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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Global Optimization of Chemical Cluster Structures: Methods, Applications, and Challenges

Chemical clusters are relevant to many applications in catalysis, separations, materials, and energy sciences. Experimentally, the structure of clusters is difficult to determine, but it is very important in understanding their chemistry and properties. Computational methods can be used to examine cluster structure, however finding the most stable structure is not simple, particularly as the cluster size increases. Global optimization techniques have long been used to tackle the problem of the most stable structure, but such approaches would have to look for a global minimum, while sampling local minima over the whole potential energy surface as well. In this review, the state-of-the-art theory of global optimization theory is summarized. First, the definition, significance, relation to experiments, and a brief history of global optimization is presented. We then discuss, in more detail, three versatile global optimization methods: the basin hopping, the artificial bee colony algorithm, and the genetic algorithm. We close with some representative application examples of global optimization of clusters since 2016 and the challenges, open questions and opportunities in this field.

Global optimization, Chemical clusters, Artificial↗
DOE OSTI2021

Trocylation of 3-quinuclidinol, a key marker for the chemical warfare agent 3-quinuclidinyl benzilate, for its enhanced detection at low levels in complex soil matrices by electron ionization gas chromatography–mass spectrometry

Detection of 3-quinuclidinol (3Q), a marker for the chemical warfare agent 3-quinuclidinyl benzilate, is very difficult by gas chromatography–mass spectrometry (GC/MS), providing low, broad signals even when analyzed in isolated form. Therefore, a method that can convert 3Q into a substrate with enhanced detectability by GC/MS would be an important tool for its analysis. 2,2,2-Trichloroethoxycarbonyl chloride (TrocCl) was used in the derivatization of 3Q in three different soils of varying composition and total organic content (Virginia type A soil, Nebraska EPA standard soil and Ottawa sand) when present at a 10 μg g -1 concentration in each. A direct derivatization protocol and one involving the pre-extraction of the analyte were evaluated for their individual efficiencies and subsequent analysis using electron ionization GC/MS. The practical derivatization of 3Q, when present at low levels (10 μg g -1 ) in three different soil matrices, was found to be rapid (1 h) and to take place smoothly at ambient temperature (and as low as 4°C). The method detection limit was determined to be 30 ng mL -1 for the Virginia type A soil, 49 ng mL -1 for the Nebraska EPA standard soil and 72 ng mL -1 for the Ottawa sand sample. An expedient and practical derivatization method for 3Q, a chemical warfare degradation product difficult to detect by GC/MS, has been realized using trichloroethyl chloroformate. The reaction provides 3Q-Troc, a derivative with better detectability than 3Q by electron ionization GC/MS such as peak sharpness and a unique mass spectrum for its unambiguous identification.

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

Relating Texture and Thermomechanical Processing Variables in Mg–Zn–Ca Alloys

It is well known that the strong basal texture commonly produced in magnesium alloy sheets leads to poor formability at room temperature. A sizable body of work has explored how changing the alloy composition and rolling conditions can yield more desirable textures; however important thermomechanical variables, such as the feed rate during rolling, are often not included in the literature, making it difficult to correlate how changes in processing affect the final crystallographic texture. This work explores the texture evolution and grain refinement in Mg-Zn-Ca alloys during plane strain compression (PSC) using a Gleeble thermomechanical simulator. This instrument allows for precise control and capture of the thermomechanical history of the sample. The texture and grain morphology of the compressed samples were characterized using Electron Backscatter Diffraction (EBSD). The texture results will be used to identify which alloys and processing conditions should be scaled up for future rolling studies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The quality/cosmology tension for a post-inflation QCD axion

Abstract It is difficult to construct a post-inflation QCD axion model that solves the axion quality problem (and hence the Strong CP problem) without introducing a cosmological disaster. In a post-inflation axion model, the axion field value is randomized during the Peccei-Quinn phase transition, and axion domain walls form at the QCD phase transition. We emphasize that the gauge equivalence of all minima of the axion potential (i.e., domain wall number equals one) is insufficient to solve the cosmological domain wall problem. The axion string on which a domain wall ends must exist as an individual object (as opposed to a multi-string state), and it must be produced in the early universe. These conditions are often not satisfied in concrete models. Post-inflation axion models also face a potential problem from fractionally charged relics; solving this problem often leads to low-energy Landau poles for Standard Model gauge couplings, reintroducing the quality problem. We study several examples, finding that models that solve the quality problem face cosmological problems, and vice versa. This is not a no-go theorem; nonetheless, we argue that it is much more difficult than generally appreciated to find a viable post-inflation QCD axion model. Successful examples may have a nonstandard cosmological history (e.g., multiple types of cosmic axion strings of different tensions), undermining the widespread expectation that the post-inflation QCD axion scenario predicts a unique mass for axion dark matter.

