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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 OSTI2017

Functional analysis of the cfdp1 gene in zebrafish provides evidence for its crucial role in craniofacial development and osteogenesis

Highlights: • The zebrafish cfdp1 gene maps to chromosome 8 and is 2222 bp long with seven exons and six introns. • The cfdp1 gene is highly expressed since very early embryonic stages until the completion of organogenesis. • The zebrafish CFDP1 protein is highly abundant in the head structures. • CFDP1 is an essential protein that actively participates to the correct definition and morphogenesis of craniofacial territories in the zebrafish model system. The CFDP1 proteins have been linked to craniofacial development and osteogenesis in vertebrates, though specific human syndromes have not yet been identified. Alterations of craniofacial development represent the main cause of infant disability and mortality in humans. For this reason, it is crucial to understand the cellular functions and mechanism of action of the CFDP1 protein in model vertebrate organisms. Using a combination of genomic, molecular and cell biology approaches, we have performed a functional analysis of the cfdp1 gene and its encoded protein, zCFDP1, in the zebrafish model system. We found that zCFDP1 is present in the zygote, is rapidly produced after MTZ transition and is highly abundant in the head structures. Depletion of zCFDP1, induced by an ATG-blocking morpholino, produces considerable defects in craniofacial structures and bone mineralization. Together, our results show that zCFDP1 is an essential protein required for proper development and provide the first experimental evidence showing that in vertebrates it actively participates to the morphogenesis of craniofacial territories.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Light-Driven Iodine Loss and Photoluminescence Homogenization in Mixed-Halide Perovskite Semiconductors

Carrier-induced instabilities in lead halide perovskites are often investigated as either transient phenomena, e.g., photoinduced halide segregation or permanent performance changes, e.g., photodegradation, while the mechanistic links between them remain unclear. Here, we aim to connect these observations by studying a model mixed-halide system, MAPb(Br x I 1–x ) 3 . By combining grazing-incidence X-ray diffraction, photothermal deflection spectroscopy, and photoluminescence measurements with hyperspectral microscopy, we investigate the role of mobile halide defects and local chemistry on reversible and long-term instabilities in these materials. Our results show that mixed-halide perovskites are uniquely susceptible to photoinduced changes with illumination driving initial iodide redistribution (i.e., halide segregation), eventual selective iodine expulsion, and subsequent changes in photoinduced halide segregation behavior. By quantifying structural and compositional changes, we estimate an approximately 3–5% iodine loss in our mixed-halide samples after only 24 h of illumination. Further, using microscale measurements, we identify pre-existing iodide-rich domains as key contributors to both the observed transient photostability and permanent iodine loss in MAPbBrI 2 , and see evidence that extended light soaking results in iodide redistribution that improves optoelectronic homogeneity. Overall, our results emphasize the importance of carrier-induced halide oxidation in creating a dynamic defect landscape in mixed-halide perovskites and provide a framework for interpreting apparent light-driven changes in optoelectronic behavior through the lens of permanent compositional changes.

electrical conductivity↗
DOE OSTI2017

Meeting report: a hard look at the state of enamel research

Enamel is a principal component of the dentition, and defects in this hard tissue are associated with a wide variety of diseases. To assess the state of the field of enamel research, the National Institute of Dental and Craniofacial Research (NIDCR) convened the “Encouraging Novel Amelogenesis Models and Ex vivo cell Lines (ENAMEL) Development” workshop at its Bethesda headquarters on 23 June 2017. Enamel formation involves complex developmental stages and cellular differentiation mechanisms that are summarized in Figure 1. The meeting, which was organized by Jason Wan from NIDCR, had three sessions: model organisms, stem cells/cell lines, and tissues/ 3D cell culture/organoids. In attendance were investigators interested in enamel from a broad range of disciplines as well as NIDCR leadership and staff. The meeting brought together developmental biologists, cell biologists, human geneticists, materials scientists, and clinical researchers from across the United States to discuss recent progress and future challenges in our understanding of the formation and function of enamel. Lively discussions took place throughout the day, and this meeting report highlights some of the major findings and ideas that emerged during the workshop.

