Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Structural properties”

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.

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

At least 1,189 records · Page 66

Predicted Impacts of Pt and Ionomer Distributions on Low-Pt-Loaded PEMFC Performance

Low-cost, high performance proton exchange membrane fuel cells (PEMFCs) have been difficult to develop due to limited understanding of coupled processes in the cathode catalyst layer (CCL). Low-Pt-loaded PEMFCs suffer losses beyond those predicted solely due to reduced catalyst area. Although consensus links these losses to thin ionomer films in the CCL, a precise mechanistic explanation remains elusive. In this publication, we present a physically based PEMFC model with novel structure-property relationships for thin-film Nafion, validated against PEMFC data with low Pt loading. Results suggest that flooding exacerbates kinetic limitations in low-loaded PEMFCs, shifting the Faradaic current distribution. As current density increases, protons travel further into the CCL, resulting in higher Ohmic overpotentials. We also present a parametric study of CCL design parameters. We find that graded Pt and ionomer loadings reduce Ohmic losses and flooding, but individually do not provide significant improvements. However, a dual-graded CCL (i.e., graded Pt and ionomer) is predicted to significantly improve the maximum power density and limiting current compared to uniformly loaded CCLs. This work highlights the importance of accurate transport parameters for thin-film Nafion and provides a pathway to low-cost PEMFCs via precise control of CCL microstructures.

08 HYDROGEN↗

INN Airfoil Tools

This software package contains code to perform airfoil inverse shape design using a sparsified invertible neural network model. This is a specialized deep learning architecture that enables both network weights to be shared to evaluate forward or inverse passes through the network. As a design tool, this network allows practitioners to specify desired aerodynamic and structural properties and generate shapes that satisfy those properties. The invertible neural network is accompanied with tuned parameters as well as software tools to train new models as needed.

Glaws, Andrew↗

Vibrational Spectroscopic Monitoring of the Gelation Transition in Nafion Ionomer Dispersions

Infrared and Raman spectroscopy techniques were applied to investigate the drying and aggregation behavior of Nafion ionomer particles dispersed in aqueous solution. Gravimetric measurements aided the identification of gel-phase development within a series of time-resolved spectra that tracked transformations of a dispersion sample during solvent evaporation. A spectral band characteristic of ionomer sidechain end group vibration provided a quantitative probe of the dispersion-to-gel change. For sets of attenuated total reflection Fourier transform infrared (ATR FT-IR) spectra, adherence to Beer's law was attributed to the relatively constant refractive index in the frequency region of hydrated –SO$^{–}_{3}$ group vibrations as fluorocarbon-rich ionomer regions aggregate in forming the structural framework of membranes and thin films. Although vibrational bands associated with ionomer backbone CF 2 stretching vibrations were affected by distortion characteristic of wavelength-dependent refractive index change within a sample, the onset of band distortion signaled gel formation and coincided with ionomer mass % values just below the critical gelation point for Nafion aqueous dispersions. Similar temporal behavior was observed in confocal Raman microscopy experiments that monitored the formation of a thin ionomer film from an individual dispersion droplet. For the ATR FT-IR spectroscopy and confocal Raman microscopy techniques, intensity in the water H–O–H bending vibrational band dropped sharply at the ionomer critical gelation point and displayed a time dependence consistent with changes in water content derived from gravimetric measurements. The reported studies lay groundwork for examining the impact of dispersing solvents and above-ambient temperatures on fluorinated ionomer transformations that influence structural properties of dispersion-cast membranes and thin films.

