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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Hierarchical Particle Mesh: An FFT-accelerated Fast Multipole Method

I observe a modification to the original Fast Multipole Method (FMM) of Greengard & Rokhlin that approximates the gravitation field of an FMM cell as a small uniform grid (a “gridlet”) of effective masses. The effective masses on a gridlet are set from the requirement that the multipole moments of the FMM cells are reproduced exactly, thus preserving the accuracy of the gravitational field representation. The measurement of the gravitational field from a multipole expansion can then be computed for all multipole orders simultaneously, with a single Fast Fourier Transform, significantly reducing the computational cost at a given value of the required accuracy. The described approach belongs to the class of “kernel independent” variants of the FMM method and works with any Green function.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

MTS-VAE

This repository accompanies the work "Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder". It includes the datasets for model training, validation, and downstream analysis.

Mitochondria↗
DOE OSTI2017

Tracking Aging in Nuclear Electrical Cable Polymers

The electrical cable network is the nerve center of a nuclear plant, providing power, instrumentation and control of critical systems during operation, planned outage, and during design basis, unplanned outage events. It is therefore important to manage cable system health through awareness of local environments adverse to cable longevity, monitoring of cable condition, and predictive understanding of cable degradation [1-3]. Nondestructive methods can be used to assess the condition of the full length of installed cables and of localized cable regions to support cable repair and replacement planning decisions [4-5]. Informed knowledge of the effects of environment on cable performance over time combined with cable state assessment data can minimize costs associated with cable management by both avoiding outages and ramifications from unexpected cable failure and by avoiding premature replacement of functional cables. In this work, the aging behavior of commonly found nuclear cable insulation and jacketing materials is investigated along with established and emerging methods for locating and quantifying cable degradation. Ethylene-propylene rubber (EPR) and chlorinated polyethylene (CPE), examples of prevalent insulation and jacket materials used in nuclear power plants (NPPs), are thermally aged at elevated temperature to induced material changes similar to those experienced by cable material under long term service conditions. Destructive and nondestructive laboratory tests are used to follow changes in the materials with aging toward establishing predictive capabilities to help extend the life of installed nuclear cables and reduce cable management operational costs.

Cable aging, EPR, CPE, NDE, nuclear↗
DOE OSTI2025

LDRD conclusion poster - Synthesizing Heterometallic Uranium Single Crystals to Understand the Influence of the Secondary Metals on Uranyl Axial Bond Strength

Understanding how transition metals influenced the chemistry of lanthanide and actinide (f-element) materials is critical for advancing separation technologies, materials design, and coordination chemistry. This project examined how incorporating first-row transition metals affected the structural and spectroscopic properties of f-element coordination polymers. In uranium(VI)-based systems synthesized with 2,6-pyridinedicarboxylic acid (PDC) ligands, single-crystal X-ray diffraction and Raman spectroscopy revealed that the presence of transition metals shortened the uranyl axial bond and induced a blue shift in its symmetric stretching vibration—evidence of increased bond strength. Electronic structure analysis, including Density of States (DOS) calculations using density functional theory (DFT), revealed altered orbital overlaps and highlighted the role of transition metal d-orbitals in modulating bonding. Raman modes were modeled using truncated structural fragments in collaboration with the University of Notre Dame, and although the predicted frequencies were lower than experimental values, they remained within expected ranges. In parallel, similar experiments with cerium (Ce) in the presence of cobalt (Co) and PDC demonstrated multi-step single-crystal-to-single-crystal transformations—behavior not observed in the uranium systems. Initial products included light yellow, orange, and polycrystalline materials. Single-crystal X-ray diffraction studies, conducted in collaboration with the Colorado School of Mines, identified the yellow phase as monometallic Ce(PDC)2(H2O)2·4H2O and the orange phase as heterometallic Ce2Co(PDC)4(H2O)6. After standing in solution for one week, both phases fully transformed into a dark yellow crystalline phase, [Ce3(PDC)5(H2O)8].6(H2O). Remarkably, this transformation was reversible—disturbing the equilibrium by removing some crystals caused reversion to the initial Ce(PDC)2(H2O)2·4H2O phase, highlighting dynamic behavior. All three structures were previously unreported. Solid-state UV-visible and Raman spectroscopy further distinguished these phases, revealing ligand-to-metal charge transfer involving Ce and characteristic d–d transitions from Co(II). The precise mechanism driving these transformations remained unclear; however, pH-dependent experiments confirmed that the transformation did not occur when the pH decreased. Overall, the project demonstrated that transition metals could be employed to tune bonding interactions, structural dimensionality, and optical properties in f-element materials, establishing new pathways for designing functional heterometallic systems. The work resulted in several novel structural discoveries and fostered productive collaborations with the University of Notre Dame and the Colorado School of Mines.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2018

