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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hot Carrier Redistribution, Electron-Phonon Interaction, and Their Role in Carrier Relaxation in Thin Film Metal-Halide Perovskites

Temperature dependent (4–295 K) photoluminescence and transmission spectra are analyzed to study the effect of changing the different components of a perovskite compound, be it A, B, or X. Four different films are compared: FAMAPbSnI3, FAPbI3, FAMAPbI3, and FAPbBr3. The low temperature results highlight the changes that occur, especially underlying ones that are easily masked at room temperature. The overall Stokes shift is of similar magnitude at room temperature for the three Pb only based samples. This is governed by the interaction strength GLO, phonon energy ELO, and exciton binding energy Eex. One exception to this behavior is the Sn based FAMAPbSnI3 film, which shows a lack of Stokes shift between the absorption and photoluminescence. However, the strong absorption (more than 100 meV) below the band gap is indicative of an excitonic feature that has a large density of states. Transient absorption measurements confirm the trends observed in continuous wave (CW) measurements; the three Pb only films all show the convolution of an excitonic feature within 20 meV of the band gap as a contributing factor to the photobleach along with a region of high energy photoinduced absorption (PIA). However, the behavior for the Sn based film is notably different (just as it is in the CW measurements) with an unusual low energy PIA and a lack of high energy PIA. The large unusual low energy PIA is attributed to the large sub-band-gap absorption observed in the CW transmission/absorption measurements. Notably, regardless of interchanging components, the slow cooling of carriers in metal-halide perovskites shows little effect of GLO, ELO, and Eex. As such, here it is proposed that while the initial cooling of carriers is attributed to LO phonons, the overall cooling of carriers is dominated by the intrinsic low thermal conductivity of all metal-halide perovskites, which limits the dissipation of acoustic phonons in these systems

2D perovskites↗
DOE OSTI2020

Super resolution for root imaging

Premise High‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection. An effective super‐resolution (SR) algorithm is therefore needed for overcoming the resolution limitations of sensors, reducing storage space requirements, and boosting the performance of subsequent analyses. Methods We propose an SR framework for enhancing images of plant roots using convolutional neural networks. We compare three alternatives for training the SR model: (i) training with non‐plant‐root images, (ii) training with plant‐root images, and (iii) pretraining the model with non‐plant‐root images and fine‐tuning with plant‐root images. The architectures of the SR models were based on two state‐of‐the‐art deep learning approaches: a fast SR convolutional neural network and an SR generative adversarial network. Results In our experiments, we observed that the SR models improved the quality of low‐resolution images of plant roots in an unseen data set in terms of the signal‐to‐noise ratio. We used a collection of publicly available data sets to demonstrate that the SR models outperform the basic bicubic interpolation, even when trained with non‐root data sets. Discussion The incorporation of a deep learning–based SR model in the imaging process enhances the quality of low‐resolution images of plant roots. We demonstrate that SR preprocessing boosts the performance of a machine learning system trained to separate plant roots from their background. Our segmentation experiments also show that high performance on this task can be achieved independently of the signal‐to‐noise ratio. We therefore conclude that the quality of the image enhancement depends on the desired application.

Ruiz‐Munoz, Jose F.↗
DOE OSTI2025

Monocrystalline CdSeTe/MgCdTe Double‐Heterostructure Solar Cells

This article reports monocrystalline CdSeTe/MgCdTe double‐heterostructure (DH) solar cells with varying Se compositions in the absorber layers that are grown on InSb substrates by using molecular beam epitaxy. The Se composition in the samples studied is determined to be 4%–11% through high‐resolution X‐ray diffraction (XRD) and photoluminescence measurements. Increased Se incorporation induces higher defect density attributed to increased lattice mismatch, and mixed‐phase formation due to the small difference in formation energies between the wurtzite and zinc blende phases of CdSe, which causes stacking faults and grain boundaries. Devices are fabricated by directly depositing an n‐type indium tin oxide (ITO) layer on the CdSeTe/MgCdTe DHs followed by Ag metal contacts. Reduced bandgap is observed in solar cells with increased Se composition. The devices with an absorber containing 4% Se exhibit an average open‐circuit voltage ( V OC ) of 0.925 V, a short‐circuit current density ( J SC ) of 23.4 mA/cm 2 , a fill factor ( FF ) of 0.650 and an efficiency of 14.1% without anti‐reflection coating. Absorbers with higher Se compositions result in poor device performance, mainly attributed to high defect density in the materials.

