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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multimodal Defect Imaging of Pure Tungsten Components Fabricated via Electron Beam Powder Bed Fusion

The utilization of additive manufacturing (AM) techniques for refractory materials in high-temperature environments has significantly expanded because of the ability to fabricate geometrically complex components. Electron beam powder bed fusion (EB-PBF), which provides lower residual stress, a cleaner vacuum environment, and better efficiency for high melting point, is one of the best-suited AM methods to produce advanced refractory components. However, the property variation attributed to the heterogeneous microstructure and process-induced defects has hindered the widespread adoption of EB-PBF-produced material like tungsten. While numerous in-situ monitoring and defect detection methods have been demonstrated for EB-PBF, a workflow that compares and evaluates process-induced abnormalities from different imaging perspectives is still limited. This study examines a feature-embedded tungsten component manufactured via the EB-PBF process to demonstrate the defect detection capabilities of a multimodal defect imaging workflow. The predefined and process-induced defects are evaluated by harnessing various imaging techniques, including in-situ electron imaging, layerwise near-infrared (NIR) imaging, post-build high-energy x-ray computed tomography (CT), and conventional destructive metallography. The results highlight the strengths and limitations of distinctive defect imaging techniques concerning specific defect types, sizes, and conditions. It was found that electron imaging can provide more abnormal detection capabilities while maintaining a higher measuring accuracy, against the conventional metallography in this case study, compared with NIR and CT imaging techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Heterogeneous fatigue damage in a nickel-based single-crystal superalloy unraveled using correlative 3D X-ray technology

Nickel-based single-crystal (Ni-SX) superalloys under cyclic stress are susceptible to cracking at stress-concentration sites, eventually leading to low-cycle fatigue (LCF) failure. LCF cracks typically originate from intrinsic defects (e.g., voids and carbides) within solidified dendrites. However, systematic quantitative experimental analyses of defect-mediated local damage remain limited. To thoroughly understand the microscopic origins and evolution of LCF damage, correlated 3D mapping of dendrites across various regions is essential. Here, in this study, macroscale micro-computed tomography (μ-CT) was initially used to capture internal interdendritic secondary cracks within bulk DD413 superalloy after LCF testing at 760 °C. Subsequently, a multimodal methodology combining synchrotron 3D microdiffraction (3D-μXRD), high-resolution μ-CT, and electron microscopy was established. This approach allowed precise localization of internal damage zones near interdendritic secondary cracks and detailed mapping of the 3D correlated distributions of dendrites, defects, and residual stress/strain fields within these zones at submicron spatial resolution. Finally, the same approach was applied to specimens subjected to interrupted loading at approximately 40 % of the fatigue life to uncover the early damage states of dendrites. The dendrite cores (DCs) and interdendritic regions (IDs) exhibit microscale heterogeneous mechanical responses: nearly defect-free DCs accumulate local irreversible slip along specific slip systems to generate slip bands, while the IDs containing various defects accommodate local microplasticity through the activation of multiple slip systems around these defects. The local tensile stress near defects in the IDs exceeds that in the DC slip band regions by more than threefold, leading to the generation of local damage zones within the IDs. Chain-like defect distributions facilitate the interconnection of these local zones into a continuous damage region, further elevating the overall tensile stress in the IDs. Additionally, geometrically necessary dislocations alone are insufficient as indicators of LCF damage; both the internal stress state and its magnitude must be considered. These experimental results provide critical data and insights for the development of multi-physics fatigue models.

Localized deformation↗
DOE OSTI2022

In situ laser profilometry for material segmentation and digital reconstruction of a multicomponent additively manufactured part

In addition to its ability to produce geometrically complex parts, additive manufacturing offers a unique opportunity to collect data about a component while it is being fabricated. However, there has only been limited effort to characterize parts morphologically and compositionally in situ. In this article, we present a layer-by-layer, laser profilometry-based in situ characterization technique as a method to digitally reconstruct a multi-material part. Data collected by the laser profilometer yields height maps and grayscale images which are voxelized using purpose-built software to volumetrically reconstruct the part. Additionally, the same part was also analyzed using X-ray computed tomography (CT) which was not able to resolve the different compositional regions within the part, but captured the filament morphology. The part was then bisected to compare the digital reconstruction to the actual part morphology and composition. Overall, the digital reconstruction was in good agreement with both the CT and bisected images. Deviations between the digital reconstruction and the CT/bisected images are likely the result of image segmentation settings or material shifts after data was collected. The in situ characterization method demonstrated here sets the stage for real time process monitoring and paves the way for additively manufactured parts that are “born qualified.”