Physics↗
DOE OSTI2023

Removal of fission product tellurium and iodine from recently irradiated HEU using copper metal

Gamma detection of select fission products or activation products such as 153 Sm and 239 Np in a fission sample is difficult due to gamma interferences from radiotellurium and radioiodine. To aid in the detection of these difficult-to-detect nuclides, the radiotellurium and radioiodine were removed using Cu metal turnings. This method is highly effective at the removal of the interfering radionuclides removing > 98% of the radiotellurium and radioiodine. A mechanistic study was conducted. Determining the deposition mechanism, using a number of techniques including XANES and electrochemistry providing an understanding of the electrochemical path for the Te deposition. Initial work focused on the use of stable Te, further expanding into activated TeO 2 , and a fresh fission sample. Importantly, this method presents a rapid method for the direct detection of select fission products that could have a significant impact on nuclear related fields including nuclear forensics.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

A Conterminous USA-Scale Map of Relative Tidal Marsh Elevation

Abstract Tidal wetlands provide myriad ecosystem services across local to global scales. With their uncertain vulnerability or resilience to rising sea levels, there is a need for mapping flooding drivers and vulnerability proxies for these ecosystems at a national scale. However, tidal wetlands in the conterminous USA are diverse with differing elevation gradients, and tidal amplitudes, making broad geographic comparisons difficult. To address this, a national-scale map of relative tidal elevation ( Z * MHW ), a physical metric that normalizes elevation to tidal amplitude at mean high water (MHW), was constructed for the first time at 30 × 30-m resolution spanning the conterminous USA. Contrary to two study hypotheses, watershed-level median Z * MHW and its variability generally increased from north to south as a function of tidal amplitude and relative sea-level rise. These trends were also observed in a reanalysis of ground elevation data from the Pacific Coast by Janousek et al. (Estuaries and Coasts 42 (1): 85–98, 2019). Supporting a third hypothesis, propagated uncertainty in Z * MHW increased from north to south as light detection and ranging (LiDAR) errors had an outsized effect under narrowing tidal amplitudes. The drivers of Z * MHW and its variability are difficult to determine because several potential causal variables are correlated with latitude, but future studies could investigate highest astronomical tide and diurnal high tide inequality as drivers of median Z * MHW and Z * MHW variability, respectively. Watersheds of the Gulf Coast often had propagated Z * MHW uncertainty greater than the tidal amplitude itself emphasizing the diminished practicality of applying Z * MHW as a flooding proxy to microtidal wetlands. Future studies could focus on validating and improving these physical map products and using them for synoptic modeling of tidal wetland carbon dynamics and sea-level rise vulnerability analyses.

Holmquist, James R. (ORCID:0000000325466766)↗
DOE OSTI2022

Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design

Abstract There are two broad modeling paradigms in scientific applications: forward and inverse. While forward modeling estimates the observations based on known causes, inverse modeling attempts to infer the causes given the observations. Inverse problems are usually more critical as well as difficult in scientific applications as they seek to explore the causes that cannot be directly observed. Inverse problems are used extensively in various scientific fields, such as geophysics, health care and materials science. Exploring the relationships from properties to microstructures is one of the inverse problems in material science. It is challenging to solve the microstructure discovery inverse problem, because it usually needs to learn a one-to-many nonlinear mapping. Given a target property, there are multiple different microstructures that exhibit the target property, and their discovery also requires significant computing time. Further, microstructure discovery becomes even more difficult because the dimension of properties (input) is much lower than that of microstructures (output). In this work, we propose a framework consisting of generative adversarial networks and mixture density networks for inverse modeling of structure–property linkages in materials, i.e., microstructure discovery for a given property. The results demonstrate that compared to baseline methods, the proposed framework can overcome the above-mentioned challenges and discover multiple promising solutions in an efficient manner.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Precipitation-site competition in duplex stainless steels: Cu clusters vs spinodal decomposition interfaces as nucleation sites during thermal aging

