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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 OSTI2023

Piezoelectric Energy Harvesting Gyroscopes: Comparative Modeling and Effectiveness

Given its versatility in drawing power from many sources in the natural world, piezoelectric energy harvesting (PEH) has become increasingly popular. However, its energy harvesting capacities could be enhanced further. Here, a mathematical model that accurately simulates the dynamic behavior and energy harvested can facilitate further improvements in the performance of piezoelectric devices. One of the goals of this study is to create a dependable reduced-order model of a multi-purpose gyroscope. This model will make it possible to compute the harvested voltage and electrical power in a semi-analytical manner. The harvested voltage is often modeled as an average value across the whole electrode surface in piezoelectric devices. We propose a model which provides practical insights toward optimizing the performance of the system by considering a spatially varying electric field across the electrode surface length. Our framework allows investigation of the limits of applicability of the modeling assumptions across a range of load resistances. The differential quadrature method (DQM) provides the basis for the suggested numerical solution. The model is also employed to examine energy harvesting under various resistance loads. The newly developed spatially varying model is evaluated for open- and closed-circuit conditions and is proved to be accurate for various values of load resistance that have not previously been considered. The results show that using a spatially varying model is more versatile when modeling the performance of the piezoelectric multifunctional energy harvester. The performance may be accurately captured by the model for load resistances ranging between 103 Ω and 108 Ω. At optimum load resistance and near 65 KHz, the maximum power output predicted by the spatially varying (SV) model is 1.3 mV, 1.5 mV for the open-circuit (OC) model, and 2.1 mV for the closed circuit (CE) model. At a high-load resistance, the SV and OC models all predict the maximum power output to be 1.9 mV while the CE model predicted the maximum voltage to be 3 mV.

42 ENGINEERING↗
DOE OSTI2021

Assessing cathode property prediction via exchange-correlation functionals with and without long-range dispersion corrections

In this work, we benchmark calculated interlayer spacings, average topotactic voltages, thermodynamic stabilities, and band gaps in layered lithium transition-metal oxides (TMOs) and their de-lithiated counterparts, which are used in lithium-ion batteries as positive electrode materials, against available experimental data. Specifically, we examine the accuracy of properties calculated within density functional theory (DFT) using eight different treatments of electron exchange-correlation: the strongly constrained and appropriately normed (SCAN) and Perdew–Burke–Ernzerhof (PBE) density functionals, Hubbard-U-corrected SCAN and PBE (i.e., SCAN+U and PBE+U), and SCAN(+U) and PBE(+U) with added long-range dispersion (D) interactions (i.e., DFT(+U)+D). van der Waals interactions are included respectively via the revised Vydrov-Van Voorhis (rVV10) for SCAN(+U) and the DFT-D3 for PBE(+U). We find that SCAN-based functionals predict larger voltages due to an underestimation of stability of the MO2 systems, while also predicting smaller interlayer spacings compared to their PBE-based counterparts. Furthermore, adding dispersion corrections to PBE has a greater effect on voltage predictions and interlayer spacings than with SCAN, indicating that DFT-SCAN – despite being a ground-state theory – fortuitously captures some short and medium-range dispersion interactions better than PBE. While SCAN-based and PBE-based functionals yield qualitatively similar band gap predictions, there is no significant quantitative improvement of SCAN-based functionals over the corresponding PBE-based versions. Finally, we expect SCAN-based functionals to yield more accurate property predictions than the respective PBE-based functionals for most TMOs, given SCAN's stronger theoretical underpinning and better predictions of systematic trends in interlayer spacings, intercalation voltages, and band gaps obtained in this work.

25 ENERGY STORAGE↗
DOE OSTI2025

Computationally efficient models for aqueous organic redox flow batteries

The rising usage of intermittent energy has garnered the need for large scale energy storage systems. Redox flow batteries (RFB) based energy storage system shows promising potential. Numerical simulations and machine learning approaches have been widely used to study RFB performance. The development of autonomous material discovery framework and digital twin of energy storage system usually needs to query cell performance through fast response models. In this study, two computationally efficient models are introduced: a physics-based analytical flow battery model (EZBattery), and a machine learning operator model (Deep Operator Network, denoted by DeepONet). Both models can provide cell performance near instantly, and prediction accuracy was systematically examined on an application of evaluating the performances of a 780 cm 2 aqueous organic redox flow battery (AORFB), using potential anolyte candidates in dihydroxyphenazine (DHP)-based family of organic materials. A validated computationally expansive 3-dimensional multi-physics finite element model by COMSOL was used as the ground truth and provided the training data set for the DeepONet. 1280 samples were generated with 10 properties to mimic the different possible anolyte candidates, and the cell performances were evaluated under 10 different combined operating conditions. The accuracy comparisons for the two computationally efficient models show that both models can provide comparable accuracy in predicting cell charging/discharging voltage curves. DeepONet can provide slightly higher overall accuracy than EZBattery with faster calculation speed, but highly relies on the training dataset. EZBattery does not need a training dataset and can provide interpretable physics-based explanations of the results, while being more flexible to adjust to adapt any different cell designs, flow battery architectures, and electrolyte materials.

