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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Itinerant ferromagnetism in van der Waals Fe 5 – x Ge Te 2 crystals above room temperature

Two-dimensional (2D) van der Waals (vdW) magnets have recently attracted increasing attention, as they provide a novel system for exploring 2D magnetism. However, intrinsic ferromagnetism in 2D systems has almost exclusively been observed at low temperatures, limiting their technological relevance. Fe N Ge Te 2 ( N = 3 , 4, and 5) systems are currently becoming the most attractive 2D vdW materials due to their relatively high Curie temperatures and large saturation magnetization. However, the nature of their complex yet intriguing magnetic behaviors is still unclear, in part due to the multiple inequivalent iron sites and iron vacancies. In this study, we show evolution of magnetic ordering transitions in Fe 5 – x Ge Te 2 with high Curie temperature and a strong saturation magnetization using photoemission electron microscopy and transport measurements. At 275 K, the ferromagnet transitions to a ferrimagnet, and below 110 K transitions to a state with glassy clusters. These are evidenced from temperature-dependent magnetic stripe domain evolution and anisotropic magnetoresistance measurements. Our findings show a clear magnetic ground state of Fe 5 – x Ge Te 2 at room temperature which signals that Fe 5 – x Ge Te 2 system is a very promising candidate for spintronic devices and provides a material design pathway to further increase the Curie temperature and saturation moments in vdW ferromagnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Superconductivity Reinforces Charge-Density-Wave Phase Coherence across Cuprates

For decades, superconductivity in high-𝑇 c cuprates has been viewed as a competitor that suppresses charge-density-wave (CDW) order by reducing its amplitude and spatial extent. Here, in this study, we show that this picture is incomplete, as superconductivity is accompanied by a systematic enhancement of CDW phase coherence across multiple cuprate families. Using resonant soft x-ray scattering combined with a coherence-sensitive momentum-profile analysis, we uncover a BCS-like growth of phase coherence below 𝑇 c , which phenomenologically manifests as the absence of CDW peak broadening and near-perfect wave-vector locking. This enhancement remains visible even in a disorder-dominated regime created by long-term crystal aging and follows a common trend when compared with published data on Bi-, Hg-, Y-, and Nd-based cuprates. These results indicate that superconductivity reshapes CDW order in two distinct ways, suppressing its amplitude while strengthening its phase coherence, and reveal an additional phase-level interplay with lattice coupling in high-𝑇 c cuprates.

Lee, H. [SLAC National Accelerator Laboratory (SLA↗
DOE OSTI2025

Simulated effect of defect volume and location on very high cycle fatigue of laser beam powder bed fused AlSi10Mg

This study quantifies the interaction between volumetric defect location and size on the very high cycle fatigue (VHCF) of laser beam powder bed fused (LB-PBF) AlSi10Mg. Crystal plasticity finite element method (CPFEM) simulations were used to investigate the effects of defect location and size on the driving force for crack initiation. The CPFEM model was calibrated against uniaxial and cyclic experimental data of LB-PBF AlSi10Mg. Defect characteristics were informed by experimental data from the specimens produced in various geometries to create realistic representative volume elements (RVEs) with equivalent volume fractions of defects. By embedding defects of varying sizes and locations within the RVEs, fatigue indicator parameters (FIPs) were calculated to analyze the impact of defects’ characteristics on fatigue performance. Different combinations of defect volume and locations were generated for various microstructure instantiations, providing insight into extreme value fatigue responses. Larger defect volumes located on free surfaces consistently generated the highest FIPs, suggesting defect size and boundary proximity intensify stress concentration effects. RVEs with multiple smaller defects produced lower FIPs than those with single large critical defects. These findings underscore the critical role of defect characteristics on fatigue life, providing a foundation for future predictive modeling in fatigue-sensitive AM applications.

AlSi10Mg↗
DOE OSTI2022

Controlled Growth and Chemical Engineering of FeSe‐Based Superconducting Films

Abstract Chemical engineering tailors functional materials to meet the demands of physical and chemical properties, accelerating materials discovery and design in a multidisciplinary field. However, stereotyped synthetic paradigms in physical and chemical approaches obstruct the effective integration of multiple advantages of respective materials exploration methods. Solid state reaction is often considered separately with wet chemistry synthesis route, such as film growth using physical vapor deposition and hydrothermal methods. Here, the controlled growth of FeSe thin films by physical deposition techniques followed by the chemical engineering to create heterogenous interface in FeSe films via a solution‐based environment is demonstrated. The two‐step route allows an expanded crystal structure and enhanced superconducting transition temperature from 3.6 to 38 K, providing a new strategy to design functional hybrid materials.

