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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Architecture of a catalytically active homotrimeric plant cellulose synthase complex

Cellulose is an essential plant cell wall component and represents the most abundant biopolymer on Earth. Supramolecular plant cellulose synthase complexes organize multiple linear glucose polymers into microfibrils as load-bearing wall components. We determined the structure of a poplar cellulose synthase CesA homotrimer that suggests a molecular basis for cellulose microfibril formation. This complex, stabilized by cytosolic plant-conserved regions and helical exchange within the transmembrane segments, forms three channels occupied by nascent cellulose polymers. Secretion steers the polymers toward a common exit point, which could facilitate protofibril formation. CesA’s N-terminal domains assemble into a cytosolic stalk that interacts with a microtubule-tethering protein and may thus be involved in CesA localization. Here, our data suggest how cellulose synthase complexes assemble and provide the molecular basis for plant cell wall engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

ORNL_AISD_NiNb

This dataset describes the nickel-niobium solid solution binary alloy, where the two constituent elements nickel (Ni) and niobium (Nb) are randomly placed on an underlying crystal lattice. This dataset for nickel-niobium (Ni-Nb) alloys available includes the formation energy and bulk modulus for each crystal structure. Each atomic sample has a disordered phase which is obtained starting from an initial regular crystal structure of type body-centered cubic (BCC), face-centered cubic (FCC), or hexagonal compact packed (HCP). The geometry optimization ensures that all the alloy samples reached the equilibrium with negative formation energy. We perform geometry optimizations using the LAMMPS simulation package [1], a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. We utilized the embedded atom model (EAM) potential for Ni and Nb developed in a previous study [2]. The potential could describe behaviors of the liquid and solid phases of Ni-Nb alloy. The structural factors and angular distributions of three atoms are well-matched with X-ray and ab initio-based molecular dynamics data. We prepared the three different crystals with different initial lattice parameters (3.52 Ã… for FCC, 3.32 Ã… for BCC, and 3.5 Ã… for HCP). We performed energy minimization in two steps. Firstly, we minimized the structures with an isotropic unit cell to minimize the side effects from our arbitrary lattice parameters for all other compositions. Then, we applied geometry optimization with a triclinic (non-orthogonal) unit cell to fully minimize the stress components to calculate the elastic constants. In this procedure, we chose 10,000 as the maximum number of allowable steps aimed at obtaining fully relaxed atomic geometries. The dataset consists of three sets of crystal structures. The first set contains 46,086 irregular crystal structures, each of them with 54 atoms, obtained through optimization starting from a regular BCC crystal structure. The second set contains 24,543 irregular crystal structures, each of them with 32 atoms, obtained through optimization starting from a regular FCC crystal structure. The third set contains 39,303 irregular crystal structures, each of them with 48 atoms, obtained through optimization starting from a regular HCP crystal structure. The atomic configurations within each set span the possible compositional range. The three sets have been unified in a global dataset, which is extremely heterogeneous in terms of crystal structures, lattice volumes, and atomic configurations. Organization of files inside the dataset: the dataset contains three subdirectories called • BCC_opt • FCC_opt • HCP_opt based on the type of initial regular structure used to start the geometry optimization. Inside each of these folders, every atomic structure is identified by a string “A_B_Câ€, where A denotes the number of Nb in the system, B denotes index of structure with a given Nb number, and C denotes the total number of structures generated with a given Nb number. For each optimized crystal structure identified by the unique string of characters “A_B_Câ€, three files are provided: • A_B_C_opt.xyz: The optimized geometries in xyz format • A_B_C_opt.cfg: The optimized geometries in cfg format. It includes cell information and atomic energy, and forces calculated from LAMMPS. • A_B_C.elastic: Raw data of 21 elastic constants from LAMMPS output. • A_B_C.bulk: Calculated upper and lower bounds of bulk modulus and averaged one based on Voigt-Reuss-Hill approach from *.elastic. References: [1] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimpton. LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comp. Phys. Comm., 271:108171, 2022. [2] Y Zhang, R Ashcraft, MI Mendelev, CZ Wang, and KF Kelton. Experimental and molecular dynamics simulation study of structure of liquid and amorphous ni62nb38 alloy. The Journal of chemical physics, 145(20):204505, 2016.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simultaneous Two- and Three-Photon Deep Imaging of Autofluorescence in Bacterial Communities

