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At least 109 records · Page 6

Nonlinear hierarchical substructural parallelism and computer architecture

Computer architecture is investigated in conjunction with the algorithmic structures of nonlinear finite-element analysis. To help set the stage for this goal, the development is undertaken by considering the wide-ranging needs associated with the analysis of rolling tires which possess the full range of kinematic, material and boundary condition induced nonlinearity in addition to gross and local cord-matrix material properties.

Padovan, Joe↗

Membrane synthesis via in-situ pore formation in silica gels through dynamic miscibility with soybean oil

The dynamic immiscibility between vegetable oil and organic silica precursors during sol-gel synthesis was used to tailor the microstructure of gels made with tetraethoxysilane (TEOS) or tetraethoxysilane+methyltrimethoxysilane (MTMS). Vegetable oil was investigated as an environmentally friendly and cheaper alternative to many other porogens. Oil concentrations of 9.09 v/v% and 33.33 v/v% were studied. For both TEOS and TEOS+MTMS gels, the miscibility of the oil and precursor decreases as the silica gel network forms, leading to oil-rich regions within the silica matrix. Gels containing MTMS maintained partial miscibility with the oil during gel formation due to the non-hydrolysable methyl groups on the MTMS. The pore structure of MTMS gels appeared more interconnected compared to the isolated pores observed in gels made with only TEOS. To create membranes with hierarchical pore structures, solvent exchanges were performed on gels or dried gels (i.e., xerogels) were calcined. The effect of the methyl group was also observed in the results of the time sweep rheology, as the addition of oil to the TEOS+MTMS gels caused an increase in the time to form the spanning gel. The trend was the opposite for oil additions to TEOS gels, which only contained polar groups. Xerogel membranes made with TEOS+MTMS had higher specific surface areas (SSAs) than those made with TEOS. For oil concentrations of 33.33 v/v%, xerogels made from TEOS+MTMS had an average SSA of 1068 + 113 m2 g-1, an order of magnitude higher than the average SSA of 103 + 6 m2 g-1 for xerogels made with TEOS.

sol-gel, dynamic immiscibility, oil-alkoxide inter↗

Hierarchical Poly Tree Configurations for the Solution of Dynamically Refined Finte Element Models

This paper demonstrates how a multilevel substructuring technique, called the Hierarchical Poly Tree (HPT), can be used to integrate a localized mesh refinement into the original finite element model more efficiently. The optimal HPT configurations for solving isoparametrically square h-, p-, and hp-extensions on single and multiprocessor computers is derived. In addition, the reduced number of stiffness matrix elements that must be stored when employing this type of solution strategy is quantified. Moreover, the HPT inherently provides localize 'error-trapping' and a logical, efficient means with which to isolate physically anomalous and analytically singular behavior.

Gute, G. D.↗

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗

Hierarchically structured MoO 2 /dopamine-derived carbon spheres as intercalation electrodes for lithium-ion batteries

A hydrogen peroxide initiated sol-gel process involving molybdenum transformation in the presence of dopamine (Dopa) hydrochloride excess produced the metastable precipitate composed of polydopamine (PDopa) spheres coated with Dopa preintercalated molybdenum oxide, (Dopa) x MoO y @PDopa. The hydrothermal treatment (HT) of the (Dopa) x MoO y @PDopa precursor resulted in the simultaneous carbonization of Dopa and molybdenum reduction generating MoO 2 nanoplatelets distributed and confined on the surface of the Dopa-derived carbon matrix (HT-MoO 2 /C). The consecutive annealing (An) of the HT-MoO 2 /C sample at 600 °C under Ar atmosphere led to the formation of MoO 2 with increased Mo oxidation state and improved structural stability (AnHT-MoO 2 /C). Annealing had also further facilitated interaction between the molybdenum-derived and Dopa-derived components resulting in the modification of the carbon matrix confirmed by Raman spectroscopy. Morphology of both materials is best described as Dopa-derived carbon spheres decorated with MoO 2 nanoplatelets. These integrated metal oxide and carbon structures were tested as electrodes for lithium-ion batteries in the potential window that corresponds to the intercalation mechanism of charge storage. The AnHT-MoO 2 /C electrode showed enhanced electrochemical activity, with an initial specific discharge capacity of 260 mAh/g and capacity retention of 67% after 50 cycles, compared to the HT-MoO 2 /C electrode which exhibited an initial specific discharge capacity of 235 mAh g –1 and capacity retention of 47% after 50 cycles. The rate capability experiments revealed that the capacity of 93 mAh/g and 120 mAh/g was delivered by the HT-MoO 2 /C and AnHT-MoO 2 /C electrodes, respectively, when the current density was increased to 100 mA/g. Here, the improved specific capacity, electrochemical stability, and rate capability achieved after annealing were attributed to higher crystallinity of MoO 2 , increased oxidation state of Mo, and formation of the tighter MoO 2 /carbon contact accompanied by the annealing assisted interaction between MoO 2 and Dopa-derived carbon.

