SEARCH · Engineering Papers

Results for “design pattern”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

All sources NASA NTRS DOE OSTI

DOE OSTI2015

Application of sub-micrometer patterned permalloy thin film in tunable radio frequency inductors

Electrical tunable meander line inductor using coplanar waveguide structures with patterned permalloy (Py) thin film has been designed and implemented in this paper. High resistivity Si substrate is used to reduce the dielectric loss from the substrate. Inductor is implemented with a 60 nm thick Py deposited and patterned on top of the gold meander line, and Py film is patterned with dimension of 440 nm 10 lm to create the shape anisotropy field, which in turn increases the FMR frequency. Compared to a regular meanderline inductor without the application of sub-micrometer patterned Py thin film, the inductance density has been increased to 20% for the implemented inductor with patterned Py. Measured FMR frequency of the patterned Py is 4.51 GHz without the application of any external magnetic field. This has enabled the inductor application in the practical circuit boards, where the large external magnet is unavailable. Inductance tunability of the implemented inductor is demonstrated by applying a DC current. Applied DC current creates a magnetic field along the hard axis of the patterned Py thin film, which changes the magnetic moment of the thin film and thus, decreases the inductance of the line. Here, the measured results show that the inductance density of the inductor can be varied 5% by applying 300 mA DC current, larger inductance tunability is achievable by increasing the thickness of Py film.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Machine learning approaches for crystallographic classification from synthetic 2D X-ray diffraction data

Crystallographic structure identification is crucial for understanding material properties; however, current methodologies often depend on labor-intensive and time-consuming analyses of 2D X-ray diffraction (XRD) patterns. To address these limitations, this study employs synthetic 2D XRD patterns combined with deep learning (DL) techniques to enable automated and high-throughput classification of the seven crystal systems and 230 space groups. We introduce the novel Auto Diffraction Pipeline, designed to generate synthetic 2D XRD spot patterns from crystallographic information files under diverse conditions, including varying zone axes, atomic substitution, atomic depletion and mechanical loading. These conditions enhance the realism of synthetic data, mitigating the scarcity of experimental datasets and enabling the creation of large representative training sets. Convolutional neural networks were trained and validated on these synthetic datasets to classify crystallographic structures across multiple scenarios. Our results demonstrate that integrating synthetic 2D XRD patterns with DL facilitates rapid, accurate and automated crystallographic classification, promoting the wider adoption of data-driven approaches in materials science.

Shahnazari, Ayoub [Univ. of Rochester, NY (United ↗

DOE OSTI2025

Structure–Function Relationships in Sequence-Controlled Copolymers for Rare Earth Element Chelation

The ability to tune material function through primary sequence is a defining feature of biological macromolecules, allowing precise control over structure and target interactions in complex aqueous environments. However, translating sequence–structure–function relationships to synthetic macromolecules is challenging due to their dispersity in sequence, conformation, and composition. Here, we report systematic studies of amphiphilic polymer chelators designed to probe how composition and patterning influence binding affinity and selectivity for rare earth elements (REEs), a series of technologically relevant metals with challenging separation profiles. A library of copolymers varying hydrophobic monomer composition and patterning was synthesized via reversible addition–fragmentation chain transfer (RAFT) polymerization, spanning statistical, gradient, and block architectures. REE binding was quantified using a high-throughput colorimetric assay, and reconstruction of polymer ensembles using kinetic stochastic simulations enabled quantitative comparisons of sequence heterogeneity, linking local monomer colocalization to emergent REE binding. Further, we investigated the role of different hydrophobic comonomers in tuning metal coordination, with binding trends linked to structural features that influence binding site desolvation. Complementary dynamic light scattering (DLS) and small-angle X-ray scattering (SAXS) measurements showed that both polymer and monomer architecture modulate metal-induced conformational changes, and that multichain assembly behavior emerges beyond critical hydrophobic thresholds. Sequence control also altered REE selectivity, with nonmonotonic differences observed across compositionally identical polymers with different sequence architectures. Together, these findings establish design principles that connect polymer sequence and structure to binding performance, guiding the design of macromolecular chelators with enhanced affinity and selectivity for applications in separations, sensing, and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Characterization of wind conditions and impact on wind loading at an operational parabolic trough concentrating solar power plant using LiDAR observations

