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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Exploring Architectural-Aware Affinity Policies in Modern HPC Runtimes

Modern commodity and High-Performance Computing (HPC) systems are evolving with complex CPU architectures. These architectures now feature higher core and NUMA domain counts and implement features such as hyperthreading. When considering significant differences in hardware configurations, library availability, and hardware-tailored system/software stacks, which could substantially vary from one system to another, performance portability is hard to achieve. Throughout the years, this trend resulted in an increasingly high burden on application developers to fine-tune their workloads for each architecture. This work explores how hardware-dependent aspects such as locality/process/thread affinity affect performance in modern CPU architectures. We focus our study on the Global Memory and Threading (GMT) distributed runtime system as a representative of Partitioned Global Address Space (PGAS) software stacks commonly adopted for productivity. In particular, to appreciate performance implications, we evaluate GMT’s thread affinity policies, and, introduce two new ones which exploit architectural awareness. Finally, we explore alternative NUMA configurations via different process bindings and perform a scalability study on three HPC clusters with varying CPU architectures and NUMA layouts. Our analysis indicates that more complex architectures are more affected by affinity and binding policies and highlights the importance of setting proper runtime configurations to achieve superior performance.

Di Dio Lavore, Ian↗
DOE OSTI2016

A computationally identified compound antagonizes excess FGF-23 signaling in renal tubules and a mouse model of hypophosphatemia

Fibroblast growth factor–23 (FGF-23) interacts with a binary receptor complex composed of α-Klotho (α-KL) and FGF receptors (FGFRs) to regulate phosphate and vitamin D metabolism in the kidney. Excess FGF-23 production, which causes hypophosphatemia, is genetically inherited or occurs with chronic kidney disease. Among other symptoms, hypophosphatemia causes vitamin D deficiency and the bone-softening disorder rickets. Current therapeutics that target the receptor complex have limited utility clinically. In this paper, using a computationally driven, structure-based, ensemble docking and virtual high-throughput screening approach, we identified four novel compounds predicted to selectively inhibit FGF-23–induced activation of the FGFR/α-KL complex. Additional modeling and functional analysis found that Zinc13407541 bound to FGF-23 and disrupted its interaction with the FGFR1/α-KL complex; experiments in a heterologous cell expression system showed that Zinc13407541 selectivity inhibited α-KL–dependent FGF-23 signaling. Zinc13407541 also inhibited FGF-23 signaling in isolated renal tubules ex vivo and partially reversed the hypophosphatemic effects of excess FGF-23 in a mouse model. Finally, these chemical probes provide a platform to develop lead compounds to treat disorders caused by excess FGF-23.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Pyomo v5.0

Pyomo supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. Although most AMLs are implemented in custom modeling languages, Pyomo's modeling objects are embedded within Python, a full- featured high-level programming language that contains a rich set of supporting libraries.

Woodruff, David↗
DOE OSTI2019

PAO

PAO supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. PAO is derived from the Pyomo subpackage pyomo.bilevel, which has been deprecated. PAO supports the formulation and solution of optimization models that explicitly represent adversarial behavior. This includes variances of bilevel programming, including methods that represent challenging problems with discrete decisions and uncertain model parameters.

Hart, William↗
DOE OSTI2015

Pyomo

Pyomo supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. Although most AMLs are implemented in custom modeling languages, Pyomo's modeling objects are embedded within Python, a full-featured high-level programming language that contains a rich set of supporting libraries.

Source record↗
DOE OSTI2019

Enhancing Network Visibility and Security through Tensor Analysis

The increasing size, variety, rate of growth and change, and complexity of network data has warranted advanced network analysis and services. Tools that provide automated analysis through traditional or advanced signature-based systems or machine learning classifiers suffer from practical difficulties. These tools fail to provide comprehensive and contextual insights into the network when put to practical use in operational cyber security. In this paper, we present an effective tool for network security and traffic analysis that uses high-performance data analytics based on a class of unsupervised learning algorithms called tensor decompositions. The tool aims to provide a scalable analysis of the network traffic data and also reduce the cognitive load of network analysts and be network-expert-friendly by presenting clear and actionable insights into the network. With this being said, In this paper, we demonstrate the successful use of the tool in two completely diverse operational cyber security environments, namely, (1) security operations center (SOC) for the SCinet network at the SuperComputing (SC) Conference in 2016 and 2017 and (2) Reservoir Labs’ Local Area Network (LAN). In each of these environments, we produce actionable results for cyber security specialists including (but not limited to) (1) finding malicious network traffic involving internal and external attackers using port scans, SSH brute forcing, and NTP amplification attacks, (2) uncovering obfuscated network threats such as data exfiltration using DNS port and using ICMP traffic, and (3) finding network misconfiguration and performance degradation patterns.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Ammonia Oxidation by Abstraction of Three Hydrogen Atoms from a Mo–NH 3 Complex

