Soil bacterial populations are shaped by recombination and gene-specific selection across a grassland meadow
Not Available
54 ENVIRONMENTAL SCIENCES↗
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Results for “Shape selectivity”
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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A comparison of strategies for state-selective coherent Raman excitation
Here we report on the theoretical and experimental evaluation of state-selective bond activation for coherent Raman spectroscopy and control of chemical reactivity. We compare six different strategies for state-selective activation using shaped broadband femtosecond laser pulses. Results for a pair of long pulses with different wavelengths are also considered. For each of these approaches, we report on their theoretical and experimental ability to excite a desired vibrational mode while minimizing excitation of other modes including harmonics. We find that the double parabola spectral phase function gives the most intense Raman excitation with 10 cm -1 selectivity with the lowest background. The sinusoidal phase function produces intense Raman excitation with high selectivity but gives a series of harmonic excitations which could hinder selectivity. Implications of this study on several fields ranging from sensing, to controlling chemical reactions, and selective excited state excitation by X-ray pulses are discussed.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Two-Step Time-Series Data Clustering Method for Building-Level Load Profile
Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. The load profiles in the same group will have similar characteristics at the same time step, so grid operators can send the grid service signal to the customer group with a higher chance to respond at that time step. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation. In our two-step clustering approach, we first calculate the total load consumption for each building, clustering the load profiles based on energy consumption level. Then, we further cluster the load profiles in each energy cluster based on the load shape. The parameter selection for each clustering step is discussed. The proposed method is applied on actual building-level load profiles, and the results have proved the effectiveness of this method.
advanced metering infrastructure (AMI)↗
A Two-Step Time-Series Data Clustering Method for Building-Level Load Profile: Preprint
Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation. In our two-step clustering approach, we first calculate the total load consumption for each building, clustering the load profiles based on energy consumption level. Then, we further cluster the load profiles in each energy cluster based on the load shape. The parameter selection for each clustering step is discussed. The proposed method is applied on actual building-level load profiles, and the results have proved the effectiveness of this method.
advanced metering infrastructure (AMI)↗
Inkjet-Based 3D Printing: From Quantum Dots to Steel Tools
Inkjet-based additive manufacturing (AM) technologies are highly versatile among manufacturing processes due to their ability to shape any material in powder or ink form. The two inkjet-based AM technologies are binder jetting and material jetting, and as each of their names suggest, the former uses inkjet to deposit binder into the actual build material and the latter uses inkjet to deposit the actual build material. With each of these technologies comes unique opportunities in the form of embedding functional components within the build, creating material gradients within parts by selectively layering feedstocks, shaping non-weldable materials, and creating low-cost tooling with conformal cooling channels. Dr. Amy Elliott at Oak Ridge National Laboratory has explored a variety of materials and approaches with inkjet-based manufacturing technologies, focusing on industry-relevant applications such as injection molding tooling and mining drills.
Elliott, Amy↗
Modelling galaxy cluster triaxiality in stacked cluster weak lensing analyses
Counts of galaxy clusters offer a high-precision probe of cosmology, but control of systematic errors will determine the accuracy of this measurement. Using Buzzard simulations, we quantify one such systematic, the triaxiality distribution of clusters identified with the redMaPPer optical cluster finding algorithm, which was used in the Dark Energy Survey Year-1 (DES Y1) cluster cosmology analysis. We test whether redMaPPer selection biases the clusters’ shape and orientation and find that it only biases orientation, preferentially selecting clusters with their major axes oriented along the line of sight. Modelling the richness–mass relation as log-linear, we find that the log-richness amplitude ln (A) is boosted from the lowest to highest orientation bin with a significance of 14σ, while the orientation dependence of the richness-mass slope and intrinsic scatter is minimal. We also find that the weak lensing shear-profile ratios of cluster-associated dark haloes in different orientation bins resemble a ‘bottleneck’ shape that can be quantified with a Cauchy function. We test the correlation of orientation with two other leading systematics in cluster cosmology – miscentering and projection – and find a null correlation. The resulting mass bias predicted from our templates confirms the DES Y1 finding that triaxiality is a leading source of bias in cluster cosmology. However, the richness-dependence of the bias confirms that triaxiality does not fully resolve the tension at low-richness between DES Y1 cluster cosmology and other probes. Our model can be used for quantifying the impact of triaxiality bias on cosmological constraints for upcoming weak lensing surveys of galaxy clusters.
