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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Numerical and Experimental Investigations of Polyurethane Foam for Use as Cask Impact Limiter in Accidental Drop Scenarios - 12099

Rigid, closed-cell polyurethane foams are frequently used as cask impact limiters in nuclear materials and hazardous waste transport due to their high energy-absorption potential. When assessing the cask integrity in accidental scenarios based on numerical simulations, a description of the foam damping properties is required for different strain rates and for a wide temperature range with respect to waste heat generation in conjunction with critical operating and environmental conditions. Implementation and adaption of a respective finite element material model strongly relies on an appropriate experimental data base. Even though extensive impact experiments were conducted e.g. in Sandia National Laboratories, Savannah River National Laboratory and by Rolls Royce plc, not all relevant factors were taken into account. Hence, BAM who is in charge of the mechanical evaluation of such packages within the approval procedure in Germany, incorporated systematic test series into a comprehensive research project aimed to develop numerical methods for a couple of damping materials. In a first step, displacement driven compression tests have been performed on confined, cubic specimens at five loading rates ranging from 0.02 mm/s to 3 m/s at temperatures between +90 deg. C and -40 deg. C. Materials include two different polyurethane foam types called FR3718 and FR3730 having densities of 280 kg/m{sup 3} and 488 kg/m{sup 3} from the product line-up of General Plastics Manufacturing Company. Their data was used to adapt an advanced plasticity model allowing for reliably simulating cellular materials under multi-axial compression states. Therefore, an automated parameter identification procedure had been established by combining an artificial neural network with local optimization techniques. Currently, the selected numerical material input values are validated and optimized by means of more complex loading configurations with the prospect of establishing methods applicable to impact limiters under severe accidental conditions. The reference data base is provided by experiments, where weights between 212 kg and 1200 kg have been dropped from heights between 1.25 m and 7 m on confined 10 cm cubic foam specimens. By presenting the deviations between experimental values and the corresponding output of finite element simulations, the potentials and restrictions of the resulting models are highlighted. Systematic compression tests on polyurethane foams had been performed at BAM test site within the framework of a research project on impact limiters for handling casks for radioactive waste. The experimental results had been used to adapt numerical models for simulating the behaviour of different foam types at different temperatures. The loading speed, however, turned out to have a major influence on their flow curves that can not be captured by simple strain-rate dependent multipliers. Especially for guided drop tests that come close to real accidental scenarios there is a significant gap between experimental and numerical results even when applying such advanced material models. Hence, the extensive data base is currently deployed for expanding the standard algorithms to include adequate dynamic hardening factors. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Atomic-scale Imaging of PGM-free Catalyst Active Sites by 30 keV 4D-STEM

Platinum group metal (PGM)-free catalysts have attracted a large amount of attention due to their potential for enabling low-cost, commercially viable hydrogen fuel cells and electrolyzers [1]. Degradation of cell performance remains a significant challenge, however, currently limiting implementation of devices that utilize PGM-free materials [2]. Controlling degradation in these materials requires a better understanding of the atomic structure of active sites, thought to be FeN4 structures within a graphitic carbon lattice, which would enable more accurate prediction of the associated degradation pathways. The exact structural arrangement of active sites in these materials is still debated since a range of structures have been computationally predicted and methods to directly validate these models are still needed [1,3-5].While scanning transmission electron microscopy (STEM) has provided initial glimpses into the nature of the proposed active sites, detailed evaluation of the structure of these sites is challenging since they involve defects, edges, and nitrogen dopants in the graphitic lattice, which are susceptible to beam damage [6,7]. Conventional STEM imaging and spectroscopy methods exacerbate this problem with dose-inefficiency or nonideal contrast characteristics for imaging light and heavy elements simultaneously. A method that minimizes damage while generating dose-efficient, easily-interpretable contrast for both light and heavy elements is therefore needed to facilitate imaging of sensitive active site atomic structure.Here, we demonstrate direct atomic-scale imaging of PGM-free catalyst active sites by low-voltage four-dimensional (4D)-STEM. To accomplish this, we pair a 30 keV aberration-corrected probe, which minimizes knock-on damage, with a fast pixelated detector that has optimal performance at low beam energies [8]. We show how this setup enables relatively simple center-of-mass (CoM) techniques [9,10] to produce images with an increased signal-to-noise ratio (SNR) and light-element contrast over conventional imaging modes, allowing the entire active site structure to be imaged at the atomic scale. Moreover, we show how electron ptychography [11,12] enables images with further improved characteristics to be obtained, for example by minimizing residual aberrations, which provides a more accurate structural representation. The increased understanding that these low-voltage 4D-STEM techniques will provide about the atomic structure of PGM-free active sites and their associated degradation pathways will facilitate rational design of next-generation materials, promoting development of low-cost hydrogen fuel cells, electrolyzers, and other energy conversion devices [13]. References:[1] U Martinez et al., Adv. Mater. 31 (2019), p. 1806545.[2] Y Shao et al., Adv. Mater. 31 (2019), p. 1807615.[3] J Kneebone et al., J. Phys. Chem. C 121, (2017), p.16283.[4] T Mineva et al., ACS Catal. 9 (2019), p. 9359.[5] J Li et al., Nat. Catal. 4 (2021), p. 10.[6] T Susi et al., ACS Nano 6 (2012), p. 8837.[7] P Zelenay and DJ Myers, US Department of Energy Hydrogen and Fuel Cells Program 2017 Annual Merit Review and Peer Evaluation Meeting, Washington, DC (2017).[8] H Ryll et al., J. Inst. 11 (2016), p. P04006.[9] K Müller et al., Nat. Commun. 5 (2014), p. 5653.[10] I Lazic et al., Ultramicroscopy 160 (2016), p. 265.[11] H Yang et al., Nat. Commun. 7 (2016), p. 12532.[12] Y Jiang et al., Nature 559 (2018), p. 343. [13] Research sponsored by the Hydrogen and Fuel Cell Technologies Office, Office of Energy Efficiency and Renewable Energy, US Department of Energy (DOE). Research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility.

