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Results for “LU factorization”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Unraveling Vulnerabilities in Endocrine Therapy-Resistant HER2+/ER+ Breast Cancer

Abstract Breast tumors overexpressing human epidermal growth factor receptor (HER2) confer intrinsic resistance to endocrine therapy (ET), and patients with HER2/estrogen receptor–positive (HER2+/ER+) breast cancer (BCa) are less responsive to ET than HER2–/ER+. However, real-world evidence reveals that a large subset of patients with HER2+/ER+ receive ET as monotherapy, positioning this treatment pattern as a clinical challenge. In the present study, we developed and characterized 2 in vitro models of ET-resistant (ETR) HER2+/ER+ BCa to identify possible therapeutic vulnerabilities. To mimic ETR to aromatase inhibitors (AIs), we developed 2 long-term estrogen deprivation (LTED) cell lines from BT-474 (BT474) and MDA-MB-361 (MM361). Growth assays, PAM50 subtyping, and genomic and transcriptomic analyses, followed by validation and functional studies, were used to identify targetable differences between ET-responsive parental and ETR-LTED HER2+/ER+ cells. Compared to their parental cells, MM361 LTEDs grew faster, lost ER, and increased HER2 expression, whereas BT474 LTEDs grew slower and maintained ER and HER2 expression. Both LTED variants had reduced responsiveness to fulvestrant. Whole-genome sequencing of aggressive MM361 LTEDs identified mutations in genes encoding transcription factors and chromatin modifiers. Single-cell RNA sequencing demonstrated a shift towards non-luminal phenotypes, and revealed metabolic remodeling of MM361 LTEDs, with upregulated lipid metabolism and ferroptosis-associated antioxidant genes, including GPX4. Combining a GPX4 inhibitor with anti-HER2 agents induced significant cell death in both MM361 and BT474 LTEDs. The BT474 and MM361 AI-resistant models capture distinct phenotypes of HER2+/ER+ BCa and identify altered lipid metabolism and ferroptosis remodeling as vulnerabilities of this type of ETR BCa.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Phase-controlled improvement of photon lifetime in coupled superconducting cavities

High-quality cavities are crucial for various fundamental physical studies and applications. Here we find that by coupling two cavities directly or via a phase-tunable coupling channel, the photon lifetime of the local field can exceed that of the bare cavities. The cavity photon lifetime is modified by the phases of the initial states and the phase accumulation on the coupling channel, which affect the interference between cavities. In experiments, by coupling superconducting radio-frequency cavities via phase-tunable cables, we realize a factor of 2 improvement in the cavity photon lifetime. The results can bring rich revenue to quantum information science, sensing, and high-energy physics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Measurement of Neutral Current Elastic Cross Section in MicroBooNE

The MicroBooNE experiment is an 85 ton active volume liquid-argon time projection chamber located in the Fermilab Booster Neutrino Beamline. MicroBooNE’s ability to detect low-energy protons allows us to study single proton events with a four-momentum transfer squared, Q$^2$, as low as 0.10 GeV$^2$. We present a measurement of the flux-averaged neutral-current elastic differential cross sections for neutrinos scattering on argon as a function of Q$^2$, proton momentum and proton angle with respect to the direction of the neutrino beam. This is our first step towards extracting the strange quark contribution to the axial form factor, which is not only the least-constrained contribution to the neutral-current elastic scattering cross section but is also crucial for understanding the strange quark contribution to the proton spin.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Quadratic strong coupling in AlN Kerr cavity solitons

Photonic platforms with χ (2) nonlinearity offer new degrees of freedom for Kerr frequency comb development. Here, we demonstrate Kerr soliton generation at 1550 nm with phase-matched quadratic coupling to the 775 nm harmonic band in a single AlN microring and thus the formation of dual-band mode-locked combs. In the strong quadratic coupling regime where the χ (2) phase-matching window overlaps the pump mode, the pump-to-harmonic-comb conversion efficiency is optimized. However, the strong quadratic coupling also drastically modifies the Kerr comb generation dynamics and decreases the probability of soliton generation. By engineering the χ (2) phase-matching wavelength, we are able to achieve a balance between high conversion efficiency and high soliton formation rate under the available pump power and microring quality factors. Our numerical simulations confirm the experimental observations. These findings provide guidance on tailoring single-cavity dual-band coherent comb sources.

