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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Impact of Inherited Morphology on Sandbar Migration During Mild Wave Seasons

Sandbars are ubiquitous morphologic features found in the nearshore environment throughout the world, yet predictive capabilities of their evolution remain limited. In order to provide new insights on the relevant processes controlling sandbar morphodynamics, this study uses a 41-year record of 637 monthly cross-shore profiles from Duck, North Carolina, USA, to derive complex empirical orthogonal functions representative of the two dominant modes of sandbar migrations: offshore and onshore propagation. Interference of these two modes produces commonly observed sandbar states. While mild wave energies are traditionally assumed to drive onshore sandbar migration, the offshore mode is repeatedly seen to dominate sandbar migration in mild wave seasons following anomalously high late-winter wave energy and when the inherited morphology is composed of a single bar or terrace, as opposed to a more common two-bar state. A data-derived conceptual model is presented synthesizing the effect of antecedent morphology and wave climate chronology on interannual trends in net offshore sandbar migration.

58 GEOSCIENCES↗
DOE OSTI2022

Electrical resistance of the current collector controls lithium morphology

Abstract The electrodeposition of low surface area lithium is critical to successful adoption of lithium metal batteries. Here, we discover the dependence of lithium metal morphology on electrical resistance of substrates, enabling us to design an alternative strategy for controlling lithium morphology and improving electrochemical performance. By modifying the current collector with atomic layer deposited conductive (ZnO, SnO 2 ) and resistive (Al 2 O 3 ) nanofilms, we show that conductive films promote the formation of high surface area lithium deposits, whereas highly resistive films promote the formation of lithium clusters of low surface area. We reveal an electrodeposition mechanism in which radial diffusion of electroactive species is promoted on resistive substrates, resulting in lateral growth of large (150 µm in diameter) planar lithium deposits. Using resistive substrates, similar lithium morphologies are formed in three distinct classes of electrolytes, resulting in up to ten-fold improvement in battery performance. Ultimately, we report anode-free pouch cells using the Al 2 O 3 -modified copper that maintain 60 % of their initial discharge capacity after 100 cycles, displaying the benefits of resistive substrates for controlling lithium electrodeposition.

25 ENERGY STORAGE↗
DOE OSTI2023

All-polymer organic solar cells with nano-to-micron hierarchical morphology and large light receiving angle

Distributed photovoltaics in living environment harvest the sunlight in different incident angles throughout the day. The development of planer solar cells with large light-receiving angle can reduce the requirements in installation form factor and is therefore urgently required. Here, thin film organic photovoltaics with nano-sized phase separation integrated in micro-sized surface topology is demonstrated as an ideal solution to proposed applications. All-polymer solar cells, by means of a newly developed sequential processing, show large magnitude hierarchical morphology with facilitated exciton-to-carrier conversion. The nano fibrilar donor-acceptor network and micron-scale optical field trapping structure in combination contributes to an efficiency of 19.06% (certified 18.59%), which is the highest value to date for all-polymer solar cells. Furthermore, the micron-sized surface topology also contributes to a large light-receiving angle. A 30% improvement of power gain is achieved for the hierarchical morphology comparing to the flat-morphology devices. These inspiring results show that all-polymer solar cell with hierarchical features are particularly suitable for the commercial applications of distributed photovoltaics due to its low installation requirement.

14 SOLAR ENERGY↗
DOE OSTI2022

MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Morphologically-Directed Raman Spectroscopy as an Analytical Method for Subvisible Particle Characterization in Therapeutic Protein Product Quality

Abstract Subvisible particles (SVPs) are a critical quality attribute of injectable therapeutic proteins (TPs) that needs to be controlled due to potential risks associated with drug product quality. The current compendial methods routinely used to analyze SVPs for lot release provide information on particle size and count. However, chemical identification of individual particles is also important to address root-cause analysis. Herein, we introduce Morphologically-Directed Raman Spectroscopy (MDRS) for SVP characterization of TPs. The following particles were used for method development: (1) polystyrene microspheres, a traditional standard used in industry; (2) photolithographic (SU-8); and (3) ethylene tetrafluoroethylene (ETFE) particles, candidate reference materials developed by NIST. In our study, MDRS rendered high-resolution images for the ETFE particles (> 90%) ranging from 19 to 100 μm in size, covering most of SVP range, and generated comparable morphology data to flow imaging microscopy. Our method was applied to characterize particles formed in stressed TPs and was able to chemically identify individual particles using Raman spectroscopy. MDRS was able to compare morphology and transparency properties of proteinaceous particles with reference materials. The data suggests MDRS may complement the current TPs SVP analysis system and product quality characterization workflow throughout development and commercial lifecycle.

