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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Structural Aspects of Neutron Survival Probabilities

The neutron survival probability (and related quantities including probabilities of extinction and initiation) is a central element of the broader stochastic theory of neutron populations and finds application in fields including reactor start-up, analysis of reactor power bursts and criticality accidents, and safeguards. In a full neutron transport formulation, the equation governing the single-neutron survival probability is a backward or adjoint-like integro-partial differential equation with the added complexity of being highly nonlinear. Analogous formulations of this equation exist in the context of many approximate theories of neutron transport, with the point kinetics formulation having received significant theoretical attention since the 1940s. This work continues this tradition by providing a novel analysis of the single-neutron survival probability equation using the tools of boundary layer theory. The analysis reveals that the “fully dynamic” solution of the single-neutron survival probability equation—and some key probability distributions derived from it—may be cast as a singular perturbation around the underlying quasi-static single-neutron probability of initiation. In this perturbation solution, the expansion parameter is the ratio of the neutron generation time to a macroscopic time scale characterizing the overall system evolution; this interpretation illuminates some of the fundamental structural aspects of neutron survival phenomena.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Data-Driven and Multiscale Modeling of DNA-Templated Dye Aggregates

Dye aggregates are of interest for excitonic applications, including biomedical imaging, organic photovoltaics, and quantum information systems. Dyes with large transition dipole moments (μ) are necessary to optimize coupling within dye aggregates. Extinction coefficients (ε) can be used to determine the μ of dyes, and so dyes with a large ε (>150,000 M –1 cm –1 ) should be engineered or identified. However, dye properties leading to a large ε are not fully understood, and low-throughput methods of dye screening, such as experimental measurements or density functional theory (DFT) calculations, can be time-consuming. In order to screen large datasets of molecules for desirable properties (i.e., large ε and μ), a computational workflow was established using machine learning (ML), DFT, time-dependent (TD-) DFT, and molecular dynamics (MD). ML models were developed through training and validation on a dataset of 8802 dyes using structural features. A Classifier was developed with an accuracy of 97% and a Regressor was constructed with an R2 of above 0.9, comparing between experiment and ML prediction. Using the Regressor, the ε values of over 18,000 dyes were predicted. The top 100 dyes were further screened using DFT and TD-DFT to identify 15 dyes with a μ relative to a reference dye, pentamethine indocyanine dye Cy5. Two benchmark MD simulations were performed on Cy5 and Cy5.5 dimers, and it was found that MD could accurately capture experimental results. The results of this study exhibit that our computational workflow for identifying dyes with a large μ for excitonic applications is effective and can be used as a tool to develop new dyes for excitonic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Data-driven Stellar Models

We developed a data-driven model to map stellar parameters ( T eff , log g , and [Fe/H]) accurately and precisely to broadband stellar photometry. This model must, and does, simultaneously constrain the passband-specific dust reddening vector in the Milky Way, R. The model uses a neural network to learn the (de-reddened) absolute magnitude in one band and colors across many bands, given stellar parameters from spectroscopic surveys and parallax constraints from Gaia. To demonstrate the effectiveness of this approach, we train our model on a data set with spectroscopic parameters from LAMOST, APOGEE, and GALAH, Gaia parallaxes, and optical and near-infrared photometry from Gaia, Pan-STARRS 1, Two Micron All Sky Survey and Wide-field Infrared Survey Explorer. Testing the model on these data sets leads to an excellent fit and a precise—and by construction—accurate prediction of the color–magnitude diagrams in many bands. This flexible approach rigorously links spectroscopic and photometric surveys, and also results in an improved, T eff -dependent R. As such, it provides a simple and accurate method for predicting photometry in stellar evolutionary models. Our model will form a basis to infer stellar properties, distances, and dust extinction from photometric data, which should be of great use in 3D mapping of the Milky Way. Our trained model can be obtained at doi:10.5281/zenodo.3902382.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Twisted Crystalline Organic Semiconductor Photodetectors

