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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

CaloScore v2: single-shot calorimeter shower simulation with diffusion models

Diffusion generative models are promising alternatives for fast surrogate models, producing high-fidelity physics simulations. However, the generation time often requires an expensive denoising process with hundreds of function evaluations, restricting the current applicability of these models in a realistic setting. In this work, we report updates on the CaloScorearchitecture, detailing the changes in the diffusion process, which produces higher quality samples, and the use of progressive distillation, resulting in a diffusion model capable of generating new samples with a single function evaluation. Here we demonstrate these improvements using the Calorimeter Simulation Challenge 2022 dataset.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Development of a bi-solvent liquid scintillator with slow light emission

One of the most promising approaches for the next generation of neutrino experiments is the realization of large hybrid Cherenkov/scintillation detectors made possible by recent innovations in photodetection technology and liquid scintillator chemistry. The development of a potentially suitable future detector liquid with particularly slow light emission is discussed in the present publication. This cocktail is compared with respect to its fundamental characteristics (scintillation efficiency, transparency, and time profile of light emission) with liquid scintillators currently used in large-scale neutrino detectors. In addition, the optimization of the admixture of wavelength shifters for a scintillator with particularly high light emission is presented. Furthermore, the pulse-shape discrimination capabilities of the novel medium was studied using a pulsed particle accelerator driven neutron source. Beyond that, purification methods based on column chromatography and fractional vacuum distillation for the co-solvent DIN (Diisopropylnaphthalene) are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Prospects for Simulating Macromolecular Surfactant Chemistry at the Ocean-Atmosphere Boundary

Biogenic lipids and polymers are surveyed for their ability to adsorb at the water-air interfaces associated with bubbles, marine microlayers and particles in the overlying boundary layer. Representative ocean biogeochemical regimes are defined in order to estimate local concentrations for the major macromolecular classes. Surfactant equilibria and maximum excess are then derived based on a network of model compounds. Relative local coverage and upward mass transport follow directly, and specific chemical structures can be placed into regional rank order. Lipids and denatured protein-like polymers dominate at the selected locations. The assigned monolayer phase states are variable, whether assessed along bubbles or at the atmospheric spray droplet perimeter. Since oceanic film compositions prove to be irregular, effects on gas and organic transfer are expected to exhibit geographic dependence as well. Moreover, the core arguments extend across the sea-air interface into aerosol-cloud systems. Fundamental nascent chemical properties including mass to carbon ratio and density depend strongly on the geochemical state of source waters. High surface pressures may suppress the Kelvin effect, and marine organic hygroscopicities are almost entirely unconstrained. While bubble adsorption provides a well-known means for transporting lipidic or proteinaceous material into sea spray, the same cannot be said of polysaccharides. Carbohydrates tend to be strongly hydrophilic so that their excess carbon mass is low despite stacked polymeric geometries. Since sugars are abundant in the marine aerosol, gel-based mechanisms may be required to achieve uplift. Uncertainties in the surfactant logic distill to a global scale dearth of information regarding two dimensional kinetics and equilibria. Nonetheless simulations are recommended, to initiate the process of systems level quantification.

aerosol↗
DOE OSTI2022

Climate-aware decision-making: lessons for electric grid infrastructure planning and operations

Abstract Climate change poses significant risks to large-scale infrastructure systems and brings considerable uncertainties that challenge historical planning approaches. Here we focus on how climate awareness might be better incorporated into planning and decision-making in the electric power sector. To do so, we consider lessons from decision science literature where researchers have specifically focused on how to make better decisions under uncertainty. We perform a three-part review: of decision science literature on best practices for decision-making under uncertainty, of industry practice documents to understand how new uncertainties may affect the types of decisions electric utilities are making today, and of literature on electricity sector planning under climate change to assess how lessons from decision science might fit into sector-specific analyses. We discuss how characterizations of uncertainty from the decision science literature might guide approaches in the electricity sector to appropriately capture climate-related uncertainties. We also distill three key ideas from the decision science literature that can be incorporated into electricity sector planning to manage these new uncertainties: robustness, adaptive planning, and multi-stakeholder engagement. We offer example recommendations for how these key ideas might be incorporated into one essential type of planning activity, capacity expansion.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

