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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The role of oxygen in automotive grade lithium-ion battery cathodes: an atomistic survey of ageing

The rising demand for high-performance lithium-ion batteries, pivotal to electric transportation, hinges on key materials like the Ni-rich layered oxide LiNi x Co y Al z O 2 (NCA) used in cathodes. The present study investigates the redox mechanisms, with particular focus on the role of oxygen in commercial NCA electrodes, both fresh and aged under various conditions (aged cells have performed >900 cycles until a cathode capacity retention of ~80%). Our findings reveal that oxygen participates in charge compensation during NCA delithiation, both through changes in transition metal (TM)–O bond hybridization and formation of partially reversible O 2 , the latter occurs already below 3.8 V vs. Li/Li + . Aged NCA material undergoes more significant changes in TM–O bond hybridization when cycling above 50% SoC, while reversible O 2 formation is maintained. Nickel is found to be redox active throughout the entire delithiation and shows a more classical oxidation state change during cycling with smaller changes in the Ni–O hybridization. By contrast, Co redox activity relies on a stronger change in Co–O hybridization, with only smaller Co oxidation state changes. The Ni–O bond displays an almost twice as large change in its bond length on cycling as the Co–O bond. The Ni–O 6 octahedra are similar in size to the Co–O 6 octahedra in the delithiated state, but are larger in the lithiated state, a size difference that increases with battery ageing. These contrasting redox activities are reflected directly in structural changes. The NCA material exhibits the formation of nanopores upon ageing, and a possible connection to oxygen redox activity is discussed. The difference in interaction of Ni and Co with oxygen provides a key understanding of the mechanism and the electrochemical instability of Ni-rich layered transition metal oxide electrodes. Our research specifically highlights the significance of the role of oxygen in the electrochemical performance of electric-vehicle-grade NCA electrodes, offering important insights for the creation of next-generation long-lived lithium-ion batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Unifying thermochemistry concepts in computational heterogeneous catalysis

Thermophysical properties of adsorbates and gas-phase species define the free energy landscape of heterogeneously catalyzed processes and are pivotal for an atomistic understanding of the catalyst performance. These thermophysical properties, such as the free energy or the enthalpy, are typically derived from density functional theory (DFT) calculations. Enthalpies are species-interdependent properties that are only meaningful when referenced to other species. The widespread use of DFT has led to a proliferation of new energetic data in the literature and databases. However, there is a lack of consistency in how DFT data is referenced and how the associated enthalpies or free energies are stored and reported, leading to challenges in reproducing or utilizing the results of prior work. Additionally, DFT suffers from exchange–correlation errors that often require corrections to align the data with other global thermochemical networks, which are not always clearly documented or explained. In this review, we introduce a set of consistent terminology and definitions, review existing approaches, and unify the techniques using the framework of linear algebra. This set of terminology and tools facilitates the correction and alignment of energies between different data formats and sources, promoting the sharing and reuse of ab initio data. Standardization of thermochemistry concepts in computational heterogeneous catalysis reduces computational cost and enhances fundamental understanding of catalytic processes, which will accelerate the computational design of optimally performing catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry for the creation and optimization of electrocatalysts, which enhance key electrochemical reactions like the hydrogen evolution reaction (HER), the oxygen evolution reaction (OER), the hydrogen oxidation reaction (HOR), and the oxygen reduction reaction (ORR). This comprehensive review demonstrates how cutting-edge ML techniques are being leveraged in electrocatalyst design to overcome the time-consuming limitations of traditional approaches. ML methods, using experimental data from high-throughput experiments and computational data from simulations such as density functional theory (DFT), readily identify complex correlations between electrocatalyst performance and key material descriptors. Leveraging its unparalleled speed and accuracy, ML has facilitated the discovery of novel candidates and the improvement of known products through its pattern recognition capabilities. This review aims to provide a tailored breakdown of ML applications in a format that is readily accessible to materials scientists. Hence, we comprehensively organize ML-driven research by commonly studied material types for different electrochemical reactions to illustrate how ML adeptly navigates the complex landscape of descriptors for these scenarios. We further highlight ML's critical role in the future discovery and development of electrocatalysts for hydrogen energy transformation. Potential challenges and gaps to fill within this focused domain are also discussed. As a practical guide, we hope this work will bridge the gap between communities and encourage novel paradigms in electrocatalysis research, aiming for more effective and sustainable energy solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

