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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Molecular Design Considerations for Azobenzene Anolytes

Realization of high-density batteries requires the development of anolytes that display highly negative reduction potentials, solubility, and persistence in the charged state. Azobenzenes have garnered interest as potential anolytes for redox flow batteries. Here, we report the synthesis of a family of substituted azobenzene derivatives and evaluation of their solution-phase electrochemical properties. Systematic synthetic derivatization of this scaffold allows (1) access to anolytes of varying solubility, including intrinsically liquid derivatives that represent potential high-density charge carriers; (2) systematic variation of the reduction potential, and in some cases redox inventory, that provides azobenzenes with highly negative reduction potentials; and (3) control of the lifetime of the azobenzene radical anions that result from one-electron reduction. Electrokinetic experiments demonstrated that fast electron transfer occurs for all derivatives examined. Spectroscopic characterization of monoreduced azobenzene derivatives establishes that decomposition of the azobenzene radical anion proceeds via bimolecular disproportionation. Together, these results provide an experimental basis for the optimization of azobenzene anolytes for electrochemical storage applications, including redox flow batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Design and Optimization of the Direct Recycling of Spent Li-Ion Battery Cathode Materials

Direct regeneration of spent Li-ion batteries based on the hydrothermal relithiation of cathode materials is a promising next-generation recycling technology. In order to demonstrate the feasibility of this approach at a large scale, we systematically design and optimize the process parameters to minimize both energy and raw material costs. Specifically, the effects of regenerative processing parameters on the composition, structure, and electrochemical performance of the regenerated cathode materials are investigated via systematic characterization and testing. From this analysis, it was found that the raw material costs can be substantially reduced by either replacing the typically employed 4 M LiOH solution by a cost-effective mixture of 0.1 M LiOH and 3.9 M KOH or recycling of the concentrated 4 M LiOH for continuous relithiation processes. Finally, life cycle analysis suggests that this strategy results in reduced energy consumption and greenhouse gas emissions, leading to an increased potential revenue, particularly when compared with hydro- and pyrometallurgical recycling methods.

25 ENERGY STORAGE↗
DOE OSTI2026

Using Domain Insertion to Create Sulfite Reductases That Present Chemical-Dependent Activities

Domain insertion can be used to create oxidoreductases whose activities are dependent upon analyte binding. To date, most domain insertion studies have targeted relatively small oxidoreductases of known structure, so it remains unclear how to apply this protein engineering approach to large hetero-oligomeric proteins that require dynamic conformational changes for catalysis. To address this question, we studied the effects of peptide and domain insertions on the activity of NADPH-dependent sulfite reductase (SiR) from Escherichia coli, a dodecameric oxidoreductase containing four hemoprotein and eight flavoprotein subunits. SiR mutational tolerance was first evaluated using systematic octapeptide insertion and a cellular selection, which identified regions across the hemoprotein structure that retain parent-like activity following insertion. When a ligand-binding domain was inserted at backbone locations tolerant to peptide insertion, including sites proximal and distal from the intersubunit interfaces, ∼90% retained catalytic activity, and >50% presented activity that is regulated by an endocrine disruptor. With one domain insertion variant, the conditional production of sulfide could be monitored electrochemically from cells using a bioelectrochemical reactor. These results show how systematic peptide insertion can be used to inform domain insertion in a large heterooligomeric protein complex, and they illustrate how SiR can be engineered to convert chemical information in the environment into a redox-active metabolite that diffuses across the cell membrane.

bacteria↗
DOE OSTI2020

Size Transformation of the Au 22 (SG) 18 Nanocluster and Its Surface-Sensitive Kinetics

