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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Secondary Ion Mass Spectrometry (SIMS) for Chemical Characterization of Metal Halide Perovskites

Metal halide perovskite (MHP) solar cells have attracted much attention due to the rapidly growing power conversion efficiency that has reached 25.2% in a decade, comparable to established commercial photovoltaic modules. Compositional engineering is one of the most effective methods to boost the performance of MHP solar cells. Further improving the efficiency and the stability of MHP solar cells necessitates good understanding of the chemical–efficiency correlation and the chemical evolution during the degradation of MHP solar cells. In this regard, time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful tool to investigate the chemical aspect of MHPs and has played an important role in advancing the development of MHP optoelectronics. However, up to date, a review that can guide future utilization of ToF-SIMS in the MHP development is missing. In this paper, the capabilities of ToF-SIMS in MHP investigations are summarized and analyzed from simple material synthesis and chemical distribution to more complicated device operation mechanism and stability. The strength of ToF-SIMS in resolving important issues in this field, such as interface composition, ion migration, and degradation in MHP is highlighted. Finally, an outlook with an emphasis on making the utmost of ToF-SIMS in developing MHP devices is provided.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simulation of Multiphase Flow and Poromechanical Effects Around Injection Wells in CO 2 Storage Sites

In geological CO 2 storage operations, wellbore deformations and leakage pathways formations can occur around injection and abandoned wells subjected to high rates and long-term CO 2 injection. To guide engineering design and prevent CO 2 leakage risks, a full understanding of the underlying physics and robust numerical models is necessary to evaluate the response of underground formations in the near wellbore region and in the reservoir. In this study, a multi-scale and multi-physics open-source simulator (GEOS) is used to simulate multiphase flow and poromechanical deformations over time in three dimensions. The governing equations for mechanical deformations of the rock body and multiphase compositional fluid flow within the rock matrix are solved with a fully coupled finite element and finite volume approach. The Drucker–Prager model with friction hardening is applied to simulate elastoplastic deformation and a multiphase fluid model with power-law correlations for relative permeability is used to model the migration of CO 2 plume, which are coupled with numerical implicit scheme. Simulation results are verified against multiple analytical solutions for multiphase flow and wellbore problems, thus demonstrating the accuracy of this advanced simulator. In two engineering applications, here we highlight the impact of elastoplastic deformation and coupled modeling for assessing induced displacements and stress perturbations, which are more pronounced in the near wellbore regions. This work focuses on short-term processes in the vicinity of injection wells where stress evolutions, rock deformations and multiphase compositional flow and transport are simulated jointly to ensure wellbore stability and prevent damage. This fully coupled geomechanical model can simulate multiphase flow and any associated poromechanical effects within the CO 2 storage site and in the surrounding formations. Such a large-scale, long-term, multi-physics simulation model is useful in many ways: it can guide operational decisions for CO 2 injection, assess the containment potential and risks of a site, and analyze the wellbore stability and integrity during and after CO 2 injection.

58 GEOSCIENCES↗
DOE OSTI2025

Machine learning accelerated prediction of Ce-based ternary compounds involving antagonistic pairs

The discovery of novel quantum materials within ternary phase spaces containing antagonistic pairs such as Fe with Bi, Pb, In, and Ag, presents significant challenges yet holds great potential. In this work, we investigate the stabilization of these immiscible pairs through the integration of Cerium (Ce), an abundant rare-earth and cost-effective element. By employing a machine learning (ML)-guided framework, particularly crystal graph convolutional neural networks (CGCNN), combined with first-principles calculations, we efficiently explore the composition/structure space and predict 9 stable and 37 metastable Ce-Fe-X (X=Bi, Pb, In, and Ag) ternary compounds. Our findings include the identification of multiple new stable and metastable phases, which are evaluated for their structural and energetic properties. These discoveries not only contribute to the advancement of quantum materials but also offer viable alternatives to critical rare earth elements, underscoring the importance of Ce-based intermetallic compounds in technological applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimizers for stabilizing likelihood-free inference

A growing number of applications in particle physics and beyond use neural networks as unbinned likelihood ratio estimators applied to real or simulated data. Precision requirements on the inference tasks demand a high-level of stability from these networks, which are affected by the stochastic nature of training. We show how physics concepts can be used to stabilize network training through a physics-inspired optimizer. In particular, the energy conserving descent (ECD) optimization framework uses classical Hamiltonian dynamics on the space of network parameters to reduce the dependence on the initial conditions while also stabilizing the result near the minimum of the loss function. We develop a version of this optimizer known as , which has few free hyperparameters with limited ranges guided by physical reasoning. We apply to representative likelihood-ratio estimation tasks in particle physics and find on average that it out-performs the widely used Adam optimizer. We expect that ECD will be a useful tool for wide array of data-limited problems, where it is computationally expensive to exhaustively optimize hyperparameters and mitigate fluctuations with ensembling.

