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DOE OSTI2022

Activating nano-bulk interplays for sustainable ammonia electrosynthesis

Small changes in a catalyst’s composition, modification, and/or integration into a reactor can have significant yet often poorly understood effects on (electro)catalysis. Here we demonstrate the careful tailoring of Ru/La 0.25 Ce 0.75 O 2-x catalysts through the post-synthesized hydrothermal treatment together with control over the Ru loadings to create hydroxyl groups and electronic restructuring for ammonia electrosynthesis. When integrated into a protonic ceramic electrolyzer, the in situ formed Ce 3+ -OH/Ru sites facilitate both the N≡N decoupling and N—H formation at 400 °C and 1 bar of N 2 , boosting the ammonia production rate (2.92 mol h -1 m -2 ) up to 100-fold higher than the current state-of-the-art electrolyzers. Moreover, such catalysts and electrolyzer design concepts can be readily tuned to more complex applications such as coproducing ammonia and other chemicals with hydrocarbons as direct hydrogen sources. Here, the creation of coordinated saturated support –OH/metal sites in the advanced electrolyzer offers an attractive approach for future clean-energy and green-chemical industries.

03 NATURAL GAS↗

DOE OSTI2026

Facile Synthesis of Oxyhydrides by Reaction with NaBH 4 in an Open System

Oxyhydrides are an intriguing class of materials in which there is partial replacement of the oxide ion with hydride ions and oxygen vacancies. Conventional synthesis relies on vacuum sealed ampules, using long reaction times at high temperatures, limiting accessibility. Here, we demonstrate a rapid, ambient-pressure route to oxyhydride formation using NaBH 4 under flowing argon in just 1 h. This approach significantly lowers experimental barriers, enabling broader exploration of these materials. The maximum hydride incorporation, obtained using a reaction temperature of 400 °C, is given by the formula SrTiO 2.945 H 0.049 , where the hydride, oxygen vacancy, and unpaired electron concentrations are determined through thermogravimetric analysis, quantitative solid-state nuclear magnetic resonance (NMR) spectroscopy, and electron paramagnetic resonance (EPR) spectroscopy. Density functional theory simulations of the 1 H NMR shifts for candidate point defects support the assignment of the observed hydride peak, validating the efficacy of the synthetic approach. A combination of in situ and ex situ studies of the reaction pathway reveal that hydride incorporation into the perovskite occurs via direct solid-solid reaction, with higher reaction temperatures favoring NaBH 4 decomposition and H 2 (g) release over oxyhydride formation. The electronic defect structure established from the EPR and NMR studies indicate that, at ambient temperature, anion vacant sites are occupied by single electrons, whereas hydride sites do not trap electrons. As a result, this work establishes a scalable synthesis strategy and provides a computational-experimental framework for understanding defect chemistry in oxyhydrides, opening pathways for their integration into energy and electronic applications.

Anions↗

DOE OSTI2026

Developing Scenario‐Based Strategies for Health, Climate, and Environmental Preparedness: The One Health, One Earth Approach

Climate change amplifies many threats to human health. Despite advances in understanding climate change dynamics and impacts, there remains a critical gap in translating scientific knowledge into equitable, and community-driven health interventions. The inaugural One Earth, One Health workshop sought to explore this gap through human-centered design exercises involving interdisciplinary researchers from climate and Earth sciences, engineering, epidemiology, microbiology, and environmental health. Although participants did not co-develop solutions with affected communities, they used stakeholder role-playing to guide ideation and lay groundwork for actionable plans. Through these methods, participants identified community needs and proposed prototype solutions to alleviate health threats exacerbated by global environmental change. Prototypes were organized around infectious diseases, extreme weather, and air quality, as illustrative themes rather than an exhaustive set of risks. Key solutions included strategies for anticipatory systems and early warning (e.g., integrating environmental signals with health data), inclusive communication and infrastructure needs for responding to extreme weather events, and integrated platforms visualizing air quality trends to support tailored, context-aware guidance beyond one-size-fits-all alerts. The workshop highlighted opportunities such as leveraging machine learning, Earth observation, and real-time surveillance to protect communities, but also noted barriers including data quality, technological redundancy, privacy, and governance challenges. Additionally, participants emphasized the need for interdisciplinary teams capable of collaborating across sectors, breaking down silos and addressing gaps in training and education. Overall, the workshop illustrates how process-driven, human-centered approaches can help surface user needs and generate testable prototype concepts, while underscoring the importance of direct community partnership for implementation.

