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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Bi aliovalent substitution in Li 7 La 3 Zr 2 O 12 garnets: Structural and ionic conductivity effects

We report on the synthesis of cubic-phase garnet-type solid-state electrolytes based on Bi-doped Li 7 La 3 Zr 2 O 12 (LLZO). Bi aliovalent substitution of Zr in LLZO utilizing the Pechini processing method is employed to synthesize Li 7-x La 3 Zr 2-x Bi x O 12 compounds. A strong dependence of the ionic conductivity on Bi content is observed, and under our synthesis and sintering conditions, a >100-fold increase over the un-doped sample is observed for x=0.75. Cubic-phase Li 6 La 3 Zr 1 BiO 12 compounds are generated upon annealing in air in the temperature range 650 °C-900 °C. In contrast, in the absence of Bi, the cubic garnet phase of Li 7 La 3 Zr 2 O 12 is not formed below 700 °C and a transformation to the tetragonal phase is observed at similar to 900 °C for this un-doped compound. The role of Bi in lowering the formation temperature of the garnet cubic phase and in the ionic conductivity improvements is investigated in this work. We ascribe the effect of Bi-doping on ionic conductivity increments to changes in Li + -site occupancy and lattice parameters and the reduction in the formation temperature for the cubic-phase formation to rate enhancements of the solid-state reaction. To identify the site occupancy of Bi in the garnet structure, we employ synchrotron extended x-ray absorption fine structure spectroscopy. Our results indicate that Bi additions occupy the Zr-type sites exclusively, to within the accuracy of the measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nanocrystalline strain glass TiNiPt and its superelastic behavior

TiNi-based shape-memory alloys are known to exhibit a strain glass state under certain conditions, generally in the presence of high-density defects such as excess solute atoms or alloying elements, dislocations, and nanoprecipitates. In this paper, we report a strain glass transition in a nanocrystalline Ti 50 Ni 35 Pt 15 alloy. The nanocrystalline strain glass state is achieved by a combined effect of high-density grain boundaries and high concentration doping of Pt atoms in the B2 matrix. The nanocrystalline Ti 50 Ni 35 Pt 15 strain glass alloy showed a large near-complete progressive superelasticity with a recovery strain of about 6% and a low apparent Young's modulus of about 30 GPa in a wide temperature range of over 200 °C. In situ synchrotron x-ray diffraction measurement showed that the strain glass B2 [B2(SG)] phase experienced B2(SG)→R→B19 transformation upon loading and B19→B2(SG) upon unloading. The findings of this study provide insight for the development of nanocrystalline strain glass shape-memory alloys.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Intercalation And High-Pressure Effects On Structural Phase Transitions In Layered As x P 1-x Alloys

This project was aimed at understanding the role of composition, intercalation, and high pressure on the structural evolution of black phosphorous (BP) and layered arsenic phosphorous alloys, As y P 1-y . Under normal conditions, BP is the most stable phase of phosphorous, known as the α-phase, characterized by an orthorhombic honeycomb puckered crystal structure with the Cmca space group. On the other hand, the most stable phase of arsenic is its β-phase, known as gray arsenic (g-As), which has a rhombohedral buckled layered crystal structure with the R3m space group. In a wide range of compositions (y < 0.83), the arsenic phosphorous alloys form the α-phase, known as black arsenic phosphorous (b-As y P 1-y ) with a similar structure to BP. The project was aimed at the synthesis of BP and b-As y P 1-y with different compositions and at studying the structural evolution of these materials during intercalation with alkali metal (especially Li), and under high-pressure conditions. The main goals were to gain a better understanding of these processes and structural changes taking place under these conditions. In particular, the project was aimed at addressing whether such conditions could induce a structural transition between the α- and β-phases. For this, a series of systematic in-situ studies were conducted, including electrochemical lithium intercalation in an in-situ electrochemical cell, and high-pressure experiments in a diamond anvil cell (DAC). Overall, both types of experiments have shown that above a certain composition-dependent threshold level of intercalation or high pressure, the system undergoes phase segregation rather than phase transition. Specifically, the segregation of the excess arsenic was observed, and a single-phase system of b-As y P 1-y transformed into a two-phase system consisting of b-As y P 1-y and g-As, through the following process: 1∗(b-As y P 1-y ) → 1∗(b As y-δ P 1-y ) + δ∗(g-As). Also, the study showed that intercalation and high-pressure are two competing rather than synergistic processes causing at least a partial cancelation of these two factors

