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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Single-Bar SMT Creep-Fatigue Testing on Alloy 617 with Software Controls on elastic Follow-Up Feedback in Support of New Creep-Fatigue Design Methodology

The Simplified Model Test (SMT) is one of the alternative ways to calculate the creep-fatigue damage of elevated temperature components. The SMT approach unifies the creep and fatigue damage, simplifying the damage calculation process with improved accuracy. Traditionally, SMT tests has have been conducted through the two bars: first is the driver bar and second is the test bar. The driver bar stays elastic and imposes the confinement to the second bar. This experimental procedure requires two test frames and a large test specimen, which limits the test parameter range and accessibility of this testing procedures. Hence, a single-bar SMT (SB-SMT) tests has been developed to simplify complexity in SMT experiment setup. The software-controlled SB-SMT test process has been introduced which completely replaces the driver bar. This paper discusses the single-bar SMT (SB-SMT) test procedure with software controls. The challenges and critical parameters in the software-controlled SB-SMT procedure are addresses addressed and recommendations are provided. A scoping test with a set of wider strain range, elastic follow-ups and dwell time validated the proposed test procedure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Partial Least Squares, Experimental Design, and Near-Infrared Spectrophotometry for the Remote Quantification of Nitric Acid Concentration and Temperature

Near-infrared spectrophotometry and partial least squares regression (PLSR) were evaluated to create a pleasantly simple yet effective approach for measuring HNO3 concentration with varying temperature levels. A training set, which covered HNO3 concentrations (0.1–8 M) and temperature (10–40 °C), was selected using a D-optimal design to minimize the number of samples required in the calibration set for PLSR analysis. The top D-optimal-selected PLSR models had root mean squared error of prediction values of 1.4% for HNO 3 and 4.0% for temperature. The PLSR models built from spectra collected on static samples were validated against flow tests including HNO 3 concentration and temperature gradients to test abnormal conditions (e.g., bubbles) and the model performance between sample points in the factor space. Based on cross-validation and prediction modeling statistics, the designed near-infrared absorption approach can provide remote, quantitative analysis of HNO 3 concentration and temperature for production-oriented applications in facilities where laser safety challenges would inhibit the implementation of other optical techniques (e.g., Raman spectroscopy) and in which space, time, and/or resources are constrained. The experimental design approach effectively minimized the number of samples in the training set and maintained or improved PLSR model performance, which makes the described chemometric approach more amenable to nuclear field applications.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Chapter 16: Connecting Microbial Genotype with Phenotype in the Omics Era

Although rational design-based metabolic engineering has been applied widely to obtain promising microbial biocatalysts, conventional strategies such as adaptive laboratory evolution (ALE) and mutagenesis are still efficient approaches to improve microorganisms for exceptional features such as a broad spectrum of substrate utilization, robustness of cell growth, as well as high titer, yield, and productivity of the target products. In this chapter, we describe the procedure to generate mutant strains with desired phenotypes using ALE and a new mutagenesis approach of Atmosphere and Room Temperature Plasma (ARTP). In addition, we discuss the methodology to combine next-generation sequencing (NGS)-based genome-resequencing and RNA-Seq transcriptomics approaches to characterize the mutant strains and connect the phenotypes with their corresponding genotypic changes.

adaptive laboratory evolution (ALE)↗
DOE OSTI2024

Paradigm for approaching the forbidden phase transition in the one-dimensional Ising model at fixed finite temperature: Single chain in a magnetic field

In a previous paper, the forbidden spontaneous phase transition in the one-dimensional Ising model was found to be approachable arbitrarily closely in decorated ladders by ultra-narrow phase crossover (UNPC) at a given finite temperature T 0 with the crossover width 2δT reduced exponentially, which resemble a genuine first-order transition with large latent heat. Here, I reveal that the forbidden phase transition can be approached at fixed T 0 as well in decorated single-chain Ising models in the presence of a magnetic field, in which T 0 is determined by the interactions involving only the decorated parts and the magnetic field, while 2δT is independently, exponentially reduced (δT = 0 means a genuine transition) by restoring the ferromagnetic interaction between the ordinary spins on the chain backbone-which was neglected in the previous studies of pseudo-transition-thus manifesting that this asymptoticity to the forbidden transition is essentially the buildup of coherence in preformed crossover of local states. Furthermore, I show that the UNPC can be realized even in the absence of the conventional geometric frustration because the magnetic field itself can induce previously unnoticed hidden spin frustration. In conclusion, these findings make the doors wide open to the engineering and utilization of UNPC as a new paradigm for exploring exotic phenomena and 1D device applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Geospatial modeling of near subsurface temperatures of the contiguous United States for assessment of materials degradation