ameloblast↗
DOE OSTI2019

Computational description of key spectroscopic features of zeolite SSZ-13

The catalytic properties of zeolites are intimately linked to the distribution and relative positions of Al atoms and defects in the pore network. However, characterizing this distribution is challenging, in particular when different local Al arrangements are considered. In this contribution we use a combination of first principles calculations and experimental measurements to develop a model for the Al-distribution in protonated SSZ-13. We furthermore apply this model to understand trends in OH-IR, 27 Al-NMR and 29 Si-NMR spectra. We use a Boltzmann distribution to predict the proton position for a given local Al configuration and demonstrate that for each configuration several H positions are occupied. Therefore a multi-peak spectrum in OH-IR vibrational spectroscopy is observed for all Al configurations, which is in line with experimentally measured spectra for zeolites at different Si/Al ratios. From NMR spectroscopy we find that the proton position leads to significant shifts in 27 Al-NMR and 29 Si-NMR spectra due to the modification of the local strain, which is lost when a uniform background charge is introduced. These findings are supported by experimental measurements. Finally we discuss the shortcomings of the presented model in terms of unit cell size and the impact of adjacent unit cells.

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

Assessing the roles of Cu- and Ag-deficient layers in chalcopyrite-based solar cells through first principles calculations

Chalcopyrites are a demonstrated material platform for realizing efficient thin-film photovoltaics, with the most well known Cu(In,Ga)Se 2 (CIGS)-based solar cells exceeding 23%. Several factors, including flexibility in tuning the absorber bandgap, enhanced surface treatments, and the electrically benign nature of common defects are responsible for the existing high performance and future promise in chalcopyrite-based photovoltaic devices. The introduction of Cu-poor phases (also known as ordered-vacancy compounds or OVCs) between the absorber and buffer layers in CIGS solar cells is known to enhance device performance; however, the overall properties and role of OVCs remain poorly understood. Using first principles calculations based on the density functional theory with screened hybrid functionals, here we explore the electronic structure and stability of OVCs and their band offsets with defect-free chalcopyrite layers in Cu- and Ag-based compounds (ABX 2 where A=Cu, Ag; B=In, Ga, Al; and X=S, Se). Using AB 3 X 5 and AB 5 X 8 stoichiometries as model OVC systems, we report on the variation of the bandgap with the A/B ratio and discuss the trends in other Cu- and Ag-based chalcopyrites beyond CuInSe 2 . We find that the valence and conduction bands are lower in energy in OVCs with respect to the parent ABX 2 chalcopyrite owing to a reduced p–d interaction between X and A atoms. We additionally perform device-level simulations to assess the implications of the results, finding that the valence band offsets of OVCs are favorable, while the conduction band offsets of chalcopyrites beyond CuInSe 2 -based absorbers may be detrimental in conventional solar cell device designs.

14 SOLAR ENERGY↗
DOE OSTI2017

Covalently linked HslU hexamers support a probabilistic mechanism that links ATP hydrolysis to protein unfolding and translocation

The HslUV proteolytic machine consists of HslV, a double-ring self-compartmentalized peptidase, and one or two AAA+ HslU ring hexamers that hydrolyze ATP to power the unfolding of protein substrates and their translocation into the proteolytic chamber of HslV. Furthermore, we use genetic tethering and disulfide bonding strategies to construct HslU pseudohexamers containing mixtures of ATPase active and inactive subunits at defined positions in the hexameric ring. Genetic tethering impairs HslV binding and degradation, even for pseudohexamers with six active subunits, but disulfide-linked pseudohexamers do not have these defects, indicating that the peptide tether interferes with HslV interactions. Importantly, pseudohexamers containing different patterns of hydrolytically active and inactive subunits retain the ability to unfold protein substrates and/or collaborate with HslV in their degradation, supporting a model in which ATP hydrolysis and linked mechanical function in the HslU ring operate by a probabilistic mechanism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Voltage-Induced Charge Redistribution in Cu(In,Ga)Se 2 Devices Studied With High-Speed Capacitance–Voltage Profiling

