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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 271 records · Page 15

Impact of the d 0 transition metal on local structural transformations in disordered rock salt cathodes

Although it is widely accepted that the long-range (average) crystal structure plays a critical role in determining the electrochemical performance of battery materials, the relationship between local structural features and electrochemical performance is rarely studied. Disordered rock salt oxides (DRX), which have become serious contenders for next generation Li-ion electrode materials, provide an ideal platform for exploring correlations between local structure and electrochemical performance as they exhibit a simple face-centered cubic structure and combine long-range disorder and short-range order on the cation sublattice. This work examines the Li 1.1 Mn 0.7 Zr 0.2−x Ti x O 2 series of DRX cathodes and investigates the links between local structure rearrangements and capacity activation. The end-member Li 1.1 Mn 0.7 Zr 0.2 O 2 compound exhibits a low capacity in the as-synthesized state, attributed to unfavorable short-range order that hinders Li-ion transport, yet its capacity increases seven-fold, from 20 to 140 mAh g −1 , after chemical delithiation followed by a 400 °C heat treatment. Capacity activation is associated with the appearance of local spinel-like structural features that depart from the short-range order originally present in the material, without significant change to the bulk composition and average crystal structure. Investigation of a series of Li 1.1 Mn 0.7 Zr 0.2−x Ti x O 2 (x ≤ 0.2) DRX compounds reveals that the correlation length of the spinel-like ordering that emerges during the heat treatment strongly depends on the Zr : Ti ratio. Yet, dramatic capacity activation and electrochemical (pseudo-)plateaus reminiscent of Mn-based spinel cathodes are observed for all compounds irrespective of the size of the ordered domains. To explain this phenomenon, we propose that the DRX phase undergoes a complete transformation to a spinel-like domain structure, which improves bulk Li-ion transport regardless of domain size.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Limits on the Evolutionary Rates of Biological Traits

This paper focuses on the maximum speed at which biological evolution can occur. I derive inequalities that limit the rate of evolutionary processes driven by natural selection, mutations, or genetic drift. These rate limits link the variability in a population to evolutionary rates. In particular, high variances in the fitness of a population and of a quantitative trait allow for fast changes in the trait’s average. In contrast, low variability makes a trait less susceptible to random changes due to genetic drift. The results in this article generalize Fisher’s fundamental theorem of natural selection to dynamics that allow for mutations and genetic drift, via trade-of relations that constrain the evolutionary rates of arbitrary traits. The rate limits can be used to probe questions in various evolutionary biology and ecology settings. They apply, for instance, to trait dynamics within or across species or to the evolution of bacteria strains. They apply to any quantitative trait, e.g., from species’ weights to the lengths of DNA strands.

59 BASIC BIOLOGICAL SCIENCES↗

Coarse grained simulation of convectively driven turbulent mixing, transition, and turbulence decay

Accurate predictions with quantifiable uncertainties are essential to many practical turbulent flow applications exhibiting extreme geometrical complexity and broad ranges of length and time scales. Under-resolved computer simulations are typically unavoidable in such applications, and implicit large-eddy simulation (ILES) often becomes the effective strategy. In this work, we focus on assessing ILES initialized with well-characterized 25 6 3 homogeneous isotropic turbulence datasets generated with direct numerical simulation (DNS). ILES solutions based on the LANL xRAGE code are studied as function of resolution for 6 4 3 , 12 8 3 , 25 6 3 , and 51 2 3 grids. ILES performance of new directionally-unsplit high-order numerical hydrodynamics algorithms in xRAGE is examined in this context. Compared to the initial 25 6 3 DNS, we find longer inertial subranges and higher turbulence Reynolds number (Re) for 25 6 3 and 51 2 3 xRAGE — attributed to having linked DNS (Navier–Stokes based) solutions to nominally inviscid (higher Re) Euler based ILES solutions. For fixed 25 6 3 resolution, we find that significantly larger simulated turbulence Re can be achieved with the higher-order unsplit (vs. split) discretizations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Airfoil Computational Fluid Dynamics - 9k shapes, 2 AoA's

This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 8,996 airfoil shapes, computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this data, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We fixed the linear deformations to be the mean over the database and sampled new shapes over a four-dimensional parameter space of higher-order perturbation. This sampling approaches allows for isolated analysis of non-linear airfoil shape deformations while holding other aspects (e.g., airfoil thickness) approximately constant. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, Reynolds number of 9M, and at two angles of attack, 4 deg. and 12 deg. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_9k_data.ipynb.

