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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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This document describes the underlying theory and use of a computer code written to simulate scintillation effects on propagating electromagnetic (EM) signals. The Multiple Phase Screen (MPS) technique [1, 2, 3, 4] is employed to model the effects of scintillation on EM signals as they travel through the earth’s ionosphere.
Many-body Coulomb effects influence the operation of quantum-well (QW) laser diode (LD) strongly. In the present work, we study a two-band electron-hole plasma (EHP) within the Hatree-Fock approximation and the single plasmon pole approximation for static screening. Full inclusion of momentum dependence in the many-body effects is considered. An empirical expression for carrier density dependence of the bandgap renormalization (BGR) in an 8 nm GaAs/Al(0.3)G(4.7)As single QW will be given, which demonstrates a non-universal scaling behavior for quasi-two-dimension structures, due to size-dependent efficiency of screening. In addition, effective mass renormalization (EMR) due to momentum-dependent self-energy many-body correction, for both electrons and holes is studied and serves as another manifestation of the many-body effects. Finally, the effects on carrier density dependence of the alpha factor is evaluated to assess the sensitivity of the full inclusion of momentum dependence.
The atomic and electronic structures of the pristine PdSe 2 as well as various intrinsic vacancy defects in PdSe 2 are studied comprehensively by combining scanning tunneling microscopy, spectroscopy and density functional theory calculations. Other than the topmost Se atoms, sublayer Pd atoms, the intrinsic Pd and Se vacancy-defects are identified. Both V Se and V Pd defects induce defect states near Fermi level. As a result, the vacancy defects can be negatively charged by tip gating effect. At negative sample bias, the screened Coulomb interaction between STM tip and the charged vacancies creates disk-like protrusion around V Pd and crater-like features around V Se . The magnification effect of the long-range charge localization at the charged defect site makes sublayer defects as deep as 1nm visible even in STM images. In conclusion, this result proves that by gating the probe, scanning probe microscopy can be used as an easy tool for characterizing sublayer defects in a nondestructive way.
Solid oxide fuel cell systems used in the aerospace or commercial aviation environment require a compact, light-weight and highly durable catalytic fuel processor. The fuel processing method considered here is an autothermal reforming (ATR) step. The ATR converts Jet-A fuel by a reaction with steam and air forming hydrogen (H2) and carbon monoxide (CO) to be used for production of electrical power in the fuel cell. This paper addresses the first phase of an experimental catalyst screening study, looking at the relative effectiveness of several monolith catalyst types when operating with untreated Jet-A fuel. Six monolith catalyst materials were selected for preliminary evaluation and experimental bench-scale screening in a small 0.05 kWe micro-reactor test apparatus. These tests were conducted to assess relative catalyst performance under atmospheric pressure ATR conditions and processing Jet-A fuel at a steam-to-carbon ratio of 3.5, a value higher than anticipated to be run in an optimized system. The average reformer efficiencies for the six catalysts tested ranged from 75 to 83 percent at a constant gas-hourly space velocity of 12,000 hr 1. The corresponding hydrocarbon conversion efficiency varied from 86 to 95 percent during experiments run at reaction temperatures between 750 to 830 C. Based on the results of the short-duration 100 hr tests reported herein, two of the highest performing catalysts were selected for further evaluation in a follow-on 1000 hr life durability study in Phase II.
Dielectric property screening tests, and temperature range tests for determining ablation material effects on Apollo model antennas - simulation of thermal protection system
Included in the most critical factors for geological CO 2 storage site screening, selection, and operation is effective simulations of multiphase flow and transport. Relative permeability is probably the greatest source of potential uncertainty in multiphase flow simulation, second only to intrinsic permeability heterogeneity. The specific relative permeability relationship assigned greatly impacts forecasts of CO 2 trapping mechanisms, phase behavior, and long-term plume movement. A primary goal of this study is to evaluate the impacts and implications of different methods of assigning relative permeability relationships for CO 2 -EOR model forecasts. Most simulation studies published in the literature base selection of relative permeability functions on the geologic formation or rock type alone. In this study, we initially implemented reservoir model grids with previously-identified hydrostratigraphic units based on porosity and permeability relationship of the Morrow ‘B’ Sandstone, then assigned relative permeability functions for those hydrostratigraphic units. Specific, constrained relative permeability relationships were created and assigned to each hydrostratigraphic unit using petrophysical data and Mercury Intrusion Capillary Pressure (MICP) measurements, from core samples of each hydrostratigraphic unit. Results of forward simulations with the newly-calibrated models will be compared to those of previous models as well as to simulation results for a range of different relative permeability relationships. The study site is the Farnsworth Unit (FWU) in the northeast Texas Panhandle, an active CO 2 -EOR operation. The target formation is the Morrow ‘B’ Sandstone, a clastic formation composed of medium to course sands.