Abstract Understanding subsurface temperature variations is crucial for assessing material degradation in underground structures. This study maps subsurface temperatures across the contiguous United States for depths from 50 to 3500 m, comparing linear interpolation, gradient boosting (LightGBM), neural networks, and a novel hybrid approach combining linear interpolation with LightGBM. Results reveal heterogeneous temperature patterns both horizontally and vertically. The hybrid model performed best achieving a root mean square error of 2.61 °C at shallow depths (50–350 m). Model performance generally decreased with depth, highlighting challenges in deep temperature prediction. State-level analyses emphasized the importance of considering local geological factors. This study provides valuable insights for designing efficient underground facilities and infrastructure, underscoring the need for depth-specific and region-specific modeling approaches in subsurface temperature assessment.

Science & Technology - Other Topics↗
DOE OSTI2024

Electrochemical Synthesis of Zeolite Coatings with Controlled Crystal Polymorphism and Self-Regulating Growth

Zeolite coatings are studied as molecular sieves for membrane separation, membrane reactors, and chemical sensor applications. They are also studied as anticorrosive films for metals and alloys, antimicrobial and hydrophobic films for heating, ventilation, and air conditioning, and dielectrics for semiconductor applications. Zeolite coatings are synthesized by hydrothermal, ionothermal, and dry-gel conversion approaches, which require high process temperatures and lengthy times (ranging from hours to days). Here, we report the first zeolite coatings synthesized via electrochemical deposition on a cathodic electrode, with controlled crystal polymorphism achieved within subhourly duration. We demonstrate this approach by developing sodium zeolite (e.g., sodalite (SOD), NaA (LTA), and Linde Type N (LTN)) coatings on a titanium electrode and extending the synthesis method to porous stainless steel. The coating morphology and crystallinity depend on the temperature, time, and applied current. The coating thickness is independent of the applied current, showing the presence of a self-regulating mechanism to ensure a uniform coating thickness across the metal surface. The electrochemical zeolite growth mechanism was elucidated with high-resolution transmission electron microscopy, and applications of the resultant zeolite coatings for oil/water separation and ethanol/water pervaporation were exploited. Electrochemical synthesis represents a novel, simple, fast, and environmentally friendly approach to preparing zeolite coatings. It can potentially be generalized for developing zeolite materials with diverse framework structures, morphologies, and orientations for substrates with complicated geometries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Parameter extraction approaches for compact modeling of thermoelectric modules

Thermoelectric (TE) cooling has experienced rapid advancements with the foundational understanding of TE materials. TE modules, compact and lightweight devices, have become the prevalent approach for implementing TE technologies. Accurately quantifying TE physical parameters (Seebeck coefficient α, thermal conductivity κ, and thermal resistance ρ) is challenging due to the dynamic temperature changes in operation. Furthermore, extracting lumped property parameters is crucial for designing energy systems using TE modules. Existing research has several limitations, such as lack of comparative analysis between prevalent formulae, reliance on potentially inaccurate vendor-supplied data, disregard for fundamental assumptions, and absence of empirical measurements. Further, this study addresses these gaps by conducting TE material characterization, comparing three existing formulae using vendor datasheets, designing a laboratory test facility for model validation and refinement, and outlining a structured data extraction procedure. The study's novelty lies in multiple key contributions: (1) a detailed comparative analysis of existing formulae for extracting TE property parameter; (2) executing experimental work in a laboratory setting to validate the model and elucidate its limitations; (3) highlighting potential risks; (4) clarifying possible assumptions from both material and engineering perspectives; and (5) considering temperature differential impacts. This comprehensive approach addresses the current research gaps and provides valuable insights into the design and application of TE modules in various energy systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermochemical Conversion of Sugarcane Bagasse: A Comprehensive Analysis of Ignition and Burnout Temperatures

