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At least 865 records · Page 48

Gas-Phase Composition as a Predictive Metric for Calendar Life Behavior of Next-Generation Silicon Anodes

The expansion of renewable technologies and electrification of the transportation sector is driving increased demand for next-generation battery materials that provide higher power and energy density with superior cycling and calendar life stability. Silicon (Si) has a theoretical capacity nearly 10x that of graphite, and is therefore a promising anode material candidate to meet these rigorous performance demands. While leading Si anode battery demonstrations are approaching target metrics for cycle life, a series of complex and interrelated modes of reactivity lead to reduced calendar life and therefore challenge practical adoption of these materials. Deconvoluting the degradation processes that impact Si calendar life is critical to informing the rational and accelerated design of improved Si materials. In the present work, we employ novel sampling techniques and GC-MS-FID characterization to measure gas-phase composition during initial Si cycling, which we tie to selective mechanisms of Si passivation. We utilize a tiered analysis approach to identify and quantify the gas-phase reaction products associated with three advanced Si material candidates under practical operating conditions. Ex situ analysis of Si powders (pure chemical reactivity) is coupled with nondestructive in situ sampling of Si electrodes in a practical pouch-cell format (coupled chemical and electrochemical reactivity). We link the observed gas-phase species evolution to electrochemical behavior and measured calendar life of the three Si materials. Further, we evaluate the voltage-resolved evolution of gas-phase species for one such Si nanomaterial, where nonmonotonic gas generation implies competition between passivating reaction pathways. The measured gas-phase compositional data serves as a critical input for our advanced electrochemical SEI models to identify favorable vs unfavorable reaction pathways to stabilize Si. In addition to bolstering a fundamental understanding of Si reactivity, the present approach informs specific and quantifiable gas-phase metrics tied to calendar life improvements in Si, which can streamline and accelerate the process of next-generation material development.

DIRECT ENERGY CONVERSION,ENERGY STORAGE↗

Field‐representative evaluation of PID‐polarization in TOPCon PV modules by accelerated stress testing

Abstract Potential‐induced degradation‐polarization (PID‐p) can reduce module power, but how to project the extent to which PID‐p may occur in field conditions considering the factors of system voltage, condensed moisture, temperature, and illumination has not been clarified. Using tunnel oxide passivated contact (TOPCon) modules, this work demonstrates a method to test full‐size crystalline silicon PV modules for PID‐p to provide field‐representative results. In initial screening tests with positive or negative 1000 V electrical bias applied at 60°C for 96 h using Al foil electrodes on the glass surfaces, the module type exhibited reversible PID‐p only on the front face when the cell circuit was in negative voltage potential. No PID was detected on the rear after testing in either polarity. We then evaluated the PID‐p sensitivity on the front side under different UV irradiances while maintaining the glass surface wet to estimate real‐world susceptibility to PID‐p. The magnitude of the observed behavior was fit using a previously developed charge transfer and depletion by light model. Whereas power loss with −1000 V applied to the cell circuit at 60°C for 96 h in the dark was about 30%, testing the module front under 0.051 W·m −2 nm −1 at 340 nm UVA irradiation using fluorescent tubes, the mean degradation was only 3%. When the modules were tested in the dark for PID‐p with in situ dark current–voltage (I‐V) characterization, the thermal activation energy for degradation was 0.71 eV; for recovery in the dark, it was 0.58 eV. Whereas recovery from the degraded state at 60°C in the dark without voltage bias was 5% absolute in 38 h, rapid recovery of about 5% absolute was observed with 1000 W·s/m 2 exposure at 25°C using a flash tester.

14 SOLAR ENERGY↗

Critical Barriers to Successful Implementation of Earth-Abundant, Mn-Rich Cathodes for Vehicle Applications and Beyond: The Effect of Particle Morphology

As the search for improved and next-generation cathodes continues, it is clear that a deeper understanding of synthesis–structure–electrochemical property relationships is of critical importance. The effects of primary and secondary particle morphologies on various transition metal oxides have been studied, but new findings are still being reported. To date, few studies have focused on the effects of particle morphologies on Li- and Mn-rich oxides (>50% Mn) and even fewer studies have focused on the influence over key properties such as electrode-level impedance. In this study, we report the effects of particle morphologies on the area-specific-impedance (ASI) and thermal behavior of Li- and Mn-rich oxides. Samples with a fixed, layered–layered–spinel (LLS), composition were synthesized with differing primary morphologies and tested under standardized, full-cell protocols. The results suggest that smaller primary particle size (i.e., higher surface area) leads to lower overall ASI, a delay in the increasing impedance at low states-of-charge (SOCs), and surprisingly, improved thermal behavior.

