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At least 631 records · Page 35

Liquid Copper and Iron Production from Chalcopyrite, in the Absence of Oxygen

Clean energy infrastructure depends on chalcopyrite: the mineral that contains 70% of the world’s copper reserves, as well as a range of precious and critical metals. Smelting is the only commercially viable route to process chalcopyrite, where the oxygen-rich environment dictates the distribution of impurities and numerous upstream and downstream unit operations to manage noxious gases and by-products. However, unique opportunities to address urgent challenges faced by the copper industry arise by excluding oxygen and processing chalcopyrite in the native sulfide regime. Through electrochemical experiments and thermodynamic analysis, gaseous sulfur and electrochemical reduction in a molten sulfide electrolyte are shown to be effective levers to selectively extract the elements in chalcopyrite for the first time. We present a new process flow to supply the increasing demand for copper and byproduct metals using electricity and an inert anode, while decoupling metal production from fugitive gas emissions and oxidized by-products.

36 MATERIALS SCIENCE↗

Synthesis of High Surface Area VS2 for Nitrogen Reduction

Ammonia synthesis from dinitrogen provides a critical chemical feedstock to agriculture worldwide. The dominant process for ammonia synthesis is the Haber-Bosch process, which is fossil-fuel dependent and energy intensive. The electrochemical nitrogen reduction reaction (NRR) could provide a more environmentally friendly route to industrial ammonia synthesis. We have worked to realize electrochemical NRR by developing transition metal dichalcogenide NRR catalysts. In the first part of this presentation, a VS2-based NRR electrocatalyst, which has shown promising activity and selectivity, will be presented. The synthesis of this VS2-based catalyst is straightforward and results in few-layer VS2 or VSx, (x < 2) nanoflakes. Additionally, the proposed mechanism of NRR on VS2 will be discussed, and we will discuss DFT simulation of NRR on VS2 and MoS2 as well as planned in-situ Raman experiments to probe this mechanism. In the second part of this presentation, we will share several lessons learned during our early NRR research including important points of electrochemical cell design and experimental controls to reduce environmental ammonia contamination of experiments. Finally, we will address areas of opportunity for electrochemical NRR.

dichalcogenide↗

Forward and backward stimulated Raman scattering in multi-speckled beams: Density dependence and effects on cross-beam energy transfer

Particle-in-cell simulations of cross-beam energy transfer (CBET) between multi-speckled beams reveal a potentially prominent energy loss from forward stimulated Raman scattering (FSRS) in the amplified seed beam [Yin et al., Phys. Plasmas 26, 082708 (2019)]. In this work, an intensity scan is used to examine this energy loss in the CBET-amplified seed beam at intensities of a few times 1014 W/cm2. Electron tracers demonstrate both the trapping in the electron plasma waves that is sustained over multiple speckles and the subsequent acceleration to velocities well beyond the phase velocity. Motivated by expanding our understanding of this energy loss mechanism, we isolate the FSRS density dependence by using a 2×1014 W/cm2 pulse to scan densities between 0.06 ncr and 0.12 ncr; a spectral analysis characterizes the energy losses from scattering with the changing densities. At saturation, both greater beam attenuation is measured at the laser frequency and larger scattering FSRS angles are observed as density increases, along with a rapid transition to primarily backscatter SRS between 0.10 ncr and 0.12 ncr, earlier than predicted by linear theory. Density gradients are shown to effectively mitigate oblique FSRS and beam energy losses in the two lower density cases, whereas 0° forward scattering is primarily suppressed in the higher density cases. Finally returning to the two-beam CBET system of interest, the interplay and mitigation of the secondary instabilities at larger domain and beam spatial scales are discussed, here also examining backward stimulated Brillouin scattering.

Stark, D. J. (ORCID:0000000203642733)↗

High-resolution climate model datasets for energy infrastructure planning in a renewable-dependent future

Electrification and renewables deployment efforts are amplifying the interdependence of the climate and energy systems. Increases in climate model resolution, which is now approaching that of reanalysis datasets and operational weather forecast models, present a unique opportunity to use future climate projections for energy infrastructure planning. In this Perspective, we review recent developments in high-resolution climate modeling, which have been driven by increased computing power and advanced software tools. We then look ahead to discuss how high-resolution climate data can be used to plan for a renewable-dependent future, and envision a unified climate-energy model framework that captures the two-way feedbacks between these interdependent systems.

