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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 OSTI2025

Extreme flood return levels in a U.S. mid-Atlantic estuary using 40-year fluvial-coastal model simulations

Using an integrated watershed-coastal modeling framework, we conducted long-term historical simulations (1980-2019) of fluvial and coastal flooding in the Delaware Bay and River, a vulnerable estuarine system in the U.S., at high spatial resolutions. By applying process-based models, we generated physically consistent and spatially detailed estimates of estuarine, riverine, and surge-driven extreme water level compared to previous studies that used field data only. We then evaluated changes in the magnitude of flood events using the 40-year simulations and detrended Floodwater Depth values with stationary extreme value analysis. Our detailed assessment of spatial-varying extreme values revealed how different flood-generation mechanisms can dominate various zones in the estuary. The datasets produced through this work will be valuable for long-term flood hazard mitigation planning in coastal communities in the Delaware Bay and River region. Additionally, this work will serve as a benchmark for other coastal flood hazard modeling communities worldwide, aiding them in systematically modeling long-term and continuous extreme flood events.

Coastal and Riverine Flooding↗
DOE OSTI2023

Multiquanta flux jumps in superconducting fractal

We study the magnetic field response of millimeter scale fractal Sierpinski gaskets (SG) assembled of superconducting equilateral triangular patches. Directly imaged quantitative induction maps reveal hierarchical periodic filling of enclosed void areas with multiquanta magnetic flux, which jumps inside the voids in repeating bundles of individual flux quanta Φ 0 . The number N s of entering flux quanta in different triangular voids of the SG is proportional to the linear size s of the void, while the field periodicity of flux jumps varies as 1/s. We explain this behavior by modeling the triangular voids in the SG with effective superconducting rings and by calculating their response following the London analysis of persistent currents, J s , induced by the applied field H a and by the entering flux. With changing H a , J s reaches a critical value in the vertex joints that connect the triangular superconducting patches and allows the giant flux jumps into the SG voids through phase slips or multiple Abrikosov vortex transfer across the vertices. The unique flux behavior in superconducting SG patterns, may be used to design tunable low-loss resonators with multi-line high-frequency spectrum for microwave technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A general synthesis of single atom catalysts with controllable atomic and mesoporous structures

The control of single metal atomic sites has been extensively studied in the field of single atom catalysts. By contrast, the precise control of the mesoporous structure in the matrix material, which directly correlates with mass diffusions and may play a dominant role in delivering industrially relevant reaction rates, has been overlooked. In this work, we report a general method for the synthesis of a single atom catalyst with control of the atomic structure of the single atomic site as well as the mesoporous structure of the carbon support for optimized catalytic performance. Various combinations of metal centres (Ni, Co, Mn, Zn, Cu, Sc and Fe) and mass diffusion channels in two dimensions and three dimensions were achieved. Using CO 2 reduction to CO as an example, our Ni single atom catalyst with three-dimensional diffusion channels delivered a practical current of 350 mA cm –2 while maintaining a 93% CO Faradaic efficiency, representing a sixfold improvement in turnover frequency compared to two-dimensional counterparts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Wetting behavior of polyelectrolyte complex coacervates on solid surfaces

The wetting behavior of complex coacervates underpins their use in many emerging applications of surface science, particularly wet adhesives and coatings. Many factors dictate if a coacervate phase will condense on a solid surface, including solution conditions, the nature of the polymer–substrate interaction, and the underlying supernatant–coacervate bulk phase behavior. In this work, we use a simple inhomogeneous mean-field theory to study the wetting behavior of complex coacervates on solid surfaces both off-coexistence (wetting transitions) and on-coexistence (contact angles). Here we focus on the effects of salt concentration, the polycation/polyanion surface affinity, and the applied electrostatic potential on the wettability. We find that the coacervate generally wets the surface via a first order wetting transition with second order transitions possible above a surface critical point. Applying an electrostatic potential to a solid surface always improves the surface wettability when the polycation/polyanion–substrate interaction is symmetric. For asymmetric surface affinity, the wettability has a nonmonotonic dependence with the applied potential. We use simple scaling and thermodynamic arguments to explain our results.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine learning for design principles for single atom catalysts towards electrochemical reactions

