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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Structural and Interactional Analysis of the Flavonoid Pathway Proteins: Chalcone Synthase, Chalcone Isomerase and Chalcone Isomerase-like Protein

Chalcone synthase (CHS) and chalcone isomerase (CHI) catalyze the first two committed steps of the flavonoid pathway that plays a pivotal role in the growth and reproduction of land plants, including UV protection, pigmentation, symbiotic nitrogen fixation, and pathogen resistance. Based on the obtained X-ray crystal structures of CHS, CHI, and chalcone isomerase-like protein (CHIL) from the same monocotyledon, Panicum virgatum, along with the results of the steady-state kinetics, spectroscopic/thermodynamic analyses, intermolecular interactions, and their effect on each catalytic step are proposed. In addition, PvCHI’s unique activity for both naringenin chalcone and isoliquiritigenin was analyzed, and the observed hierarchical activity for those type-I and -II substrates was explained with the intrinsic characteristics of the enzyme and two substrates. The structure of PvCHS complexed with naringenin supports uncompetitive inhibition. PvCHS displays intrinsic catalytic promiscuity, evident from the formation of p-coumaroyltriacetic acid lactone (CTAL) in addition to naringenin chalcone. In the presence of PvCHIL, conversion of p-coumaroyl-CoA to naringenin through PvCHS and PvCHI displayed ~400-fold increased Vmax with reduced formation of CTAL by 70%. Supporting this model, molecular docking, ITC (Isothermal Titration Calorimetry), and FRET (Fluorescence Resonance Energy Transfer) indicated that both PvCHI and PvCHIL interact with PvCHS in a non-competitive manner, indicating the plausible allosteric effect of naringenin on CHS. Significantly, the presence of naringenin increased the affinity between PvCHS and PvCHIL, whereas naringenin chalcone decreased the affinity, indicating a plausible feedback mechanism to minimize spontaneous incorrect stereoisomers. These are the first findings from a three-body system from the same species, indicating the importance of the macromolecular assembly of CHS-CHI-CHIL in determining the amount and type of flavonoids produced in plant cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu\beta\beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76 Ge to achieve a half-life sensitivity of 10 27 (10 28 ) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of $0.024 ^{+0.004}_{-0.003} \%$ after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.

artificial intelligence↗
NASA NTRS2011

Disturbances in the Isotopic Record of Asuka 881394

Asuka 881394 is a unique achondrite with a granulitic texture, very calcic approximately An(sub 98) plagioclase, and pigeonite that has not inverted to orthopyroxene. First thought to be a eucrite, recent Oisotopic studies show it has a closer affinity to angrites . Initial isotopic studies provided evidence for now extinct A-26, Mn-53, and Sm-146. A recent study confirmed an early chronology with an absolute Pb-207 - Pb-206 age of 4566.5 +/- 0.2 Ma, a new measurement of the Al-Mg formation interval as 3.7 +/- 0.1 Ma since Al-26/Al-27 = approximately 4.63 x 10(exp -5) for the E60 CAI, and a Mn-Cr formation interval of -6.0 +/- 0.2 Ma relative to LEW86010 ("LEW"). Absolute ages relative to age anchors presented by were 4563.4 +/- 0.2 Ma by Al- Mg and 4564.6 +/- 0.5 Ma by Mn-Cr. These ages are in good, but not perfect, agreement with the Pb-207 - Pb-206 age. Perhaps the most direct comparison of the early chronology of A881394 as determined by various workers is provided by reported Al-26/Al-27 values of 1.18 +/- 0.14, 1.28 +/- 0.07, and 2.1 +/- 0.4 x 10(exp -6). Analyses of mineral separates by TIMS and MC-ICPMS6] agree well, but the higher value obtained by in situ SIMS analysis is significant in light of the slight inconsistency between absolute ages inferred from the short-lived chronometers and the Pb-207 - Pb-206 age. We examine the possibility that inconsistencies in the earliest fine-scale chronology of Asuka 881394 may be related to isotopic "disturbances" observed in Ar-39 - Ar-40, Rb-97 - Sr-87, and Sm-147 - Nd-143 chronometers.