36 MATERIALS SCIENCE↗
DOE OSTI2025

Gradient flow based phase-field modeling using separable neural networks

Allen–Cahn equation is a reaction–diffusion equation and is widely used for modeling phase separation. Machine learning methods for solving the Allen–Cahn equation in its strong form suffer from inaccuracies in collocation techniques, errors in computing higher-order spatial derivatives, and the large system size required by the space–time approach. To overcome these challenges, we propose solving the gradient flow of the Ginzburg–Landau free energy functional, which is equivalent to the Allen–Cahn equation, thereby avoiding the second-order spatial derivatives associated with the Allen–Cahn equation. A minimizing movement scheme is employed to solve the gradient flow problem, eliminating the complexities of a space–time approach. We utilize a separable neural network that efficiently represents the phase field through low-rank tensor decomposition. As we use the minimizing movement scheme to numerically solve the gradient flow problem, we thus, refer to the proposed method as the Separable Deep Minimizing Movement (SDMM) method. The evaluation of the functional in the minimizing movement scheme using the Gauss quadrature technique bypasses the inaccuracies associated with collocation techniques traditionally used to solve partial differential equations. A hyperbolic tangent transformation is introduced on the phase field prior to the evaluation of the functional to ensure that it remains strictly bounded within the values of the two phases. For this transformation, theoretical guarantee for energy stability of the minimizing movement scheme is established. Our results suggest that this transformation helps to improve the accuracy and efficiency significantly. The proposed method resolves the challenges faced by state-of-the-art machine learning techniques, outperforming them in both accuracy and efficiency. It is also the first machine learning method to achieve an order of magnitude speed improvement over the finite element method. In addition to its formulation and computational implementation, several case studies illustrate the applicability of the proposed method.

42 ENGINEERING↗
DOE OSTI2024

Effect of Zn Addition on Phase Evolution in AlCrFeCoNiZn High–Entropy Alloy

The addition of Zn to AlCrFeCoNi high-entropy alloy (HEA) poses intriguing questions as to how it would affect phase evolution. Herein, the phase evolution in AlCrFeCoNiZn is studied using a combination of experimental techniques (X-ray diffraction, scanning electron microscopy, energy-dispersive spectroscopy, and differential scanning calorimetry) and computational (density-functional theory [DFT], calculation of phase diagrams, and machine-learning) methods. Mechanically alloyed and spark-plasma-sintered AlCrFeCoNiZn assumes a metastable single-phase, body-centered-cubic (BCC) structure that undergoes diffusion-controlled phase separation upon subsequent heat treatment to form separate (Al, Cr)-rich, (Fe, Co)-rich, and (Zn, Ni)-rich phases. The formation of (Al, Cr)-rich phase, not reported previously in AlCrFeCoNi-based HEAs, is attributed to strong clustering tendency of Cr–Zn and Cr–Ni pairs, combined with the strong ordering of Zn–Ni pair, driving out Cr that in turn combines with Al to form a (Al, Cr)-rich phase. In the DFT results, the formation of thermodynamically stable L1 2 phase is shown wherein Cr–Fe–Zn [Al–Ni-Co] preferably occupy1a (000) [3c (0 ½ ½)] positions. Furthermore, the sluggish diffusional transformation to L1 2 phase from BCC precursors is attributed to the small stacking-fault energy of AlCrFeCoNiZn. The equilibrated HEA exhibits a high microhardness of 8.24 GPa with an elastic modulus of 184 GPa.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Polymorphism of gold under laser-based ramp compression to 690 GPa

The high-pressure behavior and polymorphism of gold has attracted strong recent interest from theory as well as from both static and dynamic experiments. In this study, gold was dynamically ramp-compressed to 690 GPa via laser ablation using the Omega Laser Facility (U. Rochester) in order to investigate the stability regions of this noble metal's polymorphs. Here, stresses were determined from measurements of surface or interface velocities by laser interferometry. In situ X-ray diffraction was carried out to constrain the structure and density. The ambient face-centered-cubic (fcc) phase was observed at 162 GPa, followed by a mixed phase region consisting of the fcc and body-centeredcubic (bcc). The presence of only the bcc phase was observed between 377 and 690 GPa. Our results are consistent with recent shock compression experiments and demonstrate that gold transforms to the bcc phase under conditions of both ramp and shock loading.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Ultrafast olivine-ringwoodite transformation during shock compression