For many applications of well-defined gold nanoclusters, it is desirable to understand their structural evolution behavior under working conditions with molecular precision. Here we report the first systematic investigation of the size transformation products of the Au 22 (SG) 18 nanocluster under representative working conditions and highlight the surface effect on the transformation kinetics. Under thermal and aerobic conditions, the consecutive and pH-dependent transformation from Au 22 to both well-defined clusters and small Au(I)SR species was identified by ESI-MS and UV-vis spectroscopy. By introducing a perturbation onto the Au 22 surface, significant changes in the activation parameters were determined from the kinetic study of the Au 22 transformation. This indicates the sensitivity of the nanocluster transformation pathway to the cluster surface. Finally, the systematic study of cluster transformation and the sensitivity of cluster transformation to the surface revealed herein has significant implications for future attempts to design gold nanoparticles with adaptation to the working environment and the regeneration of active nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Mechanochemical Solid Form Screening of Zeolitic Imidazolate Frameworks Using Structure-Directing Liquid Additives

We demonstrate a systematic application of the mechanochemical liquid-assisted grinding (LAG) methodology to screen for forms of zinc imidazolate (ZnIm 2 ), of fundamental importance as the simplest member of the zeolitic imidazolate framework materials family. The exploration of 45 different liquid additives, selected based on their molecular structure and physicochemical properties has resulted in eight different ZnIm 2 topological forms, appearing in 13 crystallographically distinct solid forms (including two previously unknown forms of the crb (BCT) topology), amorphous phases, and the interrupted moc-Zn 4 Im 8 HIm. All prepared topological forms were also explored computationally, using dispersion-corrected periodic density functional theory (DFT) calculations, enabling the rationalization of screening outcomes, and setting the stage for future prediction of additive-directed metal–organic framework (MOF) synthesis. This first systematic exploration of LAG in screening for three-dimensional MOFs demonstrates the potential of the liquid additive to not only accelerate materials synthesis, but also to direct it toward topologically different MOFs. The discovery of novel forms of a material that already exhibits at least 21 crystallographically and functionally different forms provides a strong testimony on the power of mechanochemistry in metal–organic materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dimensional Reduction Guides Electronic Structure Evolution in the A n Cu 4–n SnS 4 Semiconductor Series

The search for new functional materials with tunable properties remains a central challenge in chemistry, particularly for applications in energy and electronics. In this work, we present a framework for predictive crystal design in alkali metal chalcogenides that enables controlled dimensional reduction of a parent covalent motif, yielding a broad range of electronic structures, which systematically evolve from one parent to the other. We present 11 new members of the A n Cu 4–n SnS 4 family (A = alkali metal; n = 0–4), which reduce the three-dimensional (3D) covalent network of Cu 4 SnS 4 into various 3D, 2D, 1D, and 0D [Cu 4–n SnS 4 ] n− motifs through the substitution of Cu with alkali metals of various radii. The end members of the family set the range in achievable band gaps at 0.99 eV for fully covalent Cu 4 SnS 4 (n = 0) and 3.38 eV for K 4 SnS 4 (n = 4) with 0D [SnS 4 ] n− tetrahedra. As the dimensionality of [Cu 4–n SnS 4 ] n− systematically reduces within A n Cu 4–n SnS 4 (n = 1–3), a stepwise increase in band gap energy occurs through a gradual decrease in the energy of the valence band maximum and an increase in the conduction band minimum, with an increase in the effective masses of charge carriers. Furthermore, irrespective of the alkali metal, the thermal stability decreases with decreasing [Cu 4–n SnS 4 ] n− dimensionality within the quaternary members. Most importantly, we demonstrate that predictable crystal structure and property evolution for a given composition space is possible by deriving a general formula based on substituting the covalent metals of a parent structure with alkali metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Compositional Phase Control in High-Entropy Alloy Electrocatalysts