Zachman, Michael↗
DOE OSTI2020

Ultrastructure of the green alga Dunaliella salina strain CCAP19/18 (Chlorophyta) as investigated by quick-freeze deep-etch electron microscopy

The single-celled green alga Dunaliella salina is a model system for studies on stress biology, in particular regarding secondary carotenoid accumulation. Under non-stress conditions the cells are green, but under abiotic stress the cells turn orange, because they switch their metabolism and accumulate β-Carotene in globules in the chloroplast. For the first time, Quick-freeze deep-etch electron microscopy was used to visualize cellular structures in green and orange cells of D. salina strain CCAP19/18. This allowed us to present an in-depth analysis of the cellular ultrastructure describing and comparing the features of the two cell types. Our images illustrate the presence of a pericellular matrix for this strain of D. salina. The pericellular matrix was spongy and strands of unknown material anchored it into the plasma membrane. The cytoplasm contained a variety of vesicles, vacuoles, and acidocalcisomes. We could show for strain CCAP19/18 that cytoplasmic lipid bodies were often in close proximity to and sometimes in contact with the outer chloroplast envelope membrane and with the endoplasmic reticulum. Major visible differences between green and orange cells were in the chloroplast: the orange cells have greatly reduced amounts of thylakoid membranes and greatly increased numbers of β-Carotene globules. We showed that the β-Carotene globules often made point contacts with thylakoid membranes, and frequently laid side-by-side along the thylakoid membrane surface, providing support to studies that indicated exchange of molecules between β-Carotene globules and thylakoid membranes. A unique finding was the β-Carotene globule duplets, suggesting intermediate stages in β-Carotene globule morphogenesis. Overall, the β-Carotene globules appear to be similar to plant plastoglobuli. We provide this description of the cellular ultrastructure features as a resource in the context of the recent publication of the genome of D. salina strain CCAP19/18 to expand on the knowledge regarding this novel reference strain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Energy Arbitrage: Comparison of Options for use with LWR Nuclear Power Plants

Arbitrage is the opportunistic buying and selling of a commodity during local pricing valleys and peaks respectively to maximize economic value. This report evaluates options for energy arbitrage integrated with existing light water reactor (LWR) nuclear power plants (NPPs) where nuclear energy could be stored in a variety of forms and later recovered to generate electrical power during periods when grid electricity demand and pricing are high. The forms of energy storage examined in this report include the potential value of batteries, hydrogen, and thermal energy storage for coupling with nuclear power. Various large demand response options are also analyzed, including the production of liquid nitrogen via air separation and liquefaction, liquefaction of hydrogen, compressed hydrogen, and the cryogenic capture of CO2. Demand response refers to dispatchable loads that can cycle up or down depending on-grid electricity demand to aid in balancing the grid. Large demand response options could dispatch to aid nuclear power stations in avoiding power turndowns by providing an alternate disposition for electrical energy by producing marketable products (e.g., liquid nitrogen, hydrogen, or captured CO2). Static conditions were chosen and analyzed in this report for each option. Dynamic operation or optimization of energy arbitrage or demand response are out of scope for this report. The analysis is based on storage systems with discharge capacities of 500 MW for which various durations of storage and costs of charging (electricity cost) are examined. While the value of thermal energy to an industrial user for flexible plant operations has been previously proven as a business case, this report evaluates costs of hydrogen energy storage and leading thermal energy storage options, and large demand response loads that could be integrated with LWRs in comparison to utility-scale battery storage for use of off-peak nuclear energy. Compilation of this information will be used by the Idaho National Laboratory (INL) RAVEN/HERON systems integration and economics tool to evaluate thermal energy dispatch to industrial users. Relative ranking of energy storage options was done using a levelized cost of storage (LCOS) metric which calculates a rough breakeven cost for the system, taking into account the capital and operating costs as well as the revenue from arbitrage. Table ES1 below shows the LCOS for each of the energy storage options considered. First, in the table, lithium iron (Fe) phosphate batteries are listed as the base case for comparison against the other options. Next is hydrogen storage where most of the hydrogen analyses assumed the hydrogen to be produced using solid oxide electrolytic cell (SOEC) high temperature steam electrolysis (HTSE). The others used existing models of polymer electrolyte membrane (PEM) low temperature electrolysis to produce hydrogen. HTSE performance parameters and costs were taken from existing INL models. Various means were assumed to convert the hydrogen to electricity, including PEM fuel cells (FCs) and a gas turbine mixed in a 30 vol% mixture with natural gas. Physical storage (pressure vessels) and geological storage (natural underground features) were used to store the hydrogen as noted. Geological storage is more economical, but the locations are limited because of the requirement for pre-existing geological formations that will support storage. Thermal energy storage (TES) options were also analyzed including electro-thermal energy storage (ETES) and four different liquid sensible heat TES storage media as noted (Hitec, Hitec XL, Therminol-66, and Dowtherm A). The ETES process considered was modified using existing public documentation on an Echogen process and uses a separate supercritical CO2 charge and discharge cycle with sand as the heat storage media.

