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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Plant science decadal vision 2020–2030: Reimagining the potential of plants for a healthy and sustainable future

Abstract Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and "green infrastructure." Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a "parts store" that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people's natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Imaging a solvent-swollen polymer gel network by open liquid transmission electron microscopy

Visualizing the network of a solvent-swollen polymer gel remains problematic. To address this challenge, open transmission electron microscopy (TEM) was applied to thin gel films permeated by a nonvolatile ionic liquid. The targeted physical gels were prepared by cooling concentrated solutions of poly(ethylene glycol) in 1-ethyl-3-methyl imidazolium ethyl sulfate [EMIM][EtSO 4 ]. During the cooling, gelation occurred by a frustrated crystallization of the dissolved polymer, leading to a percolated, solvent-permeated semicrystalline network in which nanoscale polymer crystals acted as crosslinks. Crystalline features ranging from ~5 to ~200 nm were observed, with the visible network strands dominantly consisting of long curvilinear crystallites of ~15–20 nm diameter. Nascent spherulites irregularly decorated the network, creating a complex structural hierarchy that complicated analyses. Lacking diffraction contrast, TEM did not visualize the many disordered, fully solvated PEG chains present in the voids between crystals. Finally, recognizing that a network's three dimensionality is ambiguous when assessed through two-dimensional microscopy projections, a small gel region was studied by TEM tomography, revealing a nearly isotropic three-dimensional arrangement of the curvilinear crystallites, which displayed remarkably uniform cylindrical cross sections.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Spatial analysis of cell patterning to aid genetic and phenotypic understanding of grass stomatal density: A case study in maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Informing forest carbon inventories under the Paris Agreement using ground-based forest monitoring data

Human interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net-zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi-automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net-zero motivated future. Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well-documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi-automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground-based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground-based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Internet of Samples

Abstract Material samples are indispensable data sources in many natural science, social science, and humanity disciplines. More and more researchers recognize that samples collected in one discipline can be of great value for another. This has motivated organizations that manage a large number of samples to make their holdings accessible to the world. Currently, multiple projects are working to connect natural history and other samples managed by individual institutions or individuals into a universe of samples that follow FAIR principles. This poster reports the progress of the US NSF‐funded iSamples project, in the context of other efforts initiated by US DOE, DiSCCo, BCoN, and GBIF. By October 2021, we will also be able to present an iSamples prototype. We encourage individual organizations that hold material samples to get to know these projects and help shape these projects to realize the goal of a global linked sample cloud that connects all material samples and is accessible to all.

Richard, Stephen M.↗
DOE OSTI2026

Data‐Efficient Generation of Synthetic Microstructures of Polymer‐Bonded Energetic Material With Fine‐Tuned Stable Diffusion

Among current deep learning approaches for synthetic image generation, diffusion-based models stand out in terms of algorithmic stability and ability to retain high-fidelity image features with detailed resolution. Here, in this work, we employ Dreambooth, a method for fine-tuning Stable Diffusion, on X-ray CT images of microstructure of the polymer-bonded form (PBX) of a commonly used high explosive, Pentaerythritol tetranitrate (PETN), which yields generative models for creating synthetic PBX images. The models developed here represent five classes (or ‘lots’) of microstructures and demonstrate successful generation of images of each class with high fidelity, as verified by computed classification accuracy of ∼ 94% or higher. Data augmentation afforded by such image synthesis can be used to more reliably decipher underlying statistics, build processing-structure correlations, recognize off-normal structural anomalies, and identify age-related changes. Ideas related to converting image data into appropriate density mapping and performing mesoscale simulation or surrogate modeling of detonation are also discussed.

