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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 127 records · Page 7

HPC Digital Twins for Evaluating Scheduling Policies, Incentive Structures and their Impact on Power and Cooling

Schedulers are critical for optimal resource utilization in high-performance computing. Traditional methods to evaluate sched- ulers are limited to post-deployment analysis, or simulators, which do not model associated infrastructure. In this work, we present the first-of-its-kind integration of scheduling and digital twins in HPC. This enables what-if studies to understand the impact of parameter configurations and scheduling decisions on the physical assets, even before deployment, or regarching changes not easily realizable in production. We (1) provide the first digital twin framework extended with scheduling capabilities, (2) integrate various top-tier HPC systems given their publicly available datasets, (3) implement extensions to integrate external scheduling simulators. Finally, we show how to (4) implement and evaluate incentive structures, as- well-as (5) evaluate machine learning based scheduling, in such novel digital-twin based meta-framework to prototype scheduling. Our work enables what-if scenarios of HPC systems to evaluate sustainability, and the impact on the simulated system.

Maiterth, Matthias [ORNL] (ORCID:000000018698460X)↗

Macroscopic Monochalcogenide van der Waals Ferroics: Growth, Domain Structures, and Curie Temperature

Two-dimensional and layered van der Waals materials promise to overcome the limitations of conventional ferroelectrics in terms of miniaturization and material integration, but synthesis has produced only small (up to few micrometer-sized) ferroic crystals. Here, we report the realization of in-plane ferroelectric few-layer crystals of the monochalcogenides tin(II) sulfide and selenide (SnS, SnSe) whose linear dimensions exceed the current state of the art by up to 1 order of magnitude. Such large crystals allow the investigation of ferroic domain patterns that are unaffected by edges and finite-size effects. Analysis of the abundant stripe domains by electron microscopy and nanobeam electron diffraction shows two distinct domain types: twin domains separated by positively charged walls with alternating head-to-head and tail-to-tail polarization as well as not previously observed purely rotational domains connected by neutral domain walls with head-to-tail dipoles. Access to large crystals allowed the determination of the Curie temperature of few-layer SnSe van der Waals ferroelectrics, and it enables the investigation of this class of ferroelectrics by widely available methods such as polarized optical microscopy. Furthermore, the combination with layer transfer protocols promises uniform materials for exploring fundamentals and for implementing devices for information processing and energy conversion.

36 MATERIALS SCIENCE↗

Topochemical Oxidation of Ruddlesden–Popper Nickelates Reveals Distinct Structural Family: Oxygen-Intercalated Layered Perovskites

Layered perovskites─including the Dion–Jacobson, Ruddlesden–Popper, and Aurivillius families─exhibit a wide range of correlated electron phenomena, from high-temperature superconductivity to multiferroicity. Here, in this study, we report a new family of layered perovskites realized through topochemical oxidation of La n+1 Ni n O 3n+1+δ (n = 1–4) Ruddlesden–Popper nickelate thin films. Postgrowth ozone annealing induces a substantial c-axis expansion─17.8% for La 2 NiO 4+δ (n = 1)─that monotonically decreases with increasing n. Surface synchrotron X-ray diffraction and coherent Bragg rod analysis (COBRA) reveal that this structural expansion arises from the intercalation of approximately δ ≈ 0.7–1.0 oxygen atoms into interstitial sites within the rock salt spacer layers, far exceeding the previous record of δ ≈ 0.3 for any Ruddlesden–Popper oxide. These oxygen-intercalated phases form a new class of layered perovskites with a spacer layer composition intermediate between the Ruddlesden–Popper and Aurivillius phases. Furthermore, oxygen intercalation induces metallicity, enhances nickel–oxygen hybridization, and suppresses oxygen octahedral rotations, a feature associated with high-temperature superconductivity in Ruddlesden–Popper nickelates. Our work establishes topochemical oxidation as a powerful approach to accessing highly oxidized, metastable phases across a broad range of layered oxide systems, offering new platforms to engineer electronic properties via intercalation chemistry.