Monte Carlo methods↗
DOE OSTI2023

Elevating the Practical Application of Sodium-Ion Batteries through Advanced Characterization Studies on Cathodes

Sodium-ion batteries (SIBs) have emerged as promising alternatives to their lithium-ion counterparts due to the abundance of sodium resources and their potential for cost-effective energy storage solutions. The chemistry for SIBs has been investigated since the 1980s, but it went through a slow research and development process. Recently, there has been an acceleration in technology maturation due to a supply chain crisis originating from unequal resource distribution and sustainability and safety concerns regarding lithium-ion batteries. However, the practical application of SIBs has been hindered primarily by challenges related to cathode materials, specifically, surface and structural stabilities in different conditions. Through the integration of advanced techniques such as in situ spectroscopy, operando diffraction, and high-resolution microscopy, a comprehensive understanding of the cathode’s dynamic behavior and degradation mechanisms can be achieved. The identified structural modifications, phase transitions, and degradation pathways offer critical insights into the design of robust cathode materials with prolonged cycling stability, fast charging capability, high energy density, great low-temperature performance, and safety. This review underscores the pivotal role of cutting-edge characterization techniques in guiding the development of high-performance sodium-ion batteries, thereby fostering the realization of sustainable and efficient energy storage solutions for diverse technological applications.

25 ENERGY STORAGE↗
NASA NTRS2014

Using the NASA GRC Sectored-One-Dimensional Combustor Simulation

The document is a user manual for the NASA GRC Sectored-One-Dimensional (S-1-D) Combustor Simulation. It consists of three sections. The first is a very brief outline of the mathematical and numerical background of the code along with a description of the non-dimensional variables on which it operates. The second section describes how to run the code and includes an explanation of the input file. The input file contains the parameters necessary to establish an operating point as well as the associated boundary conditions (i.e. how it is fed and terminated) of a geometrically configured combustor. It also describes the code output. The third section describes the configuration process and utilizes a specific example combustor to do so. Configuration consists of geometrically describing the combustor (section lengths, axial locations, and cross sectional areas) and locating the fuel injection point and flame region. Configuration requires modifying the source code and recompiling. As such, an executable utility is included with the code which will guide the requisite modifications and insure that they are done correctly.

Combustion Stability↗
DOE OSTI2020

A combined machine learning and density functional theory study of binary Ti-Nb and Ti-Zr alloys: Stability and Young’s modulus

The multicomponent Ti alloys, specifically the -phase, have experienced a strong growth over the last decades, due to their outstanding properties of ultra-high strength and low Young’s modulus. These properties play a significant role in many aerospace and biomedical applications. Selection and optimization of multicomponent alloys is challenging due to the vast chemical and compositional space. Here we investigate the use of machine learning techniques informed by density functional calculations to guide the selection of Nb- and Zr-based Ti binary alloys. From the cubic structures obtained from high throughput calculations and literature, we identify several structures with Young’s moduli below 40 GPa. The multivariant decision tree methods provide efficient surrogate models to identify structure variables have high influences on the energetic stability and Young’s modulus. Furthermore, we implement a workflow of incorporating DFT provided results and machine learning method to explore the chemical and composition space of other binary and multicomponent alloys, to eventually accelerate the material design via taking advantages of identified key variables.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Interlayer Design for Halide Electrolytes in All‐Solid‐State Lithium Metal Batteries

