Search NASA⌕ Search

SEARCH · Search NASA

Results for “Criticality search”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

Search for a Grotthuss mechanism through the observation of proton transfer

The transport of protons is critical in a variety of bio- and electro-chemical processes and technologies. The Grotthuss mechanism is considered to be the most efficient proton transport mechanism, generally implying a transfer of protons between ‘chains’ of host molecules via elementary reactions within the hydrogen bonds. Although Grotthuss proposed this concept more than 200 years ago, only indirect experimental evidence of the mechanism has been observed. Here we report the first experimental observation of proton transfer between the molecules in pure and 85% aqueous phosphoric acid. Employing dielectric spectroscopy, quasielastic neutron, and light scattering, and ab initio molecular dynamic simulations we determined that protons move by surprisingly short jumps of only ~0.5–0.7 Å, much smaller than the typical ion jump length in ionic liquids. Our analysis confirms the existence of correlations in these proton jumps. However, these correlations actually reduce the conductivity, in contrast to a desirable enhancement, as is usually assumed by a Grotthuss mechanism. Furthermore, our analysis suggests that the expected Grotthuss-like enhancement of conductivity cannot be realized in bulk liquids where ionic correlations always decrease conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational and experimental search for potential polyanionic K-ion cathode materials

Discovering high-energy cathode materials is critical to construct K-ion batteries for practical applications. Owing to the great success of layered oxides in Li- and Na-ion systems, K layered cathodes have also been investigated in recent years. However, the much larger size of K + compared to Li or Na introduces strong K + –K + interaction within the layer, which results in a sloped voltage profile thereby limiting the specific capacity and operating voltage. In contrast, polyanionic materials with a three-dimensional K + arrangement can effectively mitigate K + –K + interaction. In this work, ten K polyanionic compounds with theoretical capacity >100 mA h g –1 are screened from the Inorganic Crystal Structure Database as potential cathode materials for K-ion batteries. Among the ten proposed compounds, K 2 MnP 2 O 7 , K 2 Mn 2 P 2 O 7 F 2 , K 2 Fe 2 P 2 O 7 F 2 , and K 6 V 2 (PO 4 ) 4 with average voltage <4.5 V are synthesized and evaluated electrochemically. While the re-insertion of K into these compounds is not fully reversible, it may be related to the very high migration barrier that we compute for K ions. In addition, we show the successful synthesis of a series of K 3 V 3–x Cr x (PO 4 ) 4 (x = 0, 1, 2, 3) compounds. Among these, K 3 V 2 Cr(PO 4 ) 4 exhibits the largest reversible capacity, as revealed by the in situ investigation. Lastly, we find that the redox couples in many of these compounds sit at remarkably high potential, even higher than in equivalent Li compounds, which brings both opportunities and challenges in the future research of K polyanion cathodes.

25 ENERGY STORAGE↗

Investigation of methods for targeted search of dominant higher modes in subcritical systems

The reactor physics modeling of subcritical systems requires a substantially different approach from that of a critical reactor due to the presence of the so-called higher modes. Earlier investigations showed that the dominant higher modes lie in the inner part of the eigenvalue spectrum, making the conventional eigenvalue searches unfeasible and calling for a targeted search. This paper investigates the possibility of targeted and multitudinous eigenvalue calculation by testing the Krylov-Schur and the Dynamic Modes Decomposition (DMD) method for simple, analytically tractable problems. While the DMD method clearly showed its efficiency in a one-group homogeneous problem, modal analysis of a three-dimensional reflected reactor in two-groups approximation demonstrated that the increasing complexity poses challenges for both methods. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