Abadi, Azar M. [University of Alabama, Birmingham,↗

DOE OSTI2025

Measurement of the nucleon spin structure functions for 0.01 < 𝑄 2 < 1 GeV 2 using CLAS

The spin structure functions of the proton and the deuteron were measured during the EG4 experiment at Jefferson Lab in 2006. Data were collected for longitudinally polarized electron scattering off longitudinally polarized NH 3 and ND 3 targets, for 𝑄 2 values as small as 0.012 and 0.02 GeV 2 , respectively, using the CEBAF Large Acceptance Spectrometer. This is the archival paper of the EG4 experiment that summarizes the previously reported results of the polarized structure functions 𝑔 1 , 𝐴 1 ⁢𝐹 1 , and their moments $\bar{Γ}$ 1 , $\bar{𝛾}$ 0 , and $\bar{𝐼}$ TT , for both the proton and the deuteron. In addition, we report on new results on the neutron 𝑔 1 extracted by combining proton and deuteron data and correcting for Fermi smearing, and on the neutron moments $\bar{Γ}$ 1 , $\bar{𝛾}$ 0 , and $\bar{𝐼}$ TT formed directly from those of the proton and the deuteron. Our data are in good agreement with the Gerasimov-Drell-Hearn sum rule for the proton, deuteron, and neutron. Furthermore, the isovector combination was formed for 𝑔 1 and the Bjorken integral $\bar{Γ}^{𝑝−𝑛}_1$, and it was compared to available theoretical predictions. All of our results, to the best of our knowledge, provide for the first time extensive tests of spin observable predictions from chiral effective field theory (𝜒⁢EFT) in a 𝑄 2 range commensurate with the pion mass. Finally, they motivate further improvement in 𝜒⁢EFT calculations from other approaches such as the lattice gauge method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1981

The CELSS program - An overview of its structure and use of computer modelling

NASA has initiated a research program, CELSS, directed at the acquisition of the knowledge and technology required for the development of an autonomous, regenerative life support system. The program is structured to promote effective, cooperative research in fundamental, applied and engineering science. The initial research thrusts involve investigations into problems of food production, waste processing and system control and integration. In the area of food production both conventional, higher plant-based processes as well as chemosynthetic food production technologies are being investigated. Alternative waste processing procedures, both biological and physicochemical, are being examined. Computer based modelling as an aid to design and analysis is an integral part of the approach to system control and management. A mass balance model depicting the flow of elemental mass in a conceptualized closed, regenerative life support system is described.

Averner, M. M.↗

NASA NTRS1993

A modified approach to controller partitioning

The idea of computing a decentralized control law for the integrated flight/propulsion control of an aircraft by partitioning a given centralized controller is investigated. An existing controller partitioning methodology is described, and a modified approach is proposed with the objective of simplifying the associated controller approximation problem. Under the existing approach, the decentralized control structure is a variable in the partitioning process; by contrast, the modified approach assumes that the structure is fixed a priori. Hence, the centralized controller design may take the decentralized control structure into account. Specifically, the centralized controller may be designed to include all the same inputs and outputs as the decentralized controller; then, the two controllers may be compared directly, simplifying the partitioning process considerably. Following the modified approach, a centralized controller is designed for an example aircraft mode. The design includes all the inputs and outputs to be used in a specified decentralized control structure. However, it is shown that the resulting centralized controller is not well suited for approximation by a decentralized controller of the given structure. The results indicate that it is not practical in general to cast the controller partitioning problem as a direct controller approximation problem.