36 MATERIALS SCIENCE↗
DOE OSTI2020

The role of the spatial heterogeneity and correlation length of surface wettability on two-phase flow in a CO 2 -water-rock system

This study characterized and modeled heterogeneous surface wettability in sandstone and investigated the role of spatial heterogeneity and correlation length of surface wettability on relative permeability in a supercritical CO 2 (scCO 2 )-brine-rock system. Understanding the role of wettability heterogeneity on relative permeability is essential to geological CO 2 sequestration, oil and gas recovery, and contaminated groundwater remediation. Although numerous studies have attempted to understand the influences of surface wettability, capillary number (Ca), and viscosity ratio, the role of the spatial variation and correlation length of surface wettability on two-phase flow in three-dimensional (3D) porous media has not been unraveled due to the challenges in the measurement and representation of realistic rock surface wettability. In this work, we conducted in-situ measurements of surface contact angle (CA) in a Bentheimer sandstone after CO 2 flooding using micro-computed tomography (micro-CT), and found that the pore-scale CA distribution on rock surfaces followed a log-normal distribution associated with a spatial correlation length. Based on the statistical information from CT scanning, a Gaussian random field was used to model CA distributions that had desired standard deviations and spatial correlation lengths, which were then adjusted within a certain range of values for sensitivity analyses to study their combined effects on the two-phase flow in the porous medium using the lattice Boltzmann (LB) method. The LB two-phase flow simulation was accelerated using hybrid, multicore parallel computing to overcome the challenges in simulating multiphase flow in a large 3D domain having 800 × 800 × 600 nodes. The simulation results showed that the surface wettability heterogeneity (i.e., standard deviation of CA) had a lesser effect on the relative permeability of the wetting fluid (water) but a more significant impact on the relative permeability of the non-wetting fluid (scCO 2 ). The Corey model was used to fit the LB-simulated relative permeability curves of water and scCO 2 and showed that the variations in the relative permeability curves for both water and scCO 2 increased as the standard deviation and spatial correlation length of CA increased. This study illustrated that the assumption of homogeneous surface wettability may cause errors in multiphase flow simulations. Furthermore, the impacts of both the standard deviation and spatial correlation length of CAs should be accounted for. This is the first study that explored the spatial correlation lengths associated with CA distributions on sandstone surfaces and comprehensively investigated the roles of both spatial variation and correlation length of CA on two-phase flow properties in 3D porous media. The optimized LB multiphase flow model was proved a powerful tool to study the interplays and combined effects of these statistical parameters, which had critical applications in numerous natural and engineering processes that involved multiphase flow in porous media.

58 GEOSCIENCES↗
DOE OSTI2025

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗
DOE OSTI2022

Dynamic fracture of glass fiber-reinforced ductile polymer matrix composites and loading rate effect

Here, the dynamic fracture of S-2 glass fiber-reinforced polymer matrix composites (FRPMCs) was investigated in this study. The matrix ductility was improved by a recently developed network topology modification technique via mixing partially reacted substructures (mPRS). The composite material was manufactured and characterized by micro-CT scanning and scanning electron microscopy (SEM). Dynamic single-edge notched bending (d-SENB) experiments were performed on the composites by using a modified split-Hopkinson pressure bar. Each specimen’s fracture process was visualized by ultrafast X-ray imaging. Such in-situ radiography enabled identifying the damage initiation below 50-micron scale and inspecting its propagation through the internal structures of opaque composites, thereby accurately quantifying the composites’ mechanical properties. Furthermore, the identical d-SENB experiments were designed and the digital image correlation (DIC) was employed to monitor the stress wave propagation on the composite specimens. The force and deflection measurements were modified and correlated to the physical damage processes. Besides, quasi-static SENB experiments were conducted to identify the loading rate effects on the composites’ fracture behaviors. The force and deflection history, bending stiffness, energy dissipation, and fracture toughness at different loading rates were quantified and compared. Finally, post-fracture analysis by micro-CT scanning and SEM provided physical observations on the variation of the fracture morphology by different loading rates.

