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DOE OSTI2021

An exploration of benchtop X–ray emission spectroscopy for precise characterization of the sulfur redox state in cementitious materials

The evolution of sulfur chemistry in cements is best known in the bailiwick of failure mechanisms via sulfate attack but is equally important for its contributions to the reduction capacity of cementitious materials often used for immobilizing nuclear waste streams destined for long-term storage, e.g., cementitious waste forms (CWF). The total reduction capacity of CWFs, encompassing contributions from both S and Fe reductants, and its implications toward radionuclide immobilization is most often studied by destructive wet chemistry methods requiring acid digestion in the presence of Ce(IV) and subsequent titration and colorimetric interpretation. Here, we investigate a similarly analytical but nondestructive alternative, benchtop high resolution wavelength-dispersive x-ray fluorescence spectroscopy, most commonly known as x-ray emission spectroscopy (XES), for probing the bulk sulfur oxidation state distribution. We present here an initial investigation of S XES, including an improved experimental protocol for lab XES of inhomogeneous samples, both as a complement to the Ce(IV) test and for new scientific opportunities that it enables for observing changes in sulfur chemistry. We discuss future improvements and opportunities, including: (1) the practical challenges associated with coordinating XES and Ce(IV) liquid extraction for a more comprehensive perspective on reduction capacity and for a high-precision evaluation of uncertainties in the Ce(IV) test; and (2) new opportunities, due to the nondestructive nature of XES, for controlled evolution studies aimed at elucidating specific chemical responses of CWF’s exposed to invasive gas or liquid species or to accelerated aging by radiative dose or thermal treatment.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Influence of metallic contaminants on the electrochemical and thermal behavior of Li-ion electrodes

Emerging nondestructive (direct) recycling techniques for lithium-ion batteries may introduce metallic impurities into recycled electrodes. In the present work, the impact of such nonionic contaminants on the practical performance of both anode and cathode materials is evaluated using a synergistic combination of electrochemical and thermal analysis. The impurities under study have been selected through evaluation of industrially shredded batteries, and include Fe0, Al0, Mg0, Cu0, and Si0. The electrochemical behavior of materials containing each individual contaminant at either the anode or the cathode is evaluated in both half-cell and full-cell format. Further, the first-cycle thermal signatures of full cells are used to validate and complement electrochemical signatures, and the two techniques are used in conjunction to suggest distinct mechanisms of electrochemical reactivity for the various impurities. At the anode, metallic contaminants are found to disrupt performance through direct reaction with Li and may serve as weak catalysts to accelerate electrolyte degradation. At the cathode, metallic contaminants show evidence of crossover during formation cycling to disrupt SEI formation. We suggest that coupled electrochemical and thermal analysis may be used to both identify the presence of contaminants and to elucidate specific mechanisms of reactivity for metallic impurities under anodic and cathodic conditions.

Contaminant↗

DOE OSTI2020

Development and evaluation of a list mode neutron coincidence collar for spatial response measurements of fresh fuel assemblies

A traditional safeguards neutron coincidence counting system, the Neutron Coincidence Collar, has been modified to incorporate individual preamplifiers on each of its 18 3He tubes in active interrogation mode. When used with list mode data acquisition (LMDA) and analysis, a signal from each 3He tube can be recorded and analyzed to allow a spatial response measurement to be performed on an item based on count rate and 3He tube location within the system. The ultimate goal of this project is to demonstrate the capabilities of a list mode response matrix for the nondestructive assay of fresh nuclear fuel assemblies. To enable partial defect detection of fuel pin locations and absences within an assembly, the project aims to extend well-established correlated neutron analysis techniques on a preexisting Neutron Coincidence Collar by extracting a greater number of useful signatures from the system than are currently generated. LMDA, combined with the addition of multiple preamplifiers, facilitates this capability by increasing the number of simultaneous signals that can be measured; this allows an in-depth analysis of neutron coincidence events to determine a fissioning item’s location based on the measured doubles count rate in various channel logic coincidence combinations. All of this can be done from a single measurement pulse train in offline analysis, which is the major benefit provided by LMDA. Through various stages of development and testing, a Mirion Technologies model JCC-71 Neutron Coincidence Collar has been successfully retrofit with modern electronics designed in-house at Oak Ridge National Laboratory, matching preexisting JAB-01 electronics performance, while maintaining the original system footprint. This paper presents these various stages of development and experimental evaluation of the proof of concept system.

