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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↗

Experimental Evaluation of the Fast-Neutron Passive Collar (FNPC) Performance and Comparison with Scintillation Based Collars

This report describes a new method for the verification of fresh low enrichment uranium (LEU) fuel assemblies that can reduce International Atomic Energy Agency (IAEA) inspection time in the field and be completely independent of operator declared burnable poison content. The passive measurement makes unattended mode operation practical, and thus provides the potential for reducing inspector time in the field for future applications. The new simplified passive neutron measurement uses the 238 U spontaneous fission in LEU fresh fuel rods to self-interrogate the 235 U mass in the neighboring rods. The measured response increases linearly with the increase in the linear density (LD) of 235 U. The relatively high efficiency of the passive neutron detector (24%) provides good statistical precision (~ 2%) for the singles, doubles, and triples counting rates in the thermal-neutron mode. The three observables makes possible multiplicity analysis so that both the 235 U LD and the effective burnable poison content can be determined independent of the operator declarations. This closes the potential diversion path of miss-declaration the burnable poison content. This report presents the detector design, the as-built system, the detector parameter measurements, the calibration, and the assay uncertainty estimates. The calibration measurements were performed using the Los Alamos Laboratory mockup PWR fuel assembly. The measurements were made in both the fastneutron mode (with Cd/Gd metal liners) and the thermal-neutron mode (no Cd/Gd liners).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Design, analysis and control of large transports so that control of engine thrust can be used as a back-up of the primary flight controls

A propulsion controlled aircraft (PCA) system has been developed at NASA Dryden Flight Research Center at Edwards Air Force Base, California, to provide safe, emergency landing capability should the primary flight control system of the aircraft fail. As a result of the successful PCA work being done at NASA Dryden, this project investigated the possibility of incorporating the PCA system as a backup flight control system in the design of a large, ultra-high capacity megatransport in such a way that flight path control using only the engines is not only possible, but meets MIL-Spec Level 1 or Level 2 handling quality requirements. An 800 passenger megatransport aircraft was designed and programmed into the NASA Dryden simulator. Many different analysis methods were used to evaluate the flying qualities of the megatransport while using engine thrust for flight path control, including: (1) Bode and root locus plot analysis to evaluate the frequency and damping ratio response of the megatransport; (2) analysis of actual simulator strip chart recordings to evaluate the time history response of the megatransport; and (3) analysis of Cooper-Harper pilot ratings by two NaSA test pilots.

Roskam, Jan↗

Gravity, light and plant form

Plants have evolved highly sensitive and selective mechanisms that detect and respond to various aspects of their environment. As a plant develops, it integrates the environmental information perceived by all of its sensory systems and adapts its growth to the prevailing environmental conditions. Light is of critical importance because plants depend on it for energy and, thus, survival. The quantity, quality and direction of light are perceived by several different photosensory systems that together regulate nearly all stages of plant development, presumably in order to maintain photosynthetic efficiency. Gravity provides an almost constant stimulus that is the source of critical spatial information about its surroundings and provides important cues for orientating plant growth. Gravity plays a particularly important role during the early stages of seedling growth by stimulating a negative gravitropic response in the primary shoot that orientates it towards the source of light, and a positive gravitropic response in the primary root that causes it to grow down into the soil, providing support and nutrient acquisition. Gravity also influences plant form during later stages of development through its effect on lateral organs and supporting structures. Thus, the final form of a plant depends on the cumulative effects of light, gravity and other environmental sensory inputs on endogenous developmental programs. This article is focused on developmental interactions modulated by light and gravity.

NASA Discipline Plant Biology↗

Temporal Forecasting of Distributed Temperature Sensing in a Thermal Hydraulic System With Machine Learning and Statistical Models

We benchmark performance of long-short term memory (LSTM) network machine learning model and autoregressive integrated moving average (ARIMA) statistical model in temporal forecasting of distributed temperature sensing (DTS). Data in this study consists of fluid temperature transient measured with two co-located Rayleigh scattering fiber optic sensors (FOS) in a forced convection mixing zone of a thermal tee. We treat each gauge of a FOS as an independent temperature sensor. We first study prediction of DTS time series using Vanilla LSTM and ARIMA models trained on prior history of the same FOS that is used for testing. The results yield maximum absolute percentage error (MaxAPE) and root mean squared percentage error (RMSPE) of 1.58% and 0.06% for ARIMA, and 3.14% and 0.44% for LSTM, respectively. Next, we investigate zero-shot forecasting (ZSF) with LSTM and ARIMA trained on history of the co-located FOS only, which is advantageous when limited training data is available. The ZSF MaxAPE and RMSPE values for ARIMA are comparable to those of the Vanilla use case, while the error values for LSTM increase. We show that in ZSF, performance of LSTM network can be improved by training on most correlated gauges between the two FOS, which are identified by calculating the Pearson correlation coefficient. The improved ZSF MaxAPE and RMSPE for LSTM are 4.4% and 0.33%, respectively. Performance of ZSF LSTM can be further enhanced through transfer learning (TL), where LSTM is re-trained on a subset of the FOS that is the target of forecasting. We show that LSTM pre-trained on correlated dataset and re-trained on 30% of testing target dataset achieves MaxAPE and RMSPE values of 2.32% and 0.28%, respectively.

