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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Correlation-temperature phase diagram of prototypical infinite layer rare earth nickelates

The discovery of superconductivity in hole-doped infinite layer nickelates, RNiO 2 (R = Nd, Pr, La) has resulted in sustained interest in the field. A definitive picture of low-energy many-body states has not yet emerged. Here we provide insights into the low-energy physics, based on our embedded dynamical mean-field theory calculations, and propose a correlation (U)-temperature (T) phase diagram. The key features are a low-T Fermi liquid (FL) phase, a high-T Curie-Weiss regime, and an antiferromagnetic phase in a narrow U-T region. We associate the onset of the FL phase with partial screening of Ni-d moments; however, full screening occurs at lower temperatures. This may be related to insufficiency of conduction electrons to effectively screen the Ni-d moments, suggestive of Nozieres Exhaustion Principle. Our results suggest that RNiO 2 are in the paramagnetic state, close to an antiferromagnetic dome, making magnetic fluctuations feasible. This may be consequential for superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Intricacies of frustrated magnetism in the Kondo metal YbAgGe

The combination of localized magnetic moments, their frustration and interaction with itinerant electrons is a key challenge of condensed matter physics. Frustrated magnetic interactions promote degenerate ground states with enhanced fluctuations, a topic that is predominantly studied in magnetic insulators. The coupling between itinerant and localized electrons in metals add complexity to the problem, and is presently formulated only for extreme cases in which the itinerant electrons mediate exchange between localized spins (RKKY interaction) or suppress the formation of magnetic moments (Kondo screening). Here, we report an in-depth experimental study of the distorted Kagome metal YbAgGe, unravelling the open questions of how frustration, localized magnetism and itinerant electrons are intertwined in frustrated Kondo metals. We find that coupled itinerant and localized electrons give rise to dynamic magnetic correlations below T* ≈ 20 K. At lower temperature, frustrated magnetic interactions establish anisotropic magnetic short-range correlations that culminate into antiferromagnetic long-range order below T N = 0.68 K with a significantly reduced modulated magnetic moment. We show that local moment Hamiltonians can yield limited understanding of the microscopic behaviour in frustrated metals, and prompt the extension of more sophisticated model Hamiltonians incorporating itinerant effects.

Mazzone, Daniel G. [PSI Center for Neutron and Muo↗
DOE OSTI2019

A comprehensive genomic scan reveals gene dosage balance impacts on quantitative traits in Populus trees

Gene dosage variation and the associated changes in gene expression influence a wide variety of traits, ranging from cancer in humans to yield in plants. It is also expected to affect important traits of ecological and agronomic importance in forest trees, but this variation has not been systematically characterized or exploited. Here we performed a comprehensive scan of the Populus genome for dosage-sensitive loci affecting quantitative trait variation for spring and fall phenology and biomass production. The study population was a large collection of clonally propagated F1 hybrid lines of Populus that saturate the genome 10-fold with deletions and insertions (indels) of known sizes and positions. As a group, the phenotypic means of the indel lines consistently differed from control nonindel lines, with an overall negative effect of both insertions and deletions on all biomass-related traits but more diverse effects and an overall wider phenotypic distribution of the indel lines for the phenology-related traits. We also investigated the correlation between gene dosage at specific chromosomal locations and phenotype, to identify dosage quantitative trait loci (dQTL). Such dQTL were detected for most phenotypes examined, but stronger effect dQTL were identified for the phenology-related traits than for the biomass traits. Furthermore our genome-wide screen for dosage sensitivity in a higher eukaryote demonstrates the importance of global genomic balance and the impact of dosage on life history traits.