The intrinsic fluorescence of bacterial samples has a proven potential for label-free bacterial characterization, monitoring bacterial metabolic functions, and as a mechanism for tracking the transport of relevant components through vesicles. The reduced scattering and axial confinement of the excitation offered by multiphoton imaging can be used to overcome some of the limitations of single-photon excitation (e.g., scattering and out-of-plane photobleaching) to the imaging of bacterial communities. In this work, we demonstrate in vivo multi-photon microscopy imaging of Streptomyces bacterial communities, based on the excitation of blue endogenous fluorophores, using an ultrafast Yb-fiber laser amplifier. Its parameters, such as the pulse energy, duration, wavelength, and repetition rate, enable in vivo multicolor imaging with a single source through the simultaneous two- and three-photon excitation of different fluorophores. Three-photon excitation at 1040 nm allows fluorophores with blue and green emission spectra to be addressed (and their corresponding ultraviolet and blue single-photon excitation wavelengths, respectively), and two-photon excitation at the same wavelength allows fluorophores with yellow, orange, or red emission spectra to be addressed (and their corresponding green, yellow, and orange single-photon excitation wavelengths). We demonstrate that three-photon excitation allows imaging over a depth range of more than 6 effective attenuation lengths to take place, corresponding to an 800 micrometer depth of imaging, in samples with a high density of fluorescent structures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Informative and non-informative decomposition of turbulent flow fields

Not all the information in a turbulent field is relevant for understanding particular regions or variables in the flow. Here, we present a method for decomposing a source field into its informative Φ I (x, t) and residual Φ R (x, t) components relative to another target field. The method is referred to as informative and non-informative decomposition (IND). All the necessary information for physical understanding, reduced-order modelling and control of the target variable is contained in Φ I (x, t), whereas Φ R (x, t) offers no substantial utility in these contexts. The decomposition is formulated as an optimisation problem that seeks to maximise the time-lagged mutual information of the informative component with the target variable while minimising the mutual information with the residual component. The method is applied to extract the informative and residual components of the velocity field in a turbulent channel flow, using the wall shear stress as the target variable. We demonstrate the utility of IND in three scenarios: (i) physical insight into the effect of the velocity fluctuations on the wall shear stress; (ii) prediction of the wall shear stress using velocities far from the wall; and (iii) development of control strategies for drag reduction in a turbulent channel flow using opposition control. In case (i), IND reveals that the informative velocity related to wall shear stress consists of wall-attached high- and low-velocity streaks, collocated with regions of vertical motions and weak spanwise velocity. This informative structure is embedded within a larger-scale streak–roll structure of residual velocity, which bears no information about the wall shear stress. In case (ii), the best-performing model for predicting wall shear stress is a convolutional neural network that uses the informative component of the velocity as input, while the residual velocity component provides no predictive capabilities. Finally, in case (iii), we demonstrate that the informative component of the wall-normal velocity is closely linked to the observability of the target variable and holds the essential information needed to develop successful control strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Numerical case study of the aerosol–cloud interactions in warm boundary layer clouds over the eastern North Atlantic with an interactive chemistry module

The presence of warm boundary layer stratiform clouds over the eastern North Atlantic (ENA) region is commonly influenced by the Azores High, especially during the summer season. To investigate comprehensive aerosol–cloud interactions, this study employs the Weather Research and Forecasting model coupled with a chemistry component (WRF-Chem), incorporating aerosol chemical components that are relevant to the formation of cloud condensation nuclei (CCN) and accounting for aerosol spatiotemporal variation. This study focuses on aerosol indirect effects, particularly the long-range transport of aerosols, in the ENA region under three different weather regimes: a ridge with a surface high-pressure system, a post-trough with a surface high-pressure system, and a weak trough. The WRF-Chem simulations conducted at a near-large-eddy scale offer valuable insights into the model's performance, especially in terms of its ability to use high spatial resolution to capture mesoscale cloud features across various weather regimes. Our result shows that introducing 5 times more aerosols to either non-precipitating or precipitating clouds significantly increases ambient CCN numbers, resulting in, to varying degrees, higher liquid water path (LWP) values. The substantial aerosol–cloud interaction especially occurs in the precipitating clouds and demonstrates the susceptibility of the LWP to changes in CCN under different regimes. Conversely, thin, non-rain clouds at the edges of a cloud system are prone to evaporation, exhibiting an aerosol drying effect. The aerosols released during this process transition back to the accumulation mode, facilitating future activation. This dynamic behavior is not adequately represented in prescribed-aerosol simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