Machine learning (ML) integrated density functional theory (DFT) calculations have recently been used to accelerate the design and discovery of heterogeneous catalysts such as single atom catalysts (SACs) through the establishment of deep structure–activity relationships. Here, this review provides recent progress in the ML-aided rational design of heterogeneous catalysts with the focus on SACs in terms of structure–activity relationships, feature importance analysis, high-throughput screening, stability, and metal–support interactions for electrochemistry. Support vector machine (SVM), random forest regression (RFR), and deep neural networks (DNN) along with atomic properties are mainly used for the design of SACs. The ML results have shown that the number of electrons in the d orbital, oxide formation enthalpy, ionization energy, Bader charge, d-band center, and enthalpy of vaporization are mainly the most important parameters for the defining of the structure–activity relationships for electrochemistry. However, the black-box nature of ML techniques occasionally makes a physical interpretation of descriptors, such as the Bader charge, d-band center, and enthalpy of vaporization, non-trivial. At the current stage, ML application is limited by the lack of a large and high-quality database. Future prospects for the development of a large database and a generalized ML algorithm for SAC design are discussed to give insights for further studies in this field.

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

Chemical characterization of microplastic particles formed in airborne waste discharged from sewer pipe repairs

Microplastic particles are of increasing environmental concern due to the widespread uncontrolled degradation of various commercial products made of plastic and their associated waste disposal. Recently, common technology used to repair sewer pipes was reported as one of the emission sources of airborne microplastics in urban areas. This research presents results of the multi-modal comprehensive chemical characterization of the microplastic particles related to waste discharged in the pipe repair process and compares particle composition with the components of uncured resin and cured plastic composite used in the process. Analysis of these materials employs complementary use of surface-enhanced Raman spectroscopy, scanning transmission X-ray spectro-microscopy, single particle mass spectrometry, and direct analysis in real-time high-resolution mass spectrometry. Further, it is shown that the composition of the relatively large (100 μm) microplastic particles resembles components of plastic material used in the process. In contrast, the composition of the smaller (micrometer and sub-micrometer) particles is significantly different, suggesting their formation from unintended polymerization of water-soluble components occurring in drying droplets of the air-discharged waste. In addition, resin material type influences the composition of released microplastic particles. Results are further discussed to guide the detection and advanced characterization of airborne microplastics in future field and laboratory studies pertaining to sewer pipe repair technology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A single-ion-conducting polymer and high-entropy Li-garnet composite electrolyte with simultaneous enhancement in ion transport and mechanical properties

Enabling the lithium metal anode has been the holy grail for improving the energy density for the next generation advanced batteries. Developing electrolytes that will suppress Li dendrite growth and provide sufficient ionic conductivity remains a major challenge in this field. In this study, we develop a polymer–ceramic composite electrolyte for lithium metal batteries. The polymer matrix is a vinyl ethylene carbonate (VEC) based single-ion-conducting polymer electrolyte. The ceramic filler is a Li 7 La 3 Zr 0.5 Nb 0.5 Ta 0.5 Hf 0.5 O 12 high-entropy Li-garnet (HE Li-garnet) ceramic, which is less prone to surface Li 2 CO 3 formation compared to Al-doped Li garnets. The addition of HE Li-garnet leads to a 7-fold increase in the ionic conductivity (8.6 × 10 −5 S cm −1 at 30 °C) compared to the pure polymer, while maintaining a high Li + transference of 0.73. Proton nuclear magnetic resonance and thermogravimetric analysis results suggest that the addition of HE Li-garnet results in a lower degree of polymerization of VEC, leaving more unpolymerized VEC monomers in the matrix, serving as the governing mechanism for conductivity enhancement. The favorable interactions between HE Li-garnet particles and the polymer matrix lead to a stable and well-mixed composite with 2-fold enhancement of storage modulus at 40 °C. The simultaneous ion transport and mechanical property enhancement significantly improves the composite electrolyte's dendrite resistance and cycle life in Li symmetric cells. This work highlights the positive role HE Li-garnet can play in improving polymer electrolytes to enable lithium metal anodes.