09 BIOMASS FUELS↗
DOE OSTI2023

Explainable machine learning for hydrogen diffusion in metals and random binary alloys

Hydrogen diffusion in metals and alloys plays an important role in the discovery of new materials for fuel cell and energy storage technology. While analytic models use hand-selected features that have clear physical ties to hydrogen diffusion, they often lack accuracy when making quantitative predictions. Machine learning models are capable of making accurate predictions, but their inner workings are obscured, rendering it unclear which physical features are truly important. To develop interpretable machine learning models to predict the activation energies of hydrogen diffusion in metals and random binary alloys, we create a database for physical and chemical properties of the species and use it to fit six machine learning models. Our models achieve root-mean-squared errors between 98–119 meV on the testing data and accurately predict that elemental Ru has a large activation energy, while elemental Cr and Fe have small activation energies. By analyzing the feature importances of these fitted models, we identify relevant physical properties for predicting hydrogen diffusivity. While metrics for measuring the individual feature importances for machine learning models exist, correlations between the features lead to disagreement between models and limit the conclusions that can be drawn. Instead grouped feature importance, formed by combining the features via their correlations, agree across the six models and reveal that the two groups containing the packing factor and electronic specific heat are particularly significant for predicting hydrogen diffusion in metals and random binary alloys. In conclusion, this framework allows us to interpret machine learning models and enables rapid screening of new materials with the desired rates of hydrogen diffusion.

36 MATERIALS SCIENCE↗
NASA NTRS1978

Development of the Equatorial Infrared Catalogue from satellite data

More than 40,000 infrared measurements of stellar sources have been obtained since November, 1976 during the ongoing process of compiling an Equatorial Infrared Catalogue. Because of the problem of eliminating spurious sources, which has affected earlier space surveys, an extensive effort is being made to verify the sources by means of (1) repetitive observations by satellite sensors, (2) cross correlation with a large data base developed from ground-based and space surveys at other wavelengths, and (3) investigation of a significant subset of the sources with a ground-based infrared telescope. As sources are verified, they are transferred from a working list to a screened preliminary version of the catalogue. The catalogue comprises the only survey of a significant area of the sky that has been accomplished (or is presently planned) with positional accuracies of a few arc seconds at a wavelength of not less than 2 microns.

Heinsheimer, T. F.↗
NASA NTRS2010

Development of a Catalytic Coating for a Shuttle Flight Experiment

A spray-on coating was developed for use on the shuttle wing tiles to obtain data that could be correlated with computational fluid dynamics (CFD) solutions to better understand the effect of chemical heating on a fore-body heat shield having a turbulent boundary layer during planetary entry at hypersonic speed. The selection of a spray-on coating was conducted in two Phases 1) screening tests to select the catalytic coating formulation and 2) surface property determination using both arc-jet and side-arm facilities at NASA Ames Research Center. Comparison of the predicted surface temperature profile over a flat-plate with measured values obtained during arc-jet exposure (Phase I study) was used to validate the surface properties obtained during Phase II.

Stewart, David A.↗
DOE OSTI2016

miR-144-3p serves as a tumor suppressor for renal cell carcinoma and inhibits its invasion and metastasis by targeting MAP3K8

MicroRNAs (miRNAs) are important regulators involved in various cancers, including renal cell carcinoma (RCC). The role of the miRNAs involved in RCC progress and metastasis is largely unknown. Here, miRNA microarray analysis was performed to screen the significant miRNAs involved in RCC progress, and miR-144-3p was chosen for further study. We found that the expression of miR-144-3p was significantly lower in RCC specimens and cell lines. In addition, low expression level of miR-144-3p is correlated with tumor progression and poor survival in RCC patients. Based on in vitro assays, we found that miR-144-3p significantly inhibit cancer cell proliferation and progression. Furthermore, function studies revealed that miR-144-3p was significantly correlated with the metastasis potential by affecting the epithelial-mesenchymal transition (EMT). Moreover, Mitogen-activated protein kinase 8 (MAP3K8) is direct target of miR-144-3p, while the expression levels of MAP3K8 were inversely correlated with the expression levels of miR-144-3p in RCC tissues. Overall, our findings demonstrate that miR-144-3p targeted the MAP3K8 pathway to reduce tumor cells proliferation and metastasis in RCC, suggesting that this axis may provide a novel therapeutic target for RCC therapy. - Highlights: • Downregulation of miR-144-3p expression was significantly associated with the poor survival in RCC patients. • Ectopic expression of miR-144-3p inhibits viability and metastasis of RCC cells in vitro. • miR-144-3p suppresses the epithelial-mesenchymal transition in RCC cells. • MAP3K8 is a direct target of miR-144-3p, and miR-144-3p downregulation is a factor in RCC progression through potentiation of MAP3K8 expression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Screening Ionic Liquids Based on Ionic Volume and Electrostatic Potential Analyses

