Search NASA⌕ Search

SEARCH · Search NASA

Results for “Mixing layer”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Role of Alkali-Metal Cations in Electronic Structure and Halide Segregation of Hybrid Perovskites

The ability to control or prevent phase segregation in perovskites is crucial to realizing stable and tunable mixed-halide optoelectronic devices. Here, we systematically examine the impact of alkali-metal-cation (Cs + and K + ) concentration on the band structure, chemical composition, phase segregation, and polycrystalline microstructure on formamidinium-dominated mixed-halide mixed-cation perovskite films. It was found that the incorporation of Cs + and K + cations decreases the work function and the core levels of all components shift toward higher binding energy consistent with n-doping the perovskite film, which facilitates electron transfer to the electron transport layer TiO 2 . A concentration-dependent film structure was observed by X-ray photoemission spectroscopy and grazing incidence wide-angle X-ray scattering where the halides and cations are distributed evenly across perovskite films at low metallic cation concentration (5%). A high metal-cation ratio (20%) leads to halide segregation within the perovskite film and the surface becomes bromide-poor, whereas the bromide and metal cations diffuse more deeply within the film. These differences in electronic properties, element distribution, and film morphology were reflected in the device performance where the power conversion efficiency of low-metallic-cation concentration (5% of Cs + and K + ) perovskite solar cells is ≈5% higher than the high-concentration ones (20%). This study provides valuable chemical and physical insight into the underlying trade-offs in the careful tuning of electrical properties and film structure to optimize multication and mixed-halide hybrid perovskites.

36 MATERIALS SCIENCE↗
DOE OSTI2025

SnSe 1-x S x Alloys: Anisotropic Van der Waals Semiconductors with Tunable Bandgaps

Alloying is one of the main tools of bandgap engineering, allowing the tuning of crystal structure, lattice parameters, and electronic structure of 3D and 2D/layered semiconductors. Among the latter, it can play a key role in tailoring the properties of tin monochalcogenides, a class of van der Waals semiconductors of interest for optoelectronics, thermoelectrics, ferroelectrics, and valleytronics. Here, the study investigates the synthesis and properties of large flakes of the anion substitution alloys SnSe 1-x S x . Alloy flakes across a wide range of compositions are obtained systematically by repeated growth from the same mixed (SnS, SnSe) powder precursor. Combined experiment and theory show full miscibility for all compositions, along with tunable lattice constants, bandgaps, and vibrational modes. Atomic resolution imaging demonstrates the accumulation of S and Se in alternating layers in the SnSe 1-x S x unit cell, attributed to growth kinetics. Polarized Raman spectroscopy confirms anisotropic vibrational modes; the calculated and measured band structure shows systematic changes in the band edge energies and anisotropic electronic structure due to the anisotropic in-plane lattice of the monochalcogenides. Cathodoluminescence, finally, indicates that a unique configuration of two non-degenerate, direct valleys along orthogonal k-space directions persists all the way from SnS to SnSe, making SnSe 1-x S x alloys interesting for valleytronics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Accelerating Laboratory-Based, All-Solid-State Battery Research and Development: Industrially Relevant Small-Batch Dry-Processing, Small and Low-Cost Test Fixtures, and Short-Tolerant Separators

This work presents improvements to mixing (for dry-processed electrodes), separator robustness, and cell testing jigs for all-solid-state batteries (ASSBs). These developments combine synergistically to enable rapid research and development of ASSB catholytes. A mechanical "kneader" is designed and built which emulates the mixing and fibrillation of poly-tetrafluoroethylene binder that occurs in industrially relevant twin-screw extruders. A modest improvement in the mixing and dispersion catholyte materials is observed using micro-resolution X-ray computed tomography (X-ray CT). Catholytes are paired with an In-metal anode and separated by a novel, dual-layer, polyaramid-fiber-supported, sulfide-solid electrolyte (Li6 PS5 Cl) separator. This separator achieves high short tolerance which enabled a 95% success rate across 20 attempted cells and to date over 100 successful cells have been built. ASSBs were tested in a 2032 coin-cell format. Simultaneous cycling of a large number of cells is further enabled by a compact and low cost (~ 38 USD per jig) pressure application jig of which 100 have been constructed to date. The utility of these advances is demonstrated through a brief study on the effect cathode-side conductive carbon and current collector type has on capacity and rate performance.