33 ADVANCED PROPULSION SYSTEMS↗

A new mechanism of stabilizing SEI of Si anode driven by crosstalk behavior and its potential for developing high performance Si-based batteries

Stabilizing solid electrolyte interphase (SEI) is a key factor for determining cell performance of Silicon (Si) anode, such as safety, cycle lifetime, and calendar lifetime. Here, we found a new potential for stabilizing SEI of the Si anode, driven by crosstalk with cathode material. Here we investigated the effect of crosstalk on the chemistry of SEI of the Si anode as a function of three different, representative cathode materials: LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532), LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811), and LiFePO 4 (LFP). Specifically, we observed that crosstalk significantly affected the formation and growth mechanism of SEI layer on the Si anodes. Unexpectedly, dissolved Fe ions from the LFP cathode has a positive impact on the chemistry and electrochemical stability of the SEI layer of Si anode compared to the other cathodes, resulting in better electrochemical performance in terms of initial coulombic efficiency and capacity fade.

25 ENERGY STORAGE↗

A Large Eddy Simulation Study of Flow Turbulence, Alumina Transport, and Bath Temperature Evolution in Conventional Aluminum-Smelting Cell Using OpenFOAM

In this study, a Large Eddy Simulation (LES) of the aluminum-smelting process is performed using OpenFOAM. To understand the coupled behavior of heat transfer, mass transfer, and flow of the smelting process, a multi-physics computational fluid dynamics (CFD) model based on the Eulerian–Eulerian multi-fluid approach is adopted. The model accounts for CO 2 bubble and magnetohydrodynamics (MHD)-driven flow, along with alumina dissolution, transport, and bath temperature evolution. The simulation predictions show small-scale turbulent vortical structures in the anode–cathode space caused by combined effect of MHD and CO 2 bubble-bath interactions and relatively large-scale asymmetric vortices in the inter-anode space caused by the CO 2 bubble-bath interactions. The vortex formation at the edges of the anodes evidently aids in transporting alumina from the central channel to the bottom of the anodes and prevents accumulation of gas bubbles in the periphery of the anode bottom. Symmetric bath cold spots are observed in the vicinity of the feeder. Cold spots are also observed in the anode–cathode distance space below the anode bottom due to the transport of undissolved solid to this region by the flow. The findings from the work are useful in developing and designing alumina-feeding strategy leading to reduced anode effects and smooth operation of the cell. The work also highlights the important flow structures in conventional aluminum-smelting cell.

36 MATERIALS SCIENCE↗

Solar array synthesis computer program

Photovoltaic characteristics have been measured on solar cells irradiated by 1 MeV electrons to fluences ranging from 1 x 10 to the 13th power e/sq cm to 1 x 10 to the 16th power e/sq cm, for cell temperatures ranging from 123 K to 473 K and for illumination intensities ranging from 5m W/sq cm to 1830m W/sq cm. Empirical equations have been derived from these measurements to describe the behavior of light generated current, open circuit voltage and I-V curve shape over various portions of these temperature/illumination ranges. Both 10 ohms/cm and 17 ohms/cm n-p silicon solar cells were tested, and similar analytical expressions were formulated for easy comparison between the two resistivities.

