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Results for “memory effects”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism

The Mori-Zwanzig formalism for coarse-graining a complex dynamical system typically introduces memory effects. The Markovian assumption of delta-correlated fluctuating forces is often employed to simplify the formulation of coarse-grained (CG) models and numerical implementations. However, when the time scales of a system are not clearly separated, the memory effects become strong and the Markovian assumption becomes inaccurate. To this end, we incorporate memory effects into CG modeling by preserving non-Markovian interactions between CG variables, and the memory kernel is evaluated directly from microscopic dynamics. For a specific example, molecular dynamics (MD) simulations of star polymer melts are performed while the corresponding CG system is defined by grouping many bonded atoms into single clusters. Then, the effective interactions between CG clusters as well as the memory kernel are obtained from the MD simulations. The constructed CG force field with a memory kernel leads to a non-Markovian dissipative particle dynamics (NM-DPD). Quantitative comparisons between the CG models with Markovian and non-Markovian approximations indicate that including the memory effects using NM-DPD yields similar results as the Markovian-based DPD if the system has clear time scale separation. However, for systems with small separation of time scales, NM-DPD can reproduce correct short-time properties that are related to how the system responds to high-frequency disturbances, which cannot be captured by the Markovian-based DPD model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ion fluxes and memory effects in an Ar–O 2 modulated radiofrequency-driven atmospheric pressure plasma jet

In this work we used molecular beam mass spectrometry to characterize ion fluxes produced by a modulated radiofrequency (RF)-driven atmospheric pressure plasma jet operating in a homogeneous gas environment (Ar + 1% O 2 ). The influence of the RF modulation frequency (100 Hz to 20 kHz) on the ion fluxes was investigated by time-resolved measurements, and the lifetimes of the dominant ions, O 2 + , NO + , O − , O 2 − and O 3 − , were found to be 28 ± 2, 117 ± 8, 7.3 ± 0.4, 17 ± 1 and 23 ± 2 μs, respectively. The absolute ion densities in the near afterglow region were found to be of the order of 1011 cm−3. Significant differences in the dynamics of the positive and negative ions were found; these are explained by the presence of electrons at similar densities in the afterglow produced by electron detachment reactions from negative ions due to the large concentrations of atomic oxygen and singlet delta oxygen. Transitions in ion flux dynamics for different modulation frequencies and at the startup of the plasma were analyzed together with intensified charge coupled device images recording the plasma propagation in order to assess the dynamics of plasma plume propagation and how it is impacted by ‘memory effects’. Quantitative measurements of the ion densities enabling these memory effects are reported. The results in this paper highlight the tremendous impact of memory effects on plasma propagation and the corresponding pre-ionization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Intrinsic two-way shape memory effect in a Ni-Mn-Sn metamagnetic shape memory microwire

We report an intrinsic two-way shape memory effect with a fully recoverable strain of 1.0% was achieved in an as-prepared Ni 50 Mn 37.5 Sn 12.5 metamagnetic shape memory microwire fabricated by Taylor-Ulitovsky method. This two-way shape memory effect is mainly owing to the internal stress caused by the retained martensite in austenite matrix, as revealed by transmission electron microscopy observations and high-energy X-ray diffraction experiments. After superelastic training for 30 loading/unloading cycles at room temperature, the amount of retained martensite increased and the recoverable strain of two-way shape memory effect increased significantly to 2.2%. Furthermore, a giant recoverable strain of 11.2% was attained under a bias stress of 300 MPa in the trained microwire. These properties confer this microwire great potential for micro-actuation applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology

Abstract. Vegetation phenology plays a key role in controlling the seasonality of ecosystem processes that modulate carbon, water and energy fluxes between the biosphere and atmosphere. Accurate modelling of vegetation phenology in the interplay of Earth's surface and the atmosphere is thus crucial to understand how the coupled system will respond to and shape climatic changes. Phenology is controlled by meteorological conditions at different timescales: on the one hand, changes in key meteorological variables (temperature, water, radiation) can have immediate effects on the vegetation development; on the other hand, phenological changes can be driven by past environmental conditions, known as memory effects. However, the processes governing meteorological memory effects on phenology are not completely understood, resulting in their limited performance of vegetation phenology represented in land surface models. A deep learning model, specifically a long short-term memory network (LSTM), has the potential to capture and model the meteorological memory effects on vegetation phenology. Here, we apply the LSTM to model the vegetation phenology using meteorological drivers and high-temporal-resolution canopy greenness observations through digital repeat photography by the PhenoCam network. We compare a multiple linear regression model, a no-memory-effect LSTM model and a full-memory-effect LSTM model to predict the whole seasonal greenness trajectory and the corresponding phenological transition dates across 50 sites and 317 site years during 2009–2018, covering deciduous broadleaf forests, evergreen needleleaf forests and grasslands. Results show that the deep learning model outperforms the multiple linear regression model, and the full-memory-effect LSTM model performs better than the no-memory-effect model for all three plant function types (median R2 of 0.878, 0.957 and 0.955 for broadleaf forests, evergreen needleleaf forests and grasslands). We also find that the full-memory-effect LSTM model is capable of predicting the seasonal dynamic variations of canopy greenness and reproducing trends in shifting phenological transition dates. We also performed a sensitivity analysis of the full-memory-effect LSTM model to assess its plausibility, revealing its coherence with established knowledge of vegetation phenology sensitivity to meteorological conditions, particularly changes in temperature. Our study highlights that (1) multi-variate meteorological memory effects play a crucial role in vegetation phenology, and (2) deep learning opens up new avenues for improving the representation of vegetation phenological processes in land surface models via a hybrid modelling approach.

Geology↗
DOE OSTI2022

Two-step annealing induced structural rejuvenation: A cause for memory effect in metallic glasses

The structural origin of the memory effect is still elusive in glassy materials. Here, in this letter, the memory effect in a series of metallic glasses (MGs) is observed by two step annealing using differential scanning calorimetry (DSC) and molecular dynamics simulations. It demonstrates that the Kovacs peak can be reflected from not only the system potential energy but also the atomic dynamics, showing the memory effect could originate from the formation of more loose packing configurations around mobile atoms by structural rejuvenation in the second step of high temperature annealing. In contrast, the high-low temperature annealing protocol can only induce the monotonic relaxation. Therefore, our results pave a pathway to better understand the origin of memory effect in MGs and other glassy materials from their dynamics and local atomic structure.

Memory effect↗
DOE OSTI2021

Shape memory effect in metallic glasses

Shape memory effect (SME), mainly present in crystalline Ti-Ni alloys, is basically missing in metallic glasses (MGs) that lack the long-range periodic order of crystals. In this work, we report experimental results of SME in annealed MGs, in which the low-energy configuration state recovery is observed by both differential scanning calorimetry and X-ray photon correlation spectroscopy. We elucidate the origin of SME in MGs under the potential energy landscape framework, i.e., after annealing, the energy of MGs enters into a deep basin and atoms are located in the low-energy configuration state. Albeit deviating from their relative stable configurations by temperature changes, atoms in the annealed MGs tend to return to the low-energy atomic configurations along certain trajectories as pre-annealing temperature is approached, These results could extend the application of MGs as functional materials by directionally manipulating their energy states via annealing and rejuvenation.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Influence of Detwinning on the Shape Memory Effect in Ni{sub 55}Fe{sub 18}Ga{sub 27} Single Crystals

Deformation mechanisms, one-way and two-way shape memory effects were studied in the mode of compression in the [011] single crystal of the Ni{sub 55}Fe{sub 18}Ga{sub 27} alloy where the detwinning occurred during deformation and in the [001] single crystal where the detwinning was forbidden. It was found that the [001] and [011] crystals deformed by different mechanisms during compression to 5% (reorientation was in [001] crystal, and the reorientation and detwinning were in [011] crystal) and from 15 to 20% (the 14 M → L1{sub 0} transition was in [001] crystal and plastic deformation of 14 M phase was in [011]). The compression of both single crystals from 5 to 15% occurred due to the same mechanisms: the 10 M ↔ 14 M transformation and the plastic deformation of the 14 M martensite. The 14 M and L1{sub 0} phases were stable under load, and they transformed to the 10 M martensite on unloading. It was shown that the crystal orientation and detwinning hardly affected the value of the one-way shape memory effect since both crystals were in the 10 M martensite after preliminary deformation. In this case, the transformation of 10 M martensite to the austenite on heating was accompanied by a strain of about 5% and this was the maximum value of the shape memory effect. It was found that the detwinning significantly affected the temperature ranges of strain recovery. In the [011] crystal, the strain recovered in a very narrow interval on heating (1-2°C), whereas in the [001] crystal the shape memory effect was observed in “normal” temperature range (~ 10°C). The detwinning resulted in the formation of a large oriented internal stress during the preliminary deformation that increased the value of the two-way shape memory effect that was observed in [011] crystals in comparison with the [001] crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2024