Inertial confinement fusion hotspots and cluster Coulomb explosion plasmas may develop a positive net electric charge. The Coulomb barrier penetrability and the rate of nuclear fusion reactions at ultra-low energies (≲ 10 keV) are altered by such an environment. These effects are studied via the screening potential approach. Approximate analytical results are developed by evaluating the average screening potential for some scenarios of interest. It is found that fusion is hindered for reactions between thermal fuel nuclei, while an enhancement is expected for secondary and “beam-target” reactions. Depending on the plasma conditions, the variations can be relevant even for relatively small net charges (several % difference or more in the fusion rate for an average net charge per nucleus of 10 -5 proton charges).
The industrial fluidized bed reactor (FBR) described here is designed to convert an aqueous solid laden stream into a consistent solid product material. Additionally, the FBR is heated to 650 °C and the aqueous reactant is spray-atomized into the fluidized bed, converting it into a granular solid through a series of heterogeneous chemical reactions. The objective of this study is to use the MFiX two-fluid model as a screening tool to investigate the effects of off-nominal conditions for the purpose of establishing performance guidelines. This information will be helpful to assess whether the identified boundaries of the system are steep or gradual. Initially, 13 independent operating parameters were sampled in a one-at-a-time manner using high, low, and base values and ranked against a set of performance criteria. Five operating parameters were found to have the largest effect (bed particle size, bed particle density, coal particle size, spray feed flow rate, and fluidizing gas flow rate) on three quantities of interest—bed differential temperature, solids velocity, and bed voidage. Latin hypercube sampling was used to generate a minimal number of random values for various combinations of input parameters. The spray feed flow rate was the most significant parameter for the temperature differences, and the coal particle and bed particle size were significant contributors. The bed particle size had the largest effect on the low velocity of the bed particles, with the coal particle size as a contributing second effect. The high solid packing shows the coal particle size with the largest effect, and significant secondary contributions from the feed flow rate and fluidizing gas flow rate. Finally, the fits to the five-dimensional Gaussian Process models were 0.7797, 0.8664, and 0.9440 for the temperature, velocity, and solids packing respectively.
One of the major challenges when testing drug candidates targeted at a specific pathway in whole animals is the discrimination between specific effects and unwanted, off-target effects. Here we used the zebrafish to define several developmental defects caused by impairment of Egf signaling, a major pathway of interest in tumor biology. We inactivated Egf signaling by genetically blocking Egf expression or using specific inhibitors of the Egf receptor function. We show that the combined occurrence of defects in cartilage formation, disturbance of blood flow in the trunk and a decrease of myelin basic protein expression represent good indicators for impairment of Egf signaling. Finally, we present a classification of known tyrosine kinase inhibitors according to their specificity for the Egf pathway. In conclusion, we show that developmental indicators can help to discriminate between specific effects on the target pathway from off-target effects in molecularly targeted drug screening experiments in whole animal systems. - Highlights: • We analyze the functions of Egf signaling on zebrafish development. • Genetic blocking of Egf expression causes cartilage, myelin and circulatory defects. • Chemical inhibition of Egf receptor function causes similar defects. • Developmental defects can reveal the specificity of Egf pathway inhibitors.
The intrinsic weak and highly nonlocal dielectric screening of two-dimensional materials is well-known to lead to high sensitivity of their optoelectronic properties to environment. Less studied theoretically is the role of free carriers in those properties. In this report we use ab initio GW and Bethe-Salpeter equation calculations, with a rigorous treatment of dynamical screening and local-field effects, to study the doping dependence of the quasiparticle and optical properties of a monolayer transition-metal dichalcogenide, 2H MoTe 2 . Here we predict a quasiparticle band gap renormalization of several hundreds of meV for experimentally attainable carrier densities and a similarly sizable decrease in the exciton binding energy. This results in an almost constant excitation energy for the lowest-energy exciton resonance with an increasing doping density. Using a newly developed and generally applicable plasmon-pole model and a self-consistent solution of the Bethe-Salpeter equation, we reveal the importance of accurately capturing both dynamical and local-field effects to understand detailed photoluminescence measurements.