Garg, Sanjay↗

DOE OSTI2025

Characterizing leaf-scale fluorescence with spectral invariants

Sun-induced chlorophyll fluorescence (SIF) is increasingly recognized as a non-destructive probe for tracking terrestrial photosynthesis. Emerging developments in spectral invariants theory provide an innovative and efficient approach for representing SIF radiative transfer processes at the canopy scale. However, modeling leaf-scale fluorescence based on the spectral invariants properties (SIP) remains underexplored. In this study, the spectral invariants theory is employed for the first time to model the leaf-scale total, backward and forward fluorescence (leaf-SIP SIF). The leaf-SIP SIF model separates the leaf-scale radiative transfer process into two distinct components: the wavelength-dependent one associated with leaf biochemical properties, and the wavelength-independent component linked to leaf structural characteristics. The leaf structure-related effects are characterized by two spectrally invariant parameters: the photon recollision probability (p) and the scattering asymmetry parameter (q), which are parameterized using the directly measurable leaf dry matter. Evaluation against field measurements shows that the proposed leaf-SIP SIF model has a good performance, with coefficient of determination (R 2 ) of 0.89, 0.89, 0.90 and root mean squared errors (RMSE) of 1.28, 0.69, 0.74 Wm -2 µm -1 sr -1 , respectively for the total, backward, and forward fluorescence (660–800 nm). The leaf-SIP SIF model with a more concise formulation demonstrates comparable performance with the widely used Fluspect model. Further, the leaf-SIP SIF model provides a simple and efficient approach for simulating leaf-scale fluorescence, with the potential to be integrated into a unified SIP-based model framework for simulating the radiative transfer processes across the soil-leaf-canopy-atmosphere continuum.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

First-principles thermodynamic assessment of Sr-containing secondary phase formation in strontium-substituted lanthanum manganites for solid oxide cell applications

Sr-secondary phase formation is a potentially significant degradation mode with direct impact upon solid-oxide cell (SOC) commercial viability. A first-principles based thermodynamic study was performed for La 1−x Sr x MnO 3±δ (LSM) perovskites to assess their stability against formation of different Sr-secondary phases, including SrO, SrCrO 4 , SrSO 4 , SrCO 3 , and Sr(OH) 2 , for SOC applications. The Sr-secondary phase formation reaction free energies were determined via a thermodynamic model by combining ab initio lattice dynamics calculations for the solid phases and ab initio thermodynamic data for the gas phases. The current approach expands the previously reported thermodynamic modeling studies by integrating first-principles based point defect equilibria into the thermodynamic analysis. The modeling results obtained using this new approach indicate an increased tendency to form the SrO oxide upon decreasing the oxygen partial pressure. Additionally, the enhancing factors to form the Sr-related secondary phase from the associated SrO activity in LSM are further quantified by considering the equilibrium of SrO reacting with the contaminant gas species as a function of temperature and pressure.

defect thermodynamics modeling↗

DOE OSTI2024

Deep Learning-Based Failure Prognostic Model for PV Inverter Using Field Measurements

Here, this study presents a novel approach for the precise monitoring and prognosis of photovoltaic (PV) inverter status, which is crucial for the proactive maintenance of PV systems. It addresses the gaps in traditional model-based methods, which tend to neglect the overall reliability of inverters, and the limitations of data-driven approaches that largely depend on simulated data. This research presents a robust solution applicable to real-world scenarios. The proposed data-driven model for PV inverter failure prognosis employs actual inverter measurements, integrating various operational and weather-related factors based on domain knowledge. This approach effectively represents inverter stressors and operational status. Utilizing an Enhanced Siamese Convolutional Neural Network (ESCNN), the model merges operational data with domain knowledge features, redefining the prognosis challenge as a classification task. Furthermore, the paper discusses an ESCNN-based real-time inverter failure monitoring method developed on the well-trained model. The proposed models are rigorously trained and tested with real inverter data and a novel filtering method is included to address accidental failures in practical scenarios. The results validate the model's efficacy, and the directions for future research are also outlined.