Optoelectronic properties of anisotropic crystals vary with direction requiring that the orientation of molecular organic semiconductor crystals is controlled in optoelectronic device active layers to achieve optimal performance. Here, in this work, a generalizable strategy to introduce periodic variations in the out-of-plane orientations of 5,11-bis(triisopropylsilylethynyl)anthradithiophene (TIPS ADT) crystals is presented. TIPS ADT crystallized from the melt in the presence of 16 wt.% polyethylene (PE) forms banded spherulites of crystalline fibrils that twist in concert about the radial growth direction. These spherulites exhibit band-dependent light absorption, photoluminescence, and Raman scattering depending on the local orientation of crystals. Mueller matrix imaging reveals strong circular extinction (CE), with TIPS ADT banded spherulites exhibiting domains of positive or negative CE signal depending on the crystal twisting sense. Furthermore, orientation-dependent enhancement in charge injection and extraction in films of twisted TIPS ADT crystals compared to films of straight crystals is visualized in local conductive atomic force microscopy maps. This enhancement leads to 3.3- and 6.2-times larger photocurrents and external quantum efficiencies, respectively, in photodetectors comprising twisted crystals than those comprising straight crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fine‐Tuning Alkyl Chains on Quinoxaline Nonfullerene Acceptors Enables High‐Efficiency Ternary Organic Solar Cells with Optimizing Molecular Stacking and Reducing Energy Loss

Abstract Material design of guest acceptor is always a big challenge for improving the efficiency of ternary organic solar cells (OSCs). Here, a pair of isomeric nonfullerene acceptors based on quinoxaline core, Qx–p‐C 7 H 8 O and Qx–m‐C 7 H 8 O, is designed and synthesized. By moving the alkoxy chain attached on side phenyl frommeta‐position topara‐position, both π–π stacking distance and crystallinity are enhanced simultaneously. They obtain the uplifted lowest unoccupied molecular orbital level. Compared to Qx–m‐C 7 H 8 O, Qx–p‐C 7 H 8 O exhibits wider absorption spectrum and higher extinction coefficient. Using D18‐Cl:N3 as host materials, the addition of guest acceptor Qx–p‐C 7 H 8 O significantly improves the power conversion efficiency (PCE) from 17.61% to 18.49% because of higher open‐circuit voltage (0.875 V) and short‐circuit current density (27.85 mA cm −2 ). This can be attributed to the faster exciton dissociation, more balanced carrier mobility, fine fiber morphology, and lower energy loss in the ternary devices. However, Qx–m‐C 7 H 8 O‐based ternary device achieves relatively low PCE of 17.17% because this device shows extremely low electron mobility. The results indicate that molecular stacking, film morphology, etc., can be effectively modulated by fine‐tuning the side chains of guest materials, which may be an effective design rule for further improving the PCE of OSCs.

Chemistry↗
DOE OSTI2024

Scalable Nanoimprint Manufacturing of Functional Multilayer Metasurface Devices

Optical metasurfaces, consisting of subwavelength-scale meta-atom arrays, hold great promise of overcoming the fundamental limitations of conventional optics. Due to their structural complexity, metasurfaces usually require high-resolution yet slow and expensive fabrication processes. Here, using a metasurface polarimetric imaging device as an example, the photonic structures and the Nanoimprint lithography (NIL) processes are designed, creating two separate NIL molds over a patterning area of > 20 mm2 with designed Moiré alignment markers by electron-beam writing, and further subsequently integrate silicon and aluminum metasurface structures on a chip. Uniquely, the silicon and aluminum metasurfaces are fabricated by using the nanolithography and 3D pattern-transfer capabilities of NIL, respectively, achieving nanometer-scale linewidth uniformity, sub-200 nm translational overlay accuracy, and <0.017 rotational alignment error while significantly reducing fabrication complexity and surface roughness. Here, the micro-sized multilayer metasurfaces have high circular polarization extinction ratios as large as ≈20 and ≈80 in blue and red wavelengths. Further, the metasurface chip-integrated CMOS imager demonstrates high accuracy in broad-band, full Stokes parameter analysis in the visible wavelength ranges and single-shot polarimetric imaging. This novel, NIL-based, multilayered nanomanufacturing approach is applicable to the scalable production of large-area functional structures for ultra-compact optic, electronic, and quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Detection and Signal Processing for Near-Field Nanoscale Fourier Transform Infrared Spectroscopy