Huang, Yulong↗
DOE OSTI2020

Tuning the Morphology and Electronic Properties of Single-Crystal LiNi 0.5 Mn 1.5 O 4-δ : Exploring the Influence of LiCl–KCl Molten Salt Flux Composition and Synthesis Temperature

Single-crystal materials have played a unique role in the development of high-performance cathode materials for Li batteries due to their favorable chemomechanical stability. The molten salt synthesis method has become one of the most prominent techniques used to synthesize single-crystal layered and spinel materials. In this work, the molten salt synthesis method is used as a technique to tune both the morphology and Mn 3+ content of high-voltage LiNi 0.5 Mn 1.5 O 4 (LNMO) cathodes. The resulting materials are thoroughly characterized by a suite of analytical techniques, including synchrotron X-ray core-level spectroscopy, which are sensitive to the material properties on multiple length scales. Furthermore, the multidimensional characterization allows us to build a materials library according to the molten salt phase diagram as well as to establish the relationship among synthesis, material properties, and battery performance. The results of this work show that the Mn 3+ content is primarily dependent on the synthesis temperature and increases as the temperature is increased. Additionally, the particle morphology is mostly dependent on the composition of the molten salt flux, which can be tailored to obtain well-defined octahedrons enclosed by (111) facets, plates with predominant ($11\tilde{2}$) facets, irregularly shaped particles, or mixtures of these. The electrochemical measurements indicate that the Mn 3+ content has a larger contribution to the battery performance of LNMO than do morphological characteristics and that a significant amount of Mn 3+ could become detrimental to the battery performance. However, with similar Mn 3+ contents, morphology still plays a role in influencing the battery cycle life and rate performance. The insights of molten salt synthesis parameters on the formation of LNMO, with deconvolution of the roles of Mn 3+ and morphology, are crucial to continuing studies in the rational design of LNMO cathode materials for high-energy Li batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Trajectory sampling and finite-size effects in first-principles stopping power calculations

Abstract Real-time time-dependent density functional theory (TDDFT) is presently the most accurate available method for computing electronic stopping powers from first principles. However, obtaining application-relevant results often involves either costly averages over multiple calculations or ad hoc selection of a representative ion trajectory. We consider a broadly applicable, quantitative metric for evaluating and optimizing trajectories in this context. This methodology enables rigorous analysis of the failure modes of various common trajectory choices in crystalline materials. Although randomly selecting trajectories is common practice in stopping power calculations in solids, we show that nearly 30% of random trajectories in an FCC aluminum crystal will not representatively sample the material over the time and length scales feasibly simulated with TDDFT, and unrepresentative choices incur errors of up to 60%. We also show that finite-size effects depend on ion trajectory via “ouroboros” effects beyond the prevailing plasmon-based interpretation, and we propose a cost-reducing scheme to obtain converged results even when expensive core-electron contributions preclude large supercells. This work helps to mitigate poorly controlled approximations in first-principles stopping power calculations, allowing 1–2 order of magnitude cost reductions for obtaining representatively averaged and converged results.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Screw-Dislocation-Driven Growth of 2D Perovskite Spiral Microplates

Two-dimensional (2D) organic–inorganic halide perovskites are solution-processable semiconductors that are promising for optoelectronic applications. Understanding crystallization mechanisms to achieve control over nanostructures is important for optimizing desired properties. Here we introduce a versatile strategy to synthesize spiral microplates of diverse 2D perovskites at the air–water interface through screw-dislocation-driven growth. Spirals of 11 2D perovskite compositions (LA) 2 (A) n−1 Pb n X 3n+1 with different spacer (LA) cations, A-cations, halide (X) anions, and n-number can be grown. They typically consist of single- or few-layer perovskite step heights but exhibit stacking complexity when multiple dislocations interact. The spiral microplates exhibit the characteristic optical properties (photoluminescence and second-harmonic generation) of the underlying 2D perovskites. Fluorescence-detected circular dichroism imaging shows that the chirality of the spiral center does not translate to the observed chiroptical properties of the microplate, consistent with the length scale of the chiral distortion. Furthermore, this solution growth of perovskite spirals diversifies the perovskite microstructures for optoelectronics and other applications.