Competing microstructural evolution mechanisms can exist simultaneously when duplex stainless steels are operating for several decades in a high temperature service environment. Such competition between different microstructural evolution pathways can be difficult to ascertain using simple model alloy systems necessitating detailed structural and compositional analysis of phase transformation mechanisms in complex alloys Thus, in this study duplex stainless steels with complex but well understood chemistries were used to investigate the relative importance of different heterogeneous nucleation sites – specifically spinodal decomposition and Cu clustering – on precipitation of Ni-Si-Mn particles during long term thermal aging. Precipitation of Ni-Si-Mn particles in duplex stainless steels and ferritic steels during thermal aging and irradiation is known to have profound effect on mechanical properties. Using duplex stainless steels with custom modified compositions along with atom probe tomography characterization and first-passage kinetic Monte Carlo (FPKMC) simulations it is revealed that while the interface between Cr and Fe formed during spinodal decomposition can be a pathway for diffusion of Ni, Si, Mn, and Cu, it is not a site that encourages precipitation of Ni-Si-Mn rich particles. Instead, the presence of a higher concentration of Cu in these steels leads to formation of small Cu clusters with high energy interfaces that act as nucleation sites for Ni-Si-Mn particles because of its strong interaction particularly with Ni increasing the chemical driving force for precipitation. These results will help inform predictive models for the use of duplex stainless steels and other precipitation-hardened alloys for extended operation at high temperatures.

Duplex stainless steel, Thermal aging, Precipitati↗
DOE OSTI2024

Modeling powder spreadability in powder-based processes using the discrete element method

Powder-bed fusion (PBF) processes refer to a subset of Additive Manufacturing (AM) techniques where powder is spread on the build-plate before melting (by a laser or electron beam). While PBF processes are attractive due to their ability for realizing complex structures that are either difficult or impossible to create through conventional means, the parts fabricated with these techniques can exhibit defects such as pores, inclusions, and excessive surface roughness. To minimize these defects, much research has been dedicated towards process maturation by optimizing laser or electron beam parameters. However, these developmental efforts typically do not address the recoating process where achieving dense and uniform layers of powder is a necessity for ensuring process repeatability and part quality. While the recoating process can be studied through experimentation, the dynamics of particle movement are difficult to analyze experimentally. Therefore, here, in this study, powder spreading in PBF was simulated through the Discrete Element Method (DEM) to elucidate the mechanisms that control powder-bed quality. Utilizing the Buckingham Pi theorem, a dimensionless metric referred to as the spreading index is developed that combines powder-bed density, roughness, and particle size to assess the quality of powder layers. The formulated spreading index is then related to several dimensionless quantities that provide insight into the mechanisms dominating powder spreading in PBF. The DEM simulations conducted in this work focused on the scenario where powder is spread onto an existing powder bed and revealed that a reduction in the recoating velocity causes an increase in the spreading index while little to no impact on the spreading index was observed when varying layer thickness from 30 μm to 75 μm.Particle size effects on the powder-bed quality were also investigated.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Prediction of residual stresses in additively manufactured parts using lumped capacitance and classical lamination theory

Several industries are interested in Laser Powder Bed Fusion (L-PBF) Additively Manufactured (AM) metal parts because their designs can be made arbitrarily complex while retaining bulk-type material properties. However, the residual stresses (RS) and distortions caused by the heat gradients inherent to L-PBF processes are detrimental to the structural integrity of the parts and must be taken into consideration during the part design cycle. Predicting the state of stresses in as-built 3D printed parts is a difficult problem that is typically approached with the use of transient thermomechanical Finite Element Models (FEMs). However, the nonlinearities associated with AM processes are difficult to capture in these FEMs without increasing the computational cost of the simulation, limiting their ability to be incorporated into practical design cycles. This work presents a novel analytical framework that combines lumped capacitance nonlinear heat transfer with time dependent classical lamination theory to efficiently and accurately predict RS in as-built L-PBF parts without the need of FEMs. The simulation was compared to Neutron Diffraction (ND) residual strain measurements taken at Oak Ridge National Laboratories (ORNL) as well as Synchrotron X-ray Diffraction (XRD) strain data published by the National Institute of Standards and Technology (NIST). The simulation predictions and the experimental data showed excellent agreement for the in-plane strain directions, and general agreement for the out of plane strain component, highlighting an area where further development can be implemented.

42 ENGINEERING↗
DOE OSTI2025

Open data sets for assessing photovoltaic system reliability

Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types is used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, image inspection and module materials, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driven research. Our aim is to enhance data utilization and publication among researchers and industry professionals, promoting a deeper understanding of the role of data in enhancing the performance and durability of PV systems.