We report ammonia oxidation by homolytic cleavage of all three H atoms from a Mo৶ 15 NH 3 complex using the 2,4,6-tri-tert-butylphenoxyl radical to afford a Mo-alkylimido (Mo৶ 15 NR) complex (R = 2,4,6-tri-t-butylcyclohexa-2,5-dien-1-one). Reductive cleavage of Mo৶15NR generates a terminal Mo৶N nitride, and a [Mo৶ 15 NH] + complex is formed by protonation. Computational analysis describes the energetic profile for the stepwise removal of three H atoms from the Mo৶ 15 NH 3 complex and the formation of Mo৶ 15 NR. Acknowledgment. This work was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Re-search Center funded by the U.S. Department of Energy (U.S. DOE), Office of Science, Office of Basic Energy Sciences. EPR and mass spectrometry experiments were performed using EMSL, a national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located at PNNL. The authors thank Dr. Eric D. Walter and Dr. Rosalie Chu for assistance in performing EPR and mass spectroscopy analysis, respectively. Computational resources provided by the National Energy Re-search Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. Pacific North-west National Laboratory is operated by Battelle for the U.S. DOE.

Molybdenum, ammonia, phosphines, pendant amines, h↗
DOE OSTI2020

Stochastic nonlinear analysis of unidirectional fiber composites using image-based microstructural uncertainty quantification

Here, we present a data-driven nonlinear uncertainty quantification and propagation framework to study the microstructure-induced stochastic performance of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The proposed approach integrates (1) microscopic image characterization, (2) stochastic microstructure reconstruction, and (3) efficient multiscale finite element simulations enabled by self-consistent clustering (SCA) analysis. To model the complex microstructural variability, the proposed UQ methods take the non-Gaussian uncertainty sources into account through a distribution-free sampling approach leveraging nonparametric and asymptotic statistical tools. A hierarchical conditional sampling strategy enables the simultaneous sampling of multiple sources of uncertainties. Our approach provides insights into the impact of microstructural variabilities, which are shown to have an increasing impact on the nonlinear responses of UD CFRP parts under progressive compression loading and ultimately on the failure rate over time. We discover that before CFRP parts start to fail, a characteristic time period emerges with distinctive uncertainty distributions specific to the microstructure variability and the probability of failure. Identifying the failure time period is crucial to the reliability prediction, which is an essential component of CFRP design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Towards a Robust Adaptive Digital Twin for Fusion Applications

The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.

Sammuli, Brian [General Atomics]↗
DOE OSTI2018

Stimulated x-ray emission spectroscopy in transition metal complexes

Here, we report the observation and analysis of the gain curve of amplified Kα X-ray emission from solutions of Mn(II) and Mn(VII) complexes using an X-ray free electron laser to create the 1s core-hole population inversion. We find spectra at amplification levels extending over four orders of magnitude until saturation. We observe bandwidths below the Mn 1s core-hole lifetime broadening in the onset of the stimulated emission. In the exponential amplification regime the resolution corrected spectral width of ~1.7 eV FWHM is constant over three orders of magnitude, pointing to the build-up of transform limited pulses of ~1 fs duration. Driving the amplification into saturation leads to broadening and shift of the line. Importantly, the chemical sensitivity of the stimulated X-ray emission to the Mn oxidation state is preserved at power densities of ~10 20 ~W/cm 2 for the incoming X-ray pulses. Differences in signal sensitivity and spectral information compared to conventional (spontaneous) X-ray emission spectroscopy are discussed. Our findings build a baseline for nonlinear X-ray spectroscopy for a wide range of transition metal complexes in inorganic chemistry, catalysis and materials science.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

ISAP-MATLAB Package for Sensitivity Analysis of High-Dimensional Stochastic Chemical Networks