Abstract All‐solid‐state lithium‐metal batteries (ASSLMBs) are promising for transportation electrification due to their superior safety and high energy density. Lithium halide electrolytes provide excellent processing flexibility, high ionic conductivity, and anodic stability (>4.1 V), making them highly compatible with high‐voltage cathodes, surpassing sulfide electrolytes (<2.1 V). Nevertheless, halide electrolytes suffer from low cathodic stability and form an electronically conductive interphase with lithium, resulting in a critical current density (CCD) of nearly zero. Herein, Li 3 YbCl 6 electrolytes are synthesized that are kinetically stable with lithium by forming an electronic insulating solid electrolyte interphase. Guided by critical overpotential criteria, a PI 3 interlayer is designed that transforms into Li 6 PI 3 upon contact with lithium, substantially reducing the interfacial resistance of Li 3 YbCl 6 against lithium to 34 Ω and achieving a high critical overpotential of 114 mV. By substituting Yb with Lu, Li 3 LuCl 6 electrolytes with Li 6 PI 3 interlayers reach a CCD of 1.0 mA cm −2 at a capacity of 1.0 mAh cm −2 , comparable to sulfide electrolytes but with higher oxidation stability. Additionally, Li 6 PI 3 enables stable cycling of Li//Li cells with Li 3 LuCl 6 electrolytes at 0.5 mA cm −2 for 400 cycles and maintains 86.5% capacity in Li//LiCoO 2 cells after 220 cycles at 30 °C, paving the way for high‐performance ASSLMBs.

Chemistry↗
DOE OSTI2025

Tailoring the Intermediate Phase to Control Formation of γ‑CsPbI3 Films

Controlling the crystallization pathway of inorganic CsPbI3 perovskite is essential for achieving high efficiency and stability in optoelectronic devices. Here, we report a solvent-engineering strategy that combines an antisolvent process with vacuum treatment (AVT) to modulate evaporation dynamics of the precursor, guiding the formation of highly oriented (CH3)2NH2PbI3 (DMAPbI3) and Cs4PbI6 intermediate phases. Synchrotron and in situ analyses revealed correlations between intermediate orientation and γ-CsPbI3 crystallinity. This directional crystallization pathway promotes vertical alignment and grain enlargement in γ-CsPbI3 films, resulting in fewer voids, lower defect densities, and reduced tensile strain. Photovoltaic devices based on AVT-processed films achieved a power conversion efficiency of 18.47% with a fill factor of 83.14% and retained 101.9% of their initial efficiency after 526 h without encapsulation. This study first reports that the quality of DMAPbI3 and Cs4PbI6 intermediates, controlled by combination of antisolvent and vacuum treatment, plays a crucial role in achieving high-quality γ-CsPbI3 films.

Yoon, Geon Woo↗
DOE OSTI2025

S -Adenosylhomocysteine Analogs Selectively Suppress Pan-Coronavirus Replication by Inhibition of nsp14 Methyltransferase

To address the ongoing threat of SARS-CoV-2 and potential emergence of novel coronaviruses, we employed a comprehensive strategy to identify and synthesize inhibitors of coronavirus methyltransferases with chemical analogs of S-adenosylhomocysteine (SAH). Two analogs, designated 4h and 4p, inhibit both mouse hepatitis virus and SARS-CoV-2 replication. Compound 4p was the most potent with half-maximal inhibition of biochemical activity at 0.2 μM and antiviral activity at ∼20 μM. This compound also has low cytotoxicity and preferentially inhibits nsp14 over nsp16 and human methyltransferases. Furthermore, molecular docking based on a newly determined crystal structure of the apo nsp16−nsp10 complex predicts that 4p occupies both the Sadenosylmethione and Gppp binding pockets of nsp14 and nsp16. Selectivity of 4p for nsp14 is likely due to the enhanced structural stability of the nsp14 binding pocket relative to nsp16. These findings highlight SAH analogs as scaffolds for pan-coronavirus therapeutics and underscore the value of structure-guided design in antiviral drug discovery.

Coronavirus↗
DOE OSTI2023

Towards linking lab and field lifetimes of perovskite solar cells

Metal halide perovskite solar cells (PSCs) represent a promising low-cost, thin-film photovoltaic (PV) technology, with unprecedented power conversion efficiencies (PCEs) obtained for both single-junction and tandem applications. To push PSCs toward commercialization, it is critical, albeit challenging, to understand device reliability under real-world outdoor conditions where multiple stress factors (e.g., light, heat, humidity) coexist, generating complicated degradation behaviors. It is necessary to identify accelerated indoor testing protocols - which can correlate specific stressors with observed degradation modes in fielded devices - to quickly guide PSC development. Here, we use a state-of-the-art p-i-n PSC stack (with PCE up to ~25.5%) to show that indoor accelerated stability tests can predict our 6-month outdoor aging tests. Device degradation rates under illumination and at elevated temperatures are most instructive for understanding outdoor device reliability. Further, we also find that the indium tin oxide (ITO)/self-assembled monolayer (SAM)-based hole transport layer (HTL)/perovskite interface most strongly affects our device operation stability. Improving the ion-blocking properties of the SAM HTL increases averaged device operational stability at 50 degree C-85 °C by a factor of ~2.8, reaching over 1000 h at 85 °C and to near 8200 h at 50 °C with a projected 20% degradation, which is among the best to date for high-efficiency p-i-n PSCs.