Ock, Ji-young [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2022

Plant immunity: Rice XA21-mediated resistance to bacterial infection

Significance The mechanisms plants employ to resist infection were unknown until just a few decades ago. We now understand that plants utilize diverse classes of immune receptors to recognize and respond to pathogenic microbes and pests. This paper describes the development of the plant immunity field, from early studies on the genetics of disease resistance to our increasing knowledge of how plant receptors interact with their microbial ligands, with an emphasis on the rice immune receptor XA21 and its bacterial ligand.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Climate change–induced stress disrupts ectomycorrhizal interaction networks at the boreal–temperate ecotone

The interaction networks formed by ectomycorrhizal fungi (EMF) and their tree hosts, which are important to both forest recruitment and ecosystem carbon and nutrient retention, may be particularly susceptible to climate change at the boreal–temperate forest ecotone where environmental conditions are changing rapidly. Here, we quantified the compositional and functional trait responses of EMF communities and their interaction networks with two boreal ( Pinus banksiana and Betula papyrifera ) and two temperate ( Pinus strobus and Quercus macrocarpa ) hosts to a factorial combination of experimentally elevated temperatures and reduced rainfall in a long-term open-air field experiment. The study was conducted at the B4WarmED (Boreal Forest Warming at an Ecotone in Danger) experiment in Minnesota, USA, where infrared lamps and buried heating cables elevate temperatures (ambient, +3.1 °C) and rain-out shelters reduce growing season precipitation (ambient, ~30% reduction). EMF communities were characterized and interaction networks inferred from metabarcoding of fungal-colonized root tips. Warming and rainfall reduction significantly altered EMF community composition, leading to an increase in the relative abundance of EMF with contact-short distance exploration types. These compositional changes, which likely limited the capacity for mycelial connections between trees, corresponded with shifts from highly redundant EMF interaction networks under ambient conditions to less redundant (more specialized) networks. Further, the observed changes in EMF communities and interaction networks were correlated with changes in soil moisture and host photosynthesis. Collectively, these results indicate that the projected changes in climate will likely lead to significant shifts in the traits, structure, and integrity of EMF communities as well as their interaction networks in forest ecosystems at the boreal–temperate ecotone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Pressure Response Optimization of an Eddy Current-Driven Flyer Plate Valve for the ITER Shattered Pellet Injection System

One technique for mitigating disruptions in a tokamak is shattered pellet injection (SPI). SPI is a process in which a large solid pellet consisting of deuterium, neon, or argon is desublimated in a pipe gun barsrel and launched downstream. Pellets are shattered just before entering the plasma by an impact with an angled tube. Injection of these materials into the plasma radiates stored thermal energy, limits current decay rates, suppresses the generation of runaway electrons, and dissipates runaway electrons if necessary. A critical element of the SPI system is a fast-acting valve that releases high-pressure gas to dislodge and accelerate pellets directly, or indirectly via a mechanical punch. A prototype valve sized for the ITER SPI system has been designed and fabricated. A pulsed high-voltage power supply energizes the valve’s internal magnetic coil, which induces eddy currents in the adjacent flyer plate resulting in a repulsive force between the flyer plate and the coil. The flyer plate action lifts a valve seat, allowing high-pressure gas to flow from the valve plenum to the downstream (breech) location of the pellet or mechanical punch. All of the valve’s internal components are designed to operate in ITER-level static background magnetic fields. Here, a study was conducted to optimize the downstream pressure response for a range of valve sizes and operating pressures. In particular, the study analyzes the breech pressure response associated with varying plenum pressures as well as varying breech volumes. A computational fluid dynamics simulation was built in STAR-CCM+ and validated against data from laboratory experiments. The resulting simulation outputs, in the form of downstream responses for a variety of initial plenum pressures and breech volumes, will be used as a complement to experimental data to ensure the pressure pulse is suitable for pellet survivability. These data, combined with studies on pellet shear strength and shock response, will be applied to optimization of overall operating parameters of the ITER SPI system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Skyrmion–skyrmion interaction in a magnetic film

