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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

Atomate2: modular workflows for materials science

High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screening, property database generation, and training of “universal” machine learning models. While several software frameworks have emerged to support these computational efforts, new developments such as machine learned force fields have increased demands for more flexible and programmable workflow solutions. This manuscript introduces atomate2, a comprehensive evolution of our original atomate framework, designed to address existing limitations in computational materials research infrastructure. Key features include the support for multiple electronic structure packages and interoperability between them, along with generalizable workflows that can be written in an abstract form irrespective of the DFT package or machine learning force field used within them. Our hope is that atomate2's improved usability and extensibility can reduce technical barriers for high-throughput research workflows and facilitate the rapid adoption of emerging methods in computational material science.

97 MATHEMATICS AND COMPUTING↗

Thermal Conductivity Measurement of Microstructure in Irradiated Materials

Argonne National Laboratory is establishing additional capabilities for advanced techniques for accelerated experiment-based fuel material screening. A key supporting element is expanded capabilities for the characterization of irradiated samples, including establishment of the capability to measure irradiated fuel thermal conductivity at the micro-scale level. Argonne is collaborating with the University of Illinois at Urbana-Champaign (UIUC) to adopt the suspended bridge method to measure thermal conductivity of radiation-induced microstructures in nuclear materials directly. The initial phase of work to support thermal conductivity measurements of microstructure in irradiated materials at Argonne has been executed, and is summarized here. This report is intended to serve as a status update for this activity, summarizing work completed in FY20.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

From Design to Device: Challenges and Opportunities in Computational Discovery of p -Type Transparent Conductors

A high-performance p -type transparent conductor (TC) does not yet exist but could lead to advances in a wide range of optoelectronic applications and enable new architectures for, e.g., next-generation photovoltaic (PV) devices. High-throughput computational material screenings have been a promising approach to filter databases and identify new p -type TC candidates and some of these predictions have been experimentally validated. However, most of these predicted candidates do not have experimentally achieved properties on par with n -type TCs used in solar cells and therefore have not yet been used in commercial devices. Thus, there is still a significant divide between transforming predictions into results that are actually achievable in the laboratory and an even greater lag in scaling predicted materials into functional devices. In this perspective, we outline some of the major disconnects in this materials discovery process—from scaling computational predictions into synthesizable crystals and thin films in the laboratory to scaling laboratory-grown films into real-world solar devices—and share insights to inform future strategies for TC discovery and design. Published by the American Physical Society 2024

14 SOLAR ENERGY↗

Micro-photoluminescence mapping and Chemometrics for the rapid classification of rare earth materials

This article introduces advancements in chemically mapping rare earth materials using photoluminescence (PL) and chemometrics. By leveraging the high sensitivity and selectivity of PL compared to alternative optical techniques, as well as its compatibility with microscopy, we present enhanced capabilities for noninvasive material screening and characterization. Exemplary PL spectra of samarium(III) and europium(III) in oxide, nitrate, and chloride forms demonstrated the ability to extract detailed chemical information of diverse rare earth particles. Additionally, we introduced efficient PL mapping sequences capable of covering a 9 mm diameter carbon tab within minutes, which highlighted the benefits of rapid, large-area imaging. Furthermore, an integrated approach combining PL mapping with principal component analysis and a random forest classifier enabled the resolution of overlapping spectral peaks from different chemistries and provided accurate material classification. In conclusion, these advancements underscored the versatility and robustness of PL for chemically mapping rare earth materials, with the potential to support applications in mining, energy, environmental monitoring, isotope production and beyond.