Wind loading is a major factor influencing the structural design costs of Concentrating Solar Power (CSP) collector systems, including heliostats and parabolic troughs. Traditionally, these designs have been based on wind-tunnel data, which often fail to accurately represent the dynamic effects experienced at full scale. This study presents a first-of-its-kind experimental characterization of wind conditions within an operational parabolic-trough CSP power plant focusing specifically on using lidar observations. The lidar observations give a unique opportunity to provide insights into wind flow conditions deep within the trough arrays. Our results suggest that (1) after being blocked by the first few rows, the wind speed above the troughs recovers to 73% of its inflow magnitude as it flows further over the trough field due to enhanced turbulent mixing and (2) due to the wind speed recovery, troughs in the interior field will likely experience higher shear-induced turning moments compared those at the front. The conclusions from this work stress the importance of better understanding the wind patterns and interior wind loads when designing solar collectors and highlights the need for more interior load measurements in the future field campaigns.

17 WIND ENERGY↗

DOE OSTI2011

JET MIXING ANALYSIS FOR SRS HIGH-LEVEL WASTE RECOVERY

The process of recovering the waste in storage tanks at the Savannah River Site (SRS) typically requires mixing the contents of the tank to ensure uniformity of the discharge stream. Mixing is accomplished with one to four slurry pumps located within the tank liquid. The slurry pump may be fixed in position or they may rotate depending on the specific mixing requirements. The high-level waste in Tank 48 contains insoluble solids in the form of potassium tetraphenyl borate compounds (KTPB), monosodium titanate (MST), and sludge. Tank 48 is equipped with 4 slurry pumps, which are intended to suspend the insoluble solids prior to transfer of the waste to the Fluidized Bed Steam Reformer (FBSR) process. The FBSR process is being designed for a normal feed of 3.05 wt% insoluble solids. A chemical characterization study has shown the insoluble solids concentration is approximately 3.05 wt% when well-mixed. The project is requesting a Computational Fluid Dynamics (CFD) mixing study from SRNL to determine the solids behavior with 2, 3, and 4 slurry pumps in operation and an estimate of the insoluble solids concentration at the suction of the transfer pump to the FBSR process. The impact of cooling coils is not considered in the current work. The work consists of two principal objectives by taking a CFD approach: (1) To estimate insoluble solids concentration transferred from Tank 48 to the Waste Feed Tank in the FBSR process and (2) To assess the impact of different combinations of four slurry pumps on insoluble solids suspension and mixing in Tank 48. For this work, several different combinations of a maximum of four pumps are considered to determine the resulting flow patterns and local flow velocities which are thought to be associated with sludge particle mixing. Two different elevations of pump nozzles are used for an assessment of the flow patterns on the tank mixing. Pump design and operating parameters used for the analysis are summarized in Table 1. The baseline pump orientations are chosen by the previous work [Lee et. al, 2008] and the initial engineering judgement for the conservative flow estimate since the modeling results for the other pump orientations are compared with the baseline results. As shown in Table 1, the present study assumes that each slurry pump has 900 gpm flowrate for the tank mixing analysis, although the Standard Operating Procedure for Tank 48 currently limits the actual pump speed and flowrate to a value less than 900 gpm for a 29 inch liquid level. Table 2 shows material properties and weight distributions for the solids to be modeled for the mixing analysis in Tank 48.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

The Role of Snowmelt Temporal Pattern in Flood Estimation for a Small Snow‐Dominated Basin in the Sierra Nevada