The Brazilian sugarcane industry generates a significant amount of waste each year, which should be properly analyzed and studied to allow an adequate recovery and application supported by the best understanding of its properties. The present work reports the ignition and burnout temperatures of sugarcane bagasse (SCB) obtained after performing a thermal analysis using four different heating rates. The intersection method (IM) and deviation method (DM) were employed to approach the ignition and burnout temperatures of the sugarcane bagasse. The ignition temperatures of the SCB measured from IM are between 250 and 263 °C, and their burnout temperatures are between 357 and 377 °C. The ignition temperature was in the range of 205 °C to 236 °C for the DM. IM is recommended for determining the ignition and burnout temperatures. In TGA, the heating rates in the range of 10 °C·min−1 and 15 °C·min−1 are suggested due to their accuracy and the contribution to timesaving in the analysis.

Morais, Leandro C. de (ORCID:0000000314685453)↗
DOE OSTI2024

Automated Bayesian high-throughput estimation of plasma temperature and density from emission spectroscopy

Here, this paper introduces a novel approach for automated high-throughput estimation of plasma temperature and density using atomic emission spectroscopy, integrating Bayesian inference with sophisticated physical models. We provide an in-depth examination of Bayesian methods applied to the complexities of plasma diagnostics, supported by a robust framework of physical and measurement models. Our methodology is demonstrated using experimental observations in the field of magneto-inertial fusion, focusing on individual and sequential shot analyses of the Plasma Liner Experiment at LANL. The results demonstrate the effectiveness of our approach in enhancing the accuracy and reliability of plasma parameter estimation and in using the analysis to reveal the deep hidden structure in the data. This study not only offers a new perspective of plasma analysis but also paves the way for further research and applications in nuclear instrumentation and related domains.

Bayesian inference↗
DOE OSTI2024

Exchange–correlation entropy from the generalized thermal adiabatic connection

Warm dense matter is a highly energetic phase characterized by strong correlations, thermal effects, and quantum mechanical electrons. Thermal density functional theory is commonly used in simulations of this challenging phase, driving the development of temperature-dependent approximations to the exchange–correlation free energy. Approaches using the adiabatic connection formula are well known at zero temperature and have been recently leveraged at non-zero temperatures as well. In this work, a generalized thermal adiabatic connection (GTAC) formula is proposed, introducing a fictitious temperature parameter. This allows extraction of the exchange–correlation entropy S XC using simulated interaction strength scaling. Here, this procedure uses a Hellmann–Feynman approach to express the exchange–correlation entropy in terms of a temperature- and interaction strength-dependent exchange–correlation potential energy. In addition, analysis of S XC as a function of interaction strength suggests new forms for approximations, and GTAC itself offers a new framework for exploring both the exact and approximate interplay of temperature, density, and interaction strength across a wide range of conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A valuation framework for customers impacted by extreme temperature-related outages

Extreme temperature outages can lead to not just economic losses but also various non-energy impacts (NEI), such as increased mortality rates, property damage, and reduced productivity, due to significant degradation of indoor operating conditions caused by service disruptions. However, existing resilience assessment approaches lack specificity for extreme temperature conditions. They often overlook temperature-related mortality and neglect the customer characteristics and grid response in the calculation, despite the significant influence of these factors on NEI-related economic losses. This paper aims to address these gaps by introducing a comprehensive framework to estimate the impact of resilience enhancement not only on the direct economic losses incurred by customers but also on potential NEI, including mortality and the value of statistical life during extreme temperature-related outages. The proposed resilience valuation integrates customer characteristics and grid response variables based on a scalable grid simulation environment. This study adopts a holistic approach to quantify customer-oriented economic impacts, utilizing probabilistic loss scenarios that incorporate health-related factors and damage/loss models as a function of exposure for valuation. The proposed methodology is demonstrated through comparative resilient outage planning, using grid response models emulating a Texas weather zone during the 2021 winter storm Uri. The case study results show that enhanced outage planning with hardened infrastructure can improve the system resilience and thereby reduce the relative risk of mortality by 16% and save the total costs related to non-energy impacts by 74%. In conclusion, these findings underscore the efficacy of the framework by assessing the financial implications of each case, providing valuable insights for decision-makers and stakeholders involved in extreme-weather related resilience planning for risk management and mitigation strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Validation of URANS and STRUCT-ε turbulence models for stratified sodium flow