rNets: a standalone package to visualize reaction networks

In the study of chemical processes, visualizing reaction networks is pivotal for identifying crucial compounds and transformations. Traditional methods, such as network schematics and reaction path linear plots, often struggle to effectively represent complex reaction networks due to their size and intricate connectivity. Alternatives capable of leading with complexity include graph methods, but they are not user-friendly, lacking simplicity and modularity, which hinders their integration with widely-used research software. This work introduces rNets an innovative tool designed for the efficient visualization of reaction networks with a user-friendly interface, modularity, and seamless integration with existing software packages. The effectiveness of rNets is demonstrated through its application in analyzing three catalytic reactions, showcasing its potential to significantly enhance research both in homogeneous and heterogeneous catalysis fields. This tool not only simplifies the visualization process but also opens new avenues for exploring complex reaction networks in diverse research contexts.

Pablo-García, Sergio↗
DOE OSTI2024

Structural regulation-induced Li-electron disentanglement for stabilized oxygen redox of Li-excess disordered rock-salt cathode materials

Since the discovery of its electrochemical activity, Li-excess disordered rock-salt (DRX) cathode material has received worldwide attention as it sets up a new way to exploit oxygen redox beyond the conventional layered structure with late-3d transition metals. However, the intricate structure-function relationship in the disordered lattice of the DRX material fogs the researcher's lens on the underlying redox mechanisms. Here, in this study, we employ a synergistic approach combining neutron total scattering with reverse Monte Carlo modeling and density functional theory calculations to unravel the landscape of oxygen redox reactions in DRX. Redox activities are evaluated in diverse oxygen clusters (OLi x TM 6-x ) and the spatial distribution of these clusters in the model DRX structure (Li 1.16 Ti 0.37 Ni 0.37 Nb 0.1 O 2 and Li 1.2 Ti 0.35 Ni 0.35 Nb 0.1 O 1.8 F 0.2 ) is explicitly determined. The results unveil that by regulating the short-range ordering between cations, fluorine atoms can effectively decouple the location of Li extraction and electron depletion. Such disentanglement between the Li reservoir and electron reservoir in the DRX lattice could play a pivotal role in protecting the oxidized oxygen and preserving the lattice framework during cycling. Through a tentatively designed non-fluorinated DRX oxide realizing similar Li-electron decoupling, an obvious enhancement of the cycling capability can be achieved without compromising the capacity release.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Finding a needle in a haystack: quantitative HERFD-XRF imaging and HERFD-XANES characterization of trace platinum in gold solidi from the Late Roman and Byzantine Empires

High-Energy Resolution Fluorescence Detection X-Ray Fluorescence (HERFD-XRF) imaging and HERFD X-ray Absorption Near Edge Structure (XANES) spectroscopy are used to quantify and characterize trace platinum (Pt) in gold solidi from the Late Roman and Byzantine Empires. Historically, the elemental analysis of coins has been pivotal in distinguishing authentic artifacts from forgeries, elucidating minting practices, and understanding economic shifts. Notably, a new gold source with high platinum content appeared in the fourth century CE, transforming the Roman economy. Traditional methods struggled to detect platinum due to the overwhelming gold matrix. Here, this study demonstrates the effectiveness of HERFD techniques in resolving this challenge. Three gold solidi, minted between 654 and 659 CE, were analyzed alongside reference gold materials with known Pt concentrations. The HERFD-XRF imaging revealed spatial distributions of platinum, highlighting non-uniformities within the coins. Additionally, HERFD-XANES spectroscopy identified the oxidation states and chemical speciation of platinum. Results demonstrate that platinum in the solidi primarily exists as metallic Pt, with some surface oxidation. The findings align with previous measurements but reveal higher Pt concentrations and significant inhomogeneities. This research confirms the reliability of HERFD methods for quantifying trace elements and provides new insights into the raw material sources and minting techniques of ancient gold coins. The non-destructive nature of this approach allows for extensive analyses, offering valuable data for historical, economic, and archaeological studies. This innovative application of HERFD-XRF imaging and XANES in cultural heritage research underscores the potential for detailed material characterization and conservation, enhancing our understanding of ancient economies and trade patterns.