HARMONY: Large-Scale Architecture Search for Efficient Hybrid Language Models

As large language models scale to trillions of parameters, their computational and memory requirements present critical challenges for efficient training and deployment. While Mixture of Experts (MoE) architectures enable efficient scaling through sparse parameter activation, and state-space models like Mamba offer linear-time complexity, principled methods for combining these paradigms remain undeveloped. We introduce HARMONY (Hybrid Architecture Research for Mamba, Optimized with Neural efficiencY), a multi-objective evolutionary neural architecture search framework for discovering efficient hybrid language models that integrate Transformer attention mechanisms, Mixture-of-Experts routing, and Mamba state-space components. Through large-scale distributed search using 16,384 MI250X GPUs on the Frontier supercomputer, HARMONY explores a comprehensive design space encompassing six attention variants (MHA, MQA, GQA, MLA, SWA, and Mamba-2), variable MoE configurations with both routed and shared experts, and extensive Mamba hyperparameters. Our framework discovers heterogeneous architectures that balance training performance with computational efficiency through multi-objective optimization incorporating latency penalties and fitness-based selection. Analysis of discovered architectures reveals that optimal hybrid designs favor heterogeneous component mixing rather than homogeneous patterns, with Mamba-2 and Multi-Head Latent Attention (MLA) emerging as preferred mechanisms. Discovered architectures demonstrate superior training efficiency: our best configuration achieves a final perplexity of 1.0874 with 2.38B parameters while processing 4,320 tokens/second, outperforming significantly larger manually designed models. Full-scale evaluation shows HARMONY's top architectures achieve better loss trajectories than equivalently-sized models using state-of-the-art configurations including Mixtral, Jamba, and Samba. Additionally, we demonstrate 91% weak scaling efficiency when training discovered 36B-parameter models across 1,024 GPUs. HARMONY is released as an open framework with comprehensive tools for building and training hybrid models using expert-data-pipeline parallelism, democratizing access to automated architecture design for next-generation language models.

Herron, Emily [ORNL] (ORCID:0000000273008172)↗

Chemical Recommender System: Replacement Suggestions for Small Molecules

The Chemical Recommender System (CRS) is an open-source, high-performance toolkit that enables real-time similarity searches across the complete PubChem database (over 50 million molecules) using commodity hardware. The CRS addresses critical limitations in existing chemical informatics platforms through a novel vector database infrastructure, extensible model integration capabilities, and complete algorithmic transparency. The system implements a vector database deployment with partitioned indexing that achieves a ~60x speedup over traditional approaches. A containerized model integration framework allows researchers to seamlessly incorporate custom predictive models into the full-scale search and scoring pipeline, while complete configurability of search parameters, filtering logic, and scoring functions provides capabilities not available in existing black-box solutions. Beyond structural similarity, the CRS integrates OPERA QSAR models for thermophysical and toxicity predictions, RDKit synthetic accessibility scoring, and user-defined models to compute weighted final replacement scores. The complete system is accessible through an interactive web application supporting real-time progress monitoring, post-processing score re-weighting, automated PDF reporting, and batch processing capabilities.

Nair, Parthiv Anand [Sandia National Laboratories ↗

Critical evaluation and thermodynamic modeling of the Pd–Sn system

The single crystalline material PdSn 4 , a homologue of the Dirac nodal arc semimetal PtSn 4 , is a promising candidate to search for new topological states with fascinating quantum physical properties. In the present work, the thermochemistry and phase diagram information of the Pd–Sn system published in the literature was collected and critically reviewed, two thermodynamic reassessments of the Pd–Sn system were carried out in the frame of the CALPHAD approach to optimize the Gibbs free energy of each phase presented in the system. The liquid phase was described using respectively the Bragg-Williams random mixing model and the associate solution model. All the reliable thermodynamic property and phase equilibria data can be generally described using the presently obtained thermodynamic descriptions of the Pd–Sn system. Issues related to the further improvement of the thermodynamic descriptions of the Pd–Sn system are discussed.

36 MATERIALS SCIENCE↗

Multifunctional Metal–Oxide Nanocomposite Thin Film with Plasmonic Au Nanopillars Embedded in Magnetic La 0.67 Sr 0.33 MnO 3 Matrix

Searching for multifunctional materials with tunable magnetic and optical properties has been a critical task toward the implementation of future integrated optical devices. Vertically aligned nanocomposite (VAN) thin films provide a unique platform for multifunctional material designs. In this work, a new metal–oxide VAN has been designed with plasmonic Au nanopillars embedded in a ferromagnetic La 0.67 Sr 0.33 MnO 3 (LSMO) matrix. Such Au–LSMO nanocomposite presents intriguing plasmon resonance in the visible range and magnetic anisotropy property, which are functionalized by the Au and LSMO phase, respectively. Furthermore, the vertically aligned nanostructure of metal and dielectric oxide results in the hyperbolic property for near-field electromagnetic wave manipulation. Such optical and magnetic response could be further tailored by tuning the composition of Au and LSMO phases.

