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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Novel Machine Learning Workflow to Classify Mobile Home Parks at Scale

Understanding the built environment is essential to the overall study of population dynamics, grid infrastructure, emergency response, among others. In the United States there are multiple classifications for buildings within the built environment such as residential, signifying family homes while commercial buildings consist of apartments or larger structures which are multi-purpose. While there is a high level of understanding of where these aforementioned structures are located, there is a third class of structures, mobile home parks (MHP) which have been under-represented in the literature despite there being an estimated 2.7 million of them within the United States. Research has shown that individuals who reside in MHP are at higher risk to extreme events due to their location and structural integrity of residence. Attention must now turn to identifying MHP at scale to help first responders and policy makers understand where these at risk populations reside. To address for this gap, we develop a novel methodology to infer MHP at scale based off morphologies derived at a building level. Here, we show that across 3 million buildings in 6 states within the United States it is possible to identify MHP with 83% accuracy. This novel approach to identify MHP from other structures within the built environment using a machine learning approach provides a new tool to leverage in relation to helping at-risk populations.

Stipek, Clinton [Oak Ridge National Laboratory (OR↗
DOE OSTI2022

Mirror nucleon removal reactions in p-shell nuclei

Nucleon removal reactions have been shown to be an effective tool for studying the single particle structure of nuclei. This work continues efforts to experimentally probe and benchmark the reaction and structure models used to calculate the removal reaction cross sections when using microscopic nuclear structure inputs. Here, three different single nucleon removal reactions were performed, from p -shell nuclei with masses A = 7, 9, and 10. The residual nuclei from the reactions were detected in coincidence with γ rays to determine partial cross sections to individual final states. The eikonal direct-reaction model is combined with overlap functions and residual nucleus densities from microscopic, variational Monte Carlo calculations to provide consistent nuclear structure input to the partial cross section calculations. Comparisons of measured and calculated cross sections, including for mirror reactions, are presented. The analysis of the partial cross sections leading to the ground states shows a similar behavior to the one observed from analyses of inclusive cross sections using shell model nuclear structure input: the theoretical description of the removal process is in better agreement with the data when removing weakly bound nucleons, than when removing well-bound ones. The two mirror reaction pairs presented here show consistent results between the respective members of the pairs. The results obtained for the population of the excited states, however, show a systematically different trend that appears connected to the structure part of the calculation. Additional cases are needed to better understand the respective roles of structure and dynamical effects in the deviations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

The SAGA Survey. VI. The Size–Mass Relation for Low-mass Galaxies Across Environments

We investigate how Milky Way (MW)–like environments influence the sizes and structural properties of low mass galaxies by comparing satellites of MW analogs from the Satellites Around Galactic Analogs (SAGA) Survey with two control samples: an environmentally agnostic population from the SAGA background sample and isolated galaxies from the Sloan Digital Sky Survey NASA-Sloan Atlas. All sizes and structural parameters are measured uniformly using pysersic to ensure consistency across samples. We find the half-light sizes of SAGA satellites are systematically larger than those of isolated galaxies, with the magnitude of the offset ranging from 0.05 to 0.12 dex (10%–24%) depending on the comparison sample and completeness cuts. This corresponds to physical size differences between 85 and 200 pc at log 10 (M$_{{\star}}$/M ⊙ ) = 7.5 and 220–960 pc at log 10 (M$_{{\star}}$/M ⊙ ) = 10. This offset persists among star-forming galaxies, suggesting that environment can influence the structure of low-mass galaxies even before it impacts quenching. The intrinsic scatter in the size–mass relation is lower for SAGA satellites than isolated galaxies, and the Sérsic index distributions of satellites and isolated galaxies are similar. In comparison to star-forming satellites, quenched SAGA satellites have a slightly shallower size–mass relation and rounder morphologies at low mass, suggesting that quenching is accompanied by structural transformation and that the processes responsible differ between low- and high-mass satellites. Our results show that environmental processes can imprint measurable structural differences on satellites in MW-mass halos.