25 ENERGY STORAGE↗

Machine learning-enabled multiscale modeling of mechanical deformation of aluminum and Al-SiC nanocomposites

A machine learning-enabled multiscale framework is developed for modeling the mechanical response of both pure metal and nanoparticle-reinforced metal matrix nanocomposites (MMNCs). Using aluminum–silicon carbide (Al-SiC) as an example MMNC, atomistic simulations reveal three distinct deformation mechanisms (i.e., defect-free, dislocation-based, and interface separation) governed by the interfaces between the Al matrix and SiC nanoparticles. As compared with single crystal Al, the lattice undergoes a more abrupt failure once the dislocation network becomes extensive and void nucleation initiates, whereas in Al-SiC, nanoparticle interfaces enable a more gradual progression of damage. These mechanisms are captured through a combined classification-regression neural network surrogate model that bridges atomic-scale insights with continuum-scale finite element analysis. Machine learning-enabled multiscale modeling of pure Al accurately predicted strain localization and confirmed by in-situ scanning electron microscopic tensile testing on perforated Al specimens. This study underscores the promise of integrating physics-informed machine learning with hierarchical modeling to capture the interface dominated phenomena and guide the design of advanced MMNCs.

Al-SiC↗

A new clustering algorithm applicable to multispectral and polarimetric SAR images

We describe an application of a scale-space clustering algorithm to the classification of a multispectral and polarimetric SAR image of an agricultural site. After the initial polarimetric and radiometric calibration and noise cancellation, we extracted a 12-dimensional feature vector for each pixel from the scattering matrix. The clustering algorithm was able to partition a set of unlabeled feature vectors from 13 selected sites, each site corresponding to a distinct crop, into 13 clusters without any supervision. The cluster parameters were then used to classify the whole image. The classification map is much less noisy and more accurate than those obtained by hierarchical rules. Starting with every point as a cluster, the algorithm works by melting the system to produce a tree of clusters in the scale space. It can cluster data in any multidimensional space and is insensitive to variability in cluster densities, sizes and ellipsoidal shapes. This algorithm, more powerful than existing ones, may be useful for remote sensing for land use.