climate change↗

Optical magnons with dominant bond-directional exchange interactions in the honeycomb lattice iridate α — Li 2 IrO 3

We have used resonant inelastic x-ray scattering to reveal optical magnons in a honeycomb lattice iridate α - Li 2 IrO 3 . The spectrum in the energy region 20–25 meV exhibits momentum dependence, of which energy is highest at the location of the magnetic Bragg peak, ( h , k ) = ( ± 0.32 , 0 ) , and lowered toward ( 0 , 0 ) and ( ± 1 , 0 ) . We compare our data with a linear spin-wave theory based on a generic nearest-neighbor spin model. We find that a dominant bond-directional Kitaev interaction of order 20 meV is required to explain the energy scale observed in our study. The observed excitations are understood as stemming from optical magnon modes whose intensity is modulated by a structure factor, resulting in the apparent momentum dependence. We also observed diffuse magnetic scattering arising from the short-range magnetic correlation well above T N . In contrast to Na 2 IrO 3 , this diffuse scattering lacks the C 3 rotational symmetry of the honeycomb lattice, suggesting that the bond anisotropy is far from negligible in α - Li 2 IrO 3 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Nonadiabatic Energy Fluctuations of Scale-Invariant Quantum Systems in a Time-Dependent Trap

We consider the nonadiabatic energy fluctuations of a many-body system in a time-dependent harmonic trap. In the presence of scale-invariance, the dynamics becomes self-similar and the nondiabatic energy fluctuations can be found in terms of the initial expectation values of the second moments of the Hamiltonian, square position, and squeezing operators. Nonadiabatic features are expressed in terms of the scaling factor governing the size of the atomic cloud, which can be extracted from time-of-flight images. We apply this exact relation to a number of examples: the single-particle harmonic oscillator, the one-dimensional Calogero-Sutherland model, describing bosons with inverse-square interactions that includes the non-interacting Bose gas and the Tonks-Girdardeau gas as limiting cases, and the unitary Fermi gas. We illustrate these results for various expansion protocols involving sudden quenches of the trap frequency, linear ramps and shortcuts to adiabaticity. Our results pave the way to the experimental study of nonadiabatic energy fluctuations in driven quantum fluids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Accelerated kinetic Monte Carlo: A case study; vacancy and dumbbell interstitial diffusion traps in concentrated solid solution alloys

Vacancy and self-interstitial atomic diffusion coefficients in concentrated solid solution alloys can have a non-monotonic concentration dependence. Here, the kinetics of monovacancies and $\langle$100$\rangle$ dumbbell interstitials in Ni–Fe alloys are assessed using lattice kinetic Monte Carlo (kMC). The non-monotonicity is associated with superbasins, which impels using accelerated kMC methods. Detailed implementation prescriptions for first passage time analysis kMC (FPTA-kMC), mean rate method kMC (MRM-kMC), and accelerated superbasin kMC (AS-kMC) are given. The accelerated methods are benchmarked in the context of diffusion coefficient calculations. The benchmarks indicate that MRM-kMC underestimates diffusion coefficients, while AS-kMC overestimates them. In this application, MRM-kMC and AS-kMC are computationally more efficient than the more accurate FPTA-kMC. Our calculations indicate that composition dependence of migration energies is at the origin of the vacancy’s non-monotonic behavior. In contrast, the difference between formation energies of Ni–Ni, Ni–Fe, and Fe–Fe dumbbell interstitials is at the origin of their non-monotonic diffusion behavior. Additionally, the migration barrier crossover composition—based on the situation where Ni or Fe atom jumps have lower energy barrier than the other one—is introduced. KMC simulations indicate that the interplay between composition dependent crossover of migration energy and geometrical site percolation explains the non-monotonic concentration-dependence of atomic diffusion coefficients.

