Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Yield function”

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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Leveraging neural control variates for enhanced precision in lattice field theory

Results obtained with stochastic methods have an inherent uncertainty due to the finite number of samples that can be achieved in practice. In lattice QCD this problem is particularly salient in some observables like, for instance, observables involving one or more baryons and it is the main problem preventing the calculation of nuclear forces from first principles. The method of control variables has been used extensively in statistics and it amounts to computing the expectation value of the difference between the observable of interest and another observable whose average is known to be zero but is correlated with the observable of interest. Recently, control variates methods emerged as a promising solution in the context of lattice field theories. In our current study, instead of relying on an educated guess to determine the control variate, we utilize a neural network to parametrize this function. Using 1 + 1 dimensional scalar field theory as a testbed, we demonstrate that this neural network approach yields substantial improvements. Notably, our findings indicate that the neural network ansatz is particularly effective in the strong coupling regime. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2018

Pion and Kaon Valence-quark Parton Quasidistributions

Algebraic Ansatze for the Poincare-covariant Bethe-Salpeter wave functions of the pion and kaon arc used to calculate their light-front wave functions, parton distribution amplitudes, parton quasidistribution amplitudes, valence parton distribution functions, and parton quasidistribution functions (PqDFs). The light-front wave functions arc broad, concave functions, and the scale of flavor-symmetry violation in the kaon is roughly 15%, being set by the ratio of emergent masses in the s- and u-quark sectors. Parton quasidistribution amplitudes computed with longitudinal momentum P z = 1.75 GeV provide a semiquantitatively accurate representation of the objective parton distribution amplitude, but even with P z = 3 GeV, they cannot provide information about this amplitude's end point behavior. On the valence-quark domain, similar outcomes characterize PqDFs. Lastly, in this connection, however, the ratio of kaon-to-pion u-quark PqDFs is found to provide a good approximation to the true parton distribution function ratio on 0.4 ≲ x ≲ 0.8, suggesting that with existing resources computations of ratios of parton quasidistributions can yield results that support empirical comparison.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Forward Modeling of Gamma Reaction History Signatures From Anticipated Deuterium-Tritium Filled MagLIF Implosions on Sandia’s Z-Machine

Nuclear reaction history measurements provide a bang time and burn width of Inertial Confinement Fusion (ICF) implosions and are essential for understanding implosion performance to constrain ICF capsule design. When fusion fuel contains Deuterium (D) and Tritium (T) gas, reaction history is informed by measuring the 16.75 MeV gamma rays generated from the D(T,γ) 5 He reaction. Such DT based reaction history measurements have not been made on the Magnetized Laser Inertial Fusion (MagLIF) platform on Sandia’s Z-Machine due to the lack of Tritium being used. The recent development of ICF implosions with tritiated fuel will open the possibility of measuring the gamma reaction history on the Z-Machine. A forward model of the Gamma Reaction History diagnostic on Z (GRH-Z) has been developed using the MCNP6.3 (Monte-Carlo N-Particle) radiation transport code. The model included the Z-Machine geometry of interest to characterize the impact of neutron induced gamma rays on the DT reaction history measurements. In addition, the impulse response functions of the GRH-Z diagnostic to understand the temporal response of the detector, and the minimum yields required to make a reaction history measurement were calculated. This approach also predicted that with T 2 gas doping of MagLIF implosions a reaction history may be made for high performance shots >8e12-2.4e13 depending on the chosen threshold for the detector, with a maximum signal to background ratio of 25%. It was found that for long duration ICF implosions that additional collimation will be needed to prevent the neutron induced gamma rays from modifying the shape of the measured DT reaction history curve.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Gradient-based surface nuclear magnetic resonance for groundwater investigation

