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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A peripheral component interconnect express-based scalable and highly integrated pulsed spectrometer for solution state dynamic nuclear polarization

High sensitivity, high data rates, fast pulses, and accurate synchronization all represent challenges for modern nuclear magnetic resonance spectrometers, which make any expansion or adaptation of these devices to new techniques and experiments difficult. Here, we present a Peripheral Component Interconnect Express (PCIe)-based highly integrated distributed digital architecture pulsed spectrometer that is implemented with electron and nucleus double resonances and is scalable specifically for broad dynamic nuclear polarization (DNP) enhancement applications, including DNP-magnetic resonance spectroscopy/imaging (DNP-MRS/MRI). The distributed modularized architecture can implement more transceiver channels flexibly to meet a variety of MRS/MRI instrumentation needs. The proposed PCIe bus with high data rates can significantly improve data transmission efficiency and communication reliability and allow precise control of pulse sequences. An external high speed double data rate memory chip is used to store acquired data and pulse sequence elements, which greatly accelerates the execution of the pulse sequence, reduces the TR (time of repetition) interval, and improves the accuracy of TR in imaging sequences. Using clock phase-shift technology, we can produce digital pulses accurately with high timing resolution of 1 ns and narrow widths of 4 ns to control the microwave pulses required by pulsed DNP and ensure overall system synchronization. The proposed spectrometer is proved to be both feasible and reliable by observation of a maximum signal enhancement factor of approximately −170 for {sup 1}H, and a high quality water image was successfully obtained by DNP-enhanced spin-echo {sup 1}H MRI at 0.35 T.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Why double-stranded RNA resists condensation

The addition of small amounts of multivalent cations to solutions containing double-stranded DNA leads to attraction between the negatively charged helices and eventually to condensation. Surprisingly, this effect is suppressed in double-stranded RNA, which carries the same charge as the DNA, but assumes a different double helical form. However, additional characterization of short (25 base-pairs) nucleic acid (NA) duplex structures by circular dichroism shows that measured differences in condensation are not solely determined by duplex helical geometry. Here we combine experiment, theory, and atomistic simulations to propose a mechanism that connects the observed variations in condensation of short NA duplexes with the spatial variation of cobalt hexammine (CoHex) binding at the NA duplex surface. The atomistic picture that emerged showed that CoHex distributions around the NA reveals two major NA-CoHex binding modes -- internal and external -- distinguished by the proximity of bound CoHex to the helical axis. Decreasing trends in experimentally observed condensation propensity of the four studied NA duplexes (from B-like form of homopolymeric DNA, to mixed sequence DNA, to DNA:RNA hybrid, to A-like RNA) are explained by the progressive decrease of a single quantity: the fraction of CoHex ions in the external binding mode. Thus, while NA condensation depends on a complex interplay between various structural and sequence features, our coupled experimental and theoretical results suggest a new model in which a single parameter connects the NA condensation propensity with geometry and sequence dependence of CoHex binding.

ELECTROSTATICS↗
DOE OSTI2024

Seedling nitrogen uptake and rhizodeposition between mycorrhizal types

Tree mycorrhizal associations are associated with patterns in N cycling and soil organic matter (SOM) storage, however, we still lack a mechanistic understanding of what tree and fungal traits drive these patterns and how they will respond to global changes in soil N availability. To address this knowledge gap, we investigated how arbuscular mycorrhizal (AM)- and ectomycorrhizal (EcM)-associated seedlings alter rhizodeposition in response to increased inorganic N acquisition. Specifically, we conducted this greenhouse experiment in a sealed labeling chamber with an enriched 13Carbon atmosphere and 15Nitrogen enriched fertilizer over the course of five months from April 2021 - August 2021. To include the variability across tree species, we grew eight species of seedlings belonging to eight families that were either arbuscular (Acer rubrum, Nyssa sylvatica, Thuja occidentalis, and Prunus seritina) or ectomycorrhizal-associated (Quercus rubra, Tilia americana, Pinus strobus, and Betula lenta). We measured rhizodeposition (mg 13C), plant N uptake from fertilizer (mg N), net soil carbon, and the abundance of mycorrhizal fungi (ITS sequencing and qPCR). We also characterized fungal (ITS2) and bacterial (16S) soil communities.The data from this project are ".csv" files that can up downloaded into a folder, and then run in the associated R markdown scripts after changing the source folder location at the top of the script. These data include raw outputs and processed files (using the R markdown files) for seedling growth and biomass, 15N content, soil 13C content, raw reads and processed file versions for fungal and bacterial ASVS, and a final summary file used for modeling. R software is needed to run these data, and the packages needed are listed at the top of the R markdown file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