Meteorites from interplanetary space often include high-pressure polymorphs of their constituent minerals, which provide records of past hypervelocity collisions. These collisions were expected to occur between kilometre-sized asteroids, generating transient high-pressure states lasting for several seconds to facilitate mineral transformations across the relevant phase boundaries. However, their mechanisms in such a short timescale were never experimentally evaluated and remained speculative. Here, we show a nanosecond transformation mechanism yielding ringwoodite, which is the most typical high-pressure mineral in meteorites. An olivine crystal was shock-compressed by a focused high-power laser pulse, and the transformation was time-resolved by femtosecond diffractometry using an X-ray free electron laser. Our results show the formation of ringwoodite through a faster, diffusionless process, suggesting that ringwoodite can form from collisions between much smaller bodies, such as metre to submetre-sized asteroids, at common relative velocities. Even nominally unshocked meteorites could therefore contain signatures of high-pressure states from past collisions.

42 ENGINEERING↗
DOE OSTI2023

Melt-Processed Halide Perovskite Thin Films from a Two-Dimensional Ruddlesden–Popper Phase Precursor

While halide perovskite thin films have enormous potential for photovoltaics and other optoelectronics, the use of environmentally hazardous solvents during their deposition and processing poses a barrier to their commercialization. In this work, we demonstrated the deposition of melt-processable precursors and subsequent transformation into halide perovskite thin films without using environmentally hazardous solvents. We melted the wide-bandgap layered perovskites [(C 6 H 5 CH(CH 3 )CH 2 NH 3 ) 2 PbI 4 :β-Me-PEA 2 PbI 4 ] at ~210 °C and blade coated them into films. The β-Me-PEA 2 PbI 4 films were subsequently transformed to perovskite-phase methylammonium or formamidinium lead iodide films using a cation-exchange process in an alcohol-based solvent. Lastly, we demonstrate the potential and limitations of a completely solvent-free approach that uses solid-state transformation of a β-Me-PEA 2 PbI 4 film. As a result, this work represents a substantial step toward eliminating environmentally hazardous solvents and enables inexpensive industrial-scale liquid-phase deposition processes that do not require expensive systems for handling and disposing of environmentally hazardous solvents.

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

Design of a V–Ti–Ni alloy with superelastic nano-precipitates

Stress-induced martensitic transformations enable metastable alloys to exhibit enhanced strain hardening capacity, leading to improved formability and toughness. As is well-known from transformation-induced plasticity (TRIP) steels, however, the resulting martensite can limit ductility and fatigue life due to its intrinsic brittleness. In this work, we explore an alloy design strategy that utilizes stress-induced martensitic transformations but does not retain the martensite phase. This strategy is based on the introduction of superelastic nano-precipitates, which exhibit reverse transformation after initial stress-induced forward transformation. To this end, utilizing ab-initio simulations and thermodynamic calculations we designed and produced a V 45 Ti 30 Ni 25 (at%) alloy. In this alloy, TiNi is present as nano-precipitates uniformly distributed within a ductile V-rich base-centered cubic (bcc) β matrix, as well as being present as a larger matrix phase. We characterized the microstructure of the produced alloy using various scanning electron microscopy (SEM) and transmission electron microscopy (TEM) methods. Furthermore, the bulk mechanical properties of the alloy are demonstrated through tensile tests, and the reversible transformation in each of the TiNi morphologies were confirmed by in-situ TEM micro-pillar compression experiments, in-situ high-energy diffraction synchrotron cyclic tensile tests, indentation experiments, and differential scanning calorimetry experiments. The observed transformation pathways and variables impacting phase stability are critically discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Radiation-Induced Solid-State Transformations of Uranyl Peroxides

Single-crystal X-ray diffraction studies of pristine and γ-irradiated Ca 2 [UO 2 (O 2 ) 3 ]·9H 2 O reveal site-specific atomic-scale changes during the solid-state progression from a crystalline to X-ray amorphous state with increasing dose. Following γ-irradiation to 1, 1.5, and 2 MGy, the peroxide group not bonded to Ca 2+ is progressively replaced by two hydroxyl groups separated by 2.7 Å (with minor changes in the unit cell), whereas the peroxide groups bonded to Ca 2+ cations are largely unaffected by irradiation prior to amorphization, which occurs by a dose of 3 MGy. The conversion of peroxide to hydroxyl occurs through interaction of neighboring lattice H 2 O molecules and ionization of the peroxide O–O bond, which produces two hydroxyls, and allows isolation of the important monomer building block, UO 2 (O 2 ) 2 (OH) 2 4– , that is ubiquitous in uranyl capsule polyoxometalates. Steric crowding in the equatorial plane of the uranyl ion develops and promotes transformation to an amorphous phase. In contrast, γ-irradiation of solid Li 4 [(UO 2 )(O 2 ) 3 ]·10H 2 O results in a solid-state transformation to a well-crystallized peroxide-free uranyl oxyhydrate containing sheets of equatorial edge and vertex-sharing uranyl pentagonal bipyramids with likely Li and H 2 O in interlayer positions. The irradiation products of these two uranyl triperoxide monomers are compared via X-ray diffraction (single-crystal and powder) and Raman spectroscopy, with a focus on the influence of the Li + and Ca 2+ countercations. Highly hydratable and mobile Li+ yields to uranyl hydrolysis reactions, while Ca 2+ provides lattice rigidity, allowing observation of the first steps of radiation-promoted transformation of uranyl triperoxide.

