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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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At least 19 records

Impact of particle arrays on phase separation composition patterns

We examine the symmetry-breaking effect of fixed constellations of particles on the surface-directed spinodal decomposition of binary blends in the presence of particles whose surfaces have a preferential affinity for one of the components. Our phase-field simulations indicate that the phase separation morphology in the presence of particle arrays can be tuned to have a continuous, droplet, lamellar, or hybrid morphology depending on the interparticle spacing, blend composition, and time. In particular, when the interparticle spacing is large compared to the spinodal wavelength, a transient target pattern composed of alternate rings of preferred and non-preferred phases emerges at early times, tending to adopt the symmetry of the particle configuration. We reveal that such target patterns stabilize for certain characteristic length, time, and composition scales characteristic of the pure phase-separating mixture. To illustrate the general range of phenomena exhibited by mixture-particle systems, we simulate the effects of single-particle, multi-particle, and cluster–particle systems having multiple geometrical configurations of the particle characteristic of pattern substrates on phase separation. Our simulations show that tailoring the particle configuration, or substrate pattern configuration, a relative fluid-particle composition should allow the desirable control of the phase separation morphology as in block copolymer materials, but where the scales accessible to this approach of organizing phase-separated fluids usually are significantly larger. Limited experiments confirm the trends observed in our simulations, which should provide some guidance in engineering patterned blend and other mixtures of technological interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A combinatorial model for dentate gyrus sparse coding

The dentate gyrus forms a critical link between the entorhinal cortex and CA3 by providing a sparse version of the signal. Concurrent with this increase in sparsity, a widely accepted theory suggests the dentate gyrus performs pattern separation—similar inputs yield decorrelated outputs. Although an active region of study and theory, few logically rigorous arguments detail the dentate gyrus’s (DG) coding. We suggest a theoretically tractable, combinatorial model for this action. The model provides formal methods for a highly redundant, arbitrarily sparse, and decorrelated output signal.To explore the value of this model framework, we assess how suitable it is for two notable aspects of DG coding: how it can handle the highly structured grid cell representation in the input entorhinal cortex region and the presence of adult neurogenesis, which has been proposed to produce a heterogeneous code in the DG. We find tailoring the model to grid cell input yields expansion parameters consistent with the literature. In addition, the heterogeneous coding reflects activity gradation observed experimentally. Lastly, we connect this approach with more conventional binary threshold neural circuit models via a formal embedding.

60 APPLIED LIFE SCIENCES↗

Dopamine-Mediated Polymer Coating Facilitates Area-Selective Atomic Layer Deposition

Area-selective atomic layer deposition (ALD) has the potential to significantly improve current fabrication approaches by introducing a bottom-up process in which robust and conformal thin films are selectively deposited onto patterned substrates. This bottom-up approach requires selective areas of the substrates to be masked to inhibit deposition. Spontaneous self-assembly and organization of a mask, incorporating adhesion and other functions, are particularly attractive for this role as they do not require a separate patterning step. In this work, we make use of the pH/light tunability of catechol adhesion to develop a catechol-functionalized polymer that exhibits tunable adhesion strengths on different materials based on their specific chemistry. Tunable selective deposition was shown between metal/metal oxide substrates by controlling the local pH. Moreover, by controlling the adhesion strength through UV light, the deposition of hafnium oxide (HfO 2 ) during ALD was successfully inhibited.

36 MATERIALS SCIENCE↗

CRCNS22 Learning Rules in the Hippocampus and their Mapping to Neuromorphic Systems (Final Technical Report)

Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.