Analytical model↗
DOE OSTI2026

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

Here, we present a perspective on recent progress in machine-learning (ML) force-field approaches for large-scale Landau–Lifshitz–Gilbert (LLG) simulations of metallic spin systems. Building on a generalization of the Behler–Parrinello (BP) architecture originally developed for quantum molecular dynamics, we develop scalable and transferable ML models that faithfully capture the complex, environment-dependent electron-mediated exchange fields characteristic of itinerant magnets. A central ingredient of this framework is the implementation of symmetry-aware magnetic descriptors based on group-theoretical bispectrum formalisms. Leveraging these ML force fields, LLG simulations faithfully reproduce hallmark non-collinear magnetic orders—such as the 120° and tetrahedral states—on the triangular lattice, and successfully capture the complex spin textures emerging in the mixed-phase states of a square-lattice double-exchange model under thermal quench. We further discuss a generalized potential theory that extends the BP formalism to incorporate both conservative and nonconservative electronic torques, thereby enabling ML models to learn nonequilibrium exchange fields from computationally demanding microscopic approaches such as nonequilibrium Green’s-function techniques. This extension yields quantitatively accurate predictions of voltage-driven domain-wall motion and establishes a foundation for quantum-accurate, multiscale modeling of nonequilibrium spin dynamics and spintronic functionalities.

Descriptors↗
DOE OSTI2020

Atomic-Level Understanding of Surface Reconstruction Based on Li[Ni x Mn y Co 1–x–y ]O 2 Single-Crystal Studies

The stability of cathode particle surfaces that are directly exposed to the electrolyte is one of the most crucial and determining factors for cathode performance at high operating voltages. Theory has predicted a strong dependence of surface stability on chemical compositions as well as surface facets of layered oxides, yet conflicting results on the correlations exist as most experimental studies focus on cycled secondary particles recovered from composite electrodes. Here, we synthesize well-formed Li[Ni x Mn y Co 1–x–y ]O 2 (NMC) single-crystal samples, carefully define pristine surface properties, and then monitor their evolution with cycling. Atomic-resolution scanning transmission electron microscopy (STEM) imaging and electron energy loss spectroscopy (EELS) analysis show the formation of a surface reconstruction layer (SRL) as well as an extended surface reduction layer on pristine, Li-permeable non-(001) surfaces, even before cycling. We reveal a transition region with chemical gradient, in which the layered structure gradually densifies and eventually transforms into the SRL on the top surface. Contrary to these observations, no SRL is observed on pristine, Li-impermeable (001) surfaces, revealing the facet-dependent nature of surface reconstructions during particle synthesis. Upon electrochemical cycling, significant composition-and facet-dependent SRL growth is observed. The driving force and mechanism for surface reconstruction are further discussed. The present study provides insights into the origin as well as the nature of SRLs, highlighting the significance of surface engineering in cathode material optimization.

25 ENERGY STORAGE↗
DOE OSTI2025

Toward Establishing Uniqueness of Experimentally Determined Transference Numbers

The passage of current through a battery results in the development of concentration gradients in the electrolytic phase. For a fully characterized binary electrolyte, where the conductivity, salt diffusion coefficient, cation transference number, and the thermodynamic factor are known, concentration and potential gradients in the electrolytic phase can be modeled using Newman’s concentrated solution theory. We report two methods for measuring the transference number: the standard method based on electrochemical measurements ( t + , echem 0 ) and electrophoretic NMR ( t + , eNMR 0 ). The electrochemical approach requires combining measurements from multiple experiments; the equations used to determine the cation transference number and the thermodynamic factor are coupled, nonlinear algebraic equations. In the electrophoretic-NMR-based approach, however, the equations used to determine the cation transference number and the thermodynamic factor are decoupled. We find for a liquid electrolyte comprised of a lithium salt dissolved in tetraglyme, the values of the transference numbers obtained by these two methods are distinct. For example, at 30 °C, t + , echem 0 = −1.02 ± 1.11 and t + , eNMR 0 = 0.25 ± 0.04. The corresponding thermodynamic factors are also different. While the magnitude of the predicted concentration gradients based on the two sets of parameters are different, the predicted current-voltage relationships are similar.

