationalize toxicity and carbon loss using examples from published pathways to commercial products. We explain how analyzing damage-prone areas in metabolism helps design effective engineering strategies. Finally, we use the CD-MINE toolset to predict the formation of the novel damage product N-carbamoyl proline, and present mass spectrometric evidence for its presence in Escherichia coli.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A data mining approach to investigate food groups related to incidence of bladder cancer in the BLadder cancer Epidemiology and Nutritional Determinants International Study

Abstract At present, analysis of diet and bladder cancer (BC) is mostly based on the intake of individual foods. The examination of food combinations provides a scope to deal with the complexity and unpredictability of the diet and aims to overcome the limitations of the study of nutrients and foods in isolation. This article aims to demonstrate the usability of supervised data mining methods to extract the food groups related to BC. In order to derive key food groups associated with BC risk, we applied the data mining technique C5.0 with 10-fold cross-validation in the BLadder cancer Epidemiology and Nutritional Determinants study, including data from eighteen case–control and one nested case–cohort study, compromising 8320 BC cases out of 31 551 participants. Dietary data, on the eleven main food groups of the Eurocode 2 Core classification codebook, and relevant non-diet data (i.e. sex, age and smoking status) were available. Primarily, five key food groups were extracted; in order of importance, beverages (non-milk); grains and grain products; vegetables and vegetable products; fats, oils and their products; meats and meat products were associated with BC risk. Since these food groups are corresponded with previously proposed BC-related dietary factors, data mining seems to be a promising technique in the field of nutritional epidemiology and deserves further examination.

Nutrition & Dietetics↗
DOE OSTI2022

Molecular speciation controls arsenic and lead bioaccessibility in fugitive dusts from sulfidic mine tailings

Communities nearby mine wastes in arid and semi-arid regions are potentially exposed to high concentrations of toxic metal(loid)s from fugitive dusts deriving from impoundments. To assess the relation between potentially lofted particles and human health risk, we studied the relationship between pharmacokinetic bioaccessibility and metal(loid) molecular speciation for mine tailings dust particulate matter (PM), with elevated levels of arsenic and lead (up to 59 and 34 mmol kg -1 , respectively), by coupling in vitro bioassay (IVBA) with X-ray absorption spectroscopy (XAS). Mine tailing efflorescent salts (PM ES ) and PM from the surface crust (0–1 cm, PM SC ) and near surface (0–25 cm) were isolated to <10 μm and <150 μm effective spherical diameter (PM 10 and PM 150 ) and reacted with synthetic gastric and lung fluid for 30 s to 100 h to investigate toxic metal(loid) release kinetics. Bioaccessible (BAc) fractions of arsenic and lead were about 10 and 100 times greater in gastric than in lung fluid simulant, respectively, and 10–100% of the maximum gastric BAc from PM 10 and PM 150 occurred within 30 s, with parabolic dissolution of fine, highly-reactive particles followed by slower release from less soluble sources. Evaporite salts were almost completely solubilized in gastric-fluid simulants. Arsenate within jarosite and sorbed to ferrihydrite, and lead from anglesite, were identified by XAS as the principal contaminant sources in the near surface tailings. In the synthetic lung fluid, arsenic was released continuously to 100 h, suggesting that residence time in vivo must be considered for risk determination. Analysis of pre- and post-IVBA PM indicated the release of arsenic in lung fluid was principally from arsenic-substituted jarosite, whereas in synthetic gastric fluid arsenic complexed on ferrihydrite surfaces was preferentially released and subsequently repartitioned to jarosite-like coordination at extended exposures. Lead dissolved at 30 s was subsequently repartitioned back to the solid phase as pyromorphite in phosphate rich lung fluid. The bioaccessibility of lead in surface tailings PM was limited due to robust sequestration in plumbojarosite. Kinetic release of toxic elements in both synthetic biofluids indicated that a single IVBA interval may not adequately describe release dynamics.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2026

T-FSM: A Scalable Distributed Task-Based System for Frequent Subgraph Pattern Mining from a Big Graph

Finding frequent subgraph patterns in a big graph is an important problem with many applications such as classifying chemical compounds and building indexes to speed up graph queries. Since this problem is NP-hard, some recent parallel and distributed systems have been developed to accelerate the mining. However, they often have a huge memory cost, very long running time, suboptimal load balancing, poor scale-out capability, and possibly inaccurate results. In this article, we propose an efficient system called T-FSM for parallel mining of frequent subgraph patterns in a big graph. T-FSM supports a new anti-monotonic frequentness measure called Fraction-Score, which is more accurate than the widely used MNI measure. The execution engine of T-FSM supports both intra-machine parallelism and inter-machine parallelism. For intra-machine parallelism, T-FSM adopts a novel task-based execution model to ensure high multithreading concurrency, bounded memory consumption, and effective load balancing. For inter-machine parallelism, T-FSM ensures good scale-out performance with a lightweight pattern rebalancing approach that reduces workload skewness of pattern evaluations among machines. To avoid recomputing the contexts for migrated patterns, we design a novel context cache table to support concurrent and asynchronous requesting and caching of remote context data, which can timely evict and garbage collect used pattern contexts that are no longer needed to keep memory consumption bounded. Extensive experiments show that T-FSM is orders of magnitude faster than existing state-of-the-art parallel systems (more than 10×, 51×, 131×, 55× speedup over ScaleMine, DistGraph, Pangolin and Peregrine, respectively) and distributed systems (more than 42× and 88× over ScaleMine and DistGraph, respectively) for frequent subgraph pattern mining, and it scales out satisfactorily to 512 CPU cores on the Polaris supercomputer at Argonne National Laboratory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Applying Waveform Correlation and Waveform Template Metadata to Mining Blasts to Reduce Analyst Workload

