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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Toward Complete Leading-Order Predictions for Neutrinoless Double β Decay

The amplitude for the neutrinoless double β (0νββ) decay of the two-neutron system nn → ppe – e – constitutes a key building block for nuclear-structure calculations of heavy nuclei employed in large-scale 0νββ searches. Assuming that the 0νββ process is mediated by a light-Majorana-neutrino exchange, a systematic analysis in chiral effective field theory shows that already at leading order a contact operator is required to ensure renormalizability. Here, we develop a method to estimate the numerical value of its coefficient (in analogy to the Cottingham formula for electromagnetic contributions to hadron masses) and validate the result by reproducing the charge-independence-breaking contribution to the nucleon-nucleon scattering lengths. Our central result, while derived in dimensional regularization, is given in terms of the renormalized amplitude Aν(|p|, |p'|) , matching to which will allow one to determine the contact-term contribution in regularization schemes employed in nuclear-structure calculations. Our results thus greatly reduce a crucial uncertainty in the interpretation of searches for 0νββ decay.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Detection of Synchrophasor False Data Injection Attack using Feature Interactive Network

The synchrophasor data recorded by Phasor Measurement Units (PMUs) plays an increasingly critical role in the regulation and situational awareness of power systems. However, the widely installed PMUs are vulnerable to multiple malicious attacks from cyber hackers during data transmission and storage. To address this problem, a Modified Ensemble Empirical Mode Decomposition (MEEMD) is proposed first to extract the intrinsic mode functions of each Synchrophasor Data Attacks (SDA). The frequency-based adaptive screening criterion embedded in MEEMD is used to eliminate the false intrinsic mode functions. Next, a Multivariate Convolutional Neural Network (MCNN) is proposed to identify multiple SDA by utilizing the extracted intrinsic mode functions and original SDA as input vectors. A fusion block as the main structure of MCNN is also leveraged to increase the diversity of features and compress the model parameters. Integrating MEEMD and MCNN, a framework with automatic feature extraction and multi-source information fusion capability, referred to as Feature Interactive Network (FIN), is proposed to detect multiple SDA. Based on the proposed FIN framework, six types of SDA are explored for the first time using actual synchrophasor data in FNET/Grideye that was collected from different locations in the U.S. Eastern Interconnection. Finally, a large quantity of experiments with different attack strengths are used to evaluate the adaptability and classification performance of the proposed FIN.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Computational modeling of phononic pseudocrystal isolators

Methods for the efficient computational prediction of the performance of phononic pseudocrystals (structured materials capable of blocking extraordinary ranges of frequency) in COMSOL and other comparable finite element method codes are set forth. These methods include boundary conditions that make possible halving the size of the computational domain. Also included is an introduction of elastic energy density methods for assessing the extinction of elastic waves within the patterned region.

Swift, Stephen Hales↗
DOE OSTI2025

Spatio-temporal Fourier Transformer for Long-term Dynamics Prediction (StFT) v1.0

We propose a novel machine learning model spatio-temporal Fourier transformer (StFT) to emulate long-term dynamics of multi-scale and multi-physics systems. Our method StFT overcomes the limitations of rapid error accumulation, particularly in long-term forecasting of systems characterized by complex and coupled dynamics. StFT achieves outstanding accuracy and computational efficiency by effectively capturing multi-scale interactions, and quantify the uncertainties inherent in the predictions. Our model leverages a structured hierarchy of StFT blocks, and explicitly captures dynamics across both macro- and micro- spatial scales. Evaluations conducted on three benchmark datasets (plasma, fluid, and atmospheric dynamics) demonstrate the advantages of our approach over state-of-the-art ML methods.

Bai, Zhe [Lawrence Berkeley National Laboratory (L↗
DOE OSTI2024

The ECP SICM project: Managing complex memory hierarchies for exascale applications

The Exascale Computing Project (ECP)’s Simplified Interface to Complex Memories (SICM) effort focuses on developing universal interfaces for discovering, managing, and sharing data across complex memory hierarchies. These facilitate the exploitation of emerging memory technologies and support precise control over their various trade-offs such as high-bandwidth versus low-latency, persistent versus ephemeral, high-capacity versus low-capacity, and near-CPU versus near-GPU. SICM comprises three interrelated components: a low-level interface, a high-level interface, and a persistent-heap interface. The low-level SICM interface is intended for system and run-time developers as well as expert application developers who prefer full control of the memory objects used within their application. The high-level SICM interface builds upon the low-level interface, employing application-level profiling and analysis to optimize data management for complex memory hierarchies. The persistent-heap interface provides applications with a persistent memory allocator that can allocate custom C++ data structures in both block-storage and byte-addressable persistent memories.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Transfer Operator Framework for Earth System Predictability and Water Cycle Extremes