Simulations of a transient stratified sodium experiment are carried out using a classic unsteady RANS model and the second-generation URANS model, STRUCT-ε. Turbulence modeling challenges and their implications to stratified flow prediction are discussed in the context of other sources of error. Input errors are discussed and addressed; discretization error is calculated to be less than 5% of the inlet velocity, for 80% of the domain; and remaining errors in temperature distributions are attributed to the turbulence model. Qualitative flow features from the simulations are presented and discussed. Compared to the experiment, the STRUCT-ε turbulence model provides a more physically accurate prediction of temperature and momentum mixing in key regions of the domain. Quantitative measures such as the L 2 norm of the temperature discrepancy demonstrate the improved performance of the STRUCT-ε approach. In conclusion, the magnitude of the temperature fluctuations is very well-predicted by the STRUCT-ε, while URANS overpredicts them by approximately 50%.

42 ENGINEERING↗
DOE OSTI2023

Top-Down Fabrication of Atomic Patterns in Twisted Bilayer Graphene

Atomic-scale engineering typically involves bottom-up approaches, leveraging parameters such as temperature, partial pressures, and chemical affinity to promote spontaneous arrangement of atoms. These parameters are applied globally, resulting in atomic-scale features scattered probabilistically throughout the material. In a top-down approach, different regions of the material are exposed to different parameters, resulting in structural changes varying on the scale of the resolution. In this work, the application of global and local parameters is combined in an aberration-corrected scanning transmission electron microscope (STEM) to demonstrate atomic-scale precision patterning of atoms in twisted bilayer graphene. The focused electron beam is used to define attachment points for foreign atoms through the controlled ejection of carbon atoms from the graphene lattice. The sample environment is staged with nearby source materials such that the sample temperature can induce migration of the source atoms across the sample surface. Under these conditions, the electron-beam (top-down) enables carbon atoms in the graphene to be replaced spontaneously by diffusing adatoms (bottom-up). Using image-based feedback control, arbitrary patterns of atoms and atom clusters are attached to the twisted bilayer graphene with limited human interaction. Finally, the role of substrate temperature on adatom and vacancy diffusion is explored by first-principles simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The advanced tokamak path to a compact net electric fusion pilot plant

Abstract Physics-based simulations project a compact net electric fusion pilot plant with a nuclear testing mission is possible at modest scale based on the advanced tokamak concept, and identify key parameters for its optimization. These utilize a new integrated 1.5D core-edge approach for whole device modeling to predict performance by self-consistently applying transport, pedestal and current drive models to converge fully non-inductive stationary solutions, predicting profiles and energy confinement for a given density. This physics-based approach leads to new insights and understanding of reactor optimization. In particular, the levering role of high plasma density is identified, which raises fusion performance and self-driven ‘bootstrap currents’, to reduce current drive demands and enable high pressure with net electricity at a compact scale. Solutions at 6–7 T, ∼4 m radius and 200 MW net electricity are identified with margins and trade-offs possible between parameters. Current drive comes from neutral beam and ultra-high harmonic (helicon) fast wave, though other advanced approaches are not ruled out. The resulting low recirculating power in a double null configuration leads to a divertor heat flux challenge that is comparable to ITER, though reactor solutions may require more dissipation. Strong H-mode access (x2 margin over L–H transition scalings) and ITER-like heat fluxes are maintained with ∼20%–60% core radiation, though effects on confinement need further analysis. Neutron wall loadings appear tolerable. The approach would benefit from high temperature superconductors, as higher fields would increase performance margins while potential for demountability may facilitate nuclear testing. However, solutions are possible with conventional superconductors. An advanced load sharing and reactive bucking approach in the device centerpost region provides improved mechanical stress handling. The prospect of an affordable test device which could close the loop on net-electric production and conduct essential nuclear materials and breeding research is compelling, motivating research to validate the techniques and models employed here.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Temperature transformation of blended magnesium potassium phosphate cement binders