42 ENGINEERING↗

DOE OSTI2022

Final Technical Report for "Cloud-based Low-Scaling Quantum Chemistry Simulations for Materials"

The objective of phase I was to develop the basic infrastructure for performing efficient hybrid DFT calculations on solid materials with a turnaround time amenable to the use in large-scale data-driven approaches. To fulfill the goal we have developed a novel algorithm that significantly reduces the cost of exchange matrix formation. The algorithm does so by making use of three ingredients (a) interpolative decomposition of the electron integrals (b) robust pseudospectral method and (c) occ-RI approach. Our published work demonstrates that the algorithm is orders of magnitude faster than any other hybrid-DFT method and is on the order of only 3-4 times slower than pure DFT. All steps of the algorithm developed during phase I can be accelerated to the point that, for large enough systems, the diagonalization of the Fock matrix will become the most expensive step. To treat such large systems we have created an interface to the ASCR-funded PEXSI library. The PEXSI method is used to compute the density matrix directly from the Fock matrix in a manner that preserves the sparsity of the local representation.

Shiozaki, Toru↗

DOE OSTI2026

Interactions between molecular-scale biogeochemical processes and hyporheic exchange for understanding coupled Fe-S-C cycling in iron-rich riparian wetlands (Final Technical Report)

Riparian wetlands are dynamic interfaces that exert strong control over water quality, contaminant mobility, and greenhouse gas emissions. These systems are characterized by hyporheic exchange between oxic surface water and anoxic groundwater, which generates steep redox gradients and promotes spatially and temporally variable microbial activity. Despite growing recognition of tightly coupled iron (Fe), sulfur (S), and carbon (C) cycling in these environments, the mechanisms governing these interactions—particularly under low-sulfate freshwater conditions—remain poorly constrained. This project developed a mechanistic understanding of how hydrologic variability and microbial processes interact to control Fe–S–C cycling in iron-rich riparian wetlands. Using a multi-scale and multi-method approach integrating field observations, geochemical and spectroscopic analyses, metagenomics, and reactive transport modeling, we demonstrate that “cryptic” sulfur cycling—rapid sulfur transformations involving intermediate-valence species—plays a dominant and previously underrecognized role in freshwater wetlands. These processes persist despite low sulfate concentrations and significantly influence iron reduction, carbon mineralization, and methane dynamics. The results show that cryptic sulfur cycling enhances dissolved Fe 2+ production, regulates methane concentrations, and is strongly controlled by climate-driven hydrologic fluxes. By linking hydroclimate, subsurface flow, and biogeochemical reactions, this work provides a predictive framework for understanding how wetland systems respond to environmental change, with direct implications for water quality and carbon cycling.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1997

On spurious behavior of CFD simulations

Spurious behavior in underresolved grids and/or semi-implicit temporal discretizations for four computational fluid dynamics (CFD) simulations are studied. The numerical simulations consist of (a) a 1-D chemically relaxed nonequilibrium model, (b) the direct numerical simulation (DNS) of 2-D incompressible flow over a backward facing step, (c) a loosely-coupled approach for a 2-D fluid-structure interaction, and (d) a 3-D compressible unsteady flow simulation of vortex breakdown in delta wings. Using knowledge from dynamical systems theory, various types of spurious behaviors that are numerical artifacts were systematically identified. These studies revealed the various possible dangers of misinterpreting numerical simulation of realistic complex flows that are constrained by the available computing power. In large scale computations underresolved grids, semi-implicit procedures, loosely-coupled implicit procedures, and insufficiently long time integration in DNS are most often unavoidable. Consequently, care must be taken in both computation and in interpretation of the numerical data. The results presented confirm the important role that dynamical systems theory can play in the understanding of the nonlinear behavior of numerical algorithms and in aiding the identification of the sources of numerical uncertainties in CFD.