Interaction of two skyrmions stabilized by the ferromagnetic exchange, Dzyaloshinskii–Moriya interaction (DMI), and external magnetic field has been studied numerically on a 2D lattice of size large compared to the separation, d, between the skyrmions. We show that two skyrmions of the same chirality (determined by the symmetry of the crystal) repel. In accordance with earlier analytical results, their long-range pair interaction falls out with the separation as exp(-d/δ H ), where δ H is the magnetic screening length, independent of the DMI. The prefactor in this expression depends on the DMI that drives the repulsion. The latter results in the spiral motion of the two skyrmions around each other, with the separation between them growing logarithmically with time. When two skyrmions of the total topological charge Q = 2 are pushed close to each other, the discreteness of the atomic lattice makes them collapse into one skyrmion of charge Q = 1 below a critical separation. Experiment is proposed that would allow one to measure the interaction between two skyrmions by holding them in positions with two magnetic tips. Our findings should be of value for designing topologically protected magnetic memory based upon skyrmions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Solidification dynamics in metal additive manufacturing: analysis of model assumptions

Solidification characteristics in the meltpool drive the process-microstructure relationship which helps dictate the material properties of as-built parts in additive manufacturing; therefore, being able to accurately and quickly simulate the size, shape, and solidification characteristics in the melt pool is of great interest to the field. In this study, we investigate various important physical phenomena (dynamic material properties, fluid-flow, radiation and vaporization) which can either be included or neglected in a continuum finite volume model (FVM) and their effect on the solidification conditions. Additionally, since the simplest form of such a model (conduction only) has an analytic solution which is much faster, its viability is also considered. Since the inclusion of some of these physical phenomena will inherently change the net energy input as well as the amount of energy needed to achieve melting of a control volume, each set of included phenomena had an effective absorption efficiency which was calibrated to closely match the dimensions of the melt pool to that of the ground truth data. The ground truth data for this study was defined to be the output of the FVM which included all the physical phenomena (OF). This study then goes on to compare the effects on solidification conditions each of these calibrated models has. It was found that most of the change in solidification conditions comes from the inclusion of latent heat. A posterior correlation factor (PCF) is then introduced to enable an analytic model to predict similar solidification conditions to OF model.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tunable phase-change metasurfaces coupled with mid-infrared molecular vibrations

Chiral optical metasurfaces have emerged as a promising platform in coupling with molecular vibrational fingerprints through the enhanced light-matter interaction under different circularly polarized light illumination. Here, this work reports the mode coupling between the mid-infrared phonon vibrations of polymethyl methacrylate (PMMA) molecules and the thermally tunable chiral metasurfaces based on the phase-change material Ge₂Sb₂Te₅ (GST-225). Phase-change chiral metasurfaces with high circular dichroism (CD) in absorption and tunable plasmonic resonance in the frequency range of 48–56 THz are demonstrated, which covers the phonon vibrational frequency of PMMA molecules at 52 THz. The mode splitting features are observed in the absorption and CD spectra when the metasurface resonance is tuned across the phonon vibrational frequency of PMMA molecules during the phase transition of GST-225. The underlying mechanism of molecule-metasurface coupling is further revealed by studying the electric field and power loss density distributions of the phonon–plasmon coupled modes under both left-handed and right-handed circularly polarized (LCP and RCP) light. The demonstrated results show the potential of dynamically tunable chiral metasurfaces for the applications in label-free molecular sensing, biomedical diagnostics, thermal imaging, and mid-infrared photonics.

Tang, Haotian [Missouri Univ. of Science and Techn↗
DOE OSTI2020

Machine learning enabled discovery of application dependent design principles for two-dimensional materials

Abstract The unique electronic and mechanical properties of two-dimensional (2D) materials make them promising next-generation candidates for a variety of applications. Large-scale searches for high-performing 2D materials are limited to calculating descriptors with computationally demanding first-principles density functional theory. In this work, we alleviate this issue by extending and generalizing crystal graph convolutional neural networks to systems with planar periodicity and train an ensemble of models to predict thermodynamic, mechanical and electronic properties. We carry out a screening of nearly 45,000 structures for two separate applications: mechanical strength and photovoltaics. By collecting statistics of the screened candidates, we investigate structural and compositional design principles that impact the properties of the structures surveyed. Our approach recovers some well-accepted design rules: hybrid organic-inorganic perovskites with lead and tin tend to be good candidates for solar cell applications and titanium based MXenes usually have high stiffness coefficients. Interestingly, other members of the group 4 elements also contribute to increasing the mechanical strength of MXenes. For all-inorganic perovskites, we discover some compositions that have not been deeply studied in the field of photovoltaics and thus open up paths for further investigation. We open-source the code-base to spur further development in this space.