36 MATERIALS SCIENCE↗

Utah FORGE 2439: A Multi-Component Approach to Characterizing In-Situ Stress

Core-based in-situ stress estimation, Triaxial Ultrasonic Velocity (labTUV) data, and Deformation Rate Analysis (DRA) data for Utah FORGE well 16A(78)-32 using triaxial ultrasonic velocity and deformation rate analysis. Report documenting a multi-component approach to characterizing in-situ stress at the U.S. DOE FORGE EGS site: laboratory, modeling and field measurement. Core-based methods for in-situ stress estimation were applied using samples from 5 intervals within the Utah FORGE 16A(78)-32 well. At three of these locations, Triaxial Ultrasonic Velocity (labTUV) tests were performed, resulting in experimentally-determined relationships between wave velocities and stresses. Non-monotonic increase in the velocity-stress relationships are inferred provide evidence of stress history and are therefore used to estimate in-situ stress magnitudes. Additionally, Deformation Rate Analysis (DRA) tests were run on core plugs from various orientations at each of the 5 sampling locations. These, too, provide evidence of stress history based on stress-strain behavior. A novel Weight of Evidence (WoE) method was developed as a means of synthesizing in-situ stress evidence from these two types of tests. Results indicate the minimum horizontal stress gradient ranges from 0.58 psi/ft to 0.69 psi/ft, with 4 of the 5 values between 0.66 psi/ft and 0.69 psi/ft. The vertical stress gradient ranges from 1.05 psi/ft to 1.12 psi/ft, with 4 of the 5 zones given results between 1.09 psi/ft and 1.12 psi/ft. The maximum horizontal stress gradient ranges from 0.98 psi/ft to 1.34 psi/ft, with 4 of the 5 zones falling between 0.98 psi/ft and 1.24 psi/ft. The stress regime thus appears to be on the edge between normal faulting and strike-slip faulting, potentially flipping back and forth between the two regimes due to variability of rock properties, structures such as faults, and/or thermal anomalies.

15 GEOTHERMAL ENERGY↗

Dynamic structural views in solar energy materials by femtosecond electron diffraction

Solar materials convert light into other forms of energy through excited state processes occurring on ultrafast time and atomic length scales. Understanding and controlling such nonequilibrium processes is essential for applications ranging from photovoltaics to photocatalysis. These processes are commonly studied by transient optical techniques, which resolve charge carrier dynamics. However, optical spectroscopy does not directly probe the atomic-scale motions that play a central role in the ultimate functionality of these materials. Filling this missing gap, ultrafast electron and x-ray scattering techniques enable monitoring of structural dynamics in materials with femtosecond time resolution. In this work, we focus on the use of ultrafast electron diffraction (UED) techniques to probe photoinduced energy conversion dynamics in solar energy materials. First, we discuss the use of UED as an ultrafast lattice thermometer allowing a direct probe of nonradiative relaxations such as hot carrier cooling and Auger recombination. Second, we present a time-resolved atomic pair distribution function analysis enabled by UED, which uncovers lattice deformations arising from excitation localization in materials. Finally, we provide an outlook looking toward new approaches for resolving in situ energy conversion dynamics and uncovering structure–property relationships in solar energy materials.

36 MATERIALS SCIENCE↗

Quantitative multi-image analysis in metals research

Abstract Quantitative multi-image analysis (QMA) is the systematic extraction of new information and insight through the simultaneous analysis of multiple, related images. We present examples illustrating the potential for QMA to advance materials research in multi-image characterization, automatic feature identification, and discovery of novel processing-structure–property relationships. We conclude by discussing opportunities and challenges for continued advancement of QMA, including instrumentation development, uncertainty quantification, and automatic parsing of literature data. Graphical abstract

36 MATERIALS SCIENCE↗

A perspective on Bayesian methods applied to materials discovery and design

For more than two decades, there has been increasing interest in developing frameworks for the accelerated discovery and design of novel materials that could enable promising and transformative technologies. The Integrated Computational Materials Engineering (ICME) program called for integrating computational tools to establish linkages along process-structure-property-performance (PSPP) chains. The Materials Genome Initiative called for integrating experiments and computations within data science frameworks as a strategy to accelerate the materials development cycle. While these frameworks and paradigms have been quite influential, traditional ICME or data science-based approaches tend to have some limitations, mainly when querying the materials space is costly and very little information is available. Bayesian methods are more suitable in this context due to their efficiency gains. To this end, the materials discovery problem is framed as a Bayesian Optimization (BO). Different examples in which BO has been applied to solve materials discovery problems are presented. The methods/examples discussed include BO under model uncertainty, multi-information source BO, multi-objective and multi-constraint BO, and batch BO. Bayesian Materials Discovery is a promising area of research that is likely to become more influential as more attention is put on autonomous materials discovery platforms. Therefore, a discussion is provided on the potential development of such methods to increase the ability of existing platforms in materials discovery. Here, the ultimate goal is to pave the way to autonomous materials discovery.