Faith, T. J.↗

Room Temperature, Dip Coating Organic Passivation for c-Si Surfaces

Surface passivation of crystalline Si (c-Si) to reduce recombination rate is crucial to obtain high-efficiency c-Si solar cells. A fast passivation technique that can be performed at room temperature is needed when studying the degradation behaviors using various characterization methods to not destroy the degraded states. In this contribution, we explore Nafion via dip coating on n-type Cz wafers. We show that both the Nafion concentration and the conditions of surface and edge affect the passivation quality, and we achieve excellent passivation quality of iVoc of 716 mV, with a saturation current density (J0) of 7 fA/cm2. Additionally, electron paramagnetic resonance (EPR) shows Nafion can be used under cryogenic temperature and reveals the reduction of Si dangling bond after Nafion treatment.

dielectric solar cell↗

TERRA Battery Thermal Control Anomaly - Simulation and Corrective Actions

The TERRA spacecraft was launched in December 1999 from Vandenberg Air Force Base, becoming the flagship of NASA's Earth Observing System program to gather data on how the planet's processes create climate. Originally planned as a 5 year mission, it still provides valuable science data after nearly 10 years on orbit. On October 13th, 2009 at 16:23z following a routine inclination maneuver, TERRA experienced a battery cell failure and a simultaneous failure of several battery heater control circuits used to maintain cell temperatures and gradients within the battery. With several cells nearing the minimum survival temperature, preventing the electrolyte from freezing was the first priority. After several reset attempts and power cycling of the control electronics failed to reestablish control authority on the primary side of the controller, it was switched to the redundant side, but anomalous performance again prevented full heater control of the battery cells. As the investigation into the cause of the anomaly and corrective action continued, a battery thermal model was developed to be used in determining the control ability remaining and to simulate and assess corrective actions. Although no thermal model or detailed reference data of the battery was available, sufficient information was found to allow a simplified model to be constructed, correlated against pre-anomaly telemetry, and used to simulate the thermal behavior at several points after the anomaly. It was then used to simulate subsequent corrective actions to assess their impact on cell temperatures. This paper describes the rapid development of this thermal model, including correlation to flight data before and after the anomaly., along with a comparative assessment of the analysis results used to interpret the telemetry to determine the extent of damage to the thermal control hardware, with near-term corrective actions and long-term operations plan to overcome the anomaly.

Grob, Eric W.↗

Probing elemental diffusion and radiation tolerance of perovskite solar cells via non-destructive Rutherford backscattering spectrometry

Mixed organic–inorganic halide perovskite-based solar cells have attracted interest in recent years due to their potential for both terrestrial and space applications. Analysis of interfaces is critical to predicting device behavior and optimizing device architectures. Most advanced tools to study buried interfaces are destructive in nature and can induce further degradation. Ion beam techniques, such as Rutherford backscattering spectrometry (RBS), is a useful non-destructive method to probe an elemental depth profile of multilayered perovskite solar cells (PSCs) as well as to study the inter-diffusion of various elemental species across interfaces. Additionally, PSCs are becoming viable candidates for space photovoltaic applications, and it is critical to investigate their radiation-induced degradation. RBS can be simultaneously utilized to analyze the radiation effects induced by He+ beam on the device, given their presence in space orbits. In the present work, a 2 MeV He+ beam was used to probe the evidence of elemental diffusion across PSC interfaces with architecture glass/ITO/SnO2/Cs0.05(MA0.17FA0.83)0.95Pb(I0.83Br0.17)3/spiro-OMeTAD/MoO3/Au. During the analysis, the device active area was exposed to an irradiation equivalent of up to 1.62 × 1015 He+/cm2, and yet, no measurable evidence (with a depth resolution ∼1 nm) of beam-induced ion migration was observed, implying high radiation tolerance of PSCs. On the other hand, aged PSCs exhibited indications of the movement of diverse elemental species, such as Au, Pb, In, Sn, Br, and I, in the active area of the device, which was quantified with the help of RBS.

14 SOLAR ENERGY↗

Elasticity of two-dimensional ferroelectrics across their paraelectric phase transformation

The mechanical behavior of two-dimensional (2D) materials across 2D phase changes is unknown, and the finite temperature (T) elasticity of paradigmatic SnSe monolayers—ferroelectric 2D materials turning paraelectric as their unit cell turns from a rectangle into a square—is described here in a progressive manner. To begin with, their zero–T total energy landscape gives way to (Boltzmann-like) averages from which the elastic behavior is determined. Furthermore, these estimates are complemented with results from the strain-fluctuation method, which employs the energy landscape or ab initio molecular dynamics data. All approaches capture the coalescence of elastic moduli < C 11 (T) > = < C 22 (T) > due to the structural transformation. The broad evolution and sudden changes of elastic parameters < C 11 (T) >, < C 22 (T) >, and < C 12 (T) > of these atomically thin phase-change membranes establishes a heretofore overlooked connection among 2D materials and soft matter.

