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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Connect microstructure evolution to property degradation with validated simulation

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500$^o$C to 1500$^o$C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 $\frac{D}{m^2s}$. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Cation-Driven Assembly of Bilayered Vanadium Oxide and Graphene Oxide Nanoflakes to Form Two-Dimensional Heterostructure Electrodes for Li-Ion Batteries

Lithium preintercalated bilayered vanadium oxide (LVO or δ-Li x V 2 O 5 ·nH 2 O) and graphene oxide (GO) nanoflakes were assembled using a concentrated lithium chloride solution and annealed under vacuum at 200 °C to form two-dimensional (2D) δ-Li x V 2 O 5 ·nH 2 O and reduced GO (rGO) heterostructures. Here we found that the Li + ions from LiCl enhanced the oxide/carbon heterointerface formation and served as stabilizing ions to improve structural and electrochemical stability. The graphitic content of the heterostructure could be easily controlled by changing the initial GO concentration prior to assembly. We found that increasing the GO content in our heterostructure composition helped inhibit the electrochemical degradation of LVO during cycling and improved the rate capability of the heterostructure. A combination of scanning electron microscopy and X-ray diffraction was used to help confirm that a 2D heterointerface formed between LVO and GO, and the final phase composition was determined using energy-dispersive X-ray spectroscopy and thermogravimetric analysis. Scanning transmission electron microscopy and electron energy-loss spectroscopy were additionally used to examine the heterostructures at high resolution, mapping the orientations of rGO and LVO layers and locally imaging their interlayer spacings. Further, electrochemical cycling of the cation-assembled LVO/rGO heterostructures in Li-ion cells with a non-aqueous electrolyte revealed that increasing the rGO content led to improved cycling stability and rate performance, despite slightly decreased charge storage capacity. The heterostructures with 0, 10, 20, and 35 wt % rGO exhibited capacities of 237, 216, 174, and 150 mAh g –1 , respectively. Moreover, the LVO/rGO-35 wt % and LVO/rGO-20 wt % heterostructures retained 75% (110 mAh g–1) and 67% (120 mAh g –1 ) of their initial capacities after increasing the specific current from 20 to 200 mA g –1 , while the LVO/rGO-10 wt % sample retained only 48% (107 mAh g –1 ) of its initial capacity under the same cycling conditions. In addition, the cation-assembled LVO/rGO electrodes exhibited enhanced electrochemical stability compared to electrodes prepared through physical mixing of LVO and GO nanoflakes in the same ratios as the heterostructure electrodes, further revealing the stabilizing effect of a 2D heterointerface. The cation-driven assembly approach, explored in this work using Li + cations, was found to induce and stabilize the formation of stacked 2D layers of rGO and exfoliated LVO. The reported assembly methodology can be applied for a variety of systems utilizing 2D materials with complementary properties for applications as electrodes in energy storage devices.

25 ENERGY STORAGE↗
DOE OSTI2025

Influence of counterion substitution on the properties of imidazolium-based ionic liquid clusters

Due to their unique physiochemical properties that may be tailored for specific purposes, ionic liquids (ILs) have been investigated for various applications, including chemical separations, catalysis, energy storage, and space propulsion. The different cations and anions comprising ILs may be selected to optimize a range of desired properties, such as thermal stability, ionic conductivity, and volatility, leading to the designation of certain ILs as designer “green” solvents. The effect of counterions on the properties of ILs is of both fundamental scientific interest and technological importance. Herein, we report a systematic experimental and theoretical investigation of the size, charge, stability toward dissociation, and geometric/electronic structure of 1-ethyl-3-methyl imidazolium (EMIM)-based IL clusters containing two different atomic counterions (i.e., bromide [Br − ] and iodide [I − ]). This work extends our studies of EMIM + cations with atomic chloride (Cl − ) and molecular tetrafluoroborate (BF 4 − ) anions reported previously by Baxter et al. [Chem. Mater. 34, 2612 (2022)] and Zhang et al . [J. Phys. Chem. Lett. 11, 6844 (2020)], respectively. Distributions of anionic IL clusters were generated in the gas phase using electrospray ionization and characterized by high mass resolution mass spectrometry, energy-resolved collision-induced dissociation, and negative ion photoelectron spectroscopy experiments. The experimental results reveal anion-dependent trends in the size distribution, relative abundance, ionic charge state, stability toward dissociation, and electron binding energies of the IL clusters. Complementary global optimization theory provides molecular-level insights into the bonding and electronic structure of a selected subset of clusters, including their low energy structures and electrostatic potential maps, and how these fundamental characteristics are influenced by anion substitution. Collectively, our findings demonstrate how the fundamental properties of ILs, which determine their suitability for many applications, may be tuned by substituting counterions. These observations are critical in the sub-nanometer cluster size regime where phenomena do not scale predictably to the bulk phase, and each atom counts toward determining behavior.