kb_DRAM: annotation and metabolic profiling of genomes with DRAM in KBase

Microbial genome annotation is the process of identifying structural and functional elements in DNA sequences and subsequently attaching biological information to those elements. DRAM is a tool developed to annotate bacterial, archaeal, and viral genomes derived from pure cultures or metagenomes. DRAM goes beyond traditional annotation tools by distilling multiple gene annotations to genome level summaries of functional potential. Despite these benefits, a downside of DRAM is the requirement of large computational resources, which limits its accessibility. Further, it did not integrate with downstream metabolic modeling tools that require genome annotation. To alleviate these constraints, DRAM and the viral counterpart, DRAM-v, are now available and integrated with the freely accessible KBase cyberinfrastructure. With kb_DRAM users can generate DRAM annotations and functional summaries from microbial or viral genomes in a point-and-click interface, as well as generate genome-scale metabolic models from DRAM annotations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Combining protein sequences and structures with transformers and equivariant graph neural networks to predict protein function

Abstract Motivation Millions of protein sequences have been generated by numerous genome and transcriptome sequencing projects. However, experimentally determining the function of the proteins is still a time consuming, low-throughput, and expensive process, leading to a large protein sequence-function gap. Therefore, it is important to develop computational methods to accurately predict protein function to fill the gap. Even though many methods have been developed to use protein sequences as input to predict function, much fewer methods leverage protein structures in protein function prediction because there was lack of accurate protein structures for most proteins until recently. Results We developed TransFun—a method using a transformer-based protein language model and 3D-equivariant graph neural networks to distill information from both protein sequences and structures to predict protein function. It extracts feature embeddings from protein sequences using a pre-trained protein language model (ESM) via transfer learning and combines them with 3D structures of proteins predicted by AlphaFold2 through equivariant graph neural networks. Benchmarked on the CAFA3 test dataset and a new test dataset, TransFun outperforms several state-of-the-art methods, indicating that the language model and 3D-equivariant graph neural networks are effective methods to leverage protein sequences and structures to improve protein function prediction. Combining TransFun predictions and sequence similarity-based predictions can further increase prediction accuracy. Availability and implementation The source code of TransFun is available at https://github.com/jianlin-cheng/TransFun.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Wildfire impact on soil microbiome life history traits and roles in ecosystem carbon cycling

Abstract Wildfires, which are increasing in frequency and severity with climate change, reduce soil microbial biomass and alter microbial community composition and function. The soil microbiome plays a vital role in carbon (C) and nitrogen (N) cycling, but its complexity makes it challenging to predict post-wildfire soil microbial dynamics and resulting impacts on ecosystem biogeochemistry. The application of biogeochemically relevant conceptual trait-based frameworks to the soil microbiome can distill this complexity, enabling enhanced predictability of soil microbiome recovery following wildfire and subsequent impacts to biogeochemical cycles. Conceptual frameworks that have direct links to soil C and N cycling have been developed for the soil microbiome; the Y-A-S framework overviews soil microbiome life history strategies that have tradeoffs with one another and others have proposed frameworks specific to wildfire. Here, we aimed to delineate post-wildfire changes of bacterial traits in western US coniferous forests to inform how severe wildfire influences soil microbiome recovery and resultant biogeochemical cycling. We utilized a comprehensive metagenome-assembled genome catalog from post-wildfire soils representing 1 to 11 years following low- and high-severity burning to identify traits that enable the persistence of microbial taxa in burned soils and influence ecosystem C and N cycling. We found that high-severity wildfire initially selects for fast growers and, up to a decade post-fire, taxa that invest in genes for acquiring diverse resources from the external environment, which in combination could increase soil C losses. This work begins to disentangle how climate change–induced shifts in wildfire behavior might alter microbially mediated soil biogeochemical cycling.