Ion selectivity in capacitive deionization with functionalized electrode: Theory and experimental validation

Capacitive deionization (CDI) is a promising technique for salt removal and may have potential for highly selective removal of ion species. In this work, we take advantage of functional groups usually used with ionic exchange resins and apply these to CDI. To this end, we functionalize activated carbon with a quaternary amines surfactant and use this surface to selectively and passively (no applied field) trap nitrate ions. We then set the cell voltage to a constant value to regenerate these electrodes, resulting in an inverted capacitive deionization (i-CDI) operation. Unlike resins, we avoid use of concentrated chemicals for regeneration. We measure the selectivity of nitrate versus chloride ions as a function of regeneration voltage and initial chloride concentration. We experimentally demonstrate up to about 6.5-fold (observable) selectivity in a cycle with a regeneration voltage of 0.4 V. We also demonstrate a novel multi-pass, air-flush i-CDI operation to selectively enrich nitrate with high water recovery. We further present a dynamic, multi-species electrosorption and equilibrium solution-to-surface chemical reaction model and validate the model with detailed measurements. Our i-CDI system exhibits higher nitrate selectivity at lower voltages; making it possible to reduce NaNO 3 concentrations from ~170 ppm to below the limit of maximum allowed values for nitrate in drinking water of about 50 ppm NaNO 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Analysis of heavy-ion fusion reactions using new parameterized form of the universal function of nuclear proximity potential

In the present work, we modify the original version of this formalism (Prox. 77) using a new analytical form of the universal function which is formulated based on the double-folding model with three density-dependent versions of the M3Y-type interactions, namely DDM3Y1, CDM3Y3 and BDM3Y1, for 46 fusion systems with condition 48≤Z{sub 1}Z{sub 2}≤2460 for charge product of their participant nuclei. It is found that when the Prox. 77 potential is accompanied by each of the formulated universal functions, the agreement between the theoretical and experimental data of the fusion barrier heights increase for our selected systems. The obtained results of this study reveal that the saturation property of cold nuclear matter plays a key role in the calculations of the fusion cross sections. We conclude that the Prox. 77 model with universal function based on the BDM3Y1 interactions provides the best results for fusion barrier heights and cross sections. On the basis of the prox. 77(BDM3Y1) potential model, we present the parameterized formulas for fusion barrier heights V{sub B} and positions R{sub B}. These formulas can calculate the values of R{sub B} andV{sub B} with good accuracy in comparison with the experimental data. A comparison is also presented among the theoretical results of the present work and those obtained by the modified form of the original version of proximity approach through the universal function and surface energy coefficients available in the literature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Multidimensional Analogs of the Cauchy–Riemann System and Representations of Their Solutions via Harmonic Functions

At present, there are numerous multidimensional generalizations of holomorphic vectors. The most general of these is the four-dimensional generalization of the Cauchy–Riemann system. In the present work, by introducing two quaternion functions and the notion of quaternion differentiation, we obtain, for the first time, a five-dimensional generalization of holomorphic vectors. By using the representation of holomorphic vectors via the quaternion harmonic function and its derivatives, we consider the Riemann–Hilbert problem and one problem in a layer. A new solution of the Riemann–Hilbert problem in the five-dimensional half space is obtained.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Robust Parameter Design on Dual Stochastic Response Models With Constrained Bayesian Optimization