Researchers from a broad spectrum of scientific and engineering disciplines are increasingly using scattering-type near-field infrared spectroscopic techniques to characterize materials non-destructively with nanoscale spatial resolution. However, a sub-optimal understanding of a technique's implementation can complicate data interpretation and act as a barrier to entering the field. Here the key detection and processing steps involved in producing scattering-type near-field nanoscale Fourier transform infrared spectra (nano-FTIR) are outlined. The self-contained mathematical and experimental work derives and explains: i) how normalized complex-valued nano-FTIR spectra are generated, ii) why the real and imaginary components of spectra qualitatively relate to dispersion and absorption respectively, iii) a new and generally valid equation for spectra which can be used as a springboard for additional modeling of the scattering processes, and iv) an algebraic expression that can be used to extract an approximation to the sample's local extinction coefficient from nano-FTIR. The algebraic model for weak oscillators is validated with nano-FTIR and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectra on samples of polystyrene and Kapton and further provides a pedagogical pathway to cementing some of the technique's key qualitative attributes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Stoichiometric Control and Optical Properties of BaTiO 3 Thin Films Grown by Hybrid MBE

BaTiO 3 is a technologically relevant material in the perovskite oxide class with above-room-temperature ferroelectricity and a very large electro-optical coefficient, making it highly suitable for emerging electronic and photonic devices. An easy, robust, straightforward, and scalable growth method is required to synthesize epitaxial BaTiO 3 thin films with sufficient control over the film's stoichiometry to achieve reproducible thin film properties. Here the growth of BaTiO 3 thin films by hybrid molecular beam epitaxy is reported. A self-regulated growth window is identified using complementary information obtained from reflection high energy electron diffraction, the intrinsic film lattice parameter, film surface morphology, and scanning transmission electron microscopy. Subsequent optical characterization of the BaTiO 3 films by spectroscopic ellipsometry revealed refractive index and extinction coefficient values closely resembling those of stoichiometric bulk BaTiO 3 crystals for films grown inside the growth window. Even in the absence of a lattice parameter change of BaTiO 3 thin films, degradation of optical properties is observed, accompanied by the appearance of a wide optical absorption peak in the IR spectrum, attributed to optical transitions involving defect states present. Therefore, the optical properties of BaTiO 3 can be utilized as a much finer and more straightforward probe to determine the stoichiometry level present in BaTiO 3 films.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enhanced Laser Damage Threshold in Optically Addressable Light Valves via Aluminum Nitride Photoconductors

Abstract Optically addressable light valves (OALVs) are specialized optical components utilized for spatial beam shaping in various laser‐based applications, including optics damage mitigation, and enhanced functionality in diode‐based additive manufacturing requiring high intensities. Current state‐of‐the‐art OALVs employ photoconductors such as Bismuth Silicon Oxide (BSO) or Bismuth Germanium Oxide (BGO), which suffer from limited laser‐induced damage thresholds (LiDT) and inadequate thermal conductivities, thus restricting their use in high peak and average power applications. Aluminum nitride (AlN), an emerging ultra‐wide band gap (UWBG) III–V semiconductor, offers promising optoelectronic properties and superior thermal conductivity (>300 Wm −1 K −1 at 298° K, compared to BSO's 3.29 Wm −1 K −1 ). In this study, the first AlN‐based OALVs are designed, fabricated, and experimentally demonstrated using commercially available single‐crystal AlN substrates. These AlN‐based OALVs have shown clear superiority over BSO and BGO‐based devices. Design considerations for OALVs incorporating UWBG photoconductors are discussed, and the photoresponsivity from defect‐mediated sub‐bandgap absorption in AlN crystals is verified as sufficient for OALVs operating under high light fluences. The optimum driving voltage for the AlN‐based OALV is determined to be ≈ 45 V pp at 100 Hz, achieving a transmittance of 91.3%, an extinction ratio (ER) of more than 100, and a 51:1 image contrast.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Real‐Time Optical Process Monitoring for Structure and Property Control of Aerosol Jet Printed Functional Materials

Abstract Aerosol jet printing is a popular digital additive manufacturing method for flexible and hybrid electronics, but it lacks sophisticated real‐time process control schemes that would enable more widespread adoption in manufacturing environments. Here, an optical measurement system is introduced to track the aerosol density upstream of the printhead. The measured optical extinction, combined with the aerosol flow rate, is directly related to deposition rate and accurately predicts functional materials properties such as the electrical resistance of printed graphene films. This real‐time system offers a compelling solution for process drift and batch‐to‐batch variability, rendering it a valuable tool for both real‐time control of aerosol jet printing and fundamental studies of the underlying process science.