79 ASTRONOMY AND ASTROPHYSICS↗
Shapes of ideal stalagmites
Stalagmites are isolated columns of calcium carbonate growing on a cave floor; their growth is driven by the constant dripping of supersaturated solutions from the roof of the cave. In this paper, we derive a closed-form expression for the shape of a steadily growing stalagmite. Our analysis gives rise to three distinct shapes, all of them observable in nature, with the shape characterized by a single dimensionless parameter. Transitions between different shapes occur at a specific value of this parameter, with additional selection rules determining the shape and size of stalagmites evolving under specific cave conditions. Our theory shows that the stalagmite shape influences the 13 C isotope shifts, which are an important source of paleoclimatic information.
invariant growth↗
An ecological framework for microbial metabolites in the ocean ecosystem
The ocean microbe‐metabolite network involves thousands of individual metabolites that encompass a breadth of chemical diversity and biological functions. These microbial metabolites mediate biogeochemical cycles, facilitate ecological relationships, and impact ecosystem health. While analytical advancements have begun to illuminate such roles, a challenge in navigating the deluge of marine metabolomics information is to identify a subset of metabolites that have the greatest ecosystem impact. Here, we present an ecological framework to distill knowledge of fundamental metabolites that underpin marine ecosystems. We borrow terms from macroecology that describe important species, namely “dominant,” “keystone,” and “indicator” species, and apply these designations to metabolites within the ocean microbial metabolome. These selected metabolites may shape marine community structure, function, and health and provide focal points for enhanced study of microbe‐metabolite networks. Applying ecological concepts to marine metabolites provides a path to leverage metabolomics data to better describe and predict marine microbial ecosystems.
microbial metabolites↗
Rational Design of Novel Biomimetic Sequence-Defined Polymers for Mineralization Applications
Silica biomineralization is a naturally occurring process, wherein organisms use proteins and other biological structures to direct the formation of complex, hierarchical nanostructures. Discovery and characterization of such proteins and their underlying mechanisms spurred significant efforts to identify routes for biomimetic mineralization that reproduce the exquisite shapes and size selectivities found in nature. A common strategy has been the use of short peptide sequences with chemistry mimicking those found in natural systems, such as the use of the silaffin-derived R5 peptide. While progress has been made using this approach, there are many limitations that have prevented breakthroughs in biomimicry. To advance our ability to use charged macromolecules for silica formation, we propose to use sequence-defined synthetic polymers known as peptoids, or N-substituted polyglycines, which present significant capability for the precise tuning of sequence and structure beyond what can often be achieved with peptides alone. This study presents a computationally predicted design of these polymers that leads to the controlled formation of silica nanomaterials. We investigate surface adsorption and the mineralization process through analysis of binding mechanisms and energetics of the R5 system. Next, we synthesized two R5-inspired peptoids and validated our prediction in the design of mineralization polymers through characterization using surface plasmon resonance and electron microscopy. Here, this computationally guided study holds great promise for designing new sequences with unprecedented control of the placement of chemical functional groups, thus allowing for further unraveling of silicification mechanisms and the eventual design of sequence-defined synthetic polymers leading to the predictive synthesis of nanostructured functional materials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Molecular-Resolution Electron Imaging of Defects and Dynamics at the Ice-Water Interface
