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47th International Conference and Expo on Advanced Ceramics and Composites (ICACC 2023), Daytona Beach, FL, January 22-27, 2023
23rd Annual Solid Oxide Fuel Cell (SOFC) Project Review Meeting, Pittsburgh, PA, October 25-27, 2022
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Understanding the time-varying magnetic field in a fusion device is critical for the successful design and construction of clean-burning fusion power plants. Poincaré analysis provides a powerful method for the visualization of magnetic fields in fusion devices. However, Poincaré plots can be very computationally expensive making it impractical, for example, to generate these plots in situ during a simulation. In this short paper, we describe a collaboration among computer science and physics researchers to develop a new Poincaré tool that provides a significant reduction in the time to generate analysis results.
The Regional Energy Deployment System (ReEDS) is an open-source, spatially explicit, long-term capacity expansion model for the bulk electric power system of the contiguous United States, encompassing multiple scenarios with technological and political assumptions (see https://github.com/NREL/ReEDS-2.0). With the increased needs for capabilities, higher temporal and spatial resolutions to model the evolution of the power system with modern technologies and low-carbon pathways, ReEDS' model solution times have increased significantly from 4-6 hours in 2018 to 18-48+ hours in 2023 . Also, the model size for commonly-run ReEDS scenarios reached 22 and 28 million equations and variables, respectively. These runtimes can be especially challenging under certain scenario settings (e.g., very high temporal or spatial resolution) or with limited computational power. In this presentation, we will discuss several methods we used to improve model runtime, including data preparation, model modification, and solver tuning. The implementation of these methods shrank the model size to 7.2 and 7.3 million equations and variables, respectively. Furthermore, this led to a 77% reduction in the model's run time for commonly-run ReEDS scenarios. We will discuss the process of identifying areas for solve time improvements and how the specific enhancements for the ReEDS model might be applied to other similar large-scale models.
This study explores the optimization of toolpaths for short fiber polymer composite additive manufacturing (AM) printed molds in compression molding applications, an emerging trend driven by advancements in 3D printing technology. AM printed molds offer reduced tooling costs and greater design flexibility, particularly for prototyping and low-volume production. The proposed optimization approach evaluates mold performance using two key metrics: deformation and shape accuracy. Multiple toolpaths are generated, and finite element (FE) simulations capture fiber orientation and material properties, which are then integrated into a mechanical performance model. Shape accuracy is assessed by comparing the deformed mold shape with the original using surface normals as a descriptor. The analysis identifies the toolpath that delivers the best overall performance, establishing it as the most suitable option for achieving optimal mold characteristics in compression molding applications.
Improved performance of lithium-ion batteries (LIBs) plays a critical role in the future of next- generation battery applications. Nickel-rich layered oxides such as LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC 811), are popular cathodes due to their high energy densities. However, they suffer from high surface reactivity, which results in the formation of Li 2 CO 3 passive layer. Herein, we show the role of nanosecond pulsed laser annealing (PLA) in improving the current capacity and cycling stability of LIBs by reducing the carbonate layer, in addition to forming a protective LiF layer and manipulating the NMC 811 microstructures. We use high-power nanosecond laser pulses in a controlled way to create nanostructured surface topography which has a positive impact on the capacity retention and current capacity by providing an increased active surface area, which influences the diffusion kinetics of lithium-ions in the electrode materials during the battery cycling process. Advanced characterizations show that the PLA treatment results in the thinning of the passive Li 2 CO 3 layer, which is formed on as-received NMC811 samples, along with the decomposition of excess polyvinylidene fluoride (PVDF) binder. The high-power laser interacts with the decomposed binder and surface Li + to form LiF phase, which acts as a protective layer to prevent surface reactive sites from initiating parasitic reactions. As a result, the laser treated cathodes show relative increase of the current capacity of up to 50%, which is consistent with electrochemical measurements of LiB cells.
Improved high work function back contacts for solar cells are provided. In one aspect, a method of forming a solar cell includes: forming a completed solar cell having a substrate coated with an electrically conductive material, an absorber disposed on the electrically conductive material, a buffer layer disposed on the absorber, a transparent front contact disposed on the buffer layer, and a metal grid disposed on the transparent front contact; removing the substrate and the electrically conductive material using exfoliation, exposing a backside surface of the solar cell; depositing a high work function material onto the back side surface of the solar cell; and depositing a back contact onto the high work function material. A solar cell formed by the present techniques is also provided. Yield of the exfoliated device can be improved by removing bubbles from adhesive used for exfoliation and/or forming contact pads to access the metal grid.