25 ENERGY STORAGE↗
DOE OSTI2024

Identifying point defects and ordering in the high-entropy layered oxide Li 1.5 MO 3-δ (M=Mn, Al, Fe, Co, Ni) for energy storage applications

High-entropy layered oxides (HELOs) represent a very promising class of next-generation battery cathodes, combining the well-studied properties of layered cathode materials such as LiCoO 2 with the chemical tunability and stability of high-entropy materials. HELO materials often form particles with complex defects and domain structures, complicating accurate characterization of structure and cation mixing. Understanding disorder and order in HELO materials is necessary for understanding their performance and utility as cathodes. Here we demonstrate the characterization of the HELO Li 1.5 MO 3-δ (M = Mn, Al, Fe, Co, Ni), wherein X-ray powder diffraction, transmission electron microscopy imaging, and electron diffraction patterns are analyzed to reveal the presence of ordering in the HELO, with imaging and diffraction simulation employed to compare experimental results to atomic modeling. Finally, without rigorous characterization at the atomic scale, important features such as defect ordering can be easily overlooked and therefore remain unconsidered when interpreting experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2026

HydraGNN_Predictive_GFM_2026 - Ensemble of predictive graph foundation models for atomistic materials modeling

This release contains data and parameters of HydraGNN-based graph foundation models trained as a result of the work published in the pre-print "Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic Data" by M. Lupo Pasini et al. (https://arxiv.org/abs/2604.15380). We jointly train on 16 open first-principles datasets (544+ million structures covering 85+ elements) using a multi-task architecture with per-dataset heads and a scalable ADIOS2/DDStore data pipeline. On Frontier, we execute six large-scale DeepHyper hyperparameter optimization campaigns in FP64 and promote the top-performing message-passing models to sustained 2,048-node training, yielding a PaiNN-based lead model. The version of HydraGNN used to generate the outputs provided in this release is HydraGNN v5.0 (https://github.com/ORNL/HydraGNN/releases/tag/v5.0) The list of datasets used for the training of the graph foundation model is the following: 1) Alexandria [1] 2) ANI1x [2] 3) MPTrj [3] 4) Open Catalyst 2020 (OC20) [4] 5) Open Catalyst 2022 (OC22) [5] 6) Open Catalyst 2025 (OC25) [6] 7) Open Direct ir Capture 2023 (ODAC23) [7] 8) Open Materials 2024 (OMat24) [8] 9) Open Molecules 2025 (OMol25) [9] 10) OMol25-neutral (subset of OMol25 that contains only molecules with zero total charge) 11) OMol25-non-neutral (subset of OMol25 that contains only molecules with non-zero total charge) 12) Open Polymers 2026 (OPoly2026) [10] 13) Nabla2DFT [11] 14) QCML [12] 15) QM7X [reference 13] 16) transition1x [14] Dataset references: [1] J. Schmidt et al., “A dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals,” Scientific Data, vol. 9, p. 64, 2022. [2] J. S. Smith et al., “The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules,” Scientific Data, vol. 7, p. 134, 2020. [Online]. Available: https: //www.nature.com/articles/s41597-020-0473-z [3] A. Jain et al., “Commentary: The Materials Project: A materials genome approach to accelerating materials innovation,” APL Materials, vol. 1, no. 1, p. 011002, 07 2013. [Online]. Available: https://doi.org/10.1063/1.4812323 [4] L. Chanussot et al., “Open catalyst 2020 (oc20) dataset and community challenges,” ACS Catalysis, vol. 11, no. 10, pp. 6059–6072, 2021. [Online]. Available: https://doi.org/10.1021/acscatal.0c04525 [5] K. Tran et al., “Open catalyst 2022 (oc22) dataset and challenges for oxidation electrocatalysts,” ACS Catalysis, vol. 13, no. 5, pp. 3066–3084, 2023. [Online]. Available: https://doi.org/10.1021/acscatal.2c05426 [6] S. J. Sahoo et al., “The open catalyst 2025 (oc25) dataset and models for solid-liquid interfaces,” arXiv preprint arXiv:2509.17862, 2025. [Online]. Available: https://arxiv.org/abs/2509.17862 [7] A. Sriram et al., “The open DAC 2023 dataset and challenges for sorbent discovery in direct air capture,” ACS Central Science, vol. 10, no. 5, pp. 923–941, 2024. [8] L. Barroso-Luque et al., “Open materials 2024 (omat24) inorganic materials dataset and models,” 2024. [Online]. Available: https://arxiv.org/abs/2410.12771 [9] D. S. Levine et al., “The open molecules 2025 (OMol25) dataset, evaluations, and models,” 2025. [Online]. Available: https://arxiv.org/abs/2505.08762 [10] D. S. Levine et al., The open polymers 2026 (OPoly26) dataset and evaluations,” arXiv preprint arXiv:2512.23117, 2025. [Online]. Available: https://arxiv.org/abs/2512.23117 [11] K. Khrabrov et al., “Nabla2dft: A universal quantum chemistry dataset of drug-like molecules and a benchmark for neural network potentials,” in NeurIPS 2024 Datasets and Benchmarks Track, 2024. [Online]. Available: https://openreview.net/forum?id=ElUrNM9U8c [12] S. Ganscha et al., “The QCML dataset, quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations,” Scientific Data, vol. 12, p. 406, 2025. [13] J. Hoja et al., “QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules,” Scientific Data, vol. 8, p. 43, 2021. [Online]. Available: https://www.nature.com/articles/s41597-021-00812-2 [14] M. Schreiner et al., “Transition1x - a dataset for building generalizable reactive machine learning potentials,” Scientific Data, vol. 9, p. 779, 2022. The folder "datasets_ADIOS2_format" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "datasets_ADIOS2_format" directory contains 2 sub-directories, one for the version "v1" of the datasets and one for the version "v2" of the datasets. The version "v1" of the datasets provides values of the total energy as they are extracted from the original data as it was released by the respective institutions. The version "v2" of the datasets provides values of the energy that have been realigned. The realignment was performed by training a linear regression model that predicts the total energy as a function of the chemical composition of the atomistic structure, and then subtract such prediction from the original value of the total energy. Both folders "v1" and "v2" contain 16 sub-directories, each corresponding to an ADIOS2-formatted dataset The folder "DeepHyper-results" contains the configurational files and model's parameters for all the 186 HPO trials that were successfully completed by the scalable hyperparameter optimization (HPO) runs on Frontier. The content of the folder "DeepHyper-results" I structured as follows: 1) task-list.txt: list of mpnn name, jobid, and deephyper task id 2) gfm_${MPNN}_${JOBID}_0.${TASKID}: run directory with checkpoint files 3) gfm_${MPNN}: deephyper summary directory (*.csv) for each specific MPNN type 4) deephyper-experiment-${JOBID}: output and error logs for each job The file "deephyper-sorted.csv" contains the details of each HydraGNN model built and tested by HPO, obtained by merging the (*.csv) filed from each HPO run executed. Out of all the HPO trials, we selected 10 to continue the training of the respective HydraGNN models. Due to limited computational budget available in the LRN070 allocation we could not complete the training till convergence for all these 10 selected models. The folder "models" contains multiple sub-folders, one per each HydraGNN model trained. Each model sub-folder contains the parameters of each HydraGNN model, with multiple checkpoint-restarts. The list of sub-folders are as follows: 1) multidataset_hpo-BEST1-fp64 2) multidataset_hpo-BEST2-fp64 3) multidataset_hpo-BEST3-fp64 4) multidataset_hpo-BEST4-fp64 5) multidataset_hpo-BEST5-fp64 6) multidataset_hpo-BEST6-fp64 7) multidataset_hpo-BEST7-fp64 8) multidataset_hpo-BEST8-fp64 9) multidataset_hpo-BEST9-fp64 10) multidataset_hpo-BEST10-fp64 Within each one of these folders, additional auxiliary log files are provided with descriptions about how the training proceeded. The lead PaiNN-model is contained inside "multidataset_hpo-BEST6-fp64". The file "mlp_branch_weights" contains the parameters of the multi-layer perceptron (MLP) used to reconcile the predictions of the 16 output decoding heads of the HydragNN architectures. The MLP takes in input the chemical composition of the atomistic structure and predicts averaging weights to linearly mix the predictions of each output decoding head toward consolidating them into a single one. The folder "1.1billion-structure-inference" contains 1.1 billion atomistic structures randomly generated. Each structures is associated with energy and forces predicted with the lead-PaiNN model combined with the MLP model for reconciliation of the multi-branch predictions generated by the 16 output decoding heads. The folder "1.1billion-structure-inference" contains 9,300 (*.tar.gz) subdirectories, one per Frontier compute node used to execute the inference at exascale. Once uncompressed, each (*.tar.gz) subdirectory contains an ADIOS2 (*.bp) file container, where each atomistic structure is stored as a PyTorch-Geometric Data object. The file "export_dataset_environment_variables.sh" contains the environment variables that need to be set before running the HydraGNN code to reproduce the results provided in this dataset release. The code that can be used to load the ADIOS2 files, load HydraGNN models, and run inference is available at: https://github.com/ORNL/HydraGNN/releases/tag/v5.0