Wong, Yiu-Fai↗

HarDWR - Harmonized Water Rights Records

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Recalculated based on data sourced from WestDAAT - Changed using a Site ID column to identify unique records to using aa combination of Site ID and Allocation ID - Removed the Water Management Area (WMA) column from the harmonized records. The replacement is a separate file which stores the relationship between allocations and WMAs. This allows for allocations to contribute to water right amounts to multiple WMAs during the subsequent cumulative process. - Added a column describing a water rights legal status - Added "Unspecified" was a water source category - Added an acre-foot (AF) column - Added a column for the classification of the right's owner v1.02 - Added a .RData file to the dataset as a convenience for anyone exploring our code. This is an internal file, and the one referenced in analysis scripts as the data objects are already in R data objects. v1.01 - Updated the names of each file with an ID number less than 3 digits to include leading 0s v1.0 - Initial public release Description Here we present an updated database of Western U.S. water right records. This database provides consistent unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of seven broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of inter-sectoral water allocation changes though water markets (Grogan et al., *in review*). Specifically, the data were formatted for use as input to a process-based hydrologic model, Water Balance Model (WBM), with a water rights module (Grogan et al., *in review*). While this specific study motivated the development of the database presented here, water management in the U.S. West is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al., 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. West. We produced the water rights database presented here in four main steps: (1) data collection, (2) data quality control, (3) data harmonization, and (4) generation of cumulative water rights curves. Each of steps (1)-(3) had to be completed in order to produce (4), the final product that was used in the modeling exercise in Grogan et al. (*in review*). All data in each step is associated with a spatial unit called a Water Management Area (WMA), which is the unit of water right administration utilized by the state in which the right came from. Steps (2) and (3) required use to make assumptions and interpretation, and to remove records from the raw data collection. We describe each of these assumptions and interpretations below so that other researchers can choose to implement alternative assumptions an interpretation as fits their research aims. Motivation for Changing Data Sources The most significant change has been a switch from collecting the raw water rights directly from each state to using the water rights records presented in WestDAAT, a product of the Water Data Exchange (WaDE) Program under the Western States Water Council (WSWC). One of the main reasons for this is that each state of interest is a member of the WSWC, meaning that WaDE is partially funded by these states, as well as many universities. As WestDAAT is also a database with consistent categorization, it has allowed us to spend less time on data collection and quality control and more time on answering research questions. This has included records from water right sources we had previously not known about when creating v1.0 of this database. The only major downside to utilizing the WestDAAT records as our raw data is that further updates are tied to when WestDAAT is updated, as some states update their public water right records daily. However, as our focus is on cumulative water amounts at the regional scale, it is unlikely most records updates would have a significant effect on our results. The structure of WestDAAT led to several important changes to how HarWR is formatted. The most significant change is that WaDE has calculated a field known as `SiteUUID`, which is a unique identifier for the Point of Diversion (POD), or where the water is drawn from. This separate from `AllocationNativeID`, which is the identifier for the allocation of water, or the amount of water associated with the water right. It should be noted that it is possible for a single site to have multiple allocations associated with it and for an allocation to be able to be extracted from multiple sites. The site-allocation structure has allowed us to adapt a more consistent, and hopefully more realistic, approach in organizing the water right records than we had with HarDWR v1.0. This was incredibly helpful as the raw data from many states had multiple water uses within a single field within a single row of their raw data, and it was not always clear if the first water use was the most important, or simply first alphabetically. WestDAAT has already addressed this data quality issue. Furthermore, with v1.0, when there were multiple records with the same water right ID, we selected the largest volume or flow amount and disregarded the rest. As WestDAAT was already a common structure for disparate data formats, we were better able to identify sites with multiple allocations and, perhaps more importantly, allocations with multiple sites. This is particularly helpful when an allocation has sites which cross WMA boundaries, instead of just assigning the full water amount to a single WMA we are now able to divide the amount of water between the number of relevant WMAs. As it is now possible to identify allocations with water used in multiple WMAs, it is no longer practical to store this information within a single column. Instead the stAllocationToWMATab.csv file was created, which is an allocation by WMA matrix containing the percent Place of Use area overlap with