Ionic liquids are known to have tunable solvation properties, based on the pairing of different anions and cations, but the compositional landscape is vast and challenging to navigate efficiently. Some computational screening protocols are available, but they can be either time-consuming or difficult to implement. Herein, we perform a detailed investigation of the fundamental role of electrostatic interactions in these systems. We effectively develop a bridge between the previous volume-based approach (VBA) with a quantum structure–property relationship (QSPR) approach to create fast, simple screening guidelines. We propose a new parameter that is applicable to both monovalent and multivalent ions, the ionic polarity index (IPI), which is defined as the ratio of the average electrostatic surface potential ($\bar{V}$) of the ion to the net charge of the ion (q). The IPI correlation has been tested on a diverse dataset of 121 ions and reliable predictions can be obtained within a homologous series of ionic liquid compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Role of effective mass and long-range interactions in the band-gap renormalization of photoexcited semiconductors

Understanding how to control changes in the electronic structure and related dynamical renormalizations by external driving fields is the key for understanding ultrafast spectroscopy and applications in electronics. Here, we focus on the band gap's modulation by external electric fields and uncover the effect of band dispersion on the gap renormalization. We employ the Green's function formalism using the real-time Dyson expansion to account for dynamical correlations induced by photodoping. The many-body formalism captures the dynamics of systems with long-range interactions, carrier mobility, and variable electron and hole effective mass. We also demonstrate that mean-field simulations based on the Hartree-Fock Hamiltonian, which lacks dynamical correlations, yields a qualitatively incorrect picture of band-gap renormalization. We find the trend that increasing effective mass, thus decreasing mobility, leads to as much as a 6% enhancement in band-gap renormalization. Further, the renormalization is strongly dependent on the degree of photodoping. As the screening induced by free electrons and holes effectively reduces any long-range and interband interactions for highly excited systems, we show that there is a specific turnover point with a minimal band gap. Here, we further demonstrate that the optical gap renormalization follows the same trend though its magnitude is altered by the Moss-Burstein effect.

Approximation methods for many-body systems↗
DOE OSTI2016

What goes on behind closed doors? How college dormitory residents change to save energy during a competition-based energy reduction intervention

Here, the aim of our study was to evaluate the impact of a competition-based intervention combining high resolution electricity feedback, incentives, information, and prompts on college dormitory residents’ energy consumption and participation in demand response (DR) events. We also investigated changes in individual-level pro-environmental behaviors and examined psycho-social correlates of behavior change. Residents of 39 suites in a freshman residence hall competed against one another to reduce energy consumption and win prizes as part of a 3-week competition. Feedback was provided in near real time at the suite-level via an interactive touch-screen kiosk. Participants also completed baseline and followup surveys. Findings have indicated that electricity use among all suites was approximately 6.4% lower during the competition period compared to baseline, a significant reduction. Additionally, participants reported engaging in various pro-environmental behaviors significantly more frequently during the competition relative to baseline. Changes in pro-environmental behavior were associated with changes in level of group identification and perceived social norms. In three weeks, dormitory residents saved 3, 158 kWh of electricity compared to baseline – the equivalent of more than 3, 470 pounds of carbon dioxide emissions. Our findings provide evidence that real-time feedback, combined with incentives, information, and prompts, can motivate on-campus residents to reduce energy consumption. We contribute to a limited body of evidence supporting the effectiveness of dorm energy competitions in motivating college students to save energy. In addition, we identified individual-level behavioral and psycho-social changes made during such an intervention. University residential life planners may also use the results of this research to inform student programming.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Enhancing chemical bioproduction with rational control of bacterial post-translational modifications

