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Results for “elastic modulus”

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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

High-strength 3D printed poly(lactic acid) composites reinforced by shear-aligned polymer-grafted cellulose nanofibrils

This work demonstrates the application of pilot-scale surface functionalization of cellulose nanofibrils (CNFs) by aqueous grafting-through polymerization and subsequent spray drying in 3D printed poly(lactic acid) (PLA) composites. Grafted-CNF composites attain an ultimate tensile strength of 88 ± 3 MPa and a tensile modulus of elasticity of 7.8 ± 1.3 GPa in the printing direction at 20 wt% reinforcement loading. These increases, 42% and 139% over neat PLA, respectively, represent the strongest reported 3D printed CNF/PLA composite to date in the literature. The mechanisms behind these improvements are investigated by comparisons to neat PLA and unmodified spray-dried CNF/PLA controls using melt rheology, dynamic mechanical analysis, and assessment of the reinforcement dispersion. These experiments reveal that improved network formation and shear-induced alignment of the grafted CNFs facilitate the remarkable tensile properties of the printed composites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Strengthening poly(lactic acid) composites with poly(methyl methacrylate) functionalized flax nanofibrils

Biobased reinforcements for poly(lactic acid) (PLA) are needed for more additive manufacturing applications requiring higher strength and sustainability. Flax nanofibrils (FNFs) produced through mechanical refining were explored as a lower energy alternative to cellulose nanofibril (CNF) reinforcements. To compatibilize the FNFs for the PLA matrix, a grafting-through surfactant free emulsion polymerization (SFEP) was performed to functionalize the FNF surface with poly(methyl methacrylate) (PMMA). FNFs produced using different refining energy were functionalized under varying solid contents in suspension. Polymerizations performed at 0.7 wt% FNFs in water yielded the highest degree of PMMA functionality. These optimal conditions were scaled up and the PMMA modified FNFs melt compounded into PLA yielding a 12% increase in tensile strength and 92% increase in the modulus of elasticity as compared to the original PLA. Interestingly, the FNFs with the lowest refining energy yielded the strongest composites using these methods, surpassing the higher refining energy CNF reinforcements. This increase was attributed to improved dispersion of the FNF reinforcements in the PLA matrix that was enabled by the PMMA coating on the FNF surface preventing interfibrillar adhesion and aggregation within the PLA matrix.

Mulligan, Abigail [University of Maine]↗
DOE OSTI2024

Sound speed measurements in shock-compressed cemented Tungsten carbides at pressures up to 100 GPa

To gain insights into thermodynamic states attained during shock compression of cemented tungsten carbide with 3.7 wt.% cobalt binder, we present results of longitudinal sound (release wave) speed measurements and their analysis at peak stresses up to 100 GPa (volumetric compression ratio ~ 15%). The sound speeds are determined using front-surface impact and release-wave overtake plate impact experimental configurations using laser interferometry. The measured sound speed data along with estimates for bulk sound speeds obtained using the fourth-order Birch-Murnaghan EoS and thermodynamics are used to determine the longitudinal moduli and shear moduli of shocked tungsten carbide at the various peak compression states attained in the experiments. Here, the longitudinal sound speeds were found to increase linearly with volume compression ratio from 6.97 ± 0.010 km/s at ambient conditions to 8.26 ± 0.156 km/s at a volume compression ratio of ~ 15%. The corresponding longitudinal elastic moduli also increase nearly linearly with the volume compression ratio but remain consistently lower than their theoretical predictions based on continuum models with no damage. Also, the sensitivity of shear moduli to pressure, as predicted by the Steinberg-Guinan model, is reduced substantially and the shear moduli of cemented WC with 3.7 wt.% Co remains nearly constant at ~ 310 GPa at the various peak compression stress states investigated in the present study.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Neural network potential from bispectrum components: A case study on crystalline silicon