High-entropy alloys (HEAs) provide uniquely tunable structural and electronic properties that enable robust electrocatalysis. While compositional manipulation of HEAs is well-known, systematically controlling the crystalline phase and morphology remains a challenge that could provide new avenues for controlling reactive sites and physical properties. Here, we show the preferential stabilization of mixed fcc/bcc to fcc phases by controlling the Au content in quinary AuPdFeCoNi HEA nanoparticles. This systematic structural and compositional control, when investigated with an ensemble of electronic, X-ray synchrotron, and surface techniques, allows us to identify the critical short- (few-Å) and medium- (6–10 Å) range structural motifs that deliver exceptional hydrogen evolution reaction (HER) catalysis. Specifically, these HEAs exhibit both outstanding durability (240 h) and high mass activity (50 A/mg PGM ) normalized to noble metal content, outperforming commercial Pt/C (3.18 A/mg PGM ). This structural control over HEA morphology, and its direct association with changes in specific metallic oxidation states and pair–pair atomic structural features, provides new means and strategies for finely designing robust and sustainable electrocatalysts with a majority nonprecious metal composition.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth’s atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently-developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next-generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process-level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Assessment of Global Positioning System Velocity Uncertainty in California

We analyze data from 580 continuous global positioning system (GPS) stations in California to quantify differences in published velocity estimates from five analysis centers. Horizontal and vertical rates for individual stations can differ up to 5 mm/yr, with systematic differences in some areas comparable to deformation rates. Published velocity uncertainties vary between analysis centers and are systematically underreported in the horizontal relative to empirical uncertainties calculated from the scatter of analysis center velocities. In the vertical, published velocity uncertainties are both over and underreported and vary more widely between centers. An interpolated ensemble vertical velocity field shows high-subsidence regions in the Central Valley and Salton Trough have the largest empirical uncertainties, while station density has a modest impact on uncertainties. Applications that rely on subcentimeter GPS accuracy should consider the possibility that formal errors published with velocity rate estimates understate true velocity uncertainties in both the horizontal and vertical.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Machine Learning Predicts the Timing and Shear Stress Evolution of Lab Earthquakes Using Active Seismic Monitoring of Fault Zone Processes

Abstract Machine learning (ML) techniques have become increasingly important in seismology and earthquake science. Lab‐based studies have used acoustic emission data to predict time‐to‐failure and stress state, and in a few cases, the same approach has been used for field data. However, the underlying physical mechanisms that allow lab earthquake prediction and seismic forecasting remain poorly resolved. Here, we address this knowledge gap by coupling active‐source seismic data, which probe asperity‐scale processes, with ML methods. We show that elastic waves passing through the lab fault zone contain information that can predict the full spectrum of labquakes from slow slip instabilities to highly aperiodic events. The ML methods utilize systematic changes in P‐wave amplitude and velocity to accurately predict the timing and shear stress during labquakes. The ML predictions improve in accuracy closer to fault failure, demonstrating that the predictive power of the ultrasonic signals improves as the fault approaches failure. Our results demonstrate that the relationship between the ultrasonic parameters and fault slip rate, and in turn, the systematically evolving real area of contact and asperity stiffness allow the gradient boosting algorithm to “learn” about the state of the fault and its proximity to failure. Broadly, our results demonstrate the utility of physics‐informed ML in forecasting the imminence of fault slip at the laboratory scale, which may have important implications for earthquake mechanics in nature.

58 GEOSCIENCES↗
DOE OSTI2021

A Guide to Using GitHub for Developing and Versioning Data Standards and Reporting Formats

Abstract Data standardization combined with descriptive metadata facilitate data reuse, which is the ultimate goal of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. Community data or metadata standards are increasingly created through an approach that emphasizes collaboration between various stakeholders. Such an approach requires platforms for collaboration on the development process that centers on sharing information and receiving feedback. Our objective in this study was to conduct a systematic review to identify data standards and reporting formats that use version control for developing data standards and to summarize common practices, particularly in earth and environmental sciences. Out of 108 data standards and reporting formats identified in our review, 32 used GitHub as the version control platform, and no other platforms were used. We found no universally accepted methodology for developing and publishing data standards. Many GitHub repositories did not use key features that could help developers to gather user feedback, or to create and revise standards that build on previous work. We provide guidance for community‐driven standard development and associated documentation on GitHub based on a systematic review of existing practices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Subtropical Eastern North Pacific SST bias in earth system models