Asali, Yasmeen [Yale Univ., New Haven, CT (United ↗
DOE OSTI2024

Neural architecture search via similarity adaptive guidance

Evolutionary neural network architecture search (ENAS) has attracted the attention of many experts due to its global optimization capabilities to automatically search for convolutional neural network architectures based on the target task. The current search space for ENAS is not to design a fully structured network, but to search for smaller cell architectures to reduce search costs. However, blind search strategies do not effectively utilize the potential experience of the population. In order to utilize the potential experience learned by the current population to guide the evolutionary search of the population, we propose a similarity guided neural network architecture search algorithm based on cell architecture, which utilizes the similarity between pairwise architectures in the population as empirical knowledge learned by the population. Our proposed algorithm provides a novel method for calculating architecture similarity, which calculates architecture similarity separately from the cell and macro-structure. Then we decouple the connections and operations in the cell and calculate connection and operation similarity separately. In addition, we propose adaptive similarity selection and binary tournament selection strategies to enhance the algorithm’s global and local search capabilities and effectively explore the search space. Finally, we design an improved single-point crossover operator to enhance the local search ability of the evolutionary operator. The experimental results show that SAGNAS is a competitive algorithm that achieves 97.44% and 81.60% in CIFAR10 and CIFAR100 with only 1.9 GPU-days spent.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Effect of grafting density on the two-dimensional assembly of nanoparticles

Employing grazing-incidence small-angle X-ray scattering (GISAXS) and X-ray reflectivity (XRR), we demonstrate that films composed of polyethylene glycol (PEG)-grafted silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs), as well as their binary mixtures, form highly stable hexagonal structures at the vapor–liquid interface. These nanoparticles exhibit remarkable stability under varying environmental conditions, including changes in pH, mixing concentration, and PEG chain length. Short-chain PEG grafting produces dense, well-ordered films, while longer chains produce more complex, less dense quasi-bilayer structures. AuNPs exhibit higher grafting densities than AgNPs, leading to more ordered in-plane arrangements. In binary mixtures, AuNPs dominate the population at the surface, while AgNPs integrate into the system, expanding the lattice without forming a distinct binary superstructure. In conclusion, these results offer valuable insights into the structural behavior of PEG-grafted nanoparticles and provide a foundation for optimizing binary nanoparticle assemblies for advanced nanotechnology applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The impact of long-range dispersal on gene surfing

Range expansions lead to distinctive patterns of genetic variation in populations, even in the absence of selection. These patterns and their genetic consequences have been well studied for populations advancing through successive short-ranged migration events. However, most populations harbor some degree of long-range dispersal, experiencing rare yet consequential migration events over arbitrarily long distances. Although dispersal is known to strongly affect spatial genetic structure during range expansions, the resulting patterns and their impact on neutral diversity remain poorly understood. Here, we systematically study the consequences of long-range dispersal on patterns of neutral variation during range expansion in a class of dispersal models which spans the extremes of local (effectively short-ranged) and global (effectively well-mixed) migration. We find that sufficiently long-ranged dispersal leaves behind a mosaic of monoallelic patches, whose number and size are highly sensitive to the distribution of dispersal distances. We develop a coarse-grained model which connects statistical features of these spatial patterns to the evolution of neutral diversity during the range expansion. We show that growth mechanisms that appear qualitatively similar can engender vastly different outcomes for diversity: Depending on the tail of the dispersal distance distribution, diversity can be either preserved (i.e., many variants survive) or lost (i.e., one variant dominates) at long times. Our results highlight the impact of spatial and migratory structure on genetic variation during processes as varied as range expansions, species invasions, epidemics, and the spread of beneficial mutations in established populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure

Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as sensor selection. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The Role of Cation Coordination in the Electrical and Optical Properties of Amorphous Transparent Conducting Oxides