CheKiPEUQ Intro 2: Harnessing Uncertainties from Data Sets, Bayesian Design of Experiments in Chemical Kinetics**

When choosing experimental conditions, Bayesian statistical tools can predict the experimental choices which will yield the highest information gain. Experimental choices could be temperature, pressure, reaction time, number of measurements, reactor volume, etc.. Three example analyses are presented here, each using the software Chemical Kinetics Parameter Estimation and Uncertainty Quantification (CheKiPEUQ). Information gain is a measure of reduction of uncertainty in a model's parameters. The three chemical system examples presented each illustrate Bayesian Design of Experiments using information gain. In the first chemical example, temperature selection impacts the information gain for the free energy of reaction in a two-component equilibrium reaction. In the second example, temperature and pressure are explored for a competitive adsorption Langmuir replacement reaction system. Finally, the third example is a catalytic membrane reactor which is a culmination of the previous examples. The catalytic membrane reactor has a complex and nonlinear response in the observables which is solved by numerical evaluation. In the three examples, the experimental conditions are treated as design variables for maximizing information gain.

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

Ad Hoc File Systems for High-Performance Computing

Storage backends of parallel compute clusters are still based mostly on magnetic disks, while newer and faster storage technologies such as flash-based SSDs or non-volatile random access memory (NVRAM) are deployed within compute nodes. Including these new storage technologies into scientific workflows is unfortunately today a mostly manual task, and most scientists therefore do not take advantage of the faster storage media. One approach to systematically include nodelocal SSDs or NVRAMs into scientific workflows is to deploy ad hoc file systems over a set of compute nodes, which serve as temporary storage systems for single applications or longer-running campaigns. This paper presents results from the Dagstuhl Seminar 17202 “Challenges and Opportunities of User-Level File Systems for HPC” and discusses application scenarios as well as design strategies for ad hoc file systems using node-local storage media. The discussion includes open research questions, such as how to couple ad hoc file systems with the batch scheduling environment and how to schedule stage-in and stage-out processes of data between the storage backend and the ad hoc file systems. Also presented are strategies to build ad hoc file systems by using reusable components for networking and how to improve storage device compatibility. Various interfaces and semantics are presented, for example those used by the three ad hoc file systems BeeOND, GekkoFS, and BurstFS. Their presentation covers a range from file systems running in production to cutting-edge research focusing on reaching the performance limits of the underlying devices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Microstructure Evolution During Controlled Solidification of “Fe{sub 2}O{sub 3}”-CaO-SiO{sub 2} Liquids in Air

The principal chemical components in iron ore sintering are Fe{sub 2}O{sub 3}, CaO, and SiO{sub 2}. This sintering process consists of three key steps: heating, holding at peak temperature, and cooling. During the cooling stage, a liquid oxide solidifies to form the final sinter microstructures. To investigate the fundamental processes taking place during the cooling of sinters, a new experimental technique has been developed that allows the stages of solidification to be determined in isolation, rather than inferred from the final microstructures. Fe{sub 2}O{sub 3}-CaO-SiO{sub 2} oxide samples of a bulk composition having a CaO/SiO{sub 2} mass ratio of 3.46 and 73.2 wt pct Fe{sub 2}O{sub 3} were cooled in air from 1623 K (1350 °C) at 2 K/s, quenched at 5 K temperature intervals from 1533 K to 1453 K (1260 °C to 1180 °C), and analyzed using Electron Probe Micro X-Ray Analysis (EPMA). During cooling, four distinct stages were observed, consisting of the phase assemblages Liquid + Hematite (I), Liquid + Hematite + C{sub 2}S(II), Liquid + C{sub 2}S + CF{sub 2}(III), and C{sub 2}S + CF{sub 2} + CF (IV). This solidification sequence differs from that predicted under equilibrium and Scheil–Gulliver Cooling. Importantly, no Silico-Ferrite of Calcium (SFC) phase was observed to form on solidification of the liquid. Based on the microstructures formed and liquid compositions, measured by EPMA, it was demonstrated that kinetic factors play a major role in determining the phases and microstructures formed under the conditions investigated.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Unraveling the role of EGR olefins at advanced combustion conditions in the presence of nitric oxide: Ethylene, propene and isobutene