Moore, Angela S.↗

DOE OSTI2021

Thermoluminescence and optically stimulated luminescence response of Al 2 O 3 coatings deposited by mist-chemical vapor deposition

Aluminum oxide (Al 2 O 3 ) is a widely used ceramic material which can be applied as a protective coating on metallic structures to improve corrosion resistance and mechanical properties. Al 2 O 3 also has great potential as a functional thin film device in optoelectronics. When it is doped with carbon (Al 2 O 3 :C), this material system can serve as a reliable radiation dosimeter. The combination of optoelectronic, dosimetric, and protective properties demonstrated by Al 2 O 3 uniquely positions it for dual use applications in nuclear forensics, nonproliferation and safeguards, emergency response, retrospective dosimetry, and nondestructive inspection. Here, in this study, an innovative ultrasonic mist-chemical vapor deposition (Mist-CVD) system was used to deposit thin (nm level) Al 2 O 3 coatings on 304 stainless steel substrates. The single aliquot regeneration (SAR) and additive dose reconstruction techniques were then used to investigate the thermoluminescence (TL) and optically stimulated luminescence (OSL) response of the coated substrates to increasing doses of β irradiation. This study demonstrates that nm-thick Al 2 O 3 coatings hold promise as novel nano-dosimeters which could be leveraged for a series of applications such as nonproliferation and safeguards, retrospective dosimetry, and nondestructive inspection.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2025

Comparison of three measurement modalities for 3D characterization of manufactured features and process-induced porosity in titanium alloy additively manufactured parts

Nondestructive characterization of internal features and defects within complex components is vital for many industrial applications, particularly with the advent of additive manufacturing (AM) technologies. However, community understanding of the limitations of nondestructive methods such as X-ray Computed Tomography (CT) can be limited in certain industrial sectors as these may be emergent applications. In this paper, we investigate the limits of X-ray CT measurements and compare extracted data with mechanical polishing serial sectioning (MPSS) and confocal laser scanning microscopy (CLSM). The test object is an additively manufactured titanium alloy disk that contains both process-induced porosity and machined features, including focused ion beam milled features designed to probe the resolution limits of X-ray CT. Results show that each of these characterization techniques has advantages and disadvantages. We compare data acquisition times, spatial resolution, geometric measurement accuracy and defect visualization fidelity across these modalities to establish a practical framework.

Additive manufacturing↗

DOE OSTI2024

Differential Exudation Creates Biogeochemically Distinct Microenvironments during Rhizosphere Evolution

Plant roots and associated microbes release a diverse range of functionally distinct exudates into the surrounding rhizosphere with direct impacts on soil carbon storage, nutrient availability, and contaminant dynamics. Yet mechanistic linkages between root exudation and emergent biogeochemical processes remain challenging to measure nondestructively, in real soil, over time. Here we used a novel combination of in situ microsensors with high-resolution mass spectrometry to measure, nondestructively, changing exudation and associated biogeochemical dynamics along single growing plant roots (Avena sativa). We found that metabolite and dissolved organic carbon (DOC) concentrations as well as microbial growth, redox potential (EH), and pH dynamics vary significantly among bulk soil, root tip, and more mature root zones. Surprisingly, the significant spike of rhizosphere DOC upon root tip emergence did not significantly correlate with any biogeochemical parameters. However, the presence of sugars significantly correlated with declines in EH following the arrival of the root tip, likely due to enhanced microbial oxygen demand. Similarly, the presence of organic acids significantly correlated to declines in pH upon root tip emergence. Altogether, our in situ measurements highlight how different exudates released along growing roots create functionally distinct soil microenvironments that evolve over time.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Resonant ultrasound spectroscopy for crystalline samples containing initial strain

Resonant ultrasound spectroscopy (RUS) is a mature and robust technique for the nondestructive characterization of the elastic properties of solids capable of providing the elastic constants of anisotropic crystalline solids. The traditional method is based on assuming that the solid is linear elastic and, therefore, obeys a linearized Hookean constitutive relationship (Hooke’s law). In this work, an alternative constitutive law is provided that allows for an initial strain or prestrain to be present stemming from residual stress. Then, the constitutive relationship is integrated into the RUS framework. The model is demonstrated using a realistic prestrain field obtained by simulating shot-peening processing of a polycrystalline Cu sample. The sensitivity of the resonances to the developed prestrain is established and discussed. This work allows researchers to consider the influence of initial strain or residual stress in their samples and the potential influence on accurate elastic constant estimates. The model also supports the potential of RUS for the nondestructive characterization of prestrain in materials.