36 MATERIALS SCIENCE↗

Compiler and Runtime Approaches to Enable Large-Scale Irregular Programs. Final report, July 2013 - July 2019

While regular algorithms, characterized by operations on dense matrices and arrays, have long been the mainstay of scientific, high-performance computing, irregular algorithms, which feature unpredictable accesses to pointer-based data structures, are becoming increasingly common in high performance computing, arising in graph analysis, data mining and visualization, among other domains. Unfortunately, the defining characteristics of irregular applications, their dynamic, unpredictable, data-dependent access patterns and data layouts, make achieving high performance on large scale systems difficult. Scaling applications to peta- and exa-scale requires carefully controlling communication and data movement and placement, an inherently difficult task when access patterns and data layouts are unpredictable! Most irregular applications that attain high performance must be painstakingly hand-written and hand-tuned, with few common principles or paradigms uniting various implementations and easing future development. Despite the increasing importance of irregular applications, there is little programmer knowledge, and even less compiler ability, devoted to optimizing them. This project aims to solve these problems. By allowing programmers to write irregular applications in high level forms, with at most a few annotations highlighting key structural properties, programmers can focus on developing their algorithms and methods. The compiler and run-time system can take on the tedious task of optimizing the application for execution at large scales, and can automatically provide efficient implementations. This will provide portability and ease maintenance for existing irregular applications, but, more importantly, open up whole new domains of computational science to large-scale, high-performance simulation codes.

97 MATHEMATICS AND COMPUTING↗

Novel High Temperature Carbide and Boride Ceramics for Direct Power Extraction Electrode Applications. Final report

The current project aims to develop new carbide and boride ceramic materials that incorporate different metal elements (e.g., (Hf 1-x Zr x )B 2 , also called ceramic solid solutions) and understand the fundamental composition-processing-structure-property relationships for such materials. Specifically, nano powders and related nano-composites for selected mixed metal carbide and boride materials are synthesized from nano-scale mixed precursors obtained from solution-based processing via heat treatment in inert atmosphere. The obtained fine powders were then consolidated into dense ceramics via a novel flash sintering process. The mechanical properties and thermal oxidation resistance for the obtained materials were evaluated for these materials. It was found that different synthesis routes produced powders with somewhat different characteristics in terms of composition and microstructure, which then led to different properties for the final ceramics. The synthesis and processing methods demonstrated in this study might be adopted for developing other similar high temperature ceramics, while the mixed metal or solid solution ceramic materials obtained from this study might be used as hot electrodes for direction power extraction and other energy-related applications.

20 FOSSIL-FUELED POWER PLANTS↗

Enabling Efficiencies > 22.5% with Metal Oxide Passivating Contacts using Low-Cost Spatial Atomic Layer Deposition (Final Technical Report)

In this project, the University of Central Florida (UCF) worked to both increase module efficiency and reduce manufacturing cost by driving demonstrated lab-scale passivating contact technology using materials and processes compatible with high-volume manufacturing for crystalline silicon (c-Si) photovoltaic (PV) cells. Passivating contacts have garnered significant attention in recent years. They provide a means of suppressing contact recombination, a loss mechanism that limits the performance of industrially relevant cell architectures like Al back surface field (Al-BSF) cells and passivated emitter and rear cells (PERC). Most of the development of passivating contact technology has focused on the use of doped amorphous silicon or doped polysilicon contacts, but both suffer from parasitic optical absorption amongst other issues. Our team developed fully transparent hole-selective heterojunctions, deposited using atomic layer deposition (ALD), and showed how they could be incorporated into c-Si PV cells. The team conducted experiments to understand the process-structure-property relationship of hole-selective oxides, surface passivation oxide materials, and transparent conductive oxides deposited by ALD, and use that understanding to reduce contact recombination, contact resistivity, and parasitic optical absorption within c-Si PV cells. Before getting into the details of the report, we would like to note that COVID-19 has made it more challenging to conduct experimental research at UCF. UCF has a number of mandatory policies in place to ensure social distancing, testing, and contact tracing are all carried out in day-to-day operations. Despite these challenges, we worked diligently to make progress on this project in a manner that was as safe as possible. Over the course of the project, the UCF team and its collaborators have made the following discoveries and developments.