Ferenc Segedin, Dan [Harvard Univ., Cambridge, MA ↗

Elucidating the Role of InGaAs and InAlAs Buffers on Carrier Dynamics of Tensile-Strained Ge Double Heterostructures

Extensive research efforts of strained germanium (Ge) are currently underway due to its unique properties, namely, (i) possibility of band gap and strain engineering to achieve a direct band gap, thus exhibiting superior radiative properties, and (ii) higher electron and hole mobilities than Si for upcoming technology nodes. Realizing lasing structures is vital to leveraging the benefits of tensile-strained Ge (ε-Ge). Here, we use a combination of different analytical tools to elucidate the effect of the underlying InGaAs/InAlAs and InGaAs overlaying heterostructures on the material quality and strain state of ε-Ge grown by molecular beam epitaxy. Using X-ray analysis, we show the constancy of tensile strain in sub-50 nm ε-Ge in a quantum-well (QW) heterostructure. Further, effective carrier lifetime using photoconductive decay as a function of buffer type exhibited a high (low) defect-limited carrier lifetime of ~68 ns (~13 ns) in 0.61% (0.66%) ε-Ge grown on an InGaAs (InAlAs) buffer. These results correspond well with the measured surface roughness of 1.289 nm (6.303 nm), consistent with the surface effect of the ε-Ge/III–V heterointerface. Furthermore, a reasonably high effective lifetime of ~78 ns is demonstrated in a QW of ~30 nm 1.6% ε-Ge, a moderate reduction from ~99 ns in uncapped ε-Ge, alluding to the surface effect of the overlying heterointerface. Thus, the above results highlight the prime quality of ε-Ge that can be achieved via III–V heteroepitaxy and paves a path for integrated Ge photonics.

36 MATERIALS SCIENCE↗

Zero-added-loss entanglement multiplexing using time-bin spectral shearing

High-quality quantum communications that enable important capabilities, such as distributed quantum computing and sensing, will require quantum repeaters for providing high-quality entanglement. To realize high-rate heralded entanglement for quantum repeaters, Chen et al . [Phys. Rev. Appl. 19 , 054029 (2023)] proposed a scheme for heralded-multiplexed generation of quasideterministic entangled photon pairs, called zero-added-loss multiplexing (ZALM). Here, we propose a design of the ZALM source using time-bin entanglement and spectral shearing. Additionally, we provide an analysis of experimentally relevant spectral-shearing parameters to optimize the spectral multiplexing. Moreover, we experimentally verify the compatibility of time-bin pulses and spectral shearing, as supported by observation of no appreciable phase shift when the same shearing is applied to both time bins. These results expand the benefits of applying a ZALM source to time-bin entanglement use cases. Moreover, more fully demonstrating time-bin and spectral shearing compatibility clears a path toward a broader use of spectral shearing that provides a deterministic frequency shift of high utility.

entanglement production↗

One Galaxy Sample to Rule Them All: Halo Occupation Distribution Modeling of DES Year 3 Source Galaxies

Abstract For the joint analysis of second-order weak-lensing and galaxy clustering statistics, so-called 3 × 2 analyses, the selection and characterization of optimal galaxy samples is a major area of research. One promising choice is to use the same galaxy sample as lenses and sources, which reduces the systematics parameter space that describes the uncertainties related to galaxy samples. Such a “lens-equal-source” analysis significantly improves the self-calibration of photo- z systematics, leading to improved cosmological constraints. With the aim of enabling a lens-equal-source analysis on small scales, we investigate the halo–galaxy connection of DES Year 3 source galaxies. We develop a technique to construct mock source galaxy populations by matching COSMOS/UltraVISTA photometry to U niverse M achine galaxies. These mocks predict a source halo occupation distribution (HOD) that exhibits significant redshift evolution, nontrivial central incompleteness, and galaxy assembly bias. We produce multiple realizations of mock source galaxies drawn from the U niverse M achine posterior, with added uncertainties in the measured Dark Energy Survey photometry and galaxy shapes. We fit a modified HOD formalism to these realizations to produce priors on the galaxy–halo connection for cosmological analyses. We additionally train an emulator that predicts this HOD to ∼2% accuracy from redshift z = 0.1−1.3 that models the dependence of this HOD on (1) observational uncertainties in galaxy size and photometry and (2) uncertainties in the U niverse M achine predictions.

