USGS Science⌕ Search

USGS · 70168438

The distribution and composition of REE-bearing minerals in placers of the Atlantic and Gulf coastal plains, USA

Abstract

Rare earth element (REE) resources are currently of great interest because of their importance as raw materials for high-technology manufacturing. The REE-phosphates monazite (light REE enriched) and xenotime (heavy REE enriched) resist weathering and can accumulate in placer deposits as part of the heavy mineral assemblage. The Atlantic and Gulf coastal plains of the southeastern United States are known to host heavy mineral deposits with economic concentrations of zircon, ilmenite and rutile. This study provides a perspective on the distribution and composition of REE phosphate minerals in the region. The elemental chemistry and mineralogy of sands and associated heavy-mineral assemblages from new and archived sediment samples across the coastal plains are examined, along with phase-specific compositions of monazite, xenotime and zircon. Both monazite and xenotime are present across the coastal plains. The phase-specific compositions allow monazite content to be estimated using La as a geochemical proxy. Similarly, both Y and Yb are geochemical proxies for xenotime, but their additional presence in zircon and monazite require a correction to prevent overestimation of xenotime content. Applying this correction, maps of monazite and xenotime content across the coastal plains were generated using sample coverage from the National Geochemical Database (NGS) and National Uranium Resource Evaluation (NURE). The NGS and NURE approach of sampling stream sediments in small watersheds links samples to nearby lithologies. The results show an approximately 40 km-wide band of primarily Cretaceous, marine sediments bordering the Piedmont province from North Carolina to Alabama in which monazite and xenotime content are relatively high (up to 4.4 wt. % in < 150 &mu;m bulk sediment). Strong correlations between concentrations of the two phases were found, with estimated monazite:xenotime ratios ranging approximately 6:1 to 12:1 depending upon the dataset analyzed. From a resource perspective, xenotime correlation with monazite indicates a heavy REE potential in coastal plain placers, and exploration may be warranted within the identified coastal plain band along the boundary of the Piedmont region.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 28.613459424004414° to 38.548165423046584° latitude; -91.669921875° to -74.794921875° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Carleton R. Bern, Anjana K. Shah, William Benzel, Heather A. Lowers. 2016. The distribution and composition of REE-bearing minerals in placers of the Atlantic and Gulf coastal plains, USA. https://doi.org/10.1016/j.gexplo.2015.12.011

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Top-down targeted network analysis of critical mineral commodities applied to international geochemistry database

The global demand for critical mineral commodities is rapidly increasing, making domestic production an important factor in supporting the economy and national security. Large scale, publicly available geochemical databases allow for the application of data informatics methods to interrogate critical mineral commodities data for correlations in deposit formation and distribution, particularly for identifying enrichment of multiple critical mineral commodities at the same deposit. In this study, we applied network analysis to the Critical Minerals Mapping Initiative (CMMI) ore geochemistry (Critical Minerals in Ores, CMiO) database to identify the high concentration (defined as 10× bulk crustal abundance) co-occurrence of different critical mineral commodities across a mineral system hierarchy from deposit environments to individual deposits. Identifying patterns or unique outliers in enrichment in network communities will allow for the location of secondary critical mineral commodity resources from under-utilized deposits. We find trends in the enrichment of critical mineral commodities in network-communities between the elements praseodymium (Pr), neodymium (Nd), terbium (Tb), and dysprosium (Dy) across multiple CMiO database deposit environments and groups down to specific deposit types and sites. A separate trend in network community deposition is observed as well between iridium (Ir) and platinum (Pt) in deposit environments, groups, types, and sites. Network analysis focused on critical minerals in magmatic-hydrothermal deposits identified multiple deposit sites from different deposit types within the CMiO database with concentrations of Dy, Nd, Tb, Pr, Ir, and Pt that are at least ten times greater than the crustal average. This approach can be applied to any target element(s) or deposit(s) of interest, allowing broad investigation of co-enriched critical mineral commodities.