In engineering system design, minimizing the variations of the quality measurements while guaranteeing their overall quality up to certain levels, namely the robust parameter design (RPD), is crucial. Recent works have dealt with the design of a system whose response-control variables relationship is a deterministic function with a complex shape and function evaluation is expensive. In this work, we propose a Bayesian optimization method for the RPD of stochastic functions. Dual stochastic response models are carefully designed for stochastic functions. The heterogeneous variance of the sample mean is addressed by the predictive mean of the log variance surrogate model in a two-step approach. We establish an acquisition function that favors exploration across the feasible and optimality-improvable regions to effectively and efficiently solve the stochastic constrained optimization problem. Further, the performance of our proposed method is demonstrated by the extensive numerical and case studies. Note to Practitioners-Many manufacturing processes involve undesirable variations, which create variations in the final products. For example, many emerging manufacturing processes, such as nanomanufacturing, involve complex physical and chemical dynamics and transformation, creating variations in the manufacturing output. In such processes, it is crucial to design the manufacturing processes or products so that they have minimum variations in their quality. Meanwhile, it is also important to maintain the overall quality of the designed processes or products. Furthermore, acquiring data from many advanced manufacturing processes is often very costly, especially in the designing stage. In this work, we propose a data-driven method that automatically finds the best setting of manufacturing processes or products with the minimum variations of quality and a given constraint on the average quality satisfied. Our proposed method is used before conducting every experiment; It analyzes the historical data from previous experiments and provides a setting to be used in the next experiment. Our proposed method efficiently utilizes the historical data, and thus finds the best robust setting by conducting only a small number of experiments.

42 ENGINEERING↗
DOE OSTI2017

Temperature Sensitivity Study of Eddy Current and Digital Gauge Probes for Nuclear Fuel Rod Oxide Measurement

Temperature Sensitivity Study of Eddy Current and Digital Gauge Probes for Nuclear Fuel Rod Oxide Measurement Faith R. Beck, Department of Mechanical Engineering, Penn State University, State College, PA R. Paul Lind and James A. Smith, Idaho National Laboratory, Idaho Falls, ID Novel fuels are part of the nationwide effort to reduce the enrichment of Uranium for energy production. Performance of such fuels is determined by irradiating their surfaces. To test irradiated samples, the machinery must operate remotely. The plate checker used in this experiment at Idaho National Lab (INL) performs non-destructive testing on fuel rod and plate geometries with two different types of sensors: eddy current and digital thickness gauges. The sensors measure oxide growth and total sample thickness on research fuels, respectively. Sensor measurement accuracy is crucial because even 10 microns of error is significant when determining the viability of an experimental fuel. One parameter known to affect the eddy current and thickness gauge sensors is temperature. Since both sensor accuracies depend on the ambient temperature of the system, the plate checker has been characterized for these sensitivities. The eddy current probes were tested previously in a non-radioactive environment and are noted to have sensitivity to temperature. The manufacturer of the digital gauge probes has noted a rather large coefficient of thermal expansion for their linear scale. It should also be noted that the accuracy of the digital gauge probes are specified at 20°C, which is approximately 7°C cooler than the average hot-cell temperature. In this work, the effect of temperature on the eddy current and digital gauge probes is studied, and thickness measurements are given as empirical functions of temperature. Acknowledgement: This work was supported by the INL and the DOE office of NNSA (National Nuclear Safety Administration).

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Predictive Power of Exact Constraints and Appropriate Norms in Density Functional Theory

Ground-state Kohn-Sham density functional theory provides, in principle, the exact ground-state energy and electronic spin densities of real interacting electrons in a static external potential. In practice, the exact density functional for the exchange-correlation (xc) energy must be approximated in a computationally efficient way. About 20 mathematical properties of the exact xc functional are known. In this work, we review and discuss these known constraints on the xc energy and hole. By analyzing a sequence of increasingly sophisticated density functional approximations (DFAs), we argue that (a) the satisfaction of more exact constraints and appropriate norms makes a functional more predictive over the immense space of many-electron systems and (b) fitting to bonded systems yields an interpolative DFA that may not extrapolate well to systems unlike those in the fitting set. We discuss both how the class of well-described systems has grown along with constraint satisfaction and the possibilities for future functional development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Bridging the Homogeneous-Heterogeneous Divide: Modeling Spin for Reactivity in Single Atom Catalysis