Salcedo, Andrés N. (ORCID:000000031420527X)↗

Alternant Hydrocarbon Diradicals as Optically Addressable Molecular Qubits

High-spin molecules allow for bottom-up qubit design and are promising platforms for magnetic sensing and quantum information science. Optical addressability of molecular electron spins has also been proposed in first-row transition-metal complexes via optically detected magnetic resonance (ODMR) mechanisms analogous to the diamond-nitrogen-vacancy color center. However, significantly less progress has been made on the front of metal-free molecules, which can deliver lower costs and milder environmental impacts. At present, most luminescent open-shell organic molecules are π-diradicals, but such systems often suffer from poor ground-state open-shell characters necessary to realize a stable ground-state molecular qubit. In this work, we use alternancy symmetry to selectively minimize radical–radical interactions in the ground state, generating π-systems with high diradical characters. We call them m-dimers, referencing the need to covalently link two benzylic radicals at their meta carbon atoms for the desired symmetry. Through a detailed electronic structure analysis, we find that the excited states of alternant hydrocarbon m-diradicals contain important symmetries that can be used to construct ODMR mechanisms leading to ground-state spin polarization. Furthermore, the molecular parameters are set in the context of a tris(2,4,6-trichlorophenyl)methyl (TTM) radical dimer covalently tethered at the meta position, demonstrating the feasibility of alternant m-diradicals as molecular color centers.

Chemistry↗

High-throughput micro-scale bandgap mapping for perovskite-inspired materials with complex composition space

Abstract To realize the full promise of high-throughput experimental workflows, the rate of sample synthesis must be matched by that of characterization. Of growing interest are contactless optical techniques that can rapidly measure material homogeneity and properties. Here, we present a hyperspectral imaging method to measure local optical bandgap distributions within samples, utilizing spatially-resolved reflectance spectra coupled with automated data analysis. We collect approximately one million optical bandgap data across the compositional space of Cs 3 (Bi x Sb 1-x ) 2 (Br y I 1-y ) 9 perovskite-inspired materials. Our results show non-monotonic bandgap variations (i.e., bandgap bowing) along six composition gradient sequences, in addition to identifying samples with multiple bandgaps in statistics. High-throughput transient absorption spectroscopy reveals that within these compositions, the depletion of the ground state carriers to excited states occurred at discrete energy levels with independent carrier dynamics, consistent with the bandgap observation and indicative of phase separation. This work demonstrates the potential for rapid optical measurements to assess material quality and homogeneity in a high-throughput experimental setting, supporting screening and recipe optimization of optoelectronic material candidates with desired carrier dynamics and optical properties.

Science & Technology - Other Topics↗

Data reduction for low energy nuclear physics experiments using data frames

Low energy nuclear physics experiments are transitioning towards fully digital data acquisition systems. Realizing the gains in flexibility afforded by these systems relies on equally flexible data reduction techniques. In this paper, methods utilizing data frames and in-memory techniques to work with data, including data from self-triggering, digital data acquisition systems, are discussed within the context of a Python package, sauce. It is shown that data frame operations can encompass common analysis needs and allow interactive data analysis. Two event building techniques, dubbed referenced and referenceless event building, are shown to provide a means to transform raw list mode data into correlated multi-detector events. These techniques are demonstrated in the analysis of two example data sets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Codebase release 2.0 for sauce