25 ENERGY STORAGE↗
DOE OSTI2020

Uncovering the Relationship between Diameter and Height of Electrodeposited Lithium Protrusions in a Rigid Electrolyte

A promising approach for enabling rechargeable batteries with significantly higher energy densities than current lithium-ion batteries is by deploying lithium-metal anodes. However, the growth of lithium protrusions during charging presents significant challenges. Since these protrusions are often branched and filamentous in conventional liquid electrolytes, this problem is referred to in the literature as the “dendrite problem”. While solid electrolytes have the potential to solve this problem, protrusions grow in all electrolytes when the current density exceeds a critical value. Fundamentally understanding the formation is necessary to develop a rational approach for increasing the critical current density, but it is challenging due to the complex interplay between electrochemical and material properties. The diameters and heights of protrusions on lithium-metal anodes stabilized by a rigid block copolymer electrolyte were measured in situ by synchrotron hard X-ray microtomography. The diameter of the shorting protrusions increased linearly with increasing electrolyte thickness. Further, a universal linear relationship between protrusion height and diameter of both shorting and non-shorting protrusions was observed. A model based on the concentrated solution theory was used to establish the electrochemical and mechanical sources for our observations. Here, the computational analysis indicates that elastic and plastic deformation of both the lithium metal and the polymer are important to describe protrusion growth. Both stress-induced current density effects due to the deformation of the electrolyte near the protrusion and plastic deformation of lithium metal combine to give the counterintuitive result: the fastest-growing protrusions have the largest diameter.

25 ENERGY STORAGE↗
DOE OSTI2016

Emitter/absorber interface of CdTe solar cells

The performance of CdTe solar cells can be very sensitive to the emitter/absorber interface, especially for high-efficiency cells with high bulk lifetime. Performance losses from acceptor-type interface defects can be significant when interface defect states are located near mid-gap energies. Numerical simulations show that the emitter/absorber band alignment, the emitter doping and thickness, and the defect properties of the interface (i.e., defect density, defect type, and defect energy) can all play significant roles in the interface recombination. In particular, a type I heterojunction with small conduction-band offset (0.1 eV ≤ ΔE{sub C} ≤ 0.3 eV) can help maintain good cell efficiency in spite of high interface defect density, much like with Cu(In,Ga)Se{sub 2} (CIGS) cells. The basic principle is that positive ΔE{sub C}, often referred to as a “spike,” creates an absorber inversion and hence a large hole barrier adjacent to the interface. As a result, the electron-hole recombination is suppressed due to an insufficient hole supply at the interface. A large spike (ΔE{sub C} ≥ 0.4 eV), however, can impede electron transport and lead to a reduction of photocurrent and fill-factor. In contrast to the spike, a “cliff” (ΔE{sub C} < 0 eV) allows high hole concentration in the vicinity of the interface, which will assist interface recombination and result in a reduced open-circuit voltage. Another way to mitigate performance losses due to interface defects is to use a thin and highly doped emitter, which can invert the absorber and form a large hole barrier at the interface. CdS is the most common emitter material used in CdTe solar cells, but the CdS/CdTe interface is in the cliff category and is not favorable from the band-offset perspective. The ΔE{sub C} of other n-type emitter choices, such as (Mg,Zn)O, Cd(S,O), or (Cd,Mg)Te, can be tuned by varying the elemental ratio for an optimal positive value of ΔE{sub C}. These materials are predicted to yield higher voltages and would therefore be better candidates for the CdTe-cell emitter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Application of Spatial Data Modeling and Geographical Information Systems (GIS) for Identification of Potential Siting Options for Various Electrical Generation Sources

Oak Ridge National Laboratory (ORNL) initiated an internal National Electric Generation Siting Study, which is an ongoing multiphase study addressing several key questions related to our national electrical energy supply. This effort has led to the development of a tool, OR-SAGE (Oak Ridge Siting Analysis for power Generation Expansion), to support siting evaluations. The objective in developing OR-SAGE was to use industry-accepted approaches and/or develop appropriate criteria for screening sites and employ an array of Geographic Information Systems (GIS) data sources at ORNL to identify candidate areas for a power generation technology application. The initial phase of the study examined nuclear power generation. These early nuclear phase results were shared with staff from the Electric Power Research Institute (EPRI), which formed the genesis and support for an expansion of the work to several other power generation forms, including advanced coal with carbon capture and storage (CCS), solar, and compressed air energy storage (CAES). Wind generation was not included in this scope of work for EPRI. The OR-SAGE tool is essentially a dynamic visualization database. The results shown in this report represent a single static set of results using a specific set of input parameters. In this case, the GIS input parameters were optimized to support an economic study conducted by EPRI. A single set of individual results should not be construed as an ultimate energy solution, since US energy policy is very complex. However, the strength of the OR-SAGE tool is that numerous alternative scenarios can be quickly generated to provide additional insight into electrical generation or other GIS-based applications. The screening process divides the contiguous United States into 100 x 100 m (1-hectare) squares (cells), applying successive power generation-appropriate site selection and evaluation criteria (SSEC) to each cell. There are just under 700 million cells representing the contiguous United States. If a cell meets the requirements of each criterion, the cell is deemed a candidate area for siting a specific power generation form relative to a reference plant for that power type. Some SSEC parameters preclude siting a power plant because of an environmental, regulatory, or land-use constraint. Other SSEC assist in identifying less favorable areas, such as proximity to hazardous operations. All of the selected SSEC tend to recommend against sites. The focus of the ORNL electrical generation source siting study is on identifying candidate areas from which potential sites might be selected, stopping short of performing any detailed site evaluations or comparisons. This approach is designed to quickly screen for and characterize candidate areas. Critical assumptions supporting this work include the supply of cooling water to thermoelectric power generation; a methodology to provide an adequate siting footprint for typical power plant applications; a methodology to estimate thermoelectric plant capacity while accounting for available cooling water; and a methodology to account for future ({approx}2035) siting limitations as population increases and demands on freshwater sources change. OR-SAGE algorithms were built to account for these critical assumptions. Stream flow is the primary thermoelectric plant cooling source evaluated in this study. All cooling was assumed to be provided by a closed-cycle cooling (CCC) system requiring makeup water to account for evaporation and blowdown. Limited evaluations of shoreline cooling and the use of municipal processed water (gray) cooling were performed. Using a representative set of SSEC as input to the OR-SAGE tool and employing the accompanying critical assumptions, independent results for the various power generation sources studied were calculated.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