Amorphous oxide semiconductor materials have demonstrated numerous advantages without compromise of electrical properties as compared to their crystalline counterparts, yet understanding of the fundamental principles allowing this has remained elusive. To study the origins of enhanced optoelectronic properties, we apply high-throughput, combinatorial sputtering, structural and spectral mapping, and computationally intensive ab initio molecular dynamics simulations with density functional theory to a ternary, post-transition metal oxide system, namely, zinc tin oxide. The deposited thin films exhibit a high figure of merit, achieving carrier densities in the range of 1019 to 1020 cm–3 and carrier mobilities up to 35 cm2/Vs. These results highlight the role of local distortions and cation coordination in determining the microscopic origins of carrier generation and transport. In particular, we identify the strong likelihood of Sn undercoordination in both Zn-poor and Zn-rich phases leading to the high carrier concentrations observed. This not only diverges from the still widespread historical indictment of oxygen vacancies controlling carrier population in crystalline oxides but also provides a comprehensive framework to describe the unique structure–property relationships using specific structural and electronic descriptors in disordered phase materials.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,M↗
DOE OSTI2022

How Cooperatively Folding Are Homopolymer Molecular Knots?

Detailed thermodynamic analysis of complex systems with multiple stable configurational states allows for insight into the cooperativity of each individual transition. In this work, we derive a heat capacity decomposition comprising contributions from each individual configurational state, which together sum to a baseline heat capacity, and contributions from each state-to-state transition. We apply this analysis framework to a series of replica exchange molecular dynamics simulations of linear and 1-1 coarse-grained homo-oligomer models, which fold into stable, configurationally well-defined molecular knots, in order to better understand the parameters leading to stable and cooperative folding of these knots. We find that a stiff harmonic backbone bending angle potential is key to achieving knots with specific 3D structures. Tuning the backbone equilibrium angle in small increments yields a variety of knot topologies. Populations of different knotted states as a function of temperature can also be manipulated by tuning the backbone torsion stiffness or by adding side-chain beads. We find that sharp total heat capacity peaks for the homo-oligomer knots are largely due to a coil-to-globule transition rather than a cooperative knotting step. Furthermore, in some cases, the cooperativity of globule-to-knot and coil-to-globule transitions is comparable, suggesting that highly cooperative folding to knotted structures can be achieved by refining the model parameters or adding sequence specificity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Evidence for Environmental Stripping in the Coma Cluster

The stability and longevity of globular clusters (GCs) make them effective tracers of the dynamical histories of galaxies in cluster environments. We construct a catalog of 23,351 GC candidates in the Coma Cluster using imaging from the Hubble Space Telescope Advanced Camera for Surveys. We cross-match galaxy data from the SIMBAD, NASA/IPAC Extragalactic Database, and Sloan Digital Sky Survey archives to construct a galaxy sample and model their GC populations using the GC specific frequency. We find several galaxies with significantly smaller GC populations than expected from their luminosities, consistent with either tidal stripping or intrinsically low formation efficiencies. We analyze annular and Voronoi GC radial profiles of the two brightest cluster galaxies (BCGs), NGC 4874 and NGC 4889, as well as other Coma galaxies. A two-dimensional Voronoi density mapping reveals GC populations with marked deficits compared to our modeled expectations, including galaxies in proximity to the BCGs (e.g., IC 3998, NGC 4875, and NGC 4876) and others distributed across Coma (e.g., NGC 4908, NGC 4883, and IC 4042). Azimuthal symmetry testing suggests past dynamical interactions may have truncated GC systems in some galaxies, while intrinsic deficits are probable in others (e.g., IC 3973, IC 3976, IC 4040, and IC 4045). Our results show that GC deficits exist in several Coma galaxies and that the two-dimensional density structure reveals environmental signatures, with asymmetry statistics consistent with directional stripping. These findings highlight GC populations as powerful probes of environmental processing and the dynamical histories of galaxies in dense cluster environments.

