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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 55 records · Page 3

Water, Protons, and the Gating of Voltage-Gated Potassium Channels

Ion channels are ubiquitous throughout all forms of life. Potassium channels are even found in viruses. Every cell must communicate with its surroundings, so all cells have them, and excitable cells, in particular, especially nerve cells, depend on the behavior of these channels. Every channel must be open at the appropriate time, and only then, so that each channel opens in response to the stimulus that tells that channel to open. One set of channels, including those in nerve cells, responds to voltage. There is a standard model for the gating of these channels that has a section of the protein moving in response to the voltage. However, there is evidence that protons are moving, rather than protein. Water is critical as part of the gating process, although it is hard to see how this works in the standard model. Here, we review the extensive evidence of the importance of the role of water and protons in gating these channels. Our principal example, but by no means the only example, will be the Kv1.2 channel. Evidence comes from the effects of D2O, from mutations in the voltage sensing domain, as well as in the linker between that domain and the gate, and at the gate itself. There is additional evidence from computations, especially quantum calculations. Structural evidence comes from X-ray studies. The hydration of ions is critical in the transfer of ions in constricted spaces, such as the gate region and the pore of a channel; we will see how the structure of the hydrated ion fits with the structure of the channel. In addition, there is macroscopic evidence from osmotic experiments and streaming current measurements. The combined evidence is discussed in the context of a model that emphasizes the role of protons and water in gating these channels.

59 BASIC BIOLOGICAL SCIENCES↗

The importance of surface recombination and energy-bandgap narrowing in p-n-junction silicon solar cells

Experimental data demonstrating the sensitivity of open-circuit voltage to front-surface conditions are presented for a variety of p-n-junction silicon solar cells. Analytical models accounting for the data are defined and supported by additional experiments. The models and the data imply that a) surface recombination significantly limits the open-circuit voltage (and the short-circuit current) of typical silicon cells, and b) energy-bandgap narrowing is important in the manifestation of these limitations. The models suggest modifications in both the structural design and the fabrication processing of the cells that would result in substantial improvements in cell performance. The benefits of one such modification - the addition of a thin thermal silicon-dioxide layer on the front surface - are indicated experimentally.

Fossum, J. G.↗

Current leakage for low altitude satellites - Modeling applications

To simulate the behavior of a high voltage solar cell array in the ionospheric plasma environment, the large (90 ft x 55 ft diameter) vacuum chamber was used to measure the high-voltage plasma interactions of a 3 ft x 30 ft conductive panel. The chamber was filled with Nitrogen and Argon plasma at electron densities of up to 1,000,000 per cu cm. Measurements of current flow to the plasma were made in three configurations: (a) with one end of the panel grounded, (b) with the whole panel floating while a high bias was applied between the ends of the panel, and (c) with the whole panel at high negative voltage with respect to the chamber walls. The results indicate that a simple model with a constant panel conductivity and plasma resistance can adequately describe the voltage distribution along the panel and the plasma current flow. As expected, when a high potential difference is applied to the panel ends more than 95% of the panel floats negative with respect to the plasma.

Konradi, A.↗

Modeling of thin, back-wall silicon solar cells

The performance of silicon solar cells with p-n junctions on the nonilluminated surface (i.e., upside-down or back-wall cells) was calculated. These structures consisted of a uniformly shaped p-type substrate layer, a p(+)-type field layer on the front (illuminated) surface, and a shallow, n-type junction on the back (nonilluminated) surface. A four-layer solar cell model was used to calculate efficiency, open-circuit voltage, and short-circuit current. The effect on performance of p-layer thickness and resistivity was determined. The diffusion length was varied to simulate the effect of radiation damage. The results show that peak initial efficiencies greater than 15 percent are possible for cell thicknesses or 100 micrometers or less. After 10 years of radiation damage in geosynchronous orbit, thin (25 to 50 micrometers thick) cells made from 10 to 100 ohm cm material show the smallest decrease (approximately 10 percent) in performance.