From shockwaves to the gravitational memory effect

We study the relationship between shockwave geometries and the gravitational memory effect in four-dimensional asymptotically flat spacetime. In particular, we show the ’t Hooft commutation relations of shockwave operators are equivalent to the commutation relation between soft and Goldstone modes parametrizing a sector of the gravitational phase space. We demonstrate this equivalence via a diffeomorphism that takes a shockwave metric to a metric whose transverse traceless component is the gravitational memory. The shockwave momentum in ’t Hooft’s analysis is related to the soft graviton mode, which is responsible for the memory effect, while the shift in the shockwave position is related to the Goldstone mode. This equivalence opens new directions to utilize the gravitational memory effect to explore the observational implications of shockwave geometries in flat space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Fractionation of Lignin for Selective Shape Memory Effects at Elevated Temperatures

We report a facile approach to control the shape memory effects and thermomechanical characteristics of a lignin-based multiphase polymer. Solvent fractionation of a syringylpropane-rich technical organosolv lignin resulted in selective lignin structures having excellent thermal stability coupled with high stiffness and melt-flow resistance. The fractionated lignins were reacted with rubber in melt-phase to form partially networked elastomer enabling selective programmability of the material shape either at 70 °C, a temperature that is high enough for rubbery matrix materials, or at an extremely high temperature, 150 °C. Utilizing appropriate functionalities in fractionated lignins, tunable shape fixity with high strain and stress recovery, particularly high-stress tolerance were maintained. Detailed studies of lignin structures and chemistries were correlated to molecular rigidity, morphology, and stress relaxation, as well as shape memory effects of the materials. The fractionation of lignin enabled enrichment of specific lignin properties for efficient shape memory effects that broaden the materials’ application window. Electron microscopy, melt-rheology, dynamic mechanical analysis and ultra-small angle neutron scattering were conducted to establish morphology of acrylonitrile butadiene rubber (NBR)-lignin elastomers from solvent fractionated lignins.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multilayered microstructures with shape memory effects for vertical deployment

This paper presents a fabrication and characterization of multilayered microstructures with shape memory effects enabling large vertical deployment under electro-thermal actuation. Our previous research demonstrated vertical deployment of such microstructures by the effect of thermal mismatch. Development of equiatomic NiTi layers in the multilayered microstructure is investigated further for shape memory effects. Multilayered microstructures are built by sputtered NiTi layers and a lift-off process. Negative photoresist ma-N1420 enables clean lift-off of 500 nm thick NiTi layers by forming a significant undercut profile after development. The parametric study on co-sputter powers for Ti and Ni 50 Ti 50 targets suggests that 100 W RF on Ti target and 200 W DC on Ni 50 Ti 50 target can deposit Ni 49.62 Ti 50.38 layers. X-Ray Diffraction (XRD) and Atomic Force Microscopy (AFM) were used to study the crystal structures and surface topography of NiTi layers. XRD results of post-annealed Ni 49.62 Ti 50.38 layers show coexistence of austenite and martensitic phases at room temperature, suggesting that the transformation temperature of such NiTi layers should be approximate 20 °C. The surface topography of Ni 49.62 Ti 50.38 layers reveals substantial increase of surface roughness at ambient conditions after the annealing. Experimental verification of the multilayered microstructure for vertical deployment was carried out by Signatone Probe Station and Dual Scanning Electron Microscope/Focused Ion Beam (SEM/FIB) system. Finally, a vertical deployment of the two-dimensional (2D) multilayered microstructures for three-dimensional (3D) can be detected by applying a constant voltage of 0.04 V, and the expected 3D deployment displacement is enlarged from 2 μm to 10 μm by introducing the shape memory effect.