We report the role of EGR (exhaust gas recirculation) olefinic constituents at advanced combustion conditions in the presence of nitric oxide is unraveled in this study through experimental and modeling efforts using a twin-piston rapid compression machine operating at a stochiometric fuel loading with 20% EGR by mass, pressures of 20 and 40 bar, and temperatures from 680 to 950 K. Five different levels of olefin addition, focusing on ethylene, propene and isobutene, with a fixed amount of NO at 70 ppm are doped into test mixtures of PACE-20, a multi-component gasoline surrogate, where olefin addition effects are characterized through changes in ignition times and heat release rates. Experiments indicate that all three EGR olefins inhibit autoignition reactivity and low-temperature heat release at Tc < 850 K, with isobutene exhibiting the greatest impact, while at Tc > 850 K, low ethylene and propene additions promote reactivity. A recently updated chemical kinetic model, with detailed gasoline/NO x interacting and olefin/NO x interacting chemistry incorporated, is adopted to simulate the experiments. Simulation results are somewhat inconsistent with the experiments, where the model captures the inhibiting effects of all olefins on first-stage ignition reactivity, while consistently predicting a promoting effect on main ignition reactivity. Sensitivity and rate of production analyses reveal that adding olefins greatly alters the role of the consuming pathways for the olefins and their primary derivatives at the initial stage of the oxidation process, particularly with the presence of NO, where the olefins and their derivatives interact with both NO x species such as NO 2 and other species such as OH and HO 2 . The olefin/NO x interactions are particularly pronounced with propene and isobutene addition, where these lead to increased ignition reactivity by facilitating NO production and are mostly responsible for the disagreement between the model and experiments. Further investigations of olefin interacting chemistry, particularly those with NOx species, are needed for chemistry models to accurately predict the complicated effects of EGR.

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

Approaching the Practical Conductivity Limits of Aerosol Jet Printed Silver

Previous efforts to directly write conductive metals have been narrowly focused on nanoparticle ink suspensions that require aggressive sintering (>200°C) and result in low-density, small-grained agglomerates with electrical conductivities <25% of bulk metal. Here, we demonstrate aerosol jet printing of a reactive ink solution and characterize high-density (93%) printed silver traces having near-bulk conductivity and grain sizes greater than the electron mean free path, while only requiring low temperature (80°C) treatment. We have developed a predictive electronic transport model which correlates the microstructure to the measured conductivity and identifies a strategy to approach the practical conductivity limit for printed metals. Our analysis of how grain boundaries and tortuosity contribute to electrical resistivity provides insight into the basic materials science that governs how an ink formulator or process developer might approach improving the conductivity. Transmission line measurements validate that electrical properties are preserved up to 20GHz, which demonstrates the utility of this technique for printed RF components. Finally, this work reveals a new method of producing robust printed electronics that retain the advantages of rapid prototyping and three-dimensional fabrication while achieving the performance necessary for success within the aerospace and communications industries.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Spatially resolved polarization swings in the supermassive binary black hole candidate OJ 287 with first Event Horizon Telescope observations

We present the first Event Horizon Telescope 1.3 mm observations of the supermassive binary black hole candidate OJ 287. The observations achieved an unprecedented angular resolution of 18 μas and reveal significant structural and polarization variability over just five days, marking the shortest timescale on which such changes have been directly imaged in this source. The inner jet exhibits a twisted ridgeline structure, with features displaying apparent superluminal motions up to about 22 c. The linear polarization maps reveal three main polarized features whose electric-vector position angles (EVPAs) change substantially over the time span of our observations, including a component with a radial polarization consistent with being produced by a recollimation shock. Most notably, we directly resolved two innermost jet components whose EVPAs rotate in opposite directions. The faster component, moving at 2.4 ± 0.9 μas/day (17.4 ± 6.5 c), exhibits counterclockwise EVPA swings of roughly 3.7° per day, while the slower component, with a proper motion of 1.4 ± 0.3 μas/day (10.2 ± 2.2 c), rotates clockwise at approximately 2.5° per day. Previous studies inferred helical magnetic fields in AGN jets from time-resolved or integrated polarization variability but lacked the angular resolution to directly image this effect. Our results provide spatially resolved evidence that a helical magnetic field threads the jet’s collimation and acceleration zone, ruling out models based on the superposition of unresolved components. Our analysis suggests that propagating shocks interact with a Kelvin–Helmholtz plasma instability, illuminating different phases of the helical magnetic field and producing the observed polarization spatial and temporal variability. Moreover, our model naturally accounts for the more rapid polarization rotation observed in the faster moving component. Our model predicts even more rapid swings in polarization, which could be tested with future observations featuring a more densely sampled time coverage.