Gong, Zheng (ORCID:0000000301704870)↗
DOE OSTI2024

Machine-learning based approach to examine ecological processes influencing the diversity of riverine dissolved organic matter composition

Dissolved organic matter (DOM) assemblages in freshwater rivers are formed from mixtures of simple to complex compounds that are highly variable across time and space. These mixtures largely form due to the environmental heterogeneity of river networks and the contribution of diverse allochthonous and autochthonous DOM sources. Most studies are, however, confined to local and regional scales, which precludes an understanding of how these mixtures arise at large, e.g., continental, spatial scales. The processes contributing to these mixtures are also difficult to study because of the complex interactions between various environmental factors and DOM. Here we propose the use of machine learning (ML) approaches to identify ecological processes contributing toward mixtures of DOM at a continental-scale. We related a dataset that characterized the molecular composition of DOM from river water and sediment with Fourier-transform ion cyclotron resonance mass spectrometry to explanatory physicochemical variables such as nutrient concentrations and stable water isotopes ( 2 H and 18 O). Using unsupervised ML, distinctive clusters for sediment and water samples were identified, with unique molecular compositions influenced by environmental factors like terrestrial input and microbial activity. Sediment clusters showed a higher proportion of protein-like and unclassified compounds than water clusters, while water clusters exhibited a more diversified chemical composition. We then applied a supervised ML approach, involving a two-stage use of SHapley Additive exPlanations (SHAP) values. In the first stage, SHAP values were obtained and used to identify key physicochemical variables. These parameters were employed to train models using both the default and subsequently tuned hyperparameters of the Histogram-based Gradient Boosting (HGB) algorithm. The supervised ML approach, using HGB and SHAP values, highlighted complex relationships between environmental factors and DOM diversity, in particular the existence of dams upstream, precipitation events, and other watershed characteristics were important in predicting higher chemical diversity in DOM. Our data-driven approach can now be used more generally to reveal the interplay between physical, chemical, and biological factors in determining the diversity of DOM in other ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dual-Band Electrochromism in Hydrous Tungsten Oxide

The independent modulation of visible and near-infrared light by a single material, termed dualband electrochromism, is highly desirable for smart windows to enhance the energy efficiency of buildings. Tungsten oxides are commercially important electrochromic materials, exhibiting reversible visible and near-infrared absorption when electrochemically reduced in an electrolyte containing small cations or protons. The presence of structural water in tungsten oxides has been associated with faster electrochromic switching speeds. Here, we find that WO 3 ·H 2 O, a crystalline hydrate, exhibits dual-band electrochromism unlike the anhydrous WO 3 providing a heretofore unexplored route to tune the electrochromic response of tungsten oxides. Absorption of near-infrared light is achieved at low Li + /e - injection, followed by the absorption of visible light at higher Li + /e - injection as a result of an electrochemically-induced phase transition. We propose that this dual-band modulation is possible due to the more open structure of WO 3 ·H 2 O as compared to WO 3 . This facilitates a more extended solid solution Li + insertion regime that benefits the modulation of near-infrared radiation via plasmon absorption. Higher degrees of Li + /e - insertion lead to polaronic absorption associated with localized charge storage. Furthermore, these results inform how structural factors influence the electrochemically induced spectral response of transition metal oxides and the important role of structural water beyond optical switching speed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Non-degenerate parametric mixing and Q-enhancement in ALN Lamb wave resonator

In this Letter, we explore a non-degenerate phase independent parametric quality factor (Q)-enhancement technique for aluminum nitride (AlN) Lamb wave resonators. Unlike other active Q-enhancement techniques which require precise phase control of the electronic feedback loop, this technique is implemented by parametrically pumping AlN material stiffness to realize a negative resistance seen at the signal path. The negative resistance is dependent on the nonlinear material modulation and multi-resonance coupling in the device. A nonlinear circuit model is developed to simulate the parametric coupling of each resonance and extract the nonlinearity of AlN from experimental data. With proper pump frequency and pump power, the device quality factor is boosted in both simulation and experiment. The demonstrated Q-enhancement method is simple to implement and can be applied to other types of resonators that have nonlinear behavior and support multi-resonance operation.

