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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Complexin2 modulates working memory-related neural activity in patients with schizophrenia

The specific contribution of risk or candidate gene variants to the complex phenotype of schizophrenia is largely unknown. Studying the effects of such variants on brain function can provide insight into disease-associated mechanisms on a neural systems level. Previous studies found common variants in the complexin2 ( CPLX2 ) gene to be highly associated with cognitive dysfunction in schizophrenia patients. Similarly, cognitive functioning was found to be impaired in Cplx2 gene-deficient mice if they were subjected to maternal deprivation or mild brain trauma during puberty. Here, we aimed to study seven common CPLX2 single-nucleotide polymorphisms (SNPs) and their neurogenetic risk mechanisms by investigating their relationship to a schizophrenia-related functional neuroimaging intermediate phenotype. In this paper, we examined functional MRI and genotype data collected from 104 patients with DSM-IV-diagnosed schizophrenia and 122 healthy controls who participated in the Mind Clinical Imaging Consortium study of schizophrenia. Seven SNPs distributed over the whole CPLX2 gene were tested for association with working memory-elicited neural activity in a frontoparietal neural network. Three CPLX2 SNPs were significantly associated with increased neural activity in the dorsolateral prefrontal cortex and intraparietal sulcus in the schizophrenia sample, but showed no association in healthy controls. Finally, since increased working memory-related neural activity in individuals with or at risk for schizophrenia has been interpreted as ‘neural inefficiency,’ these findings suggest that certain variants of CPLX2 may contribute to impaired brain function in schizophrenia, possibly combined with other deleterious genetic variants, adverse environmental events, or developmental insults.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

High Damping of Lightweight TiNi-Ti{sub 2}Ni Shape Memory Composites for Wide Temperature Range Usage

A bimodal porous TiNi-Ti{sub 2}Ni shape memory alloy composite (SMAC) with 59% porosity was fabricated by sintering Ti-46at.%Ni elemental powders with pore-forming agent. The porous TiNi-Ti{sub 2}Ni SMAC contains two irregular pores of about 400 and 120 μm. We investigated the microstructure and pore morphology correlated with the mechanical properties and damping capacities of the SMAC. Ti{sub 2}Ni intermetallic phases with size of 1-3 μm were homogeneously distributed in the TiNi matrix. The porous TiNi-Ti{sub 2}Ni SMAC exhibits exceptionally high inverse mechanical quality factor (Q{sup −1}) of ~0.25 at < 40 °C, which is among the highest value reported for porous/dense shape memory alloys or composites to best of our knowledge, and it shows very high compressive fracture strain of about 25%. Moreover, the fabricated porous SMAC at relatively low strain amplitude can exhibit considerable high Q{sup −1} of 0.06 ~ 0.11 for a wide range of temperature between − 90 and 200 °C, which is attributed to the stress concentration distribution provided by the bimodal structure of pores and the massive interfaces between pore/matrix and TiNi/Ti{sub 2}Ni. These porous SMACs can be an ideal candidate for using as a lightweight damping material in the energy-saving applications.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Structure Analysis of a Precipitate Phase in an Ni-Rich High Temperature NiTiHf Shape Memory Alloy

Thermal aging of the high temperature shape memory alloy 50.3Ni-29.7Ti-20Hf (at.%) introduces a novel precipitate phase, which plays an important role in improving shape memory properties. The precipitate phase was investigated by conventional electron diffraction, high resolution scanning transmission electron microscopy (STEM) and three dimensional atom probe tomography. An unrelaxed orthorhombic atomic structural model is proposed based on these observations. This model was subsequently relaxed by ab initio calculations. As a result of the relaxation, atom shuffle displacements occur, which in turn yields improved agreement with the STEM images. The relaxed structure, which is termed the “H-phase”, has also been verified to be thermodymanically stable at 0 K.

