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At least 415 records · Page 23

Solar Cell Performance after Exfoliation Using Sonic Liftoff

Removing grown device layers from a GaAs substrate is an essential aspect of reducing costs of III–V photovoltaics. While many methods of device layer removal have been explored, Sonic Lift‐off (SLO) demonstrates novel control of the stress conditions within the substrate during exfoliation. By utilizing acoustic energy, this technique allows for a lower maximum stress required to fully lift‐off layers from a substrate. We demonstrate that this technique results in no damage to inverted‐grown and upright‐grown exfoliated devices. The inverted device demonstrated an efficiency of 26.8% after SLO in comparison to 26.5% for a traditionally‐processed cell, and the upright device showed a 22.0% efficiency after SLO. The SLO process has been shown to produce exfoliated, damage‐free devices and opens the door for substrate reuse to reduce the cost of III–V photovoltaics.

14 SOLAR ENERGY↗

Bacterial Biomining Rare Earth Elements in Abandoned Coal Mine Drainage: Solubilization and Sequestration

Bacteria can be used to biomine rare earth elements (REEs) domestically from abandoned coal-mine drainage (AMD) solids. Pennsylvania has ~11,000 abandoned mines, with ~500 AMD passive remediation systems that precipitate AMD REE rich solids onsite. In passive systems, REEs, co-precipitate with manganese (Mn), accumulating as solids that can produce a valuable leachate when resolubilized. REEs like lanthanum (La) are used in battery technology. Microbial metabolic changes that co-resolubilize Mn and REEs could result in an affordable release process that does not require chemical additives and the select sequestering of REEs like La allow for the selective purification from a mixed REE composition. Currently, the microbial mechanisms that contribute to mass REE resolubilization and selective sequestration are poorly understood. We have isolated bacteria (Bacillus mycoides JR07 and Bacillus pseudomycoides KB7) that solubilize Mn oxide, La oxide, and AMD solids by acidogenesis. We have determined that isolates JR07 and KB7 solubilize the La from AMD PRS solids by their production of organic acids. Preliminary results show methylotrophic bacterial isolate B3 can take up soluble La(III), giving an avenue to purification of La from a rich REE leachate. Determining the microbial metabolism and genes involved in the mass resolubilization of REEs and selective biomining of La(III) is crucial to optimize the biomining of AMD solids. Our work addresses the growing need to develop novel REE recovery methods from domestic sources.

microbiology↗

Laser Ablation for Low-Cost Multijunction III-V Solar Cell Mesa Isolations

Eliminating photolithography from solar cell processing is a significant opportunity for cost reduction for III-V solar cells. In this work, we test femtosecond laser ablation and scribing as an alternative to contact photolithography and wet chemical etching for mesa isolation, when processing multijunction cells. We demonstrate that upright multijunction solar cells isolated by using the laser as a scribe to cleave through the substrate had virtually no performance loss when compared to a baseline cell processed with photolithography. By contrast, cells isolated by laser ablating through the active layers have performance losses that cannot be fully eliminated with post-processing etches. This demonstration of photolithography-free mesa isolation with no performance losses is promising for less expensive III-V manufacturing.

14 SOLAR ENERGY↗

Recovery of Rare Earth Elements (REEs) from Coal Mine Drainage, Phase 2

Phase 1 research identified a two-step refining train, acid leaching of AMD precipitate feed followed by solvent extraction (SX), to produce a 2% TREE product. For the Phase 2 bench scale system, the objective was to get the acid leaching step to operate in batch-mode with sufficient storage capacity to feed an aqueous, enriched REE liquor to a pilot SX plant operating in continuous-mode at a feed rate capable of producing 3 g/hr 2% TREE. Important process variables included feed rate, extractant makeup, flowsheet configuration, and stripping conditions. Operating parameters were optimized through a feedback-capable SCADA system configured for the SX bench scale plant. These conditions were met and exceeded. TREE grades approaching 90% were produced while our Techno-Economic Assessment indicated highly favorable economic returns. The project led to the design of a pilot facility for producing roughly 500 kg/TREE/year. That plant is now in the procurement stage with constructed expected to begin in late 2020.