In medical magnetic resonance imaging, spatial localization (imaging) is based upon the application of controlled magnetic field gradients on top of the main magnetic field to spatially modulate the frequency and/or phase of the nuclear magnetic resonance (NMR) signal across the volume of investigation. In this work, we have applied similar physical principles to produce controlled magnetic field gradients during surface NMR-based groundwater investigations. In this approach, a gradient pulse of variable amplitude or duration is applied immediately after the excitation pulse to cause predictable phase encoding of the NMR signal as a function of depth. This approach is also applicable to emerging surface NMR detection methods that use a prepolarization field with fast nonadiabatic turn-off to generate detectable NMR signals from the shallow subsurface. In this case, the gradient pulse is applied after terminating the prepolarization field and provides a heretofore unavailable means of localizing the NMR response as a function of depth. The application of gradients can also be combined with tip-angle-based modulation to yield higher imaging resolution than can be achieved through either gradient- or tip-angle-based imaging alone. We implemented this new gradient-based capability into a surface NMR gradient generation accessory that is compatible with the GMR-Flex instrument and developed surface NMR-specific forward modeling and linear inverse models. We validated the accuracy of this novel gradient-based sNMR technology using computer simulations, experiments using a small pool filled with a discrete layer of bulk water, and field experiments at well-characterized groundwater test sites along Ebey Island, WA, and Larned, KS. The gradient-based sNMR imaging observations were compared with high-resolution direct push NMR results observed at these sites. The results of computer simulations and field experiments indicate improvements in both the detection (signal-to-noise ratio) and spatial resolution of shallow subsurface water content using gradient-based surface NMR, compared with traditional surface NMR imaging methods.

Geochemistry & Geophysics↗
DOE OSTI2017

Building Foundations for Nuclear Security Enterprise Analysis Utilizing Nuclear Weapon Data

The Nuclear Security Enterprise, managed by the National Nuclear Security Administration - a semiautonomous agency within the Department of Energy - has been associated with numerous assessments with respect to the estimating, management capabilities, and practices pertaining to nuclear weapon modernization efforts. This report identifies challenges in estimating and analyzing the Nuclear Security Enterprise through an analysis of analogous timeframe conditions utilizing two types of nuclear weapon data - (1) a measure of effort and (2) a function of time. The analysis of analogous timeframe conditions that utilizes only two types of nuclear weapon data yields four summary observations that estimators and analysts of the Nuclear Security Enterprise will find useful.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify these services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index (SPI), standardized soil water content index (SSWI), and standardized streamflow index (SSI). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI12 than SPI12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Enhancing the accuracy of density functional tight binding models through ChIMES many-body interaction potentials

Semi-empirical quantum models such as Density Functional Tight Binding (DFTB) are attractive methods for obtaining quantum simulation data at longer time and length scales than possible with standard approaches. However, application of these models can require lengthy effort due to the lack of a systematic approach for their development. In this work, we discuss the use of the Chebyshev Interaction Model for Efficient Simulation (ChIMES) to create rapidly parameterized DFTB models, which exhibit strong transferability due to the inclusion of many-body interactions that might otherwise be inaccurate. We apply our modeling approach to silicon polymorphs and review previous work on titanium hydride. We also review the creation of a general purpose DFTB/ChIMES model for organic molecules and compounds that approaches hybrid functional and coupled cluster accuracy with two orders of magnitude fewer parameters than similar neural network approaches. In all cases, DFTB/ChIMES yields similar accuracy to the underlying quantum method with orders of magnitude improvement in computational cost. In conclusion, our developments provide a way to create computationally efficient and highly accurate simulations over varying extreme thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly, and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Surface Phase Stability of Fe 2 O 3 (001) in Hydrogen Reducing Environments: A DFT and XPS Analysis