Pomeroy, Richard T. [University of Texas Rio Grand↗
DOE OSTI2023

Dispersal, habitat filtering, and eco-evolutionary dynamics as drivers of local and global wetland viral biogeography

Abstract Wetlands store 20–30% of the world’s soil carbon, and identifying the microbial controls on these carbon reserves is essential to predicting feedbacks to climate change. Although viral infections likely play important roles in wetland ecosystem dynamics, we lack a basic understanding of wetland viral ecology. Here 63 viral size-fraction metagenomes (viromes) and paired total metagenomes were generated from three time points in 2021 at seven fresh- and saltwater wetlands in the California Bodega Marine Reserve. We recovered 12,826 viral population genomic sequences (vOTUs), only 4.4% of which were detected at the same field site two years prior, indicating a small degree of population stability or recurrence. Viral communities differed most significantly among the seven wetland sites and were also structured by habitat (plant community composition and salinity). Read mapping to a new version of our reference database, PIGEONv2.0 (515,763 vOTUs), revealed 196 vOTUs present over large geographic distances, often reflecting shared habitat characteristics. Wetland vOTU microdiversity was significantly lower locally than globally and lower within than between time points, indicating greater divergence with increasing spatiotemporal distance. Viruses tended to have broad predicted host ranges via CRISPR spacer linkages to metagenome-assembled genomes, and increased SNP frequencies in CRISPR-targeted major tail protein genes suggest potential viral eco-evolutionary dynamics in response to both immune targeting and changes in host cell receptors involved in viral attachment. Together, these results highlight the importance of dispersal, environmental selection, and eco-evolutionary dynamics as drivers of local and global wetland viral biogeography.

Environmental Sciences & Ecology↗
DOE OSTI2024

Generalizable, tunable control of divalent cation solvation structure via mixed anion contact ion pair formation

Multivalent batteries are a promising new technology for energy storage, but they face challenges to developing suitable electrolytes that can support reversible deposition/dissolution at the metal anode and enable compatibility with high voltage oxide cathode materials. Here, in this work, we investigate the solvation behavior of Zn 2+ , Mg 2+ , Ca 2+ and Cu 2+ in mixed anion electrolytes containing TFSI - and Cl - . Raman and nuclear magnetic resonance spectroscopies are utilized to probe the bulk solvation structure of these electrolytes and demonstrate that mixed anion contact ion pairs (CIPs) are formed in all four systems, indicating this behavior is likely general to divalent cations. Furthermore, the relative population of mixed anion CIPs can be tuned by controlling the relative ratio of TFSI : Cl, with significant CIP populations observed even at low relative fractions of Cl - . These findings imply that modifying the anion chemistry can easily adjust the solvation structure of bulk cations, which has important implications for the development of next-generation electrolytes. By understanding the factors that influence the formation of mixed anion CIPs, we can design systems that promote the formation of electrochemically-active solvation structures that can enable multivalent batteries with improved performance and lifetimes.

25 ENERGY STORAGE↗
DOE OSTI2022

Characterization of the molecular mechanisms of silicon uptake in coccolithophores

Coccolithophores are an important group of calcifying marine phytoplankton. Although coccolithophores are not silicified, some species exhibit a requirement for Si in the calcification process. These species also possess a novel protein (SITL) that resembles the SIT family of Si transporters found in diatoms. However, the nature of Si transport in coccolithophores is not yet known, making it difficult to determine the wider role of Si in coccolithophore biology. Here, we show that coccolithophore SITLs act as Na + -coupled Si transporters when expressed in heterologous systems and exhibit similar characteristics to diatom SITs. We find that CbSITL from Coccolithus braarudii is transcriptionally regulated by Si availability and is expressed in environmental coccolithophore populations. However, the Si requirement of C. braarudii and other coccolithophores is very low, with transport rates of exogenous Si below the level of detection in sensitive assays of Si transport. As coccoliths contain only low levels of Si, we propose that Si acts to support the calcification process, rather than forming a structural component of the coccolith itself. Si is therefore acting as a micronutrient in coccolithophores and natural populations are only likely to experience Si limitation in circumstances where dissolved silicon (DSi) is depleted to extreme levels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Chemical bonding, phase stability and magnetic property in Sm 2 Fe 17 X 3 (X=H, C, N): A first-principles perspective

