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DOE OSTI2022

Installation and imaging of thousands of minirhizotrons to phenotype root systems of field-grown plants

Roots are vital to plant performance because they acquire resources from the soil and provide anchorage. However, it remains difficult to assess root system size and distribution because roots are inaccessible in the soil. Existing methods to phenotype entire root systems range from slow, often destructive, methods applied to relatively small numbers of plants in the field to rapid methods that can be applied to large numbers of plants in controlled environment conditions. Much has been learned recently by extensive sampling of the root crown portion of field-grown plants. But, information on large-scale genetic and environmental variation in the size and distribution of root systems in the field remains a key knowledge gap. Minirhizotrons are the only established, non-destructive technology that can address this need in a standard field trial. Prior experiments have used only modest numbers of minirhizotrons, which has limited testing to small numbers of genotypes or environmental conditions. This study addressed the need for methods to install and collect images from thousands of minirhizotrons and thereby help break the phenotyping bottleneck in the field. Over three growing seasons, methods were developed and refined to install and collect images from up to 3038 minirhizotrons per experiment. Modifications were made to four tractors and hydraulic soil corers mounted to them. High quality installation was achieved at an average rate of up to 84.4 minirhizotron tubes per tractor per day. A set of four commercially available minirhizotron camera systems were each transported by wheelbarrow to allow collection of images of mature maize root systems at an average rate of up to 65.3 tubes per day per camera. This resulted in over 300,000 images being collected in as little as 11 days for a single experiment. The scale of minirhizotron installation was increased by two orders of magnitude by simultaneously using four tractor-mounted, hydraulic soil corers with modifications to ensure high quality, rapid operation. Image collection can be achieved at the corresponding scale using commercially available minirhizotron camera systems. Along with recent advances in image analysis, these advances will allow use of minirhizotrons at unprecedented scale to address key knowledge gaps regarding genetic and environmental effects on root system size and distribution in the field.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

PyCMG-based Simulation of Volumetric Concrete Microstructure

Concrete is a complex, heterogeneous material with a microstructure composed of aggregates, cement paste, and pores spanning multiple length scales. Understanding this microstructure is critical for advancing the performance, durability, and modeling of concrete-based systems. While experimental imaging such as X-ray computed tomography (XCT) provides valuable insights, generating large datasets with detailed ground truth annotations is both costly and labor-intensive due to challenges in segmenting similar phases, such as aggregates and cement paste, that often share similar attenuation properties. To address this, we developed a pipeline to simulate realistic 3D concrete microstructures using the open-source Python package PyCMG. This simulation effort focuses on generating high-fidelity, annotated microstructures that can serve as training or benchmarking datasets for image analysis, segmentation algorithms, and machine learning models, particularly in scenarios where experimental data is scarce.

Ziabari, Amir [Oak Ridge National Laboratory; ORNL↗

DOE OSTI2017

Simplified model of pinhole imaging for quantifying systematic errors in image shape

In this paper, we examine systematic errors in x-ray imaging by pinhole optics for quantifying uncertainties in the measurement of convergence and asymmetry in inertial confinement fusion implosions. We present a quantitative model for the total resolution of a pinhole optic with an imaging detector that more effectively describes the effect of diffraction than models that treat geometry and diffraction as independent. This model can be used to predict loss of shape detail due to imaging across the transition from geometric to diffractive optics. We find that fractional error in observable shapes is proportional to the total resolution element we present and inversely proportional to the length scale of the asymmetry being observed. Finally, we have experimentally validated our results by imaging a single object with differently sized pinholes and with different magnifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Non-destructive identification of absorptive damage sites by photoluminescence brightening

We present a non-destructive photoluminescence (PL) imaging strategy for probing damage growth behavior in fused silica under laser irradiation. Transient wide-field PL image measurements were conducted at varying excitation intensities to investigate the dynamics of radiative defect generation and annihilation in laser-induced damage sites. Our results reveal that, while low excitation intensities predominantly induce PL quenching due to defect annihilation, high-intensity excitation (>0.3 GW/cm 2 at 532 nm) triggers pronounced PL brightening (PLB), indicative of radiative defect generation. Image analysis demonstrates that PLB events are strongly correlated with subsequent damage growth (10 J/cm 2 at 351 nm), whereas overall PL intensity is not. No optically detectable morphological changes were observed during PLB, confirming the non-destructive nature of the technique. We propose that PLB arises from defect-assisted absorption of multiple photons at pre-existing absorptive centers, which enhances local absorptivity and initiates further defect formation. These findings establish PLB monitoring as a sensitive diagnostic tool for identifying damage sites with elevated absorptivity, enabling targeted maintenance and improved laser damage management in optical materials.

