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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

ConKer: An algorithm for evaluating correlations of arbitrary order

Context. High order correlations in the cosmic matter density have become increasingly valuable in cosmological analyses. However, computing these correlation functions is computationally expensive. Aims. We aim to circumvent these challenges by developing a new algorithm called ConKer for estimating correlation functions. Methods. This algorithm performs convolutions of matter distributions with spherical kernels using FFT. Since matter distributions and kernels are defined on a grid, it results in some loss of accuracy in the distance and angle definitions. We study the algorithm setting at which these limitations become critical and suggest ways to minimize them. Results. ConKer is applied to the CMASS sample of the SDSS DR12 galaxy survey and corresponding mock catalogs, and is used to compute the correlation functions up to correlation order n = 5. We compare the n = 2 and n = 3 cases to traditional algorithms to verify the accuracy of the new algorithm. We perform a timing study of the algorithm and find that three of the four distinct processes within the algorithm are nearly independent of the catalog size N , while one subdominant component scales as O ( N ). The dominant portion of the calculation has complexity of O ( N c 4/3 log N c ), where N c is the of cells in a three-dimensional grid corresponding to the matter density. Conclusions. We find ConKer to be a fast and accurate method of probing high order correlations in the cosmic matter density, then discuss its application to upcoming surveys of large-scale structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing

In this paper, we propose a method to perform empirical analysis of the loss landscape of machine learning (ML) models. The method is applied to two ML models for scientific sensing, which necessitates quantization to be deployed and are subject to noise and perturbations due to experimental conditions. Our method allows assessing the robustness of ML models to such effects as a function of quantization precision and under different regularization techniques -- two crucial concerns that remained underexplored so far. By investigating the interplay between performance, efficiency, and robustness by means of loss landscape analysis, we both established a strong correlation between gently-shaped landscapes and robustness to input and weight perturbations and observed other intriguing and non-obvious phenomena. Our method allows a systematic exploration of such trade-offs a priori, i.e., without training and testing multiple models, leading to more efficient development workflows. This work also highlights the importance of incorporating robustness into the Pareto optimization of ML models, enabling more reliable and adaptive scientific sensing systems.

Baldi, Tommaso [Pisa, Scuola Normale Superiore]↗
DOE OSTI2021

Deletion of a non-canonical regulatory sequence causes loss of Scn1a expression and epileptic phenotypes in mice

Abstract Background Genes with multiple co-active promoters appear common in brain, yet little is known about functional requirements for these potentially redundant genomic regulatory elements. SCN1A, which encodes the Na V 1.1 sodium channel alpha subunit, is one such gene with two co-active promoters. Mutations in SCN1A are associated with epilepsy, including Dravet syndrome (DS). The majority of DS patients harbor coding mutations causing SCN1A haploinsufficiency; however, putative causal non-coding promoter mutations have been identified. Methods To determine the functional role of one of these potentially redundant Scn1a promoters, we focused on the non-coding Scn1a 1b regulatory region, previously described as a non-canonical alternative transcriptional start site. We generated a transgenic mouse line with deletion of the extended evolutionarily conserved 1b non-coding interval and characterized changes in gene and protein expression, and assessed seizure activity and alterations in behavior. Results Mice harboring a deletion of the 1b non-coding interval exhibited surprisingly severe reductions of Scn1a and Na V 1.1 expression throughout the brain. This was accompanied by electroencephalographic and thermal-evoked seizures, and behavioral deficits. Conclusions This work contributes to functional dissection of the regulatory wiring of a major epilepsy risk gene, SCN1A . We identified the 1b region as a critical disease-relevant regulatory element and provide evidence that non-canonical and seemingly redundant promoters can have essential function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Direct Transformation of SiH 4 to a Molecular L(H) 2 Co=Si=Co(H) 2 L Silicide Complex

The synthesis of bimetallic molecular silicide complexes is reported, based on the use of multiple Si–H bond activations in SiH 4 at the metal centers of 14-electron LCo I fragments (L = Tp", HB(3,5-diisopropylpyrazolyl) 3 – ; [BP 2 tBu Pz], PhB(CH 2 P t Bu 2 ) 2 (pyrazolyl)). Upon exposure of (Tp"Co) 2 (μ-N 2 ) (1) to SiH 4 , a mixture of (Tp"Co) 2 (μ-H) (2) and (Tp"Co) 2 (μ-H) 2 (3) was formed and no evidence for Si–H oxidative addition products was observed. In contrast, [BP 2 tBu Pz]-supported Co complexes led to Si–H oxidative additions with the generation of silylene and silicide complexes as products. Notably, the reaction of ([BP 2 tBu Pz]Co) 2 (μ-N 2 ) (5) with SiH 4 gave the dicobalt silicide complex [BP 2 tBu Pz](H) 2 Co=Si=Co(H) 2 [BP 2 tBu Pz] (8) in high yield, representing the first direct route to a symmetrical bimetallic silicide. Here, the effect of the [BP 2 tBu Pz] ligand on Co–Si bonding in 7 and 8 was explored by analysis of solid-state molecular structures and density functional theory (DFT) investigations. Upon exposure to CO or DMAP (DMAP = 4-dimethylaminopyridine), 8 converted to the corresponding [BP 2 tBu Pz]Co(L) x adducts (L = CO, x = 2; L = DMAP, x = 1) with concomitant loss of SiH 4 , despite the lack of significant Si–H interactions in the starting complex. On heating to 60 °C, 8 underwent reaction with MeCl to produce small quantities of Me x SiH 4–x (x = 1–3), demonstrating functionalization of the μ-silicon atom in a molecular silicide to form organosilanes.