14 SOLAR ENERGY↗
DOE OSTI2024

Lattice light-sheet microscopy allows for super-resolution imaging of receptors in leaf tissue

Plant leaf tissues are difficult to image via fluorescent microscopy, largely due to the presence of chlorophyll and other pigments that provide large background fluorescence. An advantage of Lattice Light-Sheet microscopy is its use of Bessel beams that illuminate a thin focal region of interest for microscopy, allowing for the excitation of fluorescent molecules within this region without surrounding chlorophyll-like objects outside of the region of interest. Here, we apply STORM Super-resolution techniques to observe Receptor-Like Kinases in Arabidopsis thaliana leaf cells. By applying this technique with the Lattice Light-Sheet, we can localize immune response proteins in sub-100 nm length scales and reconstruct three-dimensional locations of proteins within individual leaf cells. Using this technique, we observed the effect of the elicitors ATP and flg22, where we observed a significant degree of internalization of cognate receptors P2K1 and FLS2. We were also able to similarly observe differences in colocalization due to stimulation with these elicitors, where we observe proteins on the membrane becoming less colocalized as a result of stimulation, suggesting an immune response mechanism involving receptors internalizing via pathways distinct to the receptor. Further, these data show the Lattice Light-Sheet’s capabilities for imaging tissue with problematic background fluorescence that otherwise makes super-resolution fluorescence microscopy difficult.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Transforming polymorphs, melting, and boiling during cookoff of PETN

Transforming polymorphs, melting, and boiling are physical processes that can accelerate decomposition rates during cookoff of PETN and make measurements difficult. For example, splashing liquids from large bubbles filled with decomposition products clog pressure tubing in sealed experiments. Boil over can also extinguish thermal excursions in vented experiments making ignition difficult. For better measurements, we have modified the Sandia Instrumented Thermal Ignition (SITI) experiment to obtain better sealed and vented cookoff data for PETN by reducing the sample size and including additional gas space to prevent clogged tubing and boil over. Ignition times were not affected by 1) increasing the gas space by a factor of 3 in sealed SITI experiments or by 2) venting the decomposition gasses. That is, thermal ignition of PETN is not pressure dependent and the rate-limiting step during PETN decomposition likely occurs in the condensed phase. A simple decomposition model was calibrated using these observations and includes rate acceleration caused by melting and boiling. The model is used to predict internal temperatures, pressurization, and thermal ignition in a wide variety of experiments. Furthermore, the model is also used with SITI data to estimate the previously unreported latent enthalpy (5 J/g) associated with the α (PETN-I) to β (PETN-II) polymorphic phase transformation of PETN.

42 ENGINEERING↗
DOE OSTI2025

Common Column Identification for Table Similarity Detection in Electrified Transportation Data Lakes

Electrified transportation often requires researchers and operators to interact with datasets from a wide range of sources and disciplines, such as transportation, power systems, public health, policies, and regulations. These datasets vary in quality and format, making it difficult to understand, preprocess, and identify key columns representing real-world entities or values for indexing and joining, which can negatively impact downstream analysis and operation. Existing solutions are limited, requiring extensive manual customization or data expertise to utilize. In this article, we propose a multi-layered approach to automatically identify key columns to expedite preprocessing and aid in analysis of electrified transportation data. Our method leverages a dynamic ontology to identify common fields and an information theory-based strategy for edge cases that are difficult to generalize. Evaluations on a number of datasets from data.gov and kaggle.com show improved performance of our methods over several baseline techniques, and our ablation analyses illustrate the efficacy of individual components of our method. Our case studies also demonstrate that our methods have the potential to improve analysis of electrified transportation data and aid in automatic integration of such datasets.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Geophysical monitoring using active seismic techniques at the Citronelle Alabama CO 2 storage demonstration site

