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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mapping dynamical ejecta and disk masses from numerical relativity simulations of neutron star mergers

Abstract We present fitting formulae for the dynamical ejecta properties and remnant disk masses from the largest to date sample of numerical relativity simulations. The considered data include some of the latest simulations with microphysical nuclear equations of state (EOS) and neutrino transport as well as other results with polytropic EOS available in the literature. Our analysis indicates that the broad features of the dynamical ejecta and disk properties can be captured by fitting expressions, that depend on mass ratio and reduced tidal parameter. The comparative analysis of literature data shows that microphysics and neutrino absorption have a significant impact on the dynamical ejecta properties. Microphysical nuclear EOS lead to average velocities smaller than polytropic EOS, while including neutrino absorption results in larger average ejecta masses and electron fractions. Hence, microphysics and neutrino transport are necessary to obtain quantitative models of the ejecta in terms of the binary parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

NUM-DAT File Format Specification: Used in M-9 Gun Experiment Data Archiving

The M-9 Shock and Detonation Physics group executes experiments on gun and explosive platforms with large numbers of oscilloscopes used for data acquisition. The data acquisition from these oscilloscopes was automated many years ago using a custom piece of software called RunDig . The default save format from this software is a custom structure referred to as "NUM-DAT" format. This file format includes a text ".DAT" file which is a header file used to interpret the binary ".NUM" file which contains the oscilloscope data. The data save format was originally developed by John Vorthman and has been in use by M-9 personnel for over 20 years. This data format has been used for archiving data from experiments performed by M-9 personnel at TA-40, TA-39, and the TA-55 Impact Test Facility. Numerous custom analysis and visualization programs have also been developed, and continue to be used, that utilize this data format. This document describes the NUM-DAT format and provides code examples for reading the format and converting it to other formats.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Approaches for handling high-dimensional cluster expansions of ionic systems

Disordered multicomponent systems attract great interest due to their engineering design flexibility and subsequent rich space of properties. However, detailed characterization of the structure and atomic correlations remains challenging and hinders full navigation of these complex spaces. A lattice cluster expansion is one tool to obtain configurational and energetic resolution. While in theory a cluster expansion can be applied to any system of any dimensionality, the method has primarily been used in binary systems or ternary alloys. Here we apply cluster expansions in high-component ionic systems, setting up the largest cluster expansion ever attempted to our knowledge. In doing so, we address and discuss challenges specific to high-component ionic systems, namely charge state assignments, structural relaxations, and rank-deficient systems. We introduce practical procedures to make the fitting and analysis of complex systems tractable, providing guidance for future computational studies of disordered ionic systems.

25 ENERGY STORAGE↗
DOE OSTI2023

A Dark Siren Measurement of the Hubble Constant with the LIGO/Virgo Gravitational Wave Event GW190412 and DESI Galaxies

Abstract We present a measurement of the Hubble Constant H 0 using the gravitational wave event GW190412, an asymmetric binary black hole merger detected by LIGO/Virgo, as a dark standard siren. This event does not have an electromagnetic counterpart, so we use the statistical standard siren method and marginalize over potential host galaxies from the Dark Energy Spectroscopic Instrument (DESI) survey. GW190412 is well-localized to 12 deg 2 (90% credible interval), so it is promising for a dark siren analysis. The dark siren value for H 0 = 85.4 − 33.9 + 29.1 km s −1 Mpc −1 , with a posterior shape that is consistent with redshift overdensities. When combined with the bright standard siren measurement from GW170817 we recover H 0 = 77.96 − 5.03 + 23.0 km s −1 Mpc −1 , consistent with both early and late-time Universe measurements of H 0 . This work represents the first standard siren analysis performed with DESI data, and includes the most complete spectroscopic sample used in a dark siren analysis to date.

Ballard, W.↗
DOE OSTI2026

Development of SAM Code Capabilities for Safety Analysis of GCR Air-ingress Events