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

Low-abundance populations distinguish microbiome performance in plant cell wall deconstruction

Abstract Background Plant cell walls are interwoven structures recalcitrant to degradation. Native and adapted microbiomes can be particularly effective at plant cell wall deconstruction. Although most understanding of biological cell wall deconstruction has been obtained from isolates, cultivated microbiomes that break down cell walls have emerged as new sources for biotechnologically relevant microbes and enzymes. These microbiomes provide a unique resource to identify key interacting functional microbial groups and to guide the design of specialized synthetic microbial communities. Results To establish a system assessing comparative microbiome performance, parallel microbiomes were cultivated on sorghum ( Sorghum bicolor L. Moench) from compost inocula. Biomass loss and biochemical assays indicated that these microbiomes diverged in their ability to deconstruct biomass. Network reconstructions from gene expression dynamics identified key groups and potential interactions within the adapted sorghum-degrading communities, including Actinotalea , Filomicrobium , and Gemmatimonadetes populations. Functional analysis demonstrated that the microbiomes proceeded through successive stages that are linked to enzymes that deconstruct plant cell wall polymers. The combination of network and functional analysis highlighted the importance of cellulose-degrading Actinobacteria in differentiating the performance of these microbiomes. Conclusions The two-tier cultivation of compost-derived microbiomes on sorghum led to the establishment of microbiomes for which community structure and performance could be assessed. The work reinforces the observation that subtle differences in community composition and the genomic content of strains may lead to significant differences in community performance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Impoverishing Roots Will Improve Wheat Yield and Profitability Through Increased Water and Nitrogen Use Efficiencies

We report that more than a 60% increase in crop production is required by the 2050's to feed a growing world population. Understanding how plant functional traits and field management affect crop yields has the potential to improve agricultural productivity, minimize economic and environmental losses, and maximize food security. We explored the influence of winter wheat root characteristics and management on winter wheat growth, yield, and profit using a mechanistic and well-tested ecosystem and crop model, ecosys. We applied and further tested ecosys at an agricultural farm growing winter wheat in Ardmore, Oklahoma, United States. The model accurately predicted observed shoot carbon (R 2 = 0.95), soil moisture (R 2 = 0.67), soil temperature (R 2 = 0.91), and yield (percent error = 17%). Numerical optimization experiments were conducted to explore potential improvements of winter wheat yield and profit by modifying root characteristics, including root radius and root:shoot carbon transfer conductance, and fertilizer inputs. Our results show the potential for simultaneously improving winter wheat yields and profits. The optimum conditions were found to be in the range of root radius between 0.1 and 0.3 mm, carbon transfer conductance between 0.004 and 0.01 h -1 , and the currently applied fertilizer rate of 112 kg ha -1 . Under these conditions, improvements in yields and profits of up to approximately 25% and 110%, respectively, were modeled compared to those under baseline root traits. These improvements were achieved by impoverishing root structures, thereby increasing nutrient allocation to grains. Our results also demonstrate and motivate model structures that integrate the complex network of plant physiology, soil nutrient biogeochemistry, hydrology, and management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Throughput Measurements and Profile Analysis of Cloud Networks

Cloud networks utilize virtual connections to connect virtual machines distributed across cloud sites. They are increasingly deployed due to flexible provisioning using software and cost-effectiveness in not requiring to build physical network infrastructure. However, their extensive virtualization makes it unclear how well the established practices of conventional networks translate to them. Here, we study throughput measurements over a Google Cloud network using a matching hardware emulated conventional network, which provide production and exploratory conditions, respectively. The measurements span connections representing local, cross-continental and around the Earth distances. We study the effects of parallel flows, congestion control algorithms and retransmissions on the network throughput profile expressed as a function of RTT. We compare the throughput profile of Google Cloud network with those of emulated network under various loss conditions, including those too disruptive or expensive in the former. Our analysis based on the concave-convex shape and utilization-concavity coefficients of throughput profiles indicates an overall agreement of performance between the two networks, thereby justifying the use of conventional network emulations to analyze cloud networks. In terms of practical use, our study establishes that BBR and BBRv2 alpha TCP achieve higher throughput compared to loss-based congestion control algorithms under most network configurations, especially, under losses at large RTT.