36 MATERIALS SCIENCE↗

Benchmark of the KGMf with a coupled Boltzmann equation solver

The Kinetic Global Model framework (KGMf) is an open-source general-purpose global model (spatially averaged) simulation code developed to explore the reaction kinetics and pathways in plasma discharge systems. It contains species continuity and electron energy balance equations, with a time-dependent evaluated electron energy distribution function (EEDF) for electron impact reactions. The EEDF is utilized to determine the rate coefficients for electron impact reactions, which can have profound impact on the temporal evolutions of plasma parameters. Previously, the EEDF was commonly assumed as Maxwellian or an analytical function of the effective electron temperature. In this work, the KGMf is coupled with a Boltzmann equation (BE) solver to self-consistently compute the EEDF. The EEDF evolution frequency is determined based on relative changes of the reduced electric field. The KGMf is benchmarked with the ZDPlasKin code based on high-pressure low-temperature argon plasma discharge cases. Additionally, the temporal evolutions of reduced electric field, electron temperature, EEDF, reaction rates, and species densities, are obtained and compared under different discharge conditions, showing good agreement between the KGMf and the ZDPlasKin simulations. The application of the KGMf for predicting breakdown times in high power microwave discharges is also presented, which shows qualitative agreement with particle-in-cell simulations. The KGMf can be further applied for more complicated plasma discharge systems, where the reaction kinetics are more intricate (e.g., plasma-assisted combustion systems).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Anomalous stability of non-van der Waals bonded B4C nanosheets through surface reconstruction

Boron carbide (B4C) has been well studied both theoretically and experimentally in its bulk form due to its exceptional hardness and use as a high-temperature thermoelectric. However, the properties of its two-dimensional nanosheets are not well established. In this paper, using van der Waals-corrected density-functional theory simulations, we show that bulk B4C can be cleaved along different directions to form B4C nanosheets with low formation energies. We find that there is minimal dependence of formation energies on cleavage planes and surface terminations, even though the bulk is not van der Waals layered. This anomalous stability of B4C nanosheets is found to be a result of surface reconstructions that are unique to B-rich systems. While the density of states of the bulk B4C indicate that it is a semiconductor, the B4C nanosheets are found to be predominantly metallic. We attribute this metallic behavior to a redistribution of charges on the surface bonds of the films. The Seebeck coefficients of the B4C films remain comparable to those of the bulk and are nearly constant as a function of temperature. Our results provide guidance for experimental synthesis efforts and future application of B4C nanosheets in nanoelectronic and thermoelectric applications.

Physics↗

Deer Isle and Stonington Energy Reliability Opportunities

The towns of Deer Isle and Stonington, located on the island of Deer Isle in Maine, partnered with the U.S. Department of Energy's Energy Technology Innovation Partnership Project (ETIPP) to examine options to enhance energy resilience, reduce dependence on imported fuels, and mitigate high energy costs. With technical support from the National Laboratory of the Rockies (NLR), Lawrence Berkeley National Laboratory (LBNL), and regional partner the Island Institute, the project focused on evaluation of the local electricity distribution infrastructure, examination of ongoing activities to reduce the frequency of outages, review of the applicable policy and regulatory environment, and identification of potential on-site energy solutions. Key findings revealed the island's reliance on a single distribution line, and limited hosting capacity for additional distributed energy resources. Solar photovoltaics (PV) technology, with and without battery storage, was found to be the most viable technology given economic, technical, and social considerations. While also technically feasible, wind energy faces more difficult siting and less public acceptance compared to PV. Marine energy technologies were determined to be infeasible due to technology immaturity and lengthy permitting timelines. Modeling of potential building-scale PV plus storage systems resulted in successful grant applications for installations at two local facilities. Analysis of community scale energy generation and storage options resulted the local utility, Versant, submitting a grant application for a proposed community-scale battery storage system to increase grid resilience and hosting capacity. This initiative has strengthened the communities' energy planning capabilities and laid the groundwork for future clean energy development.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Progress in Constraining Nuclear Symmetry Energy Using Neutron Star Observables Since GW170817