ARIMA↗

Rapid in situ nutrient element distribution in plants and soils using laser-induced breakdown spectroscopy ($\mathrm{LIBS}$)

The aim of this study is to develop and test the applicability of a rapid in situ plant chemistry profiling technique to determine elemental composition of small-volume plant and soil samples obtained from a woody bioenergy crop species, Populus trichocarpa. Expanding the research tools available to characterize the nutrient element correlations among plant tissue types and soil depths is a critical need in the path of understanding productivity and adaptation of plants to variations in external abiotic and biotic factors and developing sustainable perennial bioenergy crops that are co-optimized for biomass valorization aboveground and carbon sequestration belowground. Several plant root, stem, and soil samples were tested using laser-induced breakdown spectroscopy (LIBS) to evaluate the presence and distribution of nutrient elements. Samples were tested as collected and after being dried and cross sectioned to evaluate the effectiveness of using LIBS for in situ analysis on plant samples. The collected LIBS spectra show the elemental peaks were the same in both the as collected and prepared samples for roots and stems. Qualitative amounts of elements such as H, C, N, O, Li, Na, Mg, K, Ca, Fe, Al, and Si were able to be identified rapidly in raw samples. Here in this report we demonstrate suitability of LIBS in obtaining rapid, in situ, elemental distribution in plant and soil samples, utilizing only small sample volumes and minimal sample preparation. This demonstration opens up a new rapid phenotyping avenue necessary to fill the asymmetrical knowledge gaps in belowground performance of plant systems.

59 BASIC BIOLOGICAL SCIENCES↗

Knowledge acquisition and innovation quality: The moderating role of geographical characteristics of technology

Acquiring and absorbing knowledge at different geographic levels is an important step in the technological learning and innovation processes for firms. Geographically bounded knowledge searching and spillover have been shown in various network formats, industries, geographic scopes, and country contexts. This study finds evidence of localized learning in citation networks in the solar photovoltaic balance-of-systems (PV BOS) innovations, and that the levels of localized learning vary based on the degree to which technologies are relevant to local contexts. Thus, this study proposes that the value of local and non-local knowledge on patent quality is contingent on technological characteristics. Further, leveraging the different degrees of local dependence on four types of technologies in the PV BOS industry, we find that the impact of local knowledge on innovation quality is higher for technologies that are more rooted in local contexts and that the impact of non-local knowledge is higher for technologies that are less relevant to local contexts.

99 GENERAL AND MISCELLANEOUS↗

Cropbox: a declarative crop modelling framework

Abstract We introduce Cropbox, a novel modelling framework that supports various aspects of crop modelling in a unique yet concise style. Building a crop model can be easily riddled with technical details looking trivial at first but later becoming major obstacles that hamper the whole development or application process. This is particularly the case when implementing models from scratch without relying on an established framework. Cropbox adopts a declarative approach providing a domain-specific language to reduce technical debt and assist modellers to focus on high-level abstraction formed by relations between variables and enclosing systems, rather than tinkering with low-level implementation details. The syntax of Cropbox framework is based on the Julia programming language and is deliberately constrained to avoid unintended side effects caused by common mistakes while its architecture remains open to extension. We highlight key capabilities of the framework through case studies featuring a leaf gas-exchange model and a whole-plant simulation model. We also illustrate potential extensions for supporting functional-structural plant modelling by demonstrating a 3D root architectural model as an example.

Yun, Kyungdahm (ORCID:0000000322894386)↗

Deep Learning-enhanced Block-Diagram Modeling of Solar Power Systems

Data-driven models of power system inverter-based resources are desired to run simulations faster than with detailed electromagnetic transient models, to hide proprietary design details, to support control system design applications, and to aggregate the effects of distributed energy resources. This paper applies a customized Hammerstein Wiener framework to train block diagram models from thousands of electromagnetic transient simulations or experimental test records. The block diagram models integrate with larger grid simulations as voltagecontrolled current sources or current-controlled voltage sources for several simulators. Guidelines for block architecture and training are presented. Three-phase balanced, three-phase unbalanced, and single-phase examples all achieve an acceptable root mean square error of no more than 0.05 per-unit.

