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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Molecular Iodine Interactions with Fe, Ni, Cr, and Stainless Steel Alloys

The adsorption behavior of molecular iodine is important for understanding the spread of radioiodine in a nuclear accident. Prior experiments indicate that, in addition to the interaction with Fe, molecular iodine [i.e., I 2(g) ] also interacts with the next most abundant components of austenitic stainless steel (i.e., Ni, and Cr) at room temperature. Here, we investigate iodine adsorption on Fe, Ni, and Cr while focusing on understanding the variables affecting adsorption as well as the iodine compounds that are formed during adsorption. Scanning electron microscopy and energy-dispersive X-ray spectroscopy were used to characterize the surfaces of exposed metal particles and aid in the understanding of the morphology and chemistry of iodine interactions with the substrates. Inductively coupled plasma optical emission spectroscopy was used to detect low levels of metal iodides and X-ray photoelectron spectroscopy was used to confirm the formation of the metal iodides. The role of environmental factors (e.g., humidity and oxygen content) for iodine adsorption on metal substrates is addressed. The individual metals demonstrated formation of metal iodides for Fe and Ni particles from interaction with I 2(g) . The formation of metal iodides may indicate the affinity of iodine for the respective metal. In this study, the iodine affinities ranked Fe > Ni > Cr as determined by the quantity of chemisorbed iodine. This trend is also supported by the distributions and proportions of metals in the corrosion product of the stainless steels. The exposures without oxygen and humidity indicate the potential of a multistep iodine adsorption process where iodine first attacks the oxide layer and then chemisorbs to the exposed metal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Learning perturbation-inducible cell states from observability analysis of transcriptome dynamics

Abstract A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery of analyte-responsive promoters. This provides a set of biomarkers that act as a proxy for the transcriptional state referred to as cell state. We construct low-dimensional models of gene expression dynamics and rank genes by their ability to capture the perturbation-specific cell state using a novel observability analysis. Using this ranking, we extract 15 analyte-responsive promoters for the organophosphate malathion in the underutilized host organism Pseudomonas fluorescens SBW25. We develop synthetic genetic reporters from each analyte-responsive promoter and characterize their response to malathion. Furthermore, we enhance malathion reporting through the aggregation of the response of individual reporters with a synthetic consortium approach, and we exemplify the library’s ability to be useful outside the lab by detecting malathion in the environment. The engineered host cell, a living malathion sensor, can be optimized for use in environmental diagnostics while the developed machine learning tool can be applied to discover perturbation-inducible gene expression systems in the compendium of host organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Understanding the structure and composition of recalcitrant oligosaccharides in hydrolysate using high-throughput biotin-based glycome profiling and mass spectrometry

Novel Immunological and Mass Spectrometry Methods for Comprehensive Analysis of Recalcitrant Oligosaccharides in AFEX Pretreated Corn Stover. Lignocellulosic biomass is a sustainable alternative to fossil fuel and is extensively used for developing bio-based technologies to produce products such as food, feed, fuel, and chemicals. The key to these technologies is to develop cost competitive processes to convert complex carbohydrates present in plant cell wall to simple sugars such as glucose, xylose, and arabinose. Since lignocellulosic biomass is highly recalcitrant, it must undergo a combination of thermochemical treatment such as Ammonia Fiber Expansion (AFEX), dilute acid (DA), Ionic Liquid (IL) and biological treatment such as enzyme hydrolysis and microbial fermentation to produce desired products. However, when using commercial fungal enzymes during hydrolysis, only 75–85% of the soluble sugars generated are monomeric sugars, while the remaining 15–25% are soluble recalcitrant oligosaccharides that cannot be easily utilized by microorganisms. Previously, we successfully separated and purified the soluble recalcitrant oligosaccharides using a combination of charcoal and celite-based separation followed by size exclusion chromatography and studies their inhibitory properties on enzymes. We discovered that the oligosaccharides with higher degree of polymerization (DP) containing methylated uronic acid substitutions were more recalcitrant towards commercial enzyme mixtures than lower DP and neutral oligosaccharides. Here, we report the use of several complementary techniques that include glycome profiling using plant biomass glycan specific monoclonal antibodies (mAbs) to characterize sugar linkages in plant cell walls and enzymatic hydrolysate, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) using structurally-informative diagnostic peaks offered by negative ion post-secondary decay spectra, gas chromatography followed by mass spectrometry (GC–MS) to characterize oligosaccharide sugar linkages with and without derivatization. Since oligosaccharides (DP 4–20) are small, it is challenging to mobilize these molecules for mAbs binding and characterization. To overcome this problem, we have applied a new biotin-coupling based oligosaccharide immobilization method that successfully tagged most of the low DP soluble oligosaccharides on to a micro-plate surface followed by specific linkage analysis using mAbs in a high-throughput system. This new approach will help develop more advanced versions of future high throughput glycome profiling methods that can be used to separate and characterize oligosaccharides present in biomarkers for diagnostic applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Early photometric and spectroscopic observations of the extraordinarily bright INTEGRAL-detected GRB 221009A