Here, this study combines density functional theory (DFT) and ab initio thermodynamics calculations with X-ray photoelectron spectroscopy (XPS) investigations to identify the reduction properties of the Fe 2 O 3 (001) surface with implications for corrosion resistance, hydrogen transport, and energy safety. Ab initio thermodynamics modeling predicts fully hydroxylated surface stability across a broad range of pressures (1 × 10 –23 to 1 × 10 5 mbar) and temperatures below 700 K, consistent with previous experimental studies. Above 800 K, exposures to 1 × 10 –4 mbar H 2 , 1 × 10 –4 mbar O 2 , or 1 × 10 –4 mbar H 2 + 1 × 10 –4 mbar O 2 each yield unique XPS signals indicating a loss of −OH coverage, aligning with DFT predictions. Insight into the mechanism of reduction as a function of H 2 exposure is provided, as well as conditions that promote further reduction toward Fe 3 O 4 . Theoretical and experimental investigations indicate the ability to maintain the Fe 2 O 3 protective layer of iron oxides that have been exposed to H 2 environments by including trace amounts of aqueous O2.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Advanced Modeling and Simulation Methods for Evaluation of Thermal Neutron Scattering Materials

With the rise of interest in thermal neutron scattering data for advanced reactor, criticality safety, and shielding applications, new experimental data are required for evaluation of new materials or for re-evaluation (or validations) of previously evaluated materials. New experimental data are evaluated in a three-step process: (1) computing the phonon characteristics, (2) computing the dynamic structure factor (DSF) from the data, and (3) using the experimental setup to simulate the experimental data. All three steps have challenges, ranging from the need for a sufficiently general material simulation code—a processing code that can compute the corresponding DSF—to having a detailed layout of the instrument/beamline/facility where the data were measured. Whereas phonon characteristics of materials can be computed using various methods (molecular dynamics, density functional theory, etc.), a high-fidelity computation of the DSF and the simulation of the experiment based on the DSF is vital to the accuracy of the evaluation. The latter two steps can be achieved by using the two corresponding code systems developed by instrument scientists at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory: (1) OCLIMAX, a program that calculates the dynamic structure factor from DFT and MD simulation results, and (2) MCViNE, a Monte Carlo neutron ray-tracing program designed to simulate neutron scattering experiments. Recently, polyethylene and yttrium hydride were measured at the Wide Angular-Range Chopper (ARCS) and SEQUOIA instrument stations of the SNS. These experiments are simulated using the density functional theory code, the Cambridge Serial Total Energy Package (CASTEP), to compute its phonon characteristics (eigenvalues/vectors and PDOS), which is then processed using OCLIMAX to yield the DSF, and finally the data at each instrument station are simulated by the MCViNE for comparison to the measured data for evaluation. For comparison to conventional evaluation methods, the scattering data processed from OCLIMAX are compared against those processed from the LEAPR module of NJOY, and the results from MCViNE simulations are compared against previously used simplified beamline models implemented in the Monte Carlo N-Particle (MCNP) code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Effects of graphene surface functionalities towards controlled reinforcement of a lignin based renewable thermoplastic rubber

In this report, we describe methods to enhance mechanical properties of a renewable thermoplastic rubber by incorporating functional graphene platelets into an equal-mass mixture of lignin, a feedstock from plant biomass, and a nitrile-butadiene rubber having 41 mol % acrylonitrile content (NBR41) that form a nanocomposite. Not all lignins yield mechanically strong material when they are combined with NBR41, and thus, limit its use for such rubbery products. Here, we evaluate different graphene oxides (GO) and reduced graphene oxides (rGO) dry-powders with different surface areas, functionality, and wettability in the synthesis of performance-enhanced nanocomposites of soft lignin/NBR41 matrix via a solvent-free, high shear reactive process. High surface area GO (HSGO) platelets with strong hydrophilicity exhibit good dispersion in the multiphase lignin/NBR41 composites with lignin dispersion varying from 200 to 2000 nm, resulting in superior reinforcement over other graphene derivatives. The addition of 1–4 wt % HSGO increased the tensile stress of the lignin/NBR41 thermoplastic rubber matrix by 60–160% (15–24 MPa) and the modulus by 200–700% (60–140 MPa). Scanning electron microscopy and small angle X-ray scattering results show that the well-dispersed HSGO platelets effectively disrupt the lignin-rich aggregates in NBR41 matrix, resulting in both strength and stiffness enhancements in the formed nanocomposites. This report on performance enhancement of lignin-based renewable polymers via the production of nanocomposite would increase potential for ‘finding the value of lignin’—a grand challenge associated with modern biorefineries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A critical comparison of CH∙∙∙π versus π∙∙∙π interactions in the benzene dimer: obtaining benchmarks at the CCSD(T) level and assessing the accuracy of lower scaling methods