Improved high work function back contacts for solar cells are provided. In one aspect, a method of forming a solar cell includes: forming a completed solar cell having a substrate coated with an electrically conductive material, an absorber disposed on the electrically conductive material, a buffer layer disposed on the absorber, a transparent front contact disposed on the buffer layer, and a metal grid disposed on the transparent front contact; removing the substrate and the electrically conductive material using exfoliation, exposing a backside surface of the solar cell; depositing a high work function material onto the back side surface of the solar cell; and depositing a back contact onto the high work function material. A solar cell formed by the present techniques is also provided. Yield of the exfoliated device can be improved by removing bubbles from adhesive used for exfoliation and/or forming contact pads to access the metal grid.
Platinum group metal (PGM)-free catalysts are promising low-cost materials for the oxygen reduction reaction in proton exchange membrane fuel cells (PEMFCs). A variety of chemical precursors and synthesis methods have been proposed to increase their catalytic activity. In comparison, significantly less attention has been dedicated to the integration of these PGM-free catalysts into operating electrodes by investigating the role of the membrane electrode assembly (MEA) fabrication on the PEMFC performance. Here, we discuss here some remarkable performance improvements recently achieved by tuning catalyst loading, ionomer content, and ink solvent composition, and call for further explorations of the ink processing and MEA fabrication to improve performance.
Geological carbon sequestration (GCS) involves injecting CO2 into subsurface geological formationsfor permanent storage. Numerical simulations could guide decisions in GCS projects by predictingCO 2 migration pathways and the pressure distribution in storage formation. However, these simula-tions are often computationally expensive due to highly coupled physics and large spatial-temporalsimulation domains. Surrogate modelling with data-driven machine learning has become a promis-ing alternative to accelerate physics-based simulations. Among these, the Fourier neural operator(FNO) has been applied to three-dimensional synthetic subsurface models. Despite its good accuracyin simulating CO 2 plume migration, it requires large computational resources in training and alsolacks generalizability. Here, to further improve performance, we have developed a nested Fourier-DeepONet by combining the expressiveness of the FNO with the modularity of a deep operatornetwork (DeepONet). This new framework is twice as efficient as a nested FNO for training and has atleast 80% lower GPU memory requirement due to its flexibility to treat temporal coordinates sepa-rately. These performance improvements are achieved without compromising prediction accuracy.In addition, the generalization and extrapolation ability of nested Fourier-DeepONet beyond thetraining range has been thoroughly evaluated. Nested Fourier-DeepONet outperformed the nestedFNO for extrapolation in time with more than 50% reduced error. It also exhibited good extrapolationaccuracy beyond the training range in terms of reservoir properties, number of wells, and injectionrate.
This work is developing particle flow control and measurement methods for next-generation concentrating solar power systems employing particle-based technologies. Particle receivers are being pursued to provide substantial performance improvements through higher temperatures (>700 °C) for more efficient and cost-effective CSP systems with direct storage for electricity generation, process heating, thermochemistry, and solar fuels production. This specific work will develop technologies that enable more efficient particle receivers and scalable methods to accommodate variable irradiances during commercial on-sun operation. The development of next-generation particle-receiver systems and methods with potentially high consequences for improved performance and cost savings for CSP applications is an appropriate role for the government.
Particle receivers are being pursued to provide substantial performance improvements through higher temperatures (>700 °C) for more efficient and cost-effective concentrating solar power (CSP) systems with direct storage. However, the interface between the solar-collection and power-block subsystems - a high-temperature particle/supercritical CO 2 (sCO2) heat exchanger - has not been developed. The objective of this project is to design, construct, and test a first-of-a-kind particle-to-sCO2 heat exchanger. This work will enable emerging sCO2 power cycles that have the potential to meet SunShot targets of 50% thermal-to-electric efficiency, dry cooling with 40 °C ambient temperature, and $0.06/kWh for CSP systems. The development of next-generation particle-based systems and methods with potentially high consequences for improved performance and cost savings for CSP applications is an appropriate role for the government.
Direct operation of anion exchange membrane water electrolyzers (AEMWEs) with near-neutral pH feeds avoids the use of highly alkaline and corrosive solutions. However, using neutral pH solutions currently faces fundamental operational challenges that diminish performance and reduce long-term stability due to poor solution conductivity and low hydroxide ion concentration. Here, we showed that amending near-neutral pH solutions with low concentrations of alkali metal salts in a dry-cathode configuration substantially improved performance and stability. Adding NaClO 4 (10 mM) to the anolyte reduced the operating voltage by 0.19 to 2.58 V at 500 mA/cm 2 compared to non-saline solutions (2.77 V). However, further increases in the feed salt concentration (100 mM NaClO 4 ) reduced performance (2.64 V) due to a greater co-ion diffusion through the anion exchange membrane. Electrolyzer performance was further improved by utilizing salts with high conductivity such as KNO 3 . Using a saline anolyte reduced ohmic resistance, resulting in smaller applied voltage and energy consumption for hydrogen generation, while the combined effect of the membrane charge and the electric field direction in the dry-cathode feed configuration minimized ion crossover. Thus, increasing the salinity of near-neutral pH solutions represents a cost-effective strategy to improve the performance of AEMWE compared to ultrapure electrolytes, minimizing risks and costs associated with recirculating highly alkaline solutions.