GrainNN: A neighbor-aware long short-term memory network for predicting microstructure evolution during polycrystalline grain formation

High fidelity simulations of grain formation in alloys are an indispensable tool for process-to-mechanical-properties characterization. Such simulations, however, can be computationally expensive as they require fine spatial and temporal discretizations. Their cost becomes an obstacle to parametric studies and ensemble runs and ultimately makes downstream tasks like optimal control and uncertainty quantification challenging. To enable such downstream tasks, we introduce GrainNN, an efficient and accurate reduced-order model for epitaxial grain growth in additive manufacturing conditions. GrainNN is a sequence-to-sequence long-short-term-memory (LSTM) deep neural network that evolves the dynamics of manually crafted features. Its innovations are (1) an attention mechanism with grain-microstructure-specific transformer architecture; and (2) an overlapping combination of several clones of the network to generalize to grain configurations that are different from those used for training. This design enables GrainNN to predict grain formation for unseen physical parameters, grain number, domain size and geometry. Furthermore, GrainNN not only reconstructs the quantities of interest but also can be pointwise accurate. In our numerical experiments, we use a polycrystalline phase field method to both generate the training data and assess GrainNN. For multiparametric, ensemble simulations with many grains, GrainNN can be orders of magnitude faster than phase field simulations, while delivering 5%–15% pointwise error. Additionally, this speedup includes the cost of the phase field simulations for generating training data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Predicting and Synthesizing Interface Stabilized 2D Layers

The compound (Pb 2 MnSe 3 ) 0.6 VSe 2 was predicted to be kinetically stable based on density functional theory (DFT) calculations on an island of Pb 2 MnSe 3 between layers of VSe 2 . This approach provides a high degree of freedom by not forcing interlayer lattice match, making it ideal to investigate the likelihood of formation of new incommensurate layer misfit structures. The free space around the island is critical, as it allows atoms to diffuse and hence exploring the local energy landscape around the initial configuration. (Pb 2 MnSe 3 ) 0.6 VSe 2 was synthesized via a near diffusionless reaction from precursors where a repeating sequence of elemental layers matches the local composition and layer sequence of the predicted compound. The VSe 2 layer consists of a Se–V–Se trilayer with octahedral coordination of the V atoms. The Pb 2 MnSe 3 layer consists of three rock-salt-like planes, with a MnSe layer between the planes of PbSe. The center MnSe plane stabilizes the puckering of the outer PbSe layers. Electrical properties indicate that (Pb 2 Mn 1 Se 3 ) 0.6 VSe 2 undergoes a charge density wave transition at ~100 K and orders ferromagnetically at 35 K. Overall, the combination of theory and experiment enables a faster convergence to new heterostructures than either approach in isolation.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Measurement of Radioactive Contamination in the High-Resistivity Silicon CCDs of the DAMIC Experiment

We present measurements of radioactive contamination in the high-resistivity silicon charge-coupled devices (CCDs) used by the DAMIC experiment to search for dark matter particles. Novel analysis methods, which exploit the unique spatial resolution of CCDs, were developed to identify α and β particles. Uranium and thorium contamination in the CCD bulk was measured through α spectroscopy, with an upper limit on the 238 U ( 232 Th) decay rate of 5 (15) kg -1 d -1 at 95% CL. We also searched for pairs of spatially correlated electron tracks separated in time by up to tens of days, as expected from 32 Si – 32 P or 210 Pb – 210 Bi sequences of b decays. The decay rate of 32Si was found to be 80 +110 -65 (95% CI). An upper limit of ~35 kg -1 d -1 (95% CL) on the 210 Pb decay rate was obtained independently by α spectroscopy and the β decay sequence search. Furthermore, these levels of radioactive contamination are sufficiently low for the successful operation of CCDs in the forthcoming 100 g DAMIC detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