Mcdermott, Thomas E. [Private consulting company]↗

Study of the Heater-Coil Electrical Insulation for the HL-LHC Low Beta Quadrupoles

In the framework of the HL-LHC project, the present LHC low-β superconducting quadrupoles will be substituted with higher performance Nb 3 Sn magnets (MQXF) with 11.4 T coil peak field. MQXF coils are impregnated with epoxy resin to reduce risk of stress concentration on the brittle conductor. The magnet quench protection is provided by CLIQ and quench heaters to ensure a redundant system. Quench heaters are impregnated with the coils in order to have suitable thermal contact with them, and to prevent the hot spot temperature from exceeding 350K during normal operation in case of a quench. Quench heaters are insulated from the coil by S-2 Glass and polyimide. Here, the test of the first MQXF prototype (4 m long) MQXFAP1 was stopped by a coil-to-ground short circuit triggered by a heater-to-coil short. This issue triggered a root analysis of the causes of this short. Here we prove that the use of a non-conforming cloth in coil impregnation, further weakened by non-conforming high voltage test, has triggered the shorts. Moreover, we present an analysis of the heater-to-coil insulation strength, showing the role of blistering phenomena and how they are triggered by a combination of magnet powering and heater firing.

43 PARTICLE ACCELERATORS↗

Increased microbial growth, biomass, and turnover drive soil organic carbon accumulation at higher plant diversity

Species-rich plant communities have been shown to be more productive and to ­exhibit increased long-term soil organic carbon (SOC) storage. Soil microorganisms are central to the conversion of plant organic matter into SOC, yet the relationship between plant diversity, soil microbial growth, turnover as well as carbon use efficiency (CUE) and SOC accumulation is unknown. As heterotrophic soil microbes are primarily carbon limited, it is important to understand how they respond to increased plant-derived carbon inputs at higher plant species richness (PSR). We used the long-term grassland biodiversity experiment in Jena, Germany, to examine how microbial physiology responds to changes in plant diversity and how this affects SOC content. The Jena Experiment considers different numbers of species (1–60), functional groups (1–4) as well as functional identity (small herbs, tall herbs, grasses, and legumes). We found that PSR accelerated microbial growth and turnover and increased microbial biomass and necromass. PSR also accelerated microbial respiration, but this effect was less strong than for microbial growth. In contrast, PSR did not affect microbial CUE or biomass-specific respiration. Structural equation models revealed that PSR had direct positive effects on root biomass, and thereby on microbial growth and microbial biomass carbon. Finally, PSR increased SOC content via its positive influence on microbial biomass carbon. We suggest that PSR favors faster rates of microbial growth and turnover, likely due to greater plant productivity, resulting in higher amounts of microbial biomass and necromass that translate into the observed increase in SOC. We thus identify the microbial mechanism linking species-rich plant communities to a carbon cycle process of importance to Earth's climate system.

59 BASIC BIOLOGICAL SCIENCES↗

Quantification of Soil Organic Carbon in Biochar-Amended Soil Using Ground Penetrating Radar (GPR)

The application of biochar amendments to soil has been proposed as a strategy for mitigating global carbon (C) emissions and soil organic carbon (SOC) loss. Biochar can provide additional agronomic benefits to cropping systems, including improved crop yield, soil water holding capacity, seed germination, cation exchange capacity (CEC), and soil pH. To maximize the beneficial effects of biochar amendments towards the inventory, increase, and management of SOC pools, nondestructive analytical methods such as ground penetrating radar (GPR) are needed to identify and quantify belowground C. The use of GPR has been well characterized across geological, archaeological, engineering, and military applications. While GPR has been predominantly utilized to detect relatively large objects such as rocks, tree roots, land mines, and peat soils, the objective of this study was to quantify comparatively smaller, particulate sources of SOC. This research used three materials as C sources: biochar, graphite, and activated C. The C sources were mixed with sand—12 treatments in total—and scanned under three moisture levels: 0%, 10%, and 20% to simulate different soil conditions. GPR attribute analyses and Naïve Bayes predictive models were utilized in lieu of visualization methods because of the minute size of the C particles. Significant correlations between GPR attributes and both C content and moisture levels were detected. The accuracy of two predictive models using a Naïve Bayes classifier for C content was trivial but the accuracy for C structure was 56%. The analyses confirmed the ability of GPR to identify differences in both C content and C structure. Beneficial future applications could focus on applying GPR across more diverse soil conditions.