Air-ingress following a depressurized loss-of-forced-cooling (DLOFC) event is a challenging, multiphysics safety scenario for High-Temperature Gas-Cooled Reactors (HTGRs), involving coupled gas composition transport, buoyancy-driven flow redistribution, graphite oxidation, and structural heat-up. Despite its importance — air ingress is a key scenario identified in the PIRT process for the HTGRs — existing system-level safety codes have lacked the integrated capability to simulate the complete event sequence with high confidence. This report documents the development, validation, and demonstration of three new capabilities in the SAM code to address this gap: (1) a multi-component gas mixture flow model with binary diffusion to track the helium-air composition and its effect on system density and flow; (2) a 0-D graphite oxidation model based on the Roes correlation, including oxygen consumption and exothermic heat release; and (3) an isentropic critical flow model for accurate representation of primary system depressurization through a break. These capabilities are validated against two benchmark experiments. The NSTF heavy-gas ingress experiment validates the multi-component flow model: SAM correctly reproduces the rapid buoyancydriven flow stagnation and subsequent natural circulation recovery driven by composition-dependent density changes. The NACOK graphite oxidation experiment validates the oxidation model: SAM predicts a bottom-level graphite weight loss of 25%, in close agreement with the measured 24%, and reproduces the strong axial nonuniformity and block-geometry dependence of oxidation, at a level comparable to the SPECTRA and TINTE codes. The validated capabilities are then exercised together in an integrated, reactor-scale simulation of a DLOFC air-ingress transient in a simplified HTR-PM pebble-bed reactor. In a single calculation spanning approximately 8 days, SAM reproduces the complete accident sequence: rapid depressurization, densityand diffusion-driven air ingress over ˜15 hours, onset of buoyancy-driven natural circulation, exothermic graphite oxidation with a peak fuel temperature at ˜62 hours, and eventual passive cooldown. These results demonstrate that SAM now provides the nuclear community with a preliminarily validated, modern systemlevel tool for HTGR air-ingress safety analysis, filling a recognized capability gap. Future extensions to broaden species tracking, improve oxidation chemistry, and refine the reactor model are discussed.

Yang, Gang↗
DOE OSTI2025

Dynamic Excitonic Beam Switching with Atomically‐Thin Binary Blazed Gratings

Abstract Beam steering metasurfaces are ultra‐compact optical coatings that offer on‐demand redirection of optical power to specific diffraction orders. To achieve this, spatial gradients are commonly introduced in the phase of light scattered by plasmon or Mie resonant nanoparticles within the metasurface grating's unit cell. However, these phase gradients are oftentimes difficult to tune post‐fabrication. Recently, excitons in monolayer 2D semiconductors have emerged as a new metasurface building block, due to their strong and electrically‐tunable resonant light‐matter interaction. These 2D excitonic metasurfaces offer the tantalizing prospect of beam switching within a single monolayer. Here, it is demonstrated how the 2D analog of binary blazed gratings enables such beam switching by mere nanopatterning of a large monolayer WS 2 , even though nanoscale ribbons of WS 2 do not support geometrical resonances. By introducing a gradient in the nanoribbon width within the metasurface unit cell, an amplitude gradient combined with a small phase gradient in the scattered fields results in asymmetric diffraction efficiencies. Using a scattered‐field analysis, it is shown that these gradients can be further engineered via interference effects with the substrate reflection. Finally, the electrical tunability of the exciton resonance is leveraged to achieve selective and dynamic beam switching with an atomically‐thin metasurface.

Guarneri, Ludovica [Van der Waals‐Zeeman Institute↗
DOE OSTI2020

High-Entropy Metal Sulfide Nanoparticles Promise High-Performance Oxygen Evolution Reaction

Transition metal sulfide with a multi-elemental nature represents a class of promising catalysts for oxygen evolution reaction (OER) owing to its good catalytic activity. However, its synthesis remains a grand challenge due to the thermodynamic immiscibility of the constituent multimetallic elements in a sulfide structure. Herein, we for the first time report a high-entropy metal sulfide (HEMS, i.e., (CrMnFeCoNi)Sx) solid solution nanoparticles. Computational and X-ray photoelectron spectroscopy analysis suggest that the (CrMnFeCoNi)S x exhibits a synergistic effect among metal atoms that leads to desired electronic states to enhance OER activity. The (CrMnFeCoNi)Sx nanoparticles showed one of the best activities (low overpotential 295 mV at 100 mA cm -2 in 1 M KOH solution) and good durability (only slight polarization after 10 hours by chronopotentiometry) compared with the unary, binary, ternary, and quaternary sulfide counterparts. This work opens up a new synthesis paradigm for high-entropy compound nanoparticles for highly efficient electrocatalysis applications.