Ju, Zheng [Center for Photonics Innovation Arizona↗
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2020

Partitioning of tramp elements Cu and Si in a Ni-based superalloy and their effect on creep properties

An alloy's processing history, including melting, remelting or the choice of stock material, affects its purity and eventually involves tramp element pickup or retention. Herein, variants of a novel Ni-based superalloy were manufactured with different levels of purity. The so-called low purity alloys contained 0.138 wt. % Cu and 0.019 wt. % Si while the Cu and Si levels were below x-ray fluorescence (XRF) detection limits of 0.003 and 0.010 wt. %, respectively, in the high purity ingots. Atom-probe tomography (APT) was carried out and revealed Si partitioning at the following interfaces: grain boundaries, MC carbide/γ, M 3 B 2 boride/$γ$ and M 3 B 2 boride/$γ$'. Copper was found to primarily segregate to the $γ$' precipitates. An average of 2.4 × decrease in creep life and 4.3 × decrease in creep ductility was measured in the low purity alloys, which was attributed to the embrittlement caused by Si segregation to grain boundaries. Furthermore, the positive effect of B on the creep properties was mitigated by the presence of Si. Thermodynamic predictions for the matrix and γ' precipitate compositions represented the trends observed experimentally although the extent of preferential partitioning lacks accuracy. Monte Carlo simulations were performed to describe the partitioning of Cu and Si atoms to either $γ$ or $γ$' phases.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Giant anisotropic in-plane thermal conduction induced by Anomalous phonons in pentagonal PdSe 2

In two-dimensional materials, different atomic stacking induces anisotropic atomic interactions and phonon dispersions, leading to the anisotropy of in-plane thermal transport. In this work, we report an exceptional case in layered pentagonal PdSe 2 , where the bonding, force constants, and lattice constants are nearly-equal along the in-plane crystallographic axis directions, while the thermal conductivity is surprisingly much greater along b-axis than along a-axis with a ratio up to 1.8. Such strong anisotropy is not only unexpected in in-plane uniform structured materials, but also 2 comparable to the record high in-plane anisotropic thermal conductivity in the nonuniform structured material reported to date (the ratio is ~2.0 in TiS 3 ). By combining the inelastic X-ray scattering measurement and the first-principles calculations, we attribute such high anisotropy to the low-energy phonons along a-axis, particularly their lower group velocities and “avoided-crossing” behavior. The different buckling structures between a- (zigzag-type) and b-axis (flat-type) are mainly responsible for such unique phonon dynamics properties of PdSe 2 . This finding helps to discover materials with high anisotropic in-plane thermal conductivity in uniform structures and reveals new physics of anisotropy of in-plane thermal conduction. Due to the unique features in structure and thermal transport properties, PdSe 2 may serve as a new platform for designing novel devices to route heat flow precisely at the nanoscale.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Room-temperature valley-selective emission in Si-MoSe 2 heterostructures enabled by high-quality-factor chiroptical cavities

Transition metal dichalcogenides possess valley pseudospin, enabling coupling between photon spin and electron spin for classical and quantum information processing. However, rapid valley-dephasing processes have impeded the development of scalable, high-performance valleytronic devices operating at room temperature. Here we demonstrate that a chiral resonant metasurface can enable room-temperature valley-selective emission in MoSe 2 monolayers independent of excitation polarization. This platform provides circular eigen-polarization states with a high quality factor (Q-factor) and strong chiral near-field enhancement. The fabricated Si chiral metasurfaces exhibit chiroptical resonances with Q-factors up to 450 at visible wavelengths. We reveal degrees of circular polarization (DOP) reaching a record high of 0.5 at room temperature. Our measurements show that the high DOP can be attributed to the significantly increased chiroptical local density of states, which enhances valley-specific radiative transition rates by a factor of ~13. Our work could facilitate the development of ultracompact chiral classical and quantum light sources.

42 ENGINEERING↗
DOE OSTI2024

Optimizing protic ionic liquid electrolyte for pre-intercalated Ti 3 C 2 T x MXene supercapacitor electrodes

Electrical double-layer capacitors (EDLCs) are of increasing importance in energy storage from renewable sources. The properties of the electrode and electrolyte materials influence the energy and power densities of EDLCs. We examined the specific capacitance and ion dynamics of a protic ionic liquid confined in pre-intercalated Ti 3 C 2 T x MXene. Our electrochemical measurements demonstrated that the creation of a protic ionic liquid, 1-butyl-3-H-imidazolium bis(trifluoromethanesulfonyl)imide (BuIMH-NTf2), using a mixture of ionic liquid, 1-butyl imidazole (BuIM), and salt, bis(trifluoromethanesulfonyl)imide (HNTf2), in a ratio of 0.8:0.2 led to the optimal capacitance. Remarkably, quasi-elastic neutron scattering measurements revealed increased particle mobility at this composition, attributed to the more efficient accumulation of BuIMH + on the electrode surface. This deposit of additional ions results in fewer BuIM molecules away from the surface, enhancing their mobility due to reduced crowding. This composition-dependent electrochemical behavior will guide the formulation of more efficient protic ionic liquid systems, enabling faster ion transport in energy storage devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Design of an Integrated Solids Handling System to Maximize Syngas Process Reliability (Cooperative Research and Development Final Report)

