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At least 451 records · Page 25

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DOE OSTI2025

Influence of Phase-Change Materials and Operating Periods on Load Shifting for Thermal Storage Heat Pumps in European Climate Zones

As the reliance on heat pumps (HPs) for space conditioning increases worldwide, ex-tensive grid strains during utility peak hours are expected. Significant research efforts focus on investigating the use of integrated thermal energy storage (TES) systems to reduce peak energy demands. Conventionally, TES systems are often integrated to store and provide either cooling or heating, but not both. In this work, a single room-temperature phase-change material (PCM)-TES was integrated for dual-mode opera-tion with an R290 air-to-water 10.5 kW (3-Ton) HP. Two PCM melting temperatures (17°C, 22°C) were assessed to investigate their impact on system performance and cost reductions for Milan, Italy (4A); Barcelona, Spain (3A); and Oslo, Norway (6A). HP and HP-TES performance maps were generated using Modelica-based transient models and co-simulated with a prototype residential building using the Spawn of En-ergyPlusTM with simple rule-based controls. Our simulations indicate that PCM-17°C provided annual cost savings at higher peak-to-off-peak cost ratios, as the demand re-duction dominated the savings potential. The recharge energy costs and requirements became more dominant at lower cost ratios, making PCM-22°C more beneficial at lower cost ratios. Finally, despite Oslo's heating-dominated climate, the utility peak hours favor cooling demand reductions, making PCM-17°C more appealing. In all cases, the cost savings potential stabilized between 4 – 10% regardless of cost ratio, suggesting that system-level component and operation control optimization is required to maximize cost savings further.

25 ENERGY STORAGE↗

DOE OSTI2024

Brittle failure analysis and modeling of high-burnup PWR fuel cladding alloys

The aim of this research is the development of methods for predicting mechanical behavior and identification of limiting conditions to prevent brittle failure of high-burnup (HBU) pressure water reactor (PWR) fuel cladding alloys. A finite element (FE) model of the ring compression test (RCT) was created to analyze the failure behavior of zirconium-based alloys with radial hydrides during the RCT. An elastic-plastic material model describes the zirconium alloy. The stress-strain curve needed for the elastic-plastic material model was derived by inverse finite element analyses. Cohesive zone modeling is used to reproduce sudden load drops during RCT loading. Based on the failure mechanism in non-irradiated ZIRLO (R) claddings, a micro-mechanical model was developed that distinguishes between brittle failure along hydrides and ductile failure of the zirconium matrix. Two different cohesive laws representing these types of failure are present in the same cohesive interface. The key differences between these constitutive laws are the cohesive strength, the stress at which damage initiates, and the cohesive energy, which is the damage energy dissipated by the cohesive zone. Statistically generated matrix-hydride distributions were mapped onto the cohesive elements and simulations with focus on the first load drop were performed. Computational results are in good agreement with the RCT results conducted on high-burnup M5 (R) samples. It could be shown that crack initiation and propagation strongly depend on the specific configuration of hydrides and matrix material in the fracture area.

Simbruner, Kai↗

DOE OSTI2025

Exploring Domain-Wall Pinning in Ferroelectrics via Automated High-Throughput Atomic Force Microscopy

Domain-wall dynamics in ferroelectric materials are strongly position-dependent, since each polar interface is locked into a unique local microstructure. This necessitates spatially resolved studies of wall pinning using scanning-probe microscopy techniques. The pinning centers and pre-existing domain walls are usually sparse within the image plane, precluding the use of dense hyperspectral imaging modes and requiring time-consuming human experimentation. Here, a large-area epitaxial PbTiO 3 film on cubic KTaO 3 was investigated to quantify the electric-field-driven dynamics of the polar–strain domain structures using ML-controlled automated piezoresponse force microscopy. Analysis of 1500 switching events reveals that domain-wall displacement depends not only on field parameters but also on the local ferroelectric–ferroelastic configuration. For example, twin boundaries in polydomains regions, like a 1 – /c+ ∥ a 2 – /c – , stay pinned up to a certain level of bias magnitude and change only marginally as the bias increases from 20 to 30 V, whereas single-variant boundaries, like the a 2 + /c + ∥ a 2 – /c – stack, are already activated at 20 V. These statistics on the possible ferroelectric and ferroelastic wall orientations, together with the automated high-throughput AFM workflow, can be distilled into a predictive map that links domain configurations to pulse parameters. Here, this microstructure-specific rule set forms the foundation for the design of ferroelectric memories.