Between August 2012 and September 2014, about 114,000 metric tonnes of CO 2 was captured from the coal-fired Plant Barry Power Station at Bucks Alabama and injected into the Paluxy Formation above the oil pool in the southeast unit of the Citronelle Oilfield. Various monitoring methods were deployed at land surface and in project wells to measure system performance, comply with permit requirements and test new and innovative monitoring tools. The monitoring program relied heavily on active seismic methods for subsurface imaging of geologic structure and time-lapse seismic techniques to track the CO 2 migration in the injection interval. Both conventional geophone/hydrophone and fiber-optic based Distributed Acoustic Sensing (DAS) arrays were deployed and tested, allowing a side by side comparison of the equipment and techniques. Geophysical imaging of the subsurface was successful using DAS in the offset vertical seismic profile (OVSP) survey configuration. A high resolution OVSP image of the subsurface was obtained in 2014 with DAS, which exceeded project expectations in comparison to a lower resolution image obtained in 2012 using a conventional 80-level geophone array. A time-lapse image of the redistribution of CO 2 after injection ended in September 2014 was obtained with two DAS OVSP surveys from June 2014 and December 2015, thus successfully demonstrating its proof-of-concept. Unfortunately, a pre-injection baseline survey with DAS, which was in its initial stage of technology development in 2012, did not have sufficient quality for use, making it difficult to interpret the acquired DAS time-lapse difference. Additional research in this area has since demonstrated the utility of time-lapse DAS OVSP. DAS data were also acquired during a cross-well seismic survey conducted in 2014. Unfortunately, the DAS technique was not success in the cross-well survey configuration because the system noise level was too high in the crosswell frequency output range (100–1200 Hz) of the piezoelectric source (increasing by a factor of ten compared to VSP frequency band). Additionally, the cross-well geometry causes sub-horizontal (broadside) incidence on the vertical DAS fiber cable, which is known to be problematic. Current research is focused on improving the DAS cable response to broadside acoustic energy. Time-lapse seismic surveys using commercially available conventional arrays were also acquired. In contrast to the DAS acquired data, the cross-well seismic results obtained with the conventional array was highly successful and clearly showed the CO 2 remained in zone at the end of injection. Time-lapse differencing of the OSVP surveys acquired with the conventional arrays proved to be inconclusive. Finally, changes in wellbore conditions between surveys and unavoidable changes in equipment (the array used for the baseline survey was retired) affected data quality, making it difficult to interpret the OVSP results.

58 GEOSCIENCES↗
DOE OSTI2023

Mechanistic study of heterogeneous propene metathesis on WO x /SiO 2 catalysts

Silica-supported tungsten oxides are widely used industrial catalysts for olefin metathesis due to their low cost and robustness, yet the mechanisms for heterogeneously catalyzed metathesis reactions remain comparatively less understood. In this work, density-functional theory (DFT) calculations were used to study the model reactions of propene metathesis. Our calculations confirm that the metathesis reactions catalyzed by WO x /SiO 2 largely follow the Chauvin cycle, with an overall energetic barrier of 142 kJ/mol. To understand how the initial alkylidene active sites are generated, three mechanisms were examined: The pseudo-Wittig mechanism was found to be most favorable and proceeds with a metallacycle intermediate, while the allylic and vinylic C-H activations are much more difficult and require the reduction of surface sites to W(+4). Relative to the adsorbed reactant state, the overall intrinsic barriers for three mechanisms were computed to be 193, 261, and 355 kJ/mol, respectively. In conclusion, the higher barriers for active-site formation than for the metathesis cycle are consistent with the difficult, high-temperature pretreatment required in experiments to activate WO x /SiO 2 catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machinability comparison of additively manufactured and traditionally wrought Ti-6Al-4V alloys using single-point cutting

Post-machining is often needed to provide high dimensional accuracy and fine surface finish for additively manufactured Ti-6Al-4V (Ti64). The material inhomogeneity, such as pores and microstructures, can affect the machining behavior of this already difficult-machine alloy. This study adopts a holistic approach to compare the machinability of additively manufactured and traditionally wrought Ti64 in terms of key machining factors, including forces, temperature, and vibration and the major machining outcomes including tool life, surface finish, and dimensional accuracy. Stress-relief annealing is applied to each of the part conditions as a secondary variable to observe the additional effects. The results show that AM is not particularly more difficult to machine in terms of cutting force and temperature, but it creates high cutting vibrations across a wide range of frequencies (to and over 5 kHz). The high vibrations do not lead to worse surface finish or dimensional accuracy but tend to worsen the tool life by chipping off the cutting edge. The vibration can be attributed to the brittle martensitic microstructure found in additively manufactured Ti64, which is also evidenced by the more serrated chips. Stress-relieving is found to change the microstructure and reduce the level of vibration to that of the wrought counterpart.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Coupled physics simulation of fracture in nuclear fuel pellets induced by resistive heating

While it is well known that the UO 2 fuel used in light-water reactors cracks early in its life in the reactor, it is very difficult to collect in-reactor data regarding fuel cracking initiation and propagation to validate fracture models in fuel performance codes. Most fracture data comes from the post-irradiation examination of fuel that has been subjected to long and complex power histories. Replicating the thermal gradients experienced in this fuel to study crack initiation and propagation in a laboratory environment is challenging. This is primarily because the fuel is heated volumetrically by fission, which is difficult to replicate. One way to approximate this volumetric heating out of the reactor is to use electrical resistance (or Joule heating). An electrical conductivity model has been developed and coupled with the existing thermomechanical modeling capability in the BISON nuclear fuel performance code. This will permit simulation of experiments that use resistive heating for the purpose of validating fracture models in BISON. The modeling approach developed here is applied to simulate both historical and current resistive heating experiments on ceramic nuclear fuel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