Abstract Prior research confirmed the substantial bias from using precipitation‐based intensity‐duration‐frequency curves (PREC‐IDF) in design flood estimates and proposed next‐generation IDF curves (NG‐IDF) that represent both rainfall and snow processes in runoff generation. This study improves the NG‐IDF technology for a snow‐dominated test basin in the Sierra Nevada. A well‐validated physics‐based hydrologic model, the Distributed Hydrology Soil Vegetation Model (DHSVM), is used to continuously simulate snowmelt and streamflow that are used as benchmark data sets to systematically assess the NG‐IDF technology. We find that, for the studied small snow‐dominated basin, the use of standard rainfall hyetographs in the NG‐IDF technology leads to substantial underestimation of design floods. Thus, we propose probabilistic hyetographs that can represent unique patterns of events with different underlying mechanisms. For the test basin where flooding events are generated entirely by snowmelt, we develop a hyetograph that characterizes snowmelt temporal patterns, which greatly improves the performance of NG‐IDF technology in design flood estimates. In contrast to the standard rainfall hyetographs characterized by a symmetrically peaked, bell‐shaped curve, the snowmelt hyetograph displays a more rapid rise (i.e., greater intensity) and a distinct diurnal pattern influenced by solar energy input. The results also show that the uncertainty of hyetography plays an important role in design flood estimation and can have important implications for future flood projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

1.5 nm fabrication of test patterns for characterization of metrological systems

Any metrology tool is only as good as it is calibrated. The characterization of metrology systems requires test patterns at a scale about ten times smaller than the measured features. The fabrication of patterns with linewidths down to 1.5 nm is described. The test sample was designed in such a way that the distribution of linewidths appears to be random at any location. This pseudorandom test pattern is used to characterize dimensional metrology equipment over its entire dynamic range by extracting the modulation transfer function of the system. The test pattern contains alternating lines of silicon and tungsten silicide, each according to its designed width. As a result, the fabricated test samples were imaged using a transmission electron microscope, a scanning electron microscope, and an atomic force microscope. (C) 2015 American Vacuum Society.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Pit rim decomposition into multiple quantum dots on surfaces of epitaxial thin films grown on pit-patterned substrates

Here, we report results of dynamical simulations according to an experimentally validated surface morphological evolution model on the formation of regular arrays of quantum dot molecules (QDMs) consisting of 1D arrays of smaller interacting quantum dots (QDs). These QD arrays form along the sides of each pit rim on the surface of a coherently strained thin film epitaxially deposited on a semiconductor substrate, the surface of which consists of a periodic pattern of inverted prismatic pits with rectangular pit openings. We find that this complex QDM pattern results from the decomposition of the pit rim from a “quantum fortress” with four elongated QDs into four 1D arrays of multiple smaller QDs arranged along each side of the pit rim. Systematic parametric analysis indicates that varying the pit opening dimensions and the pit wall inclination directly impacts the number of QDs in the resulting QDM pattern, while varying the pit depth only affects the dimensions of the QDs in the nanostructure pattern. Therefore, the number, arrangement, and sizes of QDs in the resulting pattern of QDMs on the film surface can be engineered precisely by proper tuning of the pit design parameters. Our simulation results are supported by predictions of morphological stability analysis, which explains the pit rim decomposition into multiple QDs as the outcome of a tip-splitting instability and provides a fundamental characterization of the post-instability nanostructure pattern. Our theoretical findings can play a vital role in designing optimal semiconductor surface patterns toward enabling future nanofabrication technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Modeling photovoltaic performance in periodic patterned colloidal quantum dot solar cells

Colloidal quantum dot (CQD) solar cells have attracted tremendous attention mostly due to their wide absorption spectrum window and potentially low processability cost. The ultimate efficiency of CQD solar cells is highly limited by their high trap state density. Here in this paper we show that the overall device power conversion efficiency could be improved by employing photonic structures that enhance both charge generation and collection efficiencies. By employing a two-dimensional numerical model, we have calculated the characteristics of patterned CQD solar cells based of a simple grating structure. Our calculation predicts a power conversion efficiency as high as 11.2%, with a short circuit current density of 35.2 mA/cm 2 , a value nearly 1.5 times larger than the conventional flat design, showing the great potential value of patterned quantum dot solar cells.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

To provide mission support to the Hanford Waste Immobilization and Treatment Plant for the vitrification of legacy nuclear tank waste, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The tank waste will be separated into high-level waste (HLW) and low-activity waste (LAW) fractions, where the majority by mass (~90%) is LAW and by activity (>95%) is HLW. The first tank waste to be processed at the WTP will be LAW. Since Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high costs of radioactive operations and provide an engineering platform in close proximity to local operations staff. The objective is to produce similar process conditions to those encountered in the full-scale LAW melters and minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area, melter glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models have been developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten glass pool and within the bulk glass pool. A method was developed to correlate results to an estimated melt rate and down-select design features that produce the highest gains.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Effects of sample design and landscape features on a measure of environmental heterogeneity