59 BASIC BIOLOGICAL SCIENCES↗

A Shallow-Water Model for Convective Self-Aggregation

Randomly distributed convective storms can self-aggregate in the absence of large-scale forcings. Here we present a 1D shallow-water model to study the convective self-aggregation. This model simulates the dynamics of the planetary boundary layer and represents convection as a triggered process. Once triggered, convection lasts for finite time and occupies finite length. Here we show that the model can successfully simulate self-aggregation, and that the results are robust to a wide range of parameter values. In the simulations, convection excites gravity waves. The gravity waves then form a standing wave pattern, separating the domain into convectively active and inactive regions. We analyze the available potential energy (APE) budget and show that convection generates APE, providing energy for self-aggregation. By performing dimensional analysis, we develop a scaling theory for the size of convective aggregation, which is set by the gravity wave speed, damping time scale, and number density of convective storms. This paper provides a simple modeling framework to further study convective self-aggregation.

54 ENVIRONMENTAL SCIENCES↗

Foundry-compatible high-resolution patterning of vertically phase-separated semiconducting films for ultraflexible organic electronics

Solution processability of polymer semiconductors becomes an unfavorable factor during the fabrication of pixelated films since the underlying layer is vulnerable to subsequent solvent exposure. A foundry-compatible patterning process must meet requirements including high-throughput and high-resolution patternability, broad generality, ambient processability, environmentally benign solvents, and, minimal device performance degradation. However, known methodologies can only meet very few of these requirements. Here, a facile photolithographic approach is demonstrated for foundry-compatible high-resolution patterning of known p- and n-type semiconducting polymers. This process involves crosslinking a vertically phase-separated blend of the semiconducting polymer and a UV photocurable additive, and enables ambient processable photopatterning at resolutions as high as 0.5 μm in only three steps with environmentally benign solvents. The patterned semiconducting films can be integrated into thin-film transistors having excellent transport characteristics, low off-currents, and high thermal (up to 175 °C) and chemical (24 h immersion in chloroform) stability. Moreover, these patterned organic structures can also be integrated on 1.5 μm-thick parylene substrates to yield highly flexible (1 mm radius) and mechanically robust (5,000 bending cycles) thin-film transistors.

36 MATERIALS SCIENCE↗

Patterning of multicomponent elastic shells by gaussian curvature

Recent findings suggest that shell protein distribution and the morphology of bacterial microcompartments regulate the chemical fluxes facilitating reactions which dictate their biological function. Here, we explore how the morphology and component patterning are coupled through the competition of mean and gaussian bending energies in multicomponent elastic shells that form three-component irregular polyhedra. We observe two softer components with lower bending rigidities allocated on the edges and vertices while the harder component occupies the faces. When subjected to a nonzero interfacial line tension, the two softer components further separate and pattern into subdomains that are mediated by the gaussian curvature. We find that this degree of fractionation is maximized when there is a weaker line tension and when the ratio of bending rigidities between the two softer domains ≈2. Our results reveal a patterning mechanism in multicomponent shells that can capture the observed morphologies of bacterial microcompartments, and moreover, can be realized in synthetic vesicles.

Monte Carlo methods↗

Three practical workflow schedulers for easy maximum parallelism

Runtime scheduling and workflow systems are an increasingly popular algorithmic component in HPC because they allow full system utilization with relaxed synchronization requirements. There are so many special-purpose tools for task scheduling, one might wonder why more are needed. Use cases seen on the Summit supercomputer needed better integration with MPI and greater flexibility in job launch configurations. Preparation, execution, and analysis of computational chemistry simulations at the scale of tens of thousands of processors revealed three distinct workflow patterns. A separate job scheduler was implemented for each one using extremely simple and robust designs: file-based, task-list based, and bulk-synchronous. Comparing to existing methods shows unique benefits of this work, including simplicity of design, suitability for HPC centers, short startup time, and well-understood per-task overhead. All three new tools have been shown to scale to full utilization of Summit, and have been made publicly available with tests and documentation. This work presents a complete characterization of the minimum effective task granularity for efficient scheduler usage scenarios. Here, these schedulers have the same bottlenecks, and hence similar task granularities as those reported for existing tools following comparable paradigms.