9k↗

The genetic basis for panicle trait variation in switchgrass ( Panicum virgatum )

Grass species exhibit large diversity in panicle architecture influenced by genes, the environment, and their interaction. The genetic study of panicle architecture in perennial grasses is limited. In this study, we evaluate the genetic basis of panicle architecture including panicle length, primary branching number, and secondary branching number in an outcrossed switchgrass QTL population grown across ten field sites in the central USA through multi-environment mixed QTL analysis. We also evaluate genetic effects in a diversity panel of switchgrass grown at three of the ten field sites using genome-wide association (GWAS) and multivariate adaptive shrinkage. Furthermore, we search for candidate genes underlying panicle traits in both of these independent mapping populations. Overall, 18 QTL were detected in the QTL mapping population for the three panicle traits, and 146 unlinked genomic regions in the diversity panel affected one or more panicle trait. Twelve of the QTL exhibited consistent effects (i.e., no QTL by environment interactions or no QTL × E), and most (four of six) of the effects with QTL × E exhibited site-specific effects. Most (59.3%) significant partially linked diversity panel SNPs had significant effects in all panicle traits and all field sites and showed pervasive pleiotropy and limited environment interactions. Panicle QTL co-localized with significant SNPs found using GWAS, providing additional power to distinguish between true and false associations in the diversity panel.

59 BASIC BIOLOGICAL SCIENCES↗

High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) was successful at producing a baseline multi-model assessment of global simulations with model grid spacings of 25–50 km in the atmosphere and 10–25 km in the ocean, a significant increase when compared to models with standard resolutions on the order of 1° that are typically used as part of the Coupled Model Intercomparison Project (CMIP) experiments. In addition to over 250 peer-reviewed manuscripts using the published HighResMIP1 datasets, the results were widely cited in the Intergovernmental Panel on Climate Change report and were the basis of a variety of derived datasets, including tracked cyclones (both tropical and extratropical), river discharge, storm surge, and impact studies. There were also suggestions from the few ocean eddy-rich coupled simulations that aspects of climate variability and change might be significantly influenced by improved process representation in such models. The compromises that HighResMIP1 made should now be revisited, given the recent major advances in modelling and computing resources. Aspects that will be reconsidered include experimental design and simulation length, complexity, and resolution. In addition, larger ensemble sizes and a wider range of future scenarios would enhance the applicability of HighResMIP. Therefore, we propose the High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) to improve and extend the previous work, to address new science questions, and to further advance our understanding of the role of horizontal resolution (and hence process representation) in state-of-the-art climate simulations. With further increases in high-performance computing resources and modelling advances, along with the ability to take full advantage of these computational resources, an enhanced investigation of the drivers and consequences of variability and change in both large- and synoptic-scale weather and climate is now possible. With the arrival of global cloud-resolving models (currently run for relatively short timescales), there is also an opportunity to improve links between such models and more traditional CMIP models, with HighResMIP providing a bridge to link understanding between these domains. HighResMIP also aims to link to other CMIP projects and international efforts such as the World Climate Research Program lighthouse activities and various digital twin initiatives. It also has the potential to be used as training and validation data for the fast-evolving machine learning climate models.

54 ENVIRONMENTAL SCIENCES↗

Wildfire-dependent changes in soil microbiome diversity and function

Abstract Forest soil microbiomes have crucial roles in carbon storage, biogeochemical cycling and rhizosphere processes. Wildfire season length, and the frequency and size of severe fires have increased owing to climate change. Fires affect ecosystem recovery and modify soil microbiomes and microbially mediated biogeochemical processes. To study wildfire-dependent changes in soil microbiomes, we characterized functional shifts in the soil microbiota (bacteria, fungi and viruses) across burn severity gradients (low, moderate and high severity) 1 yr post fire in coniferous forests in Colorado and Wyoming, USA. We found severity-dependent increases of Actinobacteria encoding genes for heat resistance, fast growth, and pyrogenic carbon utilization that might enhance post-fire survival. We report that increased burn severity led to the loss of ectomycorrhizal fungi and less tolerant microbial taxa. Viruses remained active in post-fire soils and probably influenced carbon cycling and biogeochemistry via turnover of biomass and ecosystem-relevant auxiliary metabolic genes. Our genome-resolved analyses link post-fire soil microbial taxonomy to functions and reveal the complexity of post-fire soil microbiome activity.