Dreambooth↗
DOE OSTI2016

Glutathione transferase P1‐1 as an arsenic drug‐sequestering enzyme

Abstract Arsenic‐based compounds are paradoxically both poisons and drugs. Glutathione transferase (GSTP1‐1) is a major factor in resistance to such drugs. Here we describe using crystallography, X‐ray absorption spectroscopy, mutagenesis, mass spectrometry, and kinetic studies how GSTP1‐1 recognizes the drug phenylarsine oxide (PAO). In conditions of cellular stress where glutathione (GSH) levels are low, PAO crosslinks C47 to C101 of the opposing monomer, a distance of 19.9 Å, and causes a dramatic widening of the dimer interface by approximately 10 Å. The GSH conjugate of PAO, which forms rapidly in cancerous cells, is a potent inhibitor ( K i = 90 n M ) and binds as a di‐GSH complex in the active site forming part of a continuous network of interactions from one active site to the other. In summary, GSTP1‐1 can detoxify arsenic‐based drugs by sequestration at the active site and at the dimer interface, in situations where there is a plentiful supply of GSH, and at the reactive cysteines in conditions of low GSH.

Parker, Lorien J.↗
DOE OSTI2018

S tructural basis for tankyrase‐RNF146 interaction reveals noncanonical tankyrase‐binding motifs

Abstract Poly(ADP‐ribosyl)ation (PARylation) catalyzed by the tankyrase enzymes (Tankyrase‐1 and ‐2; a.k.a. PARP‐5a and ‐5b) is involved in mitosis, telomere length regulation, GLUT‐4 vesicle transport, and cell growth and differentiation. Together with the E3 ubiquitin ligase RNF146 (a.k.a. Iduna), tankyrases regulate the cellular levels of several important proteins including Axin, 3BP2, and angiomotins, which are key regulators of Wnt, Src and Hippo signaling, respectively. These tankyrase substrates are first PARylated and then ubiquitylated by RNF146, which is allosterically activated by binding to PAR polymer. Each tankyrase substrate is recognized by a tankyrase‐binding motif (TBM). Here we show that RNF146 binds directly to tankyrases via motifs in its C‐terminal region. Four of these RNF146 motifs represent novel, extended TBMs, that have one or two additional amino acids between the most conserved Arg and Gly residues. The individual RNF146 motifs display weak binding, but together mediate a strong multivalent interaction with the substrate‐binding region of TNKS, forming a robust one‐to‐one complex. A crystal structure of the first RNF146 noncanonical TBM in complex with the second ankyrin repeat domain of TNKS shows how an extended motif can be accommodated in a peptide‐binding groove on tankyrases. Overall, our work demonstrates the existence of a new class of extended TBMs that exist in previously uncharacterized tankyrase‐binding proteins including those of IF4A1 and NELFE.

DaRosa, Paul A.↗
DOE OSTI2020

Structural characterization and computational analysis of PDZ domains in Monosiga brevicollis

Abstract Identification of the molecular networks that facilitated the evolution of multicellular animals from their unicellular ancestors is a fundamental problem in evolutionary cellular biology. Choanoflagellates are recognized as the closest extant nonmetazoan ancestors to animals. These unicellular eukaryotes can adopt a multicellular‐like “rosette” state. Therefore, they are compelling models for the study of early multicellularity. Comparative studies revealed that a number of putative human orthologs are present in choanoflagellate genomes, suggesting that a subset of these genes were necessary for the emergence of multicellularity. However, previous work is largely based on sequence alignments alone, which does not confirm structural nor functional similarity. Here, we focus on the PDZ domain, a peptide‐binding domain which plays critical roles in myriad cellular signaling networks and which underwent a gene family expansion in metazoan lineages. Using a customized sequence similarity search algorithm, we identified 178 PDZ domains in the Monosiga brevicollis proteome. This includes 11 previously unidentified sequences, which we analyzed using Rosetta and homology modeling. To assess conservation of protein structure, we solved high‐resolution crystal structures of representative M. brevicollis PDZ domains that are homologous to human Dlg1 PDZ2, Dlg1 PDZ3, GIPC, and SHANK1 PDZ domains. To assess functional conservation, we calculated binding affinities for mbGIPC, mbSHANK1, mbSNX27, and mbDLG‐3 PDZ domains from M. brevicollis . Overall, we find that peptide selectivity is generally conserved between these two disparate organisms, with one possible exception, mbDLG‐3. Overall, our results provide novel insight into signaling pathways in a choanoflagellate model of primitive multicellularity.