Nyquist, L. E.↗
DOE OSTI2023

Molecular recognition requires dimerization of a VHH antibody

Camelid heavy-chain-only antibodies are a unique class of antibody that possesses only a single variable domain (termed VHH) for antigen recognition. Despite their apparent canonical mechanism of target recognition, where a single VHH domain binds a single target, an anti-caffeine VHH has been observed to possess 2:1 stoichiometry. Here, the structure of the anti-caffeine VHH/caffeine complex enabled the generation and biophysical analysis of variants that were used to better understand the role of VHH homodimerization in caffeine recognition. VHH interface mutants and caffeine analogs, which were examined to probe the mechanism of caffeine binding, suggested caffeine recognition is only possible with the VHH dimer species. Correspondingly, in the absence of caffeine, the anti-caffeine VHH was found to form a dimer with a dimerization constant comparable to that observed with VH:VL domains in conventional antibody systems, which was most stable near physiological temperature. While the VHH:VHH dimer structure (at 1.13 Å resolution) is reminiscent of conventional VH:VL heterodimers, the homodimeric VHH possesses a smaller angle of domain interaction, as well as a larger amount of apolar surface area burial. To test the general hypothesis that the short complementarity-determining region-3 (CDR3) may help drive VHH:VHH homodimerization, an anti-picloram VHH domain containing a short CDR3 was generated and characterized, which revealed it also existed as dimer species in solution. These results suggest homodimer-driven recognition may represent a more common method of VHH ligand recognition, opening opportunities for novel VHH homodimer affinity reagents and helping to guide their use in chemically induced dimerization applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Investigation and Analysis of Dolomite Dissolution in Variable Strength Systems Relevant to the WIPP

The Waste Isolation Pilot Plant (WIPP) was opened in 1999 as a solution to the long-term disposal of the nation's nuclear defense-generated transuranic (TRU) waste. The salt beds were recommended as the ideal location because they are free from flowing fresh water, easily mined, impermeable, and geologically stable. However, for performance assessment modeling, release scenarios must be considered. The most likely release scenario was determined to be human intrusion leading to direct and/or long-term brine release (US DOE 1995, US DOE 1996, Perkins et al., 1999). The focus of this research is the Rustler formation because it is located above the WIPP and is the most transmissive layer (Perkins et al., 1999). Objective: To determine the effect of chelating ligands ( e.g. EDTA) on dissolution of dolomite in high ionic strength systems. Do brines impact dolomite dissolution and how is it affected by EDTA binding with cations? By varying the ionic strengths, different brine conditions can be simulated similar to those in and around the Culebra member and evaluate trends of dissolved Ca and Mg in the aqueous phase from the quantified data. Conclusions: <2% of dolomite dissolved over one week at pH 8.5. Greater dissolution occurred at higher ionic strength and in the presence of NaCl with approximately 0.4 vs. 0.9% of Mg removed from dolomite in 0.1 and 1.0 M Na. Further, 0.3 vs. 0.9% of Mg was removed from dolomite in 1.0 M IS CaCl{sub 2} versus NaCl. EDTA increased dissolution of dolomite at low ionic strength due to its strong complexation affinity for Ca/Mg with slightly greater removal of Ca than Mg. Significant differences were not observed at high ionic strength due to the presence of large concentrations of competing cations (Na, Ca, Mg). Slightly higher concentrations of Ca were removed from dolomite than Mg after one week, suggesting either incongruent dissolution or release through ion exchange of Ca from trace mineral impurities. Further, when EDTA was present, it may have increased Ca removal due to its greater complexation for Ca than Mg. Environmental Implications: High ionic strength brines and low ionic strength solutions with organic ligands increase dissolution of dolomite. Due to the long half-lives of radionuclides in the TRU waste, it may be important to consider the long term impact of dolomite dissolution for potential release scenarios.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Lead tolerance and bioremoval by four strains of green algae from Nigerian fish ponds