Packaged air conditioning units and heat pumps, also known as rooftop units (RTUs), are responsible for almost 133 billion kWh of electricity usage annually on site for space cooling U.S. commercial buildings. In addition, the use of heat pumps is a trend we expect to accelerate as buildings transition from fossil fuel-based heating to electricity as a key step for decarbonizing the U.S. commercial buildings sector. However, the operation conditions and energy use of RTUs and heat pumps are usually not well monitored as they are not commonly integrated with building automation systems and lack exposed sensing and control points. To fill this gap, this paper proposes a framework for tracking and forecasting energy impacts resulting from degradation of performance and improved performance for unit servicing using limited data. The proposed framework makes use of a constrained dataset, specifically measurements of the outdoor air temperature and the power demand of individual RTUs, to track and forecast changes in energy use associated with changes in performance over various temporal horizons ranging from days to weeks. Following the detection of an RTU fault, performance degradation, or performance improvement, the framework employs a prediction model to assess the cumulative energy impact. We demonstrate the effectiveness of the method with field-collected data for servicing and degradation examples and compare the predicting accuracy of Gradient Boosting Decision Tree (GBDT) Regression models to Support Vector Regression and Linear Regression models. The results show that GBDT achieved the best accuracy for time-series validation datasets for the servicing and degradation cases, and the prediction model was able to track the cumulative energy impacts of events. The proposed framework can inform building owners of the cumulative change in energy usage of RTUs associated with performance degradation, performance improvement, or a fault.
Increasing the density of percolated triple phase boundaries (TPBs) by infiltrating nanoscale electrocatalysts can improve the performance of solid oxide fuel cell (SOFC) anodes. However, the complex microstructure of these infiltrated nanocatalysts creates challenges in quantifying their role in anode performance improvements. In this research, scanning electron microscopy of fractured cross-sections of a Ni-nanocatalyst infiltrated anodic symmetric cell along with three-dimensional (3-D) reconstruction of the same anode have been used to quantify the changes in percolated TPB densities due to infiltration. This change in percolated TPB density has been compared to the improvement in anode activation polarization resistance measured by electrochemical impedance spectroscopy (EIS). It was found that increased TPB densities only partially accounted for the measured performance improvement. Distribution of relaxation times (DRT) analyses showed that a reduction in the time constants of the catalytic processes in the anode also play a role, suggesting that the added nanoscale percolated TPB boundaries are more electrochemically active as compared to the cermet TPB boundaries.
The overall objective was to infiltrate anodes with nanoparticle catalysts so that anode catalytic performance can be improved as anode operation temperature is reduced from 800°C to intermediate temperatures of 700°C and 600°C and as anode fuel utilization is increased. The addition of nickel nanoparticle catalysts into the anode improves performance by providing additional triple phase boundaries (TPBs), increasing the density of electrochemical reaction sites. To achieve this goal, both liquid phase and vapor phase methods for depositing nickel nanoparticles in the anode active layer, the region of the anode near the electrolyte where the electrochemical reaction occurs. It is imperative that nanoparticles are stable against coarsening during long-term operation, so the mechanisms and kinetics of nanoparticle stability during cell operation will be investigated. Finally, priority is given to processes that are scalable and easily transferable to industry, leveraging existing Ni-YSZ cermet anode technology. Utilizing nickel nanoparticles at different temperatures has different considerations that will be addressed. At the upper end of the intermediate temperature range (800°C), it is important that performance improvement is maintained over long periods by mitigating the instability of nanoparticles. At the middle of the temperature range (700°C), it is important that performance improvement is maintained at high fuel utilizations. At the lower end of the temperature range (600°C), where the performance of cells is poor due to increased resistances, it is important to improve anode performance by significantly increasing the electrochemical reaction site density, while nanoparticle durability is less of an issue. Finally, the objective was to explore mixed ionic and electronic (MIEC) nanoparticle catalysts like GDC to see if 2-phase boundaries can be created to increase the electrochemical reactions at the anode.