25 ENERGY STORAGE↗
DOE OSTI2020

Fabrication of yttrium hydride for high-temperature moderator application

We report given the superior thermal stability and highly attainable hydrogen density, yttrium hydride is an excellent high-temperature moderator material in advanced thermal neutron spectrum reactors that require small core volumes. Large-scale, crack-free, bulk yttrium hydride is in high demand; however, fabrication of yttrium hydride is challenging and has not been demonstrated for nearly half century. The associated challenges are discussed herein. In response to these challenges, a hydriding system was designed and constructed at Oak Ridge National Laboratory and was used to successfully fabricate crack-free yttrium hydride in complex geometries at large scales. This was accomplished by precisely controlling the hydrogen’s partial pressure and the retort temperature, which was informed by the well-established thermodynamic properties of the binary H–Y system. Hydrogen content in as-fabricated hydride was determined by weight change, an approach which was considered reliable based on the use of ultra–high-purity yttrium, the absence of oxide phases up to levels detectable using x-ray diffraction (XRD), and the significant weight gain. Hydrogen distribution along one yttrium hydride rod was evaluated with XRD analysis on materials extracted from different locations on the rod. The results indicated a relatively homogeneous hydrogen distribution along the hydride rod, with <3% uncertainty in the fraction of the δ-phase hydride. In addition, significant efforts are being dedicated to establish a complete database summarizing the thermomechanical and physical properties of as-fabricated yttrium hydride and the irradiation response to facilitate its deployment as a high-temperature moderator in advanced nuclear reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Negative thermal expansion and the role of hybridization in perovskite-type PbTiO 3 -Bi(Cu 0.5 Ti 0.5) O 3

PbTiO 3 -BiMeO 3 ferroelectrics have attracted much attention due to not only their extremely large polarization and piezoelectricity but also their controllable thermal expansion. In this study, we present a new binary system of (1 - x)PbTiO 3 -xBi(Cu 0.5 Ti 0.5 )O 3 possessing large tetragonality and enhanced spontaneous polarization. Interestingly, a combination of near zero thermal expansion and negative thermal expansion over a temperature range of RT to T C (~550 °C) has been observed in tetragonal 0.85PbTiO 3 -0.15Bi(Cu 0.5 Ti 0.5 )O 3 . The comprehensive structure analysis addressed that the abnormal thermal expansion is coupled to the spontaneous volume ferroelectrostriction. Moreover, the chemical bonding investigation by a maximum entropy method further attests that the covalent hybridization of Pb/Bi–O bonds plays a vital role in the improved ferroelectricity and interacts with thermal vibration to dominate the crossover from positive to negative thermal expansion. fINALLY, The present studies would give direct evidence to verify the theoretical calculations and could be extended to reveal the nature of thermal expansion in ferroelectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

IceCube Search for Neutrinos Coincident with Compact Binary Mergers from LIGO-Virgo’s First Gravitational-wave Transient Catalog

Using the IceCube Neutrino Observatory, we search for high-energy neutrino emission coincident with compact binary mergers observed by the LIGO and Virgo gravitational-wave (GW) detectors during their first and second observing runs. In this paper, we present results from two searches targeting emission coincident with the sky localization of each GW event within a 1000 s time window centered around the reported merger time. One search uses a model-independent unbinned maximum-likelihood analysis, which uses neutrino data from IceCube to search for pointlike neutrino sources consistent with the sky localization of GW events. The other uses the Low-Latency Algorithm for Multi-messenger Astrophysics, which incorporates astrophysical priors through a Bayesian framework and includes LIGO-Virgo detector characteristics to determine the association between the GW source and the neutrinos. No significant neutrino coincidence is seen by either search during the first two observing runs of the LIGO-Virgo detectors. We set upper limits on the time-integrated neutrino emission within the 1000 s window for each of the 11 GW events. These limits range from 0.02 to 0.7 GeV cm -2 . We also set limits on the total isotropic equivalent energy, E iso , emitted in high-energy neutrinos by each GW event. These limits range from 1.7 × 10 51 to 1.8 × 10 55 erg. We conclude with an outlook for LIGO-Virgo observing run O3, during which both analyses are running in real time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Beam characterization at NSRL for radiobiological experiments—phase 1

An experimental campaign was carried out at the NASA Space Radiation Laboratory to perform an additional, independent dosimetric characterization of the beams of protons, helium and carbon ions for radiobiological experiments. The campaign was undertaken by the request and with the support from the National Cancer Institute, U.S. In this initial phase, the goals were to obtain a first assessment of the dosimetric reproducibility of the beam control system, including analysis of spatial homogeneity and evaluation of ion beam contamination. They should facilitate the design of further experimental campaigns for beam characterization for radiobiological experiments. Measurements included reference dosimetry with comparison of in-house and external ionization chambers and electrometers, lateral-dose profile measurements in air, depth-dose profile in a water tank, evaluation of water equivalent thickness of a HDPE binary range shifter and estimation of impurities of the investigated helium-ion beam. The experiments and results are presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Experimental validation of color rendition specification criteria based on ANSI/IES TM-30-18