Context. GRB 221009A, initially detected as an X-ray transient by Swift, was later revealed to have triggered the Fermi satellite about an hour earlier, marking it as a post-peak observation of the event’s emission. This GRB distinguished itself as the brightest ever recorded, presenting an unparalleled opportunity to probe the complexities of GRB physics. The unprecedented brightness, however, challenged observation efforts, as it led to the saturation of several high-energy instruments.Aims. Our study seeks to investigate the nature of the INTEGRAL-detected GRB 221009A and elucidate the environmental conditions conducive to these exceptionally powerful bursts. Moreover, we aim to understand the fundamental physics illuminated by the detection of teraelectronvolt (TeV) photons emitted by GRB 221009A.Methods. We conducted detailed analyses of early photometric and spectroscopic observations that span from the Fermi trigger through to the initial days following the prompt emission phase in order to characterize GRB 221009A’s afterglow, and we complemented these analyses with a comparative study.Results. Our findings from analyzing INTEGRAL data confirm GRB 221009A as the most energetic event observed to date. Early optical observations during the prompt phase negate the presence of bright optical emissions with internal or external shock origins. Spectroscopic analyses enabled us to measure GRB 221009A’s distance and line-of-sight properties. The afterglow’s temporal and spectral analysis suggests prolonged activity of the central engine and a transition in the circumburst medium’s density. Finally, we discuss the implications for fundamental physics of detecting photons as energetic as 18 TeV from GRB 221009A.Conclusions. Early optical observations have proven invaluable for distinguishing between the potential origins of optical emissions in GRB 221009A, underscoring their utility in GRB physics studies. However, the rarity of such data underscores the need for dedicated telescopes capable of synchronous multiwavelength observations. Additionally, our analysis suggests that the host galaxies of TeV GRBs share commonalities with those of long and short GRBs. Expanding the sample of TeV GRBs could further solidify these findings.Key words: techniques: photometric / techniques: spectroscopic / gamma-ray burst: general / gamma-ray burst: individual: GRB 221009A

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Machine learning models inaccurately predict current and future high-latitude C balances

The high-latitude carbon (C) cycle is a key feedback to the global climate system, yet because of system complexity and data limitations, there is currently disagreement over whether the region is a source or sink of C. Recent advances in big data analytics and computing power have popularized the use of machine learning (ML) algorithms to upscale site measurements of ecosystem processes, and in some cases forecast the response of these processes to climate change. Due to data limitations, however, ML model predictions of these processes are almost never validated with independent datasets. To better understand and characterize the limitations of these methods, we develop an approach to independently evaluate ML upscaling and forecasting. We mimic data-driven upscaling and forecasting efforts by applying ML algorithms to different subsets of regional process-model simulation gridcells, and then test ML performance using the remaining gridcells. In this study, we simulate C fluxes and environmental data across Alaska using ecosys, a process-rich terrestrial ecosystem model, and then apply boosted regression tree ML algorithms to training data configurations that mirror and expand upon existing AmeriFLUX eddy-covariance data availability. We first show that a ML model trained using ecosys outputs from currently-available Alaska AmeriFLUX sites incorrectly predicts that Alaska is presently a modeled net C source. Increased spatial coverage of the training dataset improves ML predictions, halving the bias when 240 modeled sites are used instead of 15. However, even this more accurate ML model incorrectly predicts Alaska C fluxes under 21st century climate change because of changes in atmospheric CO 2 , litter inputs, and vegetation composition that have impacts on C fluxes which cannot be inferred from the training data. Our results provide key insights to future C flux upscaling efforts and expose the potential for inaccurate ML upscaling and forecasting of high-latitude C cycle dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Data-driven modeling to enhance municipal water demand estimates in response to dynamic climate conditions