Heavy metals from industry pose threats to human and environmental health. Microalgae are prime candidates to remove heavy metals from water and soil due to their metal-binding affinities, high growth rates, and contamination tolerance. Strain selection and composition of resulting contaminated biomass must be considered for downstream processing. In this study, we assessed the ability of four microalgae strains (Chlorophyceae) that were isolated from contaminated Nigerian fish ponds to take up dissolved lead at environmentally relevant concentrations (<0.05 mg L -1 – WHO standard). In a microplate assay, all strains grew in the presence of lead, tolerating concentrations up to 60 ppm, though the addition of dissolved lead affected the growth of the four strains. In a photobioreactor assay, all strains demonstrated the ability to take up dissolved lead, with removal efficiencies ranging from 86 to 93%. The concentrations of lead in contaminated biomass, removal efficiencies, and bioconcentration factors were greatest in one of the isolates Chlorella sp. MOW 12. Our results reinforce the fact that live microalgae have a greater biosorption capacity. Lead recovery from freeze-dried biomass using five different reagents showed that a 0.1 M hydrochloric acid solution was the most effective, with 83.4% recovery. We also showed that presence of lead in the culture medium resulted in an increase in the quantity of protein in the biomass. Elemental analysis of lead-bound biomass showed an increase in elements including boron and copper and a decrease in cobalt and sodium. Synergystic and antagonystic effect in uptake of other elements was strain specific, suggesting the possibility of tailored wastewater treatments depending on specific requirements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Selenium interaction with iron minerals: Quantitative comparison of sorption and coprecipitation impacts on mobility

Given the significance of selenium (Se) as a micronutrient, the radioactive nature of some of its isotopes, and its affinity to iron (Fe) minerals, extensive research has been conducted on the sorption mechanisms between Se and these minerals. Here, in this study, we employ sorption data sourced from the L-SCIE database and coprecipitation data from available literature to achieve the following objectives: i) establish coherence between adsorption and coprecipitation processes, ii) quantitatively evaluate the importance of these processes in nuclear waste repository science, and iii) propose a forward-looking approach for integrating coprecipitation into reactive transport models. Our findings indicate that a correlation between Se adsorption and coprecipitation can be established using the λ formalism. The comparable log(λ Se(IV) /λ Se(VI) ) ratios derived from adsorption and coprecipitation experiments suggest that these processes can be quantitatively compared and evaluated using our numerical approach. Across all iron oxide phases examined, coprecipitation leads to significantly greater immobilization of Se compared to adsorption. Specifically, for hydrous ferric oxide, hematite, and goethite, coprecipitation is predicted to result in 100–1000 times more Se immobilization compared to adsorption, irrespective of the Se oxidation state (Se(IV) or Se(VI)); notably stronger immobilization potential via coprecipitation was observed for magnetite. The modeling approach and quantitative analysis presented herein clearly highlight the importance of including coprecipitation processes when simulating Se (and other elements) transport, particularly under conditions where mineral compositions are transient or evolving with time. Neglecting coprecipitation in models is likely to lead to significant overestimates of migration.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Do Neural Networks Trained with Topological Features Learn Different Internal Representations?

There is a growing body of work that leverages features extracted via topological data analysis to train machine learning models. While this field, sometimes known as topological machine learning (TML), has seen some notable successes, an understanding of how the process of learning from topological features differs from the process of learning from raw data is still limited. In this work, we begin to address one component of this larger issue by asking whether a model trained with topological features learns internal representations of data that are fundamentally different than those learned by a model trained with the original raw data. To quantify ``different'', we exploit two popular metrics that can be used to measure the similarity of the hidden representations of data within neural networks, neural stitching and centered kernel alignment. From these we draw a range of conclusions about how training with topological features does and does not change the representations that a model learns. Perhaps unsurprisingly, we find that structurally, the hidden representations of models trained and evaluated on topological features differ substantially compared to those trained and evaluated on the corresponding raw data. On the other hand, our experiments show that in some cases, these representations can be reconciled (at least to the degree required to solve the corresponding task) using a simple affine transformation. We conjecture that this means that neural networks trained on raw data may extract some limited topological features in the process of making predictions.