01 COAL, LIGNITE, AND PEAT↗

Recovery of Rare Earth Elements (REEs) from Coal Mine Drainage, Phase 2

Phase 1 research identified a two-step refining train, acid leaching of AMD precipitate feed followed by solvent extraction (SX), to produce a 2% TREE product. For the Phase 2 bench scale system, the objective was to get the acid leaching step to operate in batch-mode with sufficient storage capacity to feed an aqueous, enriched REE liquor to a pilot SX plant operating in continuous-mode at a feed rate capable of producing 3 g/hr 2% TREE. Important process variables included feed rate, extractant makeup, flowsheet configuration, and stripping conditions. Operating parameters were optimized through a feedback-capable SCADA system configured for the SX bench scale plant. These conditions were met and exceeded. TREE grades approaching 90% were produced while our Techno-Economic Assessment indicated highly favorable economic returns. The project led to the design of a pilot facility for producing roughly 500 kg/TREE/year. That plant is now in the procurement stage with constructed expected to begin in late 2020.

01 COAL, LIGNITE, AND PEAT↗

Potential for light-induced separation of critical rare-earth elements

Current methods for separations of critical rare earth elements (REEs) require multi-step, waste-generating procedures that lack the ability to selectively separate similarly sized ions, despite such an onerous process. REEs possess unique optoelectronic properties that are often exploited for photomagnetic or photoluminescent applications but could be harnessed to drive element selective separations. Here, recent work exploring photochemical reactions of REE complexes points to promise for investigating alternative separations using photoactive molecules and macromolecular frameworks, highlighting a possible pathway towards realizing practical REE separations to increase the sustainability and longevity of mining and recycling these elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Preliminary Report on Compositional Specification for Printed 316SS

The Advanced Materials and Manufacturing Technologies Program is focused on accelerating the development and deployment of advanced materials and components fabricated via additive manufacturing (AM). A key challenge for the widespread adoption of AM is the variability in material properties, which can originate from powder feedstock, process parameters, geometry, and the machine. AM powder feedstock compositions are based on those developed for conventional manufacturing. However, the smaller melt pools combined with multiple melt cycles over the course of a build can have substantial effects on the local phase selection resulting from minor batch-to-batch feedstock variability. Therefore, this report focuses on coupling CALPHAD calculations with data mining and visualization to aid the development of compositional specifications for stainless steel 316, an important alloy for nuclear applications and suitable for AM. This work reports that δ-ferrite formation has a stronger dependence on the amount of nickel in the alloy despite nickel being an austenite stabilizer. These findings show the need for exercising a tighter control on the amount of nickel in the alloy compared with the amount of chromium, which is a ferrite stabilizer.

36 MATERIALS SCIENCE↗

A large-scale comparison of Artificial Intelligence and Data Mining (AI&DM) techniques in simulating reservoir releases over the Upper Colorado Region

In recent years, the Artificial Intelligence and Data Mining (AI&DM) models have become popular tools in assisting various aspects of reservoir operation. However, the practical uses are still rarely reported. Comparison experiment of many AI&DM models over a large number of reservoir cases is particularly valuable to help reservoir operators first examine the usefulness and transferability of different AI&DM models, and then identify the most stable and reliable AI&DM model in assist of various decision-making processes. In this study, a total of 12 AI&DM models with different parameterizations and simulation scenarios are comprehensively tested out and compared in simulating the controlled reservoir outflows of 33 reservoir cases over the Upper Colorado Region, United States. Results show that the Random Forecast and the Long-Short-Term-Memory model could consistently derive the best statistical performance than other models under the baseline simulation scenario. The employed AI&DM models could obtain satisfactory statistical interquartile ranges (25–75%) between [0.6–0.9], [0.3–0.8], and [0.2–0.8], for CORR, NSE, and KGE measurements, respectively, and [1.5–6.5], [–15 to 20], and [0.5–8.5] for the normalized RMSE, PBIAS and RSR measurements, respectively. Results also show Multi-Layer Perceptron model and Extreme Gradient Boosting Tree Algorithm produced more stable and superior performance than other models under more complex input scenarios. We also found that the performance of different AI&DM models are closely relevant to the reservoir elevations, sizes, and functionalities. Discussions were made about the sensitivity of AI&DM models’ parameterizations and the key advantages of AI&DM models over the rule-based reservoir models. We further identify that the main advantage of AI&DM models is the flexibility in designing input structures, whereas the rule-based simulation model is rather limited. Future studies were suggested regarding the best way reservoir operators and researchers could use, select, and apply different AI&DM models in simulating reservoir releases under different natural and modeling environments. Finally, this comparison study also serves as a reference and a piece of groundwork for further promoting the practical uses of AI&DM models in assisting reservoir operation.