The density dependence of nuclear symmetry energy is among the most uncertain parts of the Equation of State (EOS) of dense neutron-rich nuclear matter. It is currently poorly known especially at suprasaturation densities partially because of our poor knowledge about isovector nuclear interactions at short distances. Because of its broad impacts on many interesting issues, pinning down the density dependence of nuclear symmetry energy has been a longstanding and shared goal of both astrophysics and nuclear physics. New observational data of neutron stars including their masses, radii, and tidal deformations since GW170817 have helped improve our knowledge about nuclear symmetry energy, especially at high densities. Based on various model analyses of these new data by many people in the nuclear astrophysics community, while our brief review might be incomplete and biased unintentionally, we learned in particular the following: (1) The slope parameter L of nuclear symmetry energy at saturation density ρ0 of nuclear matter from 24 new analyses of neutron star observables was about L≈57.7±19 MeV at a 68% confidence level, consistent with its fiducial value from surveys of over 50 earlier analyses of both terrestrial and astrophysical data within error bars. (2) The curvature Ksym of nuclear symmetry energy at ρ0 from 16 new analyses of neutron star observables was about Ksym≈−107±88 MeV at a 68% confidence level, in very good agreement with the systematics of earlier analyses. (3) The magnitude of nuclear symmetry energy at 2ρ0, i.e., Esym(2ρ0)≈51±13 MeV at a 68% confidence level, was extracted from nine new analyses of neutron star observables, consistent with the results from earlier analyses of heavy-ion reactions and the latest predictions of the state-of-the-art nuclear many-body theories. (4) While the available data from canonical neutron stars did not provide tight constraints on nuclear symmetry energy at densities above about 2ρ0, the lower radius boundary R2.01=12.2 km from NICER’s very recent observation of PSR J0740+6620 of mass 2.08±0.07M⊙ and radius R=12.2–16.3 km at a 68% confidence level set a tight lower limit for nuclear symmetry energy at densities above 2ρ0. (5) Bayesian inferences of nuclear symmetry energy using models encapsulating a first-order hadron–quark phase transition from observables of canonical neutron stars indicated that the phase transition shifted appreciably both L and Ksym to higher values, but with larger uncertainties compared to analyses assuming no such phase transition. (6) The high-density behavior of nuclear symmetry energy significantly affected the minimum frequency necessary to rotationally support GW190814’s secondary component of mass (2.50–2.67) M⊙ as the fastest and most massive pulsar discovered so far. Overall, thanks to the hard work of many people in the astrophysics and nuclear physics community, new data of neutron star observations since the discovery of GW170817 have significantly enriched our knowledge about the symmetry energy of dense neutron-rich nuclear matter.

79 ASTRONOMY AND ASTROPHYSICS↗

Regenerative Fuel Cell System (Cooperative Research and Development Final Report, CRADA Number CRD-16-635)

Grid energy storage is required to maintain reliable electricity delivery from energy producers to their customers. As electrical loads on the grid change throughout the day, stored energy supplies electricity during increased power demand periods. Further, as more renewable and alternative energy sources are added, energy storage will maximize the usefulness of these technologies. Currently, the United States has over 24.6 GW of grid storage, about 2% of the total electrical production capacity. About 95% of energy storage comes from pumped hydro. However, pumped hydro energy storage is dependent on existing geographic features, making it difficult to integrate with widespread renewable energy sources. As energy demands continue to expand, and more renewable energy (i.e. wind and solar) is added to the grid, new energy storage technologies will be needed that are not dependent on geographic features. Battery technologies can provide energy storage for some applications, but are not economically well-suited for long duration charge/discharges, such as load-leveling of renewable energy. Consequently, development of new energy storage devices will augment the existing grid and reduce the capital investment in construction upgrades. As ever-increasing mandates for renewable energy are implemented, lower-cost energy storage solutions for renewable energy will be necessary to keep electricity costs low for consumers.

13 HYDRO ENERGY↗

Mean field model parameterization to recover coverage-dependent kinetics

Lateral interactions between adsorbates introduce coverage dependence into adsorption energies and activation barriers of surface reactions. Lattice-based kinetic Monte Carlo (kMC) simulations can capture these interactions quantitatively but are laborious to parameterize and solve. Mean field models are more tractable, but protocols to construct and parameterize them are unclear. Here we explore the ability of a coverage-aware mean-field model to map to a lattice-kMC model of a generic two-step reaction network, including quasi-equilibrated adsorption and rate-limiting dissociation steps. We derive expressions for mean-field and coverage-dependent adsorption energies and dissociation barriers and parameterize against lattice-kMC predictions. We show that the parameterized mean-field rates correlate with ground truth lattice-kMC results across a wide range of reaction conditions and identify regions where the mean field fails. The mean field model similarly captures kMC-derived rate-order, Arrhenius and Sabatier plots at a greatly reduced computational cost. Further, the results provide guidance for parameterizing mean-field models, benchmarked against explicit lattice-based approaches for incorporating the influence of coverage effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Wave resource spatial and temporal variability dependence on WEC size

As the wave energy sector grows and looks to the Blue Economy for commercialization opportunities, there is a distinct and pressing need to clearly understand and quantify the coupled impacts of wave energy converter (WEC) size and wave resource characteristics on the annual energy production, spatial variability and temporal variability. Utilizing generic frequency domain representations of the Oscilla Power Triton WEC and spectral wave conditions at PacWave (Oregon), Los Angeles (California) and WETS (Hawaii), a series of interesting results emerge. Firstly, the ‘optimal’ WEC size, from an energy standpoint, is fundamentally dependent on the frequency distribution of the incoming wave variance density spectrum. Secondly, and from a seasonality perspective, the seasonal WEC energy generation doesn’t necessarily follow the seasonal distribution of gross wave power. Finally, from an hourly power variability perspective, a reduction in WEC size generally decreases variability. However, for each of the locations investigated, there appears to be a WEC size threshold; a threshold where further reducing WEC size results in increased power variability.