Nelson, Amelia R.↗
DOE OSTI2024

A pilot oral history of plant synthetic biology

The whole field of synthetic biology (SynBio) is only about 20 years old, and plant SynBio is younger still. Nevertheless, within that short time, SynBio in general has drawn more scientific, philosophical, government, and private-sector interest than anything in biology since the recombinant DNA revolution. Plant SynBio, in particular, is now drawing more and more interest in relation to plants’ potential to help solve planetary problems such as carbon capture and storage and replacing fossil fuels and feedstocks. As plant SynBio is so young and so fast-developing, we felt it was too soon to try to analyze its history. Instead, we set out to capture the essence of plant SynBio's origins and early development through interviews with 8 of the field's founders, representing 5 countries and 3 continents. We then distilled these founders’ personal recollections and reflections into this review, centering the narrative on timelines for pivotal events, articles, funding programs, and quoting from interviews. We have archived the interview recordings and documented timeline entries. This work provides a resource for future historical scholarship.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Inositol Hexakisphosphate Increases The Transition Constant And The Affinity Of Horse Aquomethemoglobin for 5,5′‐dithiobis(2‐nitrobenzoate)

CysF9[93]β exists in two tertiary conformations, r and t , which are in dynamic equilibrium. The equilibrium constant, K equ , for the reaction of 5,5′‐dithiobis(2‐nitrobenzoate) — DTNB — with the CysF9[93]β sulfhydryl group of each hemoglobin was determined at 25°C as a function of pH. The reactivity of CysF9[93]β is affected by allosteric effectors such as the proton (H + ) and inositol hexakisphosphate (inositol‐P 6 ). The major and minor haemoglobins in horse haemolysate were separated using a column of Whatman's carboxymethylcellulose (CMC 52). The absorbance of the product of DTNB reaction, 5‐thio‐2‐nitrobenzoate, at different concentrations of DTNB and 50 μmol (haem) dm −3 was read at 412 nm. The absorbance was then substituted into an appropriate equation derived for the determination of the equilibrium constant, K equ , for the reaction. K equ decreased the orders of magnitude between pH 5.6 and 9.0 in the absence and presence of inositol‐P 6 . Inositol‐P 6 increased the affinity of the major and minor Hb for DTNB but decreased the affinity of the minor aquomet‐Hb. The results show that inositol‐P 6 increases the relative population of the t tertiary conformation. So, it increases the affinity of CysF9[93]β by changing the relative distribution of two protein conformations. Study objective The study also seeks to find the equilibrium between the r and t isomers in the reaction of DTNB with CysF9[93]β sulphydryl group of the horse aquomethemoglobins. The relative populations of these two conformations from the pH dependence of equilibrium and kinetic parameters and the effect of inositol‐P 6 on these relative populations were determined. Methods Preparation and separation of horse hemoglobin had been described in Omotosho et al ., 2017. Preparation and determination of aquomethemoglobin concentration: Aquomethemoglobin was prepared by the addition of a two‐fold excess of potassium ferricyanide, K 3 Fe(CN) 6 , to oxyhemoglobin of a known concentration. An approximately 1 mol dm −3 K 3 Fe(CN) 6 solution was prepared by dissolving 0.33 g of the reagent in 1 cm 3 of distilled water. The volume of the K 3 Fe(CN) 6 , v cm 3 , added to V cm 3 of hemoglobin to give a two‐fold excess is related to the concentration of the hemoglobin solution. Results Domestic horse contains two hemoglobin types: A, the fast hemoglobin, and B, the slow hemoglobin. The two haemoglobins have identical α chains. Horse hemoglobin consists of two electrophoretically distinct components. From Figs. 1 and 2 it is seen that inositol‐P6 increases the affinity of CysF9[93]β of each haemoglobin for DTNB by about three orders of magnitude throughout the pH range 5.6 to 9.2. Conclusion Figs. 1 and 2 report the dependence of K equ, the equilibrium constant of the reaction of DTNB with CysF9[93]β, on pH. The values of K equ decrease by about two orders of magnitude for slow aquomet hemoglobin over the range 5.6 ≥ pH ≤ 9.0 whereas there in the fast hemoglobin, the values of K equ increases by about six orders of magnitude and there is an increase in the affinity for the aquomet derivative. This shows that there is more insight on the nature of the tertiary structure transition in both T and R state hemoglobin. Support or Funding Information We appreciate Covenant University Centre for Research, Innovation and Development for the financial support.