42 ENGINEERING↗

DOE OSTI2024

A Review of Online Monitoring within Used Nuclear Fuel Recycling Processes

The processing of used nuclear fuels and related materials is often complex and variable. The ability to quickly optimize conditions to the material being processed can aid in increasing efficiency and safety, but requires very quick determination of the conditions present in the feedstock, the process, and the product. Furthermore, accurate quantification of materials such as enriched uranium and plutonium aids in maintaining material accountancy and avoiding nuclear proliferation risks. Traditional analytical methods require process samples to be collected and analyzed in a laboratory, which often takes days to weeks. Online monitoring is suitable for collecting this information nearly instantaneously, enabling much faster optimization of the process or detection of material diversion. Online monitoring is also beneficial as it is typically based on robust and nondestructive analytical methods, so no material is removed as samples. This review examines online monitoring relevant to used nuclear fuel processing for the determination of both chemical and physical parameters. The chemical parameters include quantities such as concentration, isotopic composition, and speciation. These values are often well suited to spectroscopic or spectrometric measurements as they are fast, nondestructive, and easily implemented in an online manner. Physical quantities are often more varied and include temperature, pressure, tank fill levels, and others. Due to the specificity of these quantities, specialized instrumentation is often used. However, this instrumentation is often amendable to online monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Mixed Element Microparticle Characterization by Electron Probe Microanalysis

Abstract Microparticle compositional characterization for nuclear forensics has traditionally been achieved by “gold-standard” destructive analytical techniques such as large geometry-secondary ion mass spectrometry and fission track-thermal ionization mass spectrometry, but long processing times and total sample consumption eliminate the option of subsequent analysis by other methods. Electron probe microanalysis has long been widely employed for rapid, nondestructive, micrometer-scale compositional measurements and imaging in fields such as material science and geology and may therefore need to be reevaluated as an alternative tool for microparticle analysis for the nuclear forensics community. This study presents the use of electron probe microanalysis for imaging and quantitative characterization of homogeneous microparticles utilizing a calibration curve based on high-precision quadrupole-inductively coupled plasma-mass spectrometry analyses. Samples of opportunity synthesized at Savannah River National Laboratory, nickel-doped cerium oxide microparticles, were selected as analogs for plutonium-doped uranium oxide microparticles. Positive detection and accurate quantification of variable amounts of nickel dopant down to trace levels (10s of parts per million) suggest applicability of this technique to other mixed element systems (e.g., actinides). Quantitative single-particle characterization via electron probe microanalyzer may thus provide a high fidelity, nondestructive complement to techniques currently in use.

Riche, Alexis T. (ORCID:0009000121978126)↗

DOE OSTI2023

Multiplicity counting using organic scintillators to distinguish neutron sources: An advanced teaching laboratory

In this advanced instructional laboratory, students explore complex detection systems and nondestructive assay techniques used in the field of nuclear physics. After setting up and calibrating a neutron detection system, students carry out timing and energy deposition analyses of radiation signals. Through the timing of prompt fission neutron signals, multiplicity counting is used to carry out a special nuclear material (SNM) nondestructive assay. Our experimental setup is comprised of eight trans-stilbene organic scintillation detectors in a well-counter configuration, and measurements are taken on a spontaneous fission source as well as two (α,n) sources. By comparing each source's measured multiplicity distribution, the resulting measurements of the (α,n) sources can be distinguished from that of the spontaneous fission source. Such comparisons prevent the spoofing, i.e., intentional imitation, of a fission source by an (α,n) neutron source. This instructional laboratory is designed for nuclear engineering and physics students interested in organic scintillators, neutron sources, and nonproliferation radiation measurement techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Fast quantum interferometry at the nanometer and attosecond scales with energy-entangled photons

In classical optical interferometry, loss and background complicate achieving fast nanometer-resolution measurements with illumination at low light levels. Conversely, quantum two-photon interference is unaffected by loss and background, but nanometer-scale resolution is physically difficult to realize. As a solution, we enhance two-photon interference with highly nondegenerate energy entanglement featuring photon frequencies separated by 177 THz. We observe measurement resolution at the nanometer (attosecond) scale with only O(10 4 ) photon pairs, despite the presence of background and loss. Our nondestructive thickness measurement of a metallic thin film agrees with atomic force microscopy, which often achieves better resolution via destructive means. With contactless, nondestructive measurements in seconds or faster, our instrument enables metrological studies in optically challenging contexts where background, loss, or photosensitivity are factors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Monitoring Sulfuric Acid and Temperature Using Raman Spectroscopy and Multivariate Chemometrics