cluster↗
DOE OSTI2021

Active motion of multiphase oil droplets: emergent dynamics of squirmers with evolving internal structure

Synthetic soft matter systems, when driven beyond equilibrium by active processes, offer the potential to achieve dynamical states and functions of a complexity found in living matter. Emulsions offer the basis of a simple yet versatile system for identification of the physicochemical principles underlying active soft matter, but how multiple internal phases within emulsion droplets (e.g., Janus morphologies) organize to impact emergent dynamics is not understood. Here, we create multiphase oil droplets with ultralow interfacial tensions but distinct viscosities, and drive them into motion in aqueous micellar solutions. Preferential solubilization of select components of the oil both drives the droplet motion and yields a progression of internal phase morphological states with distinct symmetries. In this work, we find the active droplets to exhibit five dynamical states during morphogenesis. By quantifying microscopic flow fields, we show that it is possible to map the diverse droplet behaviors to squirmer models of spherical microswimmers in Stokes flow, thus showing that multiphase droplets offer the basis of a versatile platform with which to study and engineer the hydrodynamics of microswimmers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ensuring thermodynamic consistency with invertible coarse-graining

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.

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

An Experimental Comparison of Cyclic Variations in Diesel–Natural Gas and POMDME–Natural Gas Dual Fuel Combustion

Abstract Cyclic variations in internal combustion engines are caused by various factors, including combustion mixture stratification, in-cylinder flows, local fluctuations in air-fuel ratio, etc. Cyclic variations have a profound impact on engine performance and emissions. In this study, cyclic variations in dual fuel combustion are analyzed, comparing diesel–natural gas (NG) and polyoxymethylene dimethyl ether (POMDME)-NG dual fuel combustion. Cyclic variability was initially quantified using the coefficient of variation of gross indicated mean effective pressure (IMEPg) computed from experimental cylinder pressure data. The cases analyzed in this study had a coefficient of variation (COV) of IMEPg greater than or around 5%, which was the lower limit of onset of instability for this engine. Experiments were performed at two fixed start of injection (SOI) of high-cetane fuel: 310 CAD and 350 CAD. For all experiments, a constant load of 5 bar IMEPg was maintained, and the intake boost pressure and rail pressure were fixed at 1.5 bar and 500 bar, respectively. For each case, 1000 cycles of cylinder pressure data were recorded, filtered, and processed using an in-house heat release analysis code for each cycle. A comparison between individual cycles and the “ensemble averaged cycle” was made for both diesel–NG and POMDME–NG combustion. For the early SOI of 310 CAD, the peak cylinder pressure fluctuations of individual cycle were found to be ± 15 bar for both fuel combinations, compared to the ensemble averaged cycle, and < 1/10th of the cycles had an IMEPg lower than 0.05 bar of the ensemble averaged cycle. However, the peak pressure fluctuations were found to be lower for POMDME–NG (±3 bar) than diesel–NG dual fuel combustion at 350 CAD SOI, indicating lower cyclic variations. The higher reactivity of POMDME helped reduce fluctuations in combustion phasing at the retarded SOI. The presence of cycles of deterioration and cycles of recovery were also observed with diesel–NG combustion for 310 CAD SOI, and the scatter in the IMEPg return map was similar for both fuel combinations. The IMEPg return map for POMDME–NG combustion was less scattered at the 350 CAD SOI.