Materials science↗

DOE OSTI2019

Single-cell correlations of mRNA and protein content in a human monocytic cell line after LPS stimulation

The heterogeneity of mRNA and protein expression at the single-cell level can reveal fundamental information about cellular response to external stimuli, including the sensitivity, timing, and regulatory interactions of genes. Here we describe a fully automated system to digitally count the intron, mRNA, and protein content of up to five genes of interest simultaneously in single-cells. Full system automation of 3D microscope scans and custom image analysis routines allows hundreds of individual cells to be automatically segmented and the mRNA-protein content to be digitally counted. Single-molecule intron and mRNA content is measured by single-molecule fluorescence in-situ hybridization (smFISH), while protein content is quantified though the use of antibody probes. To mimic immune response to bacterial infection, human monocytic leukemia cells (THP-1) were stimulated with lipopolysaccharide (LPS), and the expression of two inflammatory genes, IL1β (interleukin 1β) and TNF-α (tumor necrosis factor α), were simultaneously quantified by monitoring the intron, mRNA, and protein levels over time. The simultaneous labeling of cellular content allowed for a series of correlations at the single-cell level to be explored, both in the progressive maturation of a single gene (intron-mRNA-protein) and comparative analysis between the two immune response genes. In the absence of LPS stimulation, mRNA expression of IL1β and TNF-α were uncorrelated. Following LPS stimulation, mRNA expression of the two genes became more correlated, consistent with a model in which IL1β and TNF-α upregulation occurs in parallel through independent mechanistic pathways. This smFISH methodology can be applied to different complex biological systems to provide valuable insight into highly dynamic gene mechanisms that determine cell plasticity and heterogeneity of cellular response.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Monitoring the impact of confinement on hyphal penetration and fungal behavior

Through their expansive mycelium network, soil fungi alter the physical arrangement and chemical composition of their local environment. This can significantly impact bacterial distribution and nutrient transport and can play a dramatic role in shaping the rhizosphere around a developing plant. However, direct observation and quantitation of such behaviors is extremely difficult due to the opacity and complex porosity of the soil microenvironment. In this study, we demonstrate the development and use of an engineered microhabitat to visualize fungal growth in response to varied levels of confinement. Microfluidics were fabricated using photolithography and conventional soft lithography, assembled onto glass slides, and prepared to accommodate fungal cultures. Selected fungal strains across three phyla (Ascomycota: Morchella sextalata , Fusarium falciforme ; Mucoromycota: Linnemannia elongata , Podila minutissima , Benniella ; Basidiomycota: Laccaria bicolor , and Serendipita sp.) were cultured within microhabitats and imaged using time-lapse microscopy to visualize development at the mycelial level. Fungal hyphae of each strain were imaged as they penetrated through microchannels with well-defined pore dimensions. The hyphal penetration rates through the microchannels were quantified via image analysis. Other behaviors, including differences in the degree of branching, peer movement, and tip strength were also recorded for each strain. Our results provide a repeatable and easy-to-use approach for culturing fungi within a microfluidics platform and for visualizing the impact of confinement on hyphal growth and other fungal behaviors pertinent to their remodeling of the underground environment.