Gao, Melody↗
DOE OSTI2022

Structural and biochemical analyses of selectivity determinants in chimeric Streptococcus Class A sortase enzymes

Abstract Sequence variation in related proteins is an important characteristic that modulates activity and selectivity. An example of a protein family with a large degree of sequence variation is that of bacterial sortases, which are cysteine transpeptidases on the surface of gram‐positive bacteria. Class A sortases are responsible for attachment of diverse proteins to the cell wall to facilitate environmental adaption and interaction. These enzymes are also used in protein engineering applications for sortase‐mediated ligations (SML) or sortagging of protein targets. We previously investigated SrtA from Streptococcus pneumoniae , identifying a number of putative β7–β8 loop‐mediated interactions that affected in vitro enzyme function. We identified residues that contributed to the ability of S. pneumoniae SrtA to recognize several amino acids at the P1′ position of the substrate motif, underlined in LPXT G , in contrast to the strict P1′ Gly recognition of SrtA from Staphylococcus aureus . However, motivated by the lack of a structural model for the active, monomeric form of S. pneumoniae SrtA, here, we expanded our studies to other Streptococcus SrtA proteins. We solved the first monomeric structure of S. agalactiae SrtA which includes the C‐terminus, and three others of β7–β8 loop chimeras from S. pyogenes and S. agalactiae SrtA. These structures and accompanying biochemical data support our previously identified β7–β8 loop‐mediated interactions and provide additional insight into their role in Class A sortase substrate selectivity. A greater understanding of individual SrtA sequence and structural determinants of target selectivity may also facilitate the design or discovery of improved sortagging tools.

Gao, Melody↗
DOE OSTI2025

Human IgE monoclonal antibodies define two unusual epitopes trapping dog allergen Can f 1 in different conformations

Abstract Molecular analysis of interactions between IgE antibody and allergen allows the structural basis of IgE recognition to be defined. Human IgE (hIgE) epitopes of respiratory lipocalin allergens, including Can f 1, remain elusive due to a lack of IgE‐allergen complexes. This study aims to map the structure of allergenic epitopes on Can f 1. The fragment antigen‐binding (Fab) regions of Can f 1 specific human IgE monoclonal antibodies (hIgE mAb) were used to determine the structures of IgE epitopes. Epitope mutants were designed to target Can f 1 epitopes. Immunoassays and a human FcεRIαtransgenic mouse model of passive anaphylaxis in vivo were used to assess the functional activity of epitope mutants. Crystal structures of natural or recombinant Can f 1 complexed with two hIgE mAb 1J11 and 12F3 Fabs, respectively, were determined. The hIgE mAb bound to two partially overlapping epitopes and recognized two different Can f 1 conformations. The hIgE mAb 12F3 showed an unusual mode of binding by protruding its heavy chain CDR3 inside the Can f 1 calyx. Epitope mutants generated based on the structural analyses displayed a 64%–89% reduction in IgE antibody binding and failed to induce passive anaphylaxis in a human FcεRIαtransgenic mouse model. In summary, the structures of Can f 1‐hIgE Fab complexes revealed two unique and partially overlapping epitopes on Can f 1. The modification of the identified IgE epitopes provides a pathway for the design of hypoallergens to treat dog allergies.

Biochemistry & Molecular Biology↗
DOE OSTI2025

Nuclear Magnetic Resonance ‐based fragment screen of the E3 ligase Fem‐1 homolog B

Abstract Targeted protein degradation using PROTACs (PROteolysis TArgeting Chimeras) has emerged as a transformative therapeutic strategy, largely relying on a small number of E3 ubiquitin ligases such as CRBN and VHL. However, resistance, toxicity, and poor oral bioavailability limit the utility of PROTACs and highlight the need to expand the E3 ligase toolbox. Fem‐1 homolog B (FEM1B) is a lesser‐known E3 ligase that offers a promising alternative due to its broad expression and ability to recognize diverse degron motifs. Here, we describe the development of a stable construct of FEM1B, the results of a protein‐observed NMR‐based fragment screen using this construct, and the X‐ray structures of some of the fragment hits when bound to the protein. From these results, new PROTACs utilizing FEM1B as the E3 ligase may be discovered, providing an alternative E3 ligase for targeted protein degradation.