each WMA. We then use this percentage to divide the allocation's flow amount between the given WMAs during the cumulation process to hopefully provide more realistic totals of water use in each area. However, not every state provides areas of water use, so like HarDWR v1.0, a hierarchical decision tree was used to assign each allocation to a WMA. First, if a WMA could be identified based on the allocation ID, then that WMA was used; typically, when available, this applied to the entire state and no further steps were needed. Second was the spatial analysis of Place of Use to WMAs. Third was a spatial analysis of the POD locations to WMAs, with the assumption that allocation's POD is within the WMA it should belong to; if an allocation still had multiple WMAs based on its POD locations, then the allocation's flow amount would be divided equally between all WMAs. The fourth, and final, process was to include water allocations which spatially fell outside of the state WMA boundaries. This could be due to several reasons, such as coordinate errors / imprecision in the POD location, imprecision in the WMA boundaries, or rights attached with features, such as a reservoir, which crosses state boundaries. To include these records, we decided for any POD which was within one kilometer of the state's edge would be assigned to the nearest WMA. Other Changes WestDAAT has Allowed In addition to a more nuanced and consistent method of assigning water right's data to WMAs, there are other benefits gained from using the WestDAAT dataset. Among those is a consistent categorization of a water right's legal status. In HarDWR v1.0, legal status was effectively ignored, which led to many valid concerns about the quality of the database related to the amounts of water the rights allowed to be claimed. The main issue was that rights with legal status' such as "application withdrawn", "non-active", or "cancelled" were included within HarDWR v1.0. These, and other water rights status' which were deemed to not be in use have been removed from this version of the database. Another major change has been the addition of the "unspecified water source category. This is water that can come from either surface water or groundwater, or the source of which is unknown. The addition of this source category brings the total number of categories to three. Due to reviewer feedback, we decided to add the acre-foot (AF) column so that the data may be more applicable to a wider audience. We added the ownerClassification column so that the data may be more applicable to a wider audience. File Descriptions The dataset is a series of various files organized by state sub-directories. In addition, each file begins with the state's name, in case the file is separate from its sub-directory for some reason. After the state name is the text which describes the contents of the file. Here is each file described in detail. Note that st is a placeholder for the state's name. stFullRecords_HarmonizedRights.csv: A file of the complete water records for each state. The column headers for each of this type of file are: state - The name of the state to which the allocations belong to. FIPS - The two digit numeric state ID code. siteID - The site location ID for POD locations. A site may have multiple allocations, which are the actual amount of water which can be drawn. In a simplified hypothetical, a farm stead may have an allocation for "irrigation" and an allocation for "domestic" water use, but the water is drawn from the same pumping equipment. It should be noted that many of the site ID appear to have been added by WaDE, and therefore may not be recognized by a given state's water rights database. allocationID - The allocation ID for the water right. For most states this is the water right ID, and what is recommended to use should a right be looked up on a given state's water rights database. The water amounts associated with these IDs tend to be finer scaled than those associated with siteID. It should be noted that some allocations may be extracted from multiple sites, particularly for larger Places of Use. ownerClassification - A classification of the types of owners for water rights. The most common is `Private` which incorporates a wide range of entities. Several classifications would be grouped into a government category, most of which are for the U.S. Federal Government. These allocations could be listed as "Federal", "United States of America", or as the names of any number of federal agencies. The last major grouping of entities is for "Native American"s. priorityDate - The date we use as the water right priority date for our modeling analysis. This is the legal priority date when it is available. However, for some rights, specifically from California and New Mexico, we used a pseudo priority date (e.g. well completion date or start of well drilling date) when a legal priority date was not available. The most questionable dates come from New Mexico, where the only date associated with certain water right records was the date the allocation was recorded in the database. As the allocation record creation tended to be within a few months of the filing of the application of the water right, from manually double checking the water rights, and our analysis focuses on aggregating water rights on the timescale of years, we determined it was acceptable to use such dates to include as many records as possible. primaryBeneficialUse - From the numerous state water use categories, WaDE categorized them into 21 categories WestDAAT. This column is the original WaDE category for the primary water use at the PoD site. allocationBeneficialUse - From the numerous state water use categories, WaDE categorized them into 21 categories for WestDAAT. This column is the original WaDE category