2-dimensional systems↗

Modeling Common-Sense Decisions in Artificial Intelligence

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Zak, Michail↗

In situ investigation of high-pressure hydrogen-induced swelling in elastomers and its correlation with material properties

The resistance of elastomeric materials to high-pressure hydrogen-induced damage is essential for ensuring the reliability of hydrogen infrastructure. Here, in this study, we systematically investigated the swelling behavior and hydrogen transport properties of four elastomer types – EPDM, NBR, FKM, and HNBR – using a custom in-situ view cell system capable of real-time monitoring during decompression from pressures up to 96.5 MPa. Each elastomer was formulated with and without fillers and plasticizers to assess the effects of formulation on swelling response. Thermal desorption analysis (TDA) was employed to determine equilibrium hydrogen content and diffusion coefficients, providing insight into gas uptake and mobility within each material. Correlation analyses using Pearson and Spearman coefficients revealed that the diffusion coefficient showed a stronger relationship with swelling behavior than hydrogen content, highlighting the dominant role of hydrogen mobility. Filled elastomers, particularly those with carbon black, consistently showed reduced swelling due to enhanced stiffness and reduced diffusivity. These results deepen our understanding of diffuso-mechanical interactions in elastomers and support the rational design of sealing materials for high-pressure hydrogen systems.

EPDM↗

Understanding Reliability Trade-Offs in 1T-nC and 2T-nC FeRAM Designs

Ferroelectric random access memory (FeRAM) is a promising candidate for energy-efficient nonvolatile memory, particularly for logic-in-memory and compute-in-memory (CIM) applications. Among the available cell architectures, One-Transistor–n-Capacitor (1T-nC) and two-transistor–n-capacitor (2T-nC) FeRAMs each offer distinct trade-offs in density, scalability, and reliability. In this work, we present a comparative study of these two architectures under both dimensional scaling ( XY/Z shrinkage) and vertical integration (increasing stacked capacitors per cell). Using technology computer-aided design (TCAD) and circuit-level simulations, we analyze how scaling impacts ferroelectric capacitance, parasitic coupling, and floating-node (FN) dynamics, which together dictate sense margin (SM) and read stability. A key mitigation strategy—floating unselected capacitors—is applied to both architectures, effectively decoupling the SM from the number of stacked capacitors and enabling tractable analysis across scaling regimes. Results show that 1T-nC suffers more from charge sharing with the bitline (BL), while 2T-nC benefits from transistor isolation and stronger low-voltage sensing at the cost of increased area. By systematically evaluating these behaviors across scaling directions, this work establishes the reliability trade-offs of 1T-nC and 2T-nC cells and provides design guidelines for high-density, vertically integrated FeRAM systems.

1T-nC↗

Learning curves for drug response prediction in cancer cell lines

Motivated by the size and availability of cell line drug sensitivity data, researchers have been developing machine learning (ML) models for predicting drug response to advance cancer treatment. As drug sensitivity studies continue generating drug response data, a common question is whether the generalization performance of existing prediction models can be further improved with more training data. We utilize empirical learning curves for evaluating and comparing the data scaling properties of two neural networks (NNs) and two gradient boosting decision tree (GBDT) models trained on four cell line drug screening datasets. The learning curves are accurately fitted to a power law model, providing a framework for assessing the data scaling behavior of these models. The curves demonstrate that no single model dominates in terms of prediction performance across all datasets and training sizes, thus suggesting that the actual shape of these curves depends on the unique pair of an ML model and a dataset. The multi-input NN (mNN), in which gene expressions of cancer cells and molecular drug descriptors are input into separate subnetworks, outperforms a single-input NN (sNN), where the cell and drug features are concatenated for the input layer. In contrast, a GBDT with hyperparameter tuning exhibits superior performance as compared with both NNs at the lower range of training set sizes for two of the tested datasets, whereas the mNN consistently performs better at the higher range of training sizes. Moreover, the trajectory of the curves suggests that increasing the sample size is expected to further improve prediction scores of both NNs. These observations demonstrate the benefit of using learning curves to evaluate prediction models, providing a broader perspective on the overall data scaling characteristics. A fitted power law learning curve provides a forward-looking metric for analyzing prediction performance and can serve as a co-design tool to guide experimental biologists and computational scientists in the design of future experiments in prospective research studies.

