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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 199 records · Page 11

Electrical and Spectroscopic Diagnostics as Real‐Time Metallization Indicators During Hydrogen Plasma Smelting Reduction

This study investigates the hydrogen (H 2 ) plasma reduction process of direct-reduced-iron-grade hematite ore at different arc currents (100–200 A) in an Ar–5% H 2 atmosphere at 0.9 bar. Iron ore samples (10 g) were exposed to a plasma arc, and the reduction/metallization kinetics were analyzed over fixed time intervals. Electrical diagnostics revealed that the arc voltage exhibited takeover-mode oscillations which were suppressed at higher currents due to stronger electromagnetic coupling. The voltage dropped significantly as metallization approached ∼95%, linked to increased electrical conductivity of the metallic iron (Fe) in the ore as well as Fe evaporation into the arc, lowering the arc resistance. A simplified Elenbaas–Heller model supported this explanation and confirmed that Fe vapor concentration enhances plasma conductivity. Optical emission spectroscopy focused on the plasma–metal interface revealed the plasma's optically thick nature, as the primary Fe I 526.95 nm line experienced self-absorption. However, weaker Fe I lines (404.58, 438.35 nm) normalized to Ar I 696.5 nm provided a reliable proxy for metallization. These diagnostics, electrical and spectroscopic, effectively track metallization in real-time during H 2 plasma smelting reduction.

08 HYDROGEN↗

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Structural Diversity and Magnetic Properties of Hybrid Ruthenium Halide Perovskites and Related Compounds

Abstract There has been a great deal of recent interest in extended compounds containing Ru 3+ and Ru 4+ in light of their range of unusual physical properties. Many of these properties are displayed in compounds with the perovskite and related structures. Here we report an array of structurally diverse hybrid ruthenium halide perovskites and related compounds: MA 2 Ru X 6 ( X =Cl or Br), MA 2 M RuX 6 ( M =Na, K or Ag; X =Cl or Br) and MA 3 Ru 2 X 9 ( X =Br) based upon the use of methylammonium (MA=CH 3 NH 3 + ) on the perovskite A site. The compounds MA 2 Ru X 6 with Ru 4+ crystallize in the trigonal space group and can be described as vacancy‐ordered double‐perovskites. The ordered compounds MA 2 M Ru X 6 with M + and Ru 3+ crystallize in a structure related to BaNiO 3 with alternating MX 6 and Ru X 6 face‐shared octahedra forming linear chains in the trigonal space group. The compound MA 3 Ru 2 Br 9 crystallizes in the orthorhombic Cmcm space group and displays pairs of face‐sharing octahedra forming isolated Ru 2 Br 9 moieties with very short Ru–Ru contacts of 2.789 Å. The structural details, including the role of hydrogen bonding and dimensionality, as well as the optical and magnetic properties of these compounds are described. The magnetic behavior of all three classes of compounds is influenced by spin–orbit coupling and their temperature‐dependent behavior has been compared with the predictions of the appropriate Kotani models.

Vishnoi, Pratap↗

Chemical Control of Spin‐Orbit Coupling and Charge Transfer in Vacancy‐Ordered Ruthenium(IV) Halide Perovskites

Abstract Vacancy‐ordered double perovskites are attracting significant attention due to their chemical diversity and interesting optoelectronic properties. With a view to understanding both the optical and magnetic properties of these compounds, two series of Ru IV halides are presented; A 2 RuCl 6 and A 2 RuBr 6 , where A is K, NH 4 , Rb or Cs. We show that the optical properties and spin‐orbit coupling (SOC) behavior can be tuned through changing the A cation and the halide. Within a series, the energy of the ligand‐to‐metal charge transfer increases as the unit cell expands with the larger A cation, and the band gaps are higher for the respective chlorides than for the bromides. The magnetic moments of the systems are temperature dependent due to a non‐magnetic ground state with J eff =0 caused by SOC. Ru‐ X covalency, and consequently, the delocalization of metal d ‐electrons, result in systematic trends of the SOC constants due to variations in the A cation and the halide anion.