Omotosho, Omolola E.↗
DOE OSTI2026

Accessing the gluon momentum fraction of nucleons through the gradient flow

We calculate the gluon momentum fraction of the nucleon using lattice QCD, with a nonperturbative renormalization technique based on the gradient flow. The gluon momentum fraction is determined on a single Wilson-clover ensemble using 𝑁 𝑓 =2 +1 flavors with pion mass 358 MeV and lattice spacing 0.094 fm. We employ the variational method to reduce excited-state contamination and apply the distillation framework to ensure a large operator basis. To reduce systematic uncertainties, we apply Bayesian model averaging to all fit procedures. We apply matching coefficients to the flow-time dependent lattice results to recover the gluon momentum fraction in the $\overline{MS}$-scheme at 2 GeV. Our final result is ⟨𝑥⟩ 𝑔 ⁢(𝜇 =2 GeV) =0.482⁢(35), where we quote only statistical uncertainties.

Lattice QCD↗
DOE OSTI2026

Efficient Simulation of Logical Magic State Preparation Protocols

Developing space- and time-efficient logical magic state preparation (MSP) protocols will likely be an essential step toward building a large-scale fault-tolerant quantum computer. Motivated by this need, we introduce a scalable method for simulating logical MSP protocols under the standard circuit-level noise model. When applied to protocols based on code-switching, magic state cultivation, and magic state distillation, our method yields a complexity polynomial in (i) the number of qubits and (ii) the nonstabilizerness, e.g., stabilizer rank or Pauli rank, of the target encoded magic state. The efficiency of our simulation method is rooted in a curious fact: every circuit-level Pauli error in these protocols propagates to a Clifford error at the end. This property is satisfied by a large family of protocols, including those that repeatedly measure a transversal Clifford that squares to a Pauli. We provide a proof-of-principle numerical simulation that prepares a magic state using such logical Clifford measurements. Our work enables practical simulation of logical MSP protocols without resorting to approximations or resource-intensive state-vector simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Hybrid Entanglement Distribution between Remote Microwave Quantum Computers Empowered by Machine Learning

Superconducting microwave circuits with Josephson junctions, the major platform for quantum computing, can only reach the full capability when connected. This requires an efficient protocol to distribute microwave entanglement. While quantum computers typically use discrete-variable (DV) methods for information encoding, the entire continuous-variable (CV) degree of freedom in electromagnetic fields must be utilized to achieve the highest entanglement distribution rate. Here, we propose a hybrid protocol to resolve the incompatibility between DV microwave quantum computers and CV quantum communications. CV microwave entanglement is distributed using optical swapping of optical-microwave entanglement pairs. To interface with DV microwave quantum computers, we further design a hybrid circuit to simultaneously convert and distill high-quality DV entanglement from noisy CV entanglement. The hybrid circuit is trained with machine-learning algorithms, ensuring high entanglement fidelity and generation rate. In conclusion, our work not only provides a practical method to realize efficient quantum links for superconducting microwave quantum computers, but also opens avenues to bridge the gap between DV and CV quantum systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Disorder from order among anisotropic next-nearest-neighbor Ising spin chains in SrHo 2 O 4

In this study, we describe why Ising spin chains with competing interactions in SrHo 2 O 4 segregate into ordered and disordered ensembles at low temperatures (T). Using elastic neutron scattering, magnetization, and specific heat measurements, the two distinct spin chains are inferred to have Néel (↑↓↑↓) and double-Néel (↑↑↓↓) ground states, respectively. Below T N = 0.68(2)K, the Néel chains develop three-dimensional long range order (LRO), which arrests further thermal equilibration of the double-Néel chains so they remain in a disordered incommensurate state for T below T S = 0.52(2)K. SrHo 2 O 4 distills an important feature of incommensurate low dimensional magnetism: kinetically trapped topological defects in a quasi–d–dimensional spin system can preclude order in d + 1 dimensions.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Toward the excited isoscalar meson spectrum from lattice QCD