An investigation of the multi-mode Richtmyer-Meshkov instability at a gas/HE interface using Pagosa

Here, in this work, we present a hydrocode Pagosa and explore the Richtmyer-Meshkov Instability (RMI) at an air/high explosive (HE) interface for the first time that is important but has not received much attention yet in the high explosive safety field. Thus, the presented Pagosa can be expected to predict the whole deflagration-to-detonation transition (DDT) process in future. In Pagosa, spatial discretization is implemented on cubic staggered grids by computing different variables at the vertex and the cell center, respectively, a special operator-splitting technique is employed to reduce the computational cost, and an artificial viscosity is added to handle the discontinuous shock waves in our simulations. To quantitatively evaluate the capability of Pagosa to solve these kinds of instabilities, the single mode Rayleigh-Taylor instability (RTI) and the multimode RMI at an air/SF 6 interface are first performed, respectively. The Pagosa results are compared with the related numerical solutions in the existing references and the experimental result. Moreover, a theoretical derivation of growth of RTI is also provided based on our numerical method. Subsequently, we explore the multi-mode RMI at an air/HE interface as well as the effects of several factors using Pagosa. Numerical results show that Pagosa is a powerful toolset to generate the right structures and the amplitude of RTI and RMI at an air/SF 6 interface. The solid HE can be penetrated by a strong shock wave and forms RMI deformations. The RMI at an air/HE interface behaves very different than at an air/SF 6 interface, periodic, decreased oscillation is observed due to material character, and is very sensitive to the initial simulation settings, that is, a tiny change in physical quantities will lead to a remarkable RMI structure, which is also observed in a shock bubble interaction. The findings in this work are significant, and will present a new insight for the high explosive field.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

COMPUTATIONAL MODELING OF IGNITION AND PREMIXED FLAME PROPAGATION INITIATED BY A PRE-CHAMBER TURBULENT JET

Addressing the pressing need for reduced carbon emissions, Turbulent Jet Ignition (TJI) emerges as a promising technology for ultra-lean combustion, offering enhanced thermal efficiencies and minimized cyclic variability in spark-ignited engines. To facilitate rapid testing and integration of this technology, a robust computational modeling framework is crucial. This study delves into the predictive capabilities of computational models for main-chamber ignition and premixed flame propagation using a single-cycle TJI rig measured by Biswas et al. (Applied Thermal Engineering, vol 106, 2016). Employing an open-source compressible flow simulation solver with Large Eddy Simulation (LES) for turbulence modeling, the investigation integrates the conventional Laminar Finite Rate Chemistry (LFRC) model alongside the transported Probability Density Method (PDF) for turbulence-chemistry interaction. A fully-consistent Eulerian Monte-Carlo Fields (EMCF) method is utilized to approximate the transported PDF, while Interaction by Exchange with Mean is employed to close micro-mixing terms in stochastic differential equations. A reduced chemical reaction mechanism with 21 species and 84 reactions (DRM-19) is used for solving chemical kinetics, and a double Gaussian energy deposition model is used to approximate the spark ignition in the pre-chamber. An unstructured O-grid mesh with 0.3 million cells in the prechamber and 1 million cells in the main chamber is employed. Results are divided into two phases: pre-chamber initialization and full TJI simulations. Validation of the predicted pre-chamber flame propagation and the lean ignition in the main-chamber is carried out by using available experimental data. Under quiescent conditions, both the LFRC and transported PDF methods largely underestimate the flame speed and subsequent pressure growth in the pre-chamber. A linear momentum forcing technique is applied to investigate the impact of initial turbulence in the pre-chamber, demonstrating a notable influence on flame propagation. Fine-tuning of the forcing coefficient reproduces the sudden pressure growth observed in the experiment. The experimentally validated pre-chamber simulation serves as the initial condition for the full TJI simulations. It is found that the LFRC model fails to predict lean-ignition in the main-chamber, resulting in a misfiring event. Incorporation of turbulence-chemistry interaction using the transported PDF method substantially improves the prediction of the ignition event in the main-chamber, achieving fair qualitative agreement and quantitative validation of combustion parameters within ±10% of the reported experimental data. The rich simulation results consisting of a full set of statistical description of the thermo-chemical states enable us to gain deep insights into the ignition mechanisms in the main chamber, which is limited when done experimentally. A novel dual ignition phenomenon is revealed in the TJI rig for the first time. Initially, a primary ignition kernel is formed at a downstream location which eventually detaches from the main jet. As the jet momentum decreases, a secondary ignition event follows, this time at a more upstream location which eventually combines with the primary ignition kernel to form a single connected flame front. Investigation of these ignition sequences in chemical composition space reveal distinct differences between the two. The primary ignition event in the main-chamber is followed by a large concentration of active radicals from the pre-chamber jet, accelerating the chain-branching steps, characterizing what has been referred to as flame ignition. In contrast, the secondary ignition occurs in the absence of active radicals in the pre-chamber jet, hence characterized as jet ignition. Further analysis of the effect of pre-chamber jet characteristics on lean ignition in the main-chamber is conducted by setting up cases with different initial pressure ratios (por) between the two chambers, a non-dimensional parameter, ranging from 1.2 to 3.2. As the initial pressure ratio increases, jet momentum increases, with dual ignition observed in cases above por= 2.2. Case with por= 3.2 lead to misfiring. The effect of ignition sequence on global combustion characteristics of TJI is analyzed. Dual ignition events lead to non-monotonicity in combustion characteristics such as global reaction progress variable, flame penetration, and global heat release rate. In dual ignition events, although the rate of fuel consumption and global heat release rate is initially lower, the secondary ignition leads to a sudden increase in flame surface area, resulting in a sudden jump and promoting the overall performance of the TJI system.

