Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “single layer”

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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mapping Conductance and Switching Behavior of Graphene Devices In Situ

Graphene is proposed for use in various nanodevice designs, many of which harness emergent quantum properties for device functionality. However, visualization, measurement, and manipulation become nontrivial at nanometer and atomic scales, representing a significant challenge for device fabrication, characterization, and optimization at length scales where quantum effects emerge. Herein, proof of principle results at the crossroads between 2D nanoelectronic devices, e-beam-induced modulation, and imaging with secondary electron e-beam induced currents (SEEBIC) is presented. A device platform compatible with scanning transmission electron microscopy investigations is introduced. Then how the SEEBIC imaging technique can be used to visualize conductance and connectivity in single layer graphene nanodevices, even while supported on a thicker substrate (conditions under which conventional imaging fails) is shown. Finally, it is shown that the SEEBIC imaging technique can detect subtle differences in charge transport through time in nonohmic graphene nanoconstrictions indicating the potential to reveal dynamic electronic processes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Super Flexible Transparent Conducting Oxide-Free Organic–Inorganic Hybrid Perovskite Solar Cells with 19.01% Efficiency (Active Area=1 cm 2 )

Highly efficient organic-inorganic hybrid perovskite solar cells (OIHP-SCs) are often fabricated on a transparent conducting oxide (TCO) substrate such as indium tin oxide (ITO). However, the presence of TCOs is disadvantageous to the development of flexible OIHP-SCs due to the brittle nature of ITO which is easily breakable during bending. Herein, a flexible TCO-free OIHP-SC is demonstrated by using lithium bis(trifluoromethane)sulfonimide (Li-TFSI) as a codopant for the single-layer graphene transparent conducting electrode and poly(triarylamine) hole-transporting material (HTM) on a flexible polydimethylsiloxane substrate. The optical and electrical properties of the Li-TFSI-doped graphene substrate are measured by controlling the doping amount and the best conditions for charge extraction are established at a doping concentration of 20 mm Li-TFSI, thus optimizing the device photovoltaic performance. As a result, a highest power conversion efficiency of 19.01% is demonstrated by the flexible TCO-free OIHP-SC devices with an active area of 1 cm 2 . In addition, the flexible TCO-free OIHP-SCs exhibit good bending stability after 5000 bending cycles at radii of 6, 4, and 2 mm and excellent light soaking stability under 1 Sun light intensity over 1000 h as opposed to the poor stability when using poly(3,4-ethylenedioxythiophene) polystyrene sulfonate as the HTM.

14 SOLAR ENERGY↗
DOE OSTI2023

Assessing Manufacturability of the Oxide Dispersion Strengthened (ODS) 14YWT Alloy Fuel Cladding Tube Using SolidStir™ Technology

The 14YWT (Fe–14Cr–3W–0.4Ti–0.3Y2O3 (wt.%)) alloy is a potential candidatematerial for fabricating fuel cladding tubes and other structural components to be used in next-generation advanced nuclear reactors. Due to inherent limitations of current processing routes, this research explored a new variant of friction stir processing, commercially referred to as SolidStir™ Extrusion (patent pending) technology from Enabled Engineering to consolidate and extrude 14YWT powder into a fuel cladding tube. Several single-layer and multiple-layer consolidation experiments were carried out in an Inconel 625 die to determine the suitable processing parameters for SolidStir™ extrusion of the 14YWT alloy cladding tube. With these processing parameters, a 16–18 mm long tube of the 14YWT alloy with no visible defects was successfully extruded using this novel technology. Microstructural characterization results obtained using optical microscopy, scanning electron microscopy, energy dispersive spectroscopy, electron backscatter diffraction, and transmission electron microscopy will be presented.

Advanced Materials and Manufacturing Technology↗
DOE OSTI2022

Effects of weave path parameters on the geometry of wire arc additive manufactured features

Here, the present work investigates the effect of process parameters on the geometry of wire arc additive manufactured parts. The geometric accuracy of features produced with a weaving strategy is compared to what can be accomplished with a typical overlapping bead strategy. In this work, single-layer and multi-layer geometries were deposited under varying process and path parameters. The wavelength, amplitude, and torch speed of the weaving path were varied, while the power, wire feed speed, and contact tip to work distance remained constant. The geometric deposition efficiencies of several samples produced with a weave strategy are directly compared to samples generated with two parallel overlapping beads with torch speeds defined to match the deposition rate of the weave samples. Feature geometries were characterized using optical microscopy and laser scanning data. The results indicate that implementing a weave path strategy can improve the geometric accuracy of wire arc additive features, thus increasing the effective volumetric deposition rate of the process. It is shown that the most consistent improvements resulted from the combination of low wavelength and high amplitude, which correlate to wider and taller printed layers.