42 ENGINEERING↗
DOE OSTI2022

Temperature Dependence of Charge Distributions and Carrier Mobility in an Undoped Si/SiGe Heterostructure

Capacitance–voltage (C–V ) characteristics and carrier transport properties of 2-D electron gases (2DEGs) in an undoped Si/SiGe heterostructure at T = 4 – 35 K are presented here. In this work, two capacitance plateaus due to density saturation of the 2DEG in the buried Si quantum well (QW) are observed and explained by a model of surface tunneling. The peak mobility at 4 K is 4.1 × 10 5 cm 2 /V·s and enhanced by a factor of 1.97 at an even lower carrier density compared to the saturated carrier density, which is attributed to the effect of remote carrier screening. At T = 35 K, the mobility enhancement with a factor of 1.35 is still observed, which suggests the surface tunneling is still dominant.

42 ENGINEERING↗
DOE OSTI2021

Antitumor CD8 T cell responses in glioma patients are effectively suppressed by T follicular regulatory cells

Regulatory T (Treg) cells are thought to contribute to tumor pathogenesis by suppressing tumor immunosurveillance and antitumor immunity. T follicular regulatory (Tfr) cells are a recently characterized Treg subset that expresses both the Treg transcription factor (TF) Foxp3 and the T follicular helper (Tfh) TF Bcl-6. The role of Tfr cells in glioma patients remains unclear. In this study, we found that the level of Tfr cells, identified as Foxp3{sup +}Bcl-6{sup +} CD4 T cells, was significantly elevated in tumor-infiltrating CD4 T cells from resected glioma tumors. Both Tfr cells and Treg cells significantly suppressed the proliferation and the cytotoxic capacity of CD8 T cells toward glioma tumor cells, and the suppression was positively associated with the proportion of Tfr cells and Treg cells, respectively. Tfr and Treg cells from glioma tumor samples demonstrated higher suppression potency than those from healthy blood samples and glioma blood samples. Interestingly, canonical CXCR5{sup -} Treg cells could suppress both CXCR5{sup +} and CXCR5{sup -} CD8 T cells, albeit with stronger potency toward CXCR5{sup -} CD8 T cells. However, Tfr cells presented much higher suppression potency toward CXCR5{sup +} CD8 T cells, whereas CXCR5{sup +} CD8 T cells are a potent CD8 T cell subset previously described to have antiviral and antitumor roles. Overall, these data indicate that Tfr cells are enriched in glioma tumors and have suppressive capacity toward CD8 T cell-mediated effector functions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Construction of a Pt‐CeO x Interface for the Electrocatalytic Hydrogen Evolution Reaction

Abstract The creation of metal‐metal oxide interfaces is an important approach to fine‐tuning catalyst properties through strong interfacial interactions. This article presents the work on developing interfaces between Pt and CeO x that improve Pt surface energetics for the hydrogen evolution reaction (HER) within an alkaline electrolyte. The Pt‐CeO x interfaces are formed by depositing size‐controlled Pt nanoparticles onto a carbon support already coated with ultrathin CeO x nanosheets. This interface structure facilitates substantial electron transfer from Pt to CeO x , resulting in decreased hydrogen binding energies on Pt surfaces, and water dissociation for the HER, as predicted by the density functional theory (DFT) calculations. Electrochemical testing indicates that both Pt specific activity and mass activity are improved by a factor of 2 to 3 following the formation of Pt‐CeO x interfaces. This study underscores the significance and potential of harnessing robust interfacial effects to enhance electrocatalytic reactions.