42 ENGINEERING↗
DOE OSTI2021

Effect of electrode rinse solutions on the electrodialysis of concentrated salts

The data presented indicate that modest attention to the chemistry of the electrode rinse solution can yield as much as 56% improvement in process efficiency. When operating electrodialysis (ED) with salt concentrations greater than 10,000 mg/l (as NaCl) the amperage can be relatively high even at low voltages. To maximize the overall rate of ion transport from diluate to concentrate, there is a need to minimize resistances in the electrode cells since these can represent as much as 30% of the total resistances in the entire process and in this particular ED unit, represented resistance roughly equivalent to that within the membrane stack. This work describes the performance of a 10-cell pair, 200 cm 2 (0.02 m 2 ) per membrane, pilot ED unit operated in batch mode at 5 V potential. The feedstock to the stack was varied from 0.5% to 6% NaCl. Results from Volt-amp profiles (2.0–15 V) were used as the rationale for choosing the preferred electrode rinse solution, 90 g/l (kg/m 3 ) disodium sulfate at pH 12.5. The recommended solution of 30 g/l (kg/m 3 ) disodium sulfate at neutral pH was tested against stronger solutions (60, 90, and 120 g/l (kg/m 3 ) disodium sulfate) at neutral pH and with 1 g/l (kg/m 3 ) sodium hydroxide added to yield solutions at pH 12.5. There were stark differences in the performance of the ED unit between the solutions at pH 7 and those at pH 12.5. The slopes of the Volt-amp profiles improved indicating less resistance to ion flow at pH 12.5. Most of the difference can be attributed to the greater conductivity of sodium hydroxide compared to disodium sulfate, where even a modest addition of 1 g/l (kg/m 3 ) sodium hydroxide increased the conductivity of the solution between 8 and 20% depending on the concentration of disodium sulfate. Most notably, the initiation voltage was 2.39 ± 0.08 V with solutions at pH 7 and 1.99 V ± 0.04 V when the rinse solutions were around pH 12.5, a difference of around 0.42 V. Since the full batch runs were performed at 5.0 V, this 0.42 V differential represented a loss of 8% in process efficiency. A series of tests showed a shift in initiation voltage occurred between pH 11.5 and 12.5. Nernst equations for water electrolysis are coupled with a simple flux model that estimates the concentration of hydroxide and hydronium ions at the electrode surfaces. This model indicates that the potential demanded by the electrodes is directly linked to the current. Furthermore, there is a steep drop in the potential demanded by the anode when there is sufficient hydroxide available to generate oxygen from hydroxide as opposed to generation from water. The voltage demand is minimal at pH 12.5 and reflective of the reference standard voltage (just over 1.23 V predicted at 0.1 amps). However, the flux model predicts that the voltage demanded by the electrodes at pH 7 is 1.61 V at 0.1 amps (the lowest amperage measurable with the power pack). In conclusion, comparing this result to the reference standard (E 0 = -1.23 V) yields a satisfactory explanation for the observed difference below reference standard of 0.42 V.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

PERFORMANCE EVALUATION OF A SUSTAINABLE AND ENERGY EFFICIENT RE-ROOFING TECHNOLOGY USING FIELD-TEST DATA

Three test attics were constructed to evaluate a new sustainable method of re-roofing utilizing photo-voltaic (PV) laminates, metal roofing panels, and PCM heat sink in the Envelope Systems Research Apparatus (ESRA) facility in the ORNL campus. Figure 1 is a picture of the three attic roofs located adjacent to each other. The leftmost roof is the conventional shingle roof, followed by the metal panel roof incorporating the cool-roof coating, and third from left is the roof with the PCM. On the PCM roof, the PV panels are seen as well; they're labelled from left-to-right as panels 5, 6 and 7. The metal panel roof consists of three metal panels with the cool-roof coating; in further discussion this is referred to as the infrared reflective (IRR) metal roof. The IRR metal panels reflect the incoming solar radiation and then quickly re-emit the remaining absorbed portion, thereby reducing the solar heat gain of the attic. Surface reflectance of the panels were measured using a Solar Spectrum Reflectometer. In the 0.35-2.0 {mu}m wavelength interval, which accounts for more than 94% of the solar energy, the IRR panels have an average reflectance of 0.303. In the infrared portion of the spectrum, the IRR panel reflectance is 0.633. The PCM roof consists of a layer of macro-encapsulated bio-based PCM at the bottom, followed by a 2-cm thick layer of dense fiberglass insulation with a reflective surface on top, and metal panels with pre-installed PV laminates on top. The PCM has a melting point of 29 C (84.2 F) and total enthalpy between 180 and 190 J/g. The PCM was macro-packaged in between two layers of heavy-duty plastic foil forming arrays of PCM cells. Two air cavities, between PCM cells and above the fiberglass insulation, helped the over-the-deck natural air ventilation. It is anticipated that during summer, this extra ventilation will help in reducing the attic-generated cooling loads. The extra ventilation, in conjunction with the PCM heat sink, are used to minimize thermal stresses due to the PV laminates on sunny days. In PV laminates sunlight is converted into electricity and heat simultaneous. In case of building integrated applications, a relatively high solar absorption of amorphous silicon laminates can be utilized during the winter for solar heating purposes with PCM providing necessary heat storage capacity. However, PV laminates may also generate increased building cooling loads during the summer months. Therefore, in this project, the PCM heat sink was to minimize summer heat gains as well. The PCM-fibreglass-PV assembly and the IRR metal panels are capable of being installed directly on top of existing shingle roofs during re-roofing, precluding the need for recycling or disposal of waste materials. The PV laminates installed on the PCM attic are PVL-144 models from Uni-Solar. Each laminate contains 22 triple junction amorphous silicon solar cells connected in series. The silicon cells are of dimensions 356 mm x 239 mm (14-in. x 9.4-in.). The PVL-144 laminate is encapsulated in durable ETFE (poly-ethylene-co-tetrafluoroethylene) high light-transmissive polymer. Table 1 lists the power, voltage and current ratings of the PVL-144 panel.