Atom probe tomography, Ni-Ti-Hf alloy, shape memor↗
DOE OSTI2018

Phase field simulation of martensitic transformation in pre-strained nanocomposite shape memory alloys

We show in this paper how strain engineering alters the fundamental characteristic of a martensitic transformation (MT) and gives it a new set of properties including large quasi-linear elastic strain response with nearly vanishing hysteresis and low elastic modulus. The work is motivated and inspired by a recent experimental study on elastic and inelastic (transformation) strain matching in a pre-strained nano-composite with Nb nanowires embedded in a NiTi shape memory alloy matrix. In particular, we demonstrate by computer simulation that dislocations at Nb/NiTi interfaces produced by the pre-straining are responsible for the unprecedented properties. Microstructural evolution captured in the simulations reveals that local stress fields associated with the dislocations regulate the nucleation and growth of martensite, turning the otherwise sharp, strong first-order transition into a continuous, high-order like transition. The simulations predict that the stress-strain hysteresis and modulus of the composite decrease with increasing amount of pre-strain, which agrees well with the experimental measurement. This study suggests a design strategy by introducing non-uniform stress fields for enhanced properties of shape memory alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2019

In situ investigation of stress-induced martensitic transformation in granular shape memory ceramic packings

Stress-induced martensitic transformation can occur in granular shape memory materials when individual particles experience high stresses and transform from a high-symmetry austenite phase to a low-symmetry martensite phase. This involves a highly heterogeneous distribution of the driving force and very low mechanical constraint for martensite nucleation, so the transformation behavior can be dramatically different from the well-documented case of monolithic solids. In this work, we investigate the stress-induced martensitic transformation in granular shape memory ceramic packings, which consist of single-crystal micro-particles of ZrO 2 -12 at%CeO 2 and ZrO 2 -15 at%CeO 2 . Using in situ neutron diffraction, we study how the phase fraction, lattice strain, and integral peak broadness evolve during external loading, unloading, and subsequent heating. Several peculiar features are discovered, including (i) a continuous mode of transformation with a wide range of transformation loads, (ii) co-evolution of the packing structure, contact deformation, and martensitic transformation, and (iii) a strong correlation between the peak broadening and the transformed phase fraction. In addition, we show the first direct evidence of reversible stress-induced martensitic transformation in granular materials. We additionally discuss the mechanism for martensite nucleation and growth in granular packings and show how that leads to the observed transformation characteristics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Phase diagram of magnetic shape memory alloy Ni 50 Mn $50–x$ In $x$ , 0 < $x$ , 25 from first principles, via spin cluster expansion and phonon vibrational entropies

The metamagnetic shape memory Heusler alloy Ni 50 Mn $50–x$ In $x$ exhibits a rich phase diagram featuring competing magnetic states, coupled magnetic–structural phase transitions, and strong compositional sensitivity. Existing first-principles approaches struggletocapturetheintertwinedchemical, magnetic, andvibrationaleffectsinthesealloys, necessitating a more integrated modeling framework. We develop a spin cluster expansion (spin-CE) framework augmented by a quasi-harmonic phonon model to capture both configurational (chemical and magnetic) and vibrational contributions to the free energy of Ni 50 Mn $50–x$ In $x$ over the full compositional range 0 ≤ x ≤25. The spin-CE includes both chemical clusters and composition-dependent Ising spin interactions, with parameters fit to a first-principles density functional theory (DFT) dataset. Using this approach, we predict the complete magnetostructural phase diagram and transformation temperatures of Ni 50 Mn $50–x$ In $x$ across the composition space. We find that vibrational entropy alone is insufficient to reproduce the martensitic transformation in the magnetic shape memory alloy regime, highlighting the essential role of magnetism. Incorporating both magnetic and vibrational contributions allows us to reproduce all experimentally known phases, including the disappearance of the stable martensite phase at a critical In concentration and the Curie temperature of the austenite phase. The method also captures the transition with increasing In in martensite from antiferromagnetic to ferromagnetic order and predicts re-entrant ferromagnetism, though the latter occurs at higher In content than reported experimentally. We discuss possible sources of this discrepancy and highlight the broader applicability of the method to other magnetostructurally complex materials, where it may offer mechanistic insight and predictive design capabilities.