GMAW↗
DOE OSTI2023

Uncovering acoustic signatures of pore formation in laser powder bed fusion

Abstract We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a low-dimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography. Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom $$\varvec{k}$$ k -means clustering (NMF $$\varvec{k}$$ k ) to learn the underlying spectral patterns associated with pore formation. NMF $$\varvec{k}$$ k returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMF $$\varvec{k}$$ k decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively. The intrinsic data compression of NMF k , the relatively light computational cost of the machine learning workflow, and the high classification accuracy makes the proposed workflow an attractive candidate for edge computing toward in-situ keyhole pore prediction in LPBF.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures

Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely beyond reach. In this work, we propose a learning framework to extract a peridynamics model as a mesoscale continuum surrogate from MD simulated material fracture data sets. Firstly, we develop a novel coarse-graining method, to automatically handle the material fracture and its corresponding discontinuities in the MD displacement data sets. Inspired by the weighted essentially non-oscillatory (WENO) scheme, the key idea lies at an adaptive procedure to automatically choose the locally smoothest stencil, then reconstruct the coarse-grained material displacement field as the piecewise smooth solutions containing discontinuities. Then, based on the coarse-grained MD data, a two-phase optimization-based learning approach is proposed to infer the optimal peridynamics model with damage criterion. In the first phase, we identify the optimal nonlocal kernel function from the data sets without material damage to capture the material stiffness properties. Then, in the second phase, the material damage criterion is learnt as a smoothed step function from the data with fractures. As a result, a peridynamics surrogate is obtained. As a continuum model, our peridynamics surrogate model can be employed in further prediction tasks with different grid resolutions from training, and hence allows for substantial reductions in computational cost compared with MD. We illustrate the efficacy of the proposed approach with several numerical tests for the dynamic crack propagation problem in a single-layer graphene. Our tests show that the proposed data-driven model is robust and generalizable, in the sense that it is capable of modeling the initialization and growth of fractures under discretization and loading settings that are different from the ones used during training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Graph decomposition techniques for solving combinatorial optimization problems with variational quantum algorithms

The quantum approximate optimization algorithm (QAOA) has the potential to approximately solve complex combinatorial optimization problems in polynomial time. However, current noisy quantum devices cannot solve large problems due to hardware constraints. In this work, we develop an algorithm that decomposes the QAOA input problem graph into a smaller problem and solves MaxCut using QAOA on the reduced graph. The algorithm requires a subroutine that can be classical or quantum—in this work, we implement the algorithm twice on each graph. One implementation uses the classical solver Gurobi in the subroutine and the other uses QAOA. We solve these reduced problems with QAOA. On average, the reduced problems require only approximately 1/10 of the number of vertices than the original MaxCut instances. Furthermore, the average approximation ratio of the original MaxCut problems is 0.75, while the approximation ratios of the decomposed graphs are on average of 0.96 for both Gurobi and QAOA. With this decomposition, we are able to measure optimal solutions for ten 100-vertex graphs by running single-layer QAOA circuits on the Quantinuum trapped-ion quantum computer H1-1, sampling each circuit only 500 times. This approach is best suited for sparse, particularly k-regular graphs, as k-regular graphs on n vertices can be decomposed into a graph with at most $\frac{nk}{k+1}$ vertices in polynomial time. Further reductions can be obtained with a potential trade-off in computational time. In conclusion, while this paper applies the decomposition method to the MaxCut problem, it can be applied to more general classes of combinatorial optimization problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A time-parallel method for scalable heat transfer simulations of additive manufacturing

Here, a major challenge in simulating the thermal behavior in additive manufacturing processes is the disparate length and time scales between transport phenomena occurring in the melt pool and the component. A common simulation approach relies on spatial decomposition for parallel computing, but due to the nature of heat transfer in AM, where most of the computational expenditure is localized near the melt pool, the computational speedup from spatial parallelization saturates quickly. Therefore, additional parallelism by means of time-domain decomposition is needed to fully take advantage of high-performance computing (HPC) resources. This work introduces a time-parallel method to improve the computational scalability of additive manufacturing simulations on HPC systems, while maintaining high temporal resolution of heat transfer near the melt pool. The method, inspired by the nonlinear paraexp formalism, performs an iterative superposition of nonlinear solutions to the initial value problem, integrating the heat equation across overlapping time-parallel intervals. For a single layer of the NIST AMB2018–01 L7 benchmark problem, the method achieves a 38.51x speedup in wall-clock time with a maximum error in the global temperature solution of 0.99%. This reduces the total solution time from 196.72 min to 5.11 min on 128 nodes of the ORNL Frontier supercomputer. The tradeoff between accuracy and total wall-clock time is investigated and recommendations for time-parallel deployment for AM problems are made.