automated scanning probe microscopy↗

DOE OSTI2020

Validation of finite-element models using full-field experimental data: Levelling finite-element analysis data through a digital image correlation engine

Full-field data from digital image correlation (DIC) provide rich information for finite-element analysis (FEA) validation. However, there are several inherent inconsistencies between FEA and DIC data that must be rectified before meaningful, quantitative comparisons can be made, including strain formulations, coordinate systems, data locations, strain calculation algorithms, spatial resolutions and data filtering. As such, in this paper, we investigate two full-field validation approaches: (1) the direct interpolation approach, which addresses the first three inconsistencies by interpolating the quantity of interest from one mesh to the other, and (2) the proposed DIC-levelling approach, which addresses all six inconsistencies simultaneously by processing the FEA data through a stereo-DIC simulator to ‘level’ the FEA data to the DIC data in a regularisation sense. Synthetic ‘experimental’ DIC data were generated based on a reference FEA of an exemplar test specimen. The direct interpolation approach was applied, and significant strain errorswere computed, even though therewas no model form error, because the filtering effect of theDIC enginewas neglected. In contrast, the levelling approach provided accurate validation results, with no strain error when no model form error was present. Next, model form error was purposefully introduced via a mismatch of boundary conditions. With the direct interpolation approach, the mismatch in boundary conditions was completely obfuscated, while with the levelling approach, it was clearly observed. Finally, the ‘experimental’ DIC datawere purposefully misaligned slightly fromthe FEA data. Both validation techniques suffered from the misalignment, thus motivating continued efforts to develop a robust alignment process. In conclusion, direct interpolation is insufficient, and the proposed levelling approach is required to ensure that the FEA and the DIC data have the same spatial resolution and data filtering. Only after the FEA data have been ‘levelled’ to the DIC data can meaningful, quantitative error maps be computed.

42 ENGINEERING↗

DOE OSTI2021

Terahertz Nano-Imaging of Electronic Strip Heterogeneity in a Dirac Semimetal

Emerging topological semimetals offer promise of realizing topological electronics enabled by terahertz (THz) current persistent against impurity scattering. Yet most fundamental issues remain on how to image nanoscale conductivity inhomogeneity. Here in this paper we show noninvasive and contactless conductivity mapping at THz-nm limit of electronic heterogeneity and nanostrip junctions in a Dirac material ZrTe 5 . A clear Dirac Fermion density transition, manifested as the exclusive THz conductivity contrast, is quantitatively analyzed and profiled on both sides of the junction. This also allows the determination of variable junction width of ~25–220 nm, depending on the THz conductivity contrast of adjacent strips. The unique THz-nm contrast is absent in mid-infrared nano-imaging measurements since topological semimetals with small Fermi pockets exhibit a better matching of their plasma frequency and scattering rate to the THz spectral region. The first-principles calculations provide two compelling implications: the conductivity nanocontrast can be induced by a small anisotropic strain, even less than 0.5%, due to an extreme strain sensitivity in ZrTe 5 ; A nanoscale topological phase transition is realized across some junctions induced by the strain, between strong topological insulators (TIs) and weak TIs/Dirac semimetals (DSMs).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1975

ISOFINEL: Isoparametric finite element code for elastic analysis of two-dimensional bodies

A formulation is presented for the development of a finite element program for the elastic analysis of two-dimensional bodies using the eight-node isoparametric quadrilateral. The program solves for both plane stress and plane strain problems. The finite element formulation based on the isoparametric displacement functions is presented. The program structure is given in the form of flow diagrams with descriptions of the numerical procedure used to obtain the element stiffness matrix, and the solution method employed to solve for nodal displacements. Three numerical examples (a plate under uniaxial tension, a plate under pure shear, and a beam under pure bending) are presented to illustrate the capability and limitations of the element implementation. The first problem is solved exactly by the element, as predicted by the form of its displacement functions. In the other two problems the accuracy of the solution is highly dependent upon the slenderness of the element, the number of elements in the map, and the numerical integration scheme used to build the element stiffness matrix.