14 SOLAR ENERGY↗
DOE OSTI2020

Salt-rich solid electrolyte interphase for safer high-energy-density Li metal batteries with limited Li excess

We propose a carbonate-based electrolyte optimized with dual cations and ionic liquid for high-efficiency Li metal batteries with a high-voltage cathode. An average coulombic efficiency of Li deposition of 99.6% is achieved due to the salt-rich solid electrolyte interphase and Na guided uniform Li plating. The Li||NCM811 cells can be cycled with limited Li (N/P = 1) over 90 cycles. An additional advantage is that it improves the thermal stability of the NCM811 cathode.

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

Origin for electrochemically driven phase transformation in the oxygen electrode for a solid oxide cell

The next generation of fuel cells, electrolyzers, and batteries requires higher power, faster kinetics, and larger energy density, which necessitate the use of compositionally complex oxides to achieve multifunctionalities and activity. These compositionally complex oxides may change their phases and structures during an electrochemical process—a so-called “electrochemically driven phase transformation.” The origin for such a phase change has remained obscure. The aim of this paper is to present an experimental study and a theoretical analysis of phase evolution in praseodymium nickelates. Nickelate-based electrodes show up to 60 times greater phase transformation during operation when compared with thermally annealed ones. Theoretical analysis suggests that the presence of a reduced oxygen partial pressure at the interface between the oxygen electrode and the electrolyte is the origin for the phase change in an oxygen electrode. Guided by the theory, the addition of the electronic conduction in the interface layer leads to the significant suppression of phase change while improving cell performance and performance stability.

25 ENERGY STORAGE↗
DOE OSTI2020

Prediction of exotic magnetic states in the alkali-metal quasi-one-dimensional iron selenide compound Na 2 FeSe 2

The magnetic and electronic phase diagram of a model for the quasi-one-dimensional alkali-metal iron selenide compound Na 2 FeSe 2 is presented. The novelty of this material is that the valence of iron is Fe 2+ , contrary to most other iron-chain compounds with valence Fe 3+ . Using first-principles techniques, we developed a three-orbital tight-binding model that reproduces the ab initio band structure near the Fermi level. Including Hubbard and Hund couplings and studying the model via the density-matrix renormalization group and Lanczos methods, we constructed the ground-state phase diagram. A robust region where the block state ↑↑↓↓↑↑↓↓ is stabilized was unveiled. The analog state in iron ladders, employing 2×2 ferromagnetic blocks, is by now well established, but in chains a block magnetic order has not been observed yet in real materials. The phase diagram also contains a large region of canonical staggered spin order ↑↓↑↓↑↓↑ at very large Hubbard repulsion. At the block-to-staggered transition region, an exotic phase is stabilized with a mixture of both states: an inhomogeneous orbital-selective charge density wave with the exotic spin configuration ↑↑↓↑↓↓↑↓. Our predictions for Na 2 FeSe 2 may guide crystal growers and neutron-scattering experimentalists towards the realization of block states in one-dimensional iron selenide chain materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Topological Interface between Pfaffian and Anti-Pfaffian Order in $\textit{ν}$ = 5/2 Quantum Hall Effect

A recent thermal Hall experiment triggered renewed interest in the problem of $\textit{ν}$ = 5/2 quantum Hall effect, which motivated novel interpretations based on the formation of mesoscopic puddles made of Pfaffian and anti-Pfaffian topological orders. Here, we study an interface between the Pfaffian and anti-Pfaffian states, which may play crucial roles in thermal transport, by means of state-of-the-art, density-matrix renormalization group simulations. We demonstrate that an intrinsic electric dipole moment emerges at the interface, similar to the “$\textit{p–n}$” junction sandwiched between $\textit{N}$-type and $\textit{P}$-type semiconductor. Importantly, in this work we elucidate the topological origin of this dipole moment, whose formation is to counterbalance the mismatch of guiding-center Hall viscosity of bulk Pfaffian and anti-Pfaffian states. In addition, these results imply that the formation of a dipole moment could be helpful to stabilize the puddles made of Pfaffian and anti-Pfaffian states in experimental conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1991