Cluster expansion↗
DOE OSTI2025

Microstructure-sensitive mechanical behavior of an additively manufactured psuedoelastic shape memory alloy

The additive manufacturing of shape memory alloys into complex geometries enables fabrication of advanced functional systems across a variety of fields and domains. This work presents results focused on the mechanical behavior of additively manufactured shape memory pseudoelastic NiTi. The deformation induced solid state phase transformation from austenite to martensite allows this system to accommodate large recoverable strains. This deformation behavior is fundamentally driven by crystal-scale transformation physics. Laser powder bed fusion processing reveals that the resulting microstructure, both grain morphology and crystallographic texture, is strongly dependent on the manufacturing processing history. Exhaustive mechanical testing demonstrates that these microstructural factors strongly impact both tensile and cyclic stress–strain behavior. Cyclic dissipative behavior, however, is similar across all tested microstructures following an initial transient period. Remarkably, analysis of spatial strain fields during tensile loading reveals two distinctly different localization “modes”. The first is initiation of localized deformation bands which continuously propagate through the tensile bar during loading. In the second mode localization is observed but lacks propagation; instead additional localization cites nucleate during subsequent loading. The latter phenomena is suspected to be driven by grain-scale deformation physics as the localized band morphologies coincide with grain morphologies. These phenomena strongly impact the resulting aggregate stress–strain behavior. Hence, manufacturers and designers of psuedoelastic functional components must at the very least consider the potential variability in properties when considering additive manufacturing processing. More ideally the process–structure–property relations can be used to further tailor and optimize final functional performance.

Additive manufacturing↗
DOE OSTI2022

Inductive predictions of hydrologic events using a Long Short-Term Memory network and the Soil and Water Assessment Tool

We present machine learning methods to predict hydrologic features such as streamflow and soil moisture from spatially and temporally varying hydrological and meteorological data. Here, we used a temporal reduction technique to reduce computation and memory requirements and trained a Long Short-Term Memory (LSTM) network to predict soil moisture and streamflow over multiple watersheds. We show LSTM networks can be trained in a fraction of the time required by complex process-based and attention-based models such as Soil and Water Assessment Tool (SWAT) and GeoMAN without sacrificing accuracy. We also demonstrate that outside data - sourced from a watershed other than the target - can be used to train LSTM to comparable or even superior prediction accuracy. The success of LSTM in such spatially-inductive settings shows hydrologic features can be predicted with minimal prior knowledge of the watershed in question. Finally, we make all methodologies of this work publicly available as an end-to-end software pipeline that facilitates rapid prototyping of hydrologic learners.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Loss circulation prevention in geothermal drilling by shape memory polymer

Geothermal formations are naturally fractured with large fracture openings and networks. This can often lead to frequent drilling fluid loss events which is a major contributor to the cost and non-productive time in geothermal drilling. Development of smarter technologies and methods to tackle problem lost circulation is vital for geothermal drilling cost reduction required for geothermal energy to be recognized as a competitive alternative energy source. Mitigation of this problem and other drilling problems such as stuck pipe can minimize overall project cost. In this report, a thermoset shape memory polymer that can be activated by formation natural heat was assessed to seal near wellbore fractures in geothermal wells. The performance of the shape memory polymer (SMP) was evaluated using artificial fractures created in aluminum discs and cylindrical granite cores. Rheology and particle size distribution were considered. A novel testing setup was built for this work, which allows testing of sealing efficiency under dynamic conditions at high temperature. Analysis showed that the SMP has efficiently succeeded in forming a strong plug inside the fractures and stopped fluid loss at high sealing pressure. This smart loss circulation material can expand within the fractures to reduces non-drilling time and strengthen the wellbore in high-temperature drilling operations.