An experiment was conducted to examine color preference specification criteria. Twenty-five participants each evaluated 90 lighting scenes in a room filled with objects. The lighting scenes included nine chromaticity groups, each with 10 systematically-varied color rendition conditions designed to meet or not meet previously proposed color preference specification criteria using ANSI/IES TM-30-18 Rf, Rcs,h1, and Rg. The color rendition conditions did not meet the criterion for none, one, two, or all three of these measures. Participants, who chromatically adapted to each chromaticity group, rated the objects’ color appearance on eight-point scales for saturated-dull, normal-shifted, and like-dislike (preference), as well as a binary for acceptable or unacceptable. The findings corroborate past work, but also indicate that color preference criteria could be adjusted slightly to improve performance, with Tier A having Rf = 78, Rg = 95, and -1% = Rcs,h1 = 15%, Tier B having Rf = 74, Rg = 92, and -7% = Rcs,h1 = 19%, and Tier C having Rf = 70, Rg = 89, -12% = Rcs,h1 = 23%. A companion regression analysis shows models based on Rf, Rg, and Rcs,h1 were superior in predicting color preference compared to those using other measures of color rendition.

Royer, Michael P.↗
DOE OSTI2020

Real-time biomass feedstock particle quality detection using image analysis and machine vision

Abstract A common and costly challenge in the nascent biorefinery industry is the consistent handling and conveyance of biomass feedstock materials, which can vary widely in their chemical, physical, and mechanical properties. Solutions to cope with varying feedstock qualities will be required, including advanced process controls to adjust equipment and reject feedstocks that do not meet a quality standard. In this work, we present and evaluate methods to autonomously assess corn stover feedstock quality in real time and provide data to process controls with low-cost camera hardware. We explore the use of neural networks to classify feedstocks based on actual processing behavior and pixel matrix feature parameterization to further assess particle attributes that may explain the variable processing behavior. We used the pretrained ResNet neural network coupled with a gated recurrent unit (GRU) time-series classifier trained on our image data, resulting in binary classification of feedstock anomalies with favorable performance. The textural aspects of the image data were statistically analyzed to determine if the textural features were predictive of operational disruptions. The significant textural features were angular second moment, prominence, mean height of surface profile, mean resultant vector, shade, skewness, variation of the polar facet orientation, and direction of azimuthal facets. Expansion of these models is recommended across a wider variety of labeled feedstock images of different qualities and species to develop a more robust tool that may be deployed using low-cost cameras within biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2020

Deformation-enhanced hierarchical multiscale structure heterogeneity in a Pd-Si bulk metallic glass

Here, the multiscale structures in a Pd 82 Si 18 binary bulk metallic glass before and after deformation were studied using electron microscopies, high-energy synchrotron X-ray diffraction, and small-angle scattering techniques. The experimental results revealed an enhancement of hierarchical structure heterogeneities on multiple length scales after deformation. Hierarchical multiple shear bands of high number density were observed after bending, introducing complex but periodically distributed residual strain. Pair distribution function analysis revealed that the connectivity of the short-range clusters on the medium-range scale determines the packing density difference between the tension side and the compression side in the sample after bending. In-situ synchrotron X-ray diffraction study also revealed a transformation of connection modes among short-range clusters under uniaxial tension and compression, which is consistent with those of triaxial tension/compression parts upon bending in Pd 82 Si 18 glassy alloys. The nanoscale heterogeneities for metallic glasses after deformation observed by small-angle scattering and transmission electron microscopy may be attributed to the nanoscale amorphous phase separation and interacting multiple shear bands enhanced by plastic deformation. Our findings suggested that the enhancement of hierarchical heterogeneous structure on multiple length scales may explain the excellent plasticity of Pd-Si glassy alloys, deepening the understanding of structure-property relation during plastic deformation in metallic glasses.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Disentangling error structures of precipitation datasets using decision trees