42 ENGINEERING↗
DOE OSTI2022

In-situ imaging of flexure-induced fracture in tape-laminate composites using high-resolution X-ray computed tomography

Here, this study presents development of an in-situ flexure test for imaging progressive inter- and intralaminar fracture in tape-laminate composites using X-ray computed tomography (CT). The intent of this test is to provide detailed experimental observations of ply-level damage that can be used to validate existing, and develop new, progressive damage analysis (PDA) tools. The test consists of a vertically mounted specimen which is flexed using two eccentric compressive loads using an in-situ uniaxial load stage. The flexure specimen contains a starter notch mid-span which promotes initiation of composite failure within the X-ray field of view. Specimens with two different laminate stacking sequences were tested, imaged, analyzed. For a quasi-isotropic laminate with large angle changes between adjacent plies, there was near simultaneous growth of transverse cracks and delaminations below the midplane of the laminate. For a laminate with small angles between adjacent plies, there was extensive formation of transverse crack networks which penetrated the laminate thickness without delamination growth. In addition to imaging fracture, the X-ray CT data from both specimen types were used to quantify the variability in thickness and analyze the local orientation of individual plies. Overall, the proposed test and the image-data analysis methodology provided an important insight into the fracture processes in tape laminates and highlights the inherent ply-level geometrical variabilities that should be accounted for in PDA simulations.

42 ENGINEERING↗
DOE OSTI2025

Effect of cell compression on the performance and the structure of proton exchange membrane water electrolyzer (PEMWE) assembly

Here, in the field of water electrolysis, the proton exchange membrane water electrolyzer (PEMWE) is currently the most advanced technology for producing hydrogen without emitting CO 2 . Although PEMWE plants are already in operation, further research is needed to improve cell efficiency and reduce the use of rare materials, such as iridium oxide catalysts for the oxygen evolution reaction (OER). One of the main causes of performance loss in PEMWE is the relatively low electric conductivity of the porous transport layer (PTL) and of the anode catalyst layer, which results in ohmic losses and low catalyst utilization during high current density operation. The objective of this study is to investigate how optimization of the PTL and electrode interface can increase the cell performance. To this end, we tested different cell assemblies using fibrous and sintered PTLs, decreasing membrane thickness, reducing iridium loading, and inserting a microporous layer to increase contact surface area. Electrochemical characterization of each cell configuration was systematically performed at various compression levels as the pressure is a crucial parameter influencing the electrode/PTL contact area. In parallel, X-ray microcomputed tomography (micro-CT) was employed to investigate the effects of cell hydration and compression on the structure of PEMWE components. This study combining electrochemistry and micro-CT imaging presents how optimizing the electrode/PTL contact surface area, minimizes ohmic losses, and enables PEMWE operation with low iridium loading at high current densities.

Catalyst - PTL interface↗
DOE OSTI2023

Assessing pore network heterogeneity across multiple scales to inform CO2 injection models

Geologic heterogeneity is a key feature that must be considered when translations of scaled data are performed. This paper presents the assessment of geologic heterogeneity using a multiscale workflow that includes image analysis-based methods coupled with well log analysis to provide data in which fractals and machine learning methods estimate the carbon dioxide (CO 2 ) storage resource potential of a reservoir. The heterogeneity of rock properties of the complex Bell Creek reservoir in Montana, USA, was explored at the pore scale (~nm to mm), core scale (~mm to m), and well scale (~cm to m). The data used in this study included advanced image analysis of micro-CT (computed tomography) images (pore scale), thin sections (pore scale), plugs and core images (core scale) and well logs (well scale). The micro-CT images were segmented using a U-net segmentation approach into objects of pores and grains. Further, the segmented images were reconstructed into subvolumes of different sizes. Physical properties (porosity and permeability) and fractal dimensions were calculated for the various subvolumes, and Lorenz coefficient (Lc) values, a single parameter to describe the degree of heterogeneity within a pay zone section, were calculated from thin-section images and well logs. Porosity and fractal dimension values were used to estimate the 188-µm threshold of representative elementary volume (REV) in this study. Both the Lc and fractal dimension values were found to be negatively correlated. When these two parameters are combined, it is possible to discern differences in the complex porous networks of the samples analyzed in this study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Dose Fractionation During Puberty Is More Detrimental to Mammary Gland Development Than an Equivalent Acute Dose of Radiation Exposure

Computed tomographic (CT) scans in adolescents have increased dramatically in recent years. However, the effects of cumulative low-dose exposures on the development of radiation sensitive organs, such as the mammary gland, is unknown. The purpose of this work was to define the effects of dose rate on mammary organ formation during puberty, an especially sensitive window in mammary development. We used a fractionated low-dose x-ray exposure to mimic multiple higher dose CT scans, and we hypothesized that fractionated exposure would have less of an effect on the number of mammary gland defects compared with an acute exposure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Efficient bi-directional coupling of 3D computational fluid-particle dynamics and 1D Multiple Path Particle Dosimetry lung models for multiscale modeling of aerosol dosimetry