2D halide perovskites↗
DOE OSTI2025

The structure and migration of twin boundaries in tetragonal β -Sn: An application of machine learning based interatomic potentials

Although atomistic simulations have contributed significantly to our understanding of twin boundary structure and migration in metals and alloys with hexagonal close packed (HCP) crystal structures, few direct atomistic studies of twinning have been conducted for other types of low symmetry materials, in large part due to a lack of reliable interatomic potentials. In this work, we examine twin boundary structure and migration in a tetragonal material, β-Sn, comparing high resolution Transmission Electron Microscopy (TEM) images of deformation twins in β-Sn to the results of direct atomistic simulations using multiple interatomic potentials. ML-based potentials developed in this work are found to give results consistent with our experimental data, revealing faceted twin boundary structures formed by the nucleation and motion of twinning disconnections. We use bicrystallographic methods in combination with atomistic simulations to analyze the structure, energy and shear coupled migration of observed twin facets in β-Sn. In analogy to Prismatic-Basal (PB/BP) interfaces in HCP metals, we discover low energy asymmetric Prismatic-A-plane (PA/AP) interfaces important to twin growth in β-Sn. Finally, a Moment Tensor Potential (MTP) and Rapid Artificial Neural Network (RANN) interatomic potential suitable for studying twinning and phase transformations in Sn are made publicly available as part of this work.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A crystal-plasticity-informed Gaussian Process Regression model to capture anisotropy in single crystal shape memory alloys

This work presents a machine learning (ML) framework that model the anisotropic actuation responses in a shape memory alloy. A Gaussian Process Regression (GPR) based ML model is trained on a set of different crystal orientations subjected to different actuation conditions. The training employed thermo-mechanical responses from a crystal-plasticity model that captures phase-transformation, stress-induced plasticity, and transformation-induced plasticity. Further, on training the GPR-ML model at fixed stress level for different orientations, it captured the thermo-mechanical responses accounting for the anisotropy, and predicted responses for new orientations with good accuracy. The GPR-ML model is able to capture the transformation temperature variations even when trained using multiple stress levels, and the transformation strain showed significant deviations. The developed GPR-ML model gave reasonable predictions for an unexplored sample set of orientations and loading conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Identification of and Structural Insights into Hit Compounds Targeting N -Myristoyltransferase for Cryptosporidium Drug Development

Each year, approximately 50,000 children under 5 die as a result of diarrhea caused by Cryptosporidium parvum, a protozoan parasite. There are currently no effective drugs or vaccines available to cure or prevent Cryptosporidium infection, and there are limited tools for identifying and validating targets for drug or vaccine development. We previously reported a high throughput screening (HTS) of a large compound library against Plasmodium N-myristoyltransferase (NMT), a validated drug target in multiple protozoan parasite species. To identify molecules that could be effective against Cryptosporidium, we counter-screened hits from the Plasmodium NMT HTS against Cryptosporidium NMT. We identified two potential hit compounds and validated them against CpNMT to determine if NMT might be an attractive drug target also for Cryptosporidium. We tested the compounds against Cryptosporidium using both cell-based and NMT enzymatic assays. We then determined the crystal structure of CpNMT bound to Myristoyl-Coenzyme A (MyrCoA) and structures of ternary complexes with MyrCoA and the hit compounds to identify the ligand binding modes. The binding site architectures display different conformational states in the presence of the two inhibitors and provide a basis for rational design of selective inhibitors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns

Abstract A fast, robust pipeline for strain mapping of crystalline materials is important for many technological applications. Scanning electron nanodiffraction allows us to calculate strain maps with high accuracy and spatial resolutions, but this technique is limited when the electron beam undergoes multiple scattering. Deep-learning methods have the potential to invert these complex signals, but require a large number of training examples. We implement a Fourier space, complex-valued deep-neural network, FCU-Net, to invert highly nonlinear electron diffraction patterns into the corresponding quantitative structure factor images. FCU-Net was trained using over 200,000 unique simulated dynamical diffraction patterns from different combinations of crystal structures, orientations, thicknesses, and microscope parameters, which are augmented with experimental artifacts. We evaluated FCU-Net against simulated and experimental datasets, where it substantially outperforms conventional analysis methods. Our code, models, and training library are open-source and may be adapted to different diffraction measurement problems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Quantifying patterns in optical micrographs of one- and two-dimensional ellipsoidal particle assemblies