Two-dimensional (2D) nanomaterials have fascinating structural, electrical, and optical properties, especially strong excitonic effects due to decreased dielectric screening. However, constructing 2D ultrathin nanomaterials, with the exception of layered materials, remains a challenge. In this work, we successfully realize oriented attachment on guiding one-dimensional chalcopyrite CuInS 2 nanocrystal (NC) formation and 2D assembly into lamellar nanosheets by applying pressure-driven sintering of zero-dimensional CuInS2 nanoparticles (NPs). We discuss the atomic-level mechanism of such phenomena and illustrate a pressure-driven processing diagram that reveals the sintering process of NPs coordinated by pressure and structural transformation. Optical measurements exhibit that the band gap has a narrowing by 0.21 eV compared with the initial 2.03 eV upon decompression to ambient conditions. Our findings represent a significant step forward in gaining an in-depth understanding of the pressure-driven morphology engineering of nanomaterials and provide a promising strategy to prepare 2D NCs, thereby greatly increasing the choice of materials for various applications.
Succinic acid is a biomass-derived platform chemical that can be catalytically converted in the aqueous phase to 1,4-butanediol (BDO), a prevalent building block used in the polymer and chemical industries. Despite significant interest, limited work has been reported regarding sustained catalyst performance and stability under continuous aqueous-phase process conditions. As such, this work examines Ru-Sn on activated carbon (AC) for the aqueous-phase conversion of succinic acid to BDO under batch and flow reactor conditions. Initially, powder Ru-Sn catalysts were screened to determine the most effective bimetallic ratio and provide a comparison to other monometallic (Pd, Pt, Ru) and bimetallic (Pt-Sn, Pd-Re) catalysts. Batch reactor tests determined that a ~1:1 metal weight ratio of Ru to Sn was effective for producing BDO in high yields, with complete conversion resulting in 82% molar yield. Characterization of the fresh Ru-Sn catalyst suggests that the sequential loading method results in Ru sites that are colocated and surface-enriched with Sn. Postbatch reaction characterization confirmed stable Ru-Sn material properties; however, upon a transition to continuous conditions, significant Ru-Sn/AC deactivation occurred due to stainless steel leaching of Ni that resulted in Ru-Sn metal crystallite restructuring to form discrete Ni-Sn sites. Computational modeling confirmed favorable energetics for Ru-Sn segregation and Ni-Sn formation at submonolayer Sn incorporation. To address stainless steel leaching, reactor walls were treated with an inert silica coating by chemical vapor deposition. With leaching reduced, stable Ru-Sn/AC performance was observed that resulted in a molar yield of 71% BDO and 15% tetrahydrofuran for 96 h of time on stream. Postreaction catalyst characterization confirmed low levels of Ni and Cr deposition, although early-stage islanding of Ni-Sn will likely be problematic for industrially relevant time scales (i.e., thousands of hours). Overall, these results (i) demonstrate the performance of Ru-Sn/AC for aqueous phase succinic acid reduction, (ii) provide insight into the Ru-Sn bimetallic structure and deactivation in the presence of leached Ni, and (iii) underscore the importance of compatible reactor metallurgy and durable catalysts.
Enveloped RNA viruses, such as Influenza A (H1N1) and Sindbis virus, pose persistent global health threats due to their high mutation rates, efficient transmission, and frequent drug resistance. By mimicking host cell membrane receptors, multivalent virus inhibitors can block viral attachment, making them promising broad-spectrum antiviral agents. However, most of existing antivirals are often limited by strain specificity, short-lived efficacy, and toxicity. Here, we introduce a broad-spectrum antiviral platform based on highly tunable and biocompatible two-dimensional nanomembranes (2DNMs) self-assembled from amphiphilic peptoids, operating via a non-genomic, mutation-insensitive mechanism. By varying peptoid sequence, we design and synthesize over twenty different 2DNMs with various surface charge and high density of viral-attachment ligands (VALs). The self-assembled architecture of these stable 2DNMs provides cooperative noncovalent multivalent binding to virus particles that result in effective inhibition of viral infection. Screening of variants identified three leads that potently suppressed Influenza A (H1N1) and Sindbis virus infection across median tissue culture infectious dose (TCID50), plaque, RT–qPCR, and immunofluorescence assays, while maintaining >90% cell viability. These nanosheets significantly reduced infectious titers, viral RNA replication, and intracellular viral protein expression, indicating inhibition at early stages of viral entry and propagation. The sequence programmability, chemical robustness, and mutation-insensitive antiviral activity distinguish 2DNMs from traditional antivirals and positions them as a versatile materials platform for antiviral coatings, protective barriers, and prophylactic biomedical applications.