OJ 287↗
DOE OSTI2024

Nonlinear wavepacket dynamics in proximity to a stationary inflection point

A stationary inflection point (SIP) in the Bloch dispersion relation of a periodic waveguide is an exceptional point degeneracy where three Bloch eigenmodes coalesce, forming the so-called frozen mode with a divergent amplitude and vanishing group velocity of its propagating component. For this work, we have developed a theoretical framework to study the time evolution of wavepackets centered at an SIP. Analysis of the evolution of the statistical moment distribution of linear pulses shows a strong deviation from the conventional ballistic wavepacket dynamics in dispersive media. The presence of nonlinear interactions dramatically changes the situation, resulting in a mostly ballistic propagation of nonlinear wavepackets with the speed and even the direction of propagation essentially dependent on the wavepacket amplitude. Such a behavior is unique to nonlinear wavepackets centered at an SIP and can be used for the realization of a novel family of beam power routers for classical waves.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Design and Demonstration of an 850 V dc to 13.8 kV ac 100 kW Three-phase Four-wire Power Conditioning System Converter Using 10 kV SiC MOSFETs

In this paper, an 850 V dc to 13.8 kV ac 100 kW modular multilevel three-phase four-wire dc/ac converter based on 10 kV SiC MOSFETs is designed and demonstrated. The design considerations of key components, including the dc-link, device cooling, gate driver, isolated gate driver power supply (GDPS), medium voltage (MV) ac filter inductor, MV and medium frequency transformer, and the mechanical design are discussed. Two converters are designed, and two prototypes are developed, to study the converter paralleling operation and scalability. Both converters are fully tested up to their voltage and power ratings. However, the two converters are not identical. Based on the design and test results of the first converter, the MV power stage, transformer design, GDPS, as well as the low voltage power stage in the second converter are improved for smaller size and/or higher efficiency. Compared to the version 1 converter, the version 2 converter achieves 49% volume reduction and 2 percentage point efficiency improvement, with a peak efficiency of 98.4% at the rated power.

Li, Haiguo↗
DOE OSTI2020

Chemical Modeling of the Capture of Radioiodine Species

Iodine is a common fission product resulting from the transmutation of uranium fuel in nuclear power reactors. The short-lived radioactive isotope, 131 I, with a half-life of around eight days, would be a particular health concern if released into the environment. Capture materials, such as activated carbon, are used routinely in nuclear power plants and medical isotope production facilities to remove this hazard during normal operations to reduce emissions to acceptable levels. Iodine, unlike other common fission products such as noble gases, is challenging because of the wide range of molecular forms and oxidation states (from +VII in IF 7 to -I in iodide) that it displays, which can interconvert both in the gas phase and in the solution phase for example. The work in this project is focused on three computational tasks. In the first, we consider the binding of iodine-containing molecules of varying oxidation states to the major component of activated carbon – pristine graphene-like sheets. The second task focused on molecular binding and possible chemical transformations resulting from the reaction of molecular iodine with chemical functional groups on the edge of the graphene sheets or surface defects in the sheet itself. The final task was associated with radiolytic breakdown of 131 I to 131 Xe in iodine containing molecules and investigated the resulting molecular fragmentation process both in the gas phase and on the graphene-like surface. For each of the tasks, the intent was to learn about the thermodynamics and kinetics of the chemical transformations and use the calculations to provide parameters for input into kinetic models describing these processes for interpretation of experimental data in future work.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Task 12 PV Sustainability - Environmental Life Cycle Assessment of Residential PV and Battery Storage Systems