Van Loon, Lisa L.↗
DOE OSTI2024

Highly efficient semi-hydrogenation in strained ultrathin PdCu shell and the atomic deciphering for the unlocking of activity-selectivity

Excellent ethylene selectivity in acetylene semi-hydrogenation is often obtained at the expense of activity. To break the activity-selectivity trade-off, precise control and in-depth understanding of the three-dimensional atomic structure of surfacial active sites are crucial. Here, we designed a novel Au@PdCu core–shell nanocatalyst featuring diluted and stretched Pd sites on the ultrathin shell (1.6 nm), which showed excellent reactivity and selectivity, with 100% acetylene conversion and 92.4% ethylene selectivity at 122 °C, and the corresponding activity was 3.3 times higher than that of the PdCu alloy. The atomic three-dimensional decoding for the activity-selectivity balance was revealed by combining pair distribution function (PDF) and reverse Monte Carlo simulation (RMC). The results demonstrate that a large number of active sites with a low coordination number of Pd–Pd pairs and an average 3.25% tensile strain are distributed on the surface of the nanocatalyst, which perform a pivotal function in the simultaneous improvement of hydrogenation activity and ethylene selectivity. Our work not only develops a novel strategy for unlocking the linear scaling relation in heterogeneous catalysis but also provides a paradigm for atomic 3D understanding of lattice strain in core–shell nanocatalysts.

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

Dielectric constant engineering of nonfullerene acceptors enables a record fill factor of 83.58% and a high efficiency of 20.80% in organic solar cells

Organic solar cells (OSCs) have achieved power conversion efficiencies (PCEs) surpassing 20%, but their development remains hindered by the inherently low dielectric constant (εr) of organic semiconductors, which limits charge transport and contributes to serious recombination losses. Herein, we present a comprehensive strategy to overcome the challenge by engineering the dielectric properties of nonfullerene acceptors (NFAs). Two Y-series NFAs of BTP-N3F and BTP-C3F have been synthesized featuring trifluoromethyl (CF 3 ) end-capped alkyl side chains. This molecular design significantly enhances the dipole moment and ε r (up to ∼5.9) when compared to the reference acceptor Y6 (∼3), reducing the exciton binding energy (E b ) and improving charge transport. Furthermore, the incorporation of a high-εr polymer additive, poly(pentafluorostyrene) (PPFS), synergistically improves the active layer morphology and dielectric properties, enabling efficient charge extraction and reduced recombination losses. Devices based on the optimized D18-Cl/BTP-C3F system have achieved a record-high fill factor (FF) of 83.58% and an impressive PCE of 20.80%, setting a new benchmark for OSCs. Finally, our results underscore the pivotal role of ε r in enhancing device performance and establish a versatile pathway for advancing OSC efficiency and stability through molecular and morphological optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rigid cationic ligands enable high-efficiency NIR-II photoluminescence in copper( i ) iodide hybrid semiconductors

Near-infrared (NIR) luminescent materials are pivotal for advanced optoelectronic and biomedical applications, yet attaining efficient emission in the NIR-II region (950-1400 nm) remains challenging. Here, we introduce a ligand cationization strategy for designing copper(i) iodide-organic hybrid materials that emit in the NIR-II region (920-1120 nm) with PLQYs up to 8.58%. By incorporating rigid cationic ligands with CuI modules, we synergistically achieve bandgap narrowing (to 1.51 eV) and structural rigidification via ionic-dative bonding, effectively suppressing non-radiative decay while extending emission beyond 1100 nm. Coupled with solution processability-enabled by the successful synthesis of nanometer-sized nanoparticles in various shapes-and excellent thermal stability (≥210 °C), this work establishes ligand cationization as a universal approach for designing efficient NIR-II emitters.

