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Results for “Michael Addition”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Influence of geometry on columnar to equiaxed transition during electron beam powder bed fusion of IN718

Correlation between spot-melt scan parameters (linear spot-density aka areal energy density), build geometry, and solidification microstructure evolution (columnar vs equiaxed) in a powder bed fusion technology is investigated. It is shown that to maintain the equiaxed solidification microstructure evolution in electron beam powder bed additive manufacturing (AM), the areal energy density per layer needs to be scaled with respect to the 2D cross-sectional area of the layer being melted. Samples with two different cross-sectional areas (40 × 40 mm and 20 × 20 mm) have been fabricated with varying areal energy densities. For a given square cross-section (20 × 20 mm), increasing the areal energy density (4.8 MJ/sq.m to 14.7 MJ/sq.m) transitioned the solidification microstructure from columnar to equiaxed. The observed microstructure data (Electron Back Scattered Diffraction - EBSD) is quantified by calculating the principal component (PC) score using a spatial statistics methodology. The sample with equiaxed grains is found to have a low PC score while the sample with columnar grain had a high PC score. A semi-analytical model is used to simulate the heat transfer and the local solidification conditions as a function of processing parameters (linear spot-density). The result from the heat transfer model is correlated with previously quantified microstructure data. Space-Time analysis of the melt pattern is done and correlated with the observed microstructure. In addition, from the findings, appropriate parameters have been used to additively manufacture a turbine blade with site-specific or hybrid solidification microstructure (traditional fabrication possible via a patented method of localized cold working and heat treatment).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Self-supervised learning of spatiotemporal thermal signatures in additive manufacturing using reduced order physics models and transformers

Microstructure control via additive manufacturing has enormous potential as manufacturers, materials scientists, and designers alike seek to exploit novel fabrication technologies to improve component performance. Recent works have demonstrated the feasibility of producing materials with controlled microstructures across various length scales. However, the experimental approach towards exploring the process-structure space can be laborious and costly. This is particularly true if also considering scan pattern optimization which is well suited for processes such as powder bed fusion electron beam melting. In this work we propose an approach for encoding additive manufacturing layer-wise thermal response signatures using self-supervised representation learning. Thermal simulations from a reduced order model are utilized to estimate the spatiotemporal response during printing. A machine learning framework, using video-transformers, is utilized to efficiently distill spatiotemporal patterns into a compact latent space representation. This latent state representation encodes the relevant physics which is then utilized to establish a data-driven process-structure model for an additively manufactured Ni-based superalloy. In conclusion, the proposed methodology could potentially be used towards in-situ process monitoring, scan pattern experimental design, and component qualification.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Potential of U.S. Marine and Offshore Wind Energy to Power Marine Carbon Dioxide Removal

The goal of this project was to provide a preliminary feasibility assessment of powering different marine carbon dioxide removal (mCDR), carbon capture (mCC), and carbon sequestration (mCS) strategies with marine energy. The investigation focused on methods with clear power requirements at sea beyond monitoring such as artificial upwelling, deep ocean storage, electrochemical (eChem) mCDR and mCC, offshore microalgae cultivation, and seaweed farming and sinking. The project found that eChem mCDR powered by marine energy and offshore wind energy available in the United States could meet global CDR scales needed by 2040 and 2050 to limit warming to 1.5 degrees C by 2100 and marine energy alone could greatly contribute to reaching scales needed by 2040. Note that this preliminary estimate assumes that it is possible to harvest all the marine and offshore wind resources available in the United States with existing technology options. Though the biological methods were limited in scale they still hold promise in developing carbon negative fuels and products which can reduce emissions in the short term.

afforestation↗
DOE OSTI2023

Green Additive Limits Runaway Crystallinity in PM6:Y6 Organic Solar Cells but Causes Field-Independent Geminate Recombination

Solvent additives are well-established for improving device performance of organic solar cells by enhancing nanodomain phase separation and crystallization. However, optimum additive concentrations are typically at trace amounts with slight fluctuations causing runaway crystallinity that short the device and limit scale-up potential. Furthermore, we show that a nonhalogenated solvent additive 1-phenylnaphthalene (PN) can be used to optimize high-performance PM6:Y6 devices, but without runaway crystallinity even at concentrations 10× above the optimum. Our holistic analysis of device losses shows that PN increases photoabsorption while decreasing bimolecular recombination. However, above the optimum, charge generation is reduced due to field-independent geminate recombination of charge transfer states that overcomes the other benefits. Rotated Y6 crystallite orientation is a likely culprit, where the device electric field is ineffective at separating the charges. Despite this, device performance remains higher than that of traditional additives, indicating a route to avoiding the high sensitivity of performance to processing conditions.