97 MATHEMATICS AND COMPUTING↗

Multiple models and experiments underscore large uncertainty in soil carbon dynamics

Soils contain more carbon than plants or the atmosphere, and sensitivities of soil organic carbon (SOC) stocks to changing climate and plant productivity are a major uncertainty in global carbon cycle projections. Despite a consensus that microbial degradation and mineral stabilization processes control SOC cycling, no systematic synthesis of long-term warming and litter addition experiments has been used to test process-based microbe-mineral SOC models. We explored SOC responses to warming and increased carbon inputs using a synthesis of 147 field manipulation experiments and five SOC models with different representations of microbial and mineral processes. Model projections diverged but encompassed a similar range of variability as the experimental results. Experimental measurements were insufficient to eliminate or validate individual model outcomes. While all models projected that CO 2 efflux would increase and SOC stocks would decline under warming, nearly one- third of experiments observed decreases in CO 2 flux and nearly half of experiments observed increases in SOC stocks under warming. Long-term measurements of C inputs to soil and their changes under warming are needed to reconcile modeled and observed patterns. Measurements separating the responses of mineral- protected and unprotected SOC fractions in manipulation experiments are needed to address key uncertainties in microbial degradation and mineral stabilization mechanisms. Conclusively, integrating models with experimental design will allow targeting of these uncertainties and help to reconcile divergence among models to produce more confident projections of SOC responses to global changes.

54 ENVIRONMENTAL SCIENCES↗

Groundwater Circulation Within the Mountain Block: Combining Flow and Transport Models With Magnetotelluric Observations to Untangle Its Nested Nature

Abstract Mountains are vital water sources for humans and ecosystems, continuously replenishing lowland aquifers through surface runoff and mountain recharge. Quantifying these fluxes and their relative importance is essential for sustainable water resource management. However, our mechanistic understanding of the flow and transport processes determining the connection between the mountain block and the basin aquifer remains limited. Traditional conceptualizations assume groundwater circulation within the mountain block is predominantly shallow. This view neglects the role of deep groundwater flowpaths significantly contributing to the water, solute, and energy budgets. Overcoming these limitations requires a holistic characterization of the multiscale nature of groundwater flow along the mountain‐to‐valley continuum. As a proof‐of‐concept, we use a coupled groundwater flow and transport model to design a series of numerical experiments that explore the role of geology, topography, and weathering rates in groundwater circulation and their resulting resistivity patterns. Our results show that accumulating solutes near stagnation zones create contrasting electrical resistivity patterns that separate local, intermediate, and regional flow cells, presenting a target for magnetotelluric observations. To demonstrate the sensitivity of magnetotelluric data to features in our resistivity models, we use the MARE2DEM electromagnetic modeling code to perform forward and inverse simulations. This study highlights the potential of magnetotelluric surveys to image the resistivity structure resulting from multiscale groundwater circulation through relatively impervious crystalline basement rocks in mountainous terrains. This capability could change our understanding of the critical zone, offering a holistic perspective that includes deep groundwater circulation and its role in conveying solutes and energy.

54 ENVIRONMENTAL SCIENCES↗

On-sky performance analysis of the vector apodizing phase plate coronagraph on MagAO/Clio2