Chen, Jingwen↗
DOE OSTI2020

X-ray spectral and flux variability of the microquasar GRS 1758-258 on timescales from weeks to years

We present the spectral and timing evolution of the persistent black hole X-ray binary GRS 1758-258 based on almost 12 years of observations using the Rossi X-ray Timing Explorer Proportional Counter Array. While the source was predominantly found in the hard state during this time, it entered the thermally dominated soft state seven times. In the soft state GRS 1758-258 shows a strong decline in flux above 3 keV rather than the pivoting flux around 10 keV more commonly shown by black hole transients. In its 3–20 keV hardness intensity diagram, GRS 1758-258 shows a hysteresis of hard and soft state fluxes typical for transient sources in outburst. The RXTE-PCA and RXTE-ASM long-term light curves do not show any orbital modulations in the range of 2–30 d. However, in the dynamic power spectra significant peaks drift between 18.47 and 18.04 d for the PCA data, while less significant signatures between 19 d and 20 d are seen for the ASM data as well as for the Swift/BAT data. We discuss different models for the hysteresis behavior during state transitions as well as possibilities for the origin of the long term variation in the context of a warped accretion disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Streaming Readout and Data-Stream Processing With ERSAP

With the exponential growth in the volume and complexity of data generated at high-energy physics and nuclear physics research facilities, there is an imperative demand for innovative strategies to process this data in real or near-real-time. Given the surge in the requirement for high-performance computing, it becomes pivotal to reassess the adaptability of current data processing architectures in integrating new technologies and managing streaming data. This paper introduces the ERSAP framework, a modern solution that synergizes flow-based programming with the reactive actor model, paving the way for distributed, reactive, and high performance in data stream processing applications. Additionally, we unveil a novel algorithm focused on time-based clustering and event identification in data streams. The efficacy of this approach is further exemplified through the data-stream processing outcomes obtained from the recent beam tests of the EIC prototype calorimeter at DESY.

Vardan, Gyurjyan↗
DOE OSTI2025

Strong Electromagnetic Fields in Heavy Ion Collisions

Photons play a pivotal role in both theoretical and applied physics, ranging from elementary particle studies to practical technologies. This article explores how ultra-peripheral collisions of heavy ions act as sources of nearly real photons, enabling the investigation of a wide range of photon-induced processes. By applying the equivalent photon approximation, one can study nuclear structure, QED phenomena, and potential new physics, all in a backgroundsuppressed environment.

Bertulani, C. A. [East Texas A & M Univ., Commerce↗
DOE OSTI2022

Employing Technology to Enable Remote Research Charrettes as a Method for Engaging Industry and Uncovering Best Practices: A Novel Approach for a Post-COVID-19 World

Methods to collect data in construction engineering and management (CEM) research are evolving, informed by recent technological advancements. One such method is research charrettes that allow effective interactions and knowledge sharing between expert industry practitioners and academic researchers, all colocated in a single venue, enabling rich data collection and live communication. A pivot point in technological evolution occurred with the COVID-19 pandemic, forcing a global shift to remote work. Hence, planned in-person research charrettes had to shift to remote sessions, relying on virtual conferencing platforms and online data collection mechanisms. Technology-enabled charrettes have allowed the authors to collect significantly richer data sets and ensure a more diverse representation of participants, while saving tremendous amounts of time. With the continuing emergence of technological applications, the world might not go back to functioning fully in person. The authors believe remote research charrettes (RRCs) will still be used in a post-COVID-19 world because of their superior performance. This paper builds on a previous publication that described traditional research charrettes as a method to enhance CEM research a decade ago; it offers a significantly updated and improved RRC method based on the knowledge gained from transitioning a dozen in-person charrettes into RRCs. It also presents performance comparisons between RRCs and traditional charrettes by quantifying metrics indicating how RRCs are more time-efficient and cost-saving, harness more participants from more diverse locations, and enable the collection of richer data sets and four times more industry comments and expert feedback. This paper also provides guidance on the integration of technology with traditional research charrettes, hence contributing to the CEM body of knowledge.

