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All sources NASA NTRS DOE OSTI

DOE OSTI2021

GANISP (GAN-assisted Importance SPlitting)

Genealogical importance splitting marches towards a rare event by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is made difficult when applied to deterministic systems as the initial conditions of the offspring realizations need to be adjusted. Typically, a random perturbation is applied to the offspring. For some cases, this cloning technique may not be adequate and prevent variance reduction in the probability estimate. A GAN-based replication process is proposed to address this limitation. The perturbations applied to the clones are physically consistent instead of being randomly chosen. The proposed method allows reducing the variance in the probability estimation.

Hassanaly, Malik↗

DOE OSTI2022

GANISP: A GAN-Assisted Importance Splitting Probability Estimator: Preprint

To reduce the variance of rare event probability estimator, genealogical importance splitting marches towards a rare event by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is made difficult when applied to deterministic systems as the initial conditions of the offspring realizations need to be modified. Typically, a random perturbation is applied to the offspring to differentiate their trajectory from the parent realization. It is shown that a random perturbation strategy may be effective for some systems but may also fail for others, thereby preventing variance reduction in the probability estimate. To address this limitation, it is proposed to use a generative model such as a Generative Adversarial Network (GAN) to generate perturbations that are consistent with the attractor of the dynamical system. The GAN-assisted Importance SPlitting method (GANISP) improves the variance reduction for the system targeted. An implementation of the method is available in a companion repository (https://github.com/NREL/GANISP).

generative adversarial network↗

DOE OSTI2022

GANISP: A GAN-Assisted Importance Splitting Probability Estimator

Designing manufacturing processes with high yield and strong reliability relies on effective methods for rare event estimation. Genealogical importance splitting reduces the variance of rare event probability estimators by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is difficult when applied to deterministic systems where the initial conditions of the offspring realizations need to be modified. Typically, a random perturbation is applied to the offspring to differentiate their trajectory from the parent realization. However, this random perturbation strategy may be effective for some systems while failing for others, preventing variance reduction in the probability estimate. This work seeks to address this limitation using a generative model such as a Generative Adversarial Network (GAN) to generate perturbations that are consistent with the attractor of the dynamical system. The proposed GAN-assisted Importance SPlitting method (GANISP) improves the variance reduction for the system targeted. An implementation of the method is available in a companion repository (https://github.com/NREL/GANISP).

generative adversarial network↗

DOE OSTI2023

2023 American Society for Mass Spectrometry (ASMS) 71st Annual Conference on Mass Spectrometry and Allied Topics

Title (20 words): The investigation of the mechanism for the water splitting by holmium oxide nitrate complex in gas-phase Introduction (120 words): The studies for hydrogen from water splitting is important for clean energy economy as molecular hydrogen is a potential energy carrier. Therefore, understanding the fundamental chemistry of water splitting is essential. The water splitting activated by [Ho(NO3)4]- was previously studied. The suggested mechanism was to first eliminate •NO2 from [Ho(NO3)4]- to make [HoO(NO3)3]-. Then, water was added to form [HoO(NO3)3(H2O)]-, followed by eliminating the •OH to form [HoOH(NO3)3]-. However, we proposed a new mechanism with the formation of [Ho(NO3)3]- prior to the water addition. Once water is added to this intermediate to make [Ho(NO3)3(H2O)]-, the •H is eliminated to form [HoOH(NO3)3]-. Here we have used a labeled experiments with 18-O nitrates. The results to support the new mechanism are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Probing Cellular Activity Via Charge‐Sensitive Quantum Nanoprobes

Nitrogen‐vacancy (NV) based quantum sensors hold great potential for real‐time single‐cell sensing with far‐reaching applications in fundamental biology and medical diagnostics. Although highly sensitive, the mapping of quantum measurements onto cellular physiological states has remained an exceptional challenge. Here, we introduce a novel quantum sensing modality capable of detecting changes in cellular activity. Our approach is based on the detection of environment‐induced charge depletion within an individual particle that, owing to a previously unaccounted transverse dipole term, induces systematic shifts in the zero‐field splitting (ZFS). Importantly, these charge‐induced shifts serve as a reliable indicator for lipopolysaccharide (LPS)‐mediated inflammatory response in macrophages. Furthermore, we demonstrate that surface modification of our diamond nanoprobes effectively suppresses these environment‐induced ZFS shifts, providing an important tool for differentiating electrostatic shifts caused by the environment from other unrelated effects, such as temperature variations. Notably, this surface modification also leads to significant reductions in particle‐induced toxicity and inflammation. Our findings shed light on systematic drifts and sensitivity limits of NV spectroscopy in a biological environment with ramifications for the critical discussion surrounding single‐cell thermogenesis. Notably, this work establishes the foundation for a novel sensing modality capable of probing complex cellular processes through straightforward physical measurements.