Vishnoi, Pratap↗

Structural Diversity and Magnetic Properties of Hybrid Ruthenium Halide Perovskites and Related Compounds

There has been a great deal of recent interest in extended compounds containing Ru 3+ and Ru 4+ in light of their range of unusual physical properties. Many of these properties are displayed in compounds with the perovskite and related structures. Here we report an array of structurally diverse hybrid ruthenium halide perovskites and related compounds: MA 2 RuX 6 (X=Cl or Br), MA 2 MRuX 6 (M=Na, K or Ag; X=Cl or Br) and MA 3 Ru 2 X 9 (X=Br) based upon the use of methylammonium (MA=CH 3 NH 3 + ) on the perovskite A site. The compounds MA 2 RuX 6 with Ru 4+ crystallize in the trigonal space group R3¯m and can be described as vacancy-ordered double-perovskites. The ordered compounds MA 2 MRuX 6 with M + and Ru 3+ crystallize in a structure related to BaNiO 3 with alternating MX 6 and RuX 6 face-shared octahedra forming linear chains in the trigonal P3¯m space group. The compound MA 3 Ru 2 Br 9 crystallizes in the orthorhombic Cmcm space group and displays pairs of face-sharing octahedra forming isolated Ru 2 Br 9 moieties with very short Ru–Ru contacts of 2.789 Å. The structural details, including the role of hydrogen bonding and dimensionality, as well as the optical and magnetic properties of these compounds are described. The magnetic behavior of all three classes of compounds is influenced by spin–orbit coupling and their temperature-dependent behavior has been compared with the predictions of the appropriate Kotani models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molten Salts-Driven Discovery of a Polar Mixed-Anion 3D Framework at the Nanoscale: Zn 4 Si 2 O 7 Cl 2 , Charge Transport and Photoelectrocatalytic Water Splitting

Mixed-anion compounds widen the chemical space of attainable materials compared to single anionic compounds, but the exploration of their structural diversity is limited by common synthetic paths. Especially, oxychlorides rely mainly on layered structures, which suffer from low stability during photo(electro)catalytic processes. Herein we report a strategy to design a new polar 3D tetrahedral framework with composition Zn 4 Si 2 O 7 Cl 2 . We use a molten salt medium to enable low temperature crystallization of nanowires of this new compound, by relying on tetrahedral building units present in the melt to build the connectivity of the oxychloride. These units are combined with silicon-based connectors from a non-oxidic Zintl phase to enable precise tuning of the oxygen content. This structure brings high chemical and thermal stability, as well as strongly anisotropic hole mobility along the polar axis. These features, associated with the ability to adjust the transport properties by doping, enable to tune water splitting properties for photoelectrocatalytic H 2 evolution and water oxidation. This work then paves the way to a new family of mixed-anion solids

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elusive Double Perovskite Iodides: Structural, Optical, and Magnetic Properties

Halide double perovskites [A 2 M I M III X 6 ] are an important class of materials that have garnered substantial interest as non-toxic alternatives to conventional lead iodide perovskites for optoelectronic applications. While numerous studies have examined chloride and bromide double perovskites, reports of iodide double perovskites are rare, and their definitive structural characterization has not been reported. Predictive models have aided us here in the synthesis and characterization of five iodide double perovskites of general formula Cs 2 NaLnI 6 (Ln=Ce, Nd, Gd, Tb, Dy). Finally, the complete crystal structures, structural phase transitions, optical, photoluminescent, and magnetic properties of these compounds are reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strong, Yet Split Hydrogen Bonding with Ice Rules in Delafossite (H/D)RhO 2

Despite remaining enigmatic, strong hydrogen bonding provides an advanced design handle for tailoring the properties of functional materials. Here, in this study, 3 R –(H/D)RhO 2 delafossites (prepared by ion exchange of Na + from NaRhO 2 ) contain H/D in linear coordination with O, linking Rh III O 2 layers. Bragg and real-space X-ray and neutron scattering analysis, vibrational and solid-state NMR spectroscopy, and density functional theory (DFT)–based electronic structure calculations have been employed to understand the nature of the hydrogen bonding. Despite short distances between H/D and the two O to which they are bonded, a clear double-minimum corresponding to a shorter and longer (H/D)–O distance is established. The triangular lattices formed by H/D appear to display ice-like disorder, corroborated by low-temperature heat capacity measurements.