Current developments in colloidal science include the assembly of anisotropic colloids with broad geometric diversity. As the complexity of particle assemblies increases, the need for ubiquitous algorithms that quantitatively analyze images of the assemblies to deliver key information such as quantification of crystal structures becomes more urgent. This contribution describes algorithms capable of image analysis for classifying colloidal structures based on abstracted interparticle relationship information and quantitatively analyzing the abundance of each structure in mixed pattern assemblies. The algorithm parameters can be adjusted, allowing for the algorithms to be adapted for different image analyses. Three different ellipsoidal particle assembly images are presented to demonstrate the effectiveness of the algorithms: a one-dimensional (1D) particle chain assembly and two two-dimensional (2D) polymorphic crystals each consisting of assemblies of two distinct plane symmetry groups. Angle relationships between neighbouring particles are calculated and neighbour counts of each particle are determined. Combining these two parameters as rules for classification criteria allows for the labeling and quantification of each particle into a defined symmetry class within an assembly. The algorithms provide a labelled image comprising classification results and particle counts of each defined class. For multiple images or individual frames from a video, the script can be looped to achieve automatic processing. The yielded classification data allow for more in-depth image analysis of mixed pattern particle assemblies. Finally, we envision that these algorithms will have utility in quantitative analysis of images comprising ellipsoidal colloidal materials, nanoparticles, or biological matter.

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

Lightwave-electronic harmonic frequency mixing

Electronic frequency mixers are fundamental building blocks of electronic systems. Harmonic frequency mixing in particular enables broadband electromagnetic signal analysis across octaves of spectrum using a single local oscillator. However, conventional harmonic frequency mixers do not operate beyond hundreds of gigahertz to a few terahertz. If extended to the petahertz scale in a compact and scalable form, harmonic mixers would enable field-resolved optical signal analysis spanning octaves of spectra in a monolithic device without the need for frequency conversion using nonlinear crystals. Here, we demonstrate lightwave-electronic harmonic frequency mixing beyond 0.350 PHz using plasmonic nanoantennas. We demonstrate that the mixing process enables complete, field-resolved detection of spectral content far outside that of the local oscillator, greatly extending the range of detectable frequencies compared to conventional heterodyning techniques. Our work has important implications for applications where optical signals of interest exhibit coherent femtosecond-scale dynamics spanning multiple harmonics.

Science & Technology - Other Topics↗
DOE OSTI2026

Engineering and Application of a Thermostable MHETase for PET Depolymerization

Enzymatic hydrolysis of poly(ethylene terephthalate) (PET) releases mono(2-hydroxyethyl) terephthalate (MHET) as a major product, the accumulation of which can prolong reactor residence times and complicate downstream monomer separations. The use of a MHETase enzyme can enable MHET hydrolysis to the monomers, terephthalic acid and ethylene glycol, but industrial PETases typically operate at thermophilic temperatures and the well-known MHETase from Ideonella sakaiensis is a mesophilic enzyme, thus warranting the development of thermophilic MHETases. Here, we characterize thermostable MHET-active enzymes from a natural diversity screen by applying a hidden Markov model based on the previously reported, archaeal ferulic acid esterase, PET46. We identified enzymes with higher thermostability than PET46 and quantified their MHETase activity in reactions at 70 °C. The crystal structure of MHT077, the homologue with the highest MHETase activity and an apparent melting temperature (T m,app ) of 94.6 °C, informed site saturation mutagenesis in the active site and lid-domain interface. MHT077 exhibited a ∼100-fold slower unfolding rate at 65 °C than PET46, indicating substantially greater kinetic stability. In parallel, we applied evolution-informed design, a probabilistic model that leverages coevolutionary patterns in large multiple sequence alignments, to improve the activity and thermostability of five ferulic acid esterases. One design, EV-MHT043–5 was identified with a comparable thermostability (T m,app = 96.1 °C) and a 3-fold improvement in its MHETase activity relative to the wildtype enzyme, MHT043. Combination variants of beneficial mutations were screened and afforded a variant, MHT077 LFK , which reduced MHET accumulation in bioreactor experiments with postconsumer PET waste. Overall, this study expands the known MHET-hydrolyzing protein scaffolds available for enzymatic PET recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Trimer Quinoxalines as Organic Cathode Materials for Lithium-Ion Batteries