Guo, Yi-Syuan (ORCID:0000000340142225)↗

DOE OSTI2023

Assessment of Different Approaches for Measuring Shear Fracture Appearance in Charpy Tests

In this work, different approaches for establishing shear fracture appearance (SFA) on tested Charpy specimens were assessed and compared, namely (in order of increasing expected accuracy) estimates based on characteristic forces from instrumented Charpy tests, optical measurements using image analysis software, and measurements performed with the aid of a scanning electron microscope. Comparisons between different SFA values for 129 instrumented Charpy tests currently included in the National Institute of Standards and Technology database allowed us to establish the relationships between the different available approaches and formulate recommendations for the revision of the standards ASTM E2298-18, Standard Test Method for Instrumented Impact Testing of Metallic Materials, and ISO 14556:2015, Metallic Materials — Charpy V-Notch Pendulum Impact Test — Instrumented Test Method, which currently provide four empirical correlations that can be used to estimate SFA.

36 MATERIALS SCIENCE↗

DOE OSTI2020

"Sintering" Models and In-Situ Experiments: Data Assimilation for Microstructure Prediction in SLS Additive Manufacturing of Nylon Components

Selective laser sintering methods are workhorses for additively manufacturing polymer-based components. The ease of rapid prototyping also means it is easy to produce illicit components. It is necessary to have a data-calibrated in-situ physical model of the build process in order to predict expected and defective microstructure characteristics that inform component provenance. Toward this end, sintering models are calibrated and characteristics such as component defects are explored. This is accomplished by assimilating multiple data streams, imaging analysis, and computational model predictions in an adaptive Bayesian parameter estimation algorithm. From these data sources, along with a phase-field model, bulk porosity distributions are inferred. Model parameters are constrained to physically-relevant search directions by sensitivity analysis, and then matched to predictions using adaptive sampling. Using this feedback loop, data-constrained estimates of sintering model parameters along with uncertainty bounds are obtained.

3D printing, Additive Manufacturing, polymer, sint↗

DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗

DOE OSTI2018

Grain Size and Phase Purity Characterization of U 3 Si 2 Pellet Fuel

Characterization of U 3 Si 2 fresh fuel pellets is important for quality assurance and validation of the finished product. Grain size measurement methods, phase identification methods using scanning electron microscopes equipped with energy dispersive spectroscopy and x-ray diffraction, and phase quantification methods via image analysis have been developed and implemented on U 3 Si 2 pellet samples. A wide variety of samples have been characterized including representative pellets from an initial irradiation experiment, and samples produced using optimized methods to enhance phase purity from an extended fabrication effort. The average grain size for initial pellets was between 16 and 18 µm. The typical average grain size for pellets from the extended fabrication was between 20 and 30 µm with some samples exhibiting irregular grain growth. Pellets from the latter half of extended fabrication had a bimodal grain size distribution consisting of coarsened grains (>80 µm) surrounded by the typical (20-30 µm) grain structure around the surface. Phases identified in initial uranium silicide pellets included: U 3 Si 2 as the main phase composing about 80 vol. %, Si rich phases (USi and U 5 Si 4 ) composing about 13 vol. %, and UO 2 composing about 5 vol. %. Initial batches from the extended U 3 Si 2 pellet fabrication had similar phases and phase quantities. The latter half of the extended fabrication pellet batches did not contain Si rich phases, and had between 1-5% UO 2 : achieving U 3 Si 2 phase purity between 95 vol. % and 98 vol. % U 3 Si 2 . The amount of UO 2 in sintered U 3 Si 2 pellets is correlated to the length of time between U 3 Si 2 powder fabrication and pellet formation. These measurements provide information necessary to optimize fabrication efforts and a baseline for future work on this fuel compound.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

ELECTRON BEAM SHAPING AND ITS APPLICATIONS

Transverse and longitudinal electron beam shaping is a crucial part of high-brightness electron accelerator operations. In this dissertation, we report on the corresponding beam dynamics research conducted at Fermilab Accelerator Science and Technology facility (FAST) and Argonne Wakeeld Accelerator (AWA). We demonstrate an experimental method for spatial laser and electron beam shaping using microlens arrays (MLAs) at a photoinjector facility. Such a setup was built at AWA and resulted in transverse emittance reduction by a factor of 2. We present transverse emittance partitioning methods that were recently employed at FAST facility. A strongly coupled electron beam was generated in an axial magnetic eld and accelerated in 1.3 GHz SRF cavities to 34 MeV. It was then decoupled in Round-To-Flat beam transformer and beams with emittance asymmetry ratio of 100 were generated. We introduce the new methods of measuring electron beam canonical angular momentum, beam transformer optimization and beam image analysis. We also describe a potential longitudinal space-charge amplier setup for FAST high-energy beamline. As an outcome, a broadband partially coherent radiation in the UV range could be generated.