36 MATERIALS SCIENCE↗
DOE OSTI2024

Additive Manufacturing of Thermal Energy Storage Composites with Microencapsulated Phase Change Materials Supported in a Multi-Polymer Matrix

Advanced manufacturing techniques, such as additive manufacturing (AM), that can directly integrate phase change materials (PCMs) have garnered interest in recent years due to their potential for development of highly efficient thermal energy storage architectures. Complex, high surface area geometries embedded with PCMs that are only feasible with AM can improve thermal management with reduced material waste. Our work focuses on developing composite filaments with microencapsulated phase change materials (MEPCM) bound within a single or dual polymer matrix that can be processed through standard filament extruders and additively manufactured using off-the-shelf 3D printers. Polymer powders, rather than polymer pellets, were key to homogenously mixed filaments achieving high MEPCM loadings with no deterioration in thermal energy storage (TES) capability during extrusion. Composite filaments contain upwards of 60 wt% MEPCM and were printed without loss in feature resolution, print speed, or layer adhesion. Storage enthalpies of printed composites range from 100 - 130 kJ/kg, which were within 5% of the theoretical enthalpy based on weight fraction of MEPCM and maintained enthalpies within 1% over 500 thermal cycles. We can reliably manufacture low density, high surface area structures like 15% gyroid infill, along with dense, compact pucks at a 100% concentric infill. Prints were also scalable to a 900 cm3 honeycomb infill heat exchanger model that has an estimated energy storage capacity of 9 Wh.

3D printing↗
DOE OSTI2024

Single Crystalline GeSe Van Der Waals Ribbons With Uniform Layer Stacking, High Carrier Mobility, and Adjustable Edge Morphology

Abstract Performance of the group IV monochalcogenide GeSe in solar cells, electronic, and optoelectronic devices is expected to improve when high‐quality single crystalline material is used rather than polycrystalline films. Crystalline flakes represent an attractive alternative to bulk single crystals as their synthesis may be developed to be scalable, faster, and with higher overall yield. However, large – and especially large and thin – single crystal flakes are notoriously hard to synthesize. Here it is demonstrated that vapor‐liquid‐solid growth combined with direct lateral vapor‐solid incorporation produces high‐quality single crystalline GeSe ribbons with tens of micrometers size and controllable thickness. Electron microscopy shows that the ribbons exhibit perfect equilibrium (AB) van der Waals stacking order without extended defects across the entire thickness, in contrast to the conventional case of substrate‐supported flakes where material is added via layer‐by‐layer nucleation and growth on the basal plane. Electrical measurements show anisotropic transport and a high Hall mobility of 85 cm 2 V −1 s −1 , on par with the best single crystals to date. Growth from mixed GeSe and SnSe vapors, finally, yields ribbons with unchanged structure and composition but with jagged edges, promising for applications that rely on ample chemically active edge sites, such as catalysis or photocatalysis.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Evaluating E3SM Global Storm‐Resolving Model Simulations of Deep Convection: Insights From DP‐SCREAM During TRACER