Hickson, Darby T. (ORCID:0000000251339755)↗
NASA NTRS1982

Empirical testing of an analytical model predicting electrical isolation of photovoltaic models

A major design requirement for photovoltaic modules is that the encapsulation system be capable of withstanding large DC potentials without electrical breakdown. Presented is a simple analytical model which can be used to estimate material thickness to meet this requirement for a candidate encapsulation system or to predict the breakdown voltage of an existing module design. A series of electrical tests to verify the model are described in detail. The results of these verification tests confirmed the utility of the analytical model for preliminary design of photovoltaic modules.

Garcia, A., III↗
NASA NTRS1998

AXAF-I Low Intensity-Low Temperature (LILT) Testing of the Development Verification Test (DVT) Solar Panel

The planned orbit of the AXAF-I spacecraft will subject the spacecraft to both short, less than 30 minutes for solar and less than 2 hours for lunar, and long earth eclipses and lunar eclipses with combined conjunctive duration of up to 3 to 4 hours. Lack of proper Electrical Power System (EPS) conditioning prior to eclipse may cause loss of mission. To avoid this problem, for short eclipses, it is necessary to off-point the solar array prior to or at the beginning of the eclipse to reduce the battery state of charge (SOC). This yields less overcharge during the high charge currents at sun entry. For long lunar eclipses, solar array pointing and load scheduling must be tailored for the profile of the eclipse. The battery SOC, loads, and solar array current-voltage (I-V) must be known or predictable to maintain the bus voltage within acceptable range. To address engineering concerns about the electrical performance of the AXAF-I solar array under Low Intensity and Low Temperature (LILT) conditions, Marshall Space Flight Center (MSFC) engineers undertook special testing of the AXAF-I Development Verification Test (DVT) solar panel in September-November 1997. In the test the DVT test panel was installed in a thermal vacuum chamber with a large view window with a mechanical "flapper door". The DVT test panel was "flash" tested with a Large Area Pulse Solar Simulator (LAPSS) at various fractional sun intensities and panel (solar cell) temperatures. The testing was unique with regards to the large size of the test article and type of testing performed. The test setup, results, and lessons learned from the testing will be presented.

Alexander, Doug↗
DOE OSTI2025

Explainable artificial intelligence relates perovskite luminescence images to current-voltage metrics

As the demand for low-cost, high-efficiency solar energy technologies grows, metal halide perovskite (MHP) solar cells have emerged as a promising candidate for next-generation photovoltaics due to their high power conversion efficiencies. However, their poor durability and issues with manufacturing consistency remain significant barriers to commercialization. In this work, we develop deep learning models to support materials characterization and provide insight into features and processes influencing performance. The models are trained using transfer learning of a pretrained model to predict relevant current-voltage (IV) metrics based on different combinations of input electroluminescence (EL) and photoluminescence (PL) images of MHP devices. We examine which image types are most informative in accurately predicting different IV metrics. Additionally, we use explainable artificial intelligence (XAI) techniques to provide insights into specific spatial features in the devices that drive differences in performance. We find that stabilized luminescence images (e.g. those collected after biasing the devices for at least 1 min) are better for predicting metrics of open-circuit voltage (by PL) and short-circuit current (by PL with EL), but that predicting fill factor and overall power output may use the time-evolution of EL images. Based on attribution masks generated by integrated gradients for each device performance metric, we further suggest different loss mechanisms associated with categories of large and small spatial defects. Overall, this case study highlights the potential applicability of XAI methodology for streamlining MHP device analysis and accelerating detailed understanding of the relationships between spatial defects and impacts on performance.

14 SOLAR ENERGY↗
NASA NTRS1986

Solar wind control of the polar-cap voltage

The results of using various models to predict polar-cap potentials are reviewed. Quantitative predictions of merging rate, and hence of polar-cap voltage, based on subsolar merging models are reviewed, and tests of dayside merging models and their results are reexamined. Predictions and tests of cusp merging models are discussed. Two new empirical formulas for the dependence of the asymptotic polar-cap potential on the IMF are presented, and predictions of the dependence of dayside and lobe merging voltages on the IMF are derived from the antiparallel merging hypothesis.