43 PARTICLE ACCELERATORS↗

DOE OSTI2018

AOI [3]: Smart Refractory Sensor Systems for Wireless Monitoring of Temperature, Health, and Degradation of Slagging Gasifiers

The objective of the work was to develop refractory “smart bricks”, which would contain embedded temperature, strain/stress, and spallation sensors throughout the volume of highchromia (-Cr 2 O 3 ) refractory brick. The proposed work included work to interconnect the sensors to the reactor exterior, where the sensor signals may be processed by low-power electronics and transmitted wirelessly to a central processing hub. The data processing and wireless transmitter hardware was specifically designed to be isolated (with low power consumption) and to be adaptable to future implementation of energy-harvesting strategies for extended life. Finally, the collected data was incorporated into a model to estimate refractory degradation, a technique that could help monitor the health of the refractory in real-time. The long-term goal of this program was to demonstrate high-temperature, wireless sensor arrays for in situ three-dimensional (3-D) refractory monitoring or mapping for slagging gasification systems. The research was in collaboration with HarbisonWalker International (HWI) Technology Center in West Mifflin, PA. HWI is a leading developer and manufacturer of ceramic refractory products for high-temperature applications. The work completed focused on the following areas: 1) Investigation of the chemical stability, microstructural evolution, grain growth kinetics, degree of homogeneity (quantitative image analysis), and electrical properties of refractory oxide-silicide composites at temperatures between 750-1450ºC; 2) Fabrication of silicide-alumina composite and oxide thermocouples and thermistor preforms and the development of techniques to embed them into high-chromia refractory bricks to form “smart bricks”; 3) Utilization of commercial off-the-shelf discrete components to prototype circuits for interfacing between smart brick sensors and the wireless sensor network. The prototypes were then used to design an integrated circuit for thermistor, thermocouple, and capacitive-based smart brick sensor interfacing; 4) Interfacing of the smart bricks with embedded sensors with wireless motes thus yielding a complete signal chain. This end-to-end data collection system was tested on a furnace heated to 1350°C; 5) Development of a slag penetration model and a nonlinear unknown input filter for the data from the embedded sensors for estimating temperature and extent of slag penetration.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

An Analytical Technology Platform to Identify Symbiotic Interactions Between PGPR and Root Microbiome Members from Biofuel Feedstocks

The goal of this STTR project was to establish a commericially-viable technology platform that can be used to develop formulations of plant growth promoting rhizobacteria (PGPR) that can be used as biofertilizers for improved production of woody biomass. The platform has been designed to screen thousands of different formulations of microorganisms in search for those formulations that best support the growth and survival of PGPR species. The focus of the Phase I project was to provide the existing technology with new capabilities that define its commerical pathway. These goals were to (1) adapt the existing platform for use with Populus isolates and (2) developing a highly-automated image analysis software tool that can rapidly screen large data sets to statistically identify optimized biofertilizer formulations. The project has produced a software routine for this screening and identification need, and has generated preliminary data for use of this approach to identify symbiotic PGPR communities that may be useful for promoting Populus growth.