Science & Technology - Other Topics↗
DOE OSTI2020

Optically tunable mesoscale CdSe morphologies via inorganic phototropic growth

Inorganic phototropic growth using only spatially conformal illumination generated Se–Cd films that exhibited precise light-defined mesoscale morphologies including highly ordered, anisotropic, and periodic ridge and trench nanotextures over entire macroscopic substrates. Growth was accomplished via a light-induced electrochemical method using an optically and chemically isotropic solution, an unpatterned substrate, and unstructured, incoherent, low-intensity illumination in the absence of chemical directing agents or physical templates and masks. The morphologies were defined by the illumination inputs: the nanotexture long axes aligned parallel to the optical E-field vector, and the feature sizes and periods scaled with the wavelength. Optically based modeling of the growth closely reproduced the experimental results, confirming the film morphologies were fully determined by the light–matter interactions during growth. Solution processing of the Se–Cd films resulted in stoichiometric, crystalline CdSe films that also exhibited ordered nanotextures, demonstrating that inorganic phototropic growth can effect tunable, template-free generation of ordered CdSe nanostructures over macroscopic length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Charge generation mechanism tuned via film morphology in small molecule bulk-heterojunction photovoltaic materials

Small organic molecules have emerged as promising component materials for organic photovoltaic devices. Compared to most conjugated polymers for the same application, small molecules have unique morphologies that promote electronic processes relevant to organic solar cell (OSC) function that can be significantly different from those of conjugated polymeric materials. Here we investigate constituent loading-dependent effects on OSC morphology and function using the classical fullerene acceptor, PC 61 BM, in a heterojunction blend with the small molecule donor, NDT (thiophene-capped diketopyrrolopyrrole naphthodithiophene). The evolution of active layer morphology as well as exciton speciation and dynamics as a function of the PC 61 BM content are examined in combined structural studies using GIWAXS and spectroscopic studies using transient absorption spectroscopy. We observe evidence for three types of coexisting excitons and details of the interplay between them determines the yield of charge separated states that afford sustained device efficiency.

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

Engineering endosomolytic nanocarriers of diverse morphologies using confined impingement jet mixing

The clinical translation of many biomolecular therapeutics has been hindered by undesirable pharmacokinetic (PK) properties, inadequate membrane permeability, poor endosomal escape and cytosolic delivery, and/or susceptibility to degradation. Overcoming these challenges merits the development of nanoscale drug carriers (nanocarriers) to improve the delivery of therapeutic cargo. Herein, we implement a flash nanoprecipitation (FNP) approach to produce nanocarriers of diverse vesicular morphologies by using various molecular weight PEG-bl-DEAEMA-co-BMA (PEG-DB) polymers. We demonstrated that FNP can produce uniform (PDI < 0.1) particles after 5 impingements, and that by varying the copolymer hydrophilic mass fraction, FNP enables access to a diverse variety of nanoarchitectures including micelles, unilamellar vesicles (polymersomes), and multi-compartment vesicles (MCVs). We synthesized a library of 2 kDa PEG block copolymers, with DEAEMA-co-BMA second block molecular weights of 3, 6, 12, 15, 20, and 30 kDa. All formulations were both pH responsive, endosomolytic, and capable of loading and cytosolically delivering small negatively charged molecules – albeit to different degrees. Using a B16.F10 melanoma model, we showcased the therapeutic potential of a lead FNP formulated PEG-DB nanocarrier, encapsulating the cyclic dinucleotide (CDN) cGAMP to activate the stimulator of interferon genes (STING) pathway in a therapeutically relevant context. Collectively, these data demonstrate that an FNP process can be used to formulate pH-responsive nanocarriers of diverse morphologies using a PEG-DB polymer system. As FNP is an industrially scalable process, these data address the critical translational challenge of producing PEG-DB nanoparticles at scale. Furthermore, the diverse morphologies produced may specialize in the delivery of distinct biomolecular cargos for other therapeutic applications, implicating the therapeutic potential of this platform in an array of disease applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Morphology of poly-3-hexyl-thiophene blends with styrene–isoprene–styrene block-copolymer elastomers from X-ray and neutron scattering