For chaotic dynamical systems, nonlinear instabilities lead to exponentially divergent trajectories in the evolution of system states. Unless a simulation is initialized with an infinite-precision snapshot of the state of the true system and all known physical effects that go into its evolution are directly computed, the future state predicted by the simulation will quickly diverge from that of the true system. Moreover, the Earth system is highly structured and contains localized coherent structures that are particularly important to predict. Predicting extreme events associated with coherent structures, like hurricanes and blocking events, is crucial for understanding the effects of global warming on the water cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Transfer Operator Framework for Earth System Predictability and Water Cycle Extremes

For chaotic dynamical systems, nonlinear instabilities lead to exponentially divergent trajectories in the evolution of system states. Unless a simulation is initialized with an infinite-precision snapshot of the state of the true system and all known physical effects that go into its evolution are directly computed, the future state predicted by the simulation will quickly diverge from that of the true system. Moreover, the Earth system is highly structured and contains localized coherent structures that are particularly important to predict. Predicting extreme events associated with coherent structures, like hurricanes and blocking events, is crucial for understanding the effects of global warming on the water cycle.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Predicting Catalyst Surface Stability Under Reaction Conditions Using Deep Reinforcement Learning and Machine Learning Potentials

Catalysts are critical for most large-scale energy intensive chemical transformation processes, such as energy storage, liquid fuel production, and the formation of chemical building blocks. The catalyst composition, structure, and morphology impact the performance under reaction conditions and influences properties like activity and selectivity. Many industrial catalysts offer imperfect activity/selectivity, or contain expensive metals. Further, catalysts can deactivate over time as the morphology changes or harsh reactive environments alter the surface structure. Methods to automatically model and predict the kinetics of how catalyst surfaces will restructure would enable engineers to design around these challenges, improve performance, increase longevity. This project investigated a specific type of machine learning model, deep reinforcement learning, machine learning models to act as surrogates for the physical system, and compared the results of these approaches with a specialized high-throughput experimental synthesis and measurement platform.

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

Possibility of 14 C cluster as a building block of medium-mass nuclei

The possibility of the 14 C cluster being a basic building block of medium-mass nuclei is discussed. Although α cluster structures have been widely discussed in the light N ≈ Z mass region, the neutron-to-proton ratio deviates from unity in the nuclei near β-stability line and in neutron-rich nuclei. Thus, more neutron-rich objects with N > Z could become the building blocks of cluster structures in such nuclei. The 14 C nucleus is strongly bound and can be regarded as such a candidate. In addition, the path to the lowest shell-model configuration at short relative distances is closed for the 14 C+ 14 C structure, contrary to the case of the 12 C+ 12 C structure; this allows an appreciable separation distance between the 14 C clusters. The recent development of the antisymmetrized quasicluster model (AQCM) allows us to utilize a j j-coupling shell-model wave function for each cluster in a simplified way. The AQCM results for the 14 C+ 14 C structure in 28 Mg are compared with the ones of cranked relativistic mean field (CRMF) calculations. Although theoretical frameworks of these two models are quite different, they give similar results for the nucleonic densities and rotational properties of the structure under investigation. The existence of a linear chain three- 14 C cluster structure in 42 Ar has also been predicted in AQCM. Furthermore, these results confirm the role of the 14 C cluster as a possible building block of cluster structures in medium-mass nuclei.