Engineering↗
DOE OSTI2025

Interface instabilities in hafnium hydride entrained iron metal matrix composites

The chemical interactions in Fe–HfH 2 metal matrix composites (MMCs) are studied across multiple length scales to elucidate the decomposition of the parent phases and corresponding reaction zone physics during direct current sintering. Fe–HfH 2 composites were synthesized with increasing as-mixed hydride contents of Fe–25% HfH 2 , Fe–40% HfH 2 , Fe–55% HfH 2 , and Fe–70% HfH 2 (all in vol. %) to demonstrate the ability to achieve sintered MMCs with target hydride contents. Samples were probed across multiple length scales through a multi-modal workflow employing x-ray diffraction, scanning electron microscopy and segmentation analysis, and synchrotron techniques including hard x-ray fluorescence mapping and nanoprobe x-ray absorption near-edge structure measurements. Under the selected sintering temperature and pressure conditions, hydrogen evolution is seen to evolve through parallel paths: thermal decomposition from during the transformation of HfH 2 to HfH x<2 and through subsequent reaction with the Fe matrix leading to intermetallic phase formation. Specifically, HfFe and HfFe 2 intermetallic formation accelerates the release of hydrogen with a subsequent HfO 2 phase forming at grain boundaries. For this MMC, the consumption or loss of hydrogen can be considerable in compacts with initial hydride loading of 25%–40% HfH 2 approaching 83% hydrogen loss for the lower volume fraction composites. Increasing the volume fraction of HfH 2 to 70% enhanced the retained hydrogen content to 53% and attributed to the reduced interfacial area intrinsic to the increased HfH 2 loading in this MMC.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mapping Influenza-Induced Posttranslational Modifications on Histones from CD8+ T Cells

T cell function is determined by transcriptional networks that are regulated by epigenetic programming via posttranslational modifications (PTMs) to histone proteins and DNA. Bottom-up mass spectrometry (MS) can identify histone PTMs, whereas intact protein analysis by MS can detect species missed by bottom-up approaches. We used a novel approach of online two-dimensional liquid chromatography-tandem MS with high-resolution reversed-phase liquid chromatography (RPLC), alternating electron transfer dissociation (ETD) and collision-induced dissociation (CID) on precursor ions to maximize fragmentation of uniquely modified species. The first online RPLC separation sorted histone families, then RPLC or weak cation exchange hydrophilic interaction liquid chromatography (WCX-HILIC) separated species heavily clad in PTMs. Tentative identifications were assigned by matching proteoform masses to predicted theoretical masses that were verified with tandem MS. We used this innovative approach for histone-intact protein PTM mapping (HiPTMap) to identify and quantify proteoforms purified from CD8 T cells after in vivo influenza infection. Activation significantly altered PTMs following influenza infection, histone maps changed as T cells migrated to the site of infection, and T cells responding to secondary infections had significantly more transcription enhancing modifications. Thus, HiPTMap identified and quantified proteoforms and determined changes in CD8 T cell histone PTMs over the course of infection.