25 ENERGY STORAGE↗
DOE OSTI2026

Did You Win the GPU Cloud Lottery? Benchmarking from TFLOPS to Tokens/$

Cloud GPUs are commonly assumed to deliver consistent performance for a given GPU model. This assumption does not always hold: cloud providers employ diverse system configurations and virtualization mechanisms, and GPUs themselves exhibit non-negligible manufacturing variability (the silicon lottery). In this work, we present a large-scale measurement study of GPU performance variability across 11 cloud providers, covering over 3,500 physical GPUs and 6,800 benchmark runs. Our hierarchical analysis shows that while execution-level variation stays below 9%, performance varies by up to 38% across devices and providers for the same GPU model. Regression analysis indicates that driver- and OS-related software factors contribute less than 1% of the variance; instead, silicon lottery effects dominate observed performance variation, and cloud providers further amplify them through persistent, systematic second-order effects.

Slynko, Platon [Silicon Data, New York, USA] (ORCI↗
DOE OSTI2021

DC Circuit Breakers: A Technology Development Status Survey

DC circuit breakers (DCCBs) play a significant role in obtaining the reliability and stability of DC power systems. Selective and fast isolating of faults minimizes the power supply outages to end electricity users and protects the power converters implemented in the DC system. During the last decades, DCCBs have been deeply investigated in industry and academia. There has been impressive progress in terms of efficiency, response time, power-density, lifetime, and electrical operating ratings. Introducing wide bandgap (WBG) devices further has motivated researchers to propose more efficient and novel topologies. This paper provides a point of reference and a background review for DCCBs from novel aspects, fulfilling absent parts in the literature. The elaborated subjects include current commutation circuitry, DCCBs trip-curves developments, newly added functions to DCCBs, as well as marketing analysis. The advancements of DCCBs are surveyed and development needs are recognized. This paper aims to identify the future research needs of DCCBs for emerging DC power systems.

42 ENGINEERING↗
DOE OSTI2021

On the optical anisotropy in 2D metal-halide perovskites

We develop a better understanding of the many contributing factors that give rise to extreme optical anisotropy in 2D perovskites, and we then show that spin-coated films can exhibit excellent order comparable with exfoliated crystals.

14 SOLAR ENERGY↗
DOE OSTI2024

Interfacially Enhanced Superconductivity in Fe(Te,Se)/Bi 4 Te 3 Heterostructures

Realizing topological superconductivity by integrating high-transition-temperature (T C ) superconductors with topological insulators can open new paths for quantum computing applications. Here, a new approach is reported for increasing the superconducting transition temperature $T^{onset}_C$ by interfacing the unconventional superconductor Fe(Te,Se) with the topological insulator Bi–Te system in the low-Se doping regime, near where superconductivity vanishes in the bulk. The critical finding is that the $T^{onset}_C$ of Fe(Te,Se) increases from nominally non-superconducting to as high as 12.5 K when Bi 2 Te3 is replaced with the topological phase Bi 4 Te 3 . Interfacing Fe(Te,Se) with Bi4Te3 is also found to be critical for stabilizing superconductivity in monolayer films where $T^{onset}_C$ can be as high as 6 K. Measurements of the electronic and crystalline structure of the Bi 4 Te 3 layer reveal that a large electron transfer, epitaxial strain, and novel chemical reduction processes are critical factors for the enhancement of superconductivity. This novel route for enhancing T C in an important epitaxial system provides new insight on the nature of interfacial superconductivity and a platform to identify and utilize new electronic phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Emergence of liquid following laser melting of gold thin films