Environmental heterogeneity, an important influence on organisms and ecological processes, can be quantified by the variance of an environmental characteristic over all locations within a study extent. However on landscapes with autocorrelation and gradient patterns, estimating this variance from a sample of locations may lead to errors that cannot be corrected with statistical techniques. We analytically derived the relative expected sampling error of sample designs on landscapes with particular gradient pattern and autocorrelation features. We applied this closed-form approach to temperature observations from an existing study. The expected heterogeneity differed, both in magnitude and direction, amongst sample designs over the study site's likely range of autocorrelation and gradient features. We conducted a simulation study to understand the effects of (i) landscape variability and (ii) design variability on an average sampling error. On 10 000 simulated landscapes with varying gradient and autocorrelation features, we compared estimates of variance from a variety of structured and random sample designs. While gradient patterns and autocorrelation cause large errors for some designs, others yield near-zero average sampling error. Sample location spacing is a key factor in sample design performance. Random designs have larger range of possible sampling errors than structured designs due to the potential for sample arrangements that over- and under-sample certain areas of the landscape. Furthermore, when implementing a new sample design to quantify environmental heterogeneity via variance, we recommend using a simple structured design with appropriate sample spacing. For existing designs, we recommend calculating the relative expected sampling error via our analytical derivation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Atomic understanding of structural deformations upon ablation of graphene

We investigate the atomic rearrangement in graphene under femtosecond pulse illumination with reactive molecular dynamics simulations and compare with ultra-fast laser ablation experiments. To model the impact of the laser pulse irradiation, heat is locally applied to a selected area of the graphene layer and the resulting structural deformation is simulated as a function of time, providing a detailed understanding of the bond breaking process under laser illumination and subsequent re-equilibration afterAQ3 the pulse is turned off. Analysis of the atomic dynamics indicates that the types of defects formed depend on the pulse energy and exposure duration. By varying the exposed area, we determine that the shape of the ablated area is not only a function of the pulse energy, but also of the beam spot size and pulse repetition. Furthermore, we apply a machine learning approach to extrapolate our simulated data to experimental length scales and reproduce the trends in ablated area as a function of temperature. Furthermore, our study provides a first step towards understanding the design parameters for graphene nano-patterning.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2019

QUIC-fire: A fast-running simulation tool for prescribed fire planning

Coupled fire-atmospheric modeling tools are increasingly used to understand the complex and dynamic behavior of wildland fires. Multiple research tools linking combustion to fluid flow use Navier-Stokes numerical solutions coupled to a thermodynamic model to understand fire-atmospheric feedbacks, but these computational fluid dynamics approaches require high-performance computing resources. We present a new simulation tool called QUIC-Fire to rapidly solve these feedbacks by coupling the mature 3-D rapid wind solver QUIC-URB to a physics-based cellular automata fire spread model Fire-CA. QUIC-Fire uses 3-D fuels inputs similar to the CFD model FIRETEC, allowing this tool to simulate effects of fuel structure on local winds and fire behavior. Results comparing fire behavior metrics to the computational fluid dynamic model FIRETEC show strong agreement. As a result, QUIC-Fire is the first tool intended to provide an opportunity for prescribed fire planners to compare, evaluate and design burn plans, including complex ignition patterns and coupled fire atmospheric feedbacks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

A fast method for optical simulation of flood maps of light-sharing detector modules