Efficient conversion of inexpensive feedstocks to valuable chemicals by microbes is critical for a robust bioeconomy, but the ability to rationally design bacteria is hampered by insufficient knowledge of how post translational modifications (PTMs) control bacterial protein function and thus bioproduction phenotypes. Our study will focus on the lysine acetylation, a ubiquitous bacterial PTM that can affect the function of enzymes in central metabolism that are often critical for bioproduction processes, disrupt transcriptional regulation, and reduce translation. However, most lysine acetylation data is observational, which means that we do not know when, how, and what specific acetylated residues affect protein function and bacterial physiology. For our model host, we will use a Pseudomonas putida strain that we previously engineered to convert lignocellulosic feedstocks into chemicals such as itaconic acid (ITA). With this strain, we use a dynamic two-stage bioproduction process in which ITA is produced during a non-growth associated production phase. Production is highest during growth stages when lysine acetylation is low in other organisms (early stationary phase) and stalls in conditions where acetylation is highest (late stationary phase). The switch from high to stalled ITA production is also correlated with an unexpected increase in acetate levels – the precursor to non-enzymatic lysine acetylation. As such, we predict that lysine acetylation plays a substantial role in regulating the metabolic pathways required for ITA production. We will develop a generalizable approach that combines high-throughput genetic screens and cutting-edge genome engineering with state-of-the-art proteomics, metabolomics, and genetic code expansion methods to identify and modulate lysine acetylation patterns in bacteria. Ultimately, these strategies aim to manipulate protein expression and acetylation patterns to enhance bioproduction phenotypes (e.g., sustained ITA production in late stationary phase).

60 APPLIED LIFE SCIENCES↗
NASA NTRS1992

Trend analysis for large solid rocket motors - A program level approach

This paper defines a program-level trend analysis effort that can be applied to large solid rocket motors. The effort is especially applicable to large segmented rocket motors such as the Space Transportation System's solid rocket boosters. Five types of trend analysis are discussed for different aspects of a rocket motor program, (performance, reliability, problem, supportability, and programmatic). Ideas are offered for implementing and performing a program-level trend analysis effort by giving suggestions for selecting computer capabilities, choosing parameters, selecting statistical processes, routine screening for trends, analyzing significant trends (for example, looking for related trends and determining if adverse trends are resolved), and reporting results of trend analysis. The use of program-level trending allows for the ability to easily transfer data between organizations and easily use the data to correlate trends from the various organizations to find causal relationships. Efficiency is enhanced from upper level management to the shop floor at vendor locations by using the same trend analysis software and methodology at all organizations.

Babbitt, Norman E., III↗
DOE OSTI2015

Self-consistent Kohn-Sham method based on the adiabatic-connection fluctuation-dissipation theorem and the exact-exchange kernel