Low energy nuclear physics experiments are transitioning towards fully digital data acquisition systems. Realizing the gains in flexibility afforded by these systems relies on equally flexible data reduction techniques. In this paper, methods utilizing data frames and in-memory techniques to work with data, including data from self-triggering, digital data acquisition systems, are discussed within the context of a Python package, sauce. It is shown that data frame operations can encompass common analysis needs and allow interactive data analysis. Two event building techniques, dubbed referenced and referenceless event building, are shown to provide a means to transform raw list mode data into correlated multi-detector events. These techniques are demonstrated in the analysis of two example data sets.

Marshall, Caleb (ORCID:0000000211942920)↗

A Regional Approach to Offshore Wind Energy Manufacturing in the Central Atlantic: Supply Chain

Growth of the offshore wind industry in the United States is likely to require growth in the nation's manufacturing capacity and additional resources and investments to meet energy project demands. Such growth has the potential to provide positive economic impacts for local communities, workers, and entire states. To realize the benefits of developing a domestic offshore wind supply chain, the states of Maryland, North Carolina and Virginia are working together under the Southeast and Mid-Atlantic Regional Transformative Partnership for Offshore Wind Resources (SMART-POWER) regional collaboration to advance the industry, with Delaware as a supporting state. This report is part of the SMART-POWER Workforce and Supply Chain Analysis study, funded by the National Offshore Wind Research and Development Consortium. The study assesses challenges and opportunities for the four Central Atlantic states to understand key regional strengths and identify supply chain investments that could effectively leverage their resources and provide benefits to both the member states and the offshore wind sector as a whole.

17 WIND ENERGY↗

Initial Uncertainty Analysis of Carbon Tetrachloride Contamination and Remediation in the Ringold A and Lower Mud Units at the Central Plateau

The long-term effectiveness of groundwater cleanup at the Hanford Site Central Plateau depends on predictive models that can capture key uncertainties in contaminant fate and transport. Carbon tetrachloride (CCl 4 ), a persistent and toxic compound, presents particular challenges due to variability in degradation rates, uncertainty in initial plume distribution, and subsurface heterogeneity. These uncertainties directly influence plume persistence, migration pathways, and remedy performance, and thus must be systematically evaluated to support long-term remediation planning. To address these gaps, a large-scale Monte Carlo analysis was conducted using the Plateau to River (P2R) model framework. The modeling approach parameterized three primary uncertainty factors: (1) degradation rate, (2) initial plume distribution, and (3) hydraulic conductivity. Degradation was represented as a first-order process, with half-lives ranging from 70 to 700 years. Initial plume distributions were created using a geostatistical simulation method (sgsim), which generates many equally plausible versions of how contaminants might be distributed underground. From this, 100 different scenarios were mapped onto the P2R grid. Variability in hydraulic conductivity was represented in a similar way, with 100 scenarios each for the Ringold Lower Mud and Ringold A units (layers 6 and 7), based on fitted exponential variograms and conditioned to well data. In total, more than 1000 realizations were simulated to assess plume behavior under uncertainty. Results demonstrate that degradation kinetics exert the strongest control over plume persistence: Shorter half-lives produced rapid mass reduction, while longer half-lives yielded persistent plumes with limited attenuation. A nonlinear response was observed, with steep mass reductions at half-lives greater than 200 years and near-linear declines beyond this threshold, reflecting interactions between degradation and pumping. The initial plume distribution strongly influenced early transport patterns, with broader sources generating larger plume footprints, although pump-and-treat operations constrained plume migration to managed areas. By comparison, hydraulic conductivity variability in the Ringold units had only a secondary influence, modifying spreading behavior without altering the dominant migration pathways governed by source configuration and hydraulic controls. Overall, the analysis highlights that uncertainty in degradation rate and initial plume configuration are the primary drivers of variability in plume predictions, while conductivity heterogeneity plays a limited role. These findings underscore the need for improved site-specific data on degradation processes and source characterization to enhance the reliability of long-term performance assessments and to better inform remedial decision-making at the Central Plateau.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The AGN-201 Digital Twin: A test bed for remotely monitoring nuclear reactors