Additive manufacturing↗
DOE OSTI2022

Microwave assisted heating of plastic waste: Effect of plastic/susceptor (SiC) contacting patterns

We discuss plastic accumulation as a growing sustainability challenge. Most plastics are thermally inert at room temperature, requiring high temperatures for depolymerization. In the quest for developing sustainable plastic upcycling, we investigate silicon carbide (SiC) as microwave absorbing susceptors for reaching depolymerization temperatures. We utilize three SiC topologies – particles, hot-pressed plastic films containing SiC particles, and monoliths. SiC particles of >0.5 mm in diameter can provide heating rates approaching ~200 °C/min at modest powers. Still, physically mixed plastic-susceptor beds suffer from density differences, causing non-uniform contact during plastic softening and melting. Hot-pressed plastic films containing SiC particles allow uniform plastic-susceptor contact but suffer from slow heating as only a single layer of susceptors exists between polymer layers. SiC monoliths mitigate these challenges by preferentially dissipating the microwaves and rapidly heating the plastics independently of polymeric properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Finite Difference informed Random Walk solver for simulating radiation defect evolution in polycrystalline structures with strongly inhomogeneous diffusivity

Diffusivity of species and defects on grain boundaries is usually several orders of magnitude larger than that inside grains. Such strongly inhomogeneous diffusivity requires prohibitively high computational demands for modeling microstructural evolution. Here, this paper presents a highly-efficient numerical solver, combining the Finite Difference method and Random Walk model, designed for accurately modeling strongly inhomogeneous diffusion within polycrystalline structures. The proposed solver, termed Finite Difference informed Random Walk (FDiRW), integrates a customized Finite Difference (cFD) scheme tailored for fast diffusion along thin grain boundaries represented by a single-layer of nodes. Numerical experiments demonstrate that the FDiRW solver achieves an impressive efficiency gain of 1560x compared to traditional Finite Difference methods while maintaining accuracy, making it feasible for personal computer machines to handle diffusional systems with strongly inhomogeneous diffusivity across static polycrystalline microstructures. The model has been successfully applied to simulate radiation defect evolution, showcasing its scalability to engineering scales in both length and time dimensions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effect of water vapor on high-temperature oxidation of NiAl alloy

The high-temperature oxidation of NiAl is studied with dry oxygen and water vapor. The oxidation in H 2 O results in a thicker Al 2 O 3 oxide scale than that in O 2 . The oxide scale formed initially is a single layer of γ-Al 2 O 3 that subsequently transforms into a α-Al 2 O 3 /γ-Al 2 O 3 bilayer structure, in which the inner α-Al2O3 layer formed in H2O has a higher porosity than that in O 2 . Finally, further density functional theory calculations show that H protons derived from H 2 O molecules penetrate into the oxide lattice and boost the formation of lattice vacancies in both α-Al 2 O 3 and γ-Al 2 O 3 , thus enhancing the oxide scale growth.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electronic interactions and stability issues at the copper-graphene interface in air and in alkaline solution under electrochemical control

A micro-electrochemical cell is sealed with a polymer-free single-layer graphene (SLG) membrane to monitor the stability of Cu nanoparticles (NPs) attached to SLG, as well as the interfacial electronic interactions between Cu NPs and SLG both in air and in a mildly alkaline aqueous solution under electrochemical control. A combination of techniques, including in-situ Kelvin probe force microscopy (KPFM) and ex-situ electron microscopy, are applied. When Cu NPs are metallic at cathodic potentials, there is a relatively bias-independent offset in the SLG work function due to charge transfer at the Cu-SLG contact. When Cu NPs are oxidized at anodic potentials, on the other hand, the work function of SLG also depends on the applied bias in a quasi-linear fashion due to electrochemical gating, in addition to charge transfer at the CuOx-SLG contact. Furthermore, Cu NPs were found to oxidize and detach from SLG when kept under anodic potentials for a few hours, whereas they remain adhered to SLG at cathodic potentials. This is attributed to water intercalation at the CuO-SLG interface associated with the enhanced hydrophilicity of positively polarized graphene, as supported by the absence of Cu detachment following oxidation by galvanic corrosion in air.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Evaluating cascaded and tunable phase change materials for enhanced thermal energy storage utilization and effectiveness in building envelopes