As a promising alternative to Nd–Fe–B magnets, the critical rare earth free Sm 2 Fe 17 X 3 (X = C, N) exhibits potential for high-performance magnets. However, their poor phase stability remains a major obstacle to developing bulk magnets. We investigated the phase stability and intrinsic magnetic properties of Sm 2 Fe 17 X 3 (X = H, C, N) using first-principles calculations and chemical bond analysis. The formation energies are negative, while the decomposition energies are −1.53, 0.348, and −0.74 eV per formula unit for X = H, C, and N, respectively, which is responsible for the weak thermal stability. Our chemical bond analysis reveals that the bonding asymmetry between Sm–X and Fe–X interactions creates local structural distortions and degrades the phase stability of Sm 2 Fe 17 X 3 . The project Crystal Orbital Hamilton Population (-pCOHP) analysis indicates that the Sm–X bonding remains positive up to the Fermi level, indicating stable bonding interactions. Here, in contrast, the Fe–X bonding becomes negative near the Fermi level, signifying anti-bonding contributions that reduce structural stability. Interstitial atoms X expand the lattice and enhance Fe magnetic moments, but Fe–X bonding suppresses neighboring Fe moments. Electron transfer from Sm to X modifies the valence state of Sm and the crystal field at the site, contributing to enhanced magnetocrystalline anisotropy in Sm 2 Fe 17 X 3 . Among the interstitial elements, carbon and nitrogen—with their larger atomic radius and higher electronegativity—induce greater lattice expansion and form stronger bonds with neighboring Sm and Fe atoms compared to hydrogen. Consequently, Sm 2 Fe 17 X 3 (X = C and N) exhibits better phase stability and significant improvement in magnetic properties.

Chemical bonding↗
DOE OSTI2025

The structure of high-Mg alkali-bearing aluminosilicate glasses investigated in situ at ambient and high pressure by multi-angle energy dispersive X-ray diffraction and infrared microspectroscopy

The structural properties of synthetic high-Mg alkali-bearing aluminosilicate glasses analogues of natural picritic-to-komatiitic magmas were investigated in situ by multiangle energy dispersive X-ray diffraction at 2.1 GPa and ambient pressure and by Fourier Transform infrared spectroscopy up to 5.4 GPa in a cycle of compression and decompression experiments. Our results show that the intermediate range ordering of the glass structure at 2.1 GPa is 3.14 Å, increasing to 3.19 Å when decompressed. The local structure shows T-O lengths of 1.66 Å (2.1 GPa) and 1.65 Å (ambient pressure), T-T distances of 3.19 Å at high pressure, which lengthen to 3.21 Å at ambient pressure, causing the T-O-T angle of 147° determined at 2.1 GPa to widen to 154° upon decompression. The deconvoluted infrared spectra result in the presence of Q 1 , Q 2 , Q 3 populations in the aluminosilicate spectral region, whose proportions remain relatively unchanged up to 5.4 GPa. The structural response of the investigated glasses to cold-compression does not involve changes in polymerization, but rather a shrinking and compaction of the structure as evidenced by the Qn species shifting to higher wavenumbers as a function of pressure. The structural properties determined from X-ray diffraction for this glass composition are discussed together with those of glasses emerging from previous studies to highlight a compositional dependence mainly dictated by the amount of SiO 2 and Al 2 O 3 .