42 ENGINEERING↗
DOE OSTI2024

The melt memory effects in polymer crystallization

This paper presents a systematic review of the literature on the melt memory effects observed in polymers, an area that has engendered considerable debate for over 50 years. Recent advances in experimental techniques have provided fresh insights into how a polymer's thermal history influences its recrystallization behavior. It has been observed that given other conditions unchanged, the crystallization temperature during recrystallization decreases with an increase in the melt temperature T s above the melting point T m until a critical melt temperature is attained. This phenomenon also extends to the half-time of crystallization and the secondary structures, such as lamellar thickness, of semi-crystalline polymers. Despite these findings, a comprehensive constitutive model that encapsulates polymer melt memory effects remains elusive. Cutting-edge instrumentation, including in situ small and wide-angle X-ray scattering, temperature-controlled Fourier transform infrared spectroscopy, and flash differential scanning calorimetry, have posed significant challenges to the traditional nucleation and growth models established in the 1970s. These models are foundational to our understanding of polymer crystallization, which is an integral part of polymer processing and production. In this review, the historical contours of this discourse are traced, with an examination of both the recent experimental breakthroughs and theoretical advancements pertinent to polymer melt memory effects. In conclusion, this paper delves into the prevailing theories of polymer nucleation and crystallization and engages with theoretical discussions and numerical simulations that attempt to elucidate and rationalize these melt memory phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advances in relaxation and memory effects of magnetic nanoparticles for biomedical applications

Functionalized magnetic nanoparticles are pivotal in magnetic resonance imaging, computed tomography, controlled drug delivery, and hyperthermia treatments due to their exceptional magnetic relaxation and functional properties. The magnetic core composition and structure significantly affects the complex magnetic properties of these nanoparticles necessitating a thorough examination of magnetism fundamentals related to these systems. One important aspect is the ability of magnetic nanoparticles to retain previous magnetic state configurations known as memory effect, primarily governed by domain structure and magnetic anisotropy. Despite its relevance to advanced applications, comprehensive studies on magnetic relaxation and memory effects remain limited. Here, the present review aims to bridge this gap by investigating relaxation mechanisms, synthesis strategies, and applications, fostering further innovation. It investigates the memory effects and their dependence on particle composition and morphology along with key synthesis techniques for large-scale production in industrial adoption. Structured into focused sections on magnetic properties and their influence on biomedical and technological applications, this review provides essential insights into memory effects, magneto-relaxation mechanisms, influencing factors, and both experimental and theoretical methodologies. It also delves into computational modelling and AI-driven design, which are revolutionizing the prediction, discovery, and optimization of materials with tailored properties.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Anomalous memory effect in the breakdown of low-pressure argon in a long discharge tube

The characteristics of breakdown of argon in a long tube (with a gap length of 75 cm and diameter of 2.8 cm) at pressures of 1 and 5 Torr and stationary discharge currents of 5–40 mA were studied experimentally. The breakdown was initiated by paired positive voltage pulses with a rise rate of ∼10{sup 8}–10{sup 9} V/s and duration of ∼1–10 ms. The time interval between pairs was varied in the range of Τ ∼ 0.1–1 s, and that between pulses in a pair was varied from τ = 0.4 ms to ≈Τ/2. The aim of this work was to detect and study the so-called “anomalous memory effect” earlier observed in breakdown in nitrogen. The effect consists in the dynamic breakdown voltage in the second pulse in a pair being higher than in the first pulse (in contrast to the “normal” memory effect, in which the relation between the breakdown voltages is opposite). It is found that this effect is observed when the time interval between pairs of pulses is such that the first pulse in a pair is in the range of the normal memory effect of the preceding pair (under the given conditions, Τ ≈ 0.1–0.4 s). In this case, at τ ∼ 10 ms, the breakdown voltage of the second pulse is higher than the reduced breakdown voltage of the first pulse. Optical observations of the ionization wave preceding breakdown in a long tube show that, in the range of the anomalous memory effect and at smaller values of τ, no ionization wave is detected before breakdown in the second pulse. A qualitative interpretation of the experimental results is given.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Controlling shape memory effects in NiTi thin films grown on Ru seed layer

NiTi thin films with robust shape memory effects and low deposition temperatures are greatly desired for microelectronic devices. However, sub-micron films deposited below 425 °C usually have amorphous structure and must be post-annealed to achieve full crystallization. In this article, using Ru as a seed layer, we demonstrate growth of NiTi films as thin as 120 nm with in-situ crystallization at 325 °C. NiTi thin films with a wide range of growth parameters including deposition temperature and film thickness were investigated. Shape memory effects were characterized using stress bow and resistivity studies. Structural information across the R-phase to austenite transformation was obtained using X-ray diffraction. NiTi thin films exhibited a narrow hysteresis during R-phase to austenite phase transition near 60 °C while possessing good shape memory properties.

36 MATERIALS SCIENCE↗