Karthik Balaguru (PNNL), Luke Van Roekel (LLNL), L. Ruby Leung (PNNL) and Milena Veneziani (LLNL) Abstract: This study systematically evaluates the warm SST bias in the Subtropical Eastern North Pacific (SENP), a problem plaguing most CMIP6 models, using the Energy Exascale Earth System Model version 1 (E3SM). Compared to the model at its standard resolution (1o atmosphere, 30-60 km ocean), the SST bias improves in several regions at high resolution (0.25o atmosphere, 18-6 km ocean) except in subtropical eastern boundary regions, such as the SENP. A mixed layer heat budget analysis reveals that errors in the surface radiative fluxes and horizontal heat advection are primarily responsible for the bias. Analysis of HighResMIP models indicates that the lack of improvement in the SENP SST bias with resolution is not native to E3SM alone. A larger CMIP6 inter-model correlation of SST bias with biases in surface winds than radiation highlights the important role of large-scale circulation biases in the SENP SST bias in coupled models.

Balaguru, Karthik↗
DOE OSTI2021

Spectral Fidelity of Earth's Terrestrial and Aquatic Ecosystems

The Surface Biology and Geology (SBG) investigation will create global maps of spectral surface reflectance and emissivity at a cadence of 16 days or better, with coverage to address global questions about Earth's geology, cryosphere and ecosystems. The revolutionary potential poses a commensurate challenge: creating contiguous maps free from regional biases induced by atmosphere, observation geometry, or inversion error. This will require an accurate calibration with precise knowledge of each channel's spectral response. In this work, we quantify the impact of spectral calibration on SBG's aquatic and terrestrial ecosystem objectives. We find that contemporary algorithms for ecosystem trait retrieval demand more accurate spectral calibration than historical missions. Errors due to drift or spatial nonuniformity in the wavelength calibration that have previously been considered acceptable can cause systematic errors larger than the instrument noise and of the same order as the variability SBG aims to measure. Moreover, their impact on atmospheric correction can induce climate-dependent systematic errors that thwart comparisons between ecosystems. These results underscore the importance of spectral response accuracy in SBG mission design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Aridity-Dependent Land Surface Skin Temperature Biases in CMIP5/6

Land surface skin temperature, a critical indicator of climate change, connects the water and energy cycles between the land and the atmosphere. Here, in this study, we evaluate the simulations of land surface skin temperature from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6 models with satellite-based datasets and reanalysis. We find systematic cold skin temperature biases over arid regions in CMIP5/CMIP6 simulations. Over arid and semi-arid regions, latent heat biases drive skin temperature biases by evaporative cooling. Over humid regions, surface downward shortwave and albedo biases are relatively more critical. Spatial patterns of biases remain similar in the latest CMIP6 simulations, suggesting systematic biases in land-atmosphere interactions. These biases need to be corrected or considered while using models for future projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The High-Frequency Signature of Slow and Fast Laboratory Earthquakes

Tectonic faults fail through a spectrum of slip modes, ranging from slow aseismic creep to rapid slip during earthquakes. Understanding the seismic radiation emitted during these slip modes is key for advancing earthquake science and earthquake hazard assessment. In this work, we use laboratory friction experiments instrumented with ultrasonic sensors to document the seismic radiation properties of slow and fast laboratory earthquakes. Stick-slip experiments were conducted at a constant loading rate of 8 μm/s and the normal stress was systematically increased from 7 to 15 MPa. We produced a full spectrum of slip modes by modulating the loading stiffness in tandem with the fault zone normal stress. Acoustic emission data were recorded continuously at 5 MHz. We demonstrate that the full continuum of slip modes radiate measurable high-frequency energy between 100 and 500 kHz, including the slowest events that have peak fault slip rates <100 μm/s. The peak amplitude of the high-frequency time-domain signals scales systematically with fault slip velocity. Stable sliding experiments further support the connection between fault slip rate and high-frequency radiation. Experiments demonstrate that the origin of the high-frequency energy is fundamentally linked to changes in fault slip rate, shear strain, and breaking of contact junctions within the fault gouge. Our results suggest that having measurements close to the fault zone may be key for documenting seismic radiation properties and fully understanding the connection between different slip modes.