Baraona, C. R.↗

Single Junction InGaP/GaAs Solar Cells Grown on Si Substrates using SiGe Buffer Layers

Single junction InGaP/GaAs solar cells displaying high efficiency and record high open circuit voltage values have been grown by metalorganic chemical vapor deposition on Ge/graded SiGe/Si substrates. Open circuit voltages as high as 980 mV under AM0 conditions have been verified to result from a single GaAs junction, with no evidence of Ge-related sub-cell photoresponse. Current AM0 efficiencies of close to 16% have been measured for a large number of small area cells, whose performance is limited by non-fundamental current losses due to significant surface reflection resulting from greater than 10% front surface metal coverage and wafer handling during the growth sequence for these prototype cells. It is shown that at the material quality currently achieved for GaAs grown on Ge/SiGe/Si substrates, namely a 10 nanosecond minority carrier lifetime that results from complete elimination of anti-phase domains and maintaining a threading dislocation density of approximately 8 x 10(exp 5) per square centimeter, 19-20% AM0 single junction GaAs cells are imminent. Experiments show that the high performance is not degraded for larger area cells, with identical open circuit voltages and higher short circuit current (due to reduced front metal coverage) values being demonstrated, indicating that large area scaling is possible in the near term. Comparison to a simple model indicates that the voltage output of these GaAs on Si cells follows ideal behavior expected for lattice mismatched devices, demonstrating that unaccounted for defects and issues that have plagued other methods to epitaxially integrate III-V cells with Si are resolved using SiGe buffers and proper GaAs nucleation methods. These early results already show the enormous and realistic potential of the virtual SiGe substrate approach for generating high efficiency, lightweight and strong III-V solar cells.

Ringel, S. A.↗

Effect of Aluminum Oxide on the Performance of Ionic Liquid-Based Aluminum–Air Battery

The aluminum–air (or oxygen) battery has received intense attention in the past because of its excellent benefits such as low cost and high energy density, but due to the challenging issues such as hydrogen evolution and inactive oxide film formation on the Al surface, it could not be fully applied. In this study, 1-Ethyl 3-Methyl Imidazolium Chloride ([EmIm]Cl) and aluminum chloride (AlCl3) are applied to resolve the aforementioned issues. Ex situ component-level and in situ cell-level open circuit voltage (OCV) tests combined with the physics-based model analyses were conducted to investigate the electrochemical reaction behaviors of the Al–air cell. Especially, the effect of aluminum oxide formation on the anode- and cathode-side reactions were analyzed in detail. The oxide film formed at the Al surface strongly was found to significantly impede the electrochemical reaction at the surface, and the film growth was controlled by decreasing the surface tension by aggressive anions. In the cathode side, the aluminum oxide precipitated in the porous cathode electrode was found to decrease the porous reaction area and block reactant access into the reaction sites. The effects of O2 solubility in the electrolyte, initial porosity and thickness of the porous electrode are compared in detailed, and optimal thickness is suggested.

25 ENERGY STORAGE↗

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↗

Modeling and Control of Cascaded Bridgeless Multilevel Rectifier Under Unbalanced Load Conditions

The goal of this project is to model and control a novel unidirectional cascaded multilevel bridgeless rectifier as an active front end in medium and high voltage applications. This topology has many advantages over a conventional cascaded H-bridge rectifier, such as lower implementation cost, higher reliability, and greater flexibility with similar power quality.The steady-state mathematical model is used to develop a method for the voltage balancing of dc cells. Power factor analysis is discussed to achieve unity power factor using fully controlled hbridge cells. Power loss, efficiency, and cost comparison studies between the traditional cascaded H-Bridge converter and the proposed bridgeless converter demonstrate the advantages. A novel control strategy is proposed to achieve dc voltage balancing, fast and robust grid synchronization and power factor correction under unbalanced load conditions. Simulation and experimental results validate the models and control method.