Marino, C.↗

NASA NTRS1973

ERTS Applications in earthquake research and mineral exploration in California

Examples that ERTS imagery can be effectively utilized to identify, locate, and map faults which show geomorphic evidence of geologically recent breakage are presented. Several important faults not previously known have been identified. By plotting epicenters of historic earthquakes in parts of California, Sonora, Mexico, Arizona, and Nevada, we found that areas known for historic seismicity are often characterized by abundant evidence of recent fault and crustal movements. There are many examples of seismically quiet areas where outstanding evidence of recent fault movements is observed. One application is clear: ERTS-1 imagery could be effectively utilized to delineate areas susceptible to earthquake recurrence which, on the basis of seismic data alone, may be misleadingly considered safe. ERTS data can also be utilized in planning new sites in the geophysical network of fault movement monitoring and strain and tilt measurements.

Abdel-Gawad, M.↗

DOE OSTI2021

Feature Selection Clustering and Prototype Placement for Turbulence Data Sets.

Abstract not provided.

Barone, Matthew F.↗

DOE OSTI2025

Kinetic Deep Learning v0.1

Here, we present a method that uses protein levels to predict times series of metabolite concentrations. Understanding this type of pathway dynamics is important in order to predict the behavior of the pathway and, more pragmatically, to be able to design biological systems (such as strains bioengineered to produce chemical products) reliably. Typically, for this purpose, kinetic models consisting of differential equations based on the Michaelis-Menten dynamics have been used in the past. However, these methods can rarely produce good fits to measured data time series. Possibly, this happens because the kinetic constants are unknown or are different from the ones measured in vivo, or perhaps because Michaelis-Menten dynamics is not a satisfactory description. In order to improve the predictive nature of these kinetic models we have eliminated the Michaelis-Menten description of pathway dynamics and we have substituted it by algorithms that automatically learn these dynamics from previously obtained metabolomics and proteomics data using machine learning approaches. Specifically, kinetic deep learning uses deep learning to map proteomics time series to metabolite concentration time series, instead of learning the first metabolite derivative and integrating in (as in the first version of kinetic learning). This approach is shown to provide good to excellent results with a data set specifically collected for this purpose.

Garcia Martin, Hector [Joint BioEnergy Institute (↗

DOE OSTI2024

Experimental and Numerical Characterization of High Temperature Deformation Behavior of 347H Stainless Steel

This study investigates how temperature affects the plasticity and thermal creep behavior of 347H stainless steel under uniaxial tension. The research combined experimental testing with advanced computational modeling. Two types of experiments were conducted: uniaxial tensile tests at temperatures from 100°C to 750°C using strain rates of ~10⁻⁴ s⁻¹, and creep tests at temperatures between 600°C and 750°C under various stress levels. These experimental results were used to develop and validate a new integrated mechanistic model that can predict material behavior under any loading condition while accounting for both stress and temperature effects. The model was implemented using a polycrystalline microstructure simulation framework based on elasto-viscoplastic Fast Fourier Transform (EVPFFT). It incorporates three key deformation mechanisms: thermally activated dislocation glide, dislocation climb, and vacancy diffusional creep. The model accounts for internal stress distribution within single crystals and considers how precipitates and solute atoms (both interstitial and substitutional) affect dislocation movement. After validation against experimental data, the model was used to generate Ashby-Weertman deformation mechanism maps for 347H steel, providing new insights into how microstructure influences the activation of different creep mechanisms.

Joy, Jobin K.↗

DOE OSTI2021

Role of Fluorine in Chemomechanics of Cation-Disordered Rocksalt Cathodes

The role of nanoscale chemomechanical behavior in the macroscopic performance of functional materials is well recognized. For lithium-ion battery cathodes, tremendous effort has been devoted to the development of new chemistry and structure, yet fundamental understanding of the correlation between redox processes and mechanical properties of the novel materials lags behind. In the present study, we prepare large discrete single grains of Li-excess cation-disordered rocksalts (DRX) and investigate their chemomechanical behavior at the particle level, using nanoresolution X-ray and electron-based spectro-imaging and chemical mapping techniques. While irregular cracking upon lithium extraction leads to the eventual breakdown of the baseline DRX oxide (Li 1.2 Ti 0.4 Mn 0.4 O 2 ) particles at a high delithiation state, the fluorinated-DRX (Li 1.3 Ti 0.3 Mn 0.4 O 1.7 F 0.3 ) clearly displays aligned cracking along the <001> direction. The resulting periodicity in the cracking pattern enables the particles to retain their integrity and, consequently, improved electrochemical stability. Density functional theory (DFT) calculations showed that fluorination leads to increased concentration of Li+ on the (001) planes and preferential Li movements along the <001>-family directions, revealing the underlying mechanism for directional cracking. Overall, our study demonstrates the unique role of fluorine in modulating nanoscale chemomechanics, which in turn influences the evolution of charge and strain heterogeneity at the particle level. These insights provide important design guidelines in further improving DRX cathode materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1980