Altered precipitation and temperature patterns from a changing climate will affect supply, demand, and overall municipal water system operations throughout the arid western U.S. While supply forecasts leverage hydrological models to connect climate influences with surface water availability, demand forecasts typically estimate water use independent of climate and other externalities. Stemming from an increased focus on seasonal water demand management, we use the Salt Lake City, Utah municipal water system as a test bed to assess model accuracy versus complexity trade-offs between simple climate-independent econometric-based models and complex climate-sensitive data-driven models to average to extreme wet and dry climate conditions—representative of a new climate normal. Here, the climate-independent model displayed low performance during extreme dry conditions with predictions exceeding 90% and 40% of the observed monthly and seasonal volumetric demands, respectively, which we attribute to insufficient model complexity. The climate-sensitive models displayed greater accuracy in all conditions, with an ordinary least squares model demonstrating a measurable reduction in prediction bias (3.4% vs. -27.3%) and RMSE (74.0 lpcd vs. 294 lpcd) compared to the climate-independent model. The climate-sensitive workflow increased model accuracy and characterized climate-demand interactions, demonstrating a novel tool to enhance water system management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

An Integrated Multiscale Experimental-Numerical Analysis on Reconsolidation of Salt-Clay Mixture for Disposal of Heat-Generating Waste (Final NEUP Technical Report)

The overall purpose of this research is to improve understanding of THMC coupling effect on the reconsolidation of granular (or crushed) salt-clay mixture used for seal systems of shafts and drifts in salt repositories. This proposed work is partially motivated by the recent work on the Waste Isolation Pilot Plant (WIPP) that shows the promising sealing capability of clay-salt mixture compared to crushed salt. In particular, primary emphasis is to develop a fully integrated multiscale experiment-numerical study to determine and explain what leads to the superior sealing ability of the clay-salt mixture. These research activities are designed to seek further understanding of (1) why clay additives may enhance the fluid trapping and (2) whether this flow barrier effect may prevail under different combinations of temperature, confining pressure, deviatoric stress and other foreseeable environmental factors. If successful, this enhanced flow trapping ability of the seal provides significant improvement to the seal and repository performance and therefore make the repository safer in the long-term. The experiment component includes microstructural investigation and macroscopic tests on a reconsolidated salt-clay mixture. In the microstructural study, the goal is to (1) characterize microscopic distributions of distinct phases (e.g., clay, salt crystal boundaries, trapped brine, and pore) to examine the connectivity of the pore network inside the salt-clay mixture with different amounts of clay additive and moisture content and (2) analyze multiscale imaging data to reconstruct the polycrystalline microstructures for numerical simulations. Meanwhile, macroscopic tests are performed to analyze how clay alters the failure/creep mechanisms in the salt-clay mixture. Microscopic and macroscopic experimental observations will both be used to calibrate and validate a multiscale model that explicitly simulates the capillary and multiphase flow in the connected pores and the deformation due to the presence of intra-crystalline brine at the pore scale via a new polyhedral discrete element–lattice Boltzmann method (DEM-LBM) coupling model. The pore-scale simulations are homogenized via an upscaling procedure that converts pore-scale information (e.g. force exerted on grain boundary, sliding, pressure-solution) to continuum measures (e.g. Cauchy stress, Darcy’s flow) at each integration point in the macroscopic multiphase TMHC model. This multiscale scheme will allow coupling be- tween high-fidelity simulations of brine-salt-clay interaction and the macroscopic TMHC model. The multiscale model helps the understanding of how the trapped brine inclusion affects the pressure-solution mechanism with the presence of clay and moisture. This work brings new insight into the sealing capacity of salt-clay mixture under elevated temperature over a long period of time - a key to evaluating the potential of salt-clay mixture usage for salt repositories.