Stochastic simulation and modeling play an important role to elucidate the fundamental mechanisms in complex biochemical networks. The parametric sensitivity analysis of reaction networks becomes a powerful mathematical and computational tool, yielding information regarding the robustness and the identifiability of model parameters. However, due to overwhelming computational cost, parametric sensitivity analysis is a extremely challenging problem for stochastic models with a high-dimensional parameter space and for which existing approaches are very slow. Here we present an information-theoretic sensitivity analysis in path-space (ISAP) MATLAB package that simulates stochastic processes with various algorithms and most importantly implements a gradient-free approach to quantify the parameter sensitivities of stochastic chemical reaction network dynamics using the pathwise Fisher information matrix (PFIM; Pantazis, Katsoulakis, and Vlachos 2013). The sparse, block-diagonal structure of the PFIM makes its computational complexity scale linearly with the number of model parameters. As a result of the gradientfree and the sparse nature of the PFIM, it is highly suitable for the sensitivity analysis of stochastic reaction networks with a very large number of model parameters, which are typical in the modeling and simulation of complex biochemical phenomena. Finally, the PFIM provides a fast sensitivity screening method (Arampatzis, Katsoulakis, and Pantazis 2015) which allows it to be combined with any existing sensitivity analysis software.

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

In-Plane Thorium(IV), Uranium(IV), and Neptunium(IV) Expanded Porphyrin Complexes

In our research, we report a first series of in-plane thorium(IV), uranium(IV), and neptunium(IV) expanded porphyrin complexes. These actinide (An) complexes were synthesized using a hexa-aza porphyrin analogue, termed dipyriamethyrin, and the non-aqueous An(IV) precur-sors: ThCl 4 (DME) 2 , UCl 4 , and NpCl 4 (DME) 2 under conditions of in situ sodium bis(trimethylsilyl)amide deprotonation. The molecu-lar and electronic structure of the ligand, each An(IV) complex, and a corresponding uranyl(VI) complex were characterized using NMR and UV-vis spectroscopies, as well as single crystal X-ray diffraction analysis. Computational analyses of these complexes, coupled with their structural features, provide support for the conclusion that a greater degree of covalency in the ligand-cation orbital interactions arises as the early actinide series is traversed from Th(IV) to U(IV) and Np(IV). The axial ligands in the current An(IV) complexes proved labile, allowing for the electronic features of these complexes to be further modified.

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

Dicopper( i ) complexes of a binucleating, dianionic, naphthyridine bis(amide) ligand

The dinucleating ligand, 1,8-naphthyridine-2,7-bis(2,6-diisopropylphenyl)carboxamide (NBDA), was synthesized by palladium-catalyzed aminocarbonylation. This ligand was treated with two equivalents of mesitylcopper(I) in the presence of [nBu4N]X (X = Cl, N3) to give the anionic complexes [nBu4N][Cu2(NBDA)(μ-Cl)] and [nBu4N][Cu2(NBDA)(μ-N3)]. Treatment of H2NBDA with mesitylcopper(I) and two equivalents of xylyl isocyanide led to the formation of a charge-neutral dicopper(I) complex, [Cu2(NBDA)(CNXyl)2], displaying two isocyanide ligands, each terminally bound to one of the copper atoms. The complexes were characterized by NMR and IR spectroscopy, as well as by single-crystal X-ray diffraction analysis. Electrochemical characterization of the complexes using cyclic voltammetry revealed a reversible ligand-based reduction between -1.65 and -2.0 V vs. Fc/Fc+. DFT calculations suggest a more ionic bonding character and weaker Cu-Cu interactions in the NBDA complexes compared to those with other 1,8-naphthyridine-based ligands. This is congruent with intermetallic separations of over 3 Å induced by relatively strong coordination of the copper atoms to the amide nitrogen donor atoms observed in the solid state molecular structures.