Cascaded Bridgeless Rectifier, Power factor analys↗

Physics-constrained deep neural network method for estimating parameters in a redox flow battery

Here, in this paper, we present a physics-constrained deep neural network (PCDNN) method for parameter estimation in the zero-dimensional (0D) model of the vanadium redox flow battery (VRFB). In this approach, we use deep neural networks to approximate the model parameters as functions of the operating conditions. This method allows the integration of VRFB computational models as the physical constraints in the parameter learning process, leading to enhanced accuracy of parameter estimation and cell voltage prediction. Using an experimental dataset, we demonstrate that the PCDNN method can estimate model parameters for a range of operating conditions and improve the 0D model prediction of voltage compared to the 0D model prediction with constant operation-condition-independent parameters estimated with traditional inverse methods. We also demonstrate that the PCDNN approach has an improved generalization ability for estimating parameter values for operating conditions not used in the training process.

25 ENERGY STORAGE↗

Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model

The cells in battery energy storage systems are monitored, protected, and controlled by battery management systems whose sensors are susceptible to cyberattacks. False data injection attacks (FDIAs) targeting batteries’ voltage sensors affect cell protection functions and the estimation of critical battery states like the state of charge (SoC). Inaccurate SoC estimation could result in battery overcharging and over discharging, which can have disastrous consequences on grid operations. This paper proposes a three-pronged online and offline method to detect, identify, and classify FDIAs corrupting the voltage sensors of a battery stack. To accurately model the dynamics of the series-connected cells a single particle model is used and to estimate the SoC, the unscented Kalman filter is employed. FDIA detection, identification, and classification was accomplished using a tuned cumulative sum (CUSUM) algorithm, which was compared with a baseline method, the chi-squared error detector. Online simulations and offline batch simulations were performed to determine the effectiveness of the proposed approach. Throughout the batch simulations, the CUSUM algorithm detected attacks, with no false positives, in 99.83% of cases, identified the corrupted sensor in 97% of cases, and determined if the attack was positively or negatively biased in 97% of cases.

25 ENERGY STORAGE↗

Analysis of redox additive-based overcharge protection for rechargeable lithium batteries

The overcharge condition in secondary lithium batteries employing redox additives for overcharge protection, has been theoretically analyzed in terms of a finite linear diffusion model. The analysis leads to expressions relating the steady-state overcharge current density and cell voltage to the concentration, diffusion coefficient, standard reduction potential of the redox couple, and interelectrode distance. The model permits the estimation of the maximum permissible overcharge rate for any chosen set of system conditions. Digital simulation of the overcharge experiment leads to numerical representation of the potential transients, and estimate of the influence of diffusion coefficient and interelectrode distance on the transient attainment of the steady state during overcharge. The model has been experimentally verified using 1,1-prime-dimethyl ferrocene as a redox additive. The analysis of the experimental results in terms of the theory allows the calculation of the diffusion coefficient and the formal potential of the redox couple. The model and the theoretical results may be exploited in the design and optimization of overcharge protection by the redox additive approach.

Narayanan, S. R.↗

Finite linear diffusion model for design of overcharge protection for rechargeable lithium batteries

The overcharge condition in secondary lithium batteries employing redox additives for overcharge protection has been theoretically analyzed in terms of a finite linear diffusion model. The analysis leads to expressions relating the steady-state overcharge current density and cell voltage to the concentration, diffusion coefficient, standard reduction potential of the redox couple, and interelectrode distance. The model permits the estimation of the maximum permissible overcharge rate for any chosen set of system conditions. The model has been experimentally verified using 1,1-prime-dimethylferrocene as a redox additive. The theoretical results may be exploited in the design and optimization of overcharge protection by the redox additive approach.