Organizations that monitor for underground nuclear explosive tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high - quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. In this study we use waveform template event metadata to seek corroborating detections from multiple stations in the International Monitoring System of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization. We build upon events detected in a prior waveform correlation study of mining blasts in two geographic regions, Wyoming and Scandinavia. Using a set of expert analyst-reviewed waveform correlation events that were declared to be true positive detections, we explore criteria for choosing the waveform correlation detections that are most likely to lead to bulletin-worthy events and reduction of analyst effort.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Cradle-to-Gate Life Cycle Analysis Baseline for United States Coal Mining and Delivery

The goal of this study is to highlight the environmental impacts from upstream coal production to its delivery at a power plant. This study is meant to characterize different coal basins, coal types, and mine types used to produce electric power in the North American Electric Reliability Corporation (NERC) regions in the United States using a functional unit of 1 kg of coal. The boundary of this study includes underground or surface extraction, water use at the mine, ventilation, coal handling, coal cleaning, mine tailing disposal, and transportation via conveyer belt, truck, ocean vessel, barge, and train. See the following URLs for accompanying documents: NETL Coal Baseline Model - Transportation Inventories: https://www.netl.doe.gov/energy-analysis/details?id=27ea1ba4-6ea9-4ee5-8b32-d7fce7f4e1e0. NETL Coal Baseline Model - Basin Inventories: https://www.netl.doe.gov/energy-analysis/details?id=0f290eed-5e4b-4b5f-bec0-36b0ea89c6e5. NETL Coal Baseline Model - Excel file: https://www.netl.doe.gov/energy-analysis/details?id=0dc18730-4214-4878-8a0f-d1941c45123c. NETL Coal Baseline Model - Open LCA model: https://www.netl.doe.gov/energy-analysis/details?id=0c0dde04-0d3c-4c7f-bd33-2745e061b8e0.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Targeted Biomining and Machine Learning Approaches in Critical Minerals Revealed by a Biogeochemical Survey of a Coal Mine Drainage Remediation System

Abandoned coal mine drainage (AMD) remediation systems in Pennsylvania can concentrate critical minerals and materials (CMM) at levels comparable to mining-grade ores. Remediation systems have varying engineering features and are open to the environment, resulting in diverse microbial colonization and seasonal climate influences that may impact CMM speciation. The location of CMMs, the types of bacterial communities tolerant of these pollutant conditions, and the influence of localized climate on CMM rich remediation systems are not well characterized. Through a one-year spatiotemporal survey of biogeochemistry at a remediation system, we have initiated the process to address these questions. Rare Earth Elements (REE) ranged 180-1,200 ppm and greater than 1,500 bacterial ASVs were classified via 16S sequencing. Analyses indicate biogeochemical differences are heavily influenced by engineering features. Additionally, REE precipitants correlate strongly with the elements Al, Cu, Zn, Be, and U. Unearthing these trends has refined our line of inquiry to explore biological mining opportunities more closely with these metals. Furthermore, we created a Machine Learning Model for predicting AMD REE content, with 89% accuracy, using the data from this study and several others. Further training data is required to create a more reputable model. Recently, global research efforts have prioritized modeling work or the use of the few historical surveys to design experiments. Through our data, we challenge this approach, emphasizing the importance of expanding fundamental survey efforts prior to advanced product design and experimentation.

critical minerals↗
DOE OSTI2025

STILGAR: Subsurface Models for Graymont Pleasant Gap Mine

The detection, location, and monitoring of underground structures are of great importance to national and global security. Tunnels and voids generate seismic signatures detectable at the surface, but using non-invasive seismic data to image near-surface presents several challenges in real-world applications. In this report, we describe the use of a dense surface seismic deployment to generate subsurface models of the Graymont Pleasant Gap mine - a single-layer mine with a complex structure embedded in a high-velocity P-wave limestone bedrock. Our approach consists of three key methods. We use P-wave arrival times from local blast events to perform a tomography inversion with the tomoTD method, constructing a P-wave velocity model of the subsurface. We model the layer above the mine using Rayleigh wave ellipticity and inversion techniques. We leverage ongoing anthropogenic activities to identify and locate noise sources both on the surface and within the subsurface. With this integrated approach we aim to overcome the challenges and enhance our ability to non-invasively characterize underground structures, contributing to improved seismic monitoring techniques.

58 GEOSCIENCES↗