14 SOLAR ENERGY↗

Rheo-Structural Spectroscopy: Fingerprinting the In Situ Response of Fluids to Arbitrary Flow Fields

The objectives of this project were to develop new sample environments, measurement methodologies and associated modeling tools for characterizing the structural response to arbitrarily complex processing flows using small angle scattering, and to apply these new tools for understanding the fundamental physics governing the structuring of anisotropic particulate and polymeric materials under flow histories and conditions relevant to industrial processing flows. The research resulted in the development and implementation of a new sample environment, the fluidic four roll mill (FFoRM), for in situ small angle neutron and X-ray scattering (SANS/SAXS) measurements. These measurements are capable of generating large data sets that “fingerprint” how a complex fluid responds to a wide range of flow histories involving time variations in deformation type and rate. New modeling tools were developed to extract detailed microstructural information from such data sets, including orientation distribution functions and interparticle correlation functions, as well as reduced-order parametric descriptors of these high-dimensional functions that can be used to readily map, visualize and interpret a fluid’s structural response to its flow history. These new tools were applied to a range of model materials involving elongated particle suspensions in order to provide new insights into the physics of how flow couples with orientational and structural order in complex flows, particularly under non-dilute conditions for which no accurate theories currently exist. Using these investigations, we elucidated a number of new insights into the fundamental phenomena driving such process-structure-property relationships. These findings provide guidance for the further development of rheological models, and ultimately can inform the rational and model-based design of flow processes to achieve optimized orientational ordering that is key to the properties and function of a wide range of energy-relevant materials.

36 MATERIALS SCIENCE↗

Development of efficient solar cells using combination of QSPR and DFT approaches

The awarded research project aimed to design and determine the effective organic dye-sensitizers from the ensemble of chromophores for the dye-sensitized solar cell (DSSC) and fullerene-derivatives (FDs) as acceptor for polymer solar cell (PSC) followed by explore the electron transfer mechanism using the combined quantitative structure-property relationship (QSPR) analysis in conjunction with density functional theory (DFT) and time-dependent DFT (TDDFT)-based calculations. Based on our proposal we have employed different in silico approaches to design photo-efficient organic dye-sensitizers for DSSCs and FDs as acceptor for PSCs with exhaustive screening methodology.

14 SOLAR ENERGY↗

Machine Learning for Automated Weld Quality Monitoring and Control (CRADA 461)

The emergence of Artificial Intelligence (AI) and Machine Learning (ML) methods may provide an alternative pathway to elicit the desired process-structure-property relationship. To achieve such relationship at an accelerated pace the use of data driven machine learning techniques are employed. This CRADA investigates the use and effectiveness of applying AI/ML techniques to a large dataset with the intention of creating a data-driven model that will predict processing parameters required to join lightweight materials at optimal performance.

97 MATHEMATICS AND COMPUTING↗

Durable Mn-Based PGM-Free Catalysts for Polymer Electrolyte Membrane Fuel Cells

This proposed project aims to develop and evaluate novel manganese based, nitrogen-derived, PGM-free electrocatalysts (denoted as Mn-N-C) to fully address the membrane electrolyte assemblies (MEA)’s ionomer degradation issue resulting from iron. Four thrusts will be pursed in this proposed project. First, advanced first-principles computation methods will be employed to accelerate the rational catalyst design and synthesis. Second, an effective hydro-gel method will be used to maximize atomic Mn active sites embedded in carbon matrix. Next, state-of-the art methods in fuel cell companies will be used to fabricate MEAs containing the Mn-N-C catalysts. Finally, industry standards will be rigorously followed to evaluate fuel cell performance and durability of the Mn-N-C catalysts. With successful completion of the project, it is expected that the following outcomes will be achieved. (1) A set of MEAs containing the Mn-N-C catalysts and with active area large than 50 cm 2 for independent testing, (2) testing results demonstrating that the MEAs of Mn-N-C catalysts have mass activity of 0.044 A/cm 2 at 0.9 VIR-free and H 2 /air performance of 0.50 V at 1.0 A/cm 2 ; (3) fundamental understanding of the composition-structure-property relation of the PGM-free Mn- N-C catalysts, and (4) computational data, measurement data, and publications deposited into the database of ElectroCat Consortium.