A self-consistent Kohn-Sham method based on the adiabatic-connection fluctuation-dissipation (ACFD) theorem, employing the frequency-dependent exact exchange kernel f{sub x} is presented. The resulting SC-exact-exchange-only (EXX)-ACFD method leads to even more accurate correlation potentials than those obtained within the direct random phase approximation (dRPA). In contrast to dRPA methods, not only the Coulomb kernel but also the exact exchange kernel f{sub x} is taken into account in the EXX-ACFD correlation which results in a method that, unlike dRPA methods, is free of self-correlations, i.e., a method that treats exactly all one-electron systems, like, e.g., the hydrogen atom. The self-consistent evaluation of EXX-ACFD total energies improves the accuracy compared to EXX-ACFD total energies evaluated non-self-consistently with EXX or dRPA orbitals and eigenvalues. Reaction energies of a set of small molecules, for which highly accurate experimental reference data are available, are calculated and compared to quantum chemistry methods like Møller-Plesset perturbation theory of second order (MP2) or coupled cluster methods [CCSD, coupled cluster singles, doubles, and perturbative triples (CCSD(T))]. Moreover, we compare our methods to other ACFD variants like dRPA combined with perturbative corrections such as the second order screened exchange corrections or a renormalized singles correction. Similarly, the performance of our EXX-ACFD methods is investigated for the non-covalently bonded dimers of the S22 reference set and for potential energy curves of noble gas, water, and benzene dimers. The computational effort of the SC-EXX-ACFD method exhibits the same scaling of N{sup 5} with respect to the system size N as the non-self-consistent evaluation of only the EXX-ACFD correlation energy; however, the prefactor increases significantly. Reaction energies from the SC-EXX-ACFD method deviate quite little from EXX-ACFD energies obtained non-self-consistently with dRPA orbitals and eigenvalues, and the deviation reduces even further if the Coulomb kernel is scaled by a factor of 0.75 in the dRPA to reduce self-correlations in the dRPA correlation potential. For larger systems, such a non-self-consistent EXX-ACFD method is a competitive alternative to high-level wave-function-based methods, yielding higher accuracy than MP2 and CCSD methods while exhibiting a better scaling of the computational effort than CCSD or CCSD(T) methods. Moreover, EXX-ACFD methods were shown to be applicable in situation characterized by static correlation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Rigorous Ab Initio Quantum Embedding for Quantum Chemistry Using Green’s Function Theory: Screened Interaction, Nonlocal Self-Energy Relaxation, Orbital Basis, and Chemical Accuracy

We present a detailed discussion of the self-energy embedding theory (SEET), which is a quantum embedding scheme allowing us to describe a chosen subsystem very accurately while keeping the description of the environment at a lower level. We apply SEET to molecular examples where our chosen subsystem is made out of a set of strongly correlated orbitals while the weakly correlated orbitals constitute an environment. Consequently, a highly accurate method is used to calculate the self-energy for the system, while a lower-level method is employed to find the self-energy for the environment. Such a self-energy separation is very general, and to make the SEET procedure applicable to multiple systems, a detailed and practical procedure for the evaluation of the system and environment self-energy is necessary. We list all of the intricacies for one of the possible procedures while focusing our discussion on many practical implementation aspects such as the choice of best orbital basis, impurity solver, and many steps necessary to reach chemical accuracy. Finally, on a set of carefully chosen molecular examples, we demonstrate that SEET, which is a controlled, systematically improvable Green’s function method, can be as accurate as established wave function quantum chemistry methods.

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

A small-volume, high-throughput approach for surface tension and viscosity measurements of liquid fuels

An ongoing effort looking at bioblendstocks to function as drop-in replacements or blending components for gasoline has identified a large number of candidate fuels. This work documents an approach for rapid screening of candidate fuels using relatively small sample sizes ($\mathcal{O}(\mu\,{\rm l})$) that targets two key physical properties of liquid fuels—surface tension and viscosity. The approach utilizes shape oscillation dynamics of single droplets generated by a piezo-electric device and their decay over time. Strobed imaging of the oscillation process is used along with image processing, edge detection, and data analysis to capture the decay of the oscillation over time. The time constant of the decay process along with oscillation frequency are then used to estimate viscosity and surface tension using a theory for small amplitude droplet oscillations. Measurements are obtained for primary reference fuels (isooctane and n-heptane) as well as candidate fuels from four bio-derived functional groups of interest. Measurement results for surface tension and viscosity are correlated with literature data as well as measurements from standard reference instruments. The measurement results show that the droplet oscillation based approach is capable of reproducing surface tension and viscosity values for the tested fuels within deviations of 7% and 13% respectively from literature data. Results are obtained using an average of 5 µl per fuel within about 20 s, thus demonstrating a small-volume, high-throughput approach that can be used for screening of candidate bioblendstock fuels.