band bending↗

DOE OSTI2025

Isotope-dependent Tafel analysis probes proton transfer kinetics during electrocatalytic water splitting

Proton transfer plays an important role in both hydrogen and oxygen evolution reactions during electrocatalytic water splitting to produce green hydrogen. However, directly adapting the conventional proton/deuterium kinetic isotope effect to study proton transfer in heterogeneous electrocatalytic processes is challenging. Here we propose using the shift in the Tafel slope between protic and deuteric electrolytes, or the Tafel slope isotope effect, as an effective probe of proton transfer characteristics. Comparison of the Tafel slope isotope effect for diverse hydrogen and oxygen evolution reaction electrocatalysts in different pH environments reveals that proton transfer is both pH and structure dependent. Using ruthenium oxide as an example, we show that local structure modification can change the rate-determining step from an electrochemical, concerted proton–electron transfer step to a chemical step and improve the oxygen evolution activity in acid. The isotope-dependent Tafel analysis will facilitate a better understanding of the proton transfer behaviours during electrocatalytic processes and provide guidance for designing efficient electrocatalysts.

Chemistry↗

DOE OSTI2025

Machine Learning in the Context of Laser-Induced Breakdown Spectroscopy

The integration of machine learning (ML) with Laser-Induced Breakdown Spectroscopy (LIBS) has revolutionized the analytical capabilities of LIBS. The combi-nation of both methods enables more accurate and efficient data analysis. While LIBS itself is a powerful technique for elemental analysis, the vast amount of spectral data it generates can be hard to interpret. Machine learning addresses these challenges by leveraging algorithms that can learn from data, identify patterns, and make predictions without explicit programming for the interpretation of each specific task. In LIBS application, ML techniques are used to enhance various analytical processes. For example, ML algorithms can classify materials based on their spectral fingerprints, predict the concentration of elements in a sample, and identify underlying patterns within complex datasets. Here, this application improves the precision of LIBS analyses while significantly reducing the time required for data processing and interpretation. In this chapter, the fundamental concepts of ML will be discussed first. Following this, the process of data splitting and the importance of feature selection will be examined. Several machine learning methods will then be closely examined, exploring how each can benefit LIBS analysis and highlighting their respective advantages and shortcomings. This structured approach will provide a comprehensive understanding of the integration of ML in the context of LIBS analysis.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Physics analysis and design of heavy water reflected thermal test reactor

Here, this work investigates the option of modifying the Advanced Test Reactor by replacing the current beryllium reflector with heavy water. Such a change may provide some potential benefits for not only increasing the thermal irradiation capabilities but also resolving other problems such as reflector integrity issues due to fast fluence damage, which is always a limiting factor in the lifetime of the current beryllium reflector. This paper presents the analysis and estimation of the ATR core physics parameters by replacing the current beryllium reflector with heavy water (D 2 O). The paper first describes the details of two selected conceptual designs, which are partially reflected with either beryllium or graphite, and how they are derived from the baseline beryllium reflector concept. Then, reactor physics performance parameters for the two new concepts are assessed by comparing with those of the baseline concept. The performance parameters considered in this paper include in-pile tube neutron and gamma fluxes and heating rates, maximum loop voiding reactivity, core power behavior with different power splits, predicted cycle length with a given fuel loading, and thermal hydraulic analysis with a higher lobe power split. It is important to note that this study focuses on the reactor physics aspects and does not delve into the engineering challenges associated with such a design modification.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Extracted Water Induces Concentration Fluctuations in Model Ternary Liquid–Liquid Extraction System

Organic phase aggregation and phase splitting are two important (and connected) phenomena in liquid–liquid extraction of metal ions. Previously, we demonstrated how structure in binary mixtures of extractant and diluent originates from concentration fluctuations associated with the so-called “third-phase formation” liquid–liquid phase instability. For more complex systems, we sought to understand how extracted aqueous components affect these concentration fluctuations. Here, in this study, we use small-angle X-ray scattering and molecular dynamics simulations to investigate organic phase structural changes upon contact with water in a model ternary system of water/alkane/extractant. Critical exponents were determined from scattering with temperature variation and were consistent with mean field values. Then, by controlling the water content in the organic phase through direct dissolution of fixed quantities at constant temperature, we relate the observed increase in the fluctuation length scale to changes to the spinodal temperature of the third-phase formation phase boundary. We find a roughly linear relationship between water concentration and the spinodal temperature and a similar slope in that relationship for different linear alkane diluents. This suggests that the mechanism by which water extraction impacts the organic phase structure is to enhance concentration fluctuations through the introduction of additional polar extractant-water complexes, which increases the spinodal temperature and thereby decreases the reduced temperature, i.e., the distance to the instability. This explanation for how solutes induce aggregation in liquid–liquid extraction organic phases may extend to more complex systems, explaining the large increases in correlation lengths reported under high acid and metal loading.