In this article, we present a systematic study on developing machine learning force fields (MLFFs) for crystalline silicon. While the main-stream approach of fitting a MLFF is to use a small and localized training set from molecular dynamics simulations, it is unlikely to cover the global features of the potential energy surface. Additionally, to remedy this issue, we used randomly generated symmetrical crystal structures to train a more general Si-MLFF. Furthermore, we performed substantial benchmarks among different choices of material descriptors and regression techniques on two different sets of silicon data. Our results show that neural network potential fitting with bispectrum coefficients as descriptors is a feasible method for obtaining accurate and transferable MLFFs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The ultrahigh pressure stability of silver: An experimental and theoretical study

We measured the atomic volume of Ag in a toroidal diamond anvil cell to a maximum pressure of 416 GPa and calculated the atomic volume and elastic constants of Ag up to 750 and 460 GPa, respectively. Our density functional theory calculations at 0 K utilize an all-electron fully relativistic method and agree well with our volume measurements, particularly at pressures above ~75 GPa. In this work, we corrected our experimental results for non-hydrostaticity using a line shift analysis, and the resulting Vinet equation of state (EOS) parameters are reported. We find that the uniaxial stress sustained by Ag increases linearly up to 4.5 GPa at a pressure of 416 GPa. Our experimental results indicate that the fcc structure of Ag remains stable to at least 416 GPa at room temperature. Our theoretical results show that C44 increases as pressure increases and reaches a maximum at ~100 GPa above which it begins to decrease, a sign that the fcc structure of Ag is becoming unstable, and at V/V 0 = 0.30, the bcc structure is lower in energy than fcc.

36 MATERIALS SCIENCE↗
DOE OSTI2021

On the temperature and density dependence of dislocation drag from phonon wind

At extreme strain rates, where fast moving dislocations govern plastic deformation, anharmonic phonon scattering imparts a drag force on the dislocations. In this paper, we present calculations of the dislocation drag coefficients of aluminum and copper as functions of temperature and density. We discuss the sensitivity of the drag coefficients to changes in the third-order elastic constants with temperature and density.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Fracture and fatigue of thin crystalline SrTiO 3 membranes

The increasing availability of a variety of two-dimensional materials has generated enormous growth in the field of nanoengineering and nanomechanics. Recent developments in thin film synthesis have enabled the fabrication of freestanding functional oxide membranes that can be readily incorporated in nanomechanical devices. While many oxides are extremely brittle in bulk, recent studies have shown that, in thin membrane form, they can be much more robust to fracture as compared to their bulk counterparts. Here, we investigate the ultimate tensile strength of SrTiO 3 membranes by probing freestanding SrTiO 3 drumheads using an atomic force microscope. We demonstrate that SrTiO 3 membranes can withstand an elastic deformation with an average strain of ~6% in the sub-20 nm thickness regime, which is more than an order of magnitude beyond the bulk limit. Further, we also show that these membranes are highly resilient upon a high cycle fatigue test, surviving up to a billion cycles of force modulation at 85% of their fracture strain, demonstrating their high potential for use in nanomechanical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Discovering exceptionally hard and wear-resistant metallic glasses by combining machine-learning with high throughput experimentation

Lack of crystalline order in amorphous alloys, commonly called metallic glasses (MGs), tends to make them harder and more wear-resistant than their crystalline counterparts. However, finding inexpensive MGs is daunting; finding one with enhanced wear resistance is a further challenge. Relying on machine learning (ML) predictions of MGs alone requires a highly precise model; however, incorporating high-throughput (HiTp) experiments into the search rapidly leads to higher performing materials even from moderately accurate models. Here, we exploit this synergy between ML predictions and HiTp experimentation to discover new hard and wear-resistant MGs in the Fe–Nb–B ternary material system. Several of the new alloys exhibit hardness greater than 25 GPa, which is over three times harder than hardened stainless steel and only surpassed by diamond and diamond-like carbon. This ability to use less than perfect ML predictions to successfully guide HiTp experiments, demonstrated here, is especially important for searching the vast Multi-Principal-Element-Alloy combinatorial space, which is still poorly understood theoretically and sparsely explored experimentally.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The effect of hardness on polymer-bonded pentaerythritol tetranitrate (PETN) explosive impact sensitivity