Venturi, Victor (ORCID:0000000156727549)↗
DOE OSTI2023

Microbiome-enabled genomic selection improves prediction accuracy for nitrogen-related traits in maize

Root-associated microbiomes in the rhizosphere (rhizobiomes) are increasingly known to play an important role in nutrient acquisition, stress tolerance, and disease resistance of plants. However, it remains largely unclear to what extent these rhizobiomes contribute to trait variation for different genotypes and if their inclusion in the genomic selection protocol can enhance prediction accuracy. To address these questions, we developed a microbiome-enabled genomic selection method that incorporated host SNPs and amplicon sequence variants from plant rhizobiomes in a maize diversity panel under high and low nitrogen (N) field conditions. Our cross-validation results showed that the microbiome-enabled genomic selection model significantly outperformed the conventional genomic selection model for nearly all time-series traits related to plant growth and N responses, with an average relative improvement of 3.7%. The improvement was more pronounced under low N conditions (8.4–40.2% of relative improvement), consistent with the view that some beneficial microbes can enhance N nutrient uptake, particularly in low N fields. However, our study could not definitively rule out the possibility that the observed improvement is partially due to the amplicon sequence variants being influenced by microenvironments. Using a high-dimensional mediation analysis method, our study has also identified microbial mediators that establish a link between plant genotype and phenotype. Some of the detected mediator microbes were previously reported to promote plant growth. The enhanced prediction accuracy of the microbiome-enabled genomic selection models, demonstrated in a single environment, serves as a proof-of-concept for the potential application of microbiome-enabled plant breeding for sustainable agriculture.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The impact of void environment on AGN

ABSTRACT We study the population of active galaxies in void environment in the Sloan Digital Sky Survey. We use optical spectroscopic information to analyse characteristics of the emission lines of galaxies, accomplished by WHAN and BPT diagrams. Also, we study Wide-field Infrared Survey Explorer(WISE) mid-IR colours to assess active galactic nucleus (AGN) activity. We investigate these different AGN classification schemes, both optical and mid-IR, and their dependence on the spatial location with respect to the void centres. To this end, we define three regions: void, the spherical region defined by voidcentric distance relative to void radius (distance/rvoid) smaller than 0.8, comprising overdensities lesser than −0.9, an intermediate/transition shell region (namely, void-wall) 0.8 < distance/rvoid < 1.2, and a region sufficiently distant from voids, the field: distance/rvoid > 2. We find statistical evidence for a larger fraction of AGN and star-forming galaxies in the void region, regardless of the classification scheme addressed (either BPT, WHAN, or WISE). Moreover, we obtain a significantly stronger nuclear activity in voids compared to the field. We find an unusually large fraction of the most massive black holes undergoing strong accretion when their host galaxies reside in voids. Our results suggest a strong influence of the void environment on AGN mechanisms associated with galaxy evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Type Ia supernovae in the star formation deserts of spiral host galaxies

ABSTRACT Using a sample of nearby spiral galaxies hosting 185 supernovae (SNe) Ia, we perform a comparative analysis of the locations and light-curve decline rates (Δm15) of normal and peculiar SNe Ia in the star formation deserts (SFDs) and beyond. To accomplish this, we present a simple visual classification approach based on the UV/H α images of the discs of host galaxies. We demonstrate that, from the perspective of the dynamical time-scale of the SFD, where the star formation is suppressed by the bar evolution, the Δm15 of SN Ia and progenitor age can be related. The SFD phenomenon gives an excellent possibility to separate a subpopulation of SN Ia progenitors with ages older than a few Gyr. We show, for the first time, that the SFDs contain mostly faster declining SNe Ia (Δm15 > 1.25). For the galaxies without SFDs, the region within the bar radius, and outer disc contain mostly slower declining SNe Ia. To better constrain the delay times of SNe Ia, we encourage new studies (e.g. integral field observations) using the SFD phenomenon on larger and more robust datasets of SNe Ia and their host galaxies.

Hakobyan, A. A. (ORCID:0000000173921765)↗