Chemometrics↗

Entropy-defect synergy for dual luminescence mechanism in spinel: Time-resolved anti-counterfeiting and fingerprint visualization

Multimodal luminescent materials, while promising for anti-counterfeiting, often lack dynamic time-dependent responses and controllable spatial distribution, limiting their encryption capabilities in the spatiotemporal dimension. Here, this work presents a coordinated control strategy based on entropy and defect engineering, and uses a backpropagation (BP) neural network for material screening to successfully prepare spinel Mg 0.8 (Fe 0.04 Co 0.04 Ni 0.04 Cu 0.04 Zn 0.04 )Cr 2 O 4 (MgA 5 CO) phosphors with time-dependent dynamic luminescence behavior. This phosphor simultaneously activated the d-d transition luminescence (∼618 nm) derived from Co 2+ /Cr 3+ and the defect luminescence (∼398 nm) related to zinc vacancies (V Zn ) in a single-phase solid solution. The phosphor exhibits a time-dependent color evolution from pink to purple under fixed-wavelength excitation, due to the different excited-state dynamics and decay lifetimes associated with the d-d transition and defect luminescence. Structural characterization and spectral analysis confirmed the existence of V Zn and its significant role in defect luminescence process. The fluorescent and dynamic luminescent properties of entropy-based spinel oxide enable its use in advanced anti-counterfeiting applications like fingerprint recognition and color-changing dedicated anti-counterfeiting mark, showing promise in high-end and time-dynamic anti-counterfeiting fields. This research not only developed a new type of fluorescent dynamic anti-counterfeiting material, but also provided a new idea for constructing advanced optical functional materials with multiple luminescence mechanisms.

Defect project↗

Combining four-point bending and corrosion to map stress-dependent corrosion susceptibility of 316H stainless steel in FLiNaK

Understanding the effect of stress on the corrosion of steels in molten salts is important for material screening and safety assessment of molten salt reactors. We present a method that combines four-point bending with corrosion testing, enabling the mapping of corrosion susceptibility as a function of local stress from a single specimen. Guided by finite element analysis, a four-point bending setup was used to bend a 316H stainless-steel bar under controlled elastic stress during a 100-hour exposure in FLiNaK at 700 °C. Post-exposure characterization using scanning electron microscopy and energy-dispersive X-ray spectroscopy revealed a pronounced correlation between stress and corrosion. Regions under tensile stress exhibited significantly deeper attack depths and greater chromium depletion along grain boundaries, whereas compressive zones showed shallower corrosion cracks. The stress effect is attributed to stress concentration under tensile loading, which promotes chromium dissolution and crack propagation. This technique can be readily applied to other structural alloys, enabling quantitative measurement of corrosion susceptibility as a function of local stress.

316H↗

Exploring Structure-Sensitive Relations for Small Species Adsorption Using Machine Learning

Accurate prediction of adsorption energies on heterogeneous catalyst surfaces is crucial to predicting reactivity and screening materials. Adsorption linear scaling relations have been developed extensively but often lack accuracy and apply to one adsorbate and a single binding site type at a time. These facts undermine their ability to predict structure sensitivity and optimal catalyst structure. Using machine learning on nearly 300 density functional theory calculations, we demonstrate that generalized coordination number scaling relations hold well for oxygen- and high-valency carbon-binding species but fail for others. Here we reveal that the valency and the electronic coupling of a species with the surface, along with the site type and its coordination environment, are critical for small species adsorption. The model simultaneously predicts the adsorption energy and preferred site and significantly outperforms linear scalings in accuracy. It can expose the structure sensitivity of chemical reactions and enable enhanced catalyst activity via engineering particle shape and facet defects. The generality of our methodology is validated by training the model with transition metal data and transferring it to predict adsorption energies on single-atom alloys.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-performance ionomerless cathode anion-exchange membrane fuel cells with ultra-low-loading Ag–Pd alloy electrocatalysts