20 ≤ A ≤ 38↗
DOE OSTI2024

A Three-in-One Hybrid Strategy for High-Performance Semiconducting Polymers Processed from Anisole

The development of semiconducting polymers with good processability in green solvents and competitive electrical performance is essential for realizing sustainable large-scale manufacturing and commercialization of organic electronics. A major obstacle is the processability-performance dichotomy that is dictated by the lack of ideal building blocks with balanced polarity, solubility, electronic structures, and molecular conformation. Herein, through the integration of donor, quinoid and acceptor units, an unprecedented building block, namely TQBT, is introduced for constructing a serial of conjugated polymers. The TQBT, distinct in non-symmetric structure and high dipole moment, imparts enhanced solubility in anisole—a green solvent—to the polymer TQBT-T. Furthermore, PTQBT-T possess a highly rigid and planar backbone owing to the nearly coplanar geometry and quinoidal nature of TQBT, resulting in strong aggregation in solution and localized aggregates in film. Remarkably, PTQBT-T films spuncast from anisole exhibit a hole mobility of 2.30 cm 2 V -1 s -1 , which is record high for green solvent-processable semiconducting polymers via spin-coating, together with commendable operational and storage stability. The hybrid building block emerges as a pioneering electroactive unit, shedding light on future design strategies in high-performance semiconducting polymers compatible with green processing and marking a significant stride towards ecofriendly organic electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Three-dimensional superlattice engineering with block copolymer epitaxy

Three-dimensional (3D) structures at the nanometer length scale play a crucial role in modern devices, but their fabrication using traditional top-down approaches is complex and expensive. Analogous to atomic lattices, block copolymers (BCPs) spontaneously form a rich variety of 3D nanostructures and have the potential to substantially simplify 3D nanofabrication. Here, we show that the 3D superlattice formed by BCP micelles can be controlled by lithographically defined 2D templates matching a crystallographic plane in the 3D superlattice. Using scanning transmission electron microscopy tomography, we demonstrate precise control over the lattice symmetry and orientation. Excellent ordering and substrate registration can be achieved, propagating through 284-nanometer-thick films. BCP epitaxy also showed exceptional lattice tunability, with a continuous Bain transformation from a body-centered cubic to a face-centered cubic lattice. Lattice stability was mediated by molecular packing frustration, and surface-induced lattice reconstruction was observed, leading to the formation of a unique honeycomb lattice.

42 ENGINEERING↗
DOE OSTI2023

Effect of Charged Block Length Mismatch on Double Diblock Polyelectrolyte Complex Micelle Cores

Polyelectrolyte complex micelles are hydrophilic nanoparticles that self-assemble in aqueous environments due to associative microphase separation between oppositely charged blocky polyelectrolytes. In this work, we employ a suite of physical characterization tools to examine the effect of charged block length mismatch on the equilibrium structure of double diblock polyelectrolyte complex micelles (D-PCMs) by mixing a diverse library of peptide and synthetic charged-neutral block polyelectrolytes with a wide range of charged block lengths (25–200 units) and chemistries. Early work on D-PCMs suggested that this class of micelles can only be formed from blocky polyelectrolytes with identical charged block lengths, a phenomenon referred to as chain length recognition. Here, we use salt annealing to create PCMs at equilibrium, which shows that chain length recognition, a longstanding hurdle to repeatable self-assembly from mismatched polyelectrolytes, can be overcome. Interestingly, D-PCM structure–property relationships display a range of values that vary systematically with the charged block lengths and chemical identity of constituent polyelectrolyte pairings and cannot be described by generalizable scaling laws. We discuss the interdependent growth behavior of the radius, ionic pair aggregation number, and density in the micelle core for three chemically distinct diblock pairings and suggest a potential physical mechanism that leads to this unique behavior. By comparing the results of these D-PCMs to the scaling laws recently developed for single diblock polyelectrolyte complex micelles (S-PCMs: diblock + homopolymer), we observe that D-PCM design schemes reduce the size and aggregation number and restrict their growth to a function of charged block length relative to S-PCMs. Understanding these favorable attributes enables more predictive use of a wider array of charged molecular building blocks to anticipate and control macroscopic properties of micelles spanning countless storage and delivery applications.