Economics↗

Interfacial Strength in Hierarchical Carbon Fiber Composites: Interplay of Interphase Modulus and Roughness

A facile, direct deposition approach that exploits van der Waals interactions between carbonaceous materials is utilized to create unidirectional hybrid carbon fiber composites. Two small molecule crosslinkers, a trifunctional aromatic (TL) and a difunctional aliphatic (DL) acyl chloride, are first utilized to create a crosslinked interphase with a softer and stiffer modulus respectively. TL crosslinked interphase with a higher modulus improved the tensile strength by 50%, despite non-covalent linking between fiber and matrix, elucidating the critical role of the interphase in alleviating modulus mismatch between the high modulus carbon fiber and the rubbery matrix. Fractional quantities of carbon nanotubes are additionally dispersed in the small molecule crosslinkers which behaved as a dispersant, helping introduce nanoasperities on the carbon fiber surface. Strong “pi-pi” interactions between CNTs and CF contributed to tensile properties, which are increased by 66% compared to the control. A cohesive zone model suggests that a stiffer interphase is better able to exploit surface heterogeneities and roughness on the fiber, synergistically enhancing interfacial strength.

36 MATERIALS SCIENCE↗

Non-Equilibrium Synthesis of Highly Active Nanostructured, Oxygen-Incorporated Amorphous Molybdenum Sulfide HER Electrocatalyst

Molybdenum sulfide emerged as promising hydrogen evolution reaction (HER) electrocatalyst thanks to its high intrinsic activity, however its limited active sites exposure and low conductivity hamper its performance. To address these drawbacks, the non-equilibrium nature of pulsed laser deposition (PLD) is exploited to synthesize self-supported hierarchical nanoarchitectures by gas phase nucleation and sequential attachment of defective molybdenum sulfide clusters. Furthermore, the physics of the process are studied by in situ diagnostics and correlated to the properties of the resulting electrocatalyst. The as-synthesized architectures have a disordered nanocrystalline structure, with nanodomains of bent, defective S-Mo-S layers embedded in an amorphous matrix, with excess sulfur and segregated molybdenum particles. Oxygen incorporation in this structure fosters the creation of amorphous oxide/oxysulfide nanophases with high electrical conductivity, enabling fast electron transfer to the active sites. The combined effect of the nanocrystalline pristine structure and the surface oxidation enhances the performance leading to small overpotentials, very fast kinetics (35.1 mV dec -1 Tafel slope) and remarkable long-term stability for continuous operation up to -1 A cm -2 . This work shows possible new avenues in catalytic design arising from a non-equilibrium technique as PLD and the importance of structural and chemical control to improve the HER performance of MoS-based catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting the tensile and compressive modulus of electrospun fiber mat‐reinforced hydrogels using the Halpin–Tsai equations

Abstract The reinforcement of mechanically‐weak hydrogels to yield composites with increased stiffness, strength, or toughness is a well‐established approach. In particular, introducing electrospun nanofibers into hydrogels is a common strategy for biomedical applications, as the resulting hierarchical structure mimics biology and allows for control over fiber diameter and alignment and tuning of mechanical properties. However, further study of the link between the constituent materials and the mechanical properties of the composite is uncommon. One potential model to understand the mechanical properties of fiber‐reinforced hydrogels involves the Halpin–Tsai equations, which relate the modulus values of the fibers and hydrogel matrix and the fiber volume fraction, to the modulus of the composite. To assess the application of this model to fiber‐reinforced hydrogels, predicted values were compared with experimental values from mechanical testing of a poly(ethylene glycol) (PEG) matrix reinforced with an electrospun polycaprolactone (PCL) fiber mat. Although the equations described these systems well in tension, providing a facile approach to identify a fiber volume fraction that will achieve a desired modulus, the Halpin–Tsai approach was less successful under compression. This study motivates additional investigation of the role of structural features of hydrogel composites in determining mechanical properties to enable design of materials for specific applications.

Polymer Science↗

Rotor Performance Predictions of a Next Generation Mars Science Helicopter

Since Ingenuity took flight and proved aerial capabilities on Mars, the horizon for rotorcraft on the Red Planet has only expanded. One proposed future Martian rotorcraft is the Mars Science Helicopter (MSH). The MSH is a hexacopter capable of carrying scientific payloads. As a part of its joint development by NASA Ames Research Center (ARC) and the Jet Propulsion Laboratory (JPL), key MSH rotor components will be tested inside the in-development Reduced Atmospheric Pressure Testing Of Rotors (RAPTOR) wind tunnel in the Planetary Aeolian Laboratory (PAL) at NASA ARC. In preparation for the test, the Comprehensive Hierarchical Aeromechanics Rotorcraft Model (CHARM) analysis was utilized to predict the aerodynamic performance for one MSH hexacopter isolated rotor. This paper provides an overview of the planned experiments involving the MSH reference blades, as well as CHARM pretest predictions of rotor performance in hover and forward flight. Additionally, the interference effects of wind tunnel walls on rotor performance will be evaluated to inform the test matrix of the upcoming test in the RAPTOR tunnel.