Single atom catalysts (SACs) are emergent catalytic materials that have the promise of merging the scalability of heterogeneous catalysts with the high activity and atom economy of homogeneous catalysts. Computational, first-principles modeling can provide essential insight into SAC mechanism and active site configuration, where the sub-nm-scale environment can challenge even the highest-resolution experimental spectroscopic techniques. Nevertheless, the very properties that make SACs attractive in catalysis, such as localized d electrons of the isolated transition metal center, make them challenging to study with conventional computational modeling using density functional theory (DFT). For example, Fe/N-doped graphitic SACs have exhibited spin-state dependent reactivity that remains poorly understood. However, spin-state ordering in DFT is very sensitive to the nature of the functional approximation chosen. In this work, we develop accurate benchmarks from correlated wavefunction theory (WFT) for relevant octahedral complexes. We use those benchmarks to evaluate optimal DFT functional choice for predicting spin state ordering in small octahedral complexes as well as models of pyridinic and pyrrolic nitrogen environments expected in larger SACs. Using these guidelines, we determine Fe/N-doped graphene SAC model properties and reactivity as well as their sensitivities to DFT functional choice. Finally, we conclude with broad recommendations for computational modeling of open-shell transition metal single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Density Functionals for Hydrogen Storage: Defining the H2Bind275 Test Set with Ab Initio Benchmarks and Assessment of 55 Functionals

Efficient and high-capacity storage materials are indispensable for a hydrogen-based economy. In silico tools can accelerate the process of discovery of new adsorbent materials with optimal hydrogen adsorption enthalpies. Density functional theory is well-poised to become a very useful tool for enabling high-throughput screening of potential materials. In this work, we have identified density functional approximations that provide good performance for hydrogen binding applications following a two-pronged approach. First, we have compiled a data set (H2Bind275) that comprehensively represents the hydrogen binding problem capturing the chemical and mechanistic diversity in the binding sites encountered in hydrogen storage materials. We have also computed reference interaction energies for this data set using coupled-cluster theory. Second, we have assessed the performance of 55 density functional approximations for predicting H 2 interaction energies and have identified two hybrid density functionals (ωB97X-V and ωB97M-V), two double hybrid density functionals (DSD-PBEPBE-D3(BJ) and PBE0-DH), and one semilocal density functional (B97M-V) as the best performing ones. We have recommended the addition of empirical dispersion corrections to systematically underbinding density functionals such as revPBE, BLYP, and B3LYP for improvements in performance at negligible additional cost. We have also recommended the usage of the def2-TZVPP basis set as it represents a good compromise between accuracy and cost, limiting the finite basis set errors to less than 1 kJ/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A de novo matrix for macroscopic living materials from bacteria

Engineered living materials (ELMs) embed living cells in a biopolymer matrix to create materials with tailored functions. While bottom-up assembly of macroscopic ELMs with a de novo matrix would offer the greatest control over material properties, we lack the ability to genetically encode a protein matrix that leads to collective self-organization. Here we report growth of ELMs from Caulobacter crescentus cells that display and secrete a self-interacting protein. This protein formed a de novo matrix and assembled cells into centimeter-scale ELMs. Discovery of design and assembly principles allowed us to tune the composition, mechanical properties, and catalytic function of these ELMs. This work provides genetic tools, design and assembly rules, and a platform for growing ELMs with control over both matrix and cellular structure and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A comparative study of calibration techniques for finite strain elastoplasticity: Numerically-exact sensitivities for FEMU and VFM

Accurate identification of material parameters is crucial for predictive modeling in computational mechanics. Here, the two primary approaches in the experimental mechanics community for calibration from full-field digital image correlation data are known as finite element model updating (FEMU) and the virtual fields method (VFM). In VFM, the objective function is a squared mismatch between internal and external virtual work or power. In FEMU, the objective function quantifies the weighted mismatch between model predictions and corresponding experimentally measured quantities of interest. It is minimized by iteratively updating the parameters of an FE model. While FEMU is seen as more flexible, VFM is commonly used instead of FEMU due to its considerably greater computational expense. However, comparisons between the two methods usually involve approximations of gradients or sensitivities with finite difference schemes, thereby making direct assessments difficult. Hence, in this study, we compare VFM and FEMU in the context of numerically-exact sensitivities obtained through local sensitivity analyses and the application of automatic differentiation software. To this end, we conduct a series of test cases to assess both methods under practical challenges using a finite strain elastoplasticity model.