McGuire, Sarah L.↗
DOE OSTI2023

Data-Driven Discovery of Linear Molecular Probes with Optimal Selective Affinity for PFAS in Water

Approaches to tackle the wide and growing variety of highly persistent per- and polyfluoroalkyl substances (PFAS) are of pressing global need because of their detrimental human health effects, such as cancer, birth defects, and hormone imbalance. Sensitive, selective, and easy-to-use real-time sensors to monitor and detect PFAS and sorbents to extract them are critical to meeting government-mandated environmental concentrations. In this work, we combine all-atom molecular dynamics simulations, enhanced sampling, deep representational learning, and Bayesian optimization to perform high-throughput virtual screening for highly sensitive and selective molecular probes. Our molecular design space consists of 3850 linear hydrocarbon chains with varying degrees of halogenation with and without amine- and phosphine-based headgroups. By employing a data-driven search process, we efficiently explore the molecular design space to optimize the sensitivity to perfluorooctanesulfonic acid (PFOS) as a prototypical PFAS analyte and selectivity relative to a sodium dodecyl sulfate (SDS) interferent. We calculate 504 Gibbs free energies of probe-analyte and probe-interferent interactions and identify probes with PFOS association free energies of up to (-ΔG PFOS ) = 9.8 ± 0.2 kJ/mol and selectivities relative to SDS of (-ΔΔG PFOS–SDS ) = 3.1 ± 1.5 kJ/mol. A C 11 Br 23 P(CH 3 ) 2 probe containing 11 backbone brominated carbons and a tertiary phosphine headgroup possesses the most sensitive binding constant to PFOS within the defined search space of K b PFOS = 177.4 ± 12.7, and a semibrominated probe C 5 H 11 C 7 Br 14 N(CH 3 ) 2 containing 12 backbone carbons and a tertiary amine headgroup possesses the highest selectivity relative to SDS of K b PFOS /K b SDS = 4.6 ± 1.7. A retrospective analysis of our data to extract interpretable design rules reveals that the sensitivity of linear hydrogenated probes increases by approximately 1 kJ/mol per C–C bond. The addition or removal of halogen atoms and amine or phosphine headgroups produces nonmonotonic changes in both sensitivity and selectivity with changes to the sensitivity of up to 2.5 kJ/mol. Finally, this work places empirical limitations on the performance of a wide range of linear probes for PFOS detection and offers a generic strategy for high-throughput computational screening to promote selective and sensitive binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Purification and sequence analysis of two rat tissue inhibitors of metalloproteinases

Two protein inhibitors of metalloproteinases (TIMP) were isolated from medium conditioned by the clonal rat osteosarcoma line UMR 106-01. Initial purification of both a 30-kDa inhibitor and a 20-kDa inhibitor was accomplished using heparin-Sepharose chromatography with dextran sulfate elution followed by DEAE-Sepharose and CM-Sepharose chromatography. Purification of the 20-kDa inhibitor to homogeneity was completed with reverse-phase high-performance liquid chromatography. The 20-kDa inhibitor was identified as rat TIMP-2. The 30-kDa inhibitor, although not purified to homogeneity, was identified as rat TIMP-1. Amino terminal amino acid sequence analysis of the 30-kDa inhibitor demonstrated 86% identity to human TIMP-1 for the first 22 amino acids while the sequence of the 20-kDa inhibitor was identical to that of human TIMP-2 for the first 22 residues. Treatment with peptide:N-glycosidase F indicated that the 30-kDa rat inhibitor is glycosylated while the 20-kDa inhibitor is apparently unglycosylated. Inhibition of both rat and human interstitial collagenase by rat TIMP-2 was stoichiometric, with a 1:1 molar ratio required for complete inhibition. Exposure of UMR 106-01 cells to 10(-7) M parathyroid hormone resulted in approximately a 40% increase in total inhibitor production over basal levels.