Global Storm-Resolving Models (GSRMs) are becoming increasingly vital for advancing climate modeling and improving the prediction of extreme weather events. Houston, a coastal region frequently affected by deep convective storms, offers an ideal setting to evaluate the ability of GSRMs to simulate deep convection. This study assesses the performance of the Doubly Periodic Simple Cloud-Resolving E3SM (Energy Exascale Earth System Model) Atmosphere Model (DP-SCREAM) using observations from the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. DP-SCREAM effectively reproduces the diurnal cycles of clouds and precipitation, demonstrating much greater skill than the E3SM single column model. The DP-SCREAM is demonstrated to be applicable to coastal regions, partially due to the forcing data sets already capturing the influence of breezes. DP-SCREAM also replicates biases persistent in the global version of SCREAM: the underrepresentation of boundary layer shallow clouds, a lack of mid-level congestus clouds, and the popcorn convection, characterized by small and disorganized convective cells generating the strongest precipitation. To investigate these issues, two sensitivity experiments were conducted: increasing the mixing length and scaling up the buoyancy flux within the Simplified Higher Order Closure scheme. Increasing the mixing length improved mid-level congestus representation and reduced unrealistic early morning fog occurrence. Enhancing buoyancy flux only marginally improved the bias of underproduced big convective cells. In conclusion, an additional resolution sensitivity test at 0.5 km grid spacing demonstrated that a refined horizontal resolution alone is insufficient to resolve these biases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

JWST Observations of Starbursts: Dust Processing in the M82 Superwind

We present JWST MIRI and NIRCam imaging of the inner ∼5 kpc of the M82 superwind at ~ $0''_{.}05 - 0''_{.}375$(∼0.9–6.5 pc) resolution. Targeted filters probe emission from polycyclic aromatic hydrocarbons (PAHs; F335M, F360M, F770W, F1130W) and continuum (F250M, F360M) The images reveal a network of cool wind filaments traced by PAHs. PAH surface brightness declines with the inverse square of distance to the midplane, suggesting that the incident radiation field from the starburst drives the observed PAH intensity out to ±2.5 kpc. The 3.3/11.3 and 3.3/7.7 μm band ratios show uniformity with distance from the starburst, though comparisons with mid-IR dust emission models indicate a modest shift toward larger PAHs. Outside the disk, 11.3/7.7 μm increases moderately, reflecting that PAHs become more neutral with distance from the starburst as they are exposed to a declining radiation field and ionization parameter. Overall, PAHs in the wind are consistent with standard-to-large sizes and standard-to-high ionization states. Including Spitzer and Herschel data, PAH abundance (q PAH ) is set at ∼1% in the starburst and remains unchanging out to ±5 kpc off the disk. This flat q PAH profile suggests that PAHs are shielded from the hot wind, perhaps residing in the surface layers of cool clouds, with possible replenishment from cloud interiors and enrichment of the halo from previous bursts. In this picture, clouds are not dense enough to promote PAH growth, and they likely undergo radiative cooling and mixing with the hot phase to survive the gauntlet for at least ∼20 Myr.

Cronin, Serena A. [University of Maryland, College↗
DOE OSTI2024

Atomically dispersed platinum-group metal-free catalysts and method for synthesis of the same

Atomically dispersed platinum-group metal-free catalyst and method for synthesizing the same. According to one embodiment, the catalyst is made by a method in which, in a first step, a metal oxide/zeolitic imidazolate frameworks (ZIF) composite is formed by combining (i) nanoparticles of an oxide of at least one of iron, cobalt, nickel, manganese, and copper, (ii) a hydrated zinc salt, and (iii) an imidazole. Then, in a second step, the metal oxide/ZIF composite is thermally activated, i.e., carbonized, to form an M-N—C catalyst. Thereafter, the M-N—C catalyst may be mixed with a quantity of ammonium chloride, and then the M-N—C/NH 4 Cl mixture may be pyrolyzed. The foregoing NH 4 Cl treatment may improve the intrinsic activity of the catalyst. Then, a thin layer of nitrogen-doped carbon may be added to NH 4 Cl-treated M-N—C catalyst by chemical vapor deposition (CVD). Such CVD treatment may improve the stability of the catalyst.