The MURAVES Experiment: A Study of the Vesuvius Great Cone with Muon Radiography

The MURAVES experiment aims at the muographic imaging of the internal structure of the summit of Mt. Vesuvius, exploiting muons produced by cosmic rays. Though presently quiescent, the volcano carries a dramatic hazard in its highly populated surroundings. The challenging measurement of the rock density distribution in its summit by muography, in conjunction with data from other geophysical techniques, can help the modeling of possible eruptive dynamics. The MURAVES apparatus consists of an array of three independent and identical muon trackers, with a total sensitive area of 3 square meters. In each tracker, a sequence of 4 XY tracking planes made of plastic scintillators is complemented by a 60 cm thick lead wall inserted between the two downstream planes to improve rejection of background from low-energy muons. The apparatus is currently acquiring data. Preliminary results from the analysis of the first data sample are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

On the Rapid Calculation of Binding Affinities for Antigen and Antibody Design and Affinity Maturation Simulations

The accurate and efficient calculation of protein-protein binding affinities is an essential component in antibody and antigen design and optimization, and in computer modeling of antibody affinity maturation. Such calculations remain challenging despite advances in computer hardware and algorithms, primarily because proteins are flexible molecules, and thus, require explicit or implicit incorporation of multiple conformational states into the computational procedure. The astronomical size of the amino acid sequence space further compounds the challenge by requiring predictions to be computed within a short time so that many sequence variants can be tested. In this study, we compare three classes of methods for antibody/antigen (Ab/Ag) binding affinity calculations: (i) a method that relies on the physical separation of the Ab/Ag complex in equilibrium molecular dynamics (MD) simulations, (ii) a collection of 18 scoring functions that act on an ensemble of structures created using homology modeling software, and (iii) methods based on the molecular mechanics-generalized Born surface area (MM-GBSA) energy decomposition, in which the individual contributions of the energy terms are scaled to optimize agreement with the experiment. When applied to a set of 49 antibody mutations in two Ab/HIV gp120 complexes, all of the methods are found to have modest accuracy, with the highest Pearson correlations reaching about 0.6. In particular, the most computationally intensive method, i.e., MD simulation, did not outperform several scoring functions. The optimized energy decomposition methods provided marginally higher accuracy, but at the expense of requiring experimental data for parametrization. Within each method class, we examined the effect of the number of independent computational replicates, i.e., modeled structures or reinitialized MD simulations, on the prediction accuracy. We suggest using about ten modeled structures for scoring methods, and about five simulation replicates for MD simulations as a rule of thumb for obtaining reasonable convergence. We anticipate that our study will be a useful resource for practitioners working to incorporate binding affinity calculations within their protein design and optimization process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Modifying a covarying protein–DNA interaction changes substrate preference of a site-specific endonuclease

Abstract Identifying and validating intermolecular covariation between proteins and their DNA-binding sites can provide insights into mechanisms that regulate selectivity and starting points for engineering new specificity. LAGLIDADG homing endonucleases (meganucleases) can be engineered to bind non-native target sites for gene-editing applications, but not all redesigns successfully reprogram specificity. To gain a global overview of residues that influence meganuclease specificity, we used information theory to identify protein–DNA covariation. Directed evolution experiments of one predicted pair, 227/+3, revealed variants with surprising shifts in I-OnuI substrate preference at the central 4 bases where cleavage occurs. Structural studies showed significant remodeling distant from the covarying position, including restructuring of an inter-hairpin loop, DNA distortions near the scissile phosphates, and new base-specific contacts. Our findings are consistent with a model whereby the functional impacts of covariation can be indirectly propagated to neighboring residues outside of direct contact range, allowing meganucleases to adapt to target site variation and indirectly expand the sequence space accessible for cleavage. We suggest that some engineered meganucleases may have unexpected cleavage profiles that were not rationally incorporated during the design process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Mining the phytomicrobiome to understand how bacterial coinoculations enhance plant growth

In previous work, we showed that coinoculating Rhizobium leguminosarum bv. viciae 128C53 and Bacillus simplex 30N-5 onto Pisum sativum L. roots resulted in better nodulation and increased plant growth. We now expand this research to include another alpha-rhizobial species as well as a beta-rhizobium, Burkholderia tuberum STM678. We first determined whether the rhizobia were compatible with B. simplex 30N-5 by cross-streaking experiments, and then Medicago truncatula and Melilotus alba were coinoculated with B. simplex 30N-5 and Sinorhizobium (Ensifer) meliloti to determine the effects on plant growth. Similarly, B. simplex 30N-5 and Bu. tuberum STM678 were coinoculated onto Macroptilium atropurpureum . The exact mechanisms whereby coinoculation results in increased plant growth are incompletely understood, but the synthesis of phytohormones and siderophores, the improved solubilization of inorganic nutrients, and the production of antimicrobial compounds are likely possibilities. Because B. simplex 30N-5 is not widely recognized as a Plant Growth Promoting Bacterial (PGPB) species, after sequencing its genome, we searched for genes proposed to promote plant growth, and then compared these sequences with those from several well studied PGPB species. In addition to genes involved in phytohormone synthesis, we detected genes important for the production of volatiles, polyamines, and antimicrobial peptides as well as genes for such plant growth-promoting traits as phosphate solubilization and siderophore production. Experimental evidence is presented to show that some of these traits, such as polyamine synthesis, are functional in B. simplex 30N-5, whereas others, e.g., auxin production, are not.