59 BASIC BIOLOGICAL SCIENCES↗

Prediction of the structures and heats of formation of MO 2 , MO 3 , and M 2 O 5 for M = V, Nb, Ta, Pa

Structures for the mono-, di-, and tri-bridge isomers of M 2 O 5 as well as those for the MO 2 and MO 3 fragments for M = V, Nb, Ta, and Pa were optimized at the density functional theory (DFT) level. Single point CCSD(T) calculations extrapolated to the complete basis set (CBS) limit at the DFT geometries were used to predict the energetics. Here, the lowest energy dimer isomer was the di-bridge for M = V and Nb and the tri-bridge for M = Ta and Pa. The di-bridge isomers were predicted to be composed of MO 2 + and MO 3 - fragments, whereas the mono- and tri-bridge are two MO 2 + fragments linked by an O 2 - . The heats of formation of M 2 O 5 dimers, as well as MO 2 and MO 3 neutral and ionic species were predicted using the Feller–Peterson–Dixon (FPD) approach. The heats of formation of the MF 5 species were calculated to provide additional benchmarks. Dimerization energies to form the M 2 O 5 dimers are predicted to become more negative going down group 5 and range from -29 to -45 kcal mol -1 . The ionization energies (IEs) for VO 2 and TaO 2 are essentially the same at 8.75 eV whereas the IEs for NbO 2 and PaO 2 are 8.10 and 6.25 eV, respectively. The predicted adiabatic electron affinities (AEAs) range from 3.75 eV to 4.45 eV for the MO 3 species and vertical detachment energies from 4.21 to 4.59 eV for MO 3 - . The calculated M[double bond, length as m-dash]O bond dissociation energies increase from 143 kcal mol -1 for M = V to ~170 kcal mol -1 for M = Nb and Ta to ~200 kcal mol -1 for M = Pa. The M–O bond dissociation energies are all similar ranging from 97 to 107 kcal mol -1 . Natural bond analysis provided insights into the types of chemical bonds in terms of their ionic character. Pa 2 O 5 is predicted to behave like an actinyl species dominated by the interactions of approximately linear PaO 2 + groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Permeability and Induced Polarization of Mudstones

Electrical measurements can be used to estimate hydraulic properties such as permeability ( k ) in sedimentary rocks. Previous work has focused on sandstones, siltstones, and carbonates, while investigations on mudstones have rarely been reported. In this study, we report on electrical geophysical measurements for 23 mudstone samples using an experimental approach designed to reliably saturate these low permeability mudstones. The modified Hagen-Poiseuille model linking permeability to the formation factor ( F ) and an effective pore radius ( r ) provides an excellent fit to the data set with a near-constant pore radius, indicating that the effective porosity (1/ F ) is the controlling factor on k . In these samples, the surface area normalized to pore volume ( S por ), frequently used in permeability estimation models, varies by 1–2 orders of magnitude and is thus not a reliable proxy of the inverse effective hydraulic radius. The formation factor also exerts the primary control on induced polarization (IP) parameters, whereas Spor shows no relation to the IP parameters. A strong linear relationship is found between IP parameters (imaginary conductivity and normalized chargeability) and surface conductivity, although the proportionality factor is significantly lower than those observed in more permeable rocks and sediments. Apparent relationships between the polarization strength-derived and time constant-derived geophysical length scales and the effective hydraulic radius appear to be driven by variations in the electrochemical parameters (i.e., specific polarizability and diffusion coefficient). Overall, these findings emphasize that predicting hydraulic properties from electrical measurements in fine-grained rocks remains challenging and requires further investigation into the electrochemical properties involved.