60 APPLIED LIFE SCIENCES↗

A methodology for experimentally based determination of gap shrinkage and effective lifetimes in the emitter and base of p-n junction solar cells and other p-n junction devices

An experimentally based methodology that determines the effective gap shrinkage and lifetime in the emitter of a p-n junction solar cell is described which provides an experimental means for assessing the importance of gap shrinkage relative to that of large recombination rates in the highly doped emitter. The base lifetime is also determined. The methodology pertains to a solar cell after the junction is formed, so that each material parameter determined includes the effects of the processing used in junction fabrication. The methodology consists of strategy and procedures for designing experiments and interpreting data consistently with the physical mechanisms governing device behavior. This careful linking to the device physics uncover the material parameters concealed in the data. To illustrate the procedures, they are applied to an n(+)-p solar cell having substrate resistivity of about 0.1 ohm-cm.

Lindholm, F. A.↗

Heat flow control and segregation in directional solidification: Development of an experimental and theoretical basis for Bridgman-type growth experiments in a microgravity environment

Within the framework of the proposed research, emphasis was placed on application of magnetic fields to semiconductor growth systems. It was found that magnetic fields up to 3 kGauss do not affect the growth behavior nor the macro-segregation behavior in the system Ge(Ga). Applied fields are found to significantlty alter the radial dopant distribution, which is attributed to alterations in the spatial orientation of convective cells. Increasing the magnetic field to 30 kGauss is found to have a fundamental effect on dopant segregation. Emphasis is also placed on the potential of KC-135 flights for preliminary studies on the effects of reduced gravity environments on the wetting behavior of semiconductor systems in growth configuration. The limited number of experiments conducted does not allow any conclusions on the merits of KC-135 flights for semiconductor processing research.

Witt, A. F.↗

Auxin-activated NADH oxidase activity of soybean plasma membranes is distinct from the constitutive plasma membrane NADH oxidase and exhibits prion-like properties

The hormone-stimulated and growth-related cell surface hydroquinone (NADH) oxidase activity of etiolated hypocotyls of soybeans oscillates with a period of about 24 min or 60 times per 24-h day. Plasma membranes of soybean hypocotyls contain two such NADH oxidase activities that have been resolved by purification on concanavalin A columns. One in the apparent molecular weight range of 14-17 kDa is stimulated by the auxin herbicide 2,4-dichlorophenoxyacetic acid (2,4-D). The other is larger and unaffected by 2,4-D. The 2,4-D-stimulated activity absolutely requires 2,4-D for activity and exhibits a period length of about 24 min. Also exhibiting 24-min oscillations is the rate of cell enlargement induced by the addition of 2,4-D or the natural auxin indole-3-acetic acid (IAA). Immediately following 2,4-D or IAA addition, a very complex pattern of oscillations is frequently observed. However, after several hours a dominant 24-min period emerges at the expense of the constitutive activity. A recruitment process analogous to that exhibited by prions is postulated to explain this behavior.

Non-NASA Center↗

Frequency dependence of BCS and residual resistance using multi-mode measurement of nitrogen-doped single-cell elliptical cavities

Various cavity surface treatments have been found to significantly improve cavity quality factor, Q0, with one such treatment being nitrogen-doping (N-doping). N-doped 1.3 GHz cavities were the first found to exhibit anti-Q slope, the increase of Q0 with accelerating field, Eacc. However, even with the use of the same N-doping recipes, this anti-Q slope behavior has not been realized in sub-GHz frequency cavities. In this study, we measured the Q0 and surface resistance, RS, of our N-doped, single-cell, elliptical cavity for both the 644 MHz fundamental mode (FM) and 1.45 GHz higher-order mode (HOM). As a result of multi-mode measurements, the BCS and residual resistances, the temperature-dependent and temperature-in-dependent RF surface resistances, could be determined without the influence of cavity-to-cavity surface treatment variations. We will discuss the frequency-dependent behaviors of the BCS and residual resistances.

Accelerator Physics↗