The geology and morphology of Ina

The lunar feature Ina, an unusual D-shaped depression, is located in Lacus Felicitatis north of Mare Vaporum. Attention was drawn to the feature because of its strange 'blistered' appearance. Using detailed topographic data available from the Lunar Topographic Orthophotomap (LTO) series, it is now possible to depict the morphology and structure of Ina and the surrounding region more accurately than was previously feasible. The maps employed in the study are 41C3 and 41C4 at 1:250,000 scale, and 41C3S1 (Ina) at 1:10,000 scale. Attention is given to the regional setting, and the morphologic characteristics and origins of features. It is concluded that Ina is an apparently unique volcanic feature. It rests on a dome displaying evidence of episodic extrusive activity. Its odd D-shape is probably related to a local fracture pattern, since the straight edge is aligned with other small lineaments in the area. Ina's floor exhibits several volcanic units.

Strain, P. L.↗

DOE OSTI2024

Exploring Geothermal Potential of Great Basin Sub-Regions: Preprint

The INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project aims to discover new, economically viable hidden geothermal systems in the Great Basin region by building on previous work in play fairway analysis and machine learning. A key objective of this project is to develop an exploration workflow to reduce geothermal exploration risks for hidden geothermal systems. A single preliminary play fairway workflow was developed from the assessment of the regional INGENIOUS geological, geophysical, and geochemical datasets. This workflow provided new preliminary predictive geothermal fairway maps for the INGENIOUS study area, which encompasses most of Nevada, western Utah, southern Idaho, southeastern Oregon, and easternmost California. However, a recent study (incorporating machine learning techniques) of a portion of Nevada identified four geologic domains and determined that the relative importance of individual datasets or features as indicators of geothermal potential may differ across these domains. The INGENIOUS study area includes a much larger and more geologically diverse region; therefore, additional geologic domains or sub-regions are expected. To assess the sub-regions in the INGENIOUS study area, principal component analysis and k-means clustering were applied. Preliminary results indicate that the INGENIOUS regional data cluster into groups that relate to different geologic domains in the Great Basin region. These include domains such as the Walker Lane, extensional western Great Basin region, broad lower strain region in the eastern Great Basin of western Utah and eastern Nevada, Quaternary volcanic fields, and the area adjacent to the Snake River Plain. These clusters are assessed to determine the key geologic drivers of the identified clusters. Understanding this variability can provide key insights for the exploration and characterization of hidden geothermal systems in the Great Basin region and could indicate the need to develop multiple geothermal conceptual models and play fairway workflows for the INGENIOUS study area.

GEOTHERMAL ENERGY↗

DOE OSTI2025

Exploring Geothermal Potential of Great Basin Sub-Regions

exploration↗

NASA NTRS2000

Cloning and characterization of ftsZ and pyrF from the archaeon Thermoplasma acidophilum

To characterize cytoskeletal components of archaea, the ftsZ gene from Thermoplasma acidophilum was cloned and sequenced. In T. acidophilum ftsZ, which is involved in cell division, was found to be in an operon with the pyrF gene, which encodes orotidine-5'-monophosphate decarboxylase (ODC), an essential enzyme in pyrimidine biosynthesis. Both ftsZ and pyrF from T. acidophilum were expressed in Escherichia coli and formed functional proteins. FtsZ expression in wild-type E. coli resulted in the filamentous phenotype characteristic of ftsZ mutants. T. acidophilum pyrF expression in an E. coli mutant lacking pyrF complemented the mutation and rescued the strain. Sequence alignments of ODCs from archaea, bacteria, and eukarya reveal five conserved regions, two of which have homology to 3-hexulose-6-phosphate synthase (HPS), suggesting a common substrate recognition and binding motif. Copyright 2000 Academic Press.