Research reactors have historically provided researchers and scientists with a means for testing and understanding the workings of nuclear phenomena. With the lack of new research reactors built in the past decades, it is important now more than ever to utilize and provide evidence for the usefulness of research reactors. Here, this work explores the use of the AGN-201 research reactor at Idaho State University as a test bed for developing a digital twin (named the AGN-201 DT) to realize remote monitoring for nuclear reactors. The goal of the AGN-201 DT is to monitor the AGN-201 reactor and detect when undeclared events take place to provide information for a monitoring agency. The AGN-201 DT was able to detect (without a priori knowledge) when multiple undeclared experiments were placed in the core using on-the-fly machine learning and reactor physics analysis. The AGN-201 reactor provided a test bed for developing, deploying, and testing a digital twin for monitoring nuclear reactors.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Digital Twin for Chemical Science (DTCS) v0.01

Directly visualizing the trajectories of chemistry can unravel novel insights into the behavior of catalysts, gas phase reactions, photo-induced dynamics, and building blocks for quantum information processing. The ability of explicitly identifying, tracking, and tagging the exchange of matter, hence the annihilation and creation of new chemical species, can be best realized through a close coupling of theory and experiment. While the synchrotron-based characterization facilities propelled rapidly in its hardware, providing higher brightness, better resolution, and more precision, the software infrastructure is lagging. We developed DTCS (Digital Twin for Chemical Science) v.01, a central platform that faithfully mimics advanced instrumentations in Scientific User Facilities, by solving a variety of technical challenges in data acquisition, analysis, and model-driven interpretation. Rooted in physics and accelerated by AI, we validated this concept by direct comparison with precise experimental X-ray Photoelectron Spectroscopy (XPS) observations using a ubiquitous metal-water interfacial scenario, i.e., Ag/H2O as our main narrative. The DTCS v.01 input mirrors how the bench chemists work, with the output directly linked to the end station computer, thereby providing a user-friendly, knowledge-driven, and accessible user experience with mechanistic insights standardized in a way that are ready to be published, versioned, and transferred flexibly.

Qian, Jin↗

Lignin-Derived Phenolic Compounds and Water Are Effective Cosolvents for Reductive Catalytic Fractionation

Reductive catalytic fractionation (RCF) is an effective lignin-first biorefining method to extract lignin as a stabilized oil from lignocellulosic biomass. To realize RCF at scale, process modeling has shown that minimizing the use of exogenous organic solvents is critical. To this end, here we investigate the ability of lignin-derived monomers to act as either solvents or cosolvents for RCF. We begin by examining the influence of lignin-derived aromatic compounds (4-propylguaiacol, 4-propylphenol, and propylbenzene) on RCF monomer yields and subsequently extend our analysis to mixtures of 4-propylguaiacol and either methanol or water. Here, we demonstrate that 4-propylguaiacol is an effective solvent for lignin extraction and depolymerization during RCF, especially when used in combination with water as a cosolvent. Cosolvent mixtures of 4-propylguaiacol and water enable up to 81% lignin extraction, monomer yields up to 25 wt %, and postreaction phase separation. However, unlike methanol, water as a cosolvent fails to inhibit aromatic ring hydrogenation when conducted over Ru/C as a catalyst, potentially leading to excess hydrogen consumption in a process utilizing this approach. Nonetheless, these results suggest a promising strategy for eliminating external organic solvents from RCF by utilizing mixtures of lignin-derived compounds and water as alternative extraction solvents.