Sévery, Laurent↗
DOE OSTI2022

A Simulation-based Method for Correcting Mode Coupling in CMB Angular Power Spectra

Modern cosmic microwave background (CMB) analysis pipelines regularly employ complex time-domain filters, beam models, masking, and other techniques during the production of sky maps and their corresponding angular power spectra. However, these processes can generate couplings between multipoles from the same spectrum and from different spectra, in addition to the typical power attenuation. Within the context of pseudo-C ℓ based, MASTER-style analyses, the net effect of the time-domain filtering is commonly approximated by a multiplicative transfer function, F ℓ , that can fail to capture mode mixing and is dependent on the spectrum of the signal. To address these shortcomings, we have developed a simulation-based spectral correction approach that constructs a two-dimensional transfer matrix, ${J}_{{\ell }{\ell }^{\prime} }$, which contains information about mode mixing in addition to mode attenuation. We demonstrate the application of this approach on data from the first flight of the Spider balloon-borne CMB experiment.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Revisiting the Bonding Model for Gold(I) Species: The Importance of Pauli Repulsion Revealed in a Gold(I)‐Cyclobutadiene Complex

Abstract Understanding the bonding of gold(I) species has been central to the development of gold(I) catalysis. Herein, we present the synthesis and characterization of the first gold(I)‐cyclobutadiene complex, accompanied with bonding analysis by state‐of‐the‐art energy decomposition analysis methods. Analysis of possible coordination modes for the new species not only confirms established characteristics of gold(I) bonding, but also suggests that Pauli repulsion is a key yet hitherto overlooked element. Additionally, we obtain a new perspective on gold(I)‐bonding by comparison of the gold(I)‐cyclobutadiene to congeners stabilized by p‐, d‐, and f‐block metals. Consequently, we refine the gold(I) bonding model, with a delicate interplay of Pauli repulsion and charge transfer as the key driving force for various coordination motifs. Pauli repulsion is similarly determined as a significant interaction in Au I ‐alkyne species, corroborating this revised understanding of Au I bonding.

Wong, Zeng Rong↗
DOE OSTI2022

Revisiting the Bonding Model for Gold(I) Species: The Importance of Pauli Repulsion Revealed in a Gold(I)–Cyclobutadiene Complex

Understanding the bonding of gold(I) species has been central to the development of gold(I) catalysis. Herein, we present the synthesis and characterization of the first gold(I)-cyclobutadiene complex, accompanied with bonding analysis by state-of-the-art energy decomposition analysis methods. Analysis of possible coordination modes for the new species not only confirms established characteristics of gold(I) bonding, but also suggests that Pauli repulsion is a key yet hitherto overlooked element. Additionally, we obtain a new perspective on gold(I)-bonding by comparison of the gold(I)-cyclobutadiene to congeners stabilized by p-, d-, and f-block metals. Consequently, we refine the gold(I) bonding model, with a delicate interplay of Pauli repulsion and charge transfer as the key driving force for various coordination motifs. Finally, Pauli repulsion is similarly determined as a significant interaction in Au I -alkyne species, corroborating this revised understanding of Au I bonding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Co(II) Substitution Enhances the Esterase Activity of a de Novo Designed Zn(II) Carbonic Anhydrase

Abstract Carbonic Anhydrases (CAs) have been a target forde novoprotein designers due to the simplicity of the active site and rapid rate of the reaction. The first reported mimic contained a Zn(II) bound to three histidine imidazole nitrogens and an exogenous water molecule, hence closely mimicking the native enzymes’ first coordination sphere. Co(II) has served as an alternative metal to interrogate CAs due to its d 7 electronic configuration for more detailed solution characterization. We present here the Co(II) substituted [Co(II)(H 2 O/OH − )] N (TRIL2WL23H) 3 n+ that behaves similarly to native Co(II) substituted human‐CAs. Like the Zn(II) analogue, the cobalt‐derivative at slightly basic pH is incapable of hydrolyzing p‐nitrophenylacetate (pNPA); however, as the pH is increased a significant activity develops, which at pH values above 10 eventually yields a catalytic efficiency that exceeds that of the [Zn(II)(OH − )] N (TRIL2WL23H) 3 + peptide complex. X‐ray absorption analysis is consistent with an octahedral species at pH 7.5 that converts to a 5‐coordinate species by pH 11. UV‐vis spectroscopy can monitor this transition, giving a pK a for the conversion of 10.3. We assign this conversion to the formation of a 5‐coordinate Co(II)(N imid ) 3 (OH)(H 2 O) species. The pH dependent kinetic analysis indicates the maximal rate (k cat ), and thus the catalytic efficiency (k cat /K m ), follow the same pH profile as the spectroscopic conversion to the pentacoordinate species. This correlation suggests that the chemically irreversible ester hydrolysis corresponds to the rate determining process.

Chemistry↗