Narayanan, S. R.↗

Analysis of epitaxial drift field N on P silicon solar cells

The performance of epitaxial drift field silicon solar cell structures having a variety of impurity profiles was calculated. These structures consist of a uniformly doped P-type substrate layer, and a P-type epitaxial drift field layer with a variety of field strengths. Several N-layer structures were modeled. A four layer solar cell model was used to calculate efficiency, open circuit voltage and short circuit current. The effect on performance of layer thickness, doping level, and diffusion length was determined. The results show that peak initial efficiency of 18.1% occurs for a drift field thickness of about 30 micron with the doping rising from 10 to the 17th power atoms/cu cm at the edge of the depletion region to 10 to the 18th power atoms/cu cm in the substrate. Stronger drift fields (narrow field regions) allowed very high performance (17% efficiency) even after irradiation to 3x10 to the 14th power 1 MeV electrons/sq cm.

Baraona, C. R.↗

The drift field model applied to the lithium-containing silicon solar cell

The drift field model used by Wolf (1963) to calculate the short-circuit current was extended to permit calculations of the open-circuit voltage and the maximum power under conditions of illumination of either tungsten (2800 C) source or air mass zero sunlight. Voltages were calculated using an expression for the drift field diode saturation current. The model, applied to the oxygen-rich (C-13 group) lithium solar cells, was used to calculate the pre- and post-electron bombardment trends of the open-circuit voltage, maximum power, and short-circuit current for lithium gradients in the range from 10 to the 18th power to 10 to the 19th power Li/cm to the 4th power. Diffusion length degradation and carrier removal effects were sufficient to predict the cell performance up to 3 x 10 to the 14th electrons per sq cm. Beyond this fluence it was necessary to include drift field removal effects.

Godlewski, M. P.↗

Analysis of Solar Cell Efficiency for Venus Atmosphere and Surface Missions

A simplified model of solar power in the Venus environment is developed, in which the solar intensity, solar spectrum, and temperature as a function of altitude is applied to a model of photovoltaic performance, incorporating the temperature and intensity dependence of the open-circuit voltage and the temperature dependence of the bandgap and spectral response of the cell. We use this model to estimate the performance of solar cells for both the surface of Venus and for atmospheric probes at altitudes from the surface up to 60 km. The model shows that photovoltaic cells will produce power even at the surface of Venus.

Landis, Geoffrey A.↗

Band Bending at CdTe Solar Cell Contacts: Correlating Electro‐Optical and X‐Ray Photoelectron Spectroscopy Analyses of Thin Film Solar Cells

With the semiconductor bulk properties reaching target values for highly efficient solar cells, efforts are applied to reduce losses at solar cell interfaces and contacts. Advances in understanding back contacts in thin‐film polycrystalline CdTe solar cells, a leading thin‐film PV technology, are reported. By using X‐Ray photoelectron spectroscopy, Kelvin probe spectroscopy, time‐ and energy‐resolved photoluminescence, defects at the back contact are analyzed. Densities of recombination centers and charged defects that induce near‐back‐contact band bending, both resulting in recombination losses, were estimated. Electro‐optical and surface analysis results are integrated into a device model, simulating the performance of CdSeTe/CdTe solar cells with 902 mV open circuit voltage.

14 SOLAR ENERGY↗

Impact Modeling and Testing of Pouch and Prismatic Cells

Understanding battery response under impact is critical to improve the safety of electrified vehicles. Nevertheless, predicting the impact behaviors of batteries is not straightforward since a battery cell usually contains hundreds of thin layers with dramatically different material properties and multiple physical processes occur simultaneously during cell deformation. Here we utilized both empirical tests and numerical models to capture the failure process of pouch and prismatic cells in various impact scenarios. In each test, a cell was hit once by an indenter dropped from a certain height. During which the cell penetration, loading force, voltage and temperature were monitored to characterize the cell’s response. Meanwhile, numerical models were developed to capture the coupled mechanical, electrical, electrochemical and thermal responses of batteries. In these models, the cell bulk was treated as a homogeneous part to achieve computational efficiency required by large-scale simulations, and it was represented by the geologic cap model that allows both shear and compaction deformation. Simulation results showed agreement with experimental data in essential features of cell behaviors during impact. Details of the test setup, model development and cell failure behaviors are presented in this paper. Additionally, capabilities, limitations and future improvement of the battery safety modeling are discussed.

25 ENERGY STORAGE↗