Heavy-fermion metals are prototype systems for observing emergent quantum phases driven by electronic interactions. A long-standing aspiration is the dimensional reduction of these materials to exert control over their quantum phases, which remains a significant challenge because traditional intermetallic heavy-fermion compounds have three-dimensional atomic and electronic structures. Here we report comprehensive thermodynamic and spectroscopic evidence of an antiferromagnetically ordered heavy-fermion ground state in CeSiI, an intermetallic comprising two-dimensional (2D) metallic sheets held together by weak interlayer van der Waals (vdW) interactions. Owing to its vdW nature, CeSiI has a quasi-2D electronic structure, and we can control its physical dimension through exfoliation. The emergence of coherent hybridization of f and conduction electrons at low temperature is supported by the temperature evolution of angle-resolved photoemission and scanning tunnelling spectra near the Fermi level and by heat capacity measurements. Electrical transport measurements on few-layer fakes reveal heavy-fermion behaviour and magnetic order down to the ultra-thin regime. Importantly, our work establishes CeSiI and related materials as a unique platform for studying dimensionally confined heavy fermions in bulk crystals and employing 2D device fabrication techniques and vdW heterostructures to manipulate the interplay between Kondo screening, magnetic order and proximity effects.
Three decades after the prediction of charge-vortex duality in the critical vicinity of the two-dimensional superconductor-insulator transition (SIT), one of the fundamental implications of this duality-the charge Berezinskii-Kosterlitz-Thouless (BKT) transition that should occur on the insulating side of the SIT-has remained unobserved. The dual picture of the process points to the existence of a superinsulating state endowed with zero conductance at finite temperature. Here, we report the observation of the charge BKT transition on the insulating side of the SIT in 10 nm thick NbTiN films, identified by the BKT critical behavior of the temperature and magnetic field dependent resistance, and map out the magnetic-field dependence of the critical temperature of the charge BKT transition. Lastly, we ascertain the effects of the finite electrostatic screening length and its divergence at the magnetic field-tuned approach to the superconductor-insulator transition.
The rapid adoption of machine learning in various scientific domains calls for the development of best practices and community agreed-upon benchmarking tasks and metrics. We present Matbench Discovery as an example evaluation framework for machine learning energy models, here applied as pre-filters to first-principles computed data in a high-throughput search for stable inorganic crystals. We address the disconnect between (1) thermodynamic stability and formation energy and (2) retrospective and prospective benchmarking for materials discovery. Alongside this paper, we publish a Python package to aid with future model submissions and a growing online leaderboard with adaptive user-defined weighting of various performance metrics allowing researchers to prioritize the metrics they value most. To answer the question of which machine learning methodology performs best at materials discovery, our initial release includes random forests, graph neural networks, one-shot predictors, iterative Bayesian optimizers and universal interatomic potentials. We highlight a misalignment between commonly used regression metrics and more task-relevant classification metrics for materials discovery. Accurate regressors are susceptible to unexpectedly high false-positive rates if those accurate predictions lie close to the decision boundary at 0 eV per atom above the convex hull. The benchmark results demonstrate that universal interatomic potentials have advanced sufficiently to effectively and cheaply pre-screen thermodynamic stable hypothetical materials in future expansions of high-throughput materials databases.
With promising solar cell applications, organic–inorganic lead halide perovskites belong to a novel and rapidly developing class of semiconducting materials. Unlike its well-investigated iodide counterparts, formamidinium lead chloride (FAPbCl 3 ) is a much less studied perovskite that shows superior stability and surprisingly high selectivity and sensitivity towards certain gas analytes. The origin of the sensing ability of this perovskite material can be traced to its high defect tolerance and the existence of some defects which act as the “lock” to a certain gas analyte's “key”. In this work, we deepen the understanding of this proven perovskite sensor through first-principles computational study of its defect formation energies, charge transition energies, and optical properties. These studies are done with the widely used GGA exchange–correlation functional PBE and the newer meta-GGA functional SCAN, both incorporating the Grimme's D3 dispersion correction. Additionally, we also consider experimental conditions and the effect of temperature on electron screening in the simulations, which demonstrates that screening is particularly important when considering high oxidation states of the defects. We also note the importance of antisites in the Fermi Pinning as well as the importance of FA disorder, which are previously unreported insights.
Using the dielectric continuum model, hot-electron power dissipation and energy relaxation times are calculated for a typical lattice-matched AlInN/AlN/GaN heterostructure, including effects of hot phonons and screening from the mobile electrons. The calculated power dissipation and energy relaxation times are very close to the experimental data.