NASA Discipline Musculoskeletal↗
DOE OSTI2020

Affinity propagation clustering of full-field, high-spatial-dimensional measurements for robust output-only modal identification: A proof-of-concept study

Determination of the model order is a challenging problem in system identification, especially in output-only or operational modal identification where some modes are weakly excited. While existing methods such as the stabilization diagram method (spectral information) are effective, they do not scale to high-dimensional data, which is usually needed for high-fidelity characterization of structural dynamics and has been made available in the emerging full-field measurement techniques using optical methods such as photogrammetry and laser vibrometers. In this proof-of-concept study we present a new non-parametric, data-driven approach for robust output-only identification of high-spatial-dimensional modal parameters of basic structures by efficiently processing and interactively exploiting the full-field measurement (i.e., very dense spatial measurement points). Specifically, we first over-estimate the system model once, producing a pool of candidate modes associated with their modal frequencies and full-field, high-spatial-dimensional mode shapes. This is accomplished by a data-driven method termed affinity propagation clustering (APC), where the active clusters, which are the active modes in our formulations, emerge from the "message-passing" procedure and does not require a pre-determination of the cluster number (mode or model order). Next, rather than using the spectral information to distinguish the physical and spurious modes in the stabilization diagram method, we exploit and visualize the spatial, full-field mode shape associated with each candidate mode to do so. We conduct extensive experiments on basic structural models with comparisons to a few existing methods. The results indicate that the new method is computationally efficient for identifying high-spatial-dimensional modal parameters, and robust to identify weak modes by exploiting the full-field measurement. We also discuss its applicability and limitations for structures with complex geometry (shapes).

42 ENGINEERING↗
DOE OSTI2021

Development of Chromium and Sulfur Getter for Solid Oxide Fuel Cell (SOFC) System

Under the “real world” SOFC operating conditions, gaseous Cr and S species coexist in air stream. The combined Cr and S effect on the electrochemical poisoning of candidate LSM and LSCF electrodes has been investigated. Electrochemical and structural analysis revealed that the combined Cr and S interactions with the LSCF electrode remains significantly different from those of the individual Cr and S interactions. S reacts with the surface SrO accompanied by morphological changes whereas the hexavalent gaseous Cr species mainly deposit at the LSCF/GDC interface as is the case with Cr-only poisoning. For LSM electrode, the combined interactions of Cr and S remains similar to the sum of individual Cr and S effects as SO 2 reacts with Sr-rich regions of the bulk LSM, while Cr deposits at the electrochemically active sites. The use of getter, consisting of alkaline earth and transition metal oxides, has been proposed as a cost-effective approach to mitigate electrode poisoning. SrMnO 3 (SMO) is suggested as a robust getter material for the co-capture of airborne gaseous S and Cr species entering high-temperature electrochemical systems. The honeycomb getter forms, covered with SMO nanoparticles, were fabricated using dip coating. The SMO getter successfully maintained the electrochemical activity of LSM under the presence of gaseous Cr and S species, validating the efficacy of the getter. Post-test characterization revealed that the absorption of S and Cr contaminants led to the elongation of granular SMO particles, forming SrO nanorods and SrCrO 4 whiskers leaving Mn oxides underneath where inward-migrating Cr reside, indicating the high mutual affinity of Sr and Mn. The growth of reaction products during the long term exposure favors continued absorption of incoming S and Cr contaminants. The Mn 2 O 9 dimers, existing on the surface, are considered to help absorb S and Cr impurities, along with the Sr-terminated surface. The SMO getter also displays robust stability in humid environments at high temperatures without phase transformation or hydrolysis, fulfilling the requirement for operation in high-temperature electrochemical systems.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Graph-Directed Approach for Downselecting Toxins for Experimental Structure Determination