54 ENVIRONMENTAL SCIENCES↗

Mg-Ion Conduction in Antiperovskite Solid Electrolytes Revealed by 25 Mg Ultrahigh Field NMR and First-Principles Calculations

Magnesium-ion batteries hold the potential to outperform the energy density of lithium-ion batteries, given the divalent charge carried by each Mg 2+ cation, but remain in an early stage of development. Here, in this study, 25 Mg solid-state nuclear magnetic resonance (ssNMR) is used to gain insight into the local structure and Mg-ion dynamics of candidate Mg-ion solid electrolytes, the antiperovskites Mg 3 SbN and Mg 3 AsN. Using the highest available magnetic field (35.2 T) for high-resolution solid-state NMR, the largest 25 Mg quadrupole coupling constants (C Q ) yet measured of up to 22 MHz are reported and corroborated by first-principles calculations. Predicted C Q values are shown to correlate with the antiperovskite’s tolerance factor; thus, 25 Mg NMR linewidths can report on lattice distortions and phase stability of these antiperovskites. Variable-temperature 25 Mg NMR spectra demonstrate changes at elevated temperatures, ascribed to Mg-ion motional effects. 25 Mg T 1 relaxometry measurements at ultrahigh field reveal a lower activation energy for the more distorted Mg 3 AsN phase, matching computational predictions of a lower energy barrier for Mg 2+ ion migration and suggesting that additional scrutiny of antiperovskites as Mg-ion conductors is warranted. Given the inherent challenges of 25 Mg NMR, this work demonstrates the benefits of combining ultrahigh field NMR spectroscopy, advanced pulse sequences, modern signal processing, and first-principles calculations to facilitate NMR of quadrupolar nuclei as a tool to probe the local structure and ion dynamics in beyond-Li battery materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Autonomous Synthesis and Inverse Design of Electrochromic Polymers with High Efficiency and Accuracy

Here, the design and synthesis of functional polymers, aimed at targeted properties through specific structures, have long been challenged by their complex and often nonlinear structure–property relationships. Key processes, including knowledge accumulation for predictive design and experimental refinement and validation, are traditionally labor-insensitive and time-consuming, making it difficult to balance accuracy and efficiency. Here, we introduce an accelerated, autonomous system for the on-demand synthesis of electronic polymers that achieves the desired electrochromic functionality with high accuracy and efficiency. Our approach leverages large language model-assisted data mining, a physics-informed copolymer machine learning model, and an AI-driven autonomous robotic workflow in the Polybot lab. Within 72 h, Polybot autonomously synthesized electrochromic polymers (ECPs) with targeted, previously-unreported color values, including green polymers with specific absorption profiles, precisely fine-tuning copolymer structures with a 5% step size in comonomer composition within a three-monomer system. A publicly accessible ECP informatics database has also been created to foster knowledge exchange.