09 BIOMASS FUELS↗

DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models With 3D Diffusion Models

Earth system models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the robust analysis of risks associated with extreme weather events. While low-cost climate emulators have emerged as an alternative to emulate ESMs and enable rapid analysis of future climate, many of these emulators only provide output on at most a monthly frequency. This temporal resolution is insufficient for analyzing events that require daily characterization, such as heat waves or heavy precipitation. We propose using diffusion models, a class of generative deep learning models, to effectively downscale ESM output from a monthly to a daily frequency. Trained on a handful of ESM realizations, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input, and is capable of producing daily values with statistical characteristics close to ESM output. Combined with a low-cost emulator providing monthly means, this approach requires only a small fraction of the computational resources needed to run a large ensemble. We evaluate model behavior using a number of extreme metrics, showing that DiffESM closely matches the spatio-temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.

54 ENVIRONMENTAL SCIENCES↗

Tabulated data for Lignin-Derived Phenolic Compounds and Water Are Effective Cosolvents for Reductive Catalytic Fractionation

Reductive catalytic fractionation (RCF) is an effective lignin-first biorefining method to extract lignin as a stabilized oil from lignocellulosic biomass. To realize RCF at scale, process modeling has shown that minimizing the use of exogenous organic solvents is critical. To this end, here we investigate the ability of lignin-derived monomers to act as either solvents or cosolvents for RCF. We begin by examining the influence of lignin-derived aromatic compounds (4-propylguaiacol, 4-propylphenol, and propylbenzene) on RCF monomer yields and subsequently extend our analysis to mixtures of 4-propylguaiacol and either methanol or water. We demonstrate that 4-propylguaiacol is an effective solvent for lignin extraction and depolymerization during RCF, especially when used in combination with water as a cosolvent. Cosolvent mixtures of 4-propylguaiacol and water enable up to 81% lignin extraction, monomer yields up to 25 wt %, and postreaction phase separation. However, unlike methanol, water as a cosolvent fails to inhibit aromatic ring hydrogenation when conducted over Ru/C as a catalyst, potentially leading to excess hydrogen consumption in a process utilizing this approach. Nonetheless, these results suggest a promising strategy for eliminating external organic solvents from RCF by utilizing mixtures of lignin-derived compounds and water as alternative extraction solvents. This is the tabulated data for the paper

biorefining↗

Calculation of monomer yields, verification of PG concentration approximation, catalyst comparison for neat aromatic RCF, SEM micrographs for postreaction pulps, yields of aqueous-phase sugar derivatives after PG-H2O RCF, reactor pressure transients, GPC comparing pre- and postreaction organic solvent composition, PG-H2O miscibility testing, GPC probing dimer/oligomer fractionation in PG-H2O mixtures for

Reductive catalytic fractionation (RCF) is an effective lignin-first biorefining method to extract lignin as a stabilized oil from lignocellulosic biomass. To realize RCF at scale, process modeling has shown that minimizing the use of exogenous organic solvents is critical. To this end, here we investigate the ability of lignin-derived monomers to act as either solvents or cosolvents for RCF. We begin by examining the influence of lignin-derived aromatic compounds (4-propylguaiacol, 4-propylphenol, and propylbenzene) on RCF monomer yields and subsequently extend our analysis to mixtures of 4-propylguaiacol and either methanol or water. We demonstrate that 4-propylguaiacol is an effective solvent for lignin extraction and depolymerization during RCF, especially when used in combination with water as a cosolvent. Cosolvent mixtures of 4-propylguaiacol and water enable up to 81% lignin extraction, monomer yields up to 25 wt %, and postreaction phase separation. However, unlike methanol, water as a cosolvent fails to inhibit aromatic ring hydrogenation when conducted over Ru/C as a catalyst, potentially leading to excess hydrogen consumption in a process utilizing this approach. Nonetheless, these results suggest a promising strategy for eliminating external organic solvents from RCF by utilizing mixtures of lignin-derived compounds and water as alternative extraction solvents.

biorefining↗