42 ENGINEERING↗
DOE OSTI2024

Generalized Relationship Linking Water Balance and Vegetation Productivity across Site-to-Regional Scales

Evapotranspiration (ET) is a pivotal component in catchment-scale water balance and is essential for informed watershed management. Nevertheless, uncertainties in ET observation or modeling have been hindering effective water resources management. This study addresses this gap by establishing a robust, generalized linear relationship between ET and gross primary productivity (GPP) at the catchment scale. We test the linearity of the relationships between monthly GPP and ET data at 380 near-natural catchments across various climatic and landscape conditions in the contiguous U.S., yielding Pearson’s r ≥ 0.6 for 97% of the 380 catchments. We then develop a regionalization strategy to parameterize this GPP-ET relationship at the catchment scale by identifying and utilizing the linkages between the parameter values and extensively available hydroclimatic and landscape data. We demonstrate the efficacy of the proposed GPP-ET relationship and parameter regionalization strategy by their combined predictive capacity, where the predicted monthly GPP matches well with remote-sensing-based GPP product, achieving Kling-Gupta Efficient (KGE) values ≥ 0.5 for 92% of the catchments. In addition, we verify the relationship and its parameter regionalization at 35 AmeriFlux sites with KGE ≥ 0.5 for 25 sites, suggesting that the new relationship is transferable across the site, catchment, and regional scales. Furthermore, our findings are valuable for improving remote-sensing-based estimation of monthly ET and diagnosing coupled water–carbon simulations in land surface and Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Liquid-phase mega-electron-volt ultrafast electron diffraction

The conversion of light into usable chemical and mechanical energy is pivotal to several biological and chemical processes, many of which occur in solution. To understand the structure–function relationships mediating these processes, a technique with high spatial and temporal resolutions is required. Here, we report on the design and commissioning of a liquid-phase mega-electron-volt (MeV) ultrafast electron diffraction instrument for the study of structural dynamics in solution. Limitations posed by the shallow penetration depth of electrons and the resulting information loss due to multiple scattering and the technical challenge of delivering liquids to vacuum were overcome through the use of MeV electrons and a gas-accelerated thin liquid sheet jet. To demonstrate the capabilities of this instrument, the structure of water and its network were resolved up to the 3rd hydration shell with a spatial resolution of 0.6 Å; preliminary time-resolved experiments demonstrated a temporal resolution of 200 fs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Analytic model of electron transport through and over non-linear barriers

Tunneling barriers are an essential component of electron sources, sensors, detectors, and vacuum nanoelectronics, and a pivotal factor in their performance, but the barriers themselves routinely depart from the analytic models used to model their behavior. Here, a new formalism is developed to analytically and accurately model emission through and over barriers associated with depletion layers, nanotip barriers, and MIM structures. The transmission probability for depletion layer and metal-insulator-metal (MIM) and metaloxide-semiconductor (MOS) barriers is accurately modeled as the electron energy exceeds the barrier height using approaches designed for rapid implementation demanded by simulation codes, and extensible to general barriers. The models supersede conventional thermal and field models in depletion and MIM/MOS barrier studies. Thermal-field methods are used to treat the transmission probability, and shape factor methods to treat the tunneling factor. Analytic formulae for current density are obtained. The methods ease device simulation and characterization of current-voltage relations for emerging technologically interesting barriers with better accuracy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