14 SOLAR ENERGY↗
DOE OSTI2023

Impact of hydrogen bonding pendant groups in polymer grafted nanoparticles on interlayer adhesion and mechanical properties in material extrusion printing

The addition of nanoparticles or copolymer grafted nanoparticles (CPGNPs) to polymeric matrices greatly improves thermomechanical properties of the resulting nanocomposite, but corresponding studies of nanocomposite systems created by 3D printing are few, especially in the realm of functional polymeric materials. Here we describe how silica nanoparticle-grafted, random copolymers of poly(methyl methacrylate-random-2-uriedo-[1H]-pyrimidinone methacrylate) (P(MMA-r-UPyMA) dramatically increases the mechanical properties of poly(methyl methacrylate) (PMMA) based nanocomposite specimens created by melt extrusion printing. Most notably, when these novel CPGNPs are combined with PMMA matrix chains via a solution-based process, printed specimens containing only 0.5 wt% additive show significant increases in Young’s modulus (90%), storage modulus (93%), tensile modulus (148%) and ultimate tensile strength (110%). These improvements are ascribed to strengthening of adhesion across interfaces due to multi-point hydrogen bonding between UPyMA groups, the reinforcement effect of the P(MMA-r-UPyMA)-grafted silica nanoparticles, as well as hydrogen bonding interactions and entanglements between graft and matrix chains. Imaging of fracture surfaces after tensile testing reveals that in comparison to nanocomposites created by simple mechanical mixing of solids, the solution-casting process improves the dispersion of nanoparticles and reduces the void spaces between printed roads. These studies demonstrate that introducing functionality into polymer grafts, such as hydrogen bonding interactions, and intimate mixing of polymer-modified nanomaterials can greatly improve interlayer adhesion and mechanical properties, thereby advancing this method of polymer additive manufacturing

36 MATERIALS SCIENCE↗
DOE OSTI2024

Efficient particle control in systems with large density gradients

Simulations of large density gradients present a number of challenges for direct Monte Carlo methods, since they lead to too few particles in dilute regions and prohibitively many in the dense regions. Here, we propose a particle control methodology that gives the user more control of the number of particles per cell by introducing a variable weight for each particle. The proposed scheme is based on the stochastic weighted particle method, requires only small modifications to DSMC, and exactly conserves mass, momentum, and energy. In validation tests of systems with density ratios of order 102-104, we observe 101-102 times less variance in the dilute region compared to a DSMC solution with the same number of system particles, while introducing a moderate additional computational cost.

DSMC↗
DOE OSTI2023

GMLC Technical Assistance to States: DER Interconnection Workshop #2 [Slides]

NREL hosted this workshops to help state public utility commissions (PUCs) understand the materials and support available to assist in distributed energy resource (DER) interconnection activities. This workshop focused on "Modern DER Capabilities and Deployment Concerns" and included four speakers, whose material will be posted at https://www.nrel.gov/grid/ieee-standard-1547/workshops.html. The slides in this deck were for the facilitator to provide context to the attendees, as well as additional resources on the topics discussed.

1547↗
DOE OSTI2021

Modeling of Combined Lead Fast Reactor and Concentrating Solar Power Supercritical Carbon Dioxide Cycles to Demonstrate Feasibility, Efficiency Gains, and Cost Reductions

Solar power has innate issues with weather, grid demand and time of day, which can be mitigated through use of thermal energy storage for concentrating solar power (CSP). Nuclear reactors, including lead-cooled fast reactors (LFRs), can adjust power output according to demand; but with high fixed costs and low operating costs, there may not be sufficient economic incentive to make this worthwhile. We investigate potential synergies through coupling CSP and LFR together in a single supercritical CO 2 Brayton cycle and/or using the same thermal energy storage. Combining these cycles allows for the LFR to thermally charge the salt storage in the CSP cycle during low-demand periods to be dispatched when grid demand increases. The LFR/CSP coupling into one cycle is modeled to find the preferred location of the LFR heat exchanger, CSP heat exchanger, sCO 2 -to-salt heat exchanger (C2S), turbines, and recuperators within the supercritical CO 2 Brayton cycle. Three cycle configurations have been studied: two-cycle configuration, which uses CSP and LFR heat for dedicated turbocompressors, has the highest efficiencies but with less component synergies; a combined cycle with CSP and LFR heat sources in parallel is the simplest with the lowest efficiencies; and a combined cycle with separate high-temperature recuperators for both the CSP and LFR is a compromise between efficiency and component synergies. Additionally, four thermal energy storage charging techniques are studied: the turbine positioned before C2S, requiring a high LFR outlet temperature for viability; the turbine after the C2S, reducing turbine inlet temperature and therefore power; the turbine parallel to the C2S producing moderate efficiency; and a dedicated circulator loop. While all configurations have pros and cons, use of a single cycle offers component synergies with limited efficiency penalty. Using a turbine in parallel with the C2S heat exchanger is feasible but results in a low charging efficiency, while a dedicated circulator loop offers flexibility and near-perfect heat storage efficiency but increasing cost with additional cycle components.