36 MATERIALS SCIENCE↗

Transforming energy using quantum dots

Transforming and directing the flow of energy from one form (e.g., sunlight, electricity, etc.) to other useful forms of energy (e.g., electricity, chemical bonds, light, etc.) in an efficient and controllable manner is critical to meet the increasing energy demands and build a sustainable society. In search of such energy mediators, colloidal semiconductor nanocrystals, or quantum dots (QDs) are promising building blocks for building and designing systems that can efficiently capture light and convert and direct that energy into other useful forms of energy. In this work, we summarize recent advances using QDs in energy conversion architectures with the express goal of converting optical energy to other forms of energy, including electricity (i.e., photovoltaics) , photons with different energies (i.e., photo up- or downconversion), and chemical bonds (i.e., photocatalysis). The advantages of employing QDs over molecular chromophores in absorbing and then directing and converting optical energy are highlighted. Finally, we discuss ongoing challenges as well as unique opportunities associated with the use of QDs for transforming energy.

30 DIRECT ENERGY CONVERSION↗

Optical follow-up of gravitational wave triggers with DECam during the first two LIGO/VIRGO observing runs

Gravitational wave (GW) events detectable by LIGO and Virgo have several possible progenitors, including black hole mergers, neutron star mergers, black hole–neutron star mergers, supernovae, and cosmic string cusps. A subset of GW events is expected to produce electromagnetic (EM) emission that, once detected, will provide complementary information about their astrophysical context. To that end, the LIGO–Virgo Collaboration (LVC) sends GW candidate alerts to the astronomical community so that searches for their EM counterparts can be pursued. The DESGW group, consisting of members of the Dark Energy Survey (DES), the LVC, and other members of the astronomical community, uses the Dark Energy Camera (DECam) to perform a search and discovery program for optical signatures of LVC GW events. DESGW aims to use a sample of GW events as standard sirens for cosmology. Due to the short decay timescale of the expected EM counterparts and the need to quickly eliminate survey areas with no counterpart candidates, it is critical to complete the initial analysis of each night’s images as quickly as possible. We discuss our search area determination, imaging pipeline, and candidate selection processes. We review results from the DESGW program during the first two LIGO–Virgo observing campaigns and introduce other science applications that our pipeline enables.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Role of the third dimension in searching for Majorana fermions in α-RuCl 3 via phonons

Understanding phonons in α-RuCl 3 is critical to analyze the controversy around the observation of the half-integer thermal quantum Hall effect. While many studies have focused on the magnetic excitations in α-RuCl 3 , its vibrational excitation spectrum has remained relatively unexplored. We investigate the phonon structure of α-RuCl 3 via inelastic neutron-scattering experiments and density-functional-theory calculations. Our results show excellent agreement between experiment and first-principles calculations. After validating our theoretical model, we extrapolate the low-energy phonon properties. We find that the phonons in α-RuCl 3 that either propagate or vibrate in the out-of-plane direction have significantly reduced velocities and therefore have the potential to dominate the observability of the elusive half-integer plateaus in the thermal Hall conductance. In addition, we use low-energy interlayer phonons to resolve the low-temperature stacking structure of our large crystal of α-RuCl 3 , which we find to be consistent with that of the R$\bar{3}$ space group, in agreement with neutron diffraction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

First direct 7 Be electron-capture $\mathrm{Q}$-value measurement toward high-precision searches for neutrino physics beyond the Standard Model