X-ray structural science is undergoing a revolution driven by the emergence of X-ray Free-electron Laser (XFEL) facilities. The structures of crystalline solids can now be studied on the picosecond time scale relevant to phonons, atomic vibrations which travel at acoustic velocities. In the work presented here, X-ray diffuse scattering is employed to characterize the time dependence of the liquid phase emerging from femtosecond laser-induced melting of polycrystalline gold thin films using an XFEL. In a previous analysis of Bragg peak profiles, we showed the supersonic disappearance of the solid phase and presented a model of pumped hot electrons carrying energy from the gold surface to scatter at internal grain boundaries. This generates melt fronts propagating relatively slowly into the crystal grains. By conversion of diffuse scattering to a partial X-ray pair distribution function, we demonstrate that it has the characteristic shape obtained by Fourier transformation of the measured F ( Q ). The diffuse signal fraction increases with a characteristic rise-time of 13 ps, roughly independent of the incident pump fluence and consequent final liquid fraction. This suggests the role of further melt-front nucleation processes beyond grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Scaled ILU Smoothers for Navier-Stokes Pressure Projection

Incomplete LU (ILU) smoothers are effective in the algebraic multigrid (AMG) V-cycle for reducing high-frequency components of the error. However, the requisite direct triangular solves are comparatively slow on GPUs. Previous work has demonstrated the advantages of Jacobi iteration as an alternative to direct solution of these systems. Depending on the threshold and fill-level parameters chosen, the factors can be highly nonnormal and Jacobi is unlikely to converge in a low number of iterations. We demonstrate that row scaling can reduce the departure from normality, allowing us to replace the inherently sequential solve with a rapidly converging Richardson iteration. There are several advantages beyond the lower compute time. Scaling is performed locally for a diagonal block of the global matrix because it is applied directly to the factor. Further, an ILUT Schur complement smoother maintains a constant GMRES iteration count as the number of MPI ranks increases, and thus parallel strong-scaling is improved. Our algorithms have been incorporated into hypre, and we demonstrate improved time to solution for linear systems arising in the Nalu-Wind and PeleLM pressure solvers. For large problem sizes, GMRES+AMG executes at least five times faster when using iterative triangular solves compared with direct solves on massively parallel GPUs.

algebraic multigrid↗
DOE OSTI2023

Explainable machine learning for hydrogen diffusion in metals and random binary alloys

Hydrogen diffusion in metals and alloys plays an important role in the discovery of new materials for fuel cell and energy storage technology. While analytic models use hand-selected features that have clear physical ties to hydrogen diffusion, they often lack accuracy when making quantitative predictions. Machine learning models are capable of making accurate predictions, but their inner workings are obscured, rendering it unclear which physical features are truly important. To develop interpretable machine learning models to predict the activation energies of hydrogen diffusion in metals and random binary alloys, we create a database for physical and chemical properties of the species and use it to fit six machine learning models. Our models achieve root-mean-squared errors between 98–119 meV on the testing data and accurately predict that elemental Ru has a large activation energy, while elemental Cr and Fe have small activation energies. By analyzing the feature importances of these fitted models, we identify relevant physical properties for predicting hydrogen diffusivity. While metrics for measuring the individual feature importances for machine learning models exist, correlations between the features lead to disagreement between models and limit the conclusions that can be drawn. Instead grouped feature importance, formed by combining the features via their correlations, agree across the six models and reveal that the two groups containing the packing factor and electronic specific heat are particularly significant for predicting hydrogen diffusion in metals and random binary alloys. In conclusion, this framework allows us to interpret machine learning models and enables rapid screening of new materials with the desired rates of hydrogen diffusion.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Molecular Glue Discovery: Current and Future Approaches

The intracellular interactions of biomolecules can be maneuvered to redirect signaling, reprogram the cell cycle, or decrease infectivity using only a few dozen atoms. Such "molecular glues," which can drive both novel and known interactions between protein partners, represent an enticing therapeutic strategy. Here, we review the methods and approaches that have led to the identification of small-molecule molecular glues. We first classify current FDA-approved molecular glues to facilitate the selection of discovery methods. We then survey two broad discovery method strategies, where we highlight the importance of factors such as experimental conditions, software packages, and genetic tools for success. In conclusion, we hope that this curation of methodologies for directed discovery will inspire diverse research efforts targeting a multitude of human diseases.

59 BASIC BIOLOGICAL SCIENCES↗