Rapid translation of catalysts from fundamental studies to high-performance devices could facilitate the process of developing and commercializing anion-exchange membrane fuel cells (AEMFCs). Traditionally, translation from material screening in three-electrode rotating disk electrode (RDE) cells to AEMFCs is complicated by differences in microenvironments, e.g. solid ionomer/membrane vs liquid electrolyte. Herein, we introduce a platform for translation to devices that utilizes ionomerless ultra-low-loading Ag-Pd alloy electrocatalyst cathodes synthesized by co-physical vapor deposition (PVD). Our ionomerless cathodes allow for systematic H 2 -O 2 AEMFC experiments while demonstrating comparable activity trends to those in three-electrode cells. Furthermore, here we show that our Ag 10 Pd 90 -based AEMFC reaches a peak power density of ~1 W cm$_{geo}^{-2}$ and ~10 W mg$_{PGM Cathode}^{-1}$ satisfying the U.S. Department of Energy’s platinum-group-metal (PGM) loading and cost targets. Our approach shows promise in facilitating the rapid translation between three-electrode studies and AEMFCs, offering a simple and effective design for decreasing PGM loadings.

25 ENERGY STORAGE↗

Toward a neutrino-limited dark matter search with crystalline xenon

Experiments searching for weakly interacting massive particle dark matter are now detecting background events from solar neutrino-electron scattering. However, the dominant radioactive background in state-of-the-art experiments such as LZ and XENONnT is beta decays from radon contamination. In spite of careful detector material screening, radon progenitor atoms are ubiquitous and long-lived, and radon is extremely soluble in liquid xenon. We propose a change of phase and demonstrate that crystalline xenon offers more than a factor × 500 exclusion against radon ingress, compared with the liquid state. This level of radon exclusion would allow crystallized versions of existing experiments to probe spin-independent cross sections near 10 − 47 cm 2 in roughly 11 years, as opposed to the 35 years required otherwise. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Assessing Electrolyte Fluorination Impact on Calendar Aging of Blended Silicon-Graphite Lithium-Ion Cells Using Potentiostatic Holds

Silicon-based lithium-ion batteries have started to meet cycle life metrics, but they exhibit poor calendar life. Here, electrolyte fluorination impact on calendar fade of blended silicon-graphite anodes is explored using a LiPF 6 in EC:EMC:FEC electrolyte vs LiBOB in EC:EMC electrolyte. We utilize a combined experimental-modeling approach applying potentiostatic voltage holds (V-hold) to evaluate electrolyte suitability for calendar life in a shortened testing timeframe (~2 months). Our theoretical framework deconvolutes the irreversible parasitic capacity losses (lithium lost to the solid electrolyte interphase) from the V-hold electrochemical data. Unfluorinated electrolyte (dominant LiBOB reduction) exhibits higher cell resistance as compared to fluorinated electrolyte (dominant FEC reduction). Both systems have similar irreversible capacities during the voltage hold duration with slower rate of parasitic capacity loss for the LiBOB system. Extrapolation of the parasitic losses to end of life capacity fade of 20% shows LiBOB electrolyte outperforming LiPF 6 electrolyte in calendar life. The results demonstrate the applicability of the V-hold protocol as a rapid material screening tool providing semi-quantitative calendar lifetime estimates.

25 ENERGY STORAGE↗

Charged point defect benchmark of Hybrid and GGA-PBE

Data used by the publication "High-throughput calculations of charged point defect properties with semi-local density functional theory - performance benchmarks for materials screening applications." This work presented an in-depth benchmark analysis of automated, semi-local point defect calculations with a-posteriori corrections, compared to 245 “gold standard” hybrid calculations previously published. We considered three different a-posteriori correction sets for semi-local calculations, implemented in a fully automated workflow, and consider the qualitative and quantitative differences for four different categories of defect information: thermodynamic transition levels, formation energies, fermi levels, and dopability limits. We highlighted the type of qualitative information about point defect properties that can be extracted from high-throughput calculations based on semi-local DFT methods, while also demonstrating the limits of quantitative accuracy that can be achieved by these approaches.