Conotoxins are short, cysteine-rich peptides of great interest as novel therapeutic leads and of great concern as lethal biological agents due to their high affinity and specificity for various receptors involved in neuromuscular transmission. Currently, of the approximately 6000 known conotoxin sequences, only about 3% have associated structural characterization, which leads to a bottleneck in rapid high-throughput screening (HTS) for identification of potential leads or threats. In this work, we combine a graph-based approach with homology modeling to expand the library of conotoxin structures and to identify those conotoxin sequences that are of the greatest value for experimental structural characterization. The latter would allow for the rapid expansion of the known structural space for generating high quality template-based models. Our approach generalizes to other evolutionarily-related, short, cysteine-rich venoms of interest. Overall, we present and validate an approach for venom structure modeling and experimental guidance and employ it to produce a 290%-larger library of approximate conotoxin structures for HTS. We also provide a set of ranked conotoxin sequences for experimental structure determination to further expand this library.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A natural mutation between SARS-CoV-2 and SARS-CoV determines neutralization by a cross-reactive antibody

Epitopes that are conserved among SARS-like coronaviruses are attractive targets for design of cross-reactive vaccines and therapeutics. CR3022 is a SARS-CoV neutralizing antibody to a highly conserved epitope on the receptor binding domain (RBD) on the spike protein that is able to cross-react with SARS-CoV-2, but with lower affinity. Using x-ray crystallography, mutagenesis, and binding experiments, we illustrate that of four amino acid differences in the CR3022 epitope between SARS-CoV-2 and SARS-CoV, a single mutation P384A fully determines the affinity difference. CR3022 does not neutralize SARS-CoV-2, but the increased affinity to SARS-CoV-2 P384A mutant now enables neutralization with a similar potency to SARS-CoV. We further investigated CR3022 interaction with the SARS-CoV spike protein by negative-stain EM and cryo-EM. Three CR3022 Fabs bind per trimer with the RBD observed in different up-conformations due to considerable flexibility of the RBD. In one of these conformations, quaternary interactions are made by CR3022 to the N-terminal domain (NTD) of an adjacent subunit. Overall, this study provides insights into antigenic variation and potential cross-neutralizing epitopes on SARS-like viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Scaled boundary cubature scheme for numerical integration over planar regions with affine and curved boundaries

This paper introduces the scaled boundary cubature (SBC) scheme for accurate and efficient integration of functions over polygons and two-dimensional regions bounded by parametric curves. Over two-dimensional domains, the SBC method reduces integration over a region bounded by m curves to integration over m regions (referred to as curved triangular regions), where each region is bounded by two line segments and a curve. With proper (counterclockwise) orientation of the boundary curves, the scheme is applicable to convex and nonconvex domains. Additionally, for star-convex domains, a tensor-product cubature rule with positive weights and integration points in the interior of the domain is obtained. If the integrand is homogeneous, we show that this new method reduces to the homogeneous numerical integration scheme; however, the SBC scheme is more versatile since it is equally applicable to both homogeneous and non-homogeneous functions. This paper also introduces several methods for smoothing integrands with point singularities and near-singularities. When these methods are used, highly efficient integration of weakly singular functions is realized. Finally, the SBC method is applied to a number of benchmark problems, which reveal its broad applicability and superior performance (in terms of time to generate a rule and accuracy per cubature point) when compared to existing methods for integration.

42 ENGINEERING↗
DOE OSTI2021

Guiding the design of oxidation-resistant Fe-based single atom alloy catalysts with insights from configurational space

The high activity and selectivity of Fe-based heterogeneous catalysts toward a variety of reactions that require the breaking of strong bonds are offset in large part by their considerable instability with respect to oxidative deactivation. While it has been shown that the stability of Fe catalysts is considerably enhanced by alloying them with precious metals (even at the single-atom limit), rational design criteria for choosing such secondary metals are still missing. Since oxidative deactivation occurs due to the strong binding of oxygen to Fe and reduction by adsorbed hydrogen mitigates the deactivation, we propose here to use the binding affinity of oxygen and hydrogen adatoms as the basis for rational design. As it would also be beneficial to use cheaper secondary metals, we have scanned over a large subset of 3d–5d mid-to late transition metal single atoms and computationally determined their effect on the oxygen and hydrogen adlayer binding as a function of chemical potential and adsorbate coverage. We further determine the underlying chemical origins that are responsible for these effects and connect them to experimentally tunable quantities. Our results reveal a reliable periodic trend wherein oxygen binding is weakened greatest as one moves right and down the periodic table. Hydrogen binding shows the same trend only at high (but relevant) coverages and otherwise tends to have its binding slightly increased in all systems. Trends with secondary metal coverage are also uncovered and connected to experimentally tunable parameters.