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

Design and Synthesis of Cubic K 3−2 x Ba x SbSe 4 Solid Electrolytes for K–O 2 Batteries

Developing K-ion conducting solid-state electrolytes (SSEs) plays a critical role in the safe implementation of potassium batteries. In this work, a chalcogenide-based potassium ion SSE is reported, K 3 SbSe 4 , which adopts a trigonal structure at room temperature. Single-crystal structural analysis reveals a trigonal-to-cubic phase transition at the low temperature of 50 °C, which is the lowest among similar compounds and thus provides easy access to the cubic phase. The substitution of barium for potassium in K 3 SbSe 4 leads to the creation of potassium vacancies, expansion of lattice parameters, and a transformation from a trigonal phase to a cubic phase. As a result, the maximum conductivity of K 3−2x Ba x SbSe 4 reaches around 0.1 mS cm −1 at 40 °C for K 2.2 Ba 0.4 SbSe 4 , which is over two orders of magnitude higher than that of undoped K 3 SbSe 4 . This novel SSE is successfully employed in a K–O 2 battery operating at room temperature where a polymer-laminated K 2.2 Ba 0.4 SbSe 4 pellet serves as a separator between the oxygen cathode and the potassium metal anode. Effective protection of the K metal anode against corrosion caused by O 2 is demonstrated.

25 ENERGY STORAGE↗
DOE OSTI2020

A Simple Space Vector Modulation of High-Frequency AC Linked Three-Phase-to-Single-Phase/DC Converter

High frequency (HF) ac linked converter functions well to interface between buses with different voltage types. Using a three-phase-to-single-phase matrix converter, a single-phase cyclo converter, and a HF transformer, we can compose a HF ac linked converter to interface between three-phase ac grids and single-phase ac or dc distributed generations (DGs). In this paper, a novel space vector modulation (SVM) method is proposed for such kind of converter. The proposed SVM method converts the mains three-phase ac voltage to a HF ac voltage at the primary side of transformer, and then unfolds the HF ac voltage to a single-phase ac or dc voltage at the secondary side of transformer. Without need to compute separate switching signals for the primary and secondary converters and then coordinate their operations elaborately, the proposed SVM method can be easily implemented by incorporating the HF chopping into the SVM of traditional indirect matrix converter. Therefore, no complicated duty cycle computation or elaborate switching states combination is required. Simulation and hardware-in-loop implementation demonstrate the validity of the proposed method.

42 ENGINEERING↗
DOE OSTI2024

Part-scale microstructure prediction for laser powder bed fusion Ti-6Al-4V using a hybrid mechanistic and machine learning model

Laser powder bed fusion (LPBF) Ti-6Al-4V is widely studied for use in structural applications in aerospace and medical industries, but mechanical anisotropy and microstructural inhomogeneity prohibits its wider adoption. Although successful microstructure prediction models have been developed, a remaining challenge is their limited integration across length/time scales and validation by experimental studies. Here, this work proposes a physics-augmented machine learning surrogate model to unite predictions of LPBF temperature, β phase morphology and texture, and α/α’ formation into a single framework that is calibrated and validated with experiments. First, a phase field (PF) model of the martensitic β→α’ transformation is developed and calibrated using data from in-situ synchrotron cyclic heating/cooling studies quantifying the variation of α phase fraction with time. In parallel, an established finite difference-Monte Carlo (FDMC) model predicts the part-scale temperature profile and β grain formation during solidification. A dataset is developed using LPBF cyclic temperature descriptors from the FDMC model as inputs and corresponding α/α’ phase fraction and width from the PF model as outputs. Five machine learning (ML) regression models are tested and optimized, having mean absolute error in testing ≤ 4 %, and the k-nearest neighbors (KNN) model is selected as the best performing. The KNN model is called at the nodal level during post-processing of the FDMC model to replace and downscale the response of the PF model. The combined agility and accuracy of the hybrid FDMC-ML model enables part-scale microstructure predictions that can be further used for property predictions to accelerate AM process optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Chemical and physical transformations of carbon-based nanomaterials observed by liquid phase transmission electron microscopy