Here, we report the first direct measurement of the nuclear electron-capture (EC) decay Q value of 7 Be → 7 Li via high-precision Penning trap mass spectrometry (PTMS). This was performed using the LEBIT Penning trap located at the National Superconducting Cyclotron Laboratory/Facility for Rare Isotope Beams (NSCL/FRIB) using the newly commissioned Batch-Mode Ion-Source (BMIS) to deliver the unstable 7 Be + samples. With a measured value of Q EC = 861.963(23) keV, this result is three times more precise than any previous determination of this quantity. This improved precision and accuracy of the 7 Be EC decay Q value is critical for ongoing experiments that measure the recoiling nucleus in this system as a signature to search for beyond the Standard Model (BSM) neutrino physics using 7 Be-doped superconducting sensors. This experiment has extended LEBIT capabilities, using the first low-energy beam delivered by BMIS at FRIB for PTMS, as well as measuring the lightest-mass isotopes so far with LEBIT.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Global-Local Policy Search and its Application in Grid-Interactive Building Control

As the buildings sector represents over 70% of the total U.S. electricity consumption, it offers a great amount of untapped demand-side resources to tackle many critical grid-side problems and improve the overall energy system's efficiency. To help make buildings grid-interactive, this paper proposes a global-local policy search method to train a reinforcement learning (RL) based controller which optimizes building operation during both normal hours and demand response (DR) events. Experiments on a simulated five-zone commercial building demonstrate that by adding a local fine-tuning stage to the evolution strategy policy training process, the control costs can be further reduced by 7.55% in unseen testing scenarios. Baseline comparison also indicates that the learned RL controller outperforms a pragmatic linear model predictive controller (MPC), while not requiring intensive online computation.

demand response↗

Prediction of Above-Room-Temperature Superconductivity in Lanthanide/Actinide Extreme Superhydrides

Achieving superconductivity at or above room temperature has been a century long held dream for physicists since the discovery of superconductivity in mercury in 1911. Following the recent predictions and ensuing synthesis of clathrate superhydride LaH 10 under pressure exhibiting extraordinary superconducting critical temperatures (T c ) of 250 260 K, we predict via advanced crystal structure search methods a new class of extremely hydrogen rich clathrate superhydrides. These MH 18 (M: rare earth/actinide metal atom) stoichiometric compounds consisting of H36 cage networks are predicted to host T c values above room temperature up to 330 K at pressures of 350 GPa. The bonding and electronic properties of these MH 18 clathrate superhydrides parallel those of atomic metallic hydrogen, giving rise to the highest superconducting temperatures predicted thus far for a thermodynamically stable hydride compound. In depth examination of these extreme superhydrides offers key insights for elucidating and further exploring phonon mediated superconductivity above room temperature in hydrogen rich and other low Z materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Searching for Exploding black holes

Abstract The observation of the final stages of the evaporation of a light black hole, which Hawking referred to as “black hole explosion”, would offer critical insights on quantum gravity and high-energy physics phenomena. Here, we explore, review, and revisit the observational features and rates expected for nearby, light, evaporating black holes, and we assess and compare the expected sensitivity of a broad range of observatories. We then focus on the search for candidate black hole explosions in archival data from the Fermi Large Area Telescope and Gamma-ray Burst Monitor, and outline possible future observational campaigns.

Astronomy & Astrophysics↗

Exascale Algorithms and Software for Lattice Field Theory in High Energy Physics: Searching Beyond the Standard Model

The Boston University component has focused on the algorithmic development of new Multigrid solver for the critical kernel for the Dirac propagators that dominated the both simulation require for lattice ensemble and the analysis of physical correlation functions. Progress on this has meet the above objects, even exceeding them a bit. The result is the beginning if multiscale lattice QCD applicable to future Exascale hardware and the development of the QUDA software for NVIDIA GPUs to give near optimal performance. As we approach exascale hardware and computation at that scale this provides the infrastructure for further advances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Relevant Advanced Reactor Benchmarks for Nuclear Data Assessment