In this study, a multi-technique approach was utilised to determine the high temperature performance of magnesium potassium phosphate cement (MKPC) blended with fly ash (FA) or ground granulated blast furnace slag (GBFS) with respect to nuclear waste immobilisation applications. Conceptual fire conditions were employed (up to 1200 °C, 30 min) to simulate scenarios that could occur during interim storage, transportation or within a final geological disposal facility. After exposure up to 400 °C, the main crystalline phase, struvite-K (MgKPO{sub 4}·6H{sub 2}O), was dehydrated to poorly crystalline MgKPO{sub 4} (with corresponding volumetric and mass changes), with MgKPO{sub 4} recrystallisation achieved by 800 °C. XRD and SEM/EDX analysis revealed reaction occurred between the MgKPO{sub 4} and FA/GBFS components after exposure to 1000–1200 °C, with the formation of potassium aluminosilicate phases, leucite and kalsilite (KAlSi{sub 2}O{sub 6} and KAlSiO{sub 4}), commensurate with a reduced relative intensity (or complete elimination) of the dehydrated struvite-K phase, MgKPO{sub 4.} This was further supported by solid-state NMR ({sup 27}Al and {sup 29}Si MAS), where only residual features associated with the raw FA/GBFS components were observable at 1200 °C. The high temperature phase transformation of blended MKPC binders resulted in the development of a glass/ceramic matrix with all existing porosity infilled via sintering and the formation of a vitreous phase, whilst the physical integrity was retained (no cracking or spalling). This study demonstrates that, based on small-scaled specimens, blended MKPC binders should perform satisfactorily under fire performance parameters relevant to the operation of a geological disposal facility, up to at least 1200 °C.

36 MATERIALS SCIENCE↗
DOE OSTI2024

JOINT APPOINTEE: Evolution of ferroelectric properties in SmxBi1-xFeO3 via automated Piezoresponse Force Microscopy across combinatorial spread libraries

Combinatorial spread libraries offer a innovative approach to explore the evolution of material properties over broad concentration, temperature, and growth parameter spaces. However, traditional limitation of this approach is the requirement for the read-out of functional properties across the library. Here we develop automated Piezoresponse Force Microscopy (PFM) for the exploration of combinatorial spread libraries and demonstrate its application in the SmxBi1-xFeO3 system with the ferroelectric-antiferroelectric morphotropic phase boundary. This approach relies on the synergy of the quantitative nature of PFM and the implementation of automated experiments that allow PFM-based sampling over macroscopic samples. The concentration dependence of pertinent ferroelectric parameters has been determined and used to develop the mathematical framework based on Ginzburg-Landau theory describing the evolution of these properties across the concentration space. We pose that a combination of automated scanning probe microscope and combinatorial spread library approach will emerge as an efficient research paradigm to close the characterization gap in the high-throughput materials discovery. We make the data sets open to the community and hope that this will stimulate other efforts to interpret and understand the physics of these systems.

Automated Microscopy, Combinatorial Library, Ferro↗
DOE OSTI2025

Morphophysiological Plant Phenotyping for the Development of Plant Breeding Under Drought and Heat Conditions: A Practical Approach

ABSTRACT Currently, the breeding programs focus their efforts on identifying and developing tolerant genotypes to adverse conditions, such as drought and high temperatures. In this context, the physiological approach, which involves phenotyping several traits, is useful for breeding programs. Leaf photosynthetic traits have become one of the main objectives to be evaluated for breeders due to their relationship with improving grain yield and biomass production. Gas exchange ( Ge ) and chlorophyll “a” fluorescence ( Chf ) are the main tools to characterize the photosynthetic activity in real time at the leaf level. Consequently, several association studies using proximal and nonproximal sensing (e.g., RGB, thermography) have been developed. However, for the correct application of this breeding approach, it is essential to have a basic knowledge of both the physiological principles involved in the readings and the limitations of phenotyping due to the characteristics of the devices available on the market. This revision also covers other traits, such as the morphological and anatomical characteristics of leaves and roots, and the use of isotopes complementing Ge and Chf measurements.

Estrada, Félix [Instituto de Investigaciones Agrop↗