08 HYDROGEN↗

Bamboo Bio-composite Truck/Trailer Decking

Bamboo is one of the fastest growing plants in the world. Massively productive, bamboo will maintain that productivity with limited inputs and minimal management resulting in predictable volume and operating margins and with low overhead. The goal of this project was to develop a bamboo bio-composite trailer decking product that replaces apitong, is lighter weight, stronger and luminescent. The collaboration partners, Fontaine, Resource Fiber and IACMI, worked closely to develop the bamboo bio-composite decking to Fontaine Trailer’s (end-user) specifications. The various technological objectives were (a) To conduct a comprehensive Design of Experiments study for bamboo composites to understand the structure-property relationships for different resin composites and bamboo forms (strips, woven, bulk etc); (b) To establish the nail pull out characteristics of trailer deck geometry bamboo composite form. The nail pull out is a critical test in trailer decks; (c) To design, process and prototype select number of trailer decking planks for Fontaine evaluation; and (d) To conduct life cycle analysis to conduct energy calculations from the various conversion steps of the bamboo from crop to product. The project meets DOE/IACMI metrics of reduced embodied energy, lightweighting and lowering the cost of the end product. It also offers a green solution to a value-added application, i.e. trailer decking. The development goals and benefits of bamboo composite decking included: A. Decreased weight when compared to Apitong and Gen 1, thereby reducing operating costs and petroleum usage due to increased miles per gallon. B. Flexibility to allow camber design into trailers. C. Luminescence to increase safety during low light and dark conditions. D. Composite material to maximize use of bamboo bio-composites as substitute for petroleum-based composites. E. Embedded layer(s) of conditioned bamboo for added strength and stability. F. Improved safety over Apitong by temporary cargo indentation in planks for better stability. G. Cradle-to-cradle design so end-of-life becomes beginning-of-life for other products. Resource Fiber’s bamboo biocomposite trailer decking passed nail pullout tests as compared to apitong (incumbent), was lighter weight than apitong, and used less embodied energy particularly when bamboo is sourced domestically. The planks were optimized in the lab setting to the extent possible and successfully installed on the trailer at Fontaine for field testing. Despite the process not being fully optimized due to through-heat and tooling limitations within the budget constraints, the prototype decking withstood 400 cycles of reverse fatigue loading of a 107,000 lb Caterpillar 349F which was extreme conditions of field testing by Fontaine Trailer. Resource Fiber plans to outsource production of a next round of planks with a commercial pultrusion processor, then to do a re-test with Fontaine Trailers. Tooling specific to the part is required. Long-term commercial plans are to continue outsourcing production while supplying bamboo fiber and mats. Commercial markets include heavy haul trailers, military trailers, and decking for marine, industrial and residential use.

36 MATERIALS SCIENCE↗

Complex Functional Materials

The Complex Functional Materials (CFM) area of leadership focuses on the identification and development of materials comprised of multiple components or building blocks that are integrated or chemically bound together to achieve a desired function or response. Soft materials, such as polymers, as well as structural properties at the meso- and micro-scale that control materials function are particularly emphasized in this leadership area. Further, complex functional materials are generally developed to satisfy multiple materials design criteria all of which are essential to the overall application. CFM supports applications that are aligned with all three Los Alamos National Laboratory mission areas. These mission areas are: materials for nuclear deterrence, materials for energy security, and materials for global security

36 MATERIALS SCIENCE↗

Fractal-Fin, Dimpled Solar Heat Collector with Solar Glaze

Exterior solar glaze was added to a 3 foot x 3 foot x 3 foot aluminum solar collector that had six triangular dimpled fins for enhanced heat transfer. The interior vertical wall on the south side was also dimpled. The solar glaze was added to compare its solar collection performance with unglazed solar collector experiments conducted at Sandia in 2021. The east, west, front, and top sides of the solar collector were encased with solar glaze glass. Because the solar incident heat on the north and bottom sides was minimal, they were insulated to retain the heat that was collected by the other four sides. The advantages of the solar glaze include the entrapment of more solar heat, as well as insulation from the wind. The disadvantages are that it increases the cost of the solar collector and has fragile structural properties when compared to the aluminum walls. Nevertheless, prior to conducting experiments with the glazed solar collector, it was not clear if the benefits outweighed the disadvantages. These issues are addressed herein, with the conclusion that the additional amount of heat collected by the glaze justifies the additional cost. The solar collector glaze design, experimental data, and costs and benefits are documented in this report.

14 SOLAR ENERGY↗