The nano- and micron scale morphology of poly(3-hexylthiophene) (P3HT) and polystyrene-block-polyisoprene-block-polystyrene (PS–PI–PS) elastomeric blends is investigated through the use of ultra-small and small angle X-ray and neutron scattering (USAXS, SAXS, SANS). It is demonstrated that loading P3HT into elastomer matrices is possible with little distortion of the elastomeric structure up to a loading of ~5 wt%. Increased loadings of conjugated polymer is found to significantly distort the matrix structure. Changes in processing conditions are also found to affect the blend morphology with especially strong dependence on processing temperature. Processing temperatures above the glass transition temperature (T g ) of polystyrene and the melting temperature (T m ) of the conjugated polymer additive (P3HT) creates significantly more organized mesophase domains. P3HT blends with PS–PI–PS can also be flow-aligned through processing, which results in an anisotropic structure that could be useful for the generation of anisotropic properties (e.g. conductivity). Moreover, the extent of flow alignment is significantly affected by the P3HT loading in the PS–PI–PS matrix. The work adds insight to the morphological understanding of a complex P3HT and PS–PI–PS polymer blend as conjugated polymer is added to the system. Here, we also provide studies isolating the effect of processing changes aiding in the understanding of the structural changes in this elastomeric conjugated polymer blend.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Hole formation effect on surface morphological response of plasma-facing tungsten

We report simulation results on the effect of helium (He) bubble bursting-mediated surface hole formation on the surface morphological response of tungsten plasma-facing components (PFCs) in nuclear fusion devices. Our analysis is based on an atomistically informed, continuum-scale model, which is capable of accessing the spatiotemporal scales relevant to the fuzz nanostructure formation process on the surface of PFC tungsten. Our simulations account, in an empirical fashion, for two types of subsurface bubble dynamical phenomena in the nanobubble region of PFC tungsten during He plasma irradiation, involving bubble bursting and surface crater formation. We demonstrate that the hole formation effect on the PFC tungsten surface accelerates the growth rate of nanotendrils and the onset of fuzz formation. As a result, the predicted incubation time for surface nanotendril growth is shortened, in agreement with experimental data of incubation fluence at comparable plasma exposure conditions. We also explore systematically the dependence of the PFC surface morphological response on the areal density of holes introduced at regular time intervals onto the He-implanted tungsten surface, a parameter in our analysis that serves as a proxy for the rate of He bubble bursting. More importantly, our simulations capture fine surface features in the PFC tungsten surface morphology and predict that the average spacing between nanotendrils is on the order of 100 nm, consistent with the experimental findings.

Chen, Chao-Shou (ORCID:0000000307910042)↗
DOE OSTI2022

Controlling morphology in hybrid isotropic/patchy particle assemblies

Brownian dynamics is used to study self-assembly in a hybrid system of isotropic particles (IPs), combined with anisotropic building blocks that represent special “designer particles.” Those are modeled as spherical patchy particles (PPs) with binding only allowed between their patches and IPs. In this study, two types of PPs are considered: Octahedral PPs (Oh-PPs) and Square PPs (Sq-PPs), with octahedral and square arrangements of patches, respectively. The self-assembly is additionally facilitated by the simulated annealing procedure. Here, the resultant structures are characterized by a combination of local correlations in cubatic ordering and a symmetry-specific variation of bond orientation order parameters (SymBOPs). By varying the PP/IP size ratio, we detected a sharp crossover between two distinct morphologies in both types of systems. High symmetry phases, NaCl crystal for Oh-PP and square lattice for Sq-PP, are observed for larger size ratios. For the smaller ones, the dominant morphologies are significantly different, e.g., Oh-PPs form a compact amorphous structure with predominantly face-to-face orientation of neighboring PPs. Unusually, for a morphology without a long-range order, it is still possible to identify well organized coherent clusters of this structure, thanks to the adoption of our SymBOP-based characterization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Particle-based hematite crystallization is invariant to initial particle morphology