NMR spectroscopy↗

Iodide Double Perovskites and the Limits of their Structural Stability

AbstractWhile halide double perovskites A2M(I)M(III)X6 have attracted significant attention, examples involving iodides are rare. We examine the limits of the structural stability of iodide double perovskites, presenting the synthesis and single‐crystal structures of Cs2NaScI6 and Cs2NaYI6. Bypassing the common expectation that iodides have small band gaps, these compounds display optical gaps of 3.10 eV [M(III) = Sc] and 3.65 eV [M(III) = Y]. Cs2NaScI6 is the only iodide double perovskite to exhibit a cubic crystal structure at room temperature. Density functional theory‐based electronic structure calculations help understand the role of competing Cs3M(III)2I9 (3 : 2 : 9) phases and provide possible reasons for why iodide double perovskites based around In(III), Sb(III) and Bi(III) cations have proved elusive. We confirm design rules for halide double perovskites based around concepts of the tolerance factor and the radius ratio of the smaller, trivalent ion, but also point to situations such as what is observed for Cs2NaScI6 where a double perovskite can be trapped in a metastable structure.

Mulligan, Anya S.↗

Directly Fused Porphyrin‐Tetracyanopentacenequinone Conjugates: Role of the Cross‐Conjugated, Powerful Electron Acceptor in Promoting Highly Efficient Charge Separation

Tetracyanopentacenequinone, a powerful electron acceptor, is fused directly to the porphyrin π-system to create a new class of donor-acceptor conjugates. Owing to the direct fusion and electron-deficient property of tetracyanopentacenequinone, strong intramolecular charge transfer both in the ground and excited states was witnessed. As a control, porphyrin fused with pentacenequinone was also investigated. Upon complete spectral and electrochemical characterization, the excited state properties were initially probed by time-dependent DFT studies, and the occurrence of electron transfer from different excited states was established. Free-energy calculations revealed higher exothermic electron transfer (>600 mV) than the control pentacenequinone-porphyrin systems. Pump-probe studies covering broad spatial and temporal regions revealed efficient excited state charge separation. This was unlike the control pentacenequinone-porphyrin system, where slow charge separation was witnessed only in the case of the zinc derivatives but not the free-base ones, followed by the populating of the triplet excited state. The lifetimes of the charge-separated states ranged between 30–500 ps depending on the solvent and metal ion in the porphyrin cavity. Nanosecond transient absorption studies established the charge recombination path to populate the triplet state of porphyrin or directly to the ground state as a function of solvent polarity and the nature of the conjugate. Furthermore, the significance of cross-conjugated tetracyanopentacenequinone fused directly to the porphyrin π system in promoting highly exothermic and efficient charge separation, irrespective of its cross conjugation, is borne out from this study.

Cross conjugation↗

Chemical Recycling Processes of Waste Polyethylene Terephthalate Using Solid Catalysts

Polyethylene terephthalate (PET) is a non-degradable single-use plastic and a major component of plastic waste in landfills. Chemical recycling is one of the most widely adopted methods to transform post-consumer PET into PET's building block chemicals. Non-catalytic depolymerization of PET is very slow and requires high temperatures and/or pressures. Recent advancements in the field of material science and catalysis have delivered several innovative strategies to promote PET depolymerization under mild reaction conditions. Particularly, heterogeneous catalysts assisted depolymerization of post-consumer PET to monomers and other value-added chemicals is the most industrially compatible method. Here, this review includes current progresses on the heterogeneously catalyzed chemical recycling of PET. It describes four key pathways for PET depolymerization including, glycolysis, pyrolysis, alcoholysis, and reductive depolymerization. The catalyst function, active sites and structure-activity correlations are briefly outlined in each section. An outlook for future development is also presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In‐situ Analysis of Paste Properties in Resonant Acoustic Mixers for Quality Monitoring