The incorporation of phase change materials (PCMs) in envelope is considered an effective thermal energy storage (TES) method for energy savings and load flexibility in buildings. However, an important limitation of PCMs is their fixed and narrow transition temperature range. Because the interior temperature setpoints are typically different in summer versus winter, and the exterior temperature varies substantially above and below the setpoints during the year, PCMs with a fixed transition temperature are utilized only during part of the year. In this paper, we provide an extensive numerical analysis of the performance of a lightweight building envelope containing three different types of PCMs: traditional single-layer PCM with a fixed transition temperature, novel cascaded two-layer PCM with different transition temperatures, and a "futuristic" tunable PCM whose transition temperature can be varied in-situ using external excitation. We compare their performances by evaluating the relationship between the PCM utilization and parameters such as latent heat, transition temperature range, PCM thickness, and PCM location. While traditional PCMs are mostly active during one season, properly designed cascaded and tunable PCMs can be active much longer, thereby allowing load shift and energy savings in both heating and cooling seasons. Under the operating conditions considered in this study, tunable PCMs performed best, providing the highest utilization (about 2 times the traditional PCMs) and enhanced effectiveness (up to 99% peak load reduction in cooling season and 34% peak load reduction in heating season) with the same amount of material as the traditional PCMs; however, cascaded PCMs can be a good alternative while tunable PCMs are unavailable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Enable superior performance of ultra-high loading electrodes through the cost-efficient solvent-free electrode manufacturing technology

This research explores an innovative solvent-free method for fabricating ultra-high loading NMC811 and graphite electrodes (~6mAh∙cm -2 ), showcasing remarkable electrochemical performance enhancements compared to the electrodes prepared by the conventional slurry-casting method. Here, the optimized microstructure with dry-printed (DP) electrodes enhanced electrolyte penetration and minimized lithium-ion diffusion tortuosity resulting in improved rate performance at high current rates. Additionally, this innovative electrode manufacturing approach enables more uniform CEI and SEI formation and growth, which effectively doubles the cycle life of single-layer pouch cells with DP electrodes. Beyond the performance enhancements, this method also offers a notable 29.2 % overall cost advantages, potentially revolutionizing future battery manufacturing. The findings presented in this work underscore the potential of solvent-free manufacturing technology as a high-loading capable and cost-efficient path for advanced battery production.

25 ENERGY STORAGE↗
DOE OSTI2025

Upcycling Mixed Spent Ni-Lean Cathodes into Ni-Rich Polycrystalline Cathodes

Sustainable battery recycling is vital for conserving resources and reducing environmental impacts. Current open- and closed-loop recycling strategies often focus on recovering individual components, making the reuse of mixed cathode materials a complex challenge. Meanwhile, the research on upcycling has been limited to using pristine cathode feedstocks and virgin materials for synthesis. Here, to address this issue, we present an upcycling approach for spent Ni-lean mixed cathode materials that integrate an upcycling hydrometallurgical recycling process with traditional hydrometallurgical methods. This strategy achieves a utilization of 92.31 mol % of recycled materials, enabling the regeneration of Ni-rich cathode materials while significantly reducing the reliance on virgin resources. The regenerated 83Ni cathode materials demonstrate physical properties comparable to those produced from virgin materials. Electrochemical evaluations using single-layer pouch cells show that both recycled and virgin cathodes exhibit initial specific capacity close to 201.1 mAh/g and maintain approximately 88 % capacity retention after 500 cycles. Additionally, 2Ah cells confirmed these findings, delivering 85 % capacity retention after about 900 cycles. Techno-economic analysis demonstrates notable environmental benefits, including reductions in greenhouse gas emissions and energy consumption, achieving 232.75 MJ/kg of product, which is 8.6 % lower than traditional methods and comparable to direct upcycling. Furthermore, the upcycling hydrometallurgical recycling process generates the highest profit, proving its economic viability. This scalable and versatile process is adaptable to varying transition metal compositions, facilitating a closed-loop recycling system that bridges mixed spent cathodes with next-generation cathode materials, and offers a sustainable solution for managing waste battery materials.