Automatic differentiation↗
DOE OSTI2023

Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons

Neural networks (NNs) are currently changing the computational paradigm on how to combine data with mathematical laws in physics and engineering in a profound way, tackling challenging inverse and ill-posed problems not solvable with traditional methods. However, quantifying errors and uncertainties in NN-based inference is more complicated than in traditional methods. This is because in addition to aleatoric uncertainty associated with noisy data, there is also uncertainty due to limited data, but also due to NN hyperparameters, overparametrization, optimization and sampling errors as well as model misspecification. Although there are some recent works on uncertainty quantification (UQ) in NNs, there is no systematic investigation of suitable methods towards quantifying the total uncertainty effectively and efficiently even for function approximation, and there is even less work on solving partial differential equations and learning operator mappings between infinite-dimensional function spaces using NNs. In this work, we present a comprehensive framework that includes uncertainty modeling, new and existing solution methods, as well as evaluation metrics and post-hoc improvement approaches. Further, to demonstrate the applicability and reliability of our framework, we present an extensive comparative study in which various methods are tested on prototype problems, including problems with mixed input-output data, and stochastic problems in high dimensions. In the Appendix, we include a comprehensive description of all the UQ methods employed. Further, to help facilitate the deployment of UQ in Scientific Machine Learning research and practice, we present and develop in [1] an open-source Python library (github.com/Crunch-UQ4MI/neuraluq), termed NeuralUQ, that is accompanied by an educational tutorial and additional computational experiments.

11 physics-informed neural networks↗
DOE OSTI2020

Hydrogen Bonding Optimizes Singlet Fission in Carboxylic Acid Functionalized Anthradithiophene Films

The rate of singlet fission, the process of generating two triplet excitons with photoexcitation of one singlet exciton, depends on a combination of singlet/triplet energy balance and intermolecular coupling. In this work, we perform carboxylic acid functionalization of anthradithiophene (ADT) derivatives that result in hydrogen bonds that drive molecular orientation and strong electronic coupling of polycrystalline ADT thin films, leading to ultrafast singlet fission without significant enthalpic driving force. ADT with a single carboxylic acid group exhibits weak intermolecular coupling and slow and inefficient singlet fission, much like the parent ADT, and substitution of different alkylsilyl solubilizing groups has little effect. However, the addition of two carboxylic acid groups on either end of the long axis favors significant coupling and crystallinity in as-deposited thin films that increase the effective singlet fission rate by roughly three orders of magnitude. The properties of the triplet pair, particularly its propensity to form long-lived independent triplets, are also influenced by the degree of long-range intermolecular coupling. The enhancement of intermolecular coupling specific to singlet fission using the ubiquitous cyclic hydrogen bonding motif could impact triplet pair utilization schemes in a variety of contexts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Anion Exchange Ionomers: Impact of Chemistry on Thin-Film Properties

Ionomer thin-films (i.e., 20–100 nm) on supports serve as model systems to understand ionomer-catalyst interfacial behavior as well as the confinement-driven deviation in properties from bulk membranes. While ionomer thin-films have been examined for proton exchange ionomers, the thin-film properties of anion exchange ionomers (AEIs) remain largely unexplored. More importantly, delineating the convoluted impact of chemistry and confinement on thin-film morphology and hydration is of interest to advancing the field on functional ionic interfaces. In this work, these aspects are studied by using AEIs of different backbones (perfluorinated, aliphatic, and aromatic) and side chains (various lengths, and single versus dual functional groups). Quartz-crystal microbalance and spectroscopic ellipsometry are used to analyze density and coupled with calculated free volume fraction of thin-films to provide insights on their gas transport properties. AEI side-chain's chemical character plays a key role in how confinement modulates hydration (in thin-film versus bulk). Overall, the results elucidate the effects of backbone, side-chain chemistry versus anion/cation type in the confinement-driven changes in thin-film morphology and swelling. This study also provides new insights for tuning AEI transport functionalities at interfaces via chemistry, which can benefit the design and development of electrode-ionomers for alkaline membrane-based energy systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The boundary entropy function for interface conformal field theories

In 1+1 dimensional conformal field theory with a boundary the boundary contribution to the entanglement entropy is determined by a single number g effectively counting the boundary degrees of freedom. In contrast, in 1+1 dimensional interface CFTs the corresponding quantity is a non-trivial function depending on the position of the interval relative to the interface, giving access to much more detailed information about the defect. In this work we determined this g -function in several examples using holography and derive some of its basic properties from holography and strong subadditivity.

AdS-CFT correspondence↗