Formulation control is key to achieving consistent target properties of energetic materials, as feedstock variations and slight deviations in the ratios of different ingredients can have major effects on final product properties, particularly in dense pastes with high particle loading >65 vol.%. In large‐scale operations, it is imperative to either correct or remove batches of material that perform outside baseline property specifications as early as possible to avoid unnecessary processing of suboptimal material. Quality monitoring is the practice of measuring material properties during processing using process analytical technologies as opposed to only testing the properties of the final product; it is a key principle in the quality‐by‐design frameworks used for designing formulations and manufacturing processes. Herein, a process analytical technology method for correlating material properties of dense pastes directly after mixing in a Resonant Acoustic Mixer to motor data is developed and used to detect differences in the particle content of dense paste formulations. This method was also capable of detecting variations in powder feedstock properties, such as particle packing efficiency, and is sensitive enough to detect changes of 2 wt.% in the total solids content of the formulation. The techniques presented herein show excellent promise for use as a process analytical technology capable of quantifying formulation effects on material movement modes during resonant acoustic mixing.

Materials science↗

First of Their Kind: Solar Cells with a Dry-Processed Perovskite Absorber Layer via Powder Aerosol Deposition and Hot-Pressing

Preparing halide perovskite films by solvent-free, powder-based processing approaches currently attracts more and more attention. However, working solar cells employing dry, powder-based halide perovskite thin films, have not been demonstrated so far. Herein, perovskite solar cells are presented where the absorber layer is prepared by transferring readily synthesized perovskite powders into a compact thin film using a fully dry-powder-processing concept. Compact thin films are deposited via an optimized powder aerosol deposition (PAD) process. Pressing at 120 °C further improves the morphology and the optoelectronic film properties. Integrating the perovskite films in a solar cell configuration results in fully working devices, with champion power conversion efficiencies of >6%. While the (optoelectronic) properties of the PAD-processed films are found to be comparable with their solution-processed counterparts, investigations of the solar cell stack suggest deterioration of the electron-transport layer properties due to the PAD process, and the presence of hydrates at the perovskite surface to be important factors that contribute to the limited solar cell efficiency. Herein, perspectives to overcome the identified limitations are outlined, emphasizing the high potential and realizability of efficient perovskite solar cells based on dry-powder-processing approaches in the future.

14 SOLAR ENERGY↗

Mathematical Foundation for Quantum Computing of Electromagnetic Wave Propagation in Dielectric Media

Can quantum computers effectively simulate the propagation and scattering of electromagnetic waves in a classical plasma? This chapter introduces some of the basic concepts in mathematics and physics essential to answering that question. The numerical simulations of Maxwell equations for wave propagation in dielectrics are constrained by technological limitations of the present-day computers. In contrast, there has been ample fanfare around quantum computers and their potential to far exceed the performance of traditional computers. Whether the enhanced capabilities of a quantum computer can be put to use for simulating topics in classical physics is a source of intrigue and curiosity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas

Regional hydroclimatic variability and change can affect water resources and hydropower generation. It is essential to assess hydropower potential under current and future climatic conditions to inform the design and operation of hydropower infrastructures. Here, we employ an integrated modeling framework to assess the impact of projected hydroclimatic conditions on water resource systems and hydropower generation. The integrated framework samples climate model outputs under different scenarios to force a hydrologic model and produces streamflow projections. The projected streamflows are inputs for the future hydropower potential assessment. We implement the framework in the central Himalayan river basin. Our results demonstrate substantial spatiotemporal variability in different water balance components (precipitation, evapotranspiration, and water yield) under current and future climatic conditions. For the Himalayan Tila river basin, the annual average energy production is expected to increase under future hydroclimatic conditions (up to 39% in Tila-2 hydropower project, suggested by ensemble mean). Furthermore, this increase in energy is driven mainly by the increased streamflow projections, particularly during the dry season and in the late century. Our results highlight the impacts of hydroclimatic variability in hydropower productions and are of practical use to provide decision-relevant information for designing and operating hydropower infrastructures. The integrated modeling framework presented here is region-specific; however, the approach is reproducible, and the overall insights are generalizable across the Himalayan region.