Hydrometallurgical recycling↗
DOE OSTI2022

Retrofitting stoves with forced jets of primary air improves speed, emissions, and efficiency: Evidence from six types of biomass cookstoves

Incorporating jets of forced air into biomass cookstove combustion has been shown to potentially decrease harmful emissions, leading to a variety of designs in recent years. These have shown mixed success in terms of real-world performance, usability, and durability. The Jet-Flame forced draft retrofit accessory was recently developed to implement forced jets of primary air at a low cost into a wide range of types of cookstoves using a small 1.5-W fan housed in a low-cost cast iron body to be inserted beneath the fuel bed of a biomass cooking fire. This research sought to quantify the potential efficiency and emissions performance impacts of the Jet-Flame when installed in six different types of biomass cookstoves (three open or shielded fires and three rocket stoves) versus the natural draft performance of each. The effect of the operating fan voltage was also measured. A series of tests following a modified ISO 19867-1:2018 protocol were performed in the laboratory using the Aprovecho Laboratory Emissions Measurement System (LEMS) equipped with additional oxygen and temperature sensors. Results for each stove carefully tended with a single layer of sticks showed that the global average PM 2.5 reduction with the Jet-Flame was 89 % relative to the natural draft cases, with larger relative improvements seen in the most rudimentary stoves. CO was reduced by a global average of 74 %, reaching tier 4 or 5 for all stoves. Thermal efficiency was also improved by 34 % when calculated without taking into account the energy content of the remaining char (or 21 % with char), illustrating the value of burning char to provide cooking energy rather than leaving it unburned in the combustion chamber as is common in many natural draft stoves. Time to boil was also reduced by 8 %. In addition, adjusting the voltage of the jet-flame assisted in modulating firepower, improving the usability of the stove. These results indicate a strong potential for the Jet-Flame to help reduce emissions and fuel consumption in a wide range of cookstove designs at a relatively low cost or need for changes in behavior, fuel, or cooking device. The unit also provides enhanced usability in terms of ease of startup, cooking speed, low PM emissions at high power, and burning char. Additional studies are needed to measure performance in the field and under a variety of operational conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A deep learning-accelerated data assimilation and forecasting workflow for commercial-scale geologic carbon storage

Fast assimilation of monitoring data to update forecasts of pressure buildup and carbon dioxide (CO 2 ) plume migration under geologic uncertainties is a challenging problem in geologic carbon storage. The high computational cost of data assimilation with a high-dimensional parameter space impedes fast decision-making for commercial-scale reservoir management. We propose to leverage physical understandings of porous medium flow behavior with deep learning techniques to develop a fast data assimilation-reservoir response forecasting workflow. Applying an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates geologic properties and predicts reservoir performance with quantified uncertainty from pressure history and CO 2 plumes interpreted through seismic inversion. As the most computationally expensive component in such a workflow is reservoir simulation, we developed surrogate models to predict dynamic pressure and CO 2 plume extents under multi-well injection. The surrogate models employ deep convolutional neural networks, specifically, a wide residual network and a residual U-Net. The workflow is validated against a flat threedimensional reservoir model representative of a clastic shelf depositional environment. Intelligent treatments are applied to bridge between quantities in a true-3D reservoir model and those in a single-layer reservoir model. The workflow can complete history matching and reservoir forecasting with uncertainty quantification in less than one hour on a mainstream personal workstation.

25 ENERGY STORAGE↗
DOE OSTI2022

Exchange bias and interface-related effects in two-dimensional van der Waals magnetic heterostructures: Open questions and perspectives

The exchange bias (EB) effect is known as a fundamentally and technologically important magnetic property of a magnetic bilayer film. It is manifested as a horizontal shift in a magnetic hysteresis loop of a film subject to cooling in the presence of a magnetic field. The EB effect in van der Waals (vdW) heterostructures offers a novel approach for tuning the magnetic properties of the newly discovered single-layer magnets, as well as adds a new impetus to magnetic vdW heterostructures. Indeed, intriguing EB effects have recently been reported in a variety of low-dimensional vdW magnetic systems ranging from a weakly interlayer-coupled vdW magnet (e.g., Fe 3 GeTe 2 ) to a bilayer composed of two different magnetic vdW materials (e.g., Fe 3 GeTe 2 /CrCl 3 , Fe 3 GeTe 2 /FePS 3 , Fe 3 GeTe 2 /MnPS 3 , Fe 3 GeTe 2 /CrSe, Fe 3 GeTe 2 /CrOCl, Fe 3 GeTe 2 /CoPc, Fe 5 GeTe 2 /FePS 3 ), to bilayers of two different vdW defective magnets (e.g., VSe 2 /MoS 2 ), or to metallic ferromagnet/vdW defective magnet interfaces (e.g., Fe/MoS 2 ). Despite their huge potential in spintronic device applications, the physical origins of the observed EB effects have remained elusive to researchers. Here, we present here a critical review of the EB effect and associated phenomena such as magnetic proximity (MP) in various vdW heterostructure systems and propose approaches to addressing some of the emerging fundamental questions.

2D magnets↗