Handling sensitivity is an important property to assess when working with explosive samples and can be measured using a variety of tests, including drop-weight impact sensitivity. There exists a longstanding interest in the explosives community on the importance of measurable chemical, physical, and mechanical properties of explosives in impact sensitivity. However, most recent work in this area has explored chemical attributes rather than physical and mechanical properties of explosives. In this study, we measure hardness of explosive samples of pentaerythritol tetranitrate and Sylgard binder (XTX) during the curing process. The samples have been characterized for particle morphology through scanning electron microscopy and handling sensitivity through drop-weight impact testing. The relative importance of states of cure, methods of curing, morphology, and age of material are discussed. The data indicate that although there is a notable difference in morphology and mechanical properties for the samples as the polymer-bonded mixtures cure, the resulting changes to mechanical properties have a minimal effect on the sensitivity of the XTX.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The effect of polymer stiffness on magnetization reversal of magnetorheological elastomers

Ultrasoft magnetorheological elastomers (MREs) offer convenient real-time magnetic field control of mechanical properties that provides a means to mimic mechanical cues and regulators of cells in vitro. Here, we systematically investigate the effect of polymer stiffness on magnetization reversal of MREs using a combination of magnetometry measurements and computational modeling. Poly-dimethylsiloxane-based MREs with Young’s moduli that range over two orders of magnitude were synthesized using commercial polymers Sylgard™ 527, Sylgard 184, and carbonyl iron powder. The magnetic hysteresis loops of the softer MREs exhibit a characteristic pinched loop shape with almost zero remanence and loop widening at intermediate fields that monotonically decreases with increasing polymer stiffness. A simple two-dipole model that incorporates magneto-mechanical coupling not only confirms that micrometer-scale particle motion along the applied magnetic field direction plays a defining role in the magnetic hysteresis of ultrasoft MREs but also reproduces the observed loop shapes and widening trends for MREs with varying polymer stiffnesses.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An Eulerian crystal plasticity framework for modeling large anisotropic deformations in energetic materials under shocks

Here, this paper demonstrates a novel Eulerian computational framework for modeling anisotropic elastoplastic deformations of organic crystalline energetic materials (EM) under shocks. While Eulerian formulations are advantageous for handling large deformations, constitutive laws in such formulations have been limited to isotropic elastoplastic models, which may not fully capture the shock response of crystalline EM. The present Eulerian framework for high-strain rates, large deformation material dynamics of EM incorporates anisotropic isochoric elasticity via a hypo-elastic constitutive law and visco-plastic single-crystal models. The calculations are validated against atomistic calculations and experimental data and benchmarked against Lagrangian (finite element) crystal plasticity computations for shock-propagation in a monoclinic organic crystal, octahydro-1,3,5,7-tetranitro-1,3,5,7 tetrazocine (β-HMX). The Cauchy stress components and the resolved shear stresses calculated using the present Eulerian approach are shown to be in good agreement with the Lagrangian computations for different crystal orientations. The Eulerian framework is then used for computations of shock-induced inert void collapse in β-HMX to study the effects of crystal orientations on hotspot formation under different loading intensities. The computations show that the hotspot temperature distributions and the collapse profiles are sensitive to the crystal orientations at lower impact velocities (viz., 500 m/s); when the impact velocity is increased to 1000 m/s, the collapse is predominantly hydrodynamic and the role of anisotropy is modest. The present methodology will be useful to simulate energy localization in shocked porous energetic material microstructures and other situations where large deformations of single and polycrystals govern the thermomechanical response.