Devices made from Cu(In, Ga)Se 2 (CIGS) solar cell material have been evaluated with high-speed capacitance-voltage profiling after stepwise voltage changes. The changes primarily affect near-interface charge at deep acceptors within the CIGS absorber layer and generate temperature-dependent capacitance changes observed in deep-level transient spectroscopy measurements. SCAPS device modeling indicates that the deep acceptor concentration is up to the two orders of magnitude higher than the shallow doping level. High deep acceptor concentrations are found in all materials studied here. In conclusion, the large deep defect levels are high enough to limit minority carrier lifetime and cell efficiency.

14 SOLAR ENERGY↗
DOE OSTI2019

Role of Caulobacter Cell Surface Structures in Colonization of the Air-Liquid Interface

In aquatic environments, Caulobacter spp. can be found at the boundary between liquid and air known as the neuston. I report an approach to study temporal features of Caulobacter crescentus colonization and pellicle biofilm development at the air-liquid interface and have defined the role of cell surface structures in this process. At this interface, C. crescentus initially forms a monolayer of cells bearing a surface adhesin known as the holdfast. When excised from the liquid surface, this monolayer strongly adheres to glass. The monolayer subsequently develops into a three-dimensional structure that is highly enriched in clusters of stalked cells known as rosettes. As this pellicle film matures, it becomes more cohesive and less adherent to a glass surface. A mutant strain lacking a flagellum does not efficiently reach the surface, and strains lacking type IV pili exhibit defects in organization of the three-dimensional pellicle. Strains unable to synthesize the holdfast fail to accumulate at the boundary between air and liquid and do not form a pellicle. Phase-contrast images support a model whereby the holdfast functions to trap C. crescentus cells at the air-liquid boundary. Unlike the holdfast, neither the flagellum nor type IV pili are required for C. crescentus to partition to the air-liquid interface. While it is well established that the holdfast enables adherence to solid surfaces, this study provides evidence that the holdfast has physicochemical properties that allow partitioning of nonmotile mother cells to the air-liquid interface and facilitate colonization of this microenvironment. In aquatic environments, the boundary at the air interface is often highly enriched with nutrients and oxygen. Colonization of this niche likely confers a significant fitness advantage in many cases. This study provides evidence that the cell surface adhesin known as a holdfast enables Caulobacter crescentus to partition to and colonize the air-liquid interface. Additional surface structures, including the flagellum and type IV pili, are important determinants of colonization and biofilm formation at this boundary. Considering that holdfast-like adhesins are broadly conserved in Caulobacter spp. and other members of the diverse class Alphaproteobacteria , these surface structures may function broadly to facilitate colonization of air-liquid boundaries in a range of ecological contexts, including freshwater, marine, and soil ecosystems

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Calculation of the Influence of the Ion Current Density and Temperature on the Accumulation Kinetics of Point Defects under the Irradiation of Si with Light Ions

Numerical calculations of the accumulation kinetics of point defects—vacancies and divacancies—under the irradiation of Si with ions having masses of M{sub 1} ≤ 31 amu and energies of E ≤ 100 keV under various irradiation conditions are performed. The previously proposed diffusion-coagulation model is used without application of the “weak diffusion” approximation, which was performed during its analytical implementation. The main peculiarities of the dependences of the concentrations of vacancies and divacancies on the dose, ion-current density, and temperature under irradiation are analyzed. A physical interpretation of these results is given. The developed computing complex is rather flexible and makes it possible to analyze the influence of model input parameters by means of their variation and include additional processes into consideration if necessary.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Defects in the Expression of Chloroplast Proteins Leads to H2O2 Accumulation and Activation of Cyclic Electron Flow around Photosystem I