Bonnett, Brittany L. [Argonne National Laboratory ↗

DOE OSTI2021

The Problem of overlapping formation times: In-medium virtual corrections for QCD

High energy particles traversing through medium primarily lose energy by showering through hard bremsstrahlung and pair production. These splitting processes are coherent over large distances in the very high energy limit, leading to suppression from the Landau-Pomeranchuk-Migdal (LPM) effect. Avoiding soft-emission approximations, we study the cases where the coherence lengths of two consecutive splittings overlap (which is important for calculating corrections to LPM effect in QCD). Here, we will show how to compute in-medium virtual corrections to the leading order LPM emission rates for QCD. These loop corrections will be necessary for calculating properties of in-medium high energy parton showers. To simplify the calculations, we will focus on the all-gluon case and work in the large-Nc limit of QCD, where Nc is the number of colors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

HopPyBar

HopPyBar is a python program to import, analyze, and export split-Hopkinson pressure bar (SHPB, also known as Kolsky bar) data. Traditional analysis offers a black box approach, where input data is converted to analyzed output by performing a series of calculations without user involvement. This program serves as a developmental platform to "white box" the data analysis process. Data streams can be captured (in-situ) to enable advanced or unconventional analyses, statistics, and comparisons. Additionally, the program is geared towards the standardized forms of input and output used at LANL to streamline analysis, but the open nature of the program makes additional input/output schemes straightforward to add. General workflow will import SHPB data in one of a number of formats, identify relevant portions of data signals, and convert to stress-strain-strain rate to show material behavior as a function of dynamic testing.

Morrow, Benjamin↗

DOE OSTI2026

Framework Short-Range Order Observed in a Spinel-Type Li Superionic Conductor

Solid-state superionic conductors are characterized by rich structural disorders. Though structural complexities are central to their functionalities, they often give rise to short-range order that eludes detection by conventional diffraction-based techniques and is thus overlooked in establishing precise structure-property relationships. In this work, we synthesized single crystals of a recently discovered lithium (Li) superionic conductor Li16.2(1)In9.00(2)Sn1.10(1)O23.8 (LISO) for in-depth characterizations of structural subtleties. LISO exhibits an unusual spinel-like phase with significant Li overstoichiometry and a face-sharing Li network. Single-crystal neutron diffraction confirms significant Li disorder, as manifested in Li site splitting and partial occupancy. More importantly, synchrotron diffuse scattering combined with 3D-ΔPDF analysis and Monte Carlo simulations reveal short-range order in the nonalkali framework that might contribute to the phase stability and ionic conductivity. This work showcases an example in which subtle local energetics can be directly visualized in structurally disordered ionic conductors.

Chen, Yu↗

DOE OSTI2024

Stabilization of Catalytically Active Surface Defects on Ga-doped La–Sr–Mn Perovskites for Improved Solar Thermochemical Generation of Hydrogen

Solar thermochemical hydrogen (STCH) production from water splitting typically requires performing redox cycles at temperatures above 1200 °C to reduce and re-oxidize the bulk of a reversible material. Bulk processes such as oxygen vacancy formation and oxygen diffusion energies dictate the viability of a material for STCH. The surface plays an important role in the formation and destruction of vacancies and interacts with gas phase water and surface adsorbed species. These surface processes can lead to surface reconfigurations and even the formation of surface phases with stoichiometry and oxygen content very different from the bulk composition. Understanding in-situ the surface chemical state and its evolution under water splitting is important to design nonstoichiometric oxides capable of longer-lasting STCH generation at lower temperatures. In this work, we describe the water splitting active defect sites in LSM ((La 0.65 Sr 0.35 ) 0.95 MnO 3–δ ) and Ga-doped LSM ((La 0.6 Sr 0.4 ) 0.95 (Mn 0.8 Ga 0.2 )O 3–δ ) perovskites during Operando thermochemical water splitting conditions using ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) experiments at 800 °C under steam. We show that sub-stoichiometric La +3 in the oxygen-vacancy rich surface at operating conditions can be used to correlate surface water splitting activity and the creation of surface hydroxide intermediates. The addition of Ga in LSM is shown to drastically stabilize the surface chemical composition by preventing Sr segregation and stabilizing catalytically active surface defects that promote the binding of adsorbed hydroxides. Here, we use Operando AP-XPS quantification of metastable surface hydroxide intermediates (La(OH) 3 ) to determine the amount of catalytically active surface sites in LSM (2.9%) and in LSMG (7.8–8.1%, depending on the bulk oxidation state).