The National Renewable Energy Laboratory (NREL), in partnership with Wonderful Renewable Energy (WRE) and Idaho National Laboratory (INL), plans to develop a general methodology for designing integrated biorefinery solids preprocessing, handling, and feeding systems based on the chemical, physical, and mechanical attributes of the starting biomass material. This attribute-driven approach will include detailed feedstock property measurements, iterative computational modeling, and bench-scale testing to design systems for preprocessing, handling, and reactor in-feed, up to and including the selection of the conversion reactor. The initial tests and system design will be conducted using waste material from almond and pistachio growing and production operations (shells, hulls, and wood), targeting the conversion of this material to syngas for electricity production. The methodology will then be generalized to other feedstocks. The purpose of this project is to design an integrated solids handling system to maximize the process reliability of converting almond and pistachio waste to electricity. The design methodology and workflow developed from this example will then be applied to the Feedstock Conversion Interface Consortium (FCIC) benchmark loblolly pine residues, thus demonstrating the robustness of the overall design approach and providing insight and guidance for future conversion systems. V-Grid Energy Systems was brought on as a subcontractor to provide gasifiers and labor to complete gasifier runs.

09 BIOMASS FUELS↗
DOE OSTI2020

Spatial Mapping of Riverbed Grain-Size Distribution Using Machine Learning

Recent alluvial sediments in riverbeds play a significant role in controlling hydrologic exchange flows (HEFs) in river systems. The alluvial layer is usually associated with strong heterogeneity in physical properties (e.g., permeability and hydraulic conductivity), which affects local HEFs and therefore biogeochemical processes. The spatial distribution of these physical properties needs to be determined to inform the numerical models used to reveal the realistic hydro-biogeochemical behaviors. Such information can be obtained based on the intrinsic link between sediment grain-size distribution and hydraulic properties where sediment texture information is available. However, grain-size measurements are usually spatially sparse and do not have adequate coverage and resolution, particularly for a relatively large domain such as the Hanford Reach of the Columbia River. In this paper, we adopted machine learning (ML) approaches for categorizing and mapping the spatial distributions of riverbed substrate grain size and filling in missing areas of substrate data using the ML models along the reach. Such ML models for substrate size mapping were trained at 13,372 locations using measured substrate sizes along with observed and simulated attributes, including bathymetric attributes (e.g., elevation, slope, and aspect ratio) from LIDAR and bathymetric surveys, and hydrodynamic properties (e.g., water depth, velocity, shear stress, and their statistical moments). An ensemble bagging-based ML technique, Random Forest, was adopted to identify the most influential factors as predictors to develop the predictive models with over-fitting issues addressed. The models were evaluated with respect to each individual substrate size class and the lumped group, and then used to generate the final substrate size maps covering all the grid cells in the numerical modeling domain.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Solar-wind tritium limit and the mixing rate of the solar atmosphere

Tritium has been measured, in Surveyor 3 samples, some of which were adjacent to those in which solar-wind-implanted He-4 had previously been measured. Little of the H-3 can be attributed to solar-wind implantation. The upper limit for the H-3/He-4 ratio in the solar wind is four times ten to the minus tenth power and corresponds to a H-3/H-1 limit of two times ten to the minus eleventh power. This limit imposes a requirement on the mixing rate in the solar atmosphere if the H-3 production rate in solar-surface nuclear reactions is greater than 160 sq cm/sec.

Fireman, E. L.↗
NASA NTRS1977

Monte Carlo turbulence simulation

The paper describes turbulence simulation experiments based on the principles of control system theory, that is, the construction of a system characterized by a system function such that upon exciting the system with prescribed noise processes the output of the system is a realization of a random processing the desired statistical attributes of turbulence. An experimental autocorrelation of Jimsphere measurements of wind velocity was approximated to simulate turbulent wind. From the approximate autocorrelation function, the required system function is obtained, and a discrete time system is designed. Another method of simulation is to solve the convolution integral by filter techniques. Other methods include discrete Fourier simulation and self-similar simulation.