Numerical Solution↗

NASA NTRS2000

Towards LES Models of Jets and Plumes

As pointed out by Rodi standard integral solutions for jets and plumes developed for discharge into infinite, quiescent ambient are difficult to extend to complex situations, particularly in the presence of boundaries such as the sea floor or ocean surface. In such cases the assumption of similarity breaks down and it is impossible to find a suitable entrainment coefficient. The models are also incapable of describing any but the most slowly varying unsteady motions. There is therefore a need for full time-dependent modeling of the flow field for which there are three main approaches: (1) Reynolds averaged numerical simulation (RANS), (2) large eddy simulation (LES), and (3) direct numerical simulation (DNS). Rodi applied RANS modeling to both jets and plumes with considerable success, the test being a match with experimental data for time-averaged velocity and temperature profiles as well as turbulent kinetic energy and rms axial turbulent velocity fluctuations. This model still relies on empirical constants, some eleven in the case of the buoyant jet, and so would not be applicable to a partly laminar plume, may have limited use in the presence of boundaries, and would also be unsuitable if one is after details of the unsteady component of the flow (the turbulent eddies). At the other end of the scale DNS modeling includes all motions down to the viscous scales. Boersma et al. have built such a model for the non-buoyant case which also compares well with measured data for mean and turbulent velocity components. The model demonstrates its versatility by application to a laminar flow case. As its name implies, DNS directly models the Navier-Stokes equations without recourse to subgrid modeling so for flows with a broad spectrum of motions (high Re) the cost can be prohibitive - the number of required grid points scaling with Re(exp 9/4) and the number of time steps with Re(exp 3/4). The middle road is provided by LES whereby the Navier-Stokes equations are formally filtered with the filter chosen to only exclude the smallest turbulent motions. If successful, LES should provide much of the detail available to DNS but at more bearable cost. Fatica et al. in comparing LES with DNS for a low Reynolds number jet showed that the LES could simulate the temporally evolving behavior including growth of the jet thickness. It is the intention of this report to explore the application of an LES model to jets and plumes. As always, before tackling complex situations, the model must be tested for the simplest of cases and so we address only two, a non-buoyant axisymmetric jet issuing steadily from an orifice into a semi-infinite stationary environment and a buoyant jet in the same environment. The work is a continuation of Basu and Mansour.

Webb, A. T.↗

NASA NTRS2019

Additive Manufacturing of Multi-Material Systems for Aerospace Applications

Additive manufacturing methods for producing single materials are rapidly improving. The resulting material properties and microstructures are becoming more comparable to those of conventionally fabricated materials. However, the need for multi-functional and complex structures and components requires additional innovations in manufacturing such as multi-material and hybrid additive manufacturing approaches. Additive manufacturing machines with multiple print capabilities and combinations of AM, machining, and conventional processing methods will further open up design spaces and possibilities. In this presentation, several examples of the needs and methods for multi-material fabrication will be discussed with a focus on aerospace applications. Direct printing of silver coils in conjunction with fused deposition modeling, machined parts, and, binder jetting is being developed for innovative stator designs. Binder jetting of silicon-based materials with powder bed additions is being developed for heat exchanger applications. Additive manufacturing of bi-material systems is being pursued to fabricate lightweight, integrated, multifunctional structures.

multi-materials↗

DOE OSTI2025

Information theory optimization of signals from small-angle scattering measurements

Small-angle X-ray scattering (SAXS) of particles in solution informs on the conformational states and assemblies of biological macromolecules (bioSAXS) outside of cryo- and solid-state conditions. In bioSAXS, the SAXS measurement under dilute conditions is resolution limited, and through an inverse Fourier transform, the measured SAXS intensities directly relate to the physical space occupied by the particles via the P (r)-distribution. Yet, this inverse transform of SAXS data has been historically cast as an ill-posed, ill-conditioned problem requiring an indirect approach. Here, we show that through the applications of matrix and information theories, the inverse transform of SAXS intensity data is a well-conditioned problem. The so-called ill-conditioning of the inverse problem is directly related to the Shannon number. By exploiting the oversampling enabled by modern detectors, a direct inverse Fourier transform of the SAXS data is possible, provided the recovered information does not exceed the Shannon number. The Shannon limit corresponds to the maximum number of significant singular values that can be recovered in a SAXS experiment, suggesting this relationship is a fundamental property of band-limited inverse integral transform problems. This correspondence reduces the complexity of the inverse problem to the Shannon limit and maximum dimension. We propose a hybrid scoring function using an information theory framework that assesses both the quality of the model-data fit as well as the quality of the recovered P (r)-distribution. The hybrid score utilizes the Akaike information criteria and Durbin-Watson statistic that considers parameter-model complexity, i.e., degrees of freedom, and the randomness of the model-data residuals. The described tests and findings extend the boundaries for bioSAXS by completing the information theory formalism initiated by Peter B. Moore to enable a quantitative measure of resolution in SAXS, robustly determine maximum dimension, and more precisely define the best parameter model appropriately representing the observed scattering data.