14 SOLAR ENERGY↗
DOE OSTI2019

The utility of {sup 82}Rb PET for myocardial viability assessment: Comparison with perfusion-metabolism {sup 82}Rb-{sup 18}F-FDG PET

Background: {sup 82}Rb kinetics may distinguish scar from viable but dysfunctional (hibernating) myocardium. We sought to define the relationship between {sup 82}Rb kinetics and myocardial viability compared with conventional {sup 82}Rb and {sup 18}F-fluorodeoxyglucose (FDG) perfusion-metabolism PET imaging. Methods: Consecutive patients (N = 120) referred for evaluation of myocardial viability prior to revascularization and normal volunteers (N = 37) were reviewed. Dynamic {sup 82}Rb 3D PET data were acquired at rest. {sup 18}F-FDG 3D PET data were acquired after metabolic preparation using a standardized hyperinsulinemic-euglycemic clamp. {sup 82}Rb kinetic parameters K{sub 1}, k{sub 2}, and partition coefficient (KP) were estimated by compartmental modeling Results: Segmental {sup 82}Rb k{sub 2} and KP differed significantly between scarred and hibernating segments identified by Rb-FDG perfusion-metabolism (k{sub 2}, 0.42 ± 0.25 vs. 0.22 ± 0.09 min{sup −1}; P < .0001; KP, 1.33 ± 0.62 vs. 2.25 ± 0.98 ml/g; P < .0001). As compared to Rb-FDG analysis, segmental Rb KP had a c-index, sensitivity and specificity of 0.809, 76% and 84%, respectively, for distinguishing hibernating and scarred segments. Segmental k{sub 2} performed similarly, but with lower specificity (75%, P < .001) Conclusions: In this pilot study, {sup 82}Rb kinetic parameters k{sub 2} and KP, which are readily estimated using a compartmental model commonly used for myocardial blood flow, reliably differentiated hibernating myocardium and scar. Further study is necessary to evaluate their clinical utility for predicting benefit after revascularization. [French] French Abstract: Contexte: La cinétique du {sup 82}Rb pourrait être utilisée pour distinguer la fibrose myocardique des zones viables mais dysfonctionnelles (en hibernation). Dans cette étude, nous avons cherché à définir la relation entre la cinétique du {sup 82}Rb et la viabilité myocardique en comparant les images de perfusion et métabolisme myocardique utilisant le {sup 82}Rb et le {sup 18}F-fluorodésoxyglucose (FDG) Méthodes: les données obtenues chez 120 patients consécutifs (N = 120) référés pour évaluation de la viabilité du myocarde avant revascularisation et 37 volontaires considérés normaux (N = 37) ont été étudieés. Les données TEP 3D dynamiques {sup 82}Rb ont été acquises au repos. Les données TEP 3D au {sup 18}F-FDG ont été acquises après préparation métabolique utilisant une pince hyperinsulémique-euglycémique normalisée. Les paramètres k1, k2 et le coefficient de partage (KP) de la cinétique du {sup 82}R bont été évalues par modélisation compartimentale. Résultats: les paramètres k2 et KP de distribution du {sup 82}Rb se sont révélés significativement différent entre les zones tissulaires cicatricielles fibreuses et celles en hibernation identifiées par étude métabolique au FDG (k2, 0,42 ± 0,25 vs. 0,22 ± 0,09 min{sup −1}; P < 0,0001; KP, 1,33 ± 0,62 vs. 2,25 ± 0,98 ml/g; P < 0,0001). Par rapport aux données FDG, le paramètre KP du rubidium a révélé un indice de concordance de 0,809 et une sensibilité et spécificité de 76% et 84%, pour la distinction des segments en hibernation et cicatrisés. Les résultats du paramètre k2 se sont révélés similaires, mais avec une spécificité plus faible calculée à 75% (P < 0,001). Conclusions: Dans cette étude pilote, les paramètres cinétiques k2 et KP de perfusion myocardique au {sup 82}Rb, qui sont facilement estimés à l’aide d’un modèle compartimental couramment utilisé pour flux sanguin myocardique, ont permis de différencier de manière fiable le myocarde cicatricielle des zones myocardiques hibernantes. Une étude plus approfondie est souhaitable pour valider leur utilité clinique en revacularisation. [Spanish] Spanish Abstract: Antecedentes: La cinética con {sup 82}Rb puede distinguir las cicatrices miocárdicas del tejido viable pero disfuncional (hibernante). Buscamos definir la relación entre la cinética del {sup 82}Rb y la viabilidad miocárdica comparada con las imágenes convencionales de PET con {sup 82}Rb y {sup 18}F-flurodeoxyglucosa (FDG). Métodos: se evaluaron a Pacientes Consecutivos (N = 120) referidos para evaluación de viabilidad miocárdica previos a revascularización y voluntarios normales (N = 37). Los datos de PET 3D dinámico con {sup 82}Rb fueron adquiridos en reposo. Los datos de {sup 18}F-FDG 3D PET fueron adquiridos posterior a la preparación metabólica usando un clamp hiperinsulínico-euglucémico. Los patrones cinéticos K1, k2 y el coeficiente de partición (KP) fueron estimados por el modelo compartimental. Resultados: el k2 y KP del {sup 82}Rb permitueron distinguier el tejido cicatricial de los segmentos hibernados identificados por la vía perfusión metabolismo de Rb-FDG (k{sub 2}, 0.42 ± 0.25 vs. 0.22 ± 0.09 min-1; P < .0001; KP, 1.33 ± 0.62 vs. 2.25 ± 0.98 ml/g; P < .0001). En comparación con el análisis de Rb-FDG, el KP segmentario del Rb tuvo un índice-c, sensbilidad y especificidad de 0.809 76 y 84%, respectivamente, para distinguir segmentos hibernantes y cicatriciales. k2 Segmentario tuvo un desempeño similar pero con una menor especificidad (75%, P < .001). Conclusiones: En este estudio piloto, los parámetros cinéticos k2 y KP del {sup 82}Rb, los cuales son estimados usando un modelo compartimental usado comúnmente para flujo sanguíneo miocárdico, diferenciaron el miocardio hibernante del cicatricial. Se necesita estudiar más a fondo para evaluar la utilidad clínica para la predicción del beneficio posterior a la revascularización [Chinese] Chinese Abstract: 背景: 铷-82({sup 82}Rb)药代动力学可能区分梗死与功能受损但存活的心肌(冬眠心肌)。我们将探讨{sup 82}Rb药代动力学与存活心肌的关系,并与常规的{sup 82}Rb和{sup 18}F-氟脱氧葡萄糖(FDG)灌注-代谢PET显像进行比较。 方法: 连续纳入120名血运重建前评估存活心肌的患者和37名正常志愿者。获得静息{sup 82}Rb 3D-PET动态采集数据;采用标准化的高胰岛素 - 正葡萄糖钳夹试验得到{sup 18}F-FDG 3D PET代谢显像数据; 通过房室模型计算{sup 82}Rb动力学参数k{sub 1},k{sub 2}和分配系数(KP)。 结果: 以Rb-FDG灌注代谢显像鉴定疤痕心肌组和冬眠心肌组,两组的{sup 82}Rb节段性 k{sub 2}值和KP值有明显差异(k{sub 2}, 0.42 ± 0.25 vs 0.22 ± 0.09 min{sup −1}; P < .0001; KP, 1.33 ± 0.62 vs 2.25 ± 0.98 ml/g; P < .0001)。以Rb-FDG灌注代谢显像为诊断标准,{sup 82}Rb节段性 KP对疤痕和冬眠心肌鉴别效能的c指数,敏感性和特异性分别是0.809, 76%和84%。节段性k{sub 2}的鉴别效能与KP相似,但特异性较低(75%,P < .001)。 结论: 在本试验性研究中,通过常规用于{sup 82}Rb心肌血流量测定的房室模型计算出的{sup 82}Rb动力学参数k{sub 2}和KP,可以有效的区分冬眠心肌和瘢痕心肌。 但需要进一步的研究来评估其对预测血运重建是否获益的临床价值。.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2011