Characterizing error structures in precipitation products not only facilitates their proper applications for scientific and practical purposes but also helps improve their retrieval algorithms and processing methods. Despite the fact that multiple precipitation products have been assessed in the literature, factors that affect their error structures remain inadequately addressed. By interpreting 60 binary decision trees, this study disentangles the error characteristics of precipitation products in terms of their spatiotemporal patterns and geographical factors. Three independent precipitation products - two satellite-based and one reanalysis datasets: the Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) late run (IMERG-L), Soil Moisture to Rain-Advanced SCATterometer (SM2RAIN-ASCAT), and the Modern-Era Retrospective analysis for Research and Applications, Version 2 uncorrected precipitation output (MERRA2-UC), are evaluated across the contiguous United States from 2010 to 2019. Here, the ground-based Stage IV precipitation dataset is used as the ground truth. Results indicate that the MERRA2-UC outperforms the IMERG-L and SM2RAIN-ASCAT with higher accuracy and more stable interannual patterns for the analysis period. Decision trees cross-assess three spatiotemporal factors and find that the underestimation of MERRA2-UC occurs in the east of the Rocky Mountains, and SM2RAIN-ASCAT underestimates precipitation over high latitudes, especially in winter. Additionally, the decision tree method ascribes system errors to nine different geographical characteristics, of which the distance to the coast, soil type, and DEM are the three dominant features. On the other hand, the land cover type, topography position index, and aspect are three relatively weak factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction

The discovery of high-performing and stable materials for sustainable energy applications is a pressing goal in catalysis and materials science. Understanding the relationship between a material’s structure and functionality is an important step in the process, such that viable polymorphs for a given chemical composition need to be identified. Machine-learning-based surrogate models have the potential to accelerate the search for polymorphs that target specific applications. Herein, we report a readily generalizable active-learning (AL) accelerated algorithm for identification of electrochemically stable iridium oxide polymorphs of IrO 2 and IrO 3 . The search is coupled to a subsequent analysis of the electrochemical stability of the discovered structures for the acidic oxygen evolution reaction (OER). Structural candidates are generated by identifying all 956 structurally unique AB2 and AB3 prototypes in existing materials databases (more than 38000). Next, using an active learning approach, we find 196 IrO 2 polymorphs within the thermodynamic amorphous synthesizability limit and reaffirm the global stability of the rutile structure. We find 75 synthesizable IrO 3 polymorphs and report a previously unknown FeF 3 -type structure as the most stable, termed α-IrO 3 . To test the algorithms performance, we compare to a random search of the candidate space and report at least a 2-fold increase in the rate of discovery. Additionally, the AL approach can acquire the most stable polymorphs of IrO 2 and IrO 3 with fewer than 30 density functional theory optimizations. Analysis of the structural properties of the discovered polymorphs reveals that octahedral local coordination environments are preferred for nearly all low-energy structures. Subsequent Pourbaix Ir–H 2 O analysis shows that α-IrO3 is the globally stable solid phase under acidic OER conditions and supersedes the stability of rutile IrO 2 . Calculation of theoretical OER surface activities reveal ideal weaker binding of the OER intermediates on α-IrO 3 than on any other considered iridium oxide. We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evaluation of Formate Salt PCM’s for Latent Heat Thermal Energy Storage

This work examines formate salts as potential phase change materials (PCMs) for middle-high temperature (≤250 °C) latent heat thermal energy storage applications. The thermophysical properties of three formate salts were characterized: pure sodium formate and binary blends of sodium/potassium formate and sodium/calcium formate. The stability of formate PCM’s was evaluated by thermal cycling using differential scanning calorimetry where sodium formate and sodium/potassium formate appeared stable over 600 cycles, while sodium/calcium formate exhibited a monotonic decrease in heat of fusion over the test period. A longer test with sodium formate led to gas release and decomposition of the salt. FTIR analysis of the PCM showed degradation of formate to oxalate. T-history experiments with 50-g PCM quantities demonstrated a bulk supercooling of only 2–3 °C for these salts. Thermal conductivity enhancement of over 700% was achieved by embedding aluminum in the solid PCM. Finally, mild carbon steel was immersed in molten sodium formate for up to 2000 h. Sodium formate was found to be non-corrosive, as calculated by mass loss and confirmed by cross-sectional high-resolution microscopy. FTIR analysis of the PCM after 2000 h shows oxidation at the free surface, while the bulk PCM remained unchanged, further indicating a need to protect the formate from atmospheric exposure when used as a PCM.phase change materials; formate salts; latent heat thermal energy storage; thermal cycling; supercooling; thermal conductivity enhancement; corrosion

25 ENERGY STORAGE↗