Plant Sciences↗
DOE OSTI2016

The high-mass end of the red sequence at z ~ 0.55 from SDSS-III/BOSS: completeness, bimodality and luminosity function

The history of the expanding universe is encoded in the large-scale distribution of galaxies throughout space. By mapping out the three-dimensional locations of millions of galaxies with powerful telescopes, we can directly measure this expansion history. When interpreted using Einstein's theory of gravity, this expansion history lets us infer the contents of the universe, including the amount and nature of "dark energy", an as-yet unexplained energy density associated with the empty vacuum of space. However, to make these measurements and inferences accurately, we must understand and control for a large number of experimental effects. This paper develops a novel method for large cosmological galaxy surveys, and applies it to data from the "BOSS" experiment of the Third Sloan Digital Sky Survey. This method enables an accurate statistical characterization of the "completeness" of the BOSS experiment: the probability that a given galaxy at a given place in the universe is actually detected and successfully measured. It also enables the accurate determination of the underlying demographics of the galaxy population being studied by the experiment. These two ingredients can then be used to make a more accurate comparison between the results of the experiment and the theoretical models that predict the observable effects of dark energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Evolution of A-Type Macrosegregation in Large Size Steel Ingot After Multistep Forging and Heat Treatment

A-type macrosegregation refers to the channel chemical heterogeneities that can be formed during solidification in large size steel ingots. In this research, a combination of experiment and simulation was used to study the influence of open die forging parameters on the evolution of A-type macrosegregation patterns during a multistep forging of a 40 metric ton (MT) cast, high-strength steel ingot. Macrosegregation patterns were determined experimentally by macroetch along the longitudinal axis of the forged and heat-treated ingot. Mass spectroscopy, on more than 900 samples, was used to determine the chemical composition map of the entire longitudinal sectioned surface. FORGE NxT 1.1 finite element modeling code was used to predict the effect of forging sequences on the morphology evolution of A-type macrosegregation patterns. For this purpose, grain flow variables were defined and implemented in a large scale finite element modeling code to describe oriented grains and A-type segregation patterns. Examination of the A-type macrosegregation showed four to five parallel continuous channels located nearly symmetrical to the axis of the forged ingot. In some regions, the A-type patterns became curved or obtained a wavy form in contrast to their straight shape in the as-cast state. Mass spectrometry analysis of the main alloying elements (C, Mn, Ni, Cr, Mo, Cu, P, and S) revealed that carbon, manganese, and chromium were the most segregated alloying elements in A-type macrosegregation patterns. The observed differences were analyzed using thermodynamic calculations, which indicated that changes in the chemical composition of the liquid metal can affect the primary solidification mode and the segregation intensity of the alloying elements. Finite element modeling simulation results showed very good agreement with the experimental observations, thereby allowing for the quantification of the influence of temperature and deformation on the evolution of the shape of the macrosegregation channels during the open die forging process.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Parallel Guanine Duplex and Cytosine Duplex DNA with Uninterrupted Spines of Ag I -Mediated Base Pairs