Broberg, Danny↗

Advanced Multi-Tube Mixer Combustion for 65% Efficiency (Final Report)

This project targeted advanced low NOx combustion for advanced gas turbines capable of 65%, or greater, efficiency in combined cycle application. This technology advancement has further potential to benefit gas turbines used in coal based IGCC applications with pre-combustion carbon capture and hydrogen as the resulting fuel. The program developed and synthesized the most advanced combustion system capable of achieving low NOX emissions up to turbine inlet temperatures of 3100F while also supporting the load-following needs of a modern grid. The combustion system contributes to the overall gas turbine efficiency goal by setting the maximum cycle temperature achievable for a given NOX level and by minimizing the through-combustor air flow pressure drop. Focus areas for this project targeted maximizing the turbine inlet temperature entitlement, as constrained by emissions considerations. The design also minimized parasitic air flow pressure drop by using advanced cooling techniques and performance materials selections and by minimizing hot surface area. These two technology objectives (maximum, emissions-compliant cycle temperature and minimum air flow pressure drop) were integrated into a prototype design. The primarily analytical project sought to identify the most promising technologies to meet these objectives. Additional critical “jugular” data were obtained from multi-tube mixer tests to realize the potential of leveraging “micro flames” for minimizing overall hot surface area. This data was used, in conjunction with an understanding of advanced material and cooling design technologies, to analytically develop multiple design concepts. Phase I focused on in-depth engineering analysis and design, with minimal supporting laboratory testing to enable a selection of the top three combustion architectures for achieving these overall objectives. Phase II of the program developed the selected design through a combination of sub-scale testing and analytical efforts. Early tests included a cold-flow cascade to establish aerodynamic performance characteristics and a sub-scale fired test at GE Global Research in Niskayuna, NY, to establish cooling and heat transfer characteristics in conjunction with combustion performance. The data from these tests validated the analytical models to ultimately design a full-scale, test article to evaluate at prototypical pressure and temperature conditions at GE Gas Power’s Gas Turbine Technology Laboratory in Greenville, SC. GE Gas Power also developed, tested, and recommended a suitable seal design to be applied to the unique features of the combustor. To assess the technology challenges from prospective future production of the combustor from a ceramic matrix composite material, screening tests of Environmental Barrier Coatings were completed.

20 FOSSIL-FUELED POWER PLANTS↗

Design Status and Experimental Strategy for Initial Molten Salt Irradiation Experiments in HFIR

The development and deployment of molten salt reactor (MSR) technologies require experimental capabilities that can evaluate molten fuel salt behavior and structural material performance under representative irradiation conditions. Although modeling and separate effects testing provide important insight, there remains a critical lack of in-pile data that capture the coupled effects of neutron irradiation, temperature, salt chemistry, and time. Informed by lessons learned from historical MSR programs and recent international irradiation efforts, this report presents a structured approach to addressing existing gaps in molten salt irradiation testing using the High Flux Isotope Reactor (HFIR). A phased irradiation strategy is presented that incrementally increases experimental complexity while managing cost, risk, and facility constraints. The framework progresses from passive, nonfueled static capsule experiments to fueled, instrumented, and ultimately circulating molten salt systems, providing a pathway for materials screening, mechanistic understanding, and qualification-relevant testing. The report defines a near-term Phase 1 passive capsule concept, associated irradiation conditions, and a conceptual post-irradiation examination strategy. Ongoing modeling, out-of-pile testing, and safety analysis activities are described to support continued capability maturation and to enable future phases of molten salt irradiation testing in support of MSR technology deployment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Rotating Disk Electrode Standardization and Best Practices in Acidic Oxygen Evolution for Low-Temperature Electrolysis