08 HYDROGEN↗

DOE OSTI2022

Emergence of Fermi arcs due to magnetic splitting in an antiferromagnet

The Fermi surface plays an important role in controlling the electronic, transport and thermodynamic properties of materials. As the Fermi surface consists of closed contours in the momentum space for well-defined energy bands, disconnected sections known as Fermi arcs can be signatures of unusual electronic states, such as a pseudogap. Another way to obtain Fermi arcs is to break either the time-reversal symmetry or the inversion symmetry of a three-dimensional Dirac semimetal, which results in formation of pairs of Weyl nodes that have opposite chirality, and their projections are connected by Fermi arcs at the bulk boundary. Here, we present experimental evidence that pairs of hole- and electron-like Fermi arcs emerge below the Neel temperature (TN) in the antiferromagnetic state of cubic NdBi due to a new magnetic splitting effect. The observed magnetic splitting is unusual, as it creates bands of opposing curvature, which change with temperature and follow the antiferromagnetic order parameter. This is different from previous theoretically considered and experimentally reported cases of magnetic splitting, such as traditional Zeeman and Rashba, in which the curvature of the bands is preserved. Therefore, our findings demonstrate a type of magnetic band splitting in the presence of a long-range antiferromagnetic order that is not readily explained by existing theoretical ideas.

36 MATERIALS SCIENCE↗

DOE OSTI2025

All-order splits and multi-soft limits for particle and string amplitudes

The most important aspects of scattering amplitudes have long been thought to be associated with their poles. But recently a very different sort of “split” factorizations for a wide range of particle and string tree amplitudes have been discovered away from poles. In this paper, we give a simple, conceptual origin for these splits arising from natural properties of the binary geometry of the curve integral formulation for scattering amplitudes for Tr(Φ 3 ) theory. The most natural way of “joining” smaller surfaces to build larger ones directly produces a choice of kinematics for which higher amplitudes factor into lower ones. This gives a generalization of splits to all orders in the topological expansion. These splits allow us to access and compute loop-integrated multi-soft limits for particle and string amplitudes, at all loop orders. This includes split factorizations and multisoft limits for pion and gluon amplitudes, that are related to Tr(Φ 3 ) theory by a simple kinematical shift.

Bosonic Strings↗

DOE OSTI2023

Low Catalyst Loading Enhances Charge Accumulation for Photoelectrochemical Water Splitting

Abstract Solar water oxidation is a critical step in artificial photosynthesis. Successful completion of the process requires four holes and releases four protons. It depends on the consecutive accumulation of charges at the active site. While recent research has shown an obvious dependence of the reaction kinetics on the hole concentrations on the surface of heterogeneous (photo)electrodes, little is known about how the catalyst density impacts the reaction rate. Using atomically dispersed Ir catalysts on hematite, we report a study on how the interplay between the catalyst density and the surface hole concentration influences the reaction kinetics. At low photon flux, where surface hole concentrations are low, faster charge transfer was observed on photoelectrodes with low catalyst density compared to high catalyst density; at high photon flux and high applied potentials, where surface hole concentrations are moderate or high, slower surface charge recombination was afforded by low‐density catalysts. The results support that charge transfer between the light absorber and the catalyst is reversible; they reveal the unexpected benefits of low‐density catalyst loading in facilitating forward charge transfer for desired chemical reactions. It is implied that for practical solar water splitting devices, a suitable catalyst loading is important for maximized performance.

Liu, Tianying↗

DOE OSTI2023

Low Catalyst Loading Enhances Charge Accumulation for Photoelectrochemical Water Splitting

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

The Budyko shape parameter as a descriptive index for streamflow loss

Increases in evapotranspiration (ET) from global warming are decreasing streamflow in headwater basins worldwide. However, these streamflow losses do not occur uniformly due to complex topography. To better understand the heterogeneity of streamflow loss, we use the Budyko shape parameter (ω) as a diagnostic tool. We fit ω to 37-year of hydrologic simulation output in the Upper Colorado River Basin (UCRB), an important headwater basin in the US. We split the UCRB into two categories: peak watersheds with high elevation and steep slopes, and valley watersheds with lower elevation and gradual slopes. Our results demonstrate a relationship between streamflow loss and ω. The valley watersheds with greater streamflow loss have ω higher than 3.1, while the peak watersheds with less streamflow loss have an average ω of 1.3. This work highlights the use of ω as an indicator of streamflow loss and could be generalized to other headwater basin systems.

large scale analysis↗