42 ENGINEERING↗
DOE OSTI2021

Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery

Optical water types (OWTs) were identified from an in situ dataset of concomitant biogeochemical and optical parameters acquired in the Amazon River and its tributaries, in the Lower Amazon region, at different hydrological conditions from 2014 to 2017. A seasonal bio-optical characterization was performed. The k-means classification was applied to the in situ normalized reflectance spectra (rn(λ)), allowing the identification of four OWTs. An optical index method was also applied to the rn(λ) defining the thresholds of the OWTs. Next, level-3 Sentinel-3 Ocean and Land Color Instrument images representative of the seasonal discharge conditions were classified using the identified in situ OWTs as reference. The differences between Amazon River and clearwater tributary OWTs were dependent on the hydrological dynamics of the Amazon River, also showing a strong seasonal variability. Each OWT was associated with a specific bio-optical and biogeochemical environment assessed from the corresponding absorption coefficient values of colored dissolved organic matter (aCDOM) and particulate matter (ap), chlorophyll-a and suspended particulate matter (SPM) concentrations, and aCDOM/ap ratio. The rising water season presented a unique OWT with high SPM concentration and high relative contribution of ap to total absorption compared to the other OWTs. This bio-optical characterization of Lower Amazon River waters represents a first step for developing remote sensing inversion models adjusted to the optical complexity of this region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Response of Subsurface Nitrogen-Cycling Microbial Communities to Environmental Fluctuations (Final Technical Report)

Riparian floodplains are dynamic ecosystems linking terrestrial and riverine systems. These floodplains experience hydrological shifts such as changes in water table height, flooding, and drought and can be ‘hotspots’ of biogeochemical cycling due to shifting sediment moisture (and saturation) and subsurface exchanges of water, nutrients, and other compounds across different sediment layers. Subsurface microbial communities are the primary drivers of biogeochemical processes in floodplains, and thus their structure and function can directly influence both surface and groundwater quality. The microbial nitrogen (N) cycle is particularly important in floodplains as it affects nutrient availability and removal. Two functional guilds of chemoautotrophic (i.e. CO2-fixing) microorganisms are responsible for the first oxidative step of the N cycle, nitrification: ammonia-oxidizing archaea (AOA) and bacteria (AOB) catalyze the oxidation of ammonia to nitrite, while nitrite-oxidizing bacteria (NOB) oxidize nitrite to nitrate. Despite the critical role nitrification plays in N-cycling in both terrestrial and aquatic ecosystems, our understanding of the diversity, ecophysiology, and activity of nitrifying organisms in subsurface floodplain soils/sediments is extremely limited. To help address this critical knowledge gap, the overarching goal of this project was to determine how shifts in key environmental parameters and gradients impact microbial N-cycling communities/processes, with particular emphasis on nitrification, within hydrologically-variable floodplain sediments in the Wind River Basin near Riverton, Wyoming. The three specific objectives of this project were to: (1) to associate in situ environmental drivers of N cycling with distinct functional guilds; (2) determine the guild response to variation in key ecosystem drivers; and (3) develop a dynamic ecosystem model of the microbial N cycle with the Riverton subsurface using community genomic and biogeochemical data collected in the first two objectives. Over the course of this project, we employed both 16S rRNA gene amplicon sequencing and genome-resolved metagenomics to examine the phylogenetic diversity and metabolic potential of subsurface nitrifier communities within 68 samples collected across multiple sites, depths, and time points within the Riverton floodplain, allowing for both spatial and temporal investigations at different scales. This project benefitted tremendously from recent advances in high-throughput sequencing technologies coupled with dramatic improvements in the computational tools and algorithms available for analyzing such large, complex genomic datasets. By pairing these cutting-edge genomic approaches with depth-resolved sampling and detailed geochemical analyses of the Riverton floodplain, we have gained novel insights into the structure and function of subsurface nitrifier communities in relation to both hydrology and biogeochemistry. This project resulted in the most detailed and comprehensive characterization of N-cycling floodplain microbial communities to date and will hopefully inspire and pave the way for future studies using similar approaches in other floodplains. Indeed, such information is critical for understanding subsurface biogeochemical cycling and how elemental stores are altered from perturbations initiated by the water cycle within floodplains. Finally, because of the terrestrial-aquatic nature of the Riverton floodplain, results from this project are also of relevance to disciplines such as soil science, estuarine science, limnology & oceanography, biogeochemistry, geobiology, environmental engineering, as well as genomics and data science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Cation Disordered Anti-Perovskite Cathode Materials with Enhanced Lithium Diffusion and Suppressed Phase Transition