mass spectrometry↗
DOE OSTI2025

Sulfur Species in Zinc-Rich Condylar Zones of a Rat Temporomandibular Joint

We performed synchrotron-based micro-X-ray absorption near-edge spectroscopy (µ-XANES) coupled with micro-X-ray fluorescence (µ-XRF) for the identification of elements that included biometal zinc (Zn) and nonmetal sulfur (S) (and its species) in the condylar zones of a rat temporomandibular joint (TMJ). Zone-specific spatial localization of biometal Zn and nonmetal S from a materials viewpoint when correlated with hypoxia inducible factor-1α (HIF-1α) (a surrogate for tissue oxygenation) can provide insights into Zn-specific redox pathways at the vulnerable subchondral interface. Histologic localization of Zn, HIF-1α, and sulfur-rich proteoglycans (PGs) were mapped using an optical microscope. The µ-XRF maps coupled with site-specific micro-X-ray diffraction (µ-XRD) patterns were used to underline Zn-incorporated biological apatite in the subchondral bone and the bone of a rat TMJ condyle. Results demonstrated an association between Zn, PG, and HIF-1α histologic maps with µ-XRF, µ-XANES, and µ-XRD data and provided insights into plausible biological S species in Zn-enriched zones of a rat TMJ condyle. Spatially localized Zn and S underscore their roles in cell and tissue functions in a zone-specific manner. Elemental Zn with organic and inorganic S species at the cartilage-bone interface and the biomineral phase of Zn-enriched biological apatite from subchondral bone to condylar bone were ascertained using µ-XRF-XANES and µ-XRF-XRD. The coupled µ-XRF-XANES in situ complemented with µ-XRF-XRD in situ and immunohistochemistry provided valuable biological insights into zone-specific biological pathways in rat TMJ condyles. Based on these data, we present a workflow to reliably map and correlate S species within Zn-enriched regions of cartilage, bone, and their interface. We suggest the use of this correlative and complementary microspectroscopic spatial information for zone-specific localization of biometal Zn and nonmetal S to gain insights into plausible microanatomy-specific oxidative stress in the TMJ.

apatites↗
DOE OSTI2021

Spatial Mapping of Electrostatic Fields in 2D Heterostructures

In situ electron microscopy is an effective tool for understanding the mechanisms driving novel phenomena in 2D structures. However, due to practical challenges, it is difficult to address these technologically relevant 2D heterostructures with electron microscopy. Here, we use the differential phase contrast (DPC) imaging technique to build a methodology for probing local electrostatic fields during electrical operation with nanoscale spatial resolution in such materials. We find that, by combining a traditional DPC setup with a high-pass filter, we can largely eliminate electric fluctuations emanating from short-range atomic potentials. Using a method based on this filtering algorithm, a priori electric field expectations can be directly compared with experimentally derived values to readily identify inhomogeneities and potentially problematic regions. Furthermore, we use this platform to analyze the electric field and charge density distribution across layers of hBN and MoS 2 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Complexes of tubulin oligomers and tau form a viscoelastic intervening network cross-bridging microtubules into bundles

Abstract The axon-initial-segment (AIS) of mature neurons contains microtubule (MT) fascicles (linear bundles) implicated as retrograde diffusion barriers in the retention of MT-associated protein (MAP) tau inside axons. Tau dysfunction and leakage outside of the axon is associated with neurodegeneration. We report on the structure of steady-state MT bundles in varying concentrations of Mg 2+ or Ca 2+ divalent cations in mixtures containing αβ-tubulin, full-length tau, and GTP at 37 °C in a physiological buffer. A concentration-time kinetic phase diagram generated by synchrotron SAXS reveals a wide-spacing MT bundle phase (B ws ), a transient intermediate MT bundle phase (B int ), and a tubulin ring phase. SAXS with TEM of plastic-embedded samples provides evidence of a viscoelastic intervening network (IN) of complexes of tubulin oligomers and tau stabilizing MT bundles. In this model, αβ-tubulin oligomers in the IN are crosslinked by tau’s MT binding repeats, which also link αβ-tubulin oligomers to αβ-tubulin within the MT lattice. The model challenges whether the cross-bridging of MTs is attributed entirely to MAPs. Tubulin-tau complexes in the IN or bound to isolated MTs are potential sites for enzymatic modification of tau, promoting nucleation and growth of tau fibrils in tauopathies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Theory of the phase transition in random unitary circuits with measurements