16 TIDAL AND WAVE POWER↗

Wave Resource Spatial and Temporal Variability Dependence on WEC Size

As the wave energy sector grows and looks to the Blue Economy for commercialization opportunities, there is a distinct and pressing need to clearly understand and quantify the coupled impacts of wave energy converter (WEC) size and wave resource characteristics on the annual energy production, spatial variability and temporal variability. Utilizing generic frequency domain representations of the Oscilla Power Triton WEC and spectral wave conditions at PacWave (Oregon), Los Angeles (California) and WETS (Hawaii), a series of interesting results emerge. Firstly, the 'optimal' WEC size, from an energy standpoint, is fundamentally dependent on the frequency distribution of the incoming wave variance density spectrum. Secondly, and from a seasonality perspective, the seasonal WEC energy generation doesn't necessarily follow the seasonal distribution of gross wave power. Finally, from an hourly power variability perspective, a reduction in WEC size generally decreases variability. However, for each of the locations investigated, there appears to be a WEC size threshold; a threshold where further reducing WEC size results in increased power variability.

blue economy↗

Time-dependent density functional theory of charge, energy, and spin transport, and quantum continuum mechanics (Final Report)

The overarching goal of this project, which unfolded over a period of seventeen years, including two no-cost extensions in the last two years, was to extend and deepen our ability to use time-dependent density functional theory and related theoretical methods for the description of the transport of charge, spin, or energy in quantum electronic systems at the nanoscale. The output of our efforts is contained in 52 papers, listed below, which we have published since 2006. There have also been many presentations at international conferences, workshops, colloquia and seminars. This body of work has been carried out with the essential input of 8 postdoctoral students (who were supported by the grant) and several external senior collaborators and their postdocs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Software defined grid energy storage

Today, consumer battery installations are isolated, physical devices. Virtual power plants (VPPs) allow consumer devices to aggregate for grid services, but they are are vertically integrated, vendor controlled systems (e.g., Tesla’s VPP). Consumer batteries are therefore unable to participate in energy markets or other grid services outside what their vendor provides. We describe a software system that provides software control of multiple, networked battery energy storage systems in the electric grid. The system introduces two new ideas that enable flexible and dependable management of energy storage. The first is a virtual battery, which can either partition a battery or aggregate multiple batteries. The second is a reservation-based API which allows asynchronous control of batteries to meet contractual guarantees in a safe and dependable manner. Virtual batteries and a reservation-based API address the unique challenges of achieving high and efficient utilization of energy storage systems, including heterogeneity of battery systems such as varying C-rates, participation in energy markets, utility bill management systems, community resource sharing, and reliability. Using a testbed comprised of sonnen Inc. storage units installed in several homes and a lab, we demonstrate that virtualized batteries can seamlessly replace physical batteries, flexibly manage energy storage resources, isolate multiple clients using a shared battery, and create new energy storage applications.

25 ENERGY STORAGE↗

Electrochemical reduction of acetonitrile to ethylamine

Electrifying chemical manufacturing using renewable energy is an attractive approach to reduce the dependence on fossil energy sources in chemical industries. Primary amines are important organic building blocks; however, the synthesis is often hindered by the poor selectivity because of the formation of secondary and tertiary amine byproducts. Herein, we report an electrocatalytic route to produce ethylamine selectively through an electroreduction of acetonitrile at ambient temperature and pressure. Among all the electrocatalysts, Cu nanoparticles exhibit the highest ethylamine Faradaic efficiency (~96%) at -0.29 V versus reversible hydrogen electrode. Under optimal conditions, we achieve an ethylamine partial current density of 846 mA cm -2 . A 20-hour stable performance is demonstrated on Cu at 100 mA cm -2 with an 86% ethylamine Faradaic efficiency. Moreover, the reaction mechanism is investigated by computational study, which suggests the high ethylamine selectivity on Cu is due to the moderate binding affinity for the reaction intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