Fichtl, G. H.↗
NASA NTRS1982

Investigating reliability attributes of silicon photovoltaic cells - An overview

Reliability attributes are being developed on a wide variety of advanced single-crystal silicon solar cells. Two separate investigations: cell-contact integrity (metal-to-silicon adherence), and cracked cells identified with fracture-strength-reducing flaws are discussed. In the cell-contact-integrity investigation, analysis of contact pull-strength data shows that cell types made with different metallization technologies, i.e., vacuum, plated, screen-printed and soldered, have appreciably different reliability attributes. In the second investigation, fracture strength was measured using Czochralski wafers and cells taken at various stages of processing and differences were noted. Fracture strength, which is believed to be governed by flaws introduced during wafer sawing, was observed to improve (increase) after chemical polishing and other process steps that tend to remove surface and edge flaws.

Royal, E. L.↗
NASA NTRS1985

Persistence of phosphor glow in microchannel plate image intensifiers

Image intensifier tubes using microchannel plate amplification stages and phosphor output stages are being increasingly used in various detection applications. In this paper, measurements of the decay times of what are attributed to be the P20 phosphors in various image intensifiers are reported. It is found that the long tail on the decay curve of the phosphor following illumination can be a limitation for certain observations. In addition, the background level of phosphor glow (which is seen by the subsequent detection system as a light signal) continues to build with continuing illumination.

Torr, M. R.↗
NASA NTRS1986

The response function of modulated grid Faraday cup plasma instruments

Modulated grid Faraday cup plasma analyzers are a very useful tool for making in situ measurements of space plasmas. One of their great attributes is that their simplicity permits their angular response function to be calculated theoretically. An expression is derived for this response function by computing the trajectories of the charged particles inside the cup. The Voyager Plasma Science (PLS) experiment is used as a specific example. Two approximations to the rigorous response function useful for data analysis are discussed. The theoretical formulas were tested by multi-sensor analysis of solar wind data. The tests indicate that the formulas represent the true cup response function for all angles of incidence with a maximum error of only a few percent.

Barnett, A.↗
NASA NTRS1986

Response function of modulated grid Faraday cup plasma instruments

Modulated grid Faraday cup plasma analyzers are a very useful tool for making in situ measurements of space plasmas. One of their great attributes is that their simplicity permits their angular response function to be calculated theoretically. An expression is derived for this response function by computing the trajectories of the charged particles inside the cup. The Voyager plasma science experiment is used as a specific example. Two approximations to the rigorous response function useful for data analysis are discussed. Multisensor analysis of solar wind data indicates that the formulas represent the true cup response function for all angles of incidence with a maximum error of only a few percent.

Barnett, A.↗
NASA NTRS1990

Magnetospheric interaction with Triton's ionosphere

The large electron densities measured by the Voyager radio occultation experiment are attributed to the precipitation of magnetospheric electrons with energy above 10 keV. Because the ionospheric electric Pedersen conductivity of Triton is about 10,000-20,000 mho and the Alfven conductance is about 3.5 mho, direct convective flow of plasma into the essentially infinitely conducting ionosphere is negligible. Magnetospheric electrons are transported to Triton's ionopause by curvature drift as a result of weak magnetic field line draping in a sub-Alfvenic plasma interaction with Triton. At the ionopause energetic electrons have a high probability of elastic and inelastic scattering and precipitate into the upper atmosphere. The average power dissipation is estimated to be about (2 - 3) x 10 to the 8th W.

Strobel, Darrell F.↗
NASA NTRS1994

Atmosphere-biosphere exchange flux of carbon dioxide in a tallgrass prairie modeled with satellite spectral data

The estimation of the rate of net CO2 uptake of vegetated land surfaces is essential for studies of global carbon cycle. The present paper demonstrates the use of spectral reflectance data from satellite remote sensing to model net CO2 flux (NCF) of a tallgrass canopy at the Konza prairie, Kansas. A bidirectional reflectance canopy model was used to estimate seasonal changes in canopy leaf area index (LAI) from surface reflectances remotely sensed by SPOT 1 and Landsat 5 satellites. The radiation model was also coupled with leaf conductance-photosynthesis models to scale up stomatal conductance and NCF from individual leaves to canopy level according to radiation distribution inside the canopy. The satellite-data-driven model was able to closely simulate the seasonal change in LAI as well as the short-term variation of canopy LAI caused by the dry period during late July and early August in the area. Modeled canopy stomatal conductance (g(sub c)) and NCF agree with measurements within 0.16 cm/s and 0.28 mg m(exp -2)/s, respectively, during the growth season from late May to late August. In October both measured and modeled NCF turned to small negative values as canopy photosynthesis diminished and predicted LAI approached zero. In addition to data scatter, some of the differences between modeled and measured g(sub c) and NCF may be attributed to uncertainties in seasonal changes of plant physiological status that were not detected by satellite data; some of the differences were caused by inadequate description of the dependence of nighttime CO2 flux of soil respiration on near-surface turbulent mixing.

Gao, W.↗