58 GEOSCIENCES↗
DOE OSTI2013

Shape memory properties and microstructural evolution of rapidly solidified CuAlBe alloys

In this work, the effects of Be addition on the microstructure and phase transformation temperatures of Cu–12Al–xBe (x = 0.4, 0.5 and 0.6 wt.%) shape memory alloys fabricated by using the arc-melting and melt-spinning techniques have been investigated. X-ray diffraction analysis revealed that the arc-melted alloys consisted of austenitic β{sub 1}, martensitic β{sub 1}′ and γ{sub 2} precipitate phases, whereas melt-spun ribbons were composed of a fully martensitic phase. The average grain size of martensitic phases in melt-spun ribbons was determined by electron microscopy images, showing a decrease with increasing Beryllium (Be) amount. Moreover, it was found that the Be addition in the arc-melted alloys had a distinct effect on the morphology of the γ{sub 2} precipitate phase. Transmission electron microscopy analysis showed that the thickness of martensitic plates in the melt-spun ribbons reduced with increasing Be addition. In a differential scanning calorimeter analysis, no martensitic transformation (M{sub s}) peak was observed in arc-melted alloys, but it was clearly detected in melt-spun ribbons, in which M{sub s} decreased dramatically with increasing Be addition. The improvement in the shape memory ability of melt-spun ribbons was explained in terms of the refinement in grain size and martensitic plates. - Highlights: • The CuAlBe SMAs were produced by means of arc-melter and melt-spinner techniques. • MT was directly obtained in melt-spuns without any intermediate process. • The transformation temperatures decreased with increasing Be amount. • The thickness of martensitic plates in the ribbons reduced with increasing Be. • SMP of CuAl was improved by the addition of Be together with rapid solidification.

36 MATERIALS SCIENCE↗
DOE OSTI2014

In situ X-ray diffraction strain-controlled study of Ti–Nb–Zr and Ti–Nb–Ta shape memory alloys: crystal lattice and transformation features

Phase and structure transformations in biomedical Ti–21.8Nb–6.0Zr (TNZ) and Ti–19.7Nb–5.8Ta (TNT) shape memory alloys (at.%) under and without load in the − 150 to 100 °S temperature range are studied in situ using an original tensile module for a low-temperature chamber of an X-ray diffractometer. Alpha″- and beta-phase lattice parameters, the crystallographic resource of recovery strain, phase and structure transformation sequences, and microstress appearance and disappearance are examined, compared and discussed. For both alloys, the crystallographic resource of recovery strain decreases with temperature increase to become 4.5% for TNZ and 2.5% for TNT alloy (at RT). Loading at low temperatures leads to additional α″-phase formation and reorientation. Heating under load, as compared to strain-free heating, affects the reverse transformation sequence of both alloys in different ways. For TNZ alloy, strain-free heating results in simultaneous ω→β and α″→β transformations, whereas during heating under stress, they are sequential: β + ω→α″ precedes α″→β. For TNT alloy, strain-free heating results in reverse α″→β transformation, whereas during heating under stress, α″→β transformation is preceded by α″-phase reorientation. - Highlights: • Comparative in situ XRD analysis of Ti–Nb–Zr(Ta) shape memory alloys is realized. • Lattice parameters of β- and α″-phases are calculated in the − 150 to + 100 °C range. • The higher the temperature, the lower the α″→β transformation strain. • Loading at low temperatures results in α″-phase formation and reorientation. • Transformation sequences upon heating with and without loading are different.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Active interlocking metasurfaces enabled by shape memory alloys