Reiff, Patricia H.↗
DOE OSTI2021

Quantifying Properties for a Mechanistic, Predictive Understanding of Aqueous Impact on Aging of Medium and Low Voltage AC and DC Cabling in Nuclear Power Plants

To address the gap in knowledge in understanding degradation in relevant service conditions, this project aimed to develop a mechanistic, predictive model of medium and low voltage cable failure based on the primary environmental degradation parameters of aqueous immersion time, temperature, and the oxidation extent. To do so, we took a two-fold approach toward evaluating degradation as related to the aqueous condition. First, we evaluated the chemical, mechanical, and electrical properties of polymers that comprise the cabling insulation under varied aqueous conditions at different temperatures. Secondly, we evaluated the performance of insulation materials under similar accelerated aging conditions in addition to the dielectric breakdown of the cabling under submersion conditions. Thermal oxidation and immersion of LDPE thin films were done using a Parr vessel and the extent of oxidation was monitored using the carbonyl index from ATR-FTIR spectrum, a ratio quantifying the carbonyl functionality produced on the LDPE film surface. Increasing the temperature, oxidation time, and oxygen pressure increased the water-vapor permeability and the carbonyl content. Thermogravimetric analysis of the films confirmed that there is indeed an initial weight loss of the smaller molecular weight molecules and volatiles. At higher temperatures, there is a secondary mass loss. Up to 70°C, the mass loss curves were similar until 80°C, when the aged films decreased at a much greater rate with respect to increasing temperature. This was seen in the 10, 50, 90% weight loss temperatures. The mechanical properties of sheet PP and HDPE as well as injection molded LDPE, HDPE, HDPP dog bones were plotted with respect to the time spent in the Parr vessel during thermal oxidation. For the sheet PP and HDPE, the UTS and the modulus of elasticity decreased while the elongation increased. The injection-molded LDPE, HDPE, and HDPP dog bones experienced a similar trend where the changes in the properties were within experimental uncertainty. This analysis of LDPE in dry and immersive oxygen-rich environments is an important baseline for future experiments looking at other degradation mechanisms. A predictive aging model for low-density polyethylene insulative cable housings was developed. This model revealed a combination of physical and chemical processes which lead to an increase in permeability and a decrease in strength of the insulator. In creating this predictive model, a gap of knowledge in the literature was revealed in two areas: understanding how the crystallinity of a polymer changes with time and visualizing the predicted pores formed through the insulator which leads to failure. Developing and using an adapted ATR-FTIR method, crystallinity was monitored and compared to bulk crystallinity found via DSC. Inhomogeneity in crystallinity changes were observed but the FTIR method but was found to be less reliable. Pore visualization was found utilizing electrical impedance spectroscopy saturated aged polyethylene films with synthesized citrate-capped gold nanoparticles, and chloroauric acid precursor. results indicate a decreasing impedance of the polyethylene films caused by the transport of ions through the film. SEM imaging was then performed for elemental analysis of the films and counter electrodes for the presence of ions. Chloride and gold ions were detected; however, no nanoparticles were found. This gives an estimated pore size of at least 0.3 nm through the aged film. Cyclic submergence of polyethylene and polypropylene in aqueous solutions of copper sulfate and Harrison’s solution were examined. It was discovered that aging in these mixed conditions and at 90°C did cause a small, yet significant increase to tensile strength for both unaged polyethylene and polypropylene. The PE and PP in cycled and submerged conditions did not have tensile strengths significantly different from dry-aged after 16 weeks. For both solutions, it was determined that capacitance increases with both water tree depth and cable temperature and is relatively independent of changing water tree AR. As for resistance, there is no apparent change between depth percentages of 10 and 80 for both solutions. This is because the water tree has not yet entered the conductor and thus there is no shorting current flowing through the tree yet. Between 80 and 100% water tree depth, it is observed that for both solutions there is a rapid decrease in resistance because the tree is now impacting the conductor shield and allowing shorting current to flow through it. The relationship between resistance and temperature was found to be inversed. As temperature increases, resistance decreases for both water tree solutions with distilled water having the most apparent difference across the range of temperatures simulated. With regards to water tree AR, resistance was found to be relatively independent at depth percentages of 10, 50, and 70, but there was some relationship at 100% depth for both solutions. At this depth, as water tree AR increased, resistance was found to also increase. Through the examination of voltage and electric field distribution plots, it was confirmed for EPR cables that increasing water tree depth leads to increasing distortion. The increase in shorting current at 100% depth for aqueous copper sulfate compared to distilled water was also visualized. Lastly, the relationship between shorting current and temperature for narrow water trees was visualized and validated using the distribution plots. This study has led to a better understanding of the effect of cable temperature, water tree solution, and geometry of the tree region on cable degradation. Furthermore, this study has documented simulation results of water tree degradation in EPR MV cables, which had been previously lacking in information. Future work in this area will add frequency into the mix and examine what effect it has on the rate of cable degradation as a result of water treeing. To compliment the work being carried by UMD on different polymer chemistries, harvested medium voltage (MV) cables were selected for accelerated aging study at ORNL. These medium voltage cables are representative of the vintages and materials that are currently in use at existing nuclear power plants (NPPs). These cables were immersed in water at 90°C and energized for a period of two years at elevated voltage. Partial discharge was measured during this period of time to track potential degradation. Unfortunately, due to the absence of failure, the extent of integration between the UMD techniques and the harvested MV insulation was limited. However, based on the findings and from the UMD research in the previous sections on polyethylene and polypropylene, follow-on characterization for harvested MV cable insulation should focus on sample preparation to take advantage of the UMD techniques to better understand mechanistic degradation in MV cable insulations. This would include: 1.) Utilization of solutions and impedance measurement insulation to track permeability in harvested and accelerated aging insulation samples, 2.) Adaptation of gold nanoparticle synthesis for electrical impedance spectroscopy with supporting SEM characterization to study pore formation in harvested and accelerated aged insulation samples, & 3.) ATR-FTIR crystallinity with multiple temperature dependent harvested MV cable insulation under different air and submerged accelerated aging. In addition, low voltage dielectric spectroscopy and high voltage dissipation factor, tan δ, could be implemented as a condition monitoring tool for harvested MV cable insulation in submerged environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1981