Tafoya, Rebecca R.↗
DOE OSTI2025

Rare species do not disproportionately contribute to phylogenetic diversity in a subalpine plant community

Abstract Premise Within plant communities, few species are abundant, and most are locally rare. Worldwide, 36% of plant species are exceedingly rare and often face high extinction risk. However, the community phylogenetic impact of the loss of rare plants is largely unknown in many systems. We address this gap by investigating how rare species contribute to phylogenetic diversity, considering multiple metrics of rarity and multiple elevations in a subalpine plant community. Methods We collected abundance data at three sites near the Rocky Mountain Biological Laboratory (Colorado, USA). We calculated each species' range size from public occurrence data. We calculated phylogenetic signal for abundance and range size, compared community phylogenetic metrics weighted by range size and abundance to unweighted metrics, and quantified the change in phylogenetic diversity when removing single species and groups of species ranked by rarity. Results We found phylogenetic signal for abundance, but not range size. There was no difference between rarity‐weighted and ‐unweighted phylogenetic diversity metrics. Finally, phylogenetic diversity did not decline more when we removed single rare species or groups of rare species than when we removed single common species and groups of common species. Conclusions We found that rare species, whether at low abundance or with a small range, do not disproportionately contribute to phylogenetic diversity in our subalpine plant community. These results were consistent across elevations. Instead, rare species might provide phylogenetic redundancy with common species. Deeper understanding of functional differentiation is needed to understand contributions of rare species to this system.

Plant Sciences↗
DOE OSTI2022

In Situ Optical Quantification of Extracellular Electron Transfer Using Plasmonic Metal Oxide Nanocrystals**

Extracellular electron transfer (EET) is a critical form of microbial metabolism that enables respiration on a variety of inorganic substrates, including metal oxides. However, quantifying current generated by electroactive bacteria has been predominately limited to biofilms formed on electrodes. To address this, we developed a platform for quantifying EET flux from cell suspensions using aqueous dispersions of infrared plasmonic tin-doped indium oxide nanocrystals. Furthermore, tracking the change in optical extinction during electron transfer enabled quantification of current generated by planktonic Shewanella oneidensis cultures. Using this method, we differentiated between starved and actively respiring cells, cells of varying genotype, and cells engineered to differentially express a key EET gene using an inducible genetic circuit. Overall, our results validate the utility of colloidally stable plasmonic metal oxide nanocrystals as quantitative biosensors in aqueous environments and contribute to a fundamental understanding of planktonic S. oneidensis electrophysiology using simple in situ spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Increasing temperature weakens the positive effect of genetic diversity on population growth

Abstract Genetic diversity and temperature increases associated with global climate change are known to independently influence population growth and extinction risk. Whether increasing temperature may influence the effect of genetic diversity on population growth, however, is not known. We address this issue in the model protist system Tetrahymena thermophila . We test the hypothesis that at temperatures closer to the species’ thermal optimum (i.e., the temperature at which population growth is maximal, or T opt ), genetic diversity should have a weaker effect on population growth compared to temperatures away from the thermal optimum. To do so, we grew populations of T . thermophila with varying levels of genetic diversity at increasingly warmer temperatures and quantified their intrinsic population growth rate, r . We found that genetic diversity increases population growth at cooler temperatures, but that as temperature increases, this effect weakens. We also show that a combination of changes in the amount of expressed genetic diversity (G) in r , plastic changes in population growth across temperatures (E), and strong G × E interactions underlie this temperature effect. Our results uncover important but largely overlooked temperature effects that have implications for the management of small populations with depauperate genetic stocks in an increasingly warming world.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The complex circuitry of interactions determining coexistence among plants and mycorrhizal fungi

We present a mechanistic model of coexistence among a mycorrhizal fungus and one or two plant species that compete for a single nutrient. Plant–fungal coexistence is more likely if the fungus is better at extracting the environmental nutrient than the plant and the fungus acquires carbon from the plant above a minimum rate. When they coexist, their interaction can shift from mutualistic to parasitic at high nutrient availability. The fungus is a second nutrient source for plants and can promote the coexistence of two plant competitors if one is better at environmental nutrient extraction and the other is better at acquiring the nutrient from the fungus. Because it extracts carbon from both plants, the fungus also serves as a conduit of apparent competition between the plants. Consequently, the plant with the lower environmental nutrient extraction rate can drive the plant with the higher environmental nutrient extraction rate extinct at high carbon supply rates. Furthermore, this model illustrates mechanisms to explain several observed patterns, including shifts in plant–mycorrhizal growth responses and coexistence along nutrient gradients, equivocal results among experiments testing the effect of mycorrhizal fungi on plant diversity, and differences in plant diversity among ecosystems dominated by different mycorrhizal groups.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Inadvertent Hatchery Rainbow Trout Oncorhynchus mykiss Discovered in Native Westslope Cutthroat Trout Oncorhynchus clarkii lewisi Habitat: A Cautionary Tale