Phanekham, Derek [Southern Methodist Univ., Dallas↗
DOE OSTI2025

Optimal Control Strategy With Efficiency and Reliability Improvement for Offshore DC Microgrids

Offshore microgrids, due to their remote location and lack of external energy support, face significant challenges in wide-range load operation and maintenance. Consequently, efficiency and reliability are critical concerns for converters in offshore dc microgrids. This article presents an optimal control strategy aimed at enhancing both efficiency and reliability. A normalized nonlinear relationship between power loss and thermal stress of a paralleled converter is first established. Based on this, a dual-objective optimization function with an active weight function as well as a system overall performance index is established. The active weight function dynamically adjusts the control priority based on converter efficiency and switching device thermal stress. Then, the optimal power-sharing strategy is derived by the Lagrange multiplier method with the proposed optimal function. Additionally, to accommodate a wide load range, an optimal selection strategy for operating converter combinations is proposed, requiring only low-bandwidth communication. Experiment verification is given to validate the effectiveness of the proposed control strategy. The experiment results demonstrate that the proposed control strategy can improve the overall performance of offshore microgrids by optimizing efficiency and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]

Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings. DC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated. The Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.

Frank, Stephen↗
DOE OSTI2024

Dynamic Temporal Graph Sequence Data for Resilience-Oriented Distribution Network Reconfiguration

This dataset comprises temporal dynamic graph sequences generated from power grid simulations focused on grid reconfiguration to enhance resilience. The simulations model failure propagation under varying conditions, with nodes assigned distinct failure probabilities. For each time step, the dataset captures the evolution of node states (functional or failed) and features critical to grid operations, such as pv_output, load_profile, load_dispatch, dg_output, loss, and voltage. Node types include sources, normal loads, and nodes with specific equipment like PVs, micro turbines, or shunt capacitors. The dataset is structured to support the training of dynamic graph neural networks, facilitating research on node feature prediction and edge dynamics under failure scenarios. Three distinct configurations are included, providing a robust foundation for modeling power grid resilience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Critical Metallicity of Cool Supergiant Formation. I. Effects on Stellar-mass Loss and Feedback

This paper systematically studies the relation between metallicity and mass loss of massive stars. We perform one-dimensional stellar evolution simulations and build a grid of ~2000 models with initial masses ranging between 11 and 60 M ⊙ and absolute metallicities Z between 0.00001 and 0.02. Steady-state winds, comprising hot main-sequence winds and cool supergiant winds, are the main drivers of the mass loss of massive stars in our models. We calculate the total mass loss over the stellar lifetime for each model. Our results reveal the existence of a critical metallicity Z c at Z ~ 10 –3 , where the mass loss exhibits a dramatic jump. If Z > Z c , massive stars tend to evolve into cool supergiants, and a robust cool wind is operational. In contrast, if Z < Z c , massive stars usually remain as blue supergiants, wherein the cool wind is not activated and the mass loss is generally weak. Moreover, we calculate the wind feedback in a 10 5 M ⊙ star cluster with the Salpeter initial mass function. The kinetic energy released by winds does not exhibit any significant transition at Z c because the wind velocity of a cool supergiant wind is low and contributes little to the kinetic energy. The effects of critical metallicity provide implications for the fates of metal-poor stars in the early universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Jet modification via 𝜋 0 -hadron correlations in Au + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV

High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4–12 GeV/𝑐 and 0.5–7 GeV/𝑐, respectively, have been measured by the PHENIX experiment in 2014 for Au + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au + Au collisions and 𝑝 + 𝑝 collisions, 𝐼 𝐴⁢𝐴 and Δ 𝐴⁢𝐴 , as a function of the trigger-hadron azimuthal separation, Δ⁢𝜙, are measured for the first time at the BNL Relativistic Heavy Ion Collider. Finally, these results better quantify how the yield of low-𝑝 𝑇 associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Electronic structure of Humble defects in Ge and Ge 0.8⁢ Si 0.2

The group-IV diamond-structure elements are known to host a variety of planar defects, including {001} planar defects in C and {001}, {111}, and {113} planar defects in Si and Ge. Among the {001} planar defects, the Humble defect, known for some time to occur in Ge, has recently also been observed in Si-Ge alloys, but the details of its electronic structure remain poorly understood. Here, in this work, we perform first-principles density-functional calculations to study Humble defects in both Ge and Ge 0.8⁢ Si 0.2 . We also measure the Si L 2,3 -edge electron energy-loss spectra both at the defect and in a bulk-like region far from the defect and compare with theoretical calculations on corresponding Si sites in our first-principles calculations. We find that inclusion of core-hole effects in the theory is essential for reproducing the observed L 2,3 edge spectra, and that once they are included, the results provide a set of fingerprints for different types of local atomic bonding environments in Ge 0.8⁢ Si 0.2 . Our first-principles calculations reveal that the Humble defects have a tendency to enlarge the electronic band gap, which may have potential uses in band engineering. The use of hybrid functionals for an improved description of the band gap in these systems is also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Solution Processed Ternary Tin (II) Alloy as Hole–Transport Layer of Sn–Pb Perovskite Solar Cells for Enhanced Efficiency and Stability