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

Preclinical characterization of Pan-NKG2D ligand-binding NKG2D receptor decoys

NKG2D and its ligands are critical regulators of protective immune responses controlling infections and cancer, defining a crucial immune signaling axis. Current therapeutic efforts targeting this axis almost exclusively aim at enhancing NKG2D-mediated effector functions. However, this axis can drive disease processes when dysregulated, in particular, driving stem-like cancer cell reprogramming and tumorigenesis through receptor/ligand self-stimulation on tumor cells. Despite complexities with its structure and biology, we developed multiple novel engineered proteins that functionally serve as axis-blocking NKG2D “decoys” and report biochemical, structural, in vitro , and in vivo evaluation of their functionality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A human antibody epitope map of Pfs230D1 derived from analysis of individuals vaccinated with a malaria transmission-blocking vaccine

Pfs230 domain 1 (Pfs230D1) is an advanced malaria transmission-blocking vaccine antigen demonstrating high functional activity in clinical trials. However, the structural and functional correlates of transmission-blocking activity are not defined. Here, we characterized a panel of human monoclonal antibodies (hmAbs) elicited in vaccinees immunized with Pfs230D1. These hmAbs exhibited diverse transmission-reducing activity, yet all bound to Pfs230D1 with nanomolar affinity. We compiled epitope-binning data for seventeen hmAbs and structures of nine hmAbs complexes to construct a high-resolution epitope map and revealed that potent transmission-reducing hmAbs bound to one face of Pfs230D1, while non-potent hmAbs bound to the opposing side. The structure of Pfs230D1D2 revealed that non-potent transmission-reducing epitopes were occluded by the second domain. The hmAb epitope map delineated binary hmAb combinations that synergized for extremely high-potency, transmission-reducing activity. Finally, this work provides a high-resolution guide for structure-based design of enhanced immunogens and informs diagnostics that measure the transmission-reducing response.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Structure of human NADK2 reveals atypical assembly and regulation of NAD kinases from animal mitochondria

All kingdoms of life produce essential nicotinamide dinucleotide NADP(H) using NAD kinases (NADKs). A panel of published NADK structures from bacteria, eukaryotic cytosol, and yeast mitochondria revealed similar tetrameric enzymes. Here, we present the 2.8-Å structure of the human mitochondrial kinase NADK2 with a bound substrate, which is an exception to this uniformity, diverging both structurally and biochemically from NADKs. We show that NADK2 harbors a unique tetramer disruptor/dimerization element, which is conserved in mitochondrial kinases of animals (EMKA) and absent from other NADKs. EMKA stabilizes the NADK2 dimer but prevents further NADK2 oligomerization by blocking the tetramerization interface. This structural change bears functional consequences and alters the activation mechanism of the enzyme. Whereas tetrameric NADKs undergo cooperative activation via oligomerization, NADK2 is a constitutively active noncooperative dimer. Thus, our data point to a unique regulation of NADP(H) synthesis in animal mitochondria achieved via structural adaptation of the NADK2 kinase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Structural features of 11 synthetic bacteriochlorins — comparisons with chlorins and porphyrins

As part of a program to develop the fundamental science of synthetic bacteriochlorins — analogues of Nature’s light-harvesting pigments in anoxygenic photosynthesis — 11 synthetic free base bacteriochlorins have been examined by single-crystal X-ray diffraction analysis. In each bacteriochlorin, each pyrroline ring contains a gem-dimethyl group to block adventitious (aerobic) dehydrogenation. The structural features of the bacteriochlorins (tetrahydroporphyrins) are compared with the less saturated counterparts, chlorins (dihydroporphyrins) and porphyrins. Only slight structural perturbation accrues due to the presence of the gem-dimethyl groups. Furthermore, the results presented herein may aid in understanding metal chelation processes and underpin the development of functional solid-state molecular assemblies.

X-ray diffraction↗
DOE OSTI2020

Mechanism and inhibition of Streptococcus pneumoniae IgA1 protease

Opportunistic pathogens such as Streptococcus pneumoniae secrete a giant metalloprotease virulence factor responsible for cleaving host IgA1, yet the molecular mechanism has remained unknown since their discovery nearly 30 years ago despite the potential for developing vaccines that target these enzymes to block infection. Here we show through a series of cryo-electron microscopy single particle reconstructions how the Streptococcus pneumoniae IgA1 protease facilitates IgA1 substrate recognition and how this can be inhibited. Specifically, the Streptococcus pneumoniae IgA1 protease subscribes to an active-site-gated mechanism where a domain undergoes a 10.0 Å movement to facilitate cleavage. Monoclonal antibody binding inhibits this conformational change, providing a direct means to block infection at the host interface. These structural studies explain decades of biological and biochemical studies and provides a general strategy to block Streptococcus pneumoniae IgA1 protease activity to potentially prevent infection.

59 BASIC BIOLOGICAL SCIENCES↗