Optical simulation of the detector module level is highly desired for Position Emission Tomography (PET) system design. Commonly used simulation toolkits such as GATE are not efficient in the optical simulation of detector modules with complicated light-sharing configurations, where a vast amount of photons need to be tracked. Here, we present a fast approach based on a simplified specular reflectance model and a structured light-tracking algorithm to speed up the photon tracking in detector modules constructed with polished finish and specular reflector materials. We also simulated conventional block detector designs with different slotted light guide patterns using the new approach and compared the outcomes with those from GATE simulations. And while the two approaches generated comparable flood maps, the new approach was more than 200–600 times faster. The new approach has also been validated by constructing a prototype detector and comparing the simulated flood map with the experimental flood map. The experimental flood map has nearly uniformly distributed spots similar to those in the simulated flood map. In conclusion, the new approach provides a fast and reliable simulation tool for assisting in the development of light-sharing-based detector modules with a polished surface finish and using specular reflector materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Development of a clostridia-based cell-free system for prototyping genetic parts and metabolic pathways

Gas fermentation by autotrophic bacteria, such as clostridia, offers a sustainable path to numerous bioproducts from a range of local, highly abundant, waste and low-cost feedstocks, such as industrial flue gases or syngas generated from biomass or municipal waste. Unfortunately, designing and engineering clostridia remains laborious and slow. The ability to prototype individual genetic part function, gene expression patterns, and biosynthetic pathway performance in vitro before implementing designs in cells could help address these bottlenecks by speeding up design. Unfortunately, a high-yielding cell-free gene expression (CFE) system from clostridia has yet to be developed. Here in this paper, we report the development and optimization of a high-yielding (236 ± 24 μg/mL) batch CFE platform from the industrially relevant anaerobe, Clostridium autoethanogenum. A key feature of the platform is that both circular and linear DNA templates can be applied directly to the CFE reaction to program protein synthesis. We demonstrate the ability to prototype gene expression, and quantitatively map aerobic cell-free metabolism in lysates from this system. We anticipate that the C. autoethanogenum CFE platform will not only expand the protein synthesis toolkit for synthetic biology, but also serve as a platform in expediting the screening and prototyping of gene regulatory elements in non-model, industrially relevant microbes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Broadband Light Extraction from Near-Surface NV Centers Using Crystalline-Silicon Antennas

We use crystalline silicon (Si) antennas to efficiently extract broadband single-photon fluorescence from shallow nitrogen-vacancy (NV) centers in diamond into free space. Our design features relatively easy-to-pattern high-index Si resonators on the diamond surface to boost photon extraction by overcoming total internal reflection and Fresnel reflection at the diamond-air interface and providing modest Purcell enhancement, without etching or otherwise damaging the diamond surface. In simulations, ∼17 times more single photons are collected from a single NV center compared to the case without the antenna; in experiments, we observe an enhancement of ∼9 times, limited by spatial alignment between the NV and the antenna. Furthermore, our approach can be readily applied to other color centers in diamond, and more generally to the extraction of light from quantum emitters in wide-bandgap materials.

Antennas↗

DOE OSTI2014

Synthesis and Systematic Trends in Structure and Electrical Properties of [(SnSe) 1.15 ] m (VSe 2 ) 1 , m = 1, 2, 3, and 4

Four compounds [(SnSe)1.15]m(VSe2)1, where m = 1–4, were synthesized to explore the effect of increasing the distance between Se–V–Se dichalcogenide layers on electrical transport properties. These kinetically stable compounds were prepared using designed precursors that contained a repeating pattern of elemental layers with the nanoarchitecture of the desired product. XRD and STEM data revealed that the precursors self-assembled into the desired compounds containing a Se–V–Se dichalcogenide layer precisely separated by a SnSe layer. The 00l diffraction data are used to determine the position of the Sn, Se, and V planes along the c-axis, confirming that the average structure is similar to that observed in the STEM images, and the resulting data agrees well with results obtained from calculations based on density functional theory and a semiempirical description of van der Waals interactions. The in-plane diffraction data contains reflections that can be indexed as hk0 reflections coming from the two independent constituents. The SnSe layers diffract independently from one another and are distorted from the bulk structure to lower the surface free energy. All of the samples showed metallic-like behavior in temperature-dependent resistivity between room temperature and about 150 K. The electrical resistivity systematically increases as m increases. Below 150 K the transport data strongly indicates a charge density wave transition whose onset temperature systematically increases as m increases. This suggests increasing quasi-two-dimensional behavior as increasingly thick layers of SnSe separate the Se–V–Se layers. This is supported by electronic structure calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