Katinas, Jade M. [Department of Biochemistry Vande↗
DOE OSTI2021

Improving protein tertiary structure prediction by deep learning and distance prediction in CASP14

Abstract Substantial progresses in protein structure prediction have been made by utilizing deep‐learning and residue‐residue distance prediction since CASP13. Inspired by the advances, we improve our CASP14 MULTICOM protein structure prediction system by incorporating three new components: (a) a new deep learning‐based protein inter‐residue distance predictor to improve template‐free (ab initio) tertiary structure prediction, (b) an enhanced template‐based tertiary structure prediction method, and (c) distance‐based model quality assessment methods empowered by deep learning. In the 2020 CASP14 experiment, MULTICOM predictor was ranked seventh out of 146 predictors in tertiary structure prediction and ranked third out of 136 predictors in inter‐domain structure prediction. The results demonstrate that the template‐free modeling based on deep learning and residue‐residue distance prediction can predict the correct topology for almost all template‐based modeling targets and a majority of hard targets (template‐free targets or targets whose templates cannot be recognized), which is a significant improvement over the CASP13 MULTICOM predictor. Moreover, the template‐free modeling performs better than the template‐based modeling on not only hard targets but also the targets that have homologous templates. The performance of the template‐free modeling largely depends on the accuracy of distance prediction closely related to the quality of multiple sequence alignments. The structural model quality assessment works well on targets for which enough good models can be predicted, but it may perform poorly when only a few good models are predicted for a hard target and the distribution of model quality scores is highly skewed. MULTICOM is available at https://github.com/jianlin-cheng/MULTICOM_Human_CASP14/tree/CASP14_DeepRank3 and https://github.com/multicom-toolbox/multicom/tree/multicom_v2.0 .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Assessing whole-sounder removal versus traditional control for reducing invasive wild pig ( Sus scrofa ) populations

Trapping is commonly used as the primary management tool in attempts to reduce invasive wild pigs (Sus scrofa), but traditional trapping techniques are often ineffective. However, recently developed traps permit the capture of entire social groups (sounders) of wild pigs, and the strategy of whole-sounder removal may achieve more effective control. Our objective was to experimentally compare traditional control (TC; primarily traditional trapping, but including hunting with dogs, and opportunistic shooting) and whole-sounder removal (WSR) strategies by assessing density reduction and removal rate after 1 and 2 years of treatment. After 1 year of trapping, average wild pig density on WSR units declined 53% and remained stable after the second year, whereas on TC units, pig density did not differ after trapping, although it declined 33% and remained stable after the second year of trapping. The median removal rate (percentage of uniquely marked pigs present at the beginning of each year that were removed) was 42.5% for WSR units and 0.0% for TC units during 2018 and were 29.6% from WSR units and 5.3% from TC units during 2019. WSR removal was more effective at reducing wild pig density than TC, but factors such as previous exposure of this population to traditional traps and the lack of barriers to recolonization from surrounding areas may have reduced WSR efficacy. WSR can effectively reduce wild pig density to a greater extent than TC, but managers should recognize the additional time and expense necessary for implementation.

Sus scrofa↗
DOE OSTI2016

On the sizes and lifetimes of cold pools

Cold pools of air, which are formed by evaporating precipitation, play a critical role in the triggering of new precipitation. Despite their recognized importance, little effort has been devoted to building simple models of their dynamics. Here, analytical equations are derived for the radius, height, and buoyancy of a cylindrical cold pool as a function of time, and a scale analysis reveals that entrainment is a dominant influence. These governing equations yield simple expressions for the maximum sizes and lifetimes of cold pools. The terminal radius of a cold pool is relatively insensitive to its initial conditions, with a typical maximum radius of about 14 times the initial radius, give or take a factor of 2. The terminal time of a cold pool, on the other hand, can vary over orders of magnitude depending on its initial potential and kinetic energies. Lastly, these predictions are validated against large-eddy simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Table of Standard Atomic Weights—an exercise in consensus