Abstract Fish hatcheries across North America release billions of fish into the wild every year to augment harvest opportunities in sport, commercial, and tribal fisheries, as well as to recover depressed populations. Despite these benefits, wild fish populations may be negatively affected when hatchery fish compete and/or hybridize with native species. Native Westslope Cutthroat Trout Oncorhynchus clarkii lewisi have decreased by 90% across their historic range; however, the Flathead River in Montana is a rangewide stronghold for these imperiled fish. The primary threat to Westslope Cutthroat Trout is hybridization with invasive Rainbow Trout O. mykiss, which leads to hybrid swarm formation and genomic extinction. We collected Rainbow Trout in Mill Creek, a tributary of the Flathead River, downstream from a hatchery that produces the species, and used otolith 87Sr/86Sr to determine whether individual fish were inadvertently introduced from the hatchery. Differences in 87Sr/86Sr among water samples from Mill Creek and the marine-derived hatchery food provided high-classification accuracy to determine the natal origins of Mill Creek Rainbow Trout. We found that 83 of the 106 Rainbow Trout collected (78%) were of hatchery origin. Otolith microstructure analysis indicated these fish had been in Mill Creek for ~1–32 weeks prior to capture. Our results illustrate the utility of otolith 87Sr/86Sr to identify hatchery fish in natural habitats and point to a source of invasive Rainbow Trout that pose conservation risks to native fishes in the drainage.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Southwest Pacific tropical cyclone development classification utilizing machine learning and synoptic composites

This study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated to predict the environment required for a depression to fully develop into a mature storm, and the most influential predictors in the classification decision are ranked. TD and TS are discriminated based on a maximum sustained wind speed threshold (≥17 ms -1 ). Various aerosol, thermodynamic, and dynamic parameters are extracted closest to the initiation point of each non-developing and developing sample. The covariates associated with each labelled sample are used to train a decision tree and random forest model. Results using a testing dataset suggest the random forest approach more accurately distinguishes between non-developing and developing samples. The classification accuracy of the decision tree and random forest are 72% and 91%, respectively. Random forest outperformed the decision tree by providing higher accuracy in test data. The most important variables for binary classification are sea salt aerosol optical depth (AOD), 1,000 mb relative humidity, and sea surface temperature. AOD is a quantitative estimate of the aerosols presents in the air through the extinction of a ray of light as it passes through the atmosphere. Mean composite maps constructed in an unsupervised manner have been created for the most important variables identified by the random forest classifier during TD and TS events to highlight the difference in geophysical and aerosol variables' climatology during the two different classifications. This work will advance the risk management strategies for northeastern Australia and other SWPO basin islands to control their tropical cyclone related losses through prioritizing forecasting variables that are the strongest predictors of the strengthening of tropical depressions into tropical cyclones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Activating Layered Metal Oxide Nanomaterials via Structural Engineering as Biodegradable Nanoagents for Photothermal Cancer Therapy

Layered metal oxides including MoO 3 and WO 3 have been widely explored for biological applications owing to their excellent biocompatibility, low toxicity, and easy preparation. However, they normally exhibit weak or negligible near-infrared (NIR) absorption and thus are inefficient for photo-induced biomedical applications. Herein, the structural engineering of layered MoO 3 and WO 3 nanostructures is first reported to activate their NIR-II absorption for efficient photothermal cancer therapy in the NIR-II window. White-colored micrometre-long MoO 3 nanobelts are transformed into blue-colored short, thin, defective, interlayer gap-expanded MoO 3–x nanobelts with a strong NIR-II absorption via the simple lithium treatment. The blue MoO 3–x nanobelts exhibit a large extinction coefficient of 18.2 L g –1 cm –1 and high photothermal conversion efficiency of 46.9% at 1064 nm. After surface modification, the MoO 3–x nanobelts can be used as a robust nanoagent for photoacoustic imaging-guided photothermal therapy to achieve efficient cancer cell ablation and tumor eradication under irradiation by a 1064 nm laser. Importantly, the biodegradable MoO 3–x nanobelts can be rapidly degraded and excreted from body. We report the study highlights that the structural engineering of layered metal oxides is a powerful strategy to tune their properties and thus boost their performances in given applications.

36 MATERIALS SCIENCE↗