AI-driven Robotic Lab↗

Implementing belowground controls on nutrient uptake in ELMv2-SPRUCE improves representation of a boreal peatland ecosystem

Boreal peatlands store 13 %–32 % of the global soil carbon (C) stock, a service dependent on plant-mycorrhizal fungi associations. In these nutrient poor systems, ectomycorrhizal and ericoid mycorrhizal fungi supply up to >80 % of the nutrient requirements of their plant hosts, partly with mined nitrogen (N) and phosphorus (P) from soil organic matter that are otherwise inaccessible to plants. Despite the ecological significance, mycorrhizal associations are only represented in a few land surface or ecosystem models. We modify the peatland branch of version 2 of the Energy Exascale Earth System Land Model (ELMv2-SPRUCE) to replace the default photosynthesis-driven inorganic N and P (NP) uptake process with a more realistic representation of the process via three pathways: (1) direct inorganic NP uptake by uncolonized fine roots, (2) indirect inorganic NP acquisition and (3) indirect NP acquisition from organic sources by mycorrhizal roots. We systematically evaluated the performance of the default and modified models with field observations from a whole ecosystem warming and carbon dioxide fertilization experimental site: Spruce and Peatland Responses Under Changing Environment (SPRUCE), in northern Minnesota, USA. The modified model reduces the underestimation of the growth response of shrubs in the default model to warming from 40 %–80 % to 17 %–35 % and reduces the overall relative absolute error on C fluxes from 1.61 to 1.54 in calibration. Improvements on modeled shrub growths and shrub-moss community net ecosystem exchanges are also seen in validation. The improved growth response of shrubs to warming is accompanied by several-fold increase in direct inorganic NP uptake and decrease in fungal colonization rate. The modified model simulates a smaller magnitude of transition of the ecosystem from C sink to C source under warming due to alleviation of plant nutrient limitation. Equifinality analysis shows the newly added parameters in the modified model can be constrained by the observed C fluxes. Sensitivity analysis shows the newly added parameters have stronger statistical interactions than the preexisting parameters in the default model. Overall, the modified model is an improvement over the default ELMv2-SPRUCE and will be a useful tool for understanding boreal peatland change.

Wang, Yaoping [Oak Ridge National Laboratory (ORNL↗

Compaction of crushed salt for safe containment – overview of the KOMPASS project

Abstract. In Germany, rock salt formations are possible host rock candidates for a repository for heat-emitting radioactive waste. The safety concept of a repository in salt bases on a multibarrier system consisting mainly of the geological barrier salt and geotechnical seals ensuring safe containment. Crushed salt will be used for backfilling of cavities and sealing measures in drifts and shafts due to its favourable properties and its easy availability (mined-off material). The creep of the rock salt leads to crushed salt compaction with time. Thereby, the crushed salts' porosity is reduced from the initial porosity of 30 %–40 % to a value comparable to the porosity of undisturbed rock salt (≤1 %). In such low porosity ranges, technical impermeability is assumed. The compaction behaviour of crushed salt is rather complex and involves several coupled THM processes (Kröhn et al., 2017; Hansen et al., 2014). It is influenced by internal properties like humidity and grain size distribution, as well as boundary conditions such as temperature, compaction rate or stress state. However, the current process understanding has some important gaps referring to the material behaviour, experimental database and numerical modelling. It needs to be extended and validated, especially in the low porosity range. The objective of the KOMPASS project was development of methods and strategies for the reduction of deficits in the prediction of crushed salt compaction leading to an improvement of the prognosis quality. Key results are as follows (KOMPASS Phase 1, 2020): selection of an easily available and permanently producible synthetic crushed salt mixture, acting as a reference material for generic investigations; development and proof of different techniques for producing pre-compacted samples for further investigations; establishment of a tool of microstructure investigation methods to demonstrate the comparability of grain structures of pre-compacted samples with in-situ compacted material for future investigations; execution of various laboratory experiments using pre-compacted samples, e.g. long-term creep tests which deliver reliable information about time- and stress-dependent compaction behaviour; development of a complex experimental investigation strategy to derive necessary model parameters considering individual functional dependencies. Its technical feasibility was successfully verified; benchmarking with various existing numerical models using datasets from three different triaxial long-term tests. The result was not entirely satisfactory; however, the number of influencing factors is small and further validation work has to be done. Overall, the KOMPASS project has made significant progress in the approaches to solving the outstanding question, building the basis for further investigations.