09 BIOMASS FUELS↗
DOE OSTI2024

Functional promiscuity of small multidrug resistance transporters from Staphylococcus aureus , Pseudomonas aeruginosa , and Francisella tularensis

Abstract Small multidrug resistance transporters efflux toxic compounds from bacteria and are a minimal system to understand multidrug transport. Most previous studies have focused on EmrE, the model SMR from Escherichia coli , finding that EmrE has a broader substrate profile than previously thought and that EmrE may perform multiple types of transport, resulting in substrate‐dependent resistance or susceptibility . Here, we performed a broad screen to identify potential substrates of three other SMRs: PAsmr from Pseudomonas aeruginosa ; FTsmr from Francisella tularensis ; and SAsmr from Staphylococcus aureus . This screen tested metabolic differences in E. coli expressing each transporter versus an inactive mutant, for a clean comparison of sequence and substrate‐specific differences in transporter function, and identified many substrates for each transporter. In general, resistance compounds were charged, and susceptibility substrates were uncharged, but hydrophobicity was not correlated with phenotype. Two resistance hits and two susceptibility hits were validated via growth assays and IC50 calculations. Susceptibility is proposed to occur via substrate‐gated proton leak, and the addition of bicarbonate antagonizes the susceptibility phenotype, consistent with this hypothesis.

Biochemistry & Molecular Biology↗
DOE OSTI2018

Advanced SOFC quality control and the role of manufacturing defects on stack reliability