The present Table of Standard Atomic Weights (TSAW) of the elements is perhaps one of the most familiar datasets in science. Unlike most parameters in physical science whose values and uncertainties are evaluated using the “Guidelines for Uncertainty in Measurement” (GUM), the majority of standard atomic-weight values and their uncertainties are consensus values, not GUM-evaluated values. The Commission on Isotopic Abundances and Atomic Weights of the International Union of Pure and Applied Chemistry (IUPAC) regularly evaluates the literature for new isotopic-abundance measurements that can lead to revised standard atomic-weight values, A r (E) for element E. The Commission strives to provide utmost clarity in products it disseminates, namely the TSAW and the Table of Isotopic Compositions of the Elements (TICE). In 2016, it was recognized by the Commission that a guideline recommending expression of uncertainty listed in parentheses following the standard atomic-weight value, e.g. A r (Se) = 78.971(8), is not in accord with the GUM, which suggests that this parenthetic notation be reserved to express standard uncertainty, not the expanded uncertainty used in the TSAW and TICE. In 2017, to eliminate this noncompliance with the GUM, a new format was adopted in which the uncertainty value is specified by the plus-minus symbol, e.g. A r (Se) = 78.971 ± 0.008. To clarify the definition of uncertainty, a new footnote has been added to the TSAW. This footnote emphasizes that an atomic-weight uncertainty is a consensus (decisional) uncertainty. Not only has the Commission shielded users of the TSAW and TICE from unreliable measurements that appear in the literature as a result of unduly small uncertainties, but the aim of IUPAC has been fulfilled by which any scientist, taking any natural sample from commerce or research, can expect their sample atomic weight to lie within A r (E) ± its uncertainty almost all of the time.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

The soil health assessment protocol and evaluation applied to soil organic carbon

The concept of soil health has evolved over the past several decades, recognizing that dynamic soil property response to management and land use is highly dependent on site-specific factors that must be considered when interpreting soil health measurements. Initially, the Soil Management Assessment Framework (SMAF) and Comprehensive Assessment of Soil Health (CASH) were developed and used globally for scoring soil health indicators. However, both SMAF and CASH frameworks were developed using a relatively small dataset and their interpretation curves were not validated at the nationwide scale. Expanding upon these concepts, we propose the Soil Health Assessment Protocol and Evaluation (SHAPE) tool. The SHAPE was developed using 14,680 soil organic C (SOC) observations from across the United States, and accounts for edaphic and climate factors at the continental scale. Data were compiled from the literature, the Cornell Soil Health Laboratory, and the Kellogg Soil Survey Laboratory. In this approach, scoring curves are Bayesian model-based estimates of the conditional cumulative distribution function (CDF) for defined soil peer groups reflecting five soil texture and five soil suborder classes adjusted for mean annual temperature and precipitation. Specifically, SHAPE produces scores between 0 and 1 (0–100%) for measured SOC values that reflect the quantile or position within the conditional CDF along with measures of uncertainty. Herein, we focus on development of the SHAPE scoring curve for SOC with our case studies. SHAPE is a flexible, quantitative tool that provides a regionally relevant interpretation of this key soil health indicator.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Stability of mineral-organic matter associations under varying biogeochemical conditions

It is well-recognized and documented in the literature that a considerable fraction of the soil organic matter (SOM) is associated with Fe-oxide minerals. Recent studies have also showed that the persistence of various classes of SOM may depend on soil Fe mineralogy. Other laboratory studies with model mineral-associated organic matter (MAOM) moieties, which were primarily focused on ferrihydrite, either coated or coprecipitated with natural organic matter (NOM), have suggested that the mineral phase transformation and adsorption-desorption of SOM is rather complex but appears to be largely controlled by the C/Fe ratio of the MAOM moiety and geochemical conditions. It is also clear from multiple recent studies that the nature or type of SOM (microbial vs. plant-derived) adsorbed on mineral surfaces and the rate and extent of SOM biodegradation depend on the type of mineral, and/or metal ions, that are associated with the SOM. Modeling studies that are primarily centered on achieving a better understanding of the effect of mineral type on SOM interactions with minerals and degradation are also reported. These studies have improved the understanding of the nature and stability of MAOM in soils of varying types and under different conditions, positioning researchers to better predict the properties and stabilities of organo-mineral associations in soils.

54 ENVIRONMENTAL SCIENCES↗