Friedenberg, Larissa↗

Generic Post-Closure Safety Assessment for Deep Borehole Disposal of Heat-Generating Waste - 20451

The deep borehole disposal (DBD) concept for high-activity waste consists of drilling a large-diameter borehole into crystalline basement rock to a depth of about 5,000 m, placing waste packages in the lower portion of the borehole - the waste emplacement zone - and sealing and plugging the upper portion of the borehole with a combination of bentonite, cement plugs, and sand or crushed rock ballast. The waste emplacement zone is several times deeper than typical mined repositories and is well below the typical maximum depth of fresh groundwater resources. Recent work describes a generic reference case for deep borehole disposal of Cs and Sr capsules stored at the Hanford Site. Two scenarios are described: an undisturbed (nominal) scenario, and disturbed scenario, in which a waste package is stuck adjacent to a transmissive fracture zone in crystalline basement. Simulations of the processes affecting radionuclide release and transport in the two scenarios provide the basis for quantitative post-closure performance assessment (PA) of the reference case. This paper presents a probabilistic PA of the stuck waste package scenario, i.e. uncertainties affecting radionuclide mobilization and transport are propagated through 200 realizations of a predictive model to quantify uncertainties in predicted radionuclide concentrations within the borehole and the fracture zone. Simulations predict no radionuclide transport in the borehole to distances greater than 100 m above the stuck waste package. An assumed lateral pressure gradient results in predictions of limited radionuclide transport in the fracture zone at a lateral distance of 200 m from the stuck waste package. These results complement previous results for the nominal scenario and contribute to the development of a generic safety case for DBD. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

At-source Recovery of Rare Earth Elements from Coal Mine Drainage

Conventional acid mine drainage (AMD) treatment consists of pH adjustment, oxidation, and separation of solid precipitates from discharge quality water. Alkaline addition increases the pH to the range 7 to 9 to precipitate the regulated metals Al and Mn ions as hydroxides. Mechanical or chemical oxidation then converts the reduced iron species Fe 2+ to Fe 3+ which precipitates at a low pH value as ferric hydroxide (Fe(OH) 3 ). Co-precipitation of Rare Earth Elements (REEs) with hydroxides creates a gangue-rich matrix from which REEs must be separated. Fe(OH)3 is generally the most abundant gangue-forming metal. Current research by the project team has shown raw, untreated AMD has an average total rare earth element content (TREE) of about 287 μg/L (0.287 ppm). Operators of AMD-producing facilities are obliged to treat it to neutralize acidity and remove regulated metals (e.g., iron (Fe), aluminum (Al), and manganese (Mn)) prior to discharge. Ongoing research indicates conventional AMD treatment concentrates TREE in resulting precipitates (AMD sludge) by an average factor of 2,635x to an average dry weight, elemental concentration of 708 g/t (ppm). While the economics of recovering REEs from AMD sludge are appealing, much of the cost of REE recovery would be incurred during separation of REEs from the gangue metals: Fe, Al, and Mn. Significant gains can be made by precipitating REEs when most of these gangue metals are still in solution. Significant improvements in REE extraction efficiency can be obtained through separation of REEs from the aqueous phase AMD, upstream of conventional AMD treatment by: 1) creating an enriched REE feedstock, 2) producing a more consistent feedstock, 3) reducing transportation costs to an REE refinery, 4) reducing acid consumption in the acid leaching step, and 5) reducing the volume of waste produced at the ALSX plant. This project is exploring two novel approaches for extracting REEs upstream of the conventional AMD treatment plants to create a purified REE feedstock while leaving the bulk of the Fe, Al, and Mn in solution for subsequent treatment. While the average TREE concentration of raw AMD is low and individual sites range between 10 and 2,200 μg/L, successful at-source REE separation will generate a superior feedstock to a conventional ALSX process and significantly improve the economics and environmental performance of REE extraction from AMD. AMD can be classified into two types: type A is net acid and iron is partly oxidized while type B is net alkaline, and iron occurs in the reduced, ferrous state. In Case A, the pH is raised slightly, which will precipitate Fe 3+ and Al 3+ but not REEs. The other important type of AMD is net alkaline water found in flooded, anoxic deep mines. These generally have a pH > 6.0 and are net alkaline. REE concentrations are also much lower than those found in acidic AMD while the volumes and flux are much higher. Most of these are pumped discharges with almost no Al. Case B AMD is strongly reduced and, like Case A water, Fe and Mn ions are similarly reduced and therefore soluble at pH <9.0. REEs and an array of transition ions will be the only trivalent cations in this type of AMD. In Case B, both upward pH adjustment under reducing conditions and application of an electrochemically stimulated supported liquid membrane strategy to separate REEs from ferrous ion will be explored.