MHS↗

Bayesian sparse learning with preconditioned stochastic gradient MCMC and its applications

Deep neural networks have been successfully employed in an extensive variety of research areas, including solving partial differential equations. Despite its significant success, there are some challenges in effectively training DNN, such as avoiding overfitting in over-parameterized DNNs and accelerating the optimization in DNNs with pathological curvature. Here, we propose a Bayesian type sparse deep learning algorithm. The algorithm utilizes a set of spike-and-slab priors for the parameters in the deep neural network. The hierarchical Bayesian mixture will be trained using an adaptive empirical method. That is, one will alternatively sample from the posterior using preconditioned stochastic gradient Langevin Dynamics (PSGLD), and optimize the latent variables via stochastic approximation. The sparsity of the network is achieved while optimizing the hyperparameters with adaptive searching and penalizing. A popular SG-MCMC approach is Stochastic gradient Langevin dynamics (SGLD). However, considering the complex geometry in the model parameter space in nonconvex learning, updating parameters using a universal step size in each component as in SGLD may cause slow mixing. To address this issue, we apply a computationally manageable preconditioner in the updating rule, which provides a step-size parameter to adapt to local geometric properties. Moreover, by smoothly optimizing the hyperparameter in the preconditioning matrix, our proposed algorithm ensures a decreasing bias, which is introduced by ignoring the correction term in the preconditioned SGLD. According to the existing theoretical framework, we show that the proposed algorithm can asymptotically converge to the correct distribution with a controllable bias under mild conditions. Numerical tests are performed on both synthetic regression problems and learning solutions of elliptic PDE, which demonstrate the accuracy and efficiency of the present work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Programmable display pushbuttons on the Space Station's telerobot control panel

The Man-Systems Telerobotics Laboratory at NASA's Johnson Space Center and supported by Lockheed, is working to ensure that the Flight Telerobotic Servicer (FTS) to be used on the Space Shuttle (Orbiter) and the Space Station has a well designed user interface from a Human Factors perspective. The FTS, which is a project led by NASA's Goddard Space Flight Center, will be a telerobot used for Space Station construction, maintenance, and satellite repair. It will be directly controlled from workstations on the Orbiter and the Space Station and monitored from a ground workstation. The FTS will eventually evolve into a more autonomous system, but in the short-term the system will be manually operated (teleoperated) for many tasks. This emphasizes the importance of the human/telerobot interface on this system. This phase of the FTS workstation evaluation covers a preliminary study of programmable display pushbuttons (PDP's). The PDP is constructed of a matrix of directly addressable electroluminescent (EL) pixels which can be used to form dot-matrix characters. PDP's can be used to display more than one message and to control more than one function. Since the PDP's have these features, then a single PDP may possibly replace the use of many single-function pushbuttons, rotary switches, and toggle switches, thus using less panel space. It is of interest to determine if PDP's can be used to adequately perform complex hierarchically structured task sequences. The objective of this investigation was to compare the performance of experienced and inexperienced Remote Manipulator System (RMS) operators while performing an RMS like task on simulated PDP and non-PDP computer prototypes so that guidelines governing the use of programmable display pushbuttons on the FTS workstation could be created. The functionality of the RMS on the Orbiter was used as a model for this evaluation since the functionality of the FTS at the time of this writing has not been solidified.

Stuart, Mark A.↗

Hierarchical Coupling of Molecular Dynamics and Micromechanics to Predict the Elastic Properties of Three-Phase and Four-Phase Silicon Carbide Composites

The results obtained from previously conducted molecular dynamics analysis of silicon carbide (-SiC (6H, 4H, & 2H-SiC), -SiC (3C SiC)), silicon and boron nitride, were utilized as inputs in the MAC/GMC micromechanics software to model and evaluate the elastic properties of three-phase SiC/BN/SiC and four-phase SiC/BN/Si/SiC composites. This method of analysis eliminates the need for back-calculation of the apparent properties of the base constituents from the measured ceramic matrix composites properties. The multiscale models are validated against the available data in literature.