Increasing the solar photovoltaic energy capture on sunny and cloudy days

This report analyzes an extensive set of measurements of the solar irradiance made using four identical solar arrays and associated solar sensors (collectively referred to as solar collectors) with different tilt angles relative to the earth's surface, and thus the position of the sun, in order to determine an optimal tracking algorithm for capturing solar radiation. The study included a variety of ambient conditions including different seasons and both cloudy and cloud-free conditions. One set of solar collectors was always approximately pointed directly toward the sun (DTS) for a period around solar noon. These solar collectors thus captured the direct beam component of the solar radiation that predominates on sunny days. We found that on sunny days, solar collectors with a DTS configuration captured more solar energy in accordance with the well-known cosine dependence for the response of a flat-surfaced solar collector to the angle of incidence with direct beam radiation. In particular, a DTS orientation was found to capture up to twice as much solar energy as a horizontal (H) orientation in which the array is tilted toward the zenith. Another set of solar collectors always had an H orientation, and this best captured the diffuse component of the solar radiation that predominates on cloudy days. The dependence of the H/DTS ratio on the solar-collector tilt angle was in approximate agreement with the Isotropic Diffuse Model derived for heavily overcast conditions. During cloudy periods, we found that an H configuration increased the solar energy capture by nearly 40% compared to a DTS configuration during the same period, and we estimate the solar energy increase of an H configuration over a system that tracks the obscured solar disk could reach 50% over a whole heavily-overcast day. On an annual basis the increase is predicted to be much less, typically only about 1%, because the contribution of cloudy days to the total annual solar energy captured by a photovoltaic system is small. These results are consistent with the solar tracking algorithm optimized for cloudy conditions that we proposed in an earlier report and that was based on a much smaller data set. Improving the harvesting of solar energy on cloudy days deserves wider attention due to increasing efforts to utilize renewable solar energy. In particular, increasing the output of distributed solar power systems on cloudy days is important to developing solar-powered home fueling and charging systems for hydrogen-powered fuel-cell electric and battery-powered vehicles, respectively, because it reduces the system size and cost for solar power systems that are designed to have sufficient energy output on the worst (cloudy) days. (author)

14 SOLAR ENERGY↗
DOE OSTI2026

A New Shutdown Dose Rate Benchmark Problem for Representative Fusion Applications