Hensley, Alyssa↗
DOE OSTI2020

Multi-Scale Modeling Framework for Mercury Biogeochemistry

Multi-Scale modeling of mercury (Hg) geochemical speciation and reactions has been performed by integrating atomistic quantum chemical calculations with continuum scale speciation models. Major progress has been made in the improvement of quantum chemical models to calculate critical thermodynamic data for Hg complexes in aquatic environments. Rapid and reliable quantum chemical approaches have been developed for calculating acid dissociation constants (pK a ) and stability constants (log K), with calculated mean unsigned errors of 0.5 and 1.5 log units, respectively for ligand molecules and Hg complexes. At the continuum scale, systematic analysis of uncertainty propagation in mercury (Hg) speciation modeling has been conducted and was used to identify environmental conditions under which thermodynamic constant uncertainties are significant and recommended to be accounted for. The integrated framework for multi-scale modeling of mercury geochemistry is open to the research community through the web-based multiscale modeling aqueous speciation resource, AQUA-MER. The improved quantum chemical approaches for thermodynamic constant calculations are accessible through AQUA-MER and can be used to provide the missing constants in the continuum scale speciation calculations. In addition to low molecular mass Hg complex speciation, modeling natural aquatic environments also involve the transport of high molecular weight dissolved organic matter (DOM) in reactive flows simultaneously with equilibrium and kinetic reactions. To this end, atomistic MD simulations were performed to capture the details of aggregation, mechanisms and distribution of functional groups in DOM at the molecular level. The elemental composition and calculated bulk properties of the DOM models are in close agreement with experimental measurements. A travel-time based reactive transport model in the hyporheic zone of stream corridors was established for the multicomponent Hg-DOM-S system and implemented through PFLOTRAN.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Quantifying the inhibitory impact of soluble phenolics on anaerobic carbon mineralization in a thawing permafrost peatland

The mechanisms controlling the extraordinarily slow carbon (C) mineralization rates characteristic of Sphagnum -rich peatlands (“bogs”) are not fully understood, despite decades of research on this topic. Soluble phenolic compounds have been invoked as potentially significant contributors to bog peat recalcitrance due to their affinity to slow microbial metabolism and cell growth. Despite this potentially significant role, the effects of soluble phenolic compounds on bog peat C mineralization remain unclear. We analyzed this effect by manipulating the concentration of free soluble phenolics in anaerobic bog and fen peat incubations using water-soluble polyvinylpyrrolidone (“PVP”), a compound that binds with and inactivates phenolics, preventing phenolic-enzyme interactions. CO 2 and CH 4 production rates (end-products of anaerobic C mineralization) generally correlated positively with PVP concentration following Michaelis-Menten (M.M.) saturation functions. Using M.M. parameters, we estimated that the extent to which phenolics inhibit anaerobic CO 2 production was significantly higher in the bog—62 ± 16%—than the fen—14 ± 4%. This difference was found to be more substantial with regards to methane production—wherein phenolic inhibition for the bog was estimated at 54 ± 19%, while the fen demonstrated no apparent inhibition. Consistent with this habitat difference, we observed significantly higher soluble phenolic content in bog vs. fen pore-water. Together, these findings suggest that soluble phenolics could contribute to bogs’ extraordinary recalcitrance and high (relative to other peatland habitats) CO 2 :CH 4 production ratios.

59 BASIC BIOLOGICAL SCIENCES↗