In this study, we have established CCSD(T)/CBS (Complete Basis Set) limits for 3 stationary points on the benzene dimer potential energy surface, corresponding to the π∙∙∙π (parallel displaced or PD(C 2h ), minimum) and CH∙∙∙π (T-shaped or T(C 2v ), transition state) and tilted T-shaped (or TT(Cs), minimum) bonding scenarios considering both the structure and binding energy. The CCSD(T)/CBS binding energies are -2.65 ± 0.02 (PD), -2.74 ± 0.03 (T), and -2.83 ± 0.01 kcal mol -1 (TT). To this end, the CH∙∙∙π is ~0.2 kcal mol -1 stronger than the π∙∙∙π interaction, whereas the tilting of the CH donating benzene molecule with respect to the other benzene is worth 0.1 kcal mol -1 . As previously discussed in the literature, the MP2 level of theory does not provide a close match for either the energy or structure, yet the SCS-MP2 yields structures in excellent agreement with respect to the CCSD(T) result. It is found that the SCS-MI-MP2 also gives optimized structures very close to SCS-MP2 (within ~0.01 Å of the benchmark). Despite the closer match in structure, the spin-biased MP2 methods (SCS-, SCS-MI-, and SOS-MP2) incorrectly predict the relative stabilities of the isomers. That said, none of the spin biased MP2 methods offers a good compromise between energy and structure for the systems examined. Finally, the CCSD(T)/CBS benchmarks were used to assess the performance of 13 DFT functionals selected from different rungs of Jacob's ladder. Several functionals such as TPSS-D3, B3LYP-D3, B97-D, B97-D3, and B2PLYP-D3 provided a good description of the binding energies for both CH∙∙∙π and π∙∙∙π interactions, yielding values within 6% of the CCSD(T)/CBS benchmark values. Unlike the MP2 methods, these functionals correctly predict the relative stability of the PD(C 2h ) and T(C 2v ) dimers. Further, we find that there is no systematic improvement as Jacob's ladder is ascended (increased complexity of functional). The best functionals that result in a good compromise between structure and energy accuracy are B97-D3 and B2PLYP-D3 for both the CH∙∙∙π and π∙∙∙π interaction. Despite the impressive performance of these functionals, a challenge that remains is ensuring the transferability of these density functionals in accurately describing the interaction between dimers of larger aromatic molecules, the latter requiring high-level benchmarks for these systems.

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

Efficient machine-learning model for fast assessment of elastic properties of high-entropy alloys

We combined descriptor-based analytical models for stiffness-matrix and elastic-moduli with mean-field methods to accelerate assessment of technologically useful properties of high-entropy alloys, such as strength and ductility. Model training for elastic properties uses Sure-Independence Screening (SIS) and Sparsifying Operator (SO) method yielding an optimal analytical model, constructed with meaningful atomic features to predict target properties. Computationally inexpensive analytical descriptors were trained using a database of elastic properties determined from density functional theory for binary and ternary subsets of Nb-Mo-Ta-W-V refractory alloys. The optimal Elastic-SISSO models, extracted from an exponentially large feature space, give an extremely accurate prediction of target properties, similar to or better than other models, with some verified from existing experiments. Here we also show that electronegativity variance and elastic-moduli can directly predict trends in ductility and yield strength of refractory HEAs, and reveals promising alloy concentration regions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

From Petroleum to Biobased Crude: A Thermoplastic Polyurethane from Lignin-Oil Without Isocyanates