58 GEOSCIENCES↗

Xylella fastidiosa modulates exopolysaccharide polymer length and the dynamics of biofilm development with a β-1,4-endoglucanase

Xylella fastidiosa is a Gram-negative bacterium that causes disease in many economically important crops. It colonizes the plant host xylem and the mouthparts of its insect vectors where it produces exopolysaccharide (EPS) and forms robust biofilms. Typically, the ability to form a biofilm enhances virulence, but X. fastidiosa does not fit neatly into that paradigm. Instead, X. fastidiosa enters into biofilms to attenuate its movement in the xylem, which, in turn, slows disease progression. In most of its over 600 known plant hosts, X. fastidiosa behaves as a benign commensal, but in some hosts like Vitis vinifera grapevines, it acts as a pathogen. Its ability to attenuate its own virulence in susceptible hosts may be a remnant of its commensal lifestyle in other hosts. Here, we demonstrate that X. fastidiosa utilizes a β-1,4 endoglucanase to cleave its self-produced β-1,4-glucan exopolysaccharide polymer to process it from a higher molecular weight to a lower molecular weight polymer. This processing mediates surface adherence of the cells and ultimately governs overall biofilm architecture, indicating enzymatic pruning of the EPS plays a key role in biofilm-mediated attenuation of X. fastidiosa in planta and, thus, is a key vestige that links its commensal behaviors to its parasitic behaviors in specific hosts.

59 BASIC BIOLOGICAL SCIENCES↗

Mesh objective stochastic simulations of quasibrittle fracture

Continuum finite element (FE) modeling of damage and failure of quasibrittle structures suffers from the spurious mesh sensitivity due to strain localization. Here this issue has been addressed for deterministic analysis through the development of localization limiters. Here this study proposes a mechanism-based model to mitigate the mesh sensitivity in stochastic FE simulations of quasibrittle fracture. The interest is placed on the analysis of large-size structures, where the mesh size is conveniently chosen to be larger than the width of the fracture process zone as well as the correlation length of the random fields of constitutive properties. The present model is formulated within the framework of continuum damage mechanics. Two localization parameters are introduced to describe the evolution of the damage pattern of each finite element. These parameters are used to guide the energy regularization of the constitutive law, as well as to formulate the mesh-dependent probability distributions of constitutive properties. Depending on the prevailing damage pattern, different energy regularization schemes and mesh dependence of the probability distribution functions are used in the constitutive law. The model is applied to simulate the stochastic failure behavior of quasibrittle structures of different geometries featuring different failure processes including damage initiation, localization, and propagation. It is shown that using fixed probability distribution functions of constitutive properties could lead to strong mesh dependence of the prediction of the mean and variance of the structural load capacity. The probability distribution functions of constitutive properties must be linked to the damage pattern, which may evolve during the failure process. Such a mechanism-based modeling of the probability distributions of constitutive properties is essential for mitigating the spurious mesh sensitivity in stochastic FE analysis of quasibrittle fracture.

42 ENGINEERING↗

Salinity and hydraulic retention time induce membrane phospholipid acyl chain remodeling in Halanaerobium congolense WG10 and mixed cultures from hydraulically fractured shale wells

Bacteria remodel their plasma membrane lipidome to maintain key biophysical attributes in response to ecological disturbances. For Halanaerobium and other anaerobic halotolerant taxa that persist in hydraulically fractured deep subsurface shale reservoirs, salinity, and hydraulic retention time (HRT) are important perturbants of cell membrane structure, yet their effects remain poorly understood. Membrane-linked activities underlie in situ microbial growth kinetics and physiologies which drive biogeochemical reactions in engineered subsurface systems. Hence, we used gas chromatography–mass spectrometry (GC–MS) to investigate the effects of salinity and HRT on the phospholipid fatty acid composition of H. congolense WG10 and mixed enrichment cultures from hydraulically fractured shale wells. We also coupled acyl chain remodeling to membrane mechanics by measuring bilayer elasticity using atomic force microscopy (AFM). For these experiments, cultures were grown in a chemostat vessel operated in continuous flow mode under strict anoxia and constant stirring. Our findings show that salinity and HRT induce significant changes in membrane fatty acid chemistry of H. congolense WG10 in distinct and complementary ways. Notably, under nonoptimal salt concentrations (7% and 20% NaCl), H. congolense WG10 elevates the portion of polyunsaturated fatty acids (PUFAs) in its membrane, and this results in an apparent increase in fluidity (homeoviscous adaptation principle) and thickness. Double bond index (DBI) and mean chain length (MCL) were used as proxies for membrane fluidity and thickness, respectively. These results provide new insight into our understanding of how environmental and engineered factors might disrupt the physical and biogeochemical equilibria of fractured shale by inducing physiologically relevant changes in the membrane fatty acid chemistry of persistent microbial taxa. GRAPHICAL ABSTRACT Salinity significantly alters membrane bilayer fluidity and thickness in Halanaerobium congolense WG10.