Significance Many crystallization processes occurring in nature produce highly ordered hierarchical architectures. Their formation cannot be explained using classical models of monomer-by-monomer growth. One of the possible pathways involves crystallization through the attachment of oriented nanocrystals. Thus, it requires detailed understanding of the mechanism of particle dynamics that leads to their precise crystallographic alignment along specific faces. In this study, we discover a particle-morphology–independent oriented attachment mechanism for hematite nanocrystals. Independent of crystal morphology, particles always align along the [001] direction driven by aligning interactions between (001) faces and repulsive interactions between other pairs of hematite faces. These results highlight that strong face specificity along one crystallographic direction can render oriented attachment to be independent of initial particle morphology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Morphological Model to Separate Resolved–Unresolved Sources in the DESI Legacy Surveys: Application in the LS4 Alert Stream

Separating resolved and unresolved sources in large imaging surveys is a fundamental step to enable downstream science, such as searching for extragalactic transients in wide-field time-domain surveys. Here we present our method to effectively separate point sources from the resolved, extended sources in the Dark Energy Spectroscopic Instrument (DESI) Legacy Surveys (LS). We develop a supervised machine learning model based on the Gradient Boosting algorithm XGBoost. The features input to the model are purely morphological and are derived from the tabulated LS data products. We train the model using ∼2 × 10 5 LS sources in the COSMOS field with HST morphological labels and evaluate the model performance on LS sources with spectroscopic classification from the DESI Data Release 1 (∼2 × 10 7 objects) and the Sloan Digital Sky Survey Data Release 17 (∼3 × 10 6 objects), as well as on ∼2 × 10 8 Gaia stars. A significant fraction of LS sources are not observed in every LS filter, and we therefore build a “Hybrid” model as a linear combination of two XGBoost models, each containing features combining aperture flux measurements from the “blue” (gr) and “red” (iz) filters. The Hybrid model shows a reasonable balance between sensitivity and robustness, and achieves higher accuracy and flexibility compared to the LS morphological typing. With the Hybrid model, we provide classification scores for ∼3 × 10 9 LS sources, making this the largest ever machine learning catalog separating resolved and unresolved sources. The catalog has been incorporated into the real-time pipeline of the La Silla Schmidt Southern Survey (LS4), enabling the identification of extragalactic transients within the LS4 alert stream.

astrostatistics↗
DOE OSTI2025

Inferring Neutron Star Merger Ejecta Morphology with Kilonovae

In this study we incorporate a new grid of kilonova simulations produced by the Monte Carlo radiative transfer code SuperNu in an inference pipeline for astrophysical transients and evaluate their performance. These simulations contain four different two-component ejecta morphology classes. We analyze follow-up observational strategies by Vera Rubin Observatory in optical and James Webb Space Telescope (JWST) in mid-infrared (MIR). Our analysis suggests that, within these strategies, it is possible to discriminate between the four different morphologies only when late-time JWST observations in MIR are available. We conclude that follow-ups by the new Vera Rubin Observatory alone are not sufficient to determine ejecta morphology. Additionally, we make comparisons between surrogate models based on radiative transfer simulation grids by SuperNu and POSSIS, by analyzing the historic kilonova AT2017gfo that accompanied the gravitational wave event GW170817. We show that both SuperNu and POSSIS models provide similar fits to photometric observations but their qualitative interpretations differ.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Stellar angular momentum distribution linked to galaxy morphology

ABSTRACT We study the spatially resolved stellar specific angular momentum j* in a high-quality sample of 24 Calar Alto Legacy Integral Field Area galaxies covering a broad range of visual morphology, accounting for stellar velocity and velocity dispersion. The shape of the spaxelwise probability density function of normalized s = j*/j*mean, PDF(s), deviates significantly from the near-universal initial distribution expected of baryons in a dark matter halo and can be explained by the expected baryonic effects in galaxy formation that remove and redistribute angular momentum. Further we find that the observed shape of the PDF(s) correlates significantly with photometric morphology, where late-type galaxies have a PDF(s) that is similar to a normal distribution, whereas early types have a strongly skewed PDF(s) resulting from an excess of low-angular momentum material. Galaxies that are known to host pseudo-bulges (bulge Sérsic index nb < 2.2) tend to have less skewed bulge PDF(s), with skewness (b1rb) ≲ 0.8. The PDF(s) encodes both kinematic and photometric information and appears to be a robust tracer of morphology. Its use is motivated by the desire to move away from traditional component-based classifications which are subject to observer bias, to classification on a galaxy’s fundamental (stellar mass and angular momentum) properties. In future, PDF(s) may also be useful as a kinematic decomposition tool.