glass structure↗
DOE OSTI2020

How cholesterol stiffens unsaturated lipid membranes

Cholesterol is an integral component of eukaryotic cell membranes and a key molecule in controlling membrane fluidity, organization, and other physicochemical parameters. It also plays a regulatory function in antibiotic drug resistance and the immune response of cells against viruses, by stabilizing the membrane against structural damage. While it is well understood that, structurally, cholesterol exhibits a densification effect on fluid lipid membranes, its effects on membrane bending rigidity are assumed to be nonuniversal; i.e., cholesterol stiffens saturated lipid membranes, but has no stiffening effect on membranes populated by unsaturated lipids, such as 1,2-dioleoyl- sn -glycero-3-phosphocholine (DOPC). This observation presents a clear challenge to structure–property relationships and to our understanding of cholesterol-mediated biological functions. Here, using a comprehensive approach—combining neutron spin-echo (NSE) spectroscopy, solid-state deuterium NMR ( 2 H NMR) spectroscopy, and molecular dynamics (MD) simulations—we report that cholesterol locally increases the bending rigidity of DOPC membranes, similar to saturated membranes, by increasing the bilayer’s packing density. All three techniques, inherently sensitive to mesoscale bending fluctuations, show up to a threefold increase in effective bending rigidity with increasing cholesterol content approaching a mole fraction of 50%. Our observations are in good agreement with the known effects of cholesterol on the area-compressibility modulus and membrane structure, reaffirming membrane structure–property relationships. The current findings point to a scale-dependent manifestation of membrane properties, highlighting the need to reassess cholesterol’s role in controlling membrane bending rigidity over mesoscopic length and time scales of important biological functions, such as viral budding and lipid–protein interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Long-term socioeconomic trends and climate variability as drivers of virtual water scarcity in China

Water scarcity can have far-reaching sectoral impacts beyond its physical location through the propagation of virtual water flows. Socioeconomic and hydroclimatic changes affect local and virtual water scarcity by altering availability and demand. Yet most studies of this phenomenon focus on volumetric footprints, and the few on water scarcity risk have not examined hydroclimatic variability beyond long-term trends. In this study, we ask how gross domestic product (GDP) and population changes, long-term meteorological trends, sea surface temperature (SST) patterns, and interannual meteorological variability affect water scarcity in China, both locally (through the local water scarcity risk index, LWSR) and remotely (through the virtual water scarcity risk index, VWSR). Counterfactual scenarios were compared in a regression-and-simulation framework, with the socioeconomic and meteorological drivers varying over 1923–2019 and the multi-regional input–output structure staying fixed at 2017. Relative to a 5 year baseline centered on 2017, GDP and population changes have induced a cumulative 17%–50% increase in LWSR and 13%–21% increase in VWSR, outweighing the effect of long-term meteorological trends. phase change in one of two examined SST patterns induce 4%–13% differences in LWSR and 1%–4% differences in VWSR. Interannual meteorological variability induces 10%–20% standard deviations in LWSR and 3%–7% in VWSR. The findings highlight the importance of using longer time series to accurately assess local and virtual water scarcity situations. Water scarcity management should prioritize socioeconomic factors when planning at century-long timescales and prioritize hydroclimatic factors at multidecadal or shorter timescales. water managers should consider interannual variabilities in LWSR and VWSR and plan for potential occurrences of extreme conditions.

climate variability↗
DOE OSTI2022

Effects of ion adsorption on graphene oxide films and interfacial water structure: A molecular-scale description

Herein we discuss graphene oxide as a promising, emerging separation material, as it is durable, dispersible in water, and has naturally forming functional groups. Bulk studies using graphene oxide flakes have demonstrated impressive metal adsorption. However, little interfacial information about water and metal organization near graphene oxide is available. A mechanistic understanding of water and ions interactions with graphene oxide films is critical toward advanced separations, including improved sorption efficiency and membrane regeneration. We study metal ion and local water organization near graphene oxide thin films formed at the air/water interface. These films are not typical membranes and allow us to determine nanoscale information about the graphene oxide-water interface. We accomplish this with x-ray reflectivity (XR), x-ray fluorescence near total reflection (XFNTR), and vibrational sum frequency generation spectroscopy (SFG). These interface-specific techniques provide the electron density profile normal to the interface, number of adsorbed ions, and information about the orientational ordering and hydrogen-bonding network of interfacial water, respectively. Via XFNTR and SFG, we find that trivalent yttrium ions preferentially adsorb to graphene oxide and affect its structure, compared to divalent strontium and monovalent cesium ions. Two different interfacial water populations can be described, based on their hydrogen bonding strength, and the adsorbed ions affect these populations differently. These results provide fundamental information about ion and water organization at the interface and help address the large computational-experimental agreement gap for graphene oxide systems. Additionally, they are relevant for improved soft-scaffold graphene oxide membranes and downstream applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