We report on the performance of a vector apodizing phase plate coronagraph that operates over a wavelength range of 2–5 μm and is installed in MagAO/Clio2 at the 6.5 m Magellan Clay telescope at Las Campanas Observatory, Chile. The coronagraph manipulates the phase in the pupil to produce three beams yielding two coronagraphic point-spread functions (PSFs) and one faint leakage PSF. The phase pattern is imposed through the inherently achromatic geometric phase, enabled by liquid crystal technology and polarization techniques. The coronagraphic optic is manufactured using a direct-write technique for precise control of the liquid crystal pattern and multitwist retarders for achromatization. By integrating a linear phase ramp to the coronagraphic phase pattern, two separated coronagraphic PSFs are created with a single pupil-plane optic, which makes it robust and easy to install in existing telescopes. The two coronagraphic PSFs contain a 180° dark hole on each side of a star, and these complementary copies of the star are used to correct the seeing halo close to the star. To characterize the coronagraph, we collected a data set of a bright (m{sub L} = 0–1) nearby star with ∼1.5 hr of observing time. By rotating and optimally scaling one PSF and subtracting it from the other PSF, we see a contrast improvement by 1.46 magnitudes at 3.5 λ/D. With regular angular differential imaging at 3.9 μm, the MagAO vector apodizing phase plate coronagraph delivers a 5σ Δmag contrast of 8.3 (=10{sup −3.3}) at 2 λ/D and 12.2 (=10{sup −4.8}) at 3.5 λ/D.

79 ASTRONOMY AND ASTROPHYSICS↗

Device and method for the location and identification of a radiation source

A handheld device for the location and identification of a radiation source, including: a radiation transparent housing; a radiation locator device disposed within the radiation transparent housing operable for determining the location of the radiation source, wherein the radiation locator device includes a plurality of gamma detection crystals arranged in a geometric pattern and separated by a gamma shielding material, a plurality of detectors coupled to the plurality of gamma detection crystals, and a processor module coupled to the plurality of detectors; one or more of a neutron detection crystal and a gamma spectroscopy crystal disposed within the radiation transparent housing adjacent to the radiation locator device; and one or more detectors coupled to the one or more of the neutron detection crystal and the gamma spectroscopy crystal and the processor module; wherein the one or more of the neutron detection crystal and the gamma spectroscopy crystal, the one or more detectors, and the processor module are collectively operable for identifying the radiation source.

Vencelj, Matjaz↗

System and method for large-scale PCB production including continuous selective adhesion

A method for the large-scale production of PCBs including a continuous selective adhesion process for creating printed circuit traces providing input to a production line. A roll of printed circuit traces is produced using rolls of flexible substrate, conductive layer, and conductive layer support by applying adhesive between the rolls of flexible substrate and conductive layer, bringing the rolls together, transferring a circuit pattern onto the flexible substrate, curing the adhesive through non-opaque areas of the circuit pattern, and separating the non-bonded areas. The resulting printed circuit traces are applied from the roll to mounts, and circuit components are applied from a roll to the traces as the mounts move along the line. Additional rolls of printed circuit traces and circuit components may be incorporated, and multi-layer PCBs may be produced. As part of the production line, the finished PCBs may be applied to flat or contoured products.

Hatch, Jonathan Douglas↗

Community response of soil microorganisms to combined contamination of polycyclic aromatic hydrocarbons and potentially toxic elements in a typical coking plant

Both polycyclic aromatic hydrocarbons (PAHs) and potentially toxic elements (PTEs) of coking industries impose negative effects on the stability of soil ecosystem. Soil microbes are regarded as an essential moderator of biochemical processes and soil remediation, while their responses to PAHs-PTEs combined contamination are largely unknown. In the present study, soil microbial diversity and community composition in the typical coking plant under the chronic co-exposure of PAHs and PTEs were investigated and microbial interaction networks were built to reveal microbial co-occurrence patterns. The results indicated that the concentrations of PAHs in the soil inside the coking plant were significantly higher than those outside the plant. The mean concentration of ∑16PAHs was 2894.4 ng·g −1 , which is 5.58 times higher than that outside the plant. The average Hg concentration inside the coking plant was 22 times higher than the background value of Hebei province. The soil fungal community inside the coking plant showed lower richness compared with that of outside community, and there are significant difference in the bacterial and fungal community composition between inside and outside of coking plant ( p < 0.01). Predicted contribution of different environmental factors to each dominant species based on random forest identified 20 and 25 biomarkers in bacteria and fungi, respectively, that were highly sensitive to coking plant soil in operation, such as Betaproteobacteria,Sordariomycetes and Dothideomycetes . Bacterial and fungal communities were shaped by the soil chemical properties (pH), PTEs (Hg), and PAHs together in the coking plant soils. Furthermore, the bacterial and fungal interaction patterns were investigated separately or jointly by intradomain and interdomain networks. Competition is the main strategy based on the co-exclusion pattern in fungal community, and the competitive relationship inside the coking plant is more complex than that outside the plant. In contrast, cooperation is the dominant strategy in bacterial networks based on the co-occurrence pattern. The present study provided insights into microbial response strategies and the interactions between bacteria and fungi under long-term combined contamination.