Here, this work introduces a new benchmark problem for calculating shutdown dose rates (SDDRs) aimed at fusion reactor applications. The model is designed to represent a simplified version of a typical ITER port plug. The responses of interest include neutron flux, gamma flux, and gamma SDDR at 12 different locations scattered throughout the port. This article outlines the geometry specifications of the problem, provides material definitions for the components, specifies the required responses to be calculated, and presents the source definition information. The need for this benchmark arises from the limited availability of publicly accessible references, with only one benchmark representing the typical dimensions and materials found in fusion systems. This existing benchmark has been cited extensively, reflecting the demand within the scientific community to test both established and novel workflows for SDDR calculations. However, since its presentation at a conference in 2011, the results have become increasingly well known. Moreover, the absence of formal publication and peer review has led to the details of this benchmark being extracted from secondary sources, such as subsequent studies that reference it. As a result, analysts are left with significant flexibility in interpreting the key parameters, which can be adjusted to account for unknown systematic errors, ultimately reproducing the already well-known responses. This new benchmark serves as an updated version of that earlier work, with the aim of providing a more reliable description of the materials and their impurities, which is crucial for assessing activation and subsequent gamma emission. Additionally, it seeks to provide a geometry that more closely represents an ITER port plug. The improvements in the problem definition will lead to a more reproducible benchmark problem, while also presenting the radiation transport community with a completely new challenge. The results will be published in a future article to allow analysts adequate time to analyze this problem independently.

Benchmark↗
DOE OSTI2023

NbTa_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys niobium-tantalum (Nb-Ta). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Nb. For Ta, p semi-core states as valence were chosen. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on NERSC-Perlmutter using the VASP 6.3.2. The VASP calculations for every atomic structure have been performed in 2 main steps: 1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out. 2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Cases 1-10 have been run without generating the file 'vaspout.h5'. Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for ternary alloys is AXBYCZ, where A, B, and C refer to the constituents, and X, Y, and Z are positive integers that represent the number of atoms for each constituent and their values still sum up to 128. Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included. The files contained in each sub-directory 'case-*' for each atomic structure are as follows: FILES contained in each subdirectory with name case-N where N ranges between 11 and 100, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. 0.POSCAR: input file that defines the atomic structure of a system 4. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 5. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file 7. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 9. OUTCAR: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. Subdirectories with name case-N, where N ranges between 1 and 10 (extremes included) contain all the files listed above except 'vaspout.h5'. Subdirectories with name case-N, where N ranges between 41 and 60 (extremes included), contain a duplicate copy of the files listed above except for KPOINTS. The names of the duplicate files end with -bis, and correspond to a second VASP calculation that has converged to a different optimized geometry. This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216. REFERENCES (1) Kresse, G. and Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. and Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal-amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251 (1994) (3) Kresse, G. and Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. materials science 6, 15-50 (1996) (4) Kresse, G. and Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. review B 54, 11169 (1996) (5) Kresse, G. and Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗
DOE OSTI2023

TaV_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys tantalum-vanadium (Tanu-V). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the element V. For Ta, p semi-core states as valence were chosen. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on NERSC-Perlmutter and OLCF-Summit using the VASP 6.3.2. The VASP calculations for every atomic structure have been performed in 2 main steps: 1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out. 2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Cases 1-10 have been run without generating the file 'vaspout.h5'. Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for binary alloys is AXBY, where A and B refer to the constituents, whereas X and Y are positive integers that represent the number of atoms for each constituent and their values still sum up to 128. Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included. The files contained in each sub-directory 'case-*' for each atomic structure are as follows: FILES contained in each subdirectory with name case-N where N ranges between 11 and 100, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. 0.POSCAR: input file that defines the atomic structure of a system 4. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 5. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file 7. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 9. OUTCAR: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. Subdirectories with name case-N, where N ranges between 1 and 10 (extremes included) contain all the files listed above except 'vaspout.h5'. Subdirectories with name case-N, where N ranges between 41 and 60 (extremes included), contain a duplicate copy of the files listed above except for KPOINTS. The names of the duplicate files end with -bis, and correspond to a second VASP calculation that has converged to a different optimized geometry. This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216. REFERENCES (1) Kresse, G. and Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. and Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal-amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251 (1994) (3) Kresse, G. and Furthmuller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. materials science 6, 15-50 (1996) (4) Kresse, G. and Furthmuller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. review B 54, 11169 (1996) (5) Kresse, G. and Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗
DOE OSTI2023

NbV_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys niobium-vanadium (Nb-V). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Nb and V. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on NERSC-Perlmutter and OLCF-Summit using the VASP 6.3.2. The VASP calculations for every atomic structure have been performed in 2 main steps: 1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out. 2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Cases 1-10 have been run without generating the file 'vaspout.h5'. Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for binary alloys is AXBY, where A and B refer to the constituents, whereas X and Y are positive integers that represent the number of atoms for each constituent and their values still sum up to 128. Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included. The files contained in each sub-directory 'case-*' for each atomic structure are as follows: FILES contained in each subdirectory with name case-N where N ranges between 11 and 100, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. 0.POSCAR: input file that defines the atomic structure of a system 4. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 5. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file 7. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 9. OUTCAR: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. Subdirectories with name case-N, where N ranges between 1 and 10 (extremes included) contain all the files listed above except 'vaspout.h5'. Subdirectories with name case-N, where N ranges between 41 and 60 (extremes included), contain a duplicate copy of the files listed above except for KPOINTS. The names of the duplicate files end with -bis, and correspond to a second VASP calculation that has converged to a different optimized geometry. This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216. REFERENCES (1) Kresse, G. and Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. and Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal-amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251 (1994) (3) Kresse, G. and Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. materials science 6, 15-50 (1996) (4) Kresse, G. and Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. review B 54, 11169 (1996) (5) Kresse, G. and Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

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