Tin-lead (Sn-Pb) narrow bandgap (NBG) perovskites show great potential in both single-junction and all-perovskite tandem solar cells. Sn-Pb perovskite solar cells (PSCs) are still limited by low charge collection efficiency and poor stability. Here, we report a ternary Sn (II) alloy of SnOCl as the hole-transport material (HTM) with a work function of 4.95 eV for Sn-Pb PSCs. The solution processed SnOCl layer has a texture structure which not only reduces the optical loss of the devices but also changes grain growth of Sn-Pb perovskites and boosts the carrier diffusion length to 3.63 μm. The formation of small perovskite grains at the HTM/perovskite interface is suppressed. These result in an almost constant internal quantum efficiency of 96 ± 2% across the absorption spectrum of Sn-Pb perovskites. The SnOCl HTM significantly enhances the stability of Sn-Pb PSCs with 87% of its initial efficiency retained after 1-sun illumination for 1,200 h, and keep 85% efficiency under 85°C thermal stress for 1,500 h. Furthermore, the hybrid HTM further improve the stabilized efficiencies of single-function Sn-Pb PSCs and all-perovskite tandem solar cells to 23.2% and 25.9%, respectively. This discovery opens an avenue to the multi-component metal alloys as HTM in PSCs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Surviving Under Pressure: The Role of Solvent, Crystal Size, and Morphology During Pelletization of Metal–Organic Frameworks

As metal–organic frameworks (MOFs) gain traction for applications, such as hydrogen storage, it is essential to form the as-synthesized powder materials into shaped bodies with high packing densities to maximize their volumetric performance. Mechanical compaction, which involves compressing the materials at high pressure, has been reported to yield high monolith density but often results in a significant loss in accessible porosity. Herein, we sought to systematically control (1) crystal size, (2) solvation, and (3) compacting pressure in the pelletization process to achieve high packing density without compromising the porosity that makes MOFs functional. It was determined that solvation is the most critical factor among the three factors examined. Solvation that exceeds the pore volume prevents the framework from collapsing, allowing for porosity to be maintained through pelletization. Higher pelletization pressure results in higher packing density, with extensive loss of porosity being observed at a higher pressure if the solvation is below the pore volume. Lastly, we observed that the morphology and size of the MOF particles result in variation in the highest achievable packing efficiency, but these numbers (75%) are still greater than many existing techniques used to form MOFs. Furthermore, we concluded that the application of pressure through pelletization is a suitable and widely applicable technique for forming high-density MOF-monoliths.

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

Understanding how minority relativistic electron populations may dominate charge state balance and radiative cooling of a post-thermal quench tokamak plasma

Minority relativistic electron populations can occur in a range of complex plasmas. Of specific interest is when runaway electrons form among the presence of high-atomic-number ion species in a tokamak plasma discharge. It has been recently demonstrated that ion charge state distributions and radiation losses at low bulk electron temperatures can be dominated by relativistic electrons, even though their density is orders of magnitude lower. Furthermore, this was attributed to the relativistic enhancement of electron impact inelastic cross sections. In this work, we provide a closer inspection of the atomic physics underpinning this effect. We also demonstrate the consequences of runaway enhanced scattering on post-disruption tokamak fusion discharges with neon and argon impurities present. Effects on charge state distributions, radiation and spectral characteristics, and reduced-order modeling considerations are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Optically Excited Lasing in a Cavity‐Based, High‐Current‐Density Quantum Dot Electroluminescent Device

Abstract Laser diodes based on solution‐processable materials can benefit numerous technologies including integrated electronics and photonics, telecommunications, and medical diagnostics. An attractive system for implementing these devices is colloidal semiconductor quantum dots (QDs). The progress towards a QD laser diode has been hampered by rapid nonradiative Auger decay of optical‐gain‐active multicarrier states, fast device degradation at high current densities required for laser action, and unfavorable competition between optical gain and optical losses in a multicomponent device stack. Here we resolve some of these challenges and demonstrate optically excited lasing from fully functional high‐current density electroluminescent (EL) devices with an integrated optical resonator. This advance has become possible due to excellent optical gain properties of continuously graded QDs and a refined device architecture, which allows for highly efficient light amplification in a thin, EL‐active QD layer.

36 MATERIALS SCIENCE↗