Recently, a new family of anti-perovskite Li 2 TMSO was discovered as promising cathode materials for Li-ion batteries (LIBs) with superiorities in high specific capacity, low cost, and environmental friendliness. However, the applications of these anti-perovskite materials meet severe challenges in the cyclability and rate performance. In this work, a cation-disordered anti-perovskite type solid solution Li 2 Fe 1– x Mn x SO (LFMSO, x = 0, 0.2, 0.5) with excellent electrochemical performance is reported. On the basis of comprehensive structural characterizations, the role of the cation disordering in LFMSO is clarified. In comparison with Li 2 FeSO (LFSO), the reduced Li-ion diffusion barrier and the increased Li-rich octahedral configurations in LFMSO with higher configurational entropy imply the facilitated long-range Li-ion diffusion and the suppressed phase transition, which favor the high-rate capability and cycling stability. In addition, the large lattice distortion and Coulombic interaction between the anions and cations lead to the breathing of the unit cell during charge/discharge. The variation of the unit cell volume decreases to 2.5% upon Li-ion delithiation. A superstructure is observed in LFMSO for the first time. These findings help to pave the way for the research and development of novel cathode materials for the next generation LIBs.

25 ENERGY STORAGE↗
DOE OSTI2025

Measuring Solvation Interactions of Deep Eutectic Solvents Formed by Metal Chlorides and an Imidazolium Salt by Inverse Gas Chromatography

Deep eutectic solvents (DESs) represent a class of solvents that offer a number of advantages including minimal toxicity, affordability, low vapor pressure, and simple, environmentally friendly preparation methods. They have found utility in areas, such as gas absorption, metal plating, and extractions. However, the relationship between their solvation properties and chemical composition remains poorly understood. In this study, a broad range of Type I DESs composed of metal chlorides and an imidazolium salt were prepared, employed as gas chromatographic stationary phases, and characterized using the Abraham solvation parameter model by inverse gas chromatography. The Abraham solvation parameter model allows for the study of DES solvation properties and the effects of varying structural components on system constants using a linear-free energy relationship. The DESs were investigated by systematically varying their composition, including the type of metal chloride and the molar ratio between the metal chloride and the imidazolium salt. The results show that hydrogen bond acidity, hydrogen bond basicity, and dipolarity/polarizability interactions are strongly influenced by the type of metal chloride within the DES and the ratio of metal chloride to imidazolium salt in the eutectic mixture. Furthermore, a column pretreatment procedure is presented that enables the effective coating of highly polar DESs onto open tubular capillary gas chromatography columns.

deep eutectic solvent↗
DOE OSTI2025

3D Printing of Polyelectrolyte Complex-Integrated Photocurable Hydrogel Resins

In this study, we developed a photocurable hydrogel resin incorporating a polyelectrolyte complex (PEC) for 3D printing. Acrylamide-based monomers were formulated with varying PEC contents (0–15 wt %) in an aqueous KBr medium to fabricate patterned porous hydrogel structures. The morphology of printed hydrogels was characterized by field-emission scanning electron microscopy and energy-dispersive X-ray spectroscopy. Notably, the PEC5 and PEC10 formulations exhibited optimal thermal stability and compressive properties, attributed to the homogeneous distribution of PEC domains within the hydrogel matrix. Furthermore, dye adsorption experiments demonstrated excellent removal efficiency, highlighting the potential of PEC-containing hydrogels for environmental remediation applications, particularly in the treatment of dye-contaminated wastewater.

Yang, Jinchul [University of Tennesse Knoxville]↗
DOE OSTI2024

Data sets for Unraveling Iron Oxides as Abiotic Catalysts of Organic Phosphorus Recycling in Soil and Sediment Matrices

In biogeochemical phosphorus cycling, iron oxide minerals are acknowledged as strong adsorbents of inorganic and organic phosphorus species. The dephosphorylation of organic phosphorus is attributed only to biological processes, but iron oxides could also catalyze this hydrolytic cleavage. Limited evidence of this abiotic catalysis has relied on monitoring inorganic phosphate in solution, thereby ignoring iron oxides as both catalysts and adsorbents. Here we apply high-resolution mass spectrometry and X-ray absorption spectroscopy to characterize dissolved and particulate phosphorus species, respectively. In soil and sediment samples reacted with ribonucleotides, we uncover the abiotic production of particulate inorganic phosphate associated specifically with iron oxides. Experiments with various organic phosphorus compounds revealed up to 12-fold greater catalytic and adsorption reactivities with iron oxides than with the silicate and aluminosilicate minerals identified in the environmental samples. Remarkably, we obtained dephosphorylation rates by the iron oxides that are within reported enzymatic rates in soils. However, phosphorus cycle models do not yet include a quantitative account of the abiotic evolution of inorganic phosphate from organic phosphorus trapped on iron oxides in environmental matrices. Our findings imply a missing abiotic axiom for organic phosphorus mineralization in the phosphorus cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Fine Ash-Bearing Particles as a Major Aerosol Component in Biomass Burning Smoke