54 ENVIRONMENTAL SCIENCES↗

Finite Element Analysis and Machine Learning Guided Design of Carbon Fiber Organosheet-Based Battery Enclosures for Crashworthiness

Carbon fiber composite can be a potential candidate for replacing metal-based battery enclosures of current electric vehicles (E.V.s) owing to its better strength-to-weight ratio and corrosion resistance. However, the strength of carbon fiber-based structures depends on several parameters that should be carefully chosen. Here, in this work, we implemented high throughput finite element analysis (FEA) based thermoforming simulation to virtually manufacture the battery enclosure using different design and processing parameters. Subsequently, we performed virtual crash simulations to mimic a side pole crash to evaluate the crashworthiness of the battery enclosures. This high throughput crash simulation dataset was utilized to build predictive models to understand the crashworthiness of an unknown set. Our machine learning (ML) models showed excellent performance (R 2 > 0.97) in predicting the crashworthiness metrics, i.e., crush load efficiency, absorbed energy, intrusion, and maximum deceleration during a crash. We believe that this FEA-ML work framework will be helpful in down select process parameters for carbon fiber-based component design and can be transferrable to other manufacturing technologies.

36 MATERIALS SCIENCE↗

Monte Carlo Simulations of 347H Stainless Steel Aging for the Synthetic Generation of Microstructures Under Creep Conditions

Here, a Monte Carlo simulation method capable of replicating the kinetics of M 23 C 6 precipitation in 347H stainless steels was developed for the purpose of producing synthetic microstructures that approximate its microstructural evolution under aging periods of up to 10,000 hours at temperatures between 600 °C and 750 °C. To accomplish this, experimental data from the literature was used to parameterize simulations and replicate the nucleation and growth kinetics of M 23 C 6 particles within 347H and similar austenitic stainless steel alloys. These simulations were found to have considerable fidelity to previous efforts to study the precipitation of M 23 C 6 in other 300 series stainless steel alloys. Synthetic 347H microstructures were then generated that accounted the effects of aging temperature, duration, dislocation density, and the presence of boron within the microstructure. These simulations predict several key trends, those being that (1) the size of M 23 C 6 precipitates decreased with aging temperature and (2) the growth rate of M 23 C 6 particles decreased with aging temperature. Further, while (3) the addition of dislocation density due to creep conditions resulted in increasing intragranular nucleation of M 23 C 6 precipitates with increasing dislocation density and (4) B additions within the microstructure led to modest increases in precipitate size above 700 °C, which indicates that more complex physics are necessary to account for the presence of B.

36 MATERIALS SCIENCE↗

Data Science Techniques, Assumptions, and Challenges in Alloy Clustering and Property Prediction

Data analytics methods have been increasingly applied to understanding materials chemistry, processing due to the manufacturing approach, and uni-axial and cyclic property relationships in the highly complex space of alloy design. There are several benefits to applying data analytics to this space, including the ability to manage non-linearities in the responses of the alloy attributes and the resulting mechanical properties. However, key difficulties in applying and understanding the results of data analytics include the often lack of reported assumptions and data processing steps necessary to improve interpretation and reproducibility in derived results. In this work, the methods used to generate clustering and correlation analyses for experimental 9% Cr ferritic-martensitic steel data were investigated and the resulting implications for mechanical property predictions were assessed. This work uses principal component analysis, partitioning around medoids, t-SNE, and k-means clustering to investigate trends in composition, processing and microstructure information with creep and tensile properties, building on work done previously using a smaller version of the same dataset. The initial assumptions, preprocessing steps and methods are investigated and outlined in order to depict the fine level of detail required to convey the steps taken to process data and produce analytical results. Here, the variations in the resulting analyses are explored due to the influence of new and more varied data.

36 MATERIALS SCIENCE↗