The development of predictive aerosol dosimetry models has been a major focus of environmental toxicology and pharmaceutical health research for decades. One-dimensional (1D) models successfully predict overall deposition averages but fail to accurately predict local deposition. Computational fluid-particle dynamics (CFPD) models provide site-specific predictions but at a computational cost that prohibits whole lung predictions. Thus, there is a need for developing multiscale strategies to provide a realistic subject-specific picture of the fate of inhaled aerosol in the lungs. CT-based 3D/CFPD models of the large airways were bidirectionally coupled with individualized 1D Navier-Stokes airflow and particle transport based upon the widely used Multiple Path Particle Dosimetry Model (MPPD). Distribution of airflows among lobes was adjusted by measured lobar volume changes observed in CT images between FRC and FRC + 1.5 L. Additionally, as a test of the effectiveness of the coupling procedures, deposition modeling of previous 1 µm aerosol exposure studies was performed. The complete coupled model was run for 3 breaths, with the computation-intense portion being the 3D CFD Lagrangian particle tracking calculation. The average deposition per breath was 11% in the combined multiscale model with site-specific doses available in the CFPD portion of the model and airway- or region-specific deposition available for the MPPD portion. In conclusion, the key methods developed in this study enable predictions of ventilation heterogeneities and aerosol deposition across the lungs that are not captured by 3D or 1D models alone. Overall, these methods can be used as the foundation for multi-scale modeling of the full respiratory system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Subject-specific modeling framework for particle deposition using computational fluid dynamics

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

AI↗
DOE OSTI2021

Proton-detected solid-state NMR spectroscopy of spin-1/2 nuclei with large chemical shift anisotropy

Constant-time (CT) dipolar heteronuclear multiple quantum coherence (D-HMQC) has previously been demonstrated as a method for proton detection of high-resolution wideline NMR spectra of spin-1/2 nuclei with large chemical shift anisotropy (CSA). However, 1 H transverse relaxation and t 1 -noise often reduce the sensitivity of D-HMQC experiments, preventing the theoretical gains in sensitivity provided by 1 H detection from being realized. In this paper, we demonstrate a series of improved pulse sequences for 1 H detection of spin-1/2 nuclei under fast MAS, with 195 Pt SSNMR experiments on cisplatin as an example. First, a t 1 -incrementation protocol for D-HMQC dubbed Arbitrary Indirect Dwell (AID) is demonstrated. AID allows the use of arbitrary, rotor asynchronous t 1 -increments, but removes the constant time period from CT D-HMQC, resulting in improved sensitivity by reducing transverse relaxation losses. Next, we show that short high-power adiabatic pulses (SHAPs), which efficiently invert broad MAS sideband manifolds, can be effectively incorporated into 1 H detected symmetry-based resonance echo double resonance (S-REDOR) and t 1 -noise eliminated (TONE) D-HMQC experiments. The S-REDOR experiments with SHAPs provide approximately double the dipolar dephasing, as compared to experiments with rectangular inversion pulses. We lastly show that sensitivity and resolution can be further enhanced with the use of swept excitation pulses as well as adiabatic magic angle turning (aMAT).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Voltage cycling as a dynamic operation mode for high temperature electrolysis solid oxide cells

Solid Oxide Electrolysis Cells (SOECs) have emerged as a promising technology for the efficient production of H2 via high-temperature electrolysis. However, power input from dynamic energy sources remains a significant challenge for their long-term stability. It is important to analyze the tolerance of cells under dynamic operation conditions. This study focuses on evaluating the impact of voltage cycling on the performance and durability of electrode-supported SOECs. We explore the operational limits and degradation mechanisms of SOECs subjected to various voltage conditions and find that the cells have high tolerance for dynamic voltage. Voltage cycling between 1.3 V and 1.5 V for 9000 cycles does not damage the cell. Conversely, cycling to higher voltages (≥1.7 V) results in accelerated degradation. Advanced characterization is used to screen for various degradation modes post operation. Within the oxygen electrode, XRD and STEM EDS find compositional and phase evolution in all voltage cycled samples including increased decomposition of the air electrode resulting in cation migration. Microstructural analysis of the fuel electrode from nano-CT data shows minimal change throughout the sample set and no evidence of Ni migration, indicating the fuel electrode is stable and not impacted by cycling to higher voltages within the timeframe studied.