Efforts in oxygen evolution catalyst development have significantly increased and often use rotating disk electrode half-cells to evaluate intrinsic kinetics and screen materials for short-term durability. Standardizing rotating disk electrode test protocols is critical to experimental accuracy, to realistically assess their potential impact at a device level and to assess how different catalyst approaches and concepts are prioritized. The goal of this study is to provide standardized test protocols and suggest best practices to help reduce variability in ex situ materials characterization in the broader community. Specifically, these protocols focus on test cleanliness and materials choices, including how electrodes are prepared and tested, and the impact on activity observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Defect Thermodynamics and Transport Properties of Perovskite and Fluorite Materials for Solid-Oxide and Proton Conducting Oxide Cells Evaluated Based on Density Functional Theory Modeling

Density functional theory based defect thermodynamic modeling was performed to determine the effect of humidity and H2/O2 gas pressure on various defect chemistry and transport properties of perovskite and fluorite oxides for solid-oxide and proton-conducting-oxide cell applications, with inclusion of the electronic-conducting oxides (as electrodes) and insulating oxides (as electrolytes). Automatic defect generation workflow and first-principles charged defect analysis were implemented on NETL Joule supercomputer for modeling defect equilibria and transport properties of insulating oxides as electrolytes in SOCs and proton-conducting ceramic cells. A GNU Octave defect model subroutines were developed to facilitate defect modeling of electronic conducting oxides in a wide range of operating conditions guided by modeling and experiments. The model includes the hydride defect formation reaction under reducing conditions and allows to incorporate nonstoichiometry effects on the defect thermodynamic parameters. The developed model serves as a platform to facilitate fundamental understanding of the defect thermodynamics in SOC oxide materials and can be used as a novel tool in computational materials screening for SOC and other energy applications.

Lee, Yueh-Lin↗

Computational Approaches for Clean Energy Materials

Currently, 80% of the global final energy consumption occurs in form of fuels and only 20% as electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, a successful energy transition will require enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies. As much as photovoltaic capacities have grown over the past 20 years, it is far from clear that current technologies and materials are up to the task to grow from here by yet another factor 100 until 2050. Therefore, sustained research efforts on emerging inorganic semiconductors for solar electricity and fuels are essential for facing the double challenge of climate change and energy security. Computational materials science can make important contributions, guiding and supporting research activities through both materials search and discovery and through detailed studies that help to develop a mechanistic understanding of materials performance and bottlenecks. This presentation will highlight three recent computational projects with relevance for photovoltaics and solar fuels (1) Defect graph neural networks (dGNN) for materials discovery in solar thermochemical hydrogen (STCH) [1]. The dGNN approach facilitates broad and fast materials screening for defect properties. (2) Modeling highly off-stoichiometric systems by evaluating the free energy of defect interaction [2]. This approach allows quantitative prediction of H2 production in complex STCH oxides. (3) First-principles atomic structure prediction for interfaces [3]. This work showed how an atomically thin CdCl2 interlayer phase enables in principle ideal electron transport across the incommensurate SnO2/CdTe interface. [1] M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. (2023). https://doi.org/10.1038/s43588-023-00495-2. [2] A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024). https://doi.org/10.1103/PRXEnergy.3.013008. [3] A. Sharan, M. Nardone, D. Krasikov, N. Singh, S. Lany, Appl. Phys. Rev. 9, 041411 (2022). https://doi.org/10.1063/5.0104008.

density functional theory↗

DuraMAT FY24 Annual Report: Five Results to Help America's Photovoltaic Industry

The Durable Module Materials Consortium's overarching goal is to understand photovoltaic (PV) module degradation and enable high-energy-yield modules with a 50-year lifespan. One of DuraMAT's milestones this year was to identify cases where the whole of DuraMAT really mattered and made an impact that was greater than the sum of the project results. We identified five key results that demonstrate progress toward enabling 50-year modules for a resilient PV industry: 1) Resilient PV Systems; 2) Proactive Materials Screening; 3) Understanding Wear-Out; 4) Identifying Which Cracks Matter; and 5) Software Tools and Data Resources This annual report summarizes these key results, as well as reviewing our other ongoing work in fiscal year 2024.

14 SOLAR ENERGY↗