We describe a new member of the class of mutants in Arabidopsis exhibiting high rates of cyclic electron flow around photosystem I (CEF), a light-driven process that produces ATP but not NADPH. High cyclic electron flow 2 (hcef2) shows strongly increased CEF activity through the NADPH dehydrogenase complex (NDH), accompanied by increases in thylakoid proton motive force (pmf), activation of the photoprotective qE response, and the accumulation of H 2 O 2 . Surprisingly, hcef2 was mapped to a nonsense mutation in the TADA1 (tRNA adenosine deaminase arginine) locus, coding for a plastid targeted tRNA editing enzyme required for efficient codon recognition. Comparison of protein content from representative thylakoid complexes, the cytochrome bf complex and the ATP synthase, suggests that inefficient translation of hcef2 leads to compromised complex assembly or stability leading to alterations in stoichiometries of major thylakoid complexes as well as their constituent subunits. Altered subunit stoichiometries for photosystem I, ratios and properties of cytochrome bf hemes, and the decay kinetics of the flash induced thylakoid electric field suggest that these defect lead to accumulation of H 2 O 2 in hcef2, which we have previously shown leads to activation of NDHrelated CEF. We observed similar increases in CEF and H 2 O 2 accumulation in other translation defective mutants, suggesting that loss of coordination in plastid protein levels lead to imbalances in the photosynthetic energy balance that leads to increased CEF. These results, together with a large body of previous observations, support a general model in which processes that imbalances in chloroplast energetics result in the production of H 2 O 2 , which activates CEF, either as a redox signal or by inducing deficits in ATP levels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Degradation Mechanisms in TOPCon/POLO Solar Cells

This presentation shows how Poly-Si/SiO2 contacts show a post firing degradation/regeneration cycle. The following conclusions were made: 1) cycle changes surface passivation (Jo), but not the bulk lifetime; 2) cycle time depends on anneal temperature in light or dark (higher T, faster cycle); 3) 400 degrees Celsius anneal eliminates the cycle - only generation occurs; 4) cycle time and magnitude is not correlated with Tfire; 5) contact passivation is stable after cycling; 6) fundamental nature of defect(s) responsible is not known; 7) TOPCon cells/modules, if constructed well, seem to show minimal degradation issues (PVEL, Jolywood, Jinko, ET Solar), and 8) NREL/ASU are studying TOPCon cells and UC Davis has a molecular dynamics model for TOPCon.

degradation↗
DOE OSTI2024

Structural and thermal properties and the origin of the ultralow thermal conductivity in the defect stannite CuIn 2 Se 4

Phase-pure CuIn 2 Se 4 , a ternary metal chalcogenide that forms in a disordered stannite crystal structure, was synthesized to investigate the structure thermal property relationships as well as reveal the origin of the ultralow thermal conductivity this material possesses over a large temperature range. Modeling of the temperature-dependent heat capacity and thermal conductivity revealed distinctive thermal properties and large lattice anharmonicity. Electron localization function calculations highlight the asymmetric bonding inherent to CuIn 2 Se 4 , which together with lattice anharmonicity directly impacts the thermal properties. Our findings reveal the specific atomic arrangement and bonding governing the thermal properties of this ternary metal chalcogenide. Our findings underscore the specific atomic arrangement and bonding governing the thermal properties in this ternary chalcogenide. This study advances the fundamental understanding of stannites, and our findings can be applied to these and other multinary metal chalcogenides of interest for applications where low thermal conductivity is desirable.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Thermal transport in defective and disordered materials

With significant recent advancements in thermal sciences—such as the development of new theoretical and experimental techniques, and the discovery of new transport mechanisms—it is helpful to revisit the fundamentals of vibrational heat conduction to formulate an updated and informed physical understanding. The increasing maturity of simulation and modeling methods sparks the desire to leverage these techniques to rapidly improve and develop technology through digital engineering and multi-scale, electro-thermal models. With that vision in mind, this review attempts to build a holistic understanding of thermal transport by focusing on the often unaddressed relationships between subfields, which can be critical for multi-scale modeling approaches. For example, we outline the relationship between mode-specific (computational) and spectral (analytical) models. We relate thermal boundary resistance models based on perturbation approaches and classic transmissivity based models. We discuss the relationship between lattice dynamics and molecular dynamics approaches along with two-channel transport frameworks that have emerged recently and that connect crystal-like and amorphous-like heat conduction. Throughout, we discuss best practices for modeling experimental data and outline how these models can guide material-level and system-level design.