The imaging performance of the Hubble Space Telescope

Problems with the HST instantaneous imaging performance and pointing performance are discussed. Optical tests have clearly demonstrated that the HST suffers from spherical aberration. The top level specification was that 70 percent of the energy be focused in a 0.1 in. radius, but the present, and close to optimum, focus setting gives only about 16 percent. The pointing control system also is having problems with the results that the spacecraft achieves a stability of about 0.007 rms in quiescent periods, falling short of specification which requires that such performance be maintained for 24 hr. The finite guidance sensors are not guiding well on faint stars. There is a loss of sky coverage at high Galactic latitude, especially for the Wide-Field/Planetary Camera. The consequences of these defects for the scientific program are examined.

Burrows, Christopher J.↗
DOE OSTI2024

Code-to-code comparison between FLASH and HYDRA in gas-puff Z-pinch modeling

The numerical modeling of gas-puff Z pinches involves the nonlinear coupling of a broad range of complex, multi-physics phenomena that makes such simulations challenging. The challenge is further compounded by nonlinear instabilities that can impact the dynamics of imploding gas-puff Z pinches, such as the magneto Rayleigh–Taylor instability (MRTI). If the growth rate and amplitude of the latter is comparable to the relevant timescales and properties of the imploding plasma, the MRTI can dramatically alter implosion dynamics, dictate pinch stability, and govern the plasma properties achievable in pulsed-power-driven laboratory experiments. National Laboratories and academic teams have developed numerical tools that can accurately model Z-pinch configurations and provide reliable design capabilities that can guide experimental choices and assist in interpreting experimental results. Most such tools, however, are not broadly available. Here, we present newly developed Z-pinch simulation capabilities of the publicly available FLASH code, applied in the study of MRTI growth and dynamical effects in gas-puff implosions. To verify the new implementations, we perform a comparison of FLASH gas-puff implosion simulations with previously published calculations with the HYDRA code from Lawrence Livermore National Laboratory, which have been validated with experimental data from the CESZAR pulsed-power driver at the University of California, San Diego. The experiments involved double- and triple-nozzle configurations, in an experimental attempt to stabilize the pinch to the MRTI. The code-to-code comparison shows similar results between the FLASH and HYDRA simulations, supporting the use of FLASH in the modeling of future gas-puff Z-pinch experiments at CESZAR.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies

Abstract. Climatic extreme events are expected to occur more frequently in the future, increasing the likelihood of unprecedented climate extremes (UCEs) or record-breaking events. UCEs, such as extreme heatwaves and droughts, substantially affect ecosystem stability and carbon cycling by increasing plant mortality and delaying ecosystem recovery. Quantitative knowledge of such effects is limited due to the paucity of experiments focusing on extreme climatic events beyond the range of historical experience. Here, we present a road map of how dynamic vegetation demographic models (VDMs) can be used to investigate hypotheses surrounding ecosystem responses to one type of UCE: unprecedented droughts. As a result of nonlinear ecosystem responses to UCEs that are qualitatively different from responses to milder extremes, we consider both biomass loss and recovery rates over time by reporting a time-integrated carbon loss as a result of UCE, relative to the absence of drought. Additionally, we explore how unprecedented droughts in combination with increasing atmospheric CO2 and/or temperature may affect ecosystem stability and carbon cycling. We explored these questions using simulations of pre-drought and post-drought conditions at well-studied forest sites using well-tested models (ED2 and LPJ-GUESS). The severity and patterns of biomass losses differed substantially between models. For example, biomass loss could be sensitive to either drought duration or drought intensity depending on the model approach. This is due to the models having different, but also plausible, representations of processes and interactions, highlighting the complicated variability of UCE impacts that still need to be narrowed down in models. Elevated atmospheric CO2 concentrations (eCO2) alone did not completely buffer the ecosystems from carbon losses during UCEs in the majority of our simulations. Our findings highlight the consequences of differences in process formulations and uncertainties in models, most notably related to availability in plant carbohydrate storage and the diversity of plant hydraulic schemes, in projecting potential ecosystem responses to UCEs. We provide a summary of the current state and role of many model processes that give way to different underlying hypotheses of plant responses to UCEs, reflecting knowledge gaps which in future studies could be tested with targeted field experiments and an iterative modeling–experimental conceptual framework.

54 ENVIRONMENTAL SCIENCES↗