Here, hydrogen bonding between nucleobases produces diverse DNA structural motifs, including canonical duplexes, guanine (G) quadruplexes, and cytosine (C) i-motifs. Incorporating metal-mediated base pairs into nucleic acid structures can introduce new functionalities and enhanced stabilities. Here we demonstrate, using mass spectrometry (MS), ion mobility spectrometry (IMS), and fluorescence resonance energy transfer (FRET), that parallel-stranded structures consisting of up to 20 G–Ag I –G contiguous base pairs are formed when natural DNA sequences are mixed with silver cations in aqueous solution. FRET indicates that duplexes formed by poly(cytosine) strands with 20 contiguous C–Ag I –C base pairs are also parallel. Silver-mediated G-duplexes form preferentially over G-quadruplexes, and the ability of Ag + to convert G-quadruplexes into silver-paired duplexes may provide a new route to manipulating these biologically relevant structures. IMS indicates that G-duplexes are linear and more rigid than B-DNA. DFT calculations were used to propose structures compatible with the IMS experiments. Such inexpensive, defect-free, and soluble DNA-based nanowires open new directions in the design of novel metal-mediated DNA nanotechnology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Plant Diversity and Fertilizer Management Shape the Belowground Microbiome of Native Grass Bioenergy Feedstocks

Plants may actively cultivate microorganisms in their roots and rhizosphere that enhance their nutrition. To develop cropping strategies that substitute mineral fertilizers for beneficial root symbioses, we must first understand how microbial communities associated with plant roots differ among plant taxa and how they respond to fertilization. Arbuscular mycorrhizal (AM) fungi and rhizobacteria are of particular interest because they enhance nutrient availability to plants and perform a suite of nutrient cycling functions. The purpose of this experiment is to examine the root and soil microbiome in a longterm switchgrass ( Panicum virgatum ) biofuel feedstock experiment and determine how AM fungi and rhizobacteria respond to plant diversity and soil fertility. We hypothesize that intra- and interspecific plant diversity, nitrogen fertilization (+N), and their interaction will influence the biomass and community composition of AM fungi and rhizobacteria. We further hypothesize that +N will reduce the abundance of nitrogenase-encoding nifH genes on the rhizoplane. Roots and soils were sampled from three switchgrass cultivars (Cave-in-Rock, Kanlow, Southlow) grown in monoculture, intraspecific mixture, and interspecific planting mixtures with either Andropogon gerardii or diverse native tallgrass prairie species. Molecular sequencing was performed on root and soil samples, fatty acid extractions were assessed to determine microbial biomass, and quantitative polymerase chain reaction (qPCR) was performed on nifH genes from the rhizoplane. Sequence data determined core AM fungal and bacterial microbiomes and indicator taxa for plant diversity and +N treatments. We found that plant diversity and +N influenced AM fungal biomass and community structure. Across all plant diversity treatments, +N reduced the biomass of AM fungi and nifH gene abundance by more than 40%. The AM fungal genus Scutellospora was an indicator for +N, with relative abundance significantly greater under +N and in monoculture treatments. Community composition of rhizobacteria was influenced by plant diversity but not by +N. Verrucomicrobia and Proteobacteria were the dominant bacterial phyla in both roots and soils. Our findings provide evidence that soil fertility and plant diversity structure the root and soil microbiome. Optimization of soil communities for switchgrass production must take into account differences among cultivars and their unique responses to shifts in soil fertility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Structural phylogeny by profile extraction and multiple superimposition using electrostatic congruence as a discriminator

Phylogenetic analysis of proteins using multiple sequence alignment (MSA) assumes an underlying evolutionary relationship in these proteins which occasionally remains undetected due to considerable sequence divergence. Structural alignment programs have been developed to unravel such fuzzy relationships. However, none of these structure based methods have used electrostatic properties to discriminate between spatially equivalent residues. We present a methodology for MSA of a set of related proteins with known structures using electrostatic properties as an additional discriminator (STEEP). STEEP first extracts a profile, then generates a multiple structural superimposition providing a consolidated spatial framework for comparing residues and finally emits the MSA. Residues that are aligned differently by including or excluding electrostatic properties can be targeted by directed evolution experiments to transform the enzymatic properties of one protein into another. We have compared STEEP results to those obtained from a MSA program (ClustalW) and a structural alignment method (MUSTANG) for chymotrypsin serine proteases. Subsequently, we used PhyML to generate phylogenetic trees for the serine and metallo-β-lactamase superfamilies from the STEEP generated MSA, and corroborated the accepted relationships in these superfamilies. We have observed that STEEP acts as a functional classifier when electrostatic congruence is used as a discriminator, and thus identifies potential targets for directed evolution experiments. In summary, STEEP is unique among phylogenetic methods for its ability to use electrostatic congruence to specify mutations that might be the source of the functional divergence in a protein family. Based on our results, we also hypothesize that the active site and its close vicinity contains enough information to infer the correct phylogeny for related proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Single-Molecule Electron Transport in Peptoids