Atrex Energy rolled out first commercial SOFC generator products in 2013. Following that we embarked on implementation of mass production in order to ramp up productivity and lower the costs in the meantime. To ensure the goal of mass production, an accurate, cost effective and consistent quality control methodology needs to be in place. The aim of this DOE funded project is to devise a machine and methodology for cell quality control using modern non-destructive testing methods and cell rejection criterion based on the empirical determination of the role of manufacturing flaws on stack degradation and reliability. The work scope encompasses two goals aimed at 1) developing automatable techniques for objective flaw detection and 2) developing an understanding of the ramifications of flaws on stack and cell reliability. By accomplishing these two goals it is likely that an advanced stage Quality Control (QC) device can be developed. This project scope encompasses: 1) Invention of a high speed automated instrument for spatial mapping of surface and sub-surface imperfections in production cells (ex situ) using modern imaging techniques. 2) Identification of rejection criteria upon which to screen cells from production by: a. Magnification of the effect of production defects on cell degradation through fabrication and testing of micro-cells which encompass these imperfections. b. The long term testing of full size production cells both as single cells and in small stacks, in order to correlate the (in situ) performance and degradation with the imperfection type (identified ex-situ) and hence be able to classify imperfections as actual defects. We first built a defect library with the cells containing imperfections classified and documented. The cells with various imperfections were tested to evaluate the imperfection potential impact on cell electrochemical performance. Evaluations were conducted on minicell, single cell and stack levels. On minicell level, pinhole, scratch, crack, contamination, and pop-out were investigated. We found: (1) none of the imperfections causes calamity type failure, (2) pinholes do not show measurable effect on minicell performance, (3) imperfection such as electrolyte abrasion, scratch, and pop out cause minicell potential to fluctuate by different degrees; the cells with such imperfections exhibit sensitivity of potential to high fuel utilization and “self healing” behavior. On single cell level we evaluated the effect of long crack and high population pinholes. The cell with a long crack does not show performance compromise at start. There is no potential fluctuation or sensitivity to high fuel utilization or catastrophic failure. The voltage degradation due to thermal cycle is slightly higher than normal cells. The cells with high population pinholes perform surprisingly as well as normal cells over a period of 3,500h. Even when subjected to cyclic load condition, the cells 4 show negligible degradation. Our cells appear to have “self immunization” feature which fends off the adversary effects of certain imperfections. Defects were also evaluated on stack level. Two stacks were made each with ten defect cells. The first stack was tested for 13,2000h under steady load condition while the second was tested for 9,000h under transient load conditions. We found: (1) voltage fluctuation and sensitivity to thermal cycle were not observed in contrast to minicell test, (2) of the various cracks examined, including longitudinal cracks, circumferential crack, crack near closed and open ends, none exhibited distinguishable impact on performance, (3) defect cells exhibited higher degradation rates on average under steady load condition; Individually some defect cells performed similarly or better than reference cells, (4) under steady load condition all the cells degrade monotonically with degradation rate increasing with time, (5) under cyclic (transient) load condition, both defect and reference cells exhibit complex dynamic behaviors, (6) fuel loss (leak) was measured occasionally for stack 1, the cells with crack showed the highest fuel loss increase, nevertheless, no correlation with performance degradation could be established with certainty, and (7) no catastrophic failure ever happened other than incremental degradation. Posttest inspection and microanalysis were carried out; the observations are summarized in what follows: (1) Electrolyte pinholes, some scratches and IC porosity became undetectable after testing. (2) The cathode covering the popout defects is intact without any cracking or delamination. (3) The scratch was covered by cathode in pristine state; Ni oxide or NiO-YSZ filled the space where electrolyte was missing. After >10,000h operation, the cathode that used to cover the scratch was missing but the size of the scratch remains unchanged; there is a fairly dense Ni oxide layer on top of the scratch. (4) All of the cracks remain their original dimensions. Current collector kept longitudinal cracks closed which mitigated the adversary effect of crack on cell performance/durability. (5) The crack at open end showed some deterioration manifested by a small oxidation zone in the vicinity of the crack. Wide spectrum of imaging techniques were surveyed and evaluated to detect tubular SOFC defects. Optical methods, with and without assistance of expression technique, were applied to detect all kinds of defects. Thermograph method in combination of CO2 leak, ultra-sound and electric potential was also extensively evaluated to detect surface and under-surface defects such as short circuit. Based on these works, laser camera has been selected to build the final QC machine vision inspection system. The Gocator laser profile sensor was setup to generate 2D surface intensity images of tubular SOFC surface which were analyzed with Sherlock machine vision software supplied by Teledyne Dalsa. The Gocator output was integrated with the Sherlock software and enabled live images to be imported by a Common Vision Blox driver. The Sherlock software was programmed to detect various surface defects from the surface intensity images generated by the Gocator. These measurements are subsequently used to make pass or fail decisions.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Discovery of correlated electron molecular orbital materials using graph representations

Correlated electron molecular orbital (CEMO) materials host emergent electronic states built from molecular orbitals localized over clusters of transition metal ions yet have historically been discovered sporadically and generally been treated as isolated case studies. Here we establish CEMO materials as a systematically discoverable class and introduce a graph-based framework to identify, classify, and organize transition-metal cluster motifs in inorganic solids. Starting from crystal structures in the Materials Project, we construct transition metal connectivity graphs, extract cluster motifs using a bond-cutting algorithm, and determine cluster point groups, effective cluster sublattice dimensionality, and translational symmetry. Applying this approach in a high-throughput screen of 34,548 compounds yields 5,306 cluster-containing materials, including 2,627 stable or metastable compounds with isolated clusters and 984 materials featuring mixed-metal clusters. The resulting dataset reveals symmetry and element dependent trends in cluster formation. By integrating cluster classification with flat band lattice topology and battery-relevant information, we provide further relevant information to multiple scientific communities. The accompanying open dataset, Cluster Finder software, and interactive web platform enable systematic exploration of cluster driven electronic phenomena and establish a general pathway for discovering correlated quantum materials and functional materials with cluster-based or extended metal-metal bonding in inorganic solids.

Akhond, Md. Rajbanul [Department of Chemistry, 800↗