01 COAL, LIGNITE, AND PEAT↗

A Multi-scale, Geo-data Science Method for Assessing Unconventional Critical Mineral Resources

Critical minerals (CM) supply raw materials that constitute many of our essential infrastructure, defense, technology, and electrification needs. Currently, production and refinement of these materials from conventional sources is limited to few regions globally, which makes supply of these resources particularly venerable to disruption. To help overcome these risks and meet growing demand, attention has focused on identifying and developing resource potential of unconventional geologic CM sources, such as rare-earth elements in sedimentary systems. However, the unconventional nature of these types of sources means they are often poorly characterized and/or under-explored with respect to conventional counterparts. We present a regional case study for an Unconventional Rare-earth and Critical minerals (URC) assessment method for predicting and identifying REE resource potential and occurrence in unconventional systems in the Central Appalachian Basin (CAB). The method utilizes a geologic and geospatial data-driven approach, informed and guided by knowledge of REE enrichment processes, to systematically predict and identify areas of higher enrichment. Results from the test case indicate locations with potential for different types of coal-REE deposits, demonstrating its utility for reducing the area of exploration and identifying sites for more detailed investigation. Building upon the regional scale assessment capability, ongoing science-based enhancements to the method will allow for finer-scale (e.g., mine-scale) predictions required to support technical and economic assessments.

Creason, Christopher↗

Component Identification of Solid Biomass Fuels Using Reflected Light Microscopy: Interlaboratory Study 2

As nations transition toward sustainable energy systems, biomass has become a vital component of global energy portfolios. Derived from organic materials such as wood, agricultural residues, forestry byproducts, and organic waste, biomass is a renewable energy source with significant environmental and economic benefits. Responsible biomass energy production can improve waste management, reduce emissions of greenhouse gases, and mitigate environmental pollution. However, as the diversity of biomass-derived fuels increases, robust quality assessment methods are essential to ensure their efficiency, safety, and minimal environmental impact. Reflected light microscopy (RLM) is one such technique with the potential to complement conventional physico-chemical analyses by enabling a rapid identification of material constituents and impurities. To refine this methodology and evaluate the reproducibility of solid biomass component identification using RLM, an interlaboratory study (ILS) was conducted. The study involved the recognition of 58 components across 45 photomicrographs, with the participation of 65 scientists and students from 25 countries. The participants faced high difficulty identifying some of the marked components, and as a result, the percentage of correct answers ranged from 19.0 % to 98.3 %, with an average correct identification rate of 62.7 %. The most challenging aspects of the identification process included distinguishing between woody and non-woody (agro) biomass, accurately identifying petroleum-derived materials, and differentiating agro biomass from inorganic matter. The results suggest that while RLM is an important tool for characterizing solid biomass, further development of methodology guidelines and training are necessary to enhance its effectiveness. Future research should prioritize preparing detailed, image-rich, microscopic morphological descriptions of biomass fuel components, which could improve the accuracy and reliability of using RLM in biomass fuel characterization.

09 BIOMASS FUELS↗

Automated Metadata Extraction: Challenges and Opportunities

Proper application of the FAIR data principles is what separates a vibrant data ecosystem, in which research data are frequently shared and reused, from a lifeless data graveyard. Automated metadata extraction systems have been proposed as a means of bolstering the findability, interoperability, and reusabil- ity of data repositories with little or no human intervention. These extraction systems mine metadata by crawling a repository and applying lightweight extractors that, for various types of file (e.g., image, CSV file), extract or synthesize relevant attributes. In practice, however, the automated creation of generally useful metadata is fraught with challenges. Data consumers may have different perspectives as to what metadata representations are useful, the standards for recording metadata tend to change over time, and the software model for processing updates can introduce unnecessary human and computational effort. Thus, generalizing extraction for a broad audience of data consumers is a difficult and relatively unsolved problem.In this work, we explore these challenges faced by extraction systems in the context of constructing our own extraction system for science data. We first define the metadata extraction problem and provide context to the issues faced in generalizing metadata. Additionally, we identify potential research directions to help alleviate many of these challenges for all automated extraction systems. Ultimately, this work represents a first step in designing ubiquitous metadata extraction systems that can maximize the value of research data while minimizing the human efforts required in doing so.