Using a life cycle assessment (LCA), the environmental impacts from generating 1 kWh of electricity for self-consumption via a photovoltaic-battery system are determined. The system includes a 10 kWp multicrystalline-silicon photovoltaic (PV) system (solar irradiation about 1350 kWh/m2/year and annual yield 1000 kWh/kWp), an iron phosphate lithium-ion (LiFePO4) battery, and other components such as the control system, battery housing, and two inverters (one for the PV system and one for the battery system). Three options for the AC-coupled system with changing battery capacities (5, 10, or 20 kWh nominal capacity) are investigated. The environmental impacts are assessed using the indicators greenhouse gas emissions and cumulative energy demand (separated into total and non-renewable cumulative energy demand). In addition, the four most important impact categories for PV electricity - respiratory inorganics (particulate matter), acidification, energy carrier resource use, and minerals and metals resource use - are assessed according to the environmental footprint (EF) method. Data are drawn from the DETEC data DQRv2:2018, recent literature, and product details provided by manufacturers. The results show larger environmental impacts of PV-battery systems with increasing battery capacity; for capacities of 5, 10, and 20 kWh, the cumulative greenhouse gas emissions from 1 kWh of electricity generation for self-consumption via a PV-battery system are 80, 84, and 88 g CO 2- eq/kWh, respectively. The cumulative greenhouse gas emissions of PV electricity consumed directly or fed into the grid are 54 g CO 2 -eq/kWh. The corresponding total cumulative energy demands are 5.27, 5.40, and 5.50 MJ oil-eq/kWh, with non-renewable energy carriers contributing 1.16, 1.22, and 1.29 MJ oil-eq/kWh. In the investigated EF impact categories, we similarly observe a larger environmental burden with increasing battery capacity, except in the use of minerals and metals. Our sensitivity analyses show that using a nickel cobalt manganese oxide (NCM) lithium-ion battery, instead of an LiFePO 4 battery, leads to a comparable environmental impact in terms of greenhouse gas emissions and cumulative energy demand. However, the NCM battery increases the impact in the EF categories of acidification and respiratory inorganics by 7 and 10%, respectively, whereas energy carrier resource use decreases by 4% and minerals and metals resource use decrease by 1%. Using a copper indium selenium (CIS) PV panel instead of a multicrystalline-silicon decreases greenhouse gas emissions by 24%, non-renewable cumulative energy demand by 13%, and particulate matter emissions by 60% (the largest decrease). Furthermore, the calculated environmental impacts are sensitive to the assumed battery lifetime. A decrease from 5000 to 3000 charge cycles increases non-renewable cumulative energy demand by 24% and greenhouse gas emissions by 16%. Increasing from 5000 to 7000 charge cycles decreases the environmental impacts by 6% and 7% in terms of non-renewable cumulative energy demand and greenhouse gas emissions, respectively. A utility-scale battery system case study shows that using batteries to store PV electricity overproduction reduces greenhouse gas emissions compared to using natural gas backup electricity generation.

14 SOLAR ENERGY↗
DOE OSTI2024

BeyondFingerprinting: AI-guided discovery of robust materials & processes

BeyondFingerprinting was a 2021-2024 Sandia Grand Challenge LDRD exploring the potential to develop new resilient materials and manufacturing processes by taking an artificial-intelligence (AI)-guided approach that integrates human-subject-matter expertise with algorithms enriched with physics-based constraints to unearth process-structure-property correlations. Such algorithms, trained on high-throughput experiments and simulations, are shown to serve as surrogate models that efficiently detect key “fingerprints” in materials data, prognose material performance, and guide effective process improvements. To accelerate broader adoption across mission areas, this AI-guided approach was demonstrated with three complex process-centric exemplars: electroplating, physical vapor deposition, and laser powder bed fusion. Together, these exemplars impact nearly every hardware component relevant to DOE and NNSA national security missions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Improving Real-world Measurement-based Phase Identification in Power Distribution Feeders with a Novel Reliability Criteria Assessment

This paper is concerned with solving the phase identification problem in a real-world smart grid project; where there is only a few smart meters available on each of the five power distribution feeders in the test site in Riverside, CA. The main idea is to develop and use two reliability criteria that can identify the most reliable components in a broken-down phase identification analysis; thereby significantly improving the accuracy of phase identification. The proposed method consists of three steps. The results from field implementation reveal the accuracy and consistency of the proposed method in practice, in correctly and reliability identifying the phase connectivity.

Phase identification Data-driven method Sliding wi↗
DOE OSTI2022

components for the MuMMI software release

The Department of Energy and the National Cancer Institute have developed new software for conducting multi-scale simulations of complex systems. This software, called the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), couples simulations on three spatial scales to study slow, large-scale reorganizations of biomolecular systems with the speed of continuum and coarse-grained models while revealing selected interactions at full atomic precision. In these simulations, coarse-to-fine model conversions are used to spawn relevant fine-scale simulations along chosen order parameters, and fine-to-coarse feedback is used to iteratively improve the accuracy and multi-scale consistency of coarse-scale and continuum simulations. The complete MuMMI framework will be reviewed and released as open-source software by Lawrence Livermore National Laboratory. This review covers a subset of the MuMMI components that were developed exclusively at the Los Alamos National Laboratory.

Neale, Christopher↗