09 BIOMASS FUELS↗

DOE OSTI2019

High-Dimensional Spectral Sampling

A wide variety of applications in science and engineering depend on effectively and efficiently exploring high- dimensional parameter spaces. Common examples are uncertainty quantification, inverse problems, or various optimization approaches. In such applications, the first step is to create an initial uniform, random sampling of the space to create a baseline of knowledge. The simulations evaluated at these samples are then used for subsequent processing. In its most generic form, the goal of sampling is to produce the maximal amount of information with the minimal number of samples. However, despite being the first step and thus influencing the performance of the entire workflow, the quality of the initial sample designs is rarely analyzed or optimized. This project develops a new spectral sampling theory for analyzing and creating experiment designs in high-dimensional spaces. Further, new algorithms for estimating sample properties and sample synthesis are designed. Finally, applications of the proposed spectral sampling tools in surrogate modeling, scientific machine learning and image analysis are presented.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

The Diverse Science Return from a Wide-Area Survey of the Galactic Plane

The overwhelming majority of objects visible to LSST lie within the Galactic Plane. Though many previous surveys have avoided this region for fear of stellar crowding, LSST’s spatial resolution combined with its state-of-the-art Difference Image Analysis mean that it can conduct a high cadence survey of most of the Galaxy for the first time. Here we outline the many areas of science that would greatly benefit from an LSST survey that included the Galactic Plane, Magellanic Clouds and Bulge at a cadence of 2–3 d. Particular highlights include measuring the mass spectrum of black holes, and mapping the population of exoplanets in the Galaxy in relation to variations in star forming environments. But the same survey data will provide a goldmine for a wide range of science, and we explore possible survey strategies which maximize the scientific return for a number of fields including young stellar objects, cataclysmic variables and Neptune Trojans.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Slide Test FY 2019 Report

At Los Alamos, the Slide Test was developed in 2019 to investigate whether the mass of a main charge of explosive sliding on a gritty surface, in the absence of impact, is sufficient to heat grit to ignition temperatures in PBX 9501. This is a practical test to address frictional ignition during assembly/disassembly operations at the Pantex Plant. Twenty-seven Slide Tests were performed in total, testing PBX 9501 at various slide velocities, grit diameters, grit patterns, and charge masses. Time-resolved velocimetry of the slide event (from PDV) and spot area of the explosive charge (obtained from image analysis) is reported. High-speed videography is used to diagnose explosive reaction. Eighteen of these tests were performed with a charge mass of 30 lbs at velocities ≤ 4 m s-1 and grit diameters between 75 and 1000 µm. Nine Slide Tests were performed with a 15 lb charge mass at similar parameters. No ignition was observed in any of the tests. These data provide evidence that the mass of a main charge, caused to slide on a surface at the low velocities achievable during routine handling, is insufficient stimulus to heat grit to ignition temperatures. These findings are relevant to risk assessment for explosive handling operations and provide evidence that PBX 9501 is safe within the constraints that were tested. However, because ignitions were not observed in any of the tests, we cannot determine which variables (mass or velocity) dominate the explosive response and to what extent. The absence of observed ignition also precludes the determination of a safety margin. To identify this safety margin, further research would be necessary to define the velocity and/or mass threshold at which ignition occurs.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2017

Uncertainty Quantification for Machine Learning

In this paper, we assert the importance of uncertainty quantification for machine learning and sketch an initial research agenda. We define uncertainty in the context of machine learning, identify its sources, and motivate the importance and impact of its quantification. We then illustrate these issues with an image analysis example. The paper concludes by identifying several specific research issues and by discussing the potential long-term implications of uncertainty quantification for data analytics in general.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

X-ray Computed Tomography on UNESE Core: FY2020 Data Report to Support Fracture and Multiphase Fluid Flow Studies

Natural and induced fractures are potential preferential pathways for migration of radioactive gases to earths surface from underground nuclear explosions (UNEs). This report documents X-ray computed tomography (XRCT) imaging on 26 samples of rock core that was collected to support the Underground Nuclear Explosion Signatures Experiment (UNESE) program. The XRCT datasets are intended to help fill a data gap on the three-dimensional (3D) characteristics of natural and/or induced fractures at the centimeter and smaller scale, which may strongly influence multiphase fluid flow and transport properties of preferential flow paths and interaction with the matrix of the surrounding host rock. Pre- and post-UNE rock samples were carefully chosen to enable comparison of fractures as a function of lithologic and petrophysical properties, as well as distance to the past UNEs. This report serves as documentation for the data, including an introduction with the research motivation, a methods and materials section, descriptions of the XRCT datasets without post-processing, and recommendations for 3D quantification via image analysis and digital rock physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