The movement to transfer from petroleum-based products and materials to renewables does not necessarily have to bypass the use of oil. A new type of "black-gold" is readily abundant from the earth's most abundant source of aromatic carbon: lignin. While fractionation of petroleum yields fuels and chemicals for a diverse set of industries, lignin fractionation using targeted catalysts has demonstrated the ability to generate monomers and oligomers rich in functional groups for polymer synthesis. This study explores the use of lignin-oil, generated from reductive catalytic fractionation of popular wood, to a hydroxyl-rich mixture of aromatics that is used to synthesize a thermoplastic non-isocyanate polyurethane. The lignin-oil is first converted to a cyclocarbonated derivative using a benign synthetic sequence and further polymerized with a diamine to yield the non-isocyanate TPU. While more work is underway to optimize the reaction conditions and meet typical mechanical properties of commercial materials, initial analysis shows thermoplastic behavior and flexible properties consistent with traditional thermoplastic polyurethanes.

BIOMASS FUELS↗
DOE OSTI2017

Modulating Hole Transport in Multilayered Photocathodes with Derivatized p-Type Nickel Oxide and Molecular Assemblies for Solar-Driven Water Splitting

We report here a new photocathode composed of a bi-layered doped NiO film topped by a macro-mesoporous ITO (ioITO) layer with molecular assemblies attached to the ioITO surface. The NiO film containing a 2% K+ doped NiO inner layer and a 2% Cu2+ doped NiO outer layer provides sufficient driving force for hole transport after injection to NiO by the molecular assembly. The tri-layered oxide, NiK0.02O | NiCu0.02O | ioITO, sensitized by a ruthenium polypyridyl dye and functionalized with a nickel-based hydrogen evolution catalyst, outperforms its counterpart, NiO | NiO | ioITO, in photocatalytic hydrogen evolution from water over a period of several hours with a Faradaic yield of ~90%.

Shan, Bing↗
DOE OSTI2025

Identifying High Ionic Conductivity Compositions of Ionic Liquid Electrolytes Using Features of the Solvation Environment

Binary mixtures of ionic liquids with molecular solvents are gaining interest in electrochemical applications due to the improvement in their performance over neat ionic liquids. Dilution with suitable molecular solvents can reduce the viscosity and facilitate faster diffusion of ions, thereby yielding substantially higher ionic conductivity than that for a pure ionic liquid. Although viscosity and diffusion coefficients typically behave as monotonic functions of concentration, ionic conductivity often passes through a peak value at an optimum molar ratio of the molecular solvent to the ionic liquid. The ionic conductivity maximum is generally explained in terms of a balance between the ease of charge transport and the concentration of the charge carriers. In this work, fluctuation in the local environment surrounding an ion is invoked as a plausible explanation for the ionic conductivity mechanism with a binary mixture of 1-ethyl-3-methylimidazolium tetrafluoroborate and ethylene glycol as an example. The magnitude of the dynamism in the local environment is captured by measuring the spatial and temporal features of the solvation environment. Standard deviation in the number of ions in the solvation environment serves as a spatial feature, while the cage correlation lifetimes for oppositely charged ions within the first solvation shell serve as a temporal feature. Large standard deviations in the cluster ion population and short cage correlation lifetimes are indicators of highly dynamic ionic environment at the molecular level and consequently yield high ionic conductivity. Such compositions were found to be in good agreement with the optimum ionic liquid mole fractions obtained through experimental measurement. Short cage correlation lifetimes enable the identification of optimum mixture compositions using simulation trajectories significantly shorter than those required to implement the Nernst–Einstein or Einstein formalisms for calculating ionic conductivity. We validated the applicability of this approach across force fields and in six ionic liquid-molecular solvent electrolytes formed with combination of cations, anions, and solvents. We offer a computationally efficient approach of screening ionic liquid-molecular solvent binary mixture electrolytes to identify molar ratios that yield high ionic conductivity.