We report on the extraction of an excited spectrum of isoscalar mesons using lattice QCD. Calculations on several lattice volumes are performed with a range of light quark masses corresponding to pion masses down to about ~400 MeV. The distillation method enables us to evaluate the required disconnected contributions with high statistical precision for a large number of meson interpolating fields. We find relatively little mixing between light and strange in most J PC channels; one notable exception is the pseudoscalar sector where the approximate SU(3) F octet, singlet structure of the η, η' is reproduced. We extract exotic J PC states, identified as hybrid mesons in which an excited gluonic field is coupled to a color-octet qqbar pair, along with non-exotic hybrid mesons embedded in a qq¯-like spectrum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Spectroscopy of doubly charmed baryons from lattice QCD

This study presents the ground and excited state spectra of doubly charmed baryons from lattice QCD with dynamical quark fields. Calculations are performed on anisotropic lattices of size 16³ × 128, with inverse spacing in temporal direction a t ⁻¹=5.67(4) GeV and with a pion mass of about 390 MeV. A large set of baryonic operators that respect the symmetries of the lattice yet which retain a memory of their continuum analogues are used. These operators transform as irreducible representations of SU(3) F symmetry for flavor, SU(4) symmetry for Dirac spins of quarks and O(3) for spatial symmetry. The distillation method is utilized to generate baryon correlation functions which are analyzed using the variational fitting method to extract excited states. The lattice spectra obtained have baryonic states with well-defined total spins up to 7/2 and the pattern of low-lying states does not support the diquark picture for doubly charmed baryons. On the contrary the calculated spectra are remarkably similar to the expectations from models with an SU(6)×O(3) symmetry. Various spin-dependent energy splittings between the extracted states are also evaluated.

Padmanath, M.↗
DOE OSTI2022

Entanglement Purification and Protection in a Superconducting Quantum Network

High-fidelity quantum entanglement is a key resource for quantum communication and distributed quantum computing, enabling quantum state teleportation, dense coding, and quantum encryption. Any sources of decoherence in the communication channel, however, degrade entanglement fidelity, thereby increasing the error rates of entangled state protocols. Entanglement purification provides a method to alleviate these nonidealities by distilling impure states into higher-fidelity entangled states. In this work, we demonstrate the entanglement purification of Bell pairs shared between two remote superconducting quantum nodes connected by a moderately lossy, 1-meter long superconducting communication cable. We use a purification process to correct the dominant amplitude damping errors caused by transmission through the cable, with fractional increases in fidelity as large as 25%, achieved for higher damping errors. The best final fidelity the purification achieves is 94.09 ± 0.98%. In addition, we use both dynamical decoupling and Rabi driving to protect the entangled states from local noise, increasing the effective qubit dephasing time by a factor of 4, from 3 to 12 μs. These methods demonstrate the potential for the generation and preservation of very high-fidelity entanglement in a superconducting quantum communication network.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Energy Principles of Scientific Breakeven in an Inertial Fusion Experiment

Fusion “scientific breakeven” (i.e., unity target gain G target , total fusion energy out > laser energy input) has been achieved for the first time (here, G target ∼ 1.5 ). This Letter reports on the physics principles of the design changes that led to the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce target gain greater than unity and exceeded the previously obtained conditions needed for ignition by the Lawson criterion. Key elements of the success came from reducing “coast time” (the time duration between the end of the laser pulse and implosion peak compression) and maximizing the internal energy delivered to the “hot spot” (the yield producing part of the fusion fuel). The link between coast time and maximally efficient conversion of kinetic energy into internal energy is explained. The energetics consequences of asymmetry and hydrodynamic-induced mixing were part of high-yield big radius implosion design experimental and design strategy. Herein, it is shown how asymmetry and mixing consolidate into one key relationship. It is shown that mixing distills into a kinetic energy cost similar to the impact of implosion asymmetry, shifting the threshold for ignition to higher implosion kinetic energy—a factor not normally included in most statements of the generalized Lawson criterion, but the key needed modifications clearly emerge. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