Peptoids are structural analogs of peptides in which side chains are appended to the backbone nitrogen rather than the α-carbon. The sequence-defined modularity of peptoids enables precise control over structure−function relationships, enabling applications in energy storage and biomedical materials. Despite recent progress, the role of sequence and conformation on electron transport in peptoid molecules is not fully understood. Here, we synthesize a library of peptoid oligomers and characterize their molecular electronic properties using the scanning tunneling microscope-break junction (STM-BJ) technique. Our results show well-defined electron transport behavior for peptoid sequences containing aromatic side groups lacking hydrogen bonds (H-bonds) and without chemical substitutions at the N−C α position. This behavior fundamentally differs from electron transport in peptides, where H-bond interactions give rise to higher conductance states. All-atom molecular dynamics (MD) simulations are used to understand the conformational heterogeneity of peptoids, and molecular conformations obtained from MD simulations are used in quantum mechanical calculations based on the nonequilibrium Green’s function−density functional theory (NEGF-DFT) formalism. In all cases, computational results are in reasonable qualitative agreement with experiments. Our work demonstrates that the conductance behavior of peptoids depends on monomer identity, including side-chain aromaticity and substitution at the N−C α position. Overall, this work provides new insights into the structure−function relationships governing electron transport in peptoid-based materials and establishes design rules for peptoid-based molecular junctions.

Charge transport↗
DOE OSTI2022

Compact Peptoid Molecular Brushes for Nanoparticle Stabilization

Controlling the interfaces and interactions of colloidal nanoparticles (NPs) via tethered molecular moieties is crucial for NP applications in engineered nanomaterials, optics, catalysis, and nanomedicine. Despite a broad range of molecular types explored, there is a need for a flexible approach to rationally vary the chemistry and structure of these interfacial molecules for controlling NP stability in diverse environments, while maintaining a small size of the NP molecular shell. Here, we demonstrate that low-molecular-weight, bifunctional comb-shaped, and sequence-defined peptoids can effectively stabilize gold NPs (AuNPs). The generality of this robust functionalization strategy was also demonstrated by coating of silver, platinum, and iron oxide NPs with designed peptoids. Each peptoid (PE) is designed with varied arrangements of a multivalent AuNP-binding domain and a solvation domain consisting of oligo-ethylene glycol (EG) branches. Among designs, a peptoid (PE5) with a diblock structure is demonstrated to provide a superior nanocolloidal stability in diverse aqueous solutions while forming a compact shell (similar to 1.5 nm) on the AuNP surface. We demonstrate by experiments and molecular dynamics simulations that PE5-coated AuNPs (PE5/AuNPs) are stable in select organic solvents owing to the strong PE5 (amine)-Au binding and solubility of the oligo-EG motifs. At the vapor-aqueous interface, we show that PE5/AuNPs remain stable and can self-assemble into ordered 2D lattices. The NP films exhibit strong near-field plasmonic coupling when transferred to solid substrates.

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

Exploring Water System Vulnerabilities in California's Central Valley Under the Late Renaissance Megadrought and Climate Change

Abstract California faces cycles of drought and flooding that are projected to intensify, but these extremes may impact water users across the state differently due to the region's natural hydroclimate variability and complex institutional framework governing water deliveries. To assess these risks, this study introduces a novel exploratory modeling framework informed by paleo and climate‐change based scenarios to better understand how impacts propagate through the Central Valley's complex water system. A stochastic weather generator, conditioned on tree‐ring data, produces a large ensemble of daily weather sequences conditioned on drought and flood conditions under the Late Renaissance Megadrought period (1550–1580 CE). Regional climate changes are applied to this weather data and drive hydrologic projections for the Sacramento, San Joaquin, and Tulare Basins. The resulting streamflow ensembles are used in an exploratory stress test using the California Food‐Energy‐Water System model, a highly resolved, daily model of water storage and conveyance throughout California's Central Valley. Results show that megadrought conditions lead to unprecedented reductions in inflows and storage at major California reservoirs. Both junior and senior water rights holders experience multi‐year periods of curtailed water deliveries and complete drawdowns of groundwater assets. When megadrought dynamics are combined with climate change, risks for unprecedented depletion of reservoir storage and sustained curtailment of water deliveries across multiple years increase. Asymmetries in risk emerge depending on water source, rights, and access to groundwater banks.

Gupta, Rohini S. [School of Civil and Environmenta↗