42 ENGINEERING↗
DOE OSTI2024

Towards in-situ certification of additively manufactured parts: the vital roles of physics-based and data-driven models

Certifying additively manufactured (AM) parts in-situ at the completion of a build is an enticing prospect, as it can help reduce the high costs associated with post-build testing and evaluation. However, achieving this goal presents significant challenges that may keep it aspirational for the foreseeable future. Nonetheless, incremental progress can pave the way forward. A critical aspect of in-situ certification involves continuous quality checking due to the random nature of the AM process and the difficulties in detecting defects or anomalies once layers are built over. While real-time in-situ monitoring strategies assisted by machine learning (ML) play a pivotal role in auditing part quality, they must ideally be supported by real-time (or near real-time) adaptive process control enabled by ML-assisted decision-making. By analyzing in-situ monitoring data in real-time (or near real- time) to dynamically adjust manufacturing parameters, such intervention can ensure AM parts are built to meet stringent certification standards. This can be achieved virtually by using high-fidelity performance models for the physical testing and evaluation tasks. In this short editorial, we discuss the key contributions made by data-driven and physics-based models in providing intelligence to the monitoring and process control tasks underpinning in-situ certification and in the simulation of the build’s performance under test and service conditions. While our focus lies in metal AM, the concepts discussed here are also relevant to other AM processes.

: In-situ monitoring↗
DOE OSTI2016

Ab Initio Study of Carbon Impurities in Cu$_2$ ZnSnS$_4$

Cu 2 ZnSnS 4 (CZTS) is a highly promising absorber material for efficient and low-cost solar cells. In a cost-effective method of production of high-quality CZTS, nanocrystals of precursor compounds, solved in an amine solution, are deposited on a substrate and sulfurized. Here, this can generally lead to considerable residual carbon in the final samples, in the form of separate amorphous layers as observed experimentally, but also incorporated in the CZTS matrix. In this study, preferred configurations, bonding characteristics, formation energies, and ionization levels of carbon-related defects in CZTS are calculated, including interstitials, single- and double-carbon antisites, and complexes of those with intrinsic defects. For different growth conditions of carbon, the set of dominant defects is determined, and the resulting total carbon concentrations are discussed with respect to experimental values.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Solid-state platform for cooperative quantum dynamics driven by correlated emission

While traditionally regarded as an obstacle to quantum coherence, recent breakthroughs in quantum optics have shown that the dissipative interaction of a qubit with its environment can be leveraged to protect quantum states and synthesize many-body entanglement. Inspired by this progress, here we set the stage for the—as yet uncharted—exploration of analogous cooperative phenomena in hybrid solid-state platforms. We develop a comprehensive formalism for the quantum many-body dynamics of an ensemble of solid-state spin defects interacting with the magnetic field fluctuations of a common solid-state reservoir. Our framework applies to any solid-state reservoir whose fluctuating spin, pseudospin, or charge degrees of freedom generate magnetic fields. To understand whether correlations induced by dissipative processes can play a relevant role in a realistic experimental setup, we apply our model to a qubit array interacting via the spin fluctuations of a ferromagnetic bath. Our results show that the low-temperature collective relaxation rates of the qubit ensemble can display clear signatures of super- and subradiance, i.e., forms of cooperative dynamics traditionally achieved in atomic ensembles. We find that the solid-state analog of these cooperative phenomena is robust against spatial disorder in the qubit ensemble and thermal fluctuations of the magnetic reservoir, providing a route for their feasibility in near-term experiments. Finally, our work lays the foundation for a multiqubit approach to quantum sensing of solid-state systems and the direct generation of many-body entanglement in spin-defect ensembles. Furthermore, we discuss how the tunability of solid-state reservoirs opens up novel pathways for exploring cooperative phenomena in regimes beyond the reach of conventional quantum optics setups.

NV centers↗
DOE OSTI2024

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