Rambo, Robert P. [Science and Technology Facilitie↗

NASA NTRS1991

A special purpose silicon compiler for designing supercomputing VLSI systems

Design of general/special purpose supercomputing VLSI systems for numeric algorithm execution involves tackling two important aspects, namely their computational and communication complexities. Development of software tools for designing such systems itself becomes complex. Hence a novel design methodology has to be developed. For designing such complex systems a special purpose silicon compiler is needed in which: the computational and communicational structures of different numeric algorithms should be taken into account to simplify the silicon compiler design, the approach is macrocell based, and the software tools at different levels (algorithm down to the VLSI circuit layout) should get integrated. In this paper a special purpose silicon (SPS) compiler based on PACUBE macrocell VLSI arrays for designing supercomputing VLSI systems is presented. It is shown that turn-around time and silicon real estate get reduced over the silicon compilers based on PLA's, SLA's, and gate arrays. The first two silicon compiler characteristics mentioned above enable the SPS compiler to perform systolic mapping (at the macrocell level) of algorithms whose computational structures are of GIPOP (generalized inner product outer product) form. Direct systolic mapping on PLA's, SLA's, and gate arrays is very difficult as they are micro-cell based. A novel GIPOP processor is under development using this special purpose silicon compiler.

Venkateswaran, N.↗

DOE OSTI2024

Uncertainty Quantification and Sensitivity Analysis of Non-Nuclear Advanced Controls Testbed Reactor Mockup

The research presented in this report describes our progress in applying stochastic methods and uncertainty quantification, parametric study, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated with Griffin, with the goal of developing a reduced order (surrogate) model which can be rapidly sampled while perturbing multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums, which are controlled by a hybrid proportional, integral and derivative (PID) controller, actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time and $\beta$ from a transient Griffin simulation executed with the improved quasi-static method to provide the kinetic parameters) as inputs to functions which control the CD rotation angle. Using a number of stochastic method approaches, we developed a dual purpose training-surrogate model of the NTP system using polynomial regression. The trained model can be rapidly sampled while simultaneously perturbing various input parameters of the model, such as coefficients on the PID control, or temperature (directly affect the neutron cross section). The surrogate model delivers accurate results orders-of-magnitude faster (minutes, not days) than the base model. Once the base model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs and their effect on the output. For example, coefficients used in the PID control system may vary due to some physical interference, or there may be uncertainty in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters and operational boundaries can be determined. The goal of this work is to support development of an advanced control system to operate CDs in a functioning NTP system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Enhanced ferroelectricity in ultrathin films grown directly on silicon

Ultrathin ferroelectric materials could potentially enable low-power logic and nonvolatile memories. As ferroelectric materials are made thinner, however, the ferroelectricity is usually suppressed. Size effects in ferroelectrics have been thoroughly investigated in perovskite oxides—the archetypal ferroelectric system. Perovskites, however, have so far proved unsuitable for thickness scaling and integration with modern semiconductor processes. In this paper we report ferroelectricity in ultrathin doped hafnium oxide (HfO 2 ), a fluorite-structure oxide grown by atomic layer deposition on silicon. We demonstrate the persistence of inversion symmetry breaking and spontaneous, switchable polarization down to a thickness of one nanometre. Our results indicate not only the absence of a ferroelectric critical thickness but also enhanced polar distortions as film thickness is reduced, unlike in perovskite ferroelectrics. This approach to enhancing ferroelectricity in ultrathin layers could provide a route towards polarization-driven memories and ferroelectric-based advanced transistors. This work shifts the search for the fundamental limits of ferroelectricity to simpler transition-metal oxide systems—that is, from perovskite-derived complex oxides to fluorite-structure binary oxides—in which ‘reverse’ size effects counterintuitively stabilize polar symmetry in the ultrathin regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