Skluzacek, Tyler↗

EMSL Community Science Campaign Meeting: Critical Minerals and Materials - Rhizo Critical Campaign Breakout Session Report Summary

The “Critical Minerals Biogeochemistry in the Rhizosphere – Ultramafic Soils (Rhizo Critical)” campaign breakout (BO) session was organized to identify major knowledge gaps and fundamental research needs in rhizosphere microbiology and geochemistry that, if addressed, could transform our ability to recover critical minerals from ultramafic soil systems. We sought to identify significant challenges that must be surmounted in the pursuit of deeper science knowledge. Our ultimate goal is to understand this landscape well enough to identify and prioritize opportunities for EMSL to make the greatest impact with Environmental Transformations and Interactions (ETI) science area research campaigns focused on the biogeochemical processes controlling the behavior of critical minerals and materials in the rhizosphere. The increasing demand for critical materials and minerals (CMM) in the U.S. has heightened interest in low-grade ores with much attention on ultramafic soils, which contain valuable metals such as nickel (Ni), chromium (Cr), manganese, cobalt (Co), and copper (Lee et al., 2025; DOE CMM Report, 2023) used in advanced battery, magnet, wiring and wind turbines, and stainless steel technologies. Metal hyperaccumulating plants grown in ultramafic soils can extract economically valuable concentrations of CMMs through the process of phytomining. This technology has evolved from phytoremediation, which involves using plants to cleanse contaminated environments by removing, detoxifying, or stabilizing pollutants like metals and organic compounds. Hyperaccumulator plants are capable of storing metals in their living tissues at concentrations hundreds to thousands of times higher than those found in 'normal' plants. For instance, while the average concentration of Ni in the dry matter of plants growing in typical soils is usually less than 5 µg g?¹, Ni hyperaccumulation is defined by concentrations exceeding 1,000 µg g?¹ (Corzo Remigio et al., 2020; Reeves et al., 2018). Phytomining research has primarily focused on Ni (Rylott and van der Ent, 2025), for which the U.S. has very limited conventional mines in operation. Most soils typically contain Ni concentrations ranging from 7 to 50 mg kg-1, whereas serpentine soils exhibit significantly higher levels, with Ni content often ranging between 700 and 8,000 mg kg-1 (Sobczyk et al., 2017). While more than 500 plant species in over 50 different families have been identified as Ni hyperaccumulators (Kidd et al., 2018), Ni phytomining (and phytominng in general) remains largely untested because most studies are short-term, small-scale, and conducted under simplified or artificially enriched conditions, so they fail to capture the low metal concentrations, environmental variability, and management constraints that would be needed for a field-scale demonstration. Few hyperaccumulator species have been validated as true “metal crops,” and their biomass production, stress tolerance, and rooting characteristics are usually too poor to yield economically meaningful metal outputs. Critically, the basic mechanisms of metal uptake, transport, and sequestration, especially as shaped by belowground processes such as root exudation, rhizosphere chemistry, and root–microbe interactions that control metal mobility and bioavailability (Montreemuk et al., 2023; Kidd et al., 2018; Durand et al., 2023; Alford et al., 2010), are still only partially understood, and downstream metal recovery from biomass is rarely optimized. Because these limitations stem from gaps in fundamental knowledge rather than from a failure of the concept itself (Rylott and van der Ent, 2025; van der Ent et al., 2015), there is a strong need for basic science that dissects plant metal homeostasis, rhizosphere and microbial processes, and their integration with soil chemistry and process engineering to design more robust, scalable phytomining systems.

Ahkami, Amirhossein↗