Water crystallization into hexagonal ice (type I h ) is one of the most critical processes relevant to the Earth’s environment and human activities. However, despite recent breakthroughs in imaging non-equilibrium condensed ice structures, the ice-water interface has never been imaged at a molecular resolution. This is primarily due to the low stability of the hydrogen bonds in ice under high-resolution microscopy conditions and a lack of methods to prepare compatible samples. Here, this presentation describes the first molecular-resolution imaging of ice crystallized from liquid water and the ice-water interface using high-resolution transmission electron microscopy (HRTEM). By encapsulating deionized (DI) water between two amorphous carbon (a-C) TEM grids and subsequently freezing it with liquid N 2 on a cryo sample stage, we generated two types of ice: non-equilibrium, condensed ice from the atmosphere and encapsulated ice from the DI water (Fig. 1A). Condensed ice usually shows irregular, spherulitic shapes (Fig. 1B). Selected area electron diffraction (SAED) shows that they are a mixture of cubic and hexagonal crystals (Fig. 1C). On the contrary, encapsulated ice forms thin films that contain large-area single-crystalline regions of hexagonal ice oriented along the [0001] zone axis (Fig. 1D). Differential electron energy-loss spectroscopy (EELS) confirmed the high purity of the encapsulated ice free from organic contaminations that are common in other encapsulation methods for HRTEM such as graphene liquid cells. These single-crystalline areas are robust under the electron beam up to ~100 e/Å 2 s. Aberration-corrected HRTEM imaging in these areas achieved a line resolution of ~1.3 Å (Fig. 1E and F). This platform allows us to study near-equilibrium ice structures and dynamics at an unprecedented spatial resolution (Fig. 2). For example, we discovered subdomain-rich regions near the defective crystal edges despite the structure appearing single-crystalline according to diffraction criteria. These subdomains connect via low-angle grain boundaries with flat energy landscapes as a function of tilt angles (according to simulations), showing the high tolerance of ice to defect structures. When we tuned the sample temperature and electron flux rate, we observed radiolysis-controlled bubble generation and dissolution in ice single crystals near a steady state of bubble dynamics. Furthermore, rich beam-induced melting and recrystallization dynamics were observed at the ice-water interface with lattice resolution. These data represent the first observation of the ice-water phase transformation at the sub-nanometer level. In summary, the methods developed in this work enabled molecular-resolution observations of ice and the ice-water interface and shed light on the microstructures and phase transformation pathways. Finer control on the temperature, electron irradiation profile, and imaging detector could eventually lead to real-time observation of ice nucleation in water and address long-standing questions in the nucleation pathways.
74 ATOMIC AND MOLECULAR PHYSICS↗
Commercialization of Distribution System Load Modeling Tool for Improved DER Interconnection Studies
Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. The load profiles in the same group will have similar characteristics at the same time step, so grid operators can send the grid service signal to the customer group with a higher chance to respond at that time step. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation. In our two-step clustering approach, we first calculate the total load consumption for each building, clustering the load profiles based on energy consumption level. Then, we further cluster the load profiles in each energy cluster based on the load shape. The parameter selection for each clustering step is discussed. The proposed method is applied on actual building-level load profiles, and the results have proved the effectiveness of this method.
14 SOLAR ENERGY↗
Adaptive Methods for Radial Basis Functions
Radial basis functions (RBFs) are a powerful tool for constructing high-order accurate reduced representations of scattered data in arbitrary dimension and on manifolds. We present a method of constructing data approximations in which we utilize a functional tail to capture a global background profile and a RBF neural network (NN) to capture the smaller-scale features. In the RBF NN the RBF centers, matrix shape parameters were selected adaptively for each RBF. We also utilized a geodesic notion of distance on the manifold on which the data lies, e.g., the spherical geodesic for data on the sphere. Although each of these ideas have been been investigated separately in previous works, their combination into a single algorithm is novel. We defined a machine learning problem in which these properties are learned to minimize the data reduction error. We demonstrate the algorithm for applications of scattered data reduction in the plane and on the sphere.