Wu, Gang↗
DOE OSTI2020

Phase diagram of infinite layer praseodymium nickelate Pr 1– x Sr x NiO 2 thin films

In this paper, we report the phase diagram of infinite layer Pr 1-x Sr x NiO 2 thin films synthesized via topotactic reduction from the perovskite precursor phase using CaH 2 . Based on the electrical transport properties, we find a doping-dependent superconducting dome extending between x = 0.12 and 0.28, with a maximum superconducting transition temperature T c of 14 K at x = 0.18, bounded by weakly insulating behavior on both sides. In contrast to the narrower dome observed in Nd 1–x Sr x NiO 2 , a local T c suppression near x = 0.2 was not observed for the Pr 1-x Sr x NiO 2 system. Normal state Hall effect measurements indicate mixed carrier contributions of both electrons and holes, and show a sign change in the Hall coefficient as functions of temperature and x, quite similar to that in Nd 1-x Sr x NiO 2 . Also similar is the observation of a minimum in the normal state resistivity associated with the superconducting compositions. These findings indicate an infinite layer nickelate phase diagram that is relatively insensitive to the rare-earth element, but suggest that disorder arising from the variations of the ionic radii on the rare-earth site affects the superconducting dome.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optical Properties of Individual Tar Balls in the Free Troposphere

Tar balls are brown carbonaceous particles, highly viscous, spherical, amorphous, and light absorbing. They are believed to form in biomass burning smoke plumes during transport in the troposphere. Tar balls are believed to have a significant impact on the Earth’s radiative balance, but due to poorly characterized optical properties, this impact is highly uncertain. Here, we investigate the chemical composition and optical properties of individual tar balls transported in the free troposphere to the Climate Observatory “Ottavio Vittori” on Mt. Cimone, Italy (2165 meters above sea level) using multi-modal micro-spectroscopy. Our results show that tar balls contributed 50% of carbonaceous particles by number in the size range from 0.25 to 1.8 µm. Of those tar balls, 16% were inhomogeneously mixed with other constituents. Using electron energy loss spectroscopy, we retrieved the complex refractive index from 200 to 1200 nm for both inhomogeneously and homogeneously mixed tar balls. We found no significant difference in the average refractive index of inhomogeneously and homogenously mixed tar balls (1.40 - 0.03i, and 1.36 - 0.03i at 550 nm, respectively). Furthermore, we estimated the top of the atmosphere radiative forcing using the Santa Barbara DISORT Atmospheric Radiative Transfer model (SBDART) and found that a layer of only tar balls with an optical depth of 0.1 above vegetation would exert a positive radiative forcing ranging from 2.8 Wm-2 (on a clear sky day) to 9.5 Wm-2 (when clouds are below the aerosol layer). In conclusion, understanding the optical properties of tar balls can help reduce uncertainties associated with the contribution of biomass-burning aerosol in current climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Complex Phase Transitions of Fully Rigid Sphere–Rod Amphiphiles Induced by Solvent Polarity in Dilute Solutions

Here we report complex macrophase and microphase transitions of rigid amphiphiles with spherical Keggin molecular clusters as the solvophilic block and rod-like rigid oligofluorene (OF) as the solvophobic block in mixed solvents of water and polar organic solvent. By properly adjusting the solvent polarity, the amphiphiles are found to respond accordingly by self-assembling into multilayered incomplete onion-like structures (10–25 vol % THF), single-layered vesicular structures (60 vol % THF), and an unexpected macrophase separation in the middle (40–50 vol % THF), which is due to the anomalous trends in Keggin solubility as a result of the nature of TBA + counterions. The rigidity of the OF block prevents the amphiphile from assembling by following the rule of packing parameters; instead, interdigitation among different rods leads to the formation of the solvophobic domain to achieve self-assembly. The incomplete onion structures are controlled by the interdigitation of rigid rods for the number of layers and the electrostatic interaction among Keggin head groups for the interlayer distance. When the degree of interdigitation becomes lower, the self-assembly process shows a trend that can be explained by the traditional rule of packing parameter. This study demonstrates the formation of different self-assembled structures by rigid amphiphiles and their transitions induced by solvent composition. The self-assembly (microphase separation) of rigid amphiphiles in a dilute solution could indeed represent a broad area containing complicated, uncharted rules.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A discussion on various experimental methods of impact ionization coefficient measurement in GaN