14 SOLAR ENERGY↗
DOE OSTI2023

GMLC Technical Assistance to States: DER Interconnection Workshop #3

NREL hosted this workshop to help state public utility commissions (PUCs) understand the materials and support available to assist in distributed energy resource (DER) interconnection activities. This workshop focused on DER interconnection and included four speakers, whose material will be posted at https://www.nrel.gov/grid/ieee-standard-1547/workshops.html. The slides in this deck were for the facilitator to provide context to the attendees as well as additional resources on the topics discussed.

DER↗
DOE OSTI2020

Damping and mode shape modification for additively manufactured walls with captured powder

Here, this paper describes the fabrication, modeling, and dynamic testing of laser powder bed fusion stainless steel walls with captured powder cores. The purpose of the study is to determine the increased structural damping, or energy dissipation, and mode shape modification caused by the inclusion of the unmelted powder core within the solid walls. It is shown experimentally that the damping increases with larger powder core width and that the damping addition is mode dependent. Damping increases over the solid wall values by factors of 2.9–225 are reported depending on the mode number and core width. It is also seen that the mode shapes are distorted relative to the solid wall results as the core width is increased and wall thickness is decreased. Comparisons with finite element models confirm this trend.

42 ENGINEERING↗
DOE OSTI2024

Dual material fused filament fabrication of composite core‐shell structures with improved impact resistance and interfacial adhesion

The mechanical performance of parts produced by fused filament fabrication (FFF) has been limited due to the presence of voids and poor interlayer welding. Recent advancements in FFF have enabled the fabrication of void-free objects with strong interlayer welding through the use of semicrystalline polymer shells such as high-density polyethylene (HDPE) along with a high viscosity core polymer like acrylonitrile-butadiene-styrene (ABS). Furthermore, the zero-shear viscosity (η0) of ABS is three orders of magnitude higher than HDPE making the ABS-HDPE core-shell configuration preferable. ABS holds the shape by preventing bulk flow and part bending while HDPE promotes full surface contact across the layers. Most polymers, however, are immiscible which causes a weak weld line along the core-shell interface. Herein, maleic anhydride (MAH) is grafted to the butadiene segment of the ABS core thereby compatibilizing the interface with HDPE, improving the interfacial adhesion. Attenuated total reflectance-Fourier transform infrared spectroscopy was employed to confirm successful grafting. Using a custom-made die affording the core-shell structure, the ABS-g-MAH is shown to improve the impact resistance by 253% and 16% compared to neat HDPE and ABS specimens, respectively. Additionally, a 10% increase compared to the unmodified ABS-HDPE core-shell configuration is observed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Denoising diffusion probabilistic models for generative alloy design

Inverse material design is an extremely challenging optimization task made difficult by, in part, the highly nonlinear relationship linking performance with composition. Quantitative approaches have improved significantly owing to advances in high throughput experimentation and computational thermodynamics. However, existing physics-based tools are mostly forward models; input a chemistry and obtain a prediction. More recently the materials community has leveraged advances in the machine learning community to establish novel inverse design frameworks. Very recently denoising diffusion probabilistic models have been shown to be extremely powerful generators producing synthetic data of various modalities e.g. images, text, audio, tables, etc.. In this work a novel framework for alloy design and optimization is proposed leveraging these class of models. Five key generative tasks are demonstrated (1) unconditional generation (2) composition conditioned generation (3) property conditioned generation (4) multi-feedstock conditioned generation and (5) generative optimization. These methods were tested on three case studies: high entropy alloy design, superalloy binder jet additive manufacturing, and in-situ dual-feedstock wire-arc additive manufacturing. Results indicate that the established models are extremely flexible, expressive, and robust. The architecture’s flexibility and training procedure empower the model to learn complex intra-compositional and composition-property relationships. Furthermore, the probabilistic nature of these models makes them well suited for addressing solution non-uniqueness and tackling uncertainty quantification tasks. While the fidelity and quantity of the underlying training data is paramount, we envision that future alloy design frameworks will make extensive use of these kinds of machine learning models as “search” tools bolstering the utility of experimental and computational approaches.

36 MATERIALS SCIENCE↗