Multivariate regression models were optimized for the quantification of sulfuric acid (H 2 SO 4 ) [0–8 M] and temperature (20 °C–80 °C) in the presence of ammonium sulfate ((NH 4 ) 2 SO 4 [0–0.6 M]) using Raman spectroscopy. Optical vibrational spectroscopy is a useful nondestructive technique for the in situ analysis of complex chemical systems notoriously difficult to monitor in situ and in real-time. Multivariate analysis, a chemometrics method, can be paired with these nondestructive optical methods for determining analyte concentration and speciation in complex solutions, such as dissociated species in polyprotic acids, e.g., H 2 SO 4 . The effect of temperature is often overlooked although it can have a major influence on speciation and the corresponding Raman spectra. Here, in this study, partial least squares regression models were optimized for the quantification of H 2 SO 4 and its two deprotonated forms as a function of temperature. Measuring bisulfate as a function of temperature is particularly challenging owing to changes in the second dissociation constant. A designed training set effectively minimized the sample set size and trained a robust predictive model with percent root mean square error of <3% for H 2 SO 4 . The practical strategy employed here was demonstrated to be effective for building chemometric models that directly account for dynamic temperatures with static samples and is shown to be amenable to flow cell analysis applications with a simple calibration transfer for process monitoring applications.

D-optimal design↗

DOE OSTI2020

Detection of Defects in Additively Manufactured Metallic Materials with Machine Learning of Pulsed Thermography Images

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Quality control (QC) requires nondestructive evaluation (NDE) of actual AM structures. Pulsed thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, detection sensitivity of this method is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. The ML methods with higher accuracy require longer run time. However, this runtime is sufficiently short to perform QC within a realistic time frame.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Development of a Neutron List Mode Collar (LMCL) and a List Mode Response Matrix Analysis Concept

This report was prepared for the Safeguards Program of the US Department of Energy’s (DOE’s) National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation Research and Development (DNN R&D). The report presents the development of the neutron nondestructive assay system, the List Mode Collar (LMCL) for the project OR16-List Mode for Collar-PD1La “List Mode Response Matrix for Advanced Correlated Neutron Analysis for Nuclear Safeguards.” The new list mode electronics developed under this project, and a spatial analysis concept called the List Mode Response Matrix are also described in this report. Analysis algorithms based on classification methods are published in a separate report. This research addresses the need to expand the capabilities of current nondestructive assay systems used for nuclear safeguards applications and considers the sustainability of safeguards technologies by the development of a “retrofit” concept using electronics based on modern standards. Furthermore, employing list mode data acquisition enabled the development of a spatial analysis concept and empirical measurement of a spatial response not previously used for safeguards neutron counting applications or measured in a traditional neutron collar detector and, therefore, provides new capability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Performance Validation of Pulsed Thermal Imaging System for In-Service Applications

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermography Imaging (PTI) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTI method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTI method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTI system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTI capabilities in detecting microscopic defects in metallic specimens. SS316 and IN718 specimens were developed with a pattern of subsurface calibrated flat bottom hole (FBH) defects with diameters from 500µm to 200µm. FBH’s were created with EDM (electron discharge machining) drill. PTI imaging data was processed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) algorithm. We show that defects as small as 200µm in SS316 and IN718 can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature.

42 ENGINEERING↗

DOE OSTI2021

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Ultrasonic Measurements of Temperature Profile and Heat Fluxes in Coal-Fired Power Plants (Final Report)