Bacterial Proteins/chemistry/genetics/metabolism↗

DOE OSTI2021

A method for achieving complete microbial genomes and improving bins from metagenomics data

Metagenomics facilitates the study of the genetic information from uncultured microbes and complex microbial communities. Assembling complete genomes from metagenomics data is difficult because most samples have high organismal complexity and strain diversity. Some studies have attempted to extract complete bacterial, archaeal, and viral genomes and often focus on species with circular genomes so they can help confirm completeness with circularity. However, less than 100 circularized bacterial and archaeal genomes have been assembled and published from metagenomics data despite the thousands of datasets that are available. Circularized genomes are important for (1) building a reference collection as scaffolds for future assemblies, (2) providing complete gene content of a genome, (3) confirming little or no contamination of a genome, (4) studying the genomic context and synteny of genes, and (5) linking protein coding genes to ribosomal RNA genes to aid metabolic inference in 16S rRNA gene sequencing studies. We developed a semi-automated method called Jorg to help circularize small bacterial, archaeal, and viral genomes using iterative assembly, binning, and read mapping. In addition, this method exposes potential misassemblies from k-mer based assemblies. We chose species of the Candidate Phyla Radiation (CPR) to focus our initial efforts because they have small genomes and are only known to have one ribosomal RNA operon. In addition to 34 circular CPR genomes, we present one circular Margulisbacteria genome, one circular Chloroflexi genome, and two circular megaphage genomes from 19 public and published datasets. We demonstrate findings that would likely be difficult without circularizing genomes, including that ribosomal genes are likely not operonic in the majority of CPR, and that some CPR harbor diverged forms of RNase P RNA. Code and a tutorial for this method is available at https://github.com/lmlui/Jorg and is available on the DOE Systems Biology KnowledgeBase as a beta app.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Quantitative nanoscale tracking of oxygen vacancy diffusion inside single ceria grains by in situ transmission electron microscopy

Oxygen vacancy formation and migration in ceria is critical to its electrochemical and catalytic properties in systems for chemical and energy transformation, but its quantification is rather challenging especially at atomic-scale because of disordered distribution. Here we report a rational approach to track oxygen vacancy diffusion in single grains of pure and Sm-doped ceria at -20 °C to 160 °C using in situ (scanning) transmission electron microscopy ((S)TEM). To create a gradient in oxygen vacancy concentration, a small region (~30 nm in diameter) inside a ceria grain is reduced to the C-type CeO 1.68 phase by the ionization or radiolysis effect of a high-energy electron beam. The evolution in oxygen vacancy concentration is then mapped through lattice expansion measurement using scanning nano-beam diffraction or 4D STEM at a spatial resolution better than 2 nm; this allows direct determination of local oxygen vacancy diffusion coefficients in a very small domain inside pure and Sm-doped ceria at different temperatures. Further, the activation energies for oxygen transport are determined to be 0.59, 0.66, 1.12, and 1.27 eV for pure CeO 2 , Ce 0.94 Sm 0.06 O 1.97 , Ce 0.89 Sm 0.11 O 1.945 , and Ce 0.8 Sm 0.2 O 1.9 , respectively, implying that activation energy increases due to impurity scattering. The results are qualitatively supported by density functional theory (DFT) calculations. In addition, our in situ TEM investigation reveals that dislocations impede oxygen vacancy diffusion by absorbing oxygen vacancies from the surrounding areas and pinning them locally. With more oxygen vacancies absorbed, dislocations show extended strain fields with local tensile zone sandwiched between the compressed ones. Therefore, dislocation density should be reduced in order to minimize the resistance to oxygen vacancy diffusion at low temperatures.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Reliability metrics and their management implications for open pond algae cultivation

The prevalence of contaminating organisms in outdoor algae cultivation, with the often-associated dramatic crop failures, necessitates the need for metrics describing production system reliability. Standard metrics for algae cultivation reliability are critically needed to be able to map improvements in operational parameters, but do not currently exist. In this work, we present a set of standard metrics including mean time to failure (MTTF) and mean time between failures (MTBF) as the basis for the calculation of pond failure rate (FR) and reliability coefficient (RC). Metrics associated with the numbers of contaminating organisms such as abundance ratio (AR), prevalence of infection (PI), and mean intensity of infection (MII) are also relevant. These metrics, based on measured experimental values of outdoor pond performance during the Algae Testbed Public-Private Partnership (ATP3) Unified Field Studies (UFS), provide a basis for quantifying pond failure and provide insight into potential pond management and contaminant mitigation strategies. From these reliability metrics applied to this dataset, we are able to link operational parameters, such as harvest frequency and inoculum source, to pond reliability for different algae strains and seasons, and from an assessment of AR, provide contamination thresholds beyond which a culture may be unrecoverable. Ultimately, the implementation of widely-practiced and simple-to-calculate algae pond reliability metrics calculated from rapid and easy to collect data or observations will reduce risk and uncertainty in large-scale algae deployment and aid in the development of integrated pest management (IPM) strategies.

09 BIOMASS FUELS↗