Due to synthetic ease, high redox potentials, low solubility in polar electrolytes, and good electric conductivity of their semiconducting crystals, discotic quinoxaline trimers (3Q) have been considered as possible candidates for 4 V organic cathodes in lithium-ion batteries. To assess their feasibility as such materials, several 3Q derivatives have been synthesized and tested in half-cells. In voltage limited cycling tests at 1.2–3.9 V vs Li/Li + , the specific discharge capacities of 40–180 mAh g -1 were obtained at a rate of 1 C, and multiple lithiation of 3Q and its derivatives was observed during discharge. However, the obtained discharge capacity was only a fraction of the theoretical capacity expected for reversible six-electron reduction; there was also rapid capacity fade. Our spectroscopic studies indicate the reversible three-electron lithiation at 2 V vs Li/Li + , but suggest instability of more highly discharged states. Finally, our conclusion is that while the 3Q derivatives combine several traits that are desirable in an organic cathode material (including negligible solubility, capacity for multiple charging, and near-100% coulombic efficiency), these materials are still impractical to use.

25 ENERGY STORAGE↗
DOE OSTI2024

Strain-concentration for fast, compact photonic modulation and non-volatile memory

A critical figure of merit (FoM) for electro-optic (EO) modulators is the transmission change per voltage, d T / d V . Conventional approaches in wave-guided modulators maximize d T / d V via a high EO coefficient or longer light-material interaction lengths but are ultimately limited by material losses and nonlinearities. Optical and RF resonances improve d T / d V at the cost of spectral non-uniformity, especially for high- Q optical cavity resonances. Here, we introduce an EO modulator based on piezo-strain-concentration of a photonic crystal cavity to address both trade-offs: (i) it eliminates the trade-off between d T / d V and waveguide loss—i.e., enhancement of the resonance tuning efficiency d v c / d V for the fixed EO coefficient, waveguide length, and cavity Q —and (ii) at high DC strains it exhibits a non-volatile (NV) cavity tuning Δ v c ,NV for passive memory and programming of multiple devices into resonance despite fabrication variations. The device is fabricated on a scalable silicon nitride-on-aluminum nitride platform. We measure d v c / d V =177±1MHz/V, corresponding to Δ v c =40±0.32GHz for a voltage spanning ±120V with an energy consumption of δ U /Δ v c =0.17nW/GHz. The modulation bandwidth is flat up to ω BW,3dB /2 π =3.2±0.07MHz for broadband DC-AC and 142±17MHz for resonant operation near a 2.8 GHz mechanical resonance. Optical extinction up to 25 dB is obtained via Fano-type interference. Strain-induced beam-buckling modes are programmable under a “read-write” protocol with a continuous, repeatable tuning range of 5±0.25GHz, allowing for storage and retrieval, which we quantify with mutual information of 2.4 bits and a maximum non-volatile excursion of 8 GHz. Using a full piezo-optical finite-element-model (FEM) we identify key design principles for optimizing strain-based modulators and chart a path towards achieving performance comparable to lithium niobate-based modulators and the study of high strain physics on-chip.

Wen, Y. Henry (ORCID:0009000685423628)↗
DOE OSTI2020

Dynamic clay microstructures emerge via ion complexation waves

Clays control carbon, water and nutrient transport in the lithosphere, promote cloud formation5 and lubricate fault slip through interactions among hydrated mineral interfaces. Clay mineral properties are difficult to model because their structures are disordered, curved and dynamic. Consequently, interactions at the clay mineral-aqueous interface have been approximated using electric double layer models based on single crystals of mica and atomistic simulations. We discover that waves of complexation dipoles at dynamically curving interfaces create an emergent long-range force that drives exfoliation and restacking over time- and length-scales that are not captured in existing models. Curvature delocalizes electrostatic interactions in ways that fundamentally differ from planar surfaces, altering the ratio of ions bound to the convex and concave sides of a layer. Multiple-scattering reconstruction of low-dose energy-filtered cryo electron tomography enabled direct imaging of ion complexes and electrolyte distributions at hydrated and curved mineral interfaces with {\aa}ngstrom resolution over micron length scales. Layers exfoliate and restack abruptly and repeatedly over timescales that depend strongly on the counterion identity, demonstrating that the strong coupling between elastic, electrostatic and hydration forces in clays promote collective reorganization previously thought to be a feature only of active matter.

Whittaker, Michael L↗