Many industrial processes are inaccessible or inhospitable to characterization by traditional temperature measurement methods, such as thermocouples, especially over prolonged exposure to harsh environments. Ultrasound is an established characterization technology with diverse applications ranging from medical imaging to therapies to flaw detection to nondestructive evaluation. Ultrasound may characterize solid materials and components noninvasively as a nondestructive evaluation modality and obtain internal measurements of material properties. For example, the speed of ultrasound propagation changes with Young’s modulus and Poisson’s ratio, which can be found from its measurements. Traditional ultrasonic characterization assumes all material properties remain constant with the position. When this assumption holds, a property of interest may be measured by relating it to the speed of ultrasound propagation (or a speed of sound, SOS) and measuring the SOS by timing the ultrasound propagation through a known distance. However, when a property of interest is spatially distributed, the propagation time depends on the SOS changing with the position along the ultrasound propagation path. The multiple temperature distributions may lead to an identical time of flight (TOF). Temperature is one property that impacts the speed of ultrasound and often cannot be assumed to remain constant with the position. Previously, in the context of temperature, we addressed the challenge of ultrasonic characterization of spatially distributed properties by developing a method for measuring segmental temperature distributions (MSTD). This method divides the ultrasonic propagation into segments bound by echogenic features. These features provide ultrasonic interfaces where some energy is reflected toward the receiving transducer, and the rest continues through the medium. The time-of-flight between the echoes reflected from echogenic features characterizes the spatial distribution in the properties of interest in the corresponding segment of the ultrasonic propagation path. This project demonstrated the application of the MSTD method in industrial conditions of the coal-fired power plant. We implemented the MSTD using metals and alloys waveguides, which may be the existing structure for which the temperature distribution is characterized or purposefully designed waveguides added to the structure by welding or other means specifically to quantify thermal properties using the MSTD method. Previous iterations of the MSTD method used ceramic and cementitious waveguides, which significantly attenuate ultrasound. On the other hand, low attenuation in metallic waveguides creates interactions between echogenic features which compilates the signal analysis in the segmental TOF measurements. We have established the WG design principles that minimize the interferences between trailing and primary echoes and, in some cases, eliminate them. The waveguides in which echoes do not interfere improve the timing accuracy and the robustness of ultrasonic measurements of the spatial distributions in material properties. Our emphasis remained on the estimation of the temperature distributions. We have developed general recommendations for designing ultrasonically segmented waveguides with the reduced influence of trailing echoes. Two of our waveguide designs were tested in the industry. The first waveguide was designed for insertion into a combustion zone of the utility-scale coal-fired power plant boiler. The second design allows the characterization of temperature distribution in the direction normal to the boiler’s water wall, a large heat exchanger converting the chemical energy released during combustion to the steam driving the electrical power generation turbines. These waveguides were designed to operate within a restrictive space of thermally insulated water wall and incorporate densely located echogenic features while combatting the influence of trailing echoes. The project has successfully demonstrated the feasibility of using the developed method for accurate, continuous, and robust temperature measurements in extreme environments of power generation and other industrial processes. It, therefore, has achieved its overarching goal of advancing the technology readiness level of the novel Ultrasound Measurements of Segmental Temperature Distribution (US-MSTD) method for real-time measurements of the temperature distribution and heat fluxes closer to commercial availability, developing a prototype multipoint measurement system, and validating its performance on coal-fired utility boilers. The success of this project was achieved in collaboration with the power generator, Rocky Mountain Power, and set the stage for the transfer of this technology from the laboratory to the industry.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

DEEPER: An Intergrated Platform for Deeper Roots

Crops with deeper roots would have multiple benefits, including better drought tolerance, reduced requirement for nitrogen fertilizer, and better sequestration of atmospheric CO 2 . DEEPER is an integrated platform of phenomic, genomic, and in silico technologies to generate maize lines with deeper roots. DEEPER is: LEADER (Leaf Elemental Accumulation from Deep Roots) is a breakthrough technology to nondestructively measure rooting depth by using the plant itself as a sensor. LEADER uses handheld X-ray Fluorescence spectrometry to quantify foliar accumulation of elements that are differentially distributed in the soil profile. LEADER is nondestructive and is orders of magnitude cheaper, faster, and more precise than any competing assay of rooting depth in the field. LEADER is able to distinguish deep-rooted from shallow-rooted maize lines in the field without the need for costly and noisy soil coring. RootRobot/DIRT3D, to automatically phenotype root architecture in any field, combining RootRobot, a mechatronics platform to excavate, clean, section, and image mature root crowns, with DIRT3D, software to quantify architectural traits in 3D. Anatomics, a high-throughput platform to phenotype root anatomy, combining LAT 2.0, a technology for 3D imaging of root anatomy and composition, with RootScan3D, software to automatically extract 3D anatomical and cell wall composition metrics from LAT 2.0 output. Using this platform we discovered two novel root traits, parenchyma cell wall thickness and multiseriate cortical sclerenchyma, that improve rooting depth and drought tolerance in maize and wheat. OpenSimRoot/Deep, software to simulate root interaction with hard subsoils. Using this platform we discovered novel concepts regarding how to increase crop rooting depth by modulating how individual root axes respond to hard soil. DeepGenes, a toolkit of genes, parent lines, and genomic selection strategies to enable breeding hybrids with deeper roots. We discovered 3 novel root genes that increase rooting depth in maize and wheat. DEEPER discovered novel root phenotypes for deeper rooting, and delivered validated ideotypes for deeper-rooted maize; novel technologies to rapidly assess root depth, root architecture and anatomy in field-grown plants; novel software tools for root modeling and 3D image analysis of root architecture and anatomy; and validated genes and genomic selection models to deploy traits for deeper rooting in maize breeding. Each DEEPER technology is transformative in its own right, and exceeds existing technologies. They are mutually synergistic, deployable for field-grown plants, and are ready for application. The phenotyping and modeling technologies are readily applicable to many crops, and genetic leads in maize may have utility in other grasses. Taken as a whole they represent a transformative platform to develop deeper-rooted crops, with greater drought tolerance, reduced fertilizer requirement, and greater carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