Impact ionization coefficients play a critical role in semiconductors. In addition to silicon, silicon carbide and gallium nitride are important semiconductors that are being seen more as mainstream semiconductor technologies. As a reflection of the maturity of these semiconductors, predictive modeling has become essential to device and circuit designers, and impact ionization coefficients play a key role here. Recently, several studies have measured impact ionization coefficients. We dedicated the first part of our study to comparing three experimental methods to estimate impact ionization coefficients in GaN, which are all based on photomultiplication but feature characteristic differences. The first method inserts an InGaN hole-injection layer, the accuracy of which is challenged by the dominance of ionization in InGaN, leading to possible overestimation of the coefficients. The second method utilizes the Franz–Keldysh effect for hole injection but not for electrons, where the mixed injection of induced carriers would require a margin of error. The third method uses complementary p–n and n–p structures that have been at the basis of this estimation in Si and SiC and leans on the assumption of a constant electric field, and any deviation would require a margin of error. In the second part of our study, we evaluated the models using recent experimental data from diodes demonstrating avalanche breakdown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Bond Synergy Model for Bond Energies in Alloy Oxides

In this work we introduce a metal-oxide bond-energy model for alloy oxides based on pure-phase bond energies and bond synergy factors that describe the effect of alloying on the bond energy between cations and oxygen, an important quantity to understand the formation of alloy oxides and their composition. This model is parameterized for binary cation-alloy oxides using density-functional theory energies and is shown to be directly transferable to multi-component alloy oxides. We parameterized the model for alloy oxide energies with metal cations that form the basis of corrosion resistant alloys, including Fe, Ni, Cr, Mo, Mn, W, Co, and Ru. We find that isoelectronic solutes allow quantification of pure-phase bond energies in oxides and the calculated bond energy values give sensible results compared to common experience, including the role of Cr as the passive-layer former in Fe–Ni–Cr alloys for corrosion applications. Additionally, the bond synergy factors give insights into the mutual strengthening and weakening effects of alloying on cation-oxygen bonds and can be related to enthalpy of mixing and charge neutrality constraints. We demonstrate how charge neutrality can be identified and achieved by the oxidation states that the different cations assume depending on alloy composition and the presence of defects.

Electrochemistry↗
DOE OSTI2024

On the Geometry of the Near-core Magnetic Field in Massive Stars

It is well-known that the cores of massive stars sustain a stellar dynamo with a complex magnetic field configuration. However, the same cannot be said for the field's strength and geometry at the convective–radiative boundary, which are crucial when performing asteroseismic inference. In this Letter, we present 3D magnetohydrodynamic (MHD) simulations of a 7 M ⊙ mid-main-sequence star, with particular attention given to the convective–radiative boundary in the near-core region. Our simulations reveal that the toroidal magnetic field is significantly stronger than the poloidal field in this region, contrary to recent assumptions. Moreover, the rotational shear layer, also important for asteroseismic inference, is specifically confined within the extent of the Brunt–Väisälä frequency peak. These results, which are based on the inferred properties of HD 43317, have widespread implications for asteroseismic studies of rotation, mixing, and magnetism in stars. While we expect our results to be broadly applicable across stars with similar Brunt–Väisälä frequency profiles and stellar masses, we also expect the MHD parameters (e.g., Re m ) and the initial stellar rotation rate to impact the geometry of the field and differential rotation at the convective–radiative interface.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Geometric frustration of Jahn–Teller order in the infinite-layer lattice

The Jahn–Teller effect, in which electronic configurations with energetically degenerate orbitals induce lattice distortions to lift this degeneracy, has a key role in many symmetry-lowering crystal deformations. Lattices of Jahn–Teller ions can induce a cooperative distortion, as exemplified by LaMnO 3 . Although many examples occur in octahedrally or tetrahedrally coordinated transition metal oxides due to their high orbital degeneracy, this effect has yet to be manifested for square-planar anion coordination, as found in infinite-layer copper, nickel, iron and manganese oxides. Here, for this work, we synthesize single-crystal CaCoO 2 thin films by topotactic reduction of the brownmillerite CaCoO 2.5 phase. We observe a markedly distorted infinite-layer structure, with ångström-scale displacements of the cations from their high-symmetry positions. This can be understood to originate from the Jahn–Teller degeneracy of the d xz and d yz orbitals in the d 7 electronic configuration along with substantial ligand–transition metal mixing. A complex pattern of distortions arises in a $2\sqrt2$ x $2\sqrt2$ x $1$ tetragonal supercell, reflecting the competition between an ordered Jahn–Teller effect on the CoO 2 sublattice and the geometric frustration of the associated displacements of the Ca sublattice, which are strongly coupled in the absence of apical oxygen. As a result of this competition, the CaCoO 2 structure forms an extended two-in–two-out type of Co distortion following ‘ice rules’.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