The STD/MHD codes - Comparison of analyses with experiments at AEDC/HPDE, Reynolds Metal Co., and Hercules, Inc

Data from sufficiently well-instrumented, short-duration experiments at AEDC/HPDE, Reynolds Metal Co., and Hercules, Inc., are compared to analyses with multidimensional and time-dependent simulations with the STD/MHD computer codes. These analyses reveal detailed features of major transient events, severe loss mechanisms, and anomalous MHD behavior. In particular, these analyses predicted higher-than-design voltage drops, Hall voltage overshoots, and asymmetric voltage drops before the experimental data were available. The predictions obtained with these analyses are in excellent agreement with the experimental data and the failure predictions are consistent with the experiments. The design of large, high-interaction or advanced MHD experiments will require application of sophisticated, detailed and comprehensive computational procedures in order to account for the critical mechanisms which led to the observed behavior in these experiments.

Vetter, A. A.↗
NASA NTRS1996

South Atlantic Anomaly Entry and Exit as Measured by the X-Ray Timing Explorer

The Rossi X-ray Timing Explorer (RXTE) carries instruments that must switch off high voltages (HV) when passing through the South Atlantic Anomaly (SAA). The High Energy X-ray Timing Experiment (HEXTE) contains a particle monitor that detects the increased particle flux associated with the SAA and autonomously reduces its voltage. The Proportional Counter Array (PCA) relies on uplinked predictions of SAA entry/exit times based on ephemeris data provided by the Flight Dynamics Facility. A third instrument, the All-Sky Monitor (ASM) also uses a predicted SAA model to reduce voltage when passing through the SAA. Data collected from the HEXTE particle monitor, as well as other instrument readings near the times of SAA entry/exit offer the potential for refining models of the boundaries of the SAA. The SAA has an increased particle flux which causes high rates of detection in the RXTE instruments designed to observe x-rays. The high counting rates could degrade the PCA if HV is not reduced during SAA passages. On the other hand, PCA downtime can be minimized and the science return can be optimized by having the best possible model of the SAA boundary. Thus, the PCA team planned an extensive effort during in-orbit checkout to utilize both the HEXTE particle monitor data and instrument counting rates to refine the model of the SAA boundary. The times of SAA entry and exit are compared with the definitive epemeris to determine the precise location (latitude and longitude) of the SAA boundary. Over time, the SAA and its perimeter were mapped. The RXTE Science Operations Center is continuously working to feed back the results of this effort into the science scheduling process, improving the SAA model as it affects the RXTE instruments, thus obtaining more accurate estimates of the SAA entry/exit times.