Sweet, Sarah M.↗
DOE OSTI2021

SDSS-IV DR17: final release of MaNGA PyMorph photometric and deep-learning morphological catalogues

ABSTRACT We present the MaNGA PyMorph photometric Value Added Catalogue (MPP-VAC-DR17) and the MaNGA Deep Learning Morphological VAC (MDLM-VAC-DR17) for the final data release of the MaNGA survey, which is part of the SDSS Data Release 17 (DR17). The MPP-VAC-DR17 provides photometric parameters from Sérsic and Sérsic+Exponential fits to the two-dimensional surface brightness profiles of the MaNGA DR17 galaxy sample in the g, r, and i bands (e.g. total fluxes, half-light radii, bulge-disc fractions, ellipticities, position angles, etc.). The MDLM-VAC-DR17 provides deep-learning-based morphological classifications for the same galaxies. The MDLM-VAC-DR17 includes a number of morphological properties, for example, a T-Type, a finer separation between elliptical and S0, as well as the identification of edge-on and barred galaxies. While the MPP-VAC-DR17 simply extends the MaNGA PyMorph photometric VAC published in the SDSS Data Release 15 (MPP-VAC-DR15) to now include galaxies that were added to make the final DR17, the MDLM-VAC-DR17 implements some changes and improvements compared to the previous release (MDLM-VAC-DR15): Namely, the low end of the T-Types is better recovered in this new version. The catalogue also includes a separation between early or late type, which classifies the two populations in a complementary way to the T-Type, especially at the intermediate types (−1 < T-Type < 2), where the T-Type values show a large scatter. In addition, k-fold-based uncertainties on the classifications are also provided. To ensure robustness and reliability, we have also visually inspected all the images. We describe the content of the catalogues and show some interesting ways in which they can be combined.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

On the morphology of the gamma-ray galactic centre excess

ABSTRACT The characteristics of the galactic centre excess (GCE) emission observed in gamma-ray energies – especially the morphology of the GCE – remain a hotly debated subject. The manner in which the dominant diffuse gamma-ray background is modelled has been claimed to have a determining effect on the preferred morphology. In this work, we compare two distinct approaches to the galactic diffuse gamma-ray emission background: the first approach models this emission through templates calculated from a sequence of well-defined astrophysical assumptions, while the second approach divides surrogates for the background gamma-ray emission into cylindrical galactocentric rings with free independent normalizations. At the latitudes that we focus on, we find that the former approach works better, and that the overall best fit is obtained for an astrophysically motivated fit when the GCE follows the morphology expected of dark matter annihilation. Quantitatively, the improvement compared with the best ring-based fits is roughly 6500 in the χ2 and roughly 4000 in the log of the Bayesian evidence.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Morphological traits for allometric scaling of the European Sea Bass Dicentrarchus labrax (Linnaeus, 1758) from Southern Portugal population

Abstract The present study aimed to determine the allometric scaling among a selection of morphological traits in European sea bass ( Dicentrarchus labrax ) to estimate fish body weight. A set of morphological traits (fish body weight, length, height, and width) were directly measured in 146 fish of a recirculating aquaculture system, with body weights ranging from 17.11 to 652.21 g. In addition, a collection of digital imagery of each anesthetized fish from the side and top views were used to estimate other traits (indirect measures). Multiple regression analysis and regression coefficients were calculated using all possible combinations of biometric data (predictors) to estimate fish body weight, applying different numerical fitting models (linear, log‐linear, quadratic, exponential). The results showed that the best combination of traits for estimating fish body weight were fish body width, length and height, collected from direct measure ( R 2 = 0.995), for a log‐linear model fitting, which revealed more accurate determinations than the most commonly used length–weight relationship. Nevertheless, other combinations of morphological traits and fitting models were also found to be suitable in successfully predict fish body weight, with variability ranging between 92.5% and 98.5%. For indirect measures, the best predictor was a combination of traits from top view (width, eye distance and area without fins) fitted with a log‐linear function. These results comprise a relevant baseline in supporting the high potential of noninvasive methods to accurately follow the growth of European sea bass juveniles, recurring to imagery analysis of anesthetized fish. It has major potential applications in feeding consumption trials and fish growth models, as it allows for continuously following up fish growth under different experimental conditions without therein distress derived from manipulation.

Azevedo, Ana↗