Interlocking metasurfaces (ILMs) are a newly developed joining technology that relies on arrays of interlocking features that transmit force and constrain motion between adjoining bodies in one or more directions. This study explores harnessing the shape memory effect (SME) in Nickel-Titanium shape memory alloys (NiTi SMAs) in structures fabricated using additive manufacturing (AM) to advance the development of active ILMs by creating unit cells that open or close at specific temperatures. The study encompasses designing and fabricating two distinct interlocking array configurations using near-equiatomic NiTi powder and the laser powder bed fusion (L-PBF) AM technique, following a previously developed AM process optimization framework to manufacture defect-free parts. To guide the design process, finite element analysis (FEA) was employed to predict strain values during engage-disengage cycles. The martensitic transformation characteristics of the ILMs were characterized. Thermomechanical testing revealed that the ILMs demonstrate high locking force once engaged, coupled with complete shape recovery and good cyclic stability. Digital image correlation (DIC) was also employed to validate the FEA predictions during the engage-disengage cycles. The results indicate that NiTi SMA-based ILMs can be designed and fabricated into complex shapes using L-PBF. By leveraging the SME, the functionality of an ILM can be improved upon. The combination of computational modeling, additive manufacturing, and thermomechanical and physical property characterization provides a framework for designing future ILMs out of active materials.

Additive manufacturing↗
DOE OSTI2013

Thermodynamic constitutive model for load-biased thermal cycling test of shape memory alloy

Graphical abstract: - Highlights: • Thermodynamic calculation model for martensitic transformation of shape memory alloy was proposed. • Evolution of the self-accommodation was considered independently by a rate-dependent kinetic equation. • Finite element calculation was conducted for B2–B19′ transformation of Ti–44.5Ni–5Cu–0.5 V (at.%). • Three-dimensional numerical results predict the macroscopic strain under bias loading accurately. - Abstract: This paper presents a three-dimensional calculation model for martensitic phase transformation of shape memory alloy. Constitutive model based on thermodynamic theory was provided. The average behavior was accounted for by considering the volume fraction of each martensitic variant in the material. Evolution of the volume fraction of each variant was determined by a rate-dependent kinetic equation. We assumed that nucleation rate is faster for the self-accommodation than for the stress-induced variants. Three-dimensional finite element analysis was conducted and the results were compared with the experimental data of Ti–44.5Ni–5Cu–0.5 V (at.%) alloy under bias loading.

36 MATERIALS SCIENCE↗
DOE OSTI2018

2D nanocomposite of hexagonal boron nitride nanoflakes and molybdenum disulfide quantum dots applied as the functional layer of all-printed flexible memory device

Highlights: • We have proposed a flexible, rewritable and NVM device based on an advanced 2D nanocomposite. • 2D nanocomposite is synthesized by mixing hBN flakes and MoS{sub 2} QDs. • Entire device was fabricated through extremely simple and highly controllable printing technology. • The RRAM device was tested electrically, mechanically, thermally and chemically. - Abstract: In this study, we have proposed a flexible, rewritable and nonvolatile memory device based on an advanced 2D nanocomposite of hexagonal boron nitride (hBN) flakes and molybdenum disulfide quantum dots (MoS{sub 2} QDs). Complete device fabrication was carried out by using extremely simple and highly controllable all printed technology. The electrical characteristics exhibited by the as developed memory devices included the switching ratio, electrical endurance and retention time of ∼10{sup 3}, 10{sup 3} and 10{sup 4} respectively. The device turned ON and OFF at the SET and RESET threshold voltages of +1.4 V and −1 V respectively. The obtained results of electrical and thermal characterizations exhibited that the switching ratio decreases via either increasing temperature (300 K–380 K) or device size (42 μm–100 μm) hence verifying the formation of conductive filament through the functional layer. Moreover, no major degradation in the switching characteristics was observed even after 1500 bending cycles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

Computational study of clot formation in aneurysms treated with shape memory polymer foam

To prevent aneurysmal rupture, intracranial aneurysms are often treated with endovascular metal coils that fill the aneurysm sac and stimulate thrombus formation, thereby isolating the aneurysm from the arterial flow. Despite its widespread use, this method can result in suboptimal outcomes leading to aneurysm recurrence. Recently, shape memory polymer foam has been proposed as an alternative aneurysm filler. In this work, a computational thrombus model is used to predict the clotting response within idealized 2D aneurysms virtually treated with foam. The results are compared to previously reported clot formation predictions in identical 2D aneurysm geometries filled with simplified endovascular metal coil shapes. Additionally, each of the foam-filled aneurysms reached at least 94% thrombus occlusion regardless of foam pore size or orientation, whereas the final thrombus occlusion within the coil-filled aneurysms varied from 80.8 to 92.2% with many of the cases leaving large areas in the aneurysm neck unfilled. Based on the simulations presented here, shape memory polymer foams may be able to produce more predictable, uniform, and complete clotting results than bare metal coils, independent of foam geometry or orientation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