Journal of Geochemical Exploration↗

Hyperspectral (VNIR-SWIR) analysis of roll front uranium host rocks and industrial minerals from Karnes and Live Oak Counties, Texas Coastal Plain

VNIR-SWIR (400–2500 nm) reflectance measurements were made on the surfaces of various cores, cuttings and sample splits of sedimentary rocks from the Tertiary Jackson Group, and Catahoula, Oakville and Goliad Formations. These rocks vary in composition and texture from mudstone and claystone to sandstone and are known host rocks for roll front uranium occurrences in Karnes and Live Oak Counties, Texas. Spectral reflectance profiles, 569 in total, were reduced to 125 representative spectral signatures, which were analyzed using the U.S. Geological Survey's (USGS) Material Identification and Characterization Algorithm (MICA). MICA uses an automated continuum-removal procedure together with a least-squares linear regression to determine the fit of observed sample spectral absorption features to those of reference mineral standards in a spectral library. The reference minerals include various clay, mica, carbonate, ferric and ferrous iron minerals and their mixtures. In addition, absorption feature band-depth analysis was done to identify rock surfaces exhibiting absorption features related to uranium and zeolite minerals, which were not included in the command files used to execute MICA. Rocks from each of the four geologic units produced broadly similar spectral signatures as a result of comparable mineral compositions, but there were some notable differences. For example, Ca- and Na-montmorillonite was matched most frequently to the spectral absorption features in 2-μm (∼2000–2500 nm) wavelengths, while goethite occurred often at 1-μm (∼400–1000 nm) wavelengths. The latter is related to limonitic iron-staining in and around oxidized zones of the uranium roll front as described in previous papers. Rocks of the Jackson Group differed from those of the Catahoula, Oakville and Goliad units in that the former exhibited spectral features we interpret as being due to the presence of lignite-bearing mudstone layers. Goliad rocks exhibit spectral features related to dolomite, gypsum, anhydrite, and an unidentified green clay mineral that is possibly glauconite . Jackson Group rocks also exhibit weak but well-resolved absorption features at 964 and 1157 nm related to either or both zeolite minerals clinoptilolite and heulandite. These zeolite minerals and a few spectra exhibiting hydrous silica absorption features are indicative of alteration of volcanic glass in tuffaceous mudstone and claystone layers. A few sample spectra exhibited strong absorption features at around 1135 nm related to the uranium mineral coffinite. Both the 1135 nm coffinite and 1157 nm zeolite absorption features overlap somewhat, potentially making them difficult to distinguish without additional hyperspectral field, laboratory or remote sensing data. The results of this study were compared to mixtures of minerals described for ore, gangue and alteration minerals in deposit models for sandstone-hosted uranium, sedimentary bentonite and sedimentary zeolite. Use of these spectra can help facilitate mapping of both waste materials from the legacy mining of the above commodities, as well as future exploration and resource assessment activities.

Texas↗

Hyperspectral mapping of magmatic-hydrothermal sericite, Battle Mountain mining district, Nevada

We demonstrate the utility of multi-scale imaging spectroscopy data (hyperspectral data) to differentiate magmatic-hydrothermal sericite from other white micas based on grain size, in a case study of the Battle Mountain mining district in Humboldt and Lander Counties, Nevada. The Battle Mountain mining district contains porphyry, skarn, and distal disseminated deposits that formed in magmatic-hydrothermal systems, as well as sedimentary-rock hosted gold deposits of less certain origin. We generated spectral-based mineral maps of the Battle Mountain mining district to examine the spatial distribution of spectrally dominant minerals such as kaolinite, montmorillonite , and white micas (muscovite, sericite, and illite). We then used spectral-based mineral mapping to characterize the grain size and composition of white micas, enabling us to differentiate igneous muscovite from magmatic-hydrothermal sericite. By integrating our spectral-based maps with geologic mapping, airborne aeromagnetic data, and prior studies on mines and deposits in Battle Mountain, we determined that finer grained, higher Al sericite spatially correlated with the footprints of known magmatic-hydrothermal systems and is interpreted as forming from magmatic-hydrothermal alteration. Larger grained, lower Al muscovites are distal from known magmatic-hydrothermal systems and are interpreted as being igneous derived siliciclastic sediments that became constituents of the host sedimentary rocks. Techniques described in this contribution can be applied to any appropriate hyperspectral data, regardless of sensor type used to collect the data.

Nevada↗