Smith, Evan↗
DOE OSTI2025

Bayesian optimization of entropy-stabilized metal fluoride conversion cathodes and their synthesis

Fluoride-based conversion cathodes are promising for next-generation Li ion batteries because of their high voltage and energy densities. High entropy earth abundant fluoride cathodes are attractive for sustainable battery because of the potentially higher cycling stability. While Ni and Co containing equimolar alloys stabilized by high entropy were considered previously, Ni and Co free non-equimolar metal alloy compositions might offer new opportunities to increase materials stability and average voltage. This opportunity was pursued using Bayesian optimization of average voltage for the computational prediction of (Fe x1 Cu x2 Zn x3 Mn x4 Mg x5 )F 2 cathode chemistries. Theoretical voltage, room temperature free energy, and electronic structure of potentially high voltage compositions were computed using density functional theory calculations. Here, the experimental realization of non-equimolar quinary Co and Ni free fluorides with stable rutile single phase and improved conversion reaction voltage by up to 28 % compared to the equimolar alloy demonstrated the power of Bayesian optimization methods for the computationally guided experimental synthesis of fluoride cathodes. Finally, non-equimolar cathode chemistries were found with cycling stability superior to known multi-element fluorides.

25 ENERGY STORAGE↗
DOE OSTI2022

Simulation of GaN-based light emitting diodes incorporating composition fluctuation effects

III-Nitride light emitting diodes (LEDs) are widely used in a range of high efficiency lighting and display applications, which has enabled significant energy savings in the last decade. Despite the wide application of GaN LEDs, transport mechanisms across InGaN/GaN heterostructures in these devices are not well explained. Fixed polarization sheet charges at InGaN/GaN interfaces lead to large interface dipole charges, which create large potential barriers to overcome. One-dimensional models for transport across such heterostructures predict turn-on voltages that are significantly higher than that found in real devices. As a result, conventional models for transport cannot predict the performance of new designs such as for longer wavelength LEDs or for multi-quantum well LEDs. In this work, we show that incorporating low and high indium compositions within quantum wells at the submicrometer scale can provide an accurate prediction of the characteristics of GaN/InGaN light emitting diodes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Comparison of Electromagnetic Transient and Phasor Dynamic Simulations: Implications for Inverter Dominated Systems

The simulation of very high shares of inverter-based resources in power systems has begun to draw into question the validity of phasor domain tools in capturing relevant dynamics. Electromagnetic transient simulators can capture the dynamics of power electronics with substantially smaller time steps, but are computationally expensive. This work contrasts the results of phasor domain and electromagnetic transient tools for simulations on a validated model of the Maui power system operating at very high inverter-based resource shares with near zero voltage forming devices. The results show that the phasor domain tool predicts optimistic stability with fewer voltage forming elements on the network, and loses computational stability before the electromagnetic transient tool. As the electromagnet transient model is of the entire system, and system-wide discrepancies are observed, this case study of a physical power system highlights the potential need for system-wide detailed modeling during periods of very high shares of inverter-based resources and few voltage forming devices.

electromagnetic transient-domain↗
NASA NTRS1989

Modelling and design of high performance indium phosphide solar cells

A first principles pn junction device model has predicted new designs for high voltage, high efficiency InP solar cells. Measured InP material properties were applied and device parameters (thicknesses and doping) were adjusted to obtain optimal performance designs. Results indicate that p/n InP designs will provide higher voltages and higher energy conversion efficiencies than n/p structures. Improvements to n/p structures for increased efficiency are predicted. These new designs exploit the high absorption capabilities, relatively long diffusion lengths, and modest surface recombination velocities characteristic of InP. Predictions of performance indicate achievable open-circuit voltage values as high as 943 mV for InP and a practical maximum AM0 efficiency of 22.5 percent at 1 sun and 27 C. The details of the model, the optimal InP structure and the effect of individual parameter variations on device performance are presented.

Rhoads, Sandra L.↗
NASA NTRS1975

Effects of high doping levels silicon solar cell performance

The significance of the heavy doping effects (HDE) on the open-circuit voltage of silicon solar cells is assessed. Voltage calculations based on diffusion theory are modified to include the first order features of the HDE. Comparisions of the open-circuit voltage measured for cells of various base resistivities are made with those calculated using the diffusion model with and without the HDE. Results indicate that the observed variation of voltage with base resistivity is predicted by these effects. A maximum efficiency of 19% (AM0) and a voltage of 0.7 volts are calculated for 0.1 omega-cm cells assuming an optimum diffused layer impurity profile.

Godlewski, M. P.↗