54 ENVIRONMENTAL SCIENCES↗

A unique formulation of elastic airplane longitudinal equations of motion

Control-configured vehicle technology has increased the demand for detailed analysis of dynamic stability and control, handling and ride qualities, and control system dynamics at early stages of preliminary design. An approximate, but reasonably accurate, set of equations of motion are needed for these early analyses. Such a formulation is developed for the longitudinal dynamics of elastic airplanes. It makes use of only rigid-body aerodynamic stability derivatives in formulating the forces and moments due to elastic motion. Verification of accuracy using data for the B-1 airplane shows very good agreement. Frequencies and damping ratios of the coupled modes corresponding to complex roots of the characteristic equations agree closely with four symmetric elastic modes included.

Swaim, R. L.↗

A unique formulation of elastic airplane longitudinal equations of motion

Control-configured vehicle technology has increased the demand for detailed analysis of dynamic stability and control, handling and ride qualities, and control system dynamics at early stages of preliminary design. An approximate but reasonably accurate set of equations of motion are needed for these early analyses. Such a formulation is developed for the longitudinal dynamics of elastic airplanes. It makes use of only rigid-body aerodynamic stability derivatives in formulating the forces and moments due to elastic motion. Verification of accuracy using data for the B-1 airplane shows very good agreement. Frequencies and damping ratios of the coupled modes corresponding to complex roots of the characteristic equations agree closely with four symmetric elastic modes included.

Swaim, R. L.↗

Estimating unsteady aerodynamic forces on a cascade in a three-dimensional turbulence field

An analytical method has been developed to estimate the unsteady aerodynamic forces caused by flow field turbulence on a wind tunnel turning vane cascade system (vane set). This method approximates dynamic lift and drag by linearly perturbing the appropriate steady state force equations, assuming that the dynamic loads are due only to free stream turbulence and that this turbulence is homogeneous, isotropic, and Gaussian. Correlation and unsteady aerodynamic effects are also incorporated into the analytical model. Using these assumptions, equations relating dynamic lift and drag to flow turbulence, mean velocity, and vane set geometry are derived. From these equations, estimates for the power spectra and rms (root mean squared value, delta) loading of both lift and drag can be determined.

Norman, T.↗

Estimating unsteady aerodynamic forces on a cascade in a three-dimensional turbulence field

An analytical method has been developed to estimate tne unsteady aerodynamic forces caused by flow field turbulence on a wind tunnel turning vane cascade system (vane set). This method approximates dynamic lift and drag by linearly perturbing the appropriate steady state force equations, assuming that the dynamic loads are due only to free stream turbulence and that this turbulence is homogeneous, isotropic, and Gaussian. Correlation and unsteady aerodynamic effects are also incorporated into the analytical model. Using these assumptions, equations relating dynamic lift and drag to flow turbulence, mean velocity, and vane set geometry are derived. From these equations, estimates for the power spectra and rms (root mean squared value, delta) loading of both lift and drag can be determined.

Norman, T. R.↗

Geostatistical Approaches for Spatial Estimation of Vegetation Quantities Using Ground and Image Data

A major challenge in the study of the earth system is the mapping of vegetation quantities over large regions. Geostatistical methods, such as cokriging and stochastic simulation, have the potential to exploit more fully both remotely sensed data and ground information and improve the spatial estimation of vegetation variables over traditional regression methods. A synthetic example constructed from imaging spectrometer data allows a useful comparison among regression, cokriging and a simple probability-field method. A range of linear relationships between direct (sampled) and ancillary images is used. The lowest root-mean-square-error is achieved with cokriging until the correlation between direct and ancillary data exceeds .89, at which point regression is the superior estimator. Probability-field simulation gives a range of possible realizations, most more precise than those from regression. The relationship between ground measurements and image data is thus demonstrated to be one of the critical factors in the choice of a spatial estimation method.

Dungan, Jennifer L.↗

Smartphone application for visualizing building air leakage

Annually, unwanted air leakage through building envelopes accounts for 4 quads of energy consumption in the United States, which translates to about 10% of total building energy consumption. Locating and sealing leakage sites is crucial fordecreasing building energy consumption. Smartphones are ubiquitous and contain sophisticated cameras and highperformance processors that could be employed to visualize air leakage using the background-oriented schlieren imaging technique, making leak detection cheaper and easier. This technique requires a textured and high-contrast background such as a brick or concrete masonry unit wall, a building air leak that has a temperature difference compared with the ambient air, and an imaging system. This work focuses on using smartphones as the imaging system to visualize air leakages. The paper discusses application development and the results of testing to determine leakage visualization performance as a function of leak temperature. The results show that leaks with a temperature difference greater than 16°C compared with the ambient air temperature were visualized using existing smartphones.

Boudreaux, Philip [ORNL] (ORCID:0000000229564665)↗

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