Aluko, Olanrewaju↗

Strain‐Driven Mixed‐Phase Domain Architectures and Topological Transitions in Pb 1− x Sr x TiO 3 Thin Films

Abstract The potential for creating hierarchical domain structures, or mixtures of energetically degenerate phases with distinct patterns that can be modified continually, in ferroelectric thin films offers a pathway to control their mesoscale structure beyond lattice‐mismatch strain with a substrate. Here, it is demonstrated that varying the strontium content provides deterministic strain‐driven control of hierarchical domain structures in Pb 1− x Sr x TiO 3 solid‐solution thin films wherein two types, c / a and a 1 / a 2 , of nanodomains can coexist. Combining phase‐field simulations, epitaxial thin‐film growth, detailed structural, domain, and physical‐property characterization, it is observed that the system undergoes a gradual transformation (with increasing strontium content) from droplet‐like a 1 / a 2 domains in a c / a domain matrix, to a connected‐labyrinth geometry of c / a domains, to a disconnected labyrinth structure of the same, and, finally, to droplet‐like c / a domains in an a 1 / a 2 domain matrix. A relationship between the different mixed‐phase modulation patterns and its topological nature is established. Annealing the connected‐labyrinth structure leads to domain coarsening forming distinctive regions of parallel c / a and a 1 / a 2 domain stripes, offering additional design flexibility. Finally, it is found that the connected‐labyrinth domain patterns exhibit the highest dielectric permittivity.

Kavle, Pravin↗

Porous cage-derived nanomaterial inks for direct and internal three-dimensional printing

The convergence of 3D printing techniques and nanomaterials is generating a compelling opportunity space to create advanced materials with multiscale structural control and hierarchical functionalities. While most nanoparticles consist of a dense material, less attention has been payed to 3D printing of nanoparticles with intrinsic porosity. Here, we combine ultrasmall (about 10 nm) silica nanocages with digital light processing technique for the direct 3D printing of hierarchically porous parts with arbitrary shapes, as well as tunable internal structures and high surface area. Thanks to the versatile and orthogonal cage surface modifications, we show how this approach can be applied for the implementation and positioning of functionalities throughout 3D printed objects. Furthermore, taking advantage of the internal porosity of the printed parts, an internal printing approach is proposed for the localized deposition of a guest material within a host matrix, enabling complex 3D material designs.

36 MATERIALS SCIENCE↗

Melting and solidification dynamics during laser melting of reaction-based metal matrix composites uncovered by in-situ synchrotron X-ray diffraction

Laser additive manufacturing (AM) of reaction-based metal matrix composites (MMCs) involves highly complex and non-equilibrium material transformation behavior, including melting, dissolution, precipitation, and solidification. Yet, the dynamics and interplay of these phase transformation processes remain poorly understood, posing substantial challenges in identifying the microstructure formation mechanism, and predicting and controlling the microstructure in the printed parts. Here, in this study, we performed the in-situ X-ray diffraction experiment to characterize the phase evolution dynamics of the 316L + 10 vol.%TiC system during laser melting, which provides direct and quantitative insights of the complex phase reaction and evolution dynamics under rapid heating and cooling conditions relevant to additive manufacturing of reaction-based MMCs. Further in-depth thermodynamic and kinetic calculations revealed that most of the phase evolution behavior observed in the in-situ X-ray diffraction experiment cannot be solely explained by widely used equilibrium thermodynamic models, and diffusion-controlled nonequilibrium dissolution and precipitation kinetics must be considered to elucidate the complex phase evolution behavior, including incomplete TiC dissolution, and three-step TiC precipitation. The three distinct types of precipitates generate unique hierarchical TiC micro- and nanostructures, which enhances the yield strength from 513 MPa to 877 MPa by 71 %, tensile strength from 628 MPa to 1054 MPa by 68 %, and Young's modulus from 193 GPa to 221 GPa by 14 %. The findings of our research provide the knowledge foundation for the design of unique microstructures and advanced MMC materials through laser AM.

36 MATERIALS SCIENCE↗