25 ENERGY STORAGE↗
DOE OSTI2019

Structure and functional reselection of the Mango-III fluorogenic RNA aptamer

Here, several turn-on RNA aptamers that activate small-molecule fluorophores have been selected in vitro. Among these, the ~30 nucleotide Mango-III is notable because it binds the thiazole orange derivative TO1-Biotin with high affinity and fluoresces brightly (quantum yield 0.55). Uniquely among related aptamers, Mango-III exhibits biphasic thermal melting, characteristic of molecules with tertiary structure. We report crystal structures of TO1-Biotin complexes of Mango-III, a structure-guided mutant Mango-III(A10U), and a functionally reselected mutant iMango-III. The structures reveal a globular architecture arising from an unprecedented pseudoknot-like connectivity between a G-quadruplex and an embedded non-canonical duplex. The fluorophore is restrained into a planar conformation by the G-quadruplex, a lone, long-range trans Watson–Crick pair (whose A10U mutation increases quantum yield to 0.66), and a pyrimidine perpendicular to the nucleobase planes of those motifs. The improved iMango-III and Mango-III(A10U) fluoresce ~50% brighter than enhanced green fluorescent protein, making them suitable tags for live cell RNA visualization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Fatty Acid and Alcohol Metabolism in Pseudomonas putida: Functional Analysis Using Random Barcode Transposon Sequencing.

With its ability to catabolize a wide variety of carbon sources and a growing engineering toolkit, Pseudomonas putida KT2440 is emerging as an important chassis organism for metabolic engineering. Despite advances in our understanding of the organism, many gaps remain in our knowledge of the genetic basis of its metabolic capabilities. The gaps are particularly noticeable in our understanding of both fatty acid and alcohol catabolism, where many paralogs putatively coding for similar enzymes coexist, making biochemical assignment via sequence homology difficult. To rapidly assign function to the enzymes responsible for these metabolisms, we leveraged random barcode transposon sequencing (RB-Tn-Seq). Global fitness analyses of transposon libraries grown on 13 fatty acids and 10 alcohols produced strong phenotypes for hundreds of genes. Fitness data from mutant pools grown on fatty acids of varying chain lengths indicated specific enzyme substrate preferences and enabled us to hypothesize that DUF1302/DUF1329 family proteins potentially function as esterases. From the data, we also postulate catabolic routes for the two biogasoline molecules isoprenol and isopentanol, which are catabolized via leucine metabolism after initial oxidation and activation with coenzyme A (CoA). Because fatty acids and alcohols may serve as both feedstocks and final products of metabolic-engineering efforts, the fitness data presented here will help guide future genomic modifications toward higher titers, rates, and yields. IMPORTANCE To engineer novel metabolic pathways into P. putida , a comprehensive understanding of the genetic basis of its versatile metabolism is essential. Here, we provide functional evidence for the putative roles of hundreds of genes involved in the fatty acid and alcohol metabolism of the bacterium. These data provide a framework facilitating precise genetic changes to prevent product degradation and to channel the flux of specific pathway intermediates as desired.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Single-crystal growth and superconductivity in RbNi 2 Se 2

Herein we report the synthesis and characterization of RbNi 2 Se 2 , an analog of the iron chalcogenide superconductor Rb x Fe 2 Se 2 , via transport, angle-resolved photoemission spectroscopy, and density functional theory calculations. A superconducting transition at T c =1.20 K is identified. In the normal state, RbNi 2 Se 2 shows paramagnetic and Fermi-liquid behaviors. A large Sommerfeld coefficient yields an effective electron mass of m* ≈ 6m e . In the superconducting state, zero-field electronic specific-heat data C es can be described by a two-gap BCS model, indicating that RbNi 2 Se 2 is a possible multigap superconductor. Our density functional theory calculations and angle-resolved photoemission spectroscopy measurements demonstrate that RbNi 2 Se 2 exhibits relatively weak correlations and multiband characteristics, consistent with the multigap superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