Here, we present a theory of the entanglement transition tuned by measurement strength in qudit chains evolved by random unitary circuits and subject to either weak or random projective measurements. The transition can be understood as a nonanalytic change in the amount of information extracted by the measurements about the initial state of the system, quantified by the Fisher information. To compute the von Neumann entanglement entropy $\textit{S}$ and the Fisher information $\mathcal{F}$, we apply a replica method based on a sequence of quantities $\tilde{S}^{(n)}$ and $\mathcal{F}^{(n)}$ that depend on the $\textit{n}$th moments of density matrices and reduce to $\textit{S}$ and $\mathcal{F}$ in the limit $\textit{n}$ → 1. These quantities with $\textit{n}$ ≥ 2 are mapped to free energies of a classical spin model with $\textit{n}$! internal states in two dimensions with specific boundary conditions. In particular, $\tilde{S}^{(n)}$ is the excess free energy of a domain wall terminating on the top boundary, and $\mathcal{F}^{(n)}$ is related to the magnetization on the bottom boundary. Phase transitions occur as the spin models undergo ordering transitions in the bulk. Taking the limit of large local Hilbert space dimension $\textit{q}$ followed by the replica limit $\textit{n}$ → 1, we obtain the critical measurement probability $p_c$ = 1/2 and identify the transition as a bond percolation in the 2D square lattice in this limit. Finally, we show there is no phase transition if the measurements are allowed in an arbitrary nonlocal basis, thereby highlighting the relation between the phase transition and information scrambling. We establish an explicit connection between the entanglement phase transition and the purification dynamics of a mixed state evolution and discuss implications of our results to experimental observations of the transition and simulability of quantum dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Advanced Characterization Techniques for Overcoming Challenges of Perovskite Solar Cell Materials

Abstract In the last 10 years, organic–inorganic hybrid perovskite solar cells have achieved unprecedented advances, to the point where they now exhibit extremely high efficiency. However, long‐term stability and areal scalability limitations impede the commercial application of perovskite materials, and appropriate diagnosistic tools have become necessary to evaluate perovskite materials. Characterization of perovskite materials is regularly misinterpretated, due to unique intrinsic and extrinsic factors: degradation from the measurement source, ion migration, phase transition, and separation. Herein, studies on perovskites are reviewed that have used advanced characterization tools to overcome characterization challenges. Cryogenic temperature assisted measurements mitigate degradation or phase transitions induced by the measurement source. In situ measurements can track the variation of perovskite materials depending on external stimuli. Spatial material properties are able to be evaluated by the use of multidimensional mapping techniques. An overview of these advanced characterization tools that can overcome the challenges associated with established tools provides the opportunity for further understanding perovskite materials and solving the remaining challenges on the road to commercialization.

Kim, Min‐cheol↗
DOE OSTI2022

The eROSITA Final Equatorial-Depth Survey (eFEDS): Identification and characterization of the counterparts to point-like sources

In November 2019, eROSITA on board of the Spektrum-Roentgen-Gamma (SRG) observatory started to map the entire sky in X-rays. After the four-year survey program, it will reach a flux limit that is about 25 times deeper than ROSAT. During the SRG performance verification phase, eROSITA observed a contiguous 140 deg 2 area of the sky down to the final depth of the eROSITA all-sky survey (eROSITA Final Equatorial-Depth Survey; eFEDS), with the goal of obtaining a census of the X-ray emitting populations (stars, compact objects, galaxies, clusters of galaxies, and active galactic nuclei) that will be discovered over the entire sky. This paper presents the identification of the counterparts to the point sources detected in eFEDS in the main and hard samples and their multi-wavelength properties, including redshift. To identify the counterparts, we combined the results from two independent methods (NWAY and ASTROMATCH), trained on the multi-wavelength properties of a sample of 23k XMM-Newton sources detected in the DESI Legacy Imaging Survey DR8. Then spectroscopic redshifts and photometry from ancillary surveys were collated to compute photometric redshifts. Of the eFEDS sources, 24 774 of 27 369 have reliable counterparts (90.5%) in the main sample and 231 of 246 sources (93.9%) have counterparts in the hard sample, including 2514 (3) sources for which a second counterpart is equally likely. By means of reliable spectra, Gaia parallaxes, and/or multi-wavelength properties, we have classified the reliable counterparts in both samples into Galactic (2695) and extragalactic sources (22 079). For about 340 of the extragalactic sources, we cannot rule out the possibility that they are unresolved clusters or belong to clusters. Inspection of the distributions of the X-ray sources in various optical/IR colour-magnitude spaces reveal a rich variety of diverse classes of objects. The photometric redshifts are most reliable within the KiDS/VIKING area, where deep near-infrared data are also available. This paper accompanies the eROSITA early data release of all the observations performed during the performance and verification phase. Together with the catalogues of primary and secondary counterparts to the main and hard samples of the eFEDS survey, this paper releases their multi-wavelength properties and redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Time-series forecasting using manifold learning, radial basis function interpolation, and geometric harmonics