03 NATURAL GAS↗

Airfoil Computational Fluid Dynamics - 2k shapes, 25 AoA's, 3 Re numbers

This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 1,830 airfoil shapes computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this dataset, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We sampled airfoil designs over both parameter spaces to explore the full range of possible shape variations. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, for or three different Reynolds' numbers (3M, 6M, and 9M), and for 25 angles of attack from -4 deg. to 20 deg. with 1 degree increments. Across all these various parameters, this dataset includes the results from over 250,000 CFD simulations. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy, in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_2k_data.ipynb.

2k↗

Root anatomy helps to reconcile observed root trait syndromes in tropical tree species

Premise Studying the organization of functional traits in plant leaves and stems has revealed notable patterns linking function and form; however, evidence of similarly robust organization in root tissues remains controversial. We posit that anatomical traits in roots can provide insight on the overall organization of the root system. We hypothesized that size variation in the tissue outside the stele is related in a nonlinear fashion with functional traits associated with direct resource uptake, including a negative relationship with root architectural traits, and that similar relationships detected in tropical areas also hold true in other biomes. Methods We addressed our hypotheses using empirical data from 24 tropical tree species in French Guiana, including anatomical measurements in first order roots and functional trait description for the entire fine root system. In addition, we compiled a global meta‐analysis of root traits for 500+ forest species across tropical, subtropical, and temperate forests. Results Our results supported the expected nonlinear relationships between cortical size and morphological traits and a negative linear trend with architectural traits. We confirmed a global negative relationship among specific root length (SRL), diameter, and tissue density, suggesting similar anatomical constraints in root systems across woody plants. However, the importance of factors varies across biomes, possibly related to the unequal phylogenetic representation across latitudes. Conclusions Our findings imply that the rhizocentric hypothesis can be a valuable approach to understand fine root trait syndromes and the evolution of absorptive roots in vascular plants.

Valverde‐Barrantes, Oscar J.↗

Diverse PFAS produce unique transcriptomic changes linked to developmental toxicity in zebrafish

Per- and polyfluoroalkyl substances (PFAS) are a widespread and persistent class of contaminants posing significant environmental and human health concerns. Comprehensive understanding of the modes of action underlying toxicity among structurally diverse PFAS is mostly lacking. To address this need, we recently reported on our application of developing zebrafish to evaluate a large library of PFAS for developmental toxicity. In the present study, we prioritized 15 bioactive PFAS that induced significant morphological effects and performed RNA-sequencing to characterize early transcriptional responses at a single timepoint (48 h post fertilization) after early developmental exposures (8 h post fertilization). Internal concentrations of 5 of the 15 PFAS were measured from pooled whole fish samples across multiple timepoints between 24–120 h post fertilization, and additional temporal transcriptomics at several timepoints (48–96 h post fertilization) were conducted for Nafion byproduct 2. A broad range of differentially expressed gene counts were identified across the PFAS exposures. Most PFAS that elicited robust transcriptomic changes affected biological processes of the brain and nervous system development. While PFAS disrupted unique processes, we also found that similarities in some functional head groups of PFAS were associated with the disruption in expression of similar gene sets. Body burdens after early developmental exposures to select sulfonic acid PFAS, including Nafion byproduct 2, increased from the 24–96 h post fertilization sampling timepoints and were greater than those of sulfonamide PFAS of similar chain lengths. In parallel, the Nafion byproduct 2-induced transcriptional responses increased between 48 and 96 h post fertilization. PFAS characteristics based on toxicity, transcriptomic effects, and modes of action will contribute to further prioritization of PFAS structures for testing and informed hazard assessment.

59 BASIC BIOLOGICAL SCIENCES↗

Amphiphile Organization in Organic Solutions: An Alternative Explanation for Small-Angle X-ray Scattering Features in Malonamide/Alkane Mixtures