Zhu, Zhikuan↗
DOE OSTI2022

Three-dimensional microstructure of a friction stir welded magnesium/steel interface characterized via high-energy synchrotron X-rays

Here, the three-dimensional (3D) microstructure of a friction stir assisted scribe technique (FaST) weld interface consisting of AZ31 magnesium (Mg) alloy and zinc (Zn)-coated DP590 steel was analyzed via synchrotron micro-computed tomography (μ-CT), correlated to synchrotron x-ray diffraction, and electron microscopy. Diffraction assessment of the AZ31/Zn-coated DP590 steel interface revealed the presence of several complex Mg–Zn intermetallic phases and differences in crystalline orientation of the Mg phase at the weld interface. The 3D characterization of the synchrotron μ-CT images of the weld interface revealed: (1) the presence of AZ31 weld nugget material with iron (Fe)-rich particles; (2) the presence of a weld layer at the joining interface with Fe-rich particles; (3) the formation of a thin non-uniform layer between the weld layer and the interface of the scribed DP590 material; and (4) the presence of an Fe–Al-rich intermetallic layer and Fe-rich particles at the interface of the scribed DP590 material. This study also performed a detailed analysis of lump-like features seen in the Zn coating layer at the weld interface. A detailed 3D particle analysis of the Fe-rich particles in the AZ31 weld nugget and the weld layer at the weld interface revealed the presence of several types of particle morphologies (i.e., spherical and irregular).

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine learning-assisted upscaling analysis of reservoir rock core properties based on micro-computed tomography imagery

Optimum solutions for geologic modeling and reservoir simulation in industries such as oil and gas recovery and carbon capture and storage require accurate characterization of reservoir properties, which are often heterogeneous. In this study, high-quality micro-computed tomography (CT) images (1.475-μm/pixel resolution) of a sandstone core acquired from the Bell Creek oil field, USA, were used to provide nondestructive analysis of pore- and core-scale heterogeneity across measurement scales of 94–566 μm. In addition to characterizing the as-received sample, the core sample was flooded with brine to evaluate the capacity of the core sample to receive injected fluids. The micro-CT images were systematically segmented into pore spaces and grains via machine learning (ML) steps including image preprocessing, label creation using a traditional ML method based on limited manual image annotation, and finally U-Net segmentation. The segmented image stacks were reconstructed into digital cubes of various scales of voxel lengths. The 3D porosity values were calculated for all the digital cubes, and the fractal dimensions of the cubes were estimated using a box-counting method. The results showed that smaller cubes had greater heterogeneity and that the porosity values could be accurately estimated by fractal dimension and voxel lengths using ML models. For the core sample with brine flooding, the ratio of pores filled by brine to the total pore space was related to the porosity and could also be accurately estimated by porosity, fractal dimension, and voxel lengths using ML models. In conclusion, the results of this study demonstrate that the concept of fractal dimension can be a useful vector to perform upscaling analysis of sandstone rock heterogeneity from the pore to core scale and that fractal dimensions can be used to estimate porosity values and pore space-filling capacity across those scales.

58 GEOSCIENCES↗
DOE OSTI2026

While legume-based rotation influences the chemical composition of mineral-associated organic matter, tillage has little effect on its persistence

Legume-based rotations are key to enhancing soil carbon (C) storage in stable forms such as mineral-associated organic matter (MAOM), improving soil health, and helping maintain long-term C stock. This study investigates how plant inputs and tillage practices influence the distribution, composition, and persistence of MAOM in wheat cropping systems when legumes are incorporated into the rotation. Soil samples were collected from Walla Walla silty loam of northeast Oregon, including conventional tillage (CT) and no-till (NT) treatments in a long-term dryland winter wheat (Triticum aestivum L.) and spring pea (Pisum sativum L.) rotation experiment, with an adjacent grass pasture (GP) plot serving as the baseline. Bulk soil, particulate organic matter (POM), and MAOM fractions were scanned using mid-infrared (Mid-IR) spectroscopy and analyzed for total C and nitrogen (N) as well as radiocarbon age, aggregate stability, and mineralizable C. In WP systems, NT promoted greater C accumulation and stabilization in MAOM than CT, reaching levels similar to those under native GP conditions. Furthermore, our findings indicate that decades of continuous legume-based rotation were insufficient to restore total bulk C content to levels observed in the undisturbed reference site (GP) in the 0–30 cm layer, with increases limited to the surface layer. The Mid-IR data provided insights into how cultivation may alter the chemical composition of MAOM. An increase in amide bands was observed in GP, while legume-based rotation systems favored an abundance of aliphatic (C-H) components in the MAOM fraction. In cultivated soils, C in MAOM exhibited longer residence times under arable conditions than in grassland, while POM remained an actively cycled pool across all treatments. Despite variations in the chemical composition of MAOM across treatments, mineralizable C emissions from MAOM fractions remained statistically unchanged during the 96-hour incubation period. Our findings suggest that soil physical protection, enhanced by reduced tillage, is the primary factor influencing MAOM cycling.

Carbon stabilization↗