58 GEOSCIENCES↗
DOE OSTI2024

A Comprehensive Stress Drop Map From Trench to Depth in the Northern Chilean Subduction Zone

We compute stress drops for earthquakes in Northern Chile recorded between 2007 and 2021. By applying two analysis techniques, (a) the spectral ratio (SR) method and (b) the spectral decomposition (SDC) method, a stress drop map for the subduction zone consisting of 51,510 stress drop values is produced. We build an extended set of empirical Green’s functions (EGF) for the SR method by systematic template matching. Outputs are used to compare with results from the SDC approach, where we apply cell-wise obtained global EGF's to compensate for the structural heterogeneity of the subduction zone. We find a good consistency of results of the two methods. The increased spatial coverage and quantity of stress drop estimates from the SDC method facilitate a consistent stress drop mapping of the different seismotectonic domains. Albeit only small differences of median stress drop, strike-perpendicular depth sections clearly reveal systematic variations, with earthquakes at different seismotectonic locations exhibiting distinct values. In particular, interface seismicity is characterized by the lowest observed median value, whereas upper plate earthquakes show noticeably higher stress drop values. Intermediate depth earthquakes show comparatively high average stress drop and a rather strong depth-dependent increase of median stress drop. Additionally, we observe spatio-temporal variability of stress drops related to the occurrence of the two megathrust earthquakes in the study region. The presented study is the first coherent large scale 3D stress drop mapping of the Northern Chilean subduction zone. It provides an important component for further detailed analysis of the physics of earthquake ruptures.

58 GEOSCIENCES↗
DOE OSTI2024

Evaluating Cloud Feedback Components in Observations and Their Representation in Climate Models

This study quantifies the contribution of individual cloud feedbacks to the total short-term cloud feedback in satellite observations over the period 2002–2014 and evaluates how they are represented in climate models. The observed positive total cloud feedback is primarily due to positive high-cloud altitude, extratropical high- and low-cloud optical depth, and land cloud amount feedbacks partially offset by negative tropical marine low-cloud feedback. Seventeen models from the Atmosphere Model Intercomparison Project of the sixth Coupled Model Intercomparison Project are analyzed. The models generally reproduce the observed moderate positive short-term cloud feedback. However, compared to satellite estimates, the models are systematically high-biased in tropical marine low-cloud and land cloud amount feedbacks and systematically low-biased in high-cloud altitude and extratropical high- and low-cloud optical depth feedbacks. Errors in modeled short-term cloud feedback components identified in this analysis highlight the need for improvements in model simulations of the response of high clouds and tropical marine low clouds. Our results suggest that skill in simulating interannual cloud feedback components may not indicate skill in simulating long-term cloud feedback components.

58 GEOSCIENCES↗
DOE OSTI2023

Automated Symbolic Upscaling: 2. Model Generation for Extended Applicability Regimes

Abstract In this second part of the two paper series, we detail an algorithmic procedure for systematically implementing the generalized closure form strategy presented in Part 1. This strategy extends the applicability of homogenized models with respect to classical homogenization theory, as demonstrated in Part 1 where upscaled models are rigorously derived in moderately reactive physical regimes. After encoding the algorithm into Symbolica, an automated upscaling framework, we upscale two reactive mass transport problems and numerically validate the resulting nonlinear homogenized models by showing the absolute error estimates predicted by homogenization theory are satisfied. In both problems, nontrivial closure forms and closure problems are automatically formulated using the encoded strategy with no human interaction, nor prior knowledge regarding the closure required for the systems. We hope these demonstrations spark further interest in automated analytical frameworks for multiscale modeling, as such capabilities are invaluable for generating rigorous multiscale models of complex phenomena in porous media.

Pietrzyk, Kyle↗