In this work, the role of different intermolecular interactions in the aggregation of amphiphiles in an organic solvent is studied for systems of relevance to liquid-liquid extraction (LLE), a chemical process used to selectively recover metals from complex mixtures. Of specific interest is the role, or lack thereof, of hydrogen bonding, which is often assumed to be a main driver of the organic phase structural organization that has been linked to separation efficacy. Toward that end, a series of malonamide extractants in n-dodecane have been studied in the absence of any extracted aqueous solutes, including water. The series of extractants includes N,N'-dimethyl-N,N'-dibutyltetradecylmalonamide (DMDBTDMA), two of its homologs, and N,N'-dimethyl-N,N'-dioctylhexylethoxymalonamide (DMDOHEMA). This simplified model LLE system enables systematic investigation of the role of dipole-dipole and alkyl tail steric interactions in amphiphile aggregation. Small-angle X-ray scattering (SAXS) profiles computed from molecular dynamics trajectories are in good agreement with experimental SAXS data. Molecular dynamics simulations show that malonamide aggregation results from dipole-driven self-association and lacks characteristic aggregate sizes. Mid-q correlation peaks in the SAXS profiles emerge at high concentration for each malonamide. In those densely packed solutions, the correlation peaks are observed to result from alkyl tail-induced spacing between electron-rich polar head groups, with peak positions determined by the different alkyl tail lengths present in the malonamide molecule. This explanation of the SAXS correlation peaks contrasts with the prevailing literature, which attributes mesoscale features observed in small-angle scattering to the formation of microemulsions. Instead, this work finds that these features are present in the absence of water or any reverse micellar organization of the malonamides. As such, molecular-scale malonamide self-association and packing, rather than microemulsion-based colloidal-scale descriptions, is a more appropriate framework for these LLE systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

River sinuosity describes a continuum between randomness and ordered growth

River channels are among the most common landscape features on Earth. An essential characteristic of channels is sinuosity: their tendency to take a circuitous path, which is quantified as along-stream length divided by straight-line length. River sinuosity is interpreted as a characteristic that either forms randomly at channel inception or develops over time as meander bends migrate. Studies tend to assume the latter and thus have used river sinuosity as a proxy for both modern and ancient environmental factors including climate, tectonics, vegetation, and geologic structure. But no quantitative criterion for planform expression has distinguished between random, initial sinuosity and that developed by ordered growth through channel migration. This ambiguity calls into question the utility of river sinuosity for understanding Earth’s history. We propose a quantitative framework to reconcile these competing explanations for river sinuosity. Using a coupled analysis of modeled and natural channels, we show that while a majority of observed sinuosity is consistent with randomness and limited channel migration, rivers with sinuosity ≥1.5 likely formed their geometry through sustained, ordered growth due to channel migration. This criterion frames a null hypothesis for river sinuosity that can be applied to evaluate the significance of environmental interpretations in landscapes shaped by rivers. The quantitative link between sinuosity and channel migration further informs strategies for preservation and restoration of riparian habitat and guides predictions of fluvial deposits in the rock record and in remotely sensed environments from the seafloor to planetary surfaces.

58 GEOSCIENCES↗

Adjustments to the law of the wall above an Amazon forest explained by a spectral link

Modification to the law of the wall represented by a dimensionless correction function ϕ RSL (z/h) is derived using atmospheric turbulence measurements collected at two sites in the Amazon in near-neutral stratification, where z is the distance from the forest floor and h is the mean canopy height. The sites are the Amazon Tall Tower Observatory for z/h∈ [1,2.3] and the Green Ocean Amazon (GoAmazon) site for z/h∈ [1,1.4]. Here, a link between the vertical velocity spectrum E ww (k) (k is the longitudinal wavenumber) and ϕ RSL is then established using a co-spectral budget (CSB) model interpreted by the moving-equilibrium hypothesis. The key finding is that ϕ RSL is determined by the ratio of two turbulent viscosities and is given as ν t,BL /ν t,RSL, where ν t,RSL = (1/A)∫$^{∞}_{0}$ τ(k)E ww (k)dk, ν t,BL = k v (z−d)u * , τ(k) is a scale-dependent decorrelation time scale between velocity components, A = C R /(1−C I ) = 4.5 is predicted from the Rotta constant C R = 1.8, and the isotropization of production constant C I = 3/5 given by rapid distortion theory, k v is the von Kármán constant, u * is the friction velocity at the canopy top, and d is the zero-plane displacement. Because the transfer of energy across scales is conserved in E ww (k) and is determined by the turbulent kinetic energy dissipation rate (ε), the CSB model also predicts that ϕ RSL scales with L BL /L d , where L BL is the length scale of attached eddies to z = d, and L d = u$_{*}^{3}$/ε is a macro-scale dissipation length.

54 ENVIRONMENTAL SCIENCES↗