We address a three-tier numerical framework based on nonlinear manifold learning for the forecasting of high-dimensional time series, relaxing the “curse of dimensionality” related to the training phase of surrogate/machine learning models. At the first step, we embed the high-dimensional time series into a reduced low-dimensional space using nonlinear manifold learning (local linear embedding and parsimonious diffusion maps). Then, we construct reduced-order surrogate models on the manifold (here, for our illustrations, we used multivariate autoregressive and Gaussian process regression models) to forecast the embedded dynamics. Finally, we solve the pre-image problem, thus lifting the embedded time series back to the original high-dimensional space using radial basis function interpolation and geometric harmonics. The proposed numerical data-driven scheme can also be applied as a reduced-order model procedure for the numerical solution/propagation of the (transient) dynamics of partial differential equations (PDEs). In conclusion, we assess the performance of the proposed scheme via three different families of problems: (a) the forecasting of synthetic time series generated by three simplistic linear and weakly nonlinear stochastic models resembling electroencephalography signals, (b) the prediction/propagation of the solution profiles of a linear parabolic PDE and the Brusselator model (a set of two nonlinear parabolic PDEs), and (c) the forecasting of a real-world data set containing daily time series of ten key foreign exchange rates spanning the time period 3 September 2001–29 October 2020.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Opportunities for imaging light nuclei with a second interaction region at the Electron-Ion Collider

The upcoming Electron-Ion Collider (EIC) will address several outstanding puzzles in modern nuclear physics. Key questions—such as the partonic structure of nucleons and nuclei and the origin of their mass and spin—can be explored through high-energy electron-proton and electron-nucleus collisions. Here, to maximize its scientific reach, the EIC community has advocated for the addition of a second interaction region equipped with a detector complementary to the EIC general purpose collider detector, ePIC. The preconceptual design of this interaction region aims to provide a different configuration from the first interaction region, which enhances forward acceptance at very small scattering angles (𝜃 ∼0 mrad). This machine configuration would significantly benefit exclusive, tagging, and diffractive physics programs, complementing those of the ePIC experiment. In particular, accessing coherent diffractive processes on light nuclei by tagging of the full, intact nucleus is essential for mapping their spatial parton distributions. In this work, we present an exploratory study of the detection capabilities for light nuclei at a second EIC interaction region, with a detailed discussion of the accessible kinematic phase space and its implications for imaging.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

High-sensitivity nanoscale chemical imaging with hard x-ray nano-XANES

Resolving chemical species at the nanoscale is of paramount importance to many scientific and technological developments across a broad spectrum of disciplines. Hard x-rays with excellent penetration power and high chemical sensitivity are suitable for speciation of heterogeneous (thick) materials. Here, we report nanoscale chemical speciation by combining scanning nanoprobe and fluorescence-yield x-ray absorption near-edge structure (nano-XANES). First, the resolving power of nano-XANES was demonstrated by mapping Fe(0) and Fe(III) states of a reference sample composed of stainless steel and hematite nanoparticles with 50-nm scanning steps. Nano-XANES was then used to study the trace secondary phases in lithium iron phosphate (LFP) particles. We observed individual Fe-phosphide nanoparticles in pristine LFP, whereas partially (de)lithiated particles showed Fe-phosphide nanonetworks. These findings shed light on the contradictory reports on Fe-phosphide morphology in the literature. Nano-XANES bridges the capability gap of spectromicroscopy methods and provides exciting research opportunities across multiple disciplines.

25 ENERGY STORAGE↗