Shen, Qihui↗

Differential Fragmentation of Mobility-Selected Glycans via Ultraviolet Photodissociation and Ion Mobility-Mass Spectrometry

The alternative dissociation pathways initiated by ultraviolet photodissociation (UVPD) compared with collision-induced dissociation (CID) may provide useful diagnostic fragments for biomolecule identification, including glycans. However, underivatized glycans do not commonly demonstrate strong UV absorbance, resulting in low fragmentation yields for UVPD spectra. In contrast to UVPD experiments that leverage covalent modification of glycans, we detail the capacity of metal adduction to yield comparatively rich UVPD fragmentation patterns and enhance separation factors for an isomeric glycan set in a drift tube ion mobility system. Ion mobility and UVPD-MS spectra for two N-acetyl glycan isomers were examined, each adducted with sodium or cobalt cations, with the latter providing fragment yield gains of an order of magnitude versus sodium adducts. Furthermore, our glycan analysis incorporated front-end ion mobility separation such that the structural glycan isomers could still be identified even as a mixture and not simply composite spectra of isomeric standards. Cobalt adduction proved influential in the glycan separation by yielding an isomer resolution of 0.78 when analyzed simultaneously versus no discernable separation obtained with the sodium adducts. It is the combined enhancement of both isomeric drift time separation and isomer distinction with improved UVPD fragment ion yields that further bolster multivalent metal adduction for advancing glycan IM-MS experiments. .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of quasi-two- and three-dimensional ordered porous structures by means of small-angle X-ray scattering in the grazing incidence geometry

The structure of surface layers of thin metal inverse opals has been studied first by the grazing-incidence small-angle X-ray scattering technique. Contributions of the form factor and structure factor to the small-angle diffraction pattern have been separated using a numerical model of the scattering process. The complementary use of the small-angle X-ray scattering and grazing-incidence small-angle X-ray scattering techniques has provided independent information about the bulk and surface properties of the samples and allowed a type of defect in the investigated structures to be determined. The measurement results have been verified by atomic force microscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Machine-learning-assisted analysis of transition metal dichalcogenide thin-film growth

In situ reflective high-energy electron diffraction (RHEED) is widely used to monitor the surface crystalline state during thin-film growth by molecular beam epitaxy (MBE) and pulsed laser deposition. With the recent development of machine learning (ML), ML-assisted analysis of RHEED videos aids in interpreting the complete RHEED data of oxide thin films. The quantitative analysis of RHEED data allows us to characterize and categorize the growth modes step by step, and extract hidden knowledge of the epitaxial film growth process. In this study, we employed the ML-assisted RHEED analysis method to investigate the growth of 2D thin films of transition metal dichalcogenides (ReSe2) on graphene substrates by MBE. Principal component analysis (PCA) and K-means clustering were used to separate statistically important patterns and visualize the trend of pattern evolution without any notable loss of information. Using the modified PCA, we could monitor the diffraction intensity of solely the ReSe2 layers by filtering out the substrate contribution. These findings demonstrate that ML analysis can be successfully employed to examine and understand the film-growth dynamics of 2D materials. Further, the ML-based method can pave the way for the development of advanced real-time monitoring and autonomous material synthesis techniques.

36 MATERIALS SCIENCE↗