97 MATHEMATICS AND COMPUTING↗
Central Density and Low-Mode Perturbation Control of Inertial Confinement Fusion Dynamic-Shell Targets
The dynamic-shell target is a new class of design for inertial confinement fusion (ICF). These targets address some of the target fabrication challenges prevalent in current ICF targets and take advantage of advances in manufacturing technologies. This study first examines how the dynamic-shell design can be used to control the density of the central region and therefore convergence ratio, thus expanding the design space for ICF. Additionally, the concern of low-mode perturbation growth is considered. A new class of high-performing beam configurations, based on icosahedral polyhedra and charged-particle simulations is proposed. These configurations achieve low levels of irradiation nonuniformity through selection of beam shapes that suppress the dominant symmetrical mode.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Quantifying microbial control of soil organic matter dynamics at macrosystem scales
Soil organic matter (SOM) stocks, decomposition and persistence are largely the product of controls that act locally. Yet the controls are shaped and interact at multiple spatiotemporal scales, from which macrosystem patterns in SOM emerge. Theory on SOM turnover recognizes the resulting spatial and temporal conditionality in the effect sizes of controls that play out across macrosystems, and couples them through evolutionary and community assembly processes. For example, climate history shapes plant functional traits, which in turn interact with contemporary climate to influence SOM dynamics. Selection and assembly also shape the functional traits of soil decomposer communities, but it is less clear how in turn these traits influence temporal macrosystem patterns in SOM turnover. Here, we review evidence that establishes the expectation that selection and assembly should generate decomposer communities across macrosystems that have distinct functional effects on SOM dynamics. Representation of this knowledge in soil biogeochemical models affects the magnitude and direction of projected SOM responses under global change. Yet there is high uncertainty and low confidence in these projections. To address these issues, we make the case that a coordinated set of empirical practices are required which necessitate (1) greater use of statistical approaches in biogeochemistry that are suited to causative inference; (2) long-term, macrosystem-scale, observational and experimental networks to reveal conditionality in effect sizes, and embedded correlation, in controls on SOM turnover; and (3) use of multiple measurement grains to capture local- and macroscale variation in controls and outcomes, to avoid obscuring causative understanding through data aggregation. Here, when employed together, along with process-based models to synthesize knowledge and guide further empirical work, we believe these practices will rapidly advance understanding of microbial controls on SOM and improve carbon cycle projections that guide policies on climate adaptation and mitigation.
59 BASIC BIOLOGICAL SCIENCES↗
Optimal measurement point selection for resonant ultrasound spectroscopy of complex-shaped specimens using principal component analysis
Not Available
47 OTHER INSTRUMENTATION↗
Computation and illustration of the generalized order restricted criterion (GORIC) for shape constrained spline functions
The selection of a model among alternative models that include inequality constraints is a complex task. The generalized order restricted criterion (GORIC) is a suitable approach to do so. However, the GORIC proves challenging to compute in the general case. This report discusses a number of methods to compute the GORIC and illustrates its use with a didactic example.
97 MATHEMATICS AND COMPUTING↗
Foil-based additive manufacturing system and method
An additive manufacturing system, method of manufacturing, and fabricated part. The system uses a material joining laser system to join together foil sheets to form a metal part. The material joining laser system can be configured to join adjacent foil sheets together in a substantially uniform manner. The manufacturing system also includes a material removal system that removes material from selected locations of the foil sheets to shape the foil sheets to correspond with selective slices of the part. The material removal system can be a laser system, such as a laser system configured to remove material from a foil sheet without removing material from an underlying layer. One embodiment involves the manufacture of amorphous alloy components.
Tsai, Hai-Lung↗
Space-tiled colloidal crystals from DNA-forced shape-complementary polyhedra pairing
Generating space-filling arrangements of most discrete polyhedra nanostructures of the same shape is not possible. However, if the appropriate individual building blocks are selected (e.g., cubes), or multiple shapes of the appropriate dimensions are matched (e.g., octahedra and tetrahedra) and their pairing interactions are subsequently forced, space-filled architectures may be possible. With flexible molecular ligands (polyethylene glycol–modified DNA), the shape of a polyhedral nanoparticle can be deliberately altered and used to realize geometries that favor space tessellation. In this work, 10 new colloidal crystals were synthesized from DNA-modified nanocrystal building blocks that differed in shapes and sizes, designed to form space-filling architectures with micron-scale dimensions. The insights and capabilities provided by this new strategy substantially expand the scope of colloidal crystals possible and provide an expanded tool kit for researchers interested in designing metamaterials.
Science & Technology - Other Topics↗