This article addresses recent advances in liquid phase transmission electron microscopy (LPTEM) for studying nanoscale synthetic processes of carbon-based materials that are independent of the electron beam—those driven by nonradiolytic chemical or thermal reactions. In particular, we focus on chemical/physical formations and the assembly of nanostructures composed of organic monomers/polymers, peptides/DNA, and biominerals. The synthesis of carbon-based nanomaterials generally only occurs at specific conditions, which cannot be mimicked by aqueous solution radiolysis. Carbon-based structures themselves are also acutely sensitive to the damaging effects of the irradiating beam, which make studying their synthesis using LPTEM a unique challenge that is possible when beam effects can be quantifi ed and mitigated. With new direct sensing, high frame rate cameras, and advances in liquid-cell holder designs, combined with a growing understanding of irradiation effects and proper experimental controls, microscopists have been able to make strides in observing traditionally problematic carbon-based materials under conditions where synthesis can be controlled, and imaged free from beam effects, or with beam effects quantified and accounted for. These materials systems and LPTEM experimental techniques are discussed, focusing on nonradiolytic chemical and physical transformations relevant to materials synthesis.

Parent, Lucas R.↗
DOE OSTI2024

CNN-Based Phase Fault Classification in Real and Simulated Power Systems Data

This study proposes a convolutional neural network (CNN)–based two-step phase fault detection and identification method to classify anomalies in the power grid signal. Specifically, the first step checks the fault’s existence and determines the need for the second step. Subsequently, in the case of anomalies in the power grid signal, the second step identifies the type of fault, including line-to-line, single-line-to-ground, double-line-to-ground, and triple-line. Accordingly, the CNN architecture is both designed for the classification layers and trained with simulated data. To provide maximum prediction accuracy with minimum processing time, this study investigates the combinations of various feature extraction (FE) techniques, such as fast Fourier transform (FFT), amplitude and phase (AP), auto-correlation function, power spectral density, and wavelet transform (WT). Consequently, simulated and real-world results demonstrate that the proposed two-step method outperforms conventional one-step techniques, with the best performance obtained by using the combination of AP-AP, AP-WT, FFT-AP, and FFT-WT–based FE methods.

Alaca, Ozgur↗
DOE OSTI2025

A highly wear resistant nanostructured bainitic steel with accelerated transformation kinetics

A coupled Calculation of Phase Diagrams (CALPHAD), machine learning, and data mining approach was used to design a new, highly wear-resistant nanostructured bainitic steel. Arc melting of the designed compositions, dilatometry, and advanced microscopy indicate that the designed steel had a nanoscale dual-phase structure of ferrite and austenite (approximately 50 nm) with kinetics 7x faster for the onset of bainite and 2x faster for complete transformation. Under dry sliding conditions using the current state-of-the-art AISI 52100 bearing steel as the counter sample, the designed steel little to no wear, indicating its potential for applications in high-wear service conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Personal Journey in Nanoscience via Developing and Applying Liquid Phase TEM

Liquid phase TEM has attracted widespread attention in recent years as a groundbreaking tool to address various fundamental problems in nanoscience. It has provided the opportunity to reveal many unseen dynamic phenomena of nanoscale materials in solution processes by direct imaging through liquids with high spatial and temporal resolution. After my earlier work on real-time imaging of the nucleation, growth, and dynamic motion of nanoparticles in liquids by developing high-resolution liquid phase transmission electron microscopy (TEM) down to the sub-nanometer level, I established my own research group at Lawrence Berkeley National Lab in 2010. My group focuses on developing and applying liquid phase TEM to investigate complex systems and reactions. We have studied a set of scientific problems centered on understanding how atomic level heterogeneity and fluctuations at solid-liquid interfaces impact nanoscale materials transformations using advanced liquid phase TEM. This article describes my personal journey in nanoscience, highlighting the main discoveries of my research group using liquid phase TEM as a unique tool. Some perspectives on the impacts of liquid phase TEM and the future opportunities in nanoscience and nanotechnology enabled by liquid phase TEM are also included.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