Advanced reactor concepts currently being developed throughout the industry are significantly different from light water reactor (LWR) designs with respect to geometry, materials, and operating conditions, and consequently, with respect to their reactor physics behavior. Given the limited operating experience with non-LWRs, the accurate simulation of reactor physics and the quantification of associated uncertainties are critical for ensuring that advanced reactor concepts operate within the appropriate safety margins. Nuclear data are a major source of input uncertainties in reactor physics analysis. As part of an ongoing project at Oak Ridge National Laboratory, the effects of nuclear data uncertainties on key figures of merit associated with advanced reactor safety are being assessed for selected advanced reactor technologies. Key nuclear data relevant for reactor safety analysis for each selected advanced reactor technology were identified in Phase 1, and their impact on important key figures of merit was assessed in Phase 2. This report describes the outcome of Phase 3. Available benchmarks and fuel irradiation data for use in evaluating the impact of uncertainties and gaps in nuclear data that impact reactivity control for advanced reactor designs through the fuel cycle were identified and assessed. Benchmarks were identified by searching (1) the Organisation for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) International Criticality Safety Benchmark Evaluation Project (IRPhEP) handbook, (2) the OCED/NEA International Reactor Physics Experiment Evaluation Project (IRPhEP) handbook, (3) ongoing OECD/NEA benchmark activities, and (4) documentation in public literature. Relevant benchmarks were identified by selecting reactors with geometry, materials, and neutron energy spectra similar to those of selected advanced reactor technologies. This assessment identified six benchmarks, of which three are experimental and three are purely computational. One experimental and one computation benchmark contain depleted fuel; all others are limited to fresh fuel. This report provides short descriptions of the selected benchmarks along with the availability of measured data for comparison.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Parameter identification methods for low-order gray box building energy models: A critical review

The body of knowledge on gray box building energy modeling (GBBEM) has been developed over the past few decades and has undergone some important changes recently. Starting with simple methods and simple buildings, the science of GBBEM has grown to encompass complex and more computationally intensive techniques and complex commercial buildings. Numerous works including a recent review have considered model structure and inputs in a nearly systematic way, but no extant work systematically reviews the approaches for GBBEM parameter search initialization and final identification, despite this being arguably the most difficult and impactful part of the modeling process. To this end, we critically review 55 extant works describing advantages, limitations, and domain of applicability of several classes of parameter initialization and optimization techniques specifically for GBBEM. We categorize the classes of methods and analyze the evidence of their applicability for different applications within the field of GBBEM. We find an emerging consensus that initialization of parameter searches for anything other than the simplest building elements is often challenging and sometimes requires a stochastic approach to begin the parameter identification process. After this initial process, faster methods have been used in some cases but often the nature of the problem requires stochastic methods for this portion of the process as well. For less complex systems, more deterministic and efficient methods have been shown to be effective. Finally, we draw conclusions as to the domain of applicability of different classes of initialization and optimization techniques for GBBEEM and offer suggestions for research directions that are likely to prove fruitful.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Pulse Generation Framework with Augmented Program-aware Basis Gates and Criticality Analysis

Near-term intermediate scale quantum (NISQ) de- vices are subject to considerable noise and short coherence time. Consequently, it is critical to minimize circuit execution latency. Traditionally, each basis gate of a transpiled circuit is decoded into a fixed episode of the device control pulses. Recently, people started to investigate merged pulse generation for customized gates through quantum optimal control (QOC). However, existing QOC approaches face the challenges of (i) restricted search space due to prohibitive compilation overhead; (ii) suboptimal end-to-end performance due to aggressive local optimization and falsely introduced dependency among the customized gates; (iii) inadequate adaptivity towards system calibration, which is critical for NISQ devices. In this work, we propose PAQOC, a novel QOC framework that can (i) automatically detect frequently encountered gate patterns in the logical circuit by modeling the problem as a subgraph mining process and reuse these patterns to enable much larger search space exploration (i.e., program aware); (ii) systemically construct customized gate-set based on the impact to the overall program latency (i.e., criticality-aware); and (iii) quickly adapt to system re-calibration thanks to the small-scale pattern-based gate generation (i.e., adaptivity-aware). PAQOC achieves a good tradeoff between circuit performance and compilation time, allowing fully automatic, single stop, ad- hoc customized pulse generation for more efficient execution of user programs on NISQ devices. Evaluations using fifteen applications show that PAQOC can achieve on average 1.95× speedup of the circuit latency and achieve on average 36.7% reduction in compilation overhead. With PAQOC, circuits can run faster with reduced noise, allowing deeper circuits to be tested within the coherence time of present NISQ platforms.

Chen, Yanhao↗