High-energy synchrotron radiation X-ray diffraction measurements during in situ aging of a NiTi-15 at. % Hf high temperature shape memory alloy

NiTiHf high temperature shape memory alloys (HTSMAs) have begun to show considerable progress in their ability to be manufactured and are now on the cusp of becoming viable alloys for use in the aerospace industry, mainly as actuation devices. By aging the alloys at intermediate temperatures between 450 and up to 700 °C, Ni-rich NiTiHf HTSMAs form the H-phase, a Ni-rich nanoscale precipitate which can be used to strengthen the alloy and improve the shape memory response; however, precipitate phase evolution and growth has not yet been studied in-situ nor have the effects of previous thermo-mechanical processing on their formation. In this study, H-phase precipitate formation is observed experimentally in situ during aging of a Ni-rich NiTiHf alloy using high energy synchrotron radiation X-ray diffraction (SR-XRD) measurements. The effects of prior thermo-mechanical treatments, i.e. hot and cold rolling, on its formation rate and coarsening rate are compared. It is shown that growth of the H-phase can be observed in situ using SR-XRD and the H-phase formation rate seems to exhibit linear growth when aging at 550 °C, while increasing the temperature to 650 °C shows a logarithmic trend that plateaus after approximately 1 h of aging. Other properties such as incubation time, austenite lattice strains, texture evolution, and overall comparison between hot and cold rolling are discussed. New potential peak age conditions are suggested based on the diffraction data and evaluated using three-point bending and TEM imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A long short-term memory embedding for hybrid uplifted reduced order models

In this paper, we introduce an uplifted reduced order modeling (UROM) approach through the integration of standard projection based methods with long short-term memory (LSTM) embedding. Our approach has three modeling layers or components. In the first layer, we utilize an intrusive projection approach to model dynamics represented by the largest modes. The second layer consists of an LSTM model to account for residuals beyond this truncation. This closure layer refers to the process of including the residual effect of the discarded modes into the dynamics of the largest scales. However, the feasibility of generating a low rank approximation tails off for higher Kolmogorov n -width systems due to the underlying nonlinear processes. The third uplifting layer, called super-resolution, addresses this limited representation issue by expanding the span into a larger number of modes utilizing the versatility of LSTM. Therefore, our model integrates a physics-based projection model with a memory embedded LSTM closure and an LSTM based super-resolution model. In several applications, we exploit the use of Grassmann manifold to construct UROM for unseen conditions. We performed numerical experiments by using the Burgers and Navier-Stokes equations with quadratic nonlinearity. Finally, our results show robustness of the proposed approach in building reduced order models for parameterized systems and confirm the improved trade-off between accuracy and efficiency.

42 ENGINEERING↗
DOE OSTI2020

Tuning the Mechanical Properties of Shape Memory Metallic Glass Composites with Brick and Mortar Designs

We use molecular dynamics simulations to characterize the tensile deformation and failure of shape memory alloy-bulk metallic glass composites (BMGCs). As the failure in BMGCs shifts from the MG matrix to the second phase different strategies are required to further improve their mechanical properties. Results show that a staggered brick BMGC displays enhanced ductility with mild strength loss following a homogeneously distributed plasticity. This demonstrates that judiciously designed BMGCs can effectively synergize the mechanical properties of metallic glasses and shape memory alloys by effectively distributing stress and preventing the generation of critical shear bands and premature failure while preserving strength.

36 MATERIALS SCIENCE↗