Biomass burning (BB) events are occurring globally with increasing frequency, and their emissions are having more impacts on human health and climate. Large ash particles are recognized as a BB product with major influences on soil and water environments. However, fine-ash particles, which have diameters smaller than several microns and characteristic morphologies and compositions (mainly Ca and Mg carbonates), have not yet been explicitly considered as a major BB aerosol component either in field observations or climate models. This study measured BB aerosol samples using transmission electron microscopy (TEM) and ion chromatography during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign. We show that significant amounts of fine ash-bearing particles are transported >100 km from their fire sources. Our environmental chamber experiments suggest that they can act as cloud condensation and ice nuclei. We also found considerable amounts of fine ash-bearing particles in the TEM samples collected during previous campaigns (Biomass Burning Observation Project and Megacity Initiative: Local and Global Research Observations). These ash particles are commonly mixed with organic matter and make up ~8% and 5% of BB smoke by number and mass, respectively, in samples collected during the FIREX-AQ campaign. The measured ash-mass concentrations are approximately five times and six times greater than those of BB black carbon and potassium, respectively, scaling to an estimated global emission of 11.6 Tg yr -1 with a range of 8.8–16.3 Tg yr -1 . Better characterization and constraints on these fine ash-bearing particles will improve BB aerosol measurements and strengthen assessments of BB impacts on human health and climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Temporal patterns of fine‐root dynamics have little influence on seasonal soil CO 2 efflux in a mixed, mesic forest

Among the contributors to soil CO 2 efflux, there remains uncertainty about the contribution of root activity to the overall soil efflux. Soil water and temperature frequently have been used to predict a large portion of the variation in soil CO 2 efflux. We hypothesized that fine-root dynamics explain most of the remaining variability in soil CO 2 efflux that cannot be explained by soil temperature and water content. We anticipated that seasonal increases in root production, mortality via decomposition, and standing crop would result in corresponding increases in soil CO 2 efflux. We tested our hypotheses by collecting and analyzing two years of minirhizotron and soil chamber CO 2 flux data from plots distributed throughout the Shale Hills Catchment of the Susquehanna-Shale Hills Critical Zone Observatory in Central Pennsylvania, USA. Here we showed that: (1) seasonal fluctuations in fine-root dynamics yielded only a very small increase in the predictability of soil CO 2 efflux; (2) fine-root mortality effects on soil CO 2 efflux were strongly tied to soil temperature; (3) fluctuations in fine-root presence or standing mass independent of temperature and moisture had little effect on soil CO 2 efflux; and (4) new fine-root length and root length mortality had limited impacts on soil CO 2 efflux rates. We conclude that, at least in temperate forests on rocky soils, characterizing fine-root dynamics may provide only limited improvement in the estimation of soil CO 2 efflux.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The damage Mechanics challenge Results: Participant predictions compared with experiment

In this article, We present results from a recent exercise where participating organizations were asked to provide model-based blind predictions of damage evolution in 3D-printed geomaterial analogue test articles. Participants were provided with a range of data characterizing both the undamaged state (e.g., ultrasonic measurements) and damage evolution (e.g., 3-point bending, unconfined compression, and Brazilian testing) of the material. In this paper, we focus on comparisons between the participants’ predictions and the previously secret challenge problem experimental observations. We present valuable lessons learned for the application of numerical methods to deformation and failure in brittle-ductile materials. The exercise also enables us to identify which specific types of calibration data were of most utility to the participants in developing their predictions. Further, we identify additional data that would have been useful for participants to improve the confidence of their predictions. Consequently, this work improves our understanding of how to better characterize a material to enable more accurate prediction of damage and failure propagation in natural and engineered brittle-ductile materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Comparing Model Representations of Physiological Limits on Transpiration at a Semi-arid Ponderosa Pine Site

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.

54 ENVIRONMENTAL SCIENCES↗