42 ENGINEERING↗
DOE OSTI2022

Drag reduction and the Vogel exponent of a flexible beam in transient shear flows

Interactions between a flexible beam and a fluid in a channel are of great relevance to biological hairy surfaces, aquatic vegetation, marine life (e.g., fish gills), and many industrial systems alike. While steady state response of a beam to such flows is fairly well-explored, their behavior in the transient regime is not fully understood. Here, a series of numerical simulations are performed to study the laminar Couette flow of an incompressible viscous fluid past an elastic beam in a two-dimensional channel. The flexible beam is perpendicular to the direction of flow, and its base is fixed to the stationary bottom of the channel. We measure the evolution of the Vogel exponent, drag reduction, and reconfiguration number during the transient and steady-state response of the fluid–structure system for different geometrical and physical properties. Our benchmark shows a good agreement between numerical and experimental observations. Our results show that the system's steady-state response at different bulk-fluid velocities can be reproduced by investigating the shear flow response during the transient regime. We define a new variable that characterizes the evolution of the local velocity profile in the proximity of the free end of the beam and use that to characterize the transient-regime response. The analysis yields insight into the competing effects of elasticity of the beam and non-linear flow response.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Contactless excitation of acoustic resonance in insulating wafers

Contactless excitation and detection of high harmonic acoustic overtones in a thin insulator single crystal are described using radio frequency spectroscopy techniques. Single crystal [001] silicon wafer samples were investigated, one side covered with a Nb thin film, the common starting point for the fabrication of quantum devices. Additionally, the coupling between electromagnetic signals and mechanical oscillation is achieved from the Lorentz force generated by an external magnetic field. This method is suitable for any sample with a metallic surface or covered with a thin metal film. High resolution measurements of the temperature dependence of the sound velocity and elastic constants of silicon are reported and compared with known results.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Memory in aging colloidal gels with time-varying attraction

Here, we report a combined rheology, x-ray photon correlation spectroscopy, and modeling study of gel formation and aging in suspensions of nanocolloidal spheres with volume fractions of 0.20 and 0.43 and with a short-range attraction whose strength is tuned by changing temperature. Following a quench from high temperature, where the colloids are essentially hard spheres, to a temperature below the gel point, the suspensions form gels that undergo aging characterized by a steadily increasing elastic shear modulus and slowing, increasingly constrained microscopic dynamics. The aging proceeds at a faster rate for stronger attraction strength. When the attraction strength is suddenly lowered during aging, the gel properties evolve non-monotonically in a manner resembling the Kovacs effect in glasses, in which the modulus decreases and the microscopic dynamics become less constrained for a period before more conventional aging resumes. Eventually, the properties of the gel following the decrease in attraction strength converge to those of a gel that has undergone aging at the lower attraction strength throughout. The time scale of this convergence increases as a power law with the age at which the attraction strength is decreased and decreases exponentially with the magnitude of the change in attraction. A model for gel aging in which particles attach and detach from the gel at rates that depend on their contact number reproduces these trends and reveals that the non-monotonic behavior results from the dispersion in the rates that the populations of particles with different contact number adjust to the new attraction strength.

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

Computational synthesis of a new generation of 2D-based perovskite quantum materials

Perovskite-based optoelectronic devices have emerged as a promising energy source due to their potential for scalable production. This study introduces “perovskene,” a novel class of 2D materials derived from the ABC3-like perovskites, synthesized via a data-driven, high-throughput computational strategy. We harness machine learning and multitarget deep neural networks to systematically investigate the structure–property relations, paving the way for targeted material design and optimization in fields such as renewable energy, electronics, and catalysis. The characterization of over 1500 synthesized structures shows that more than 500 structures are stable, revealing properties such as ultra-low work function and large magnetic moment, underscoring the potential for advanced technological applications.

2D materials↗
DOE OSTI2024

Enhancing high-fidelity neural network potentials through low-fidelity sampling

The efficacy of neural network potentials (NNPs) critically depends on the quality of the configurational datasets used for training. Prior research using empirical potentials has shown that well-selected liquid–solid transitional configurations of a metallic system can be translated to other metallic systems. This study demonstrates that such validated configurations can be relabeled using density functional theory (DFT) calculations, thereby enhancing the development of high-fidelity NNPs. Training strategies and sampling approaches are efficiently assessed using empirical potentials and subsequently relabeled via DFT in a highly parallelized fashion for high-fidelity NNP training. Our results reveal that relying solely on energy and force for NNP training is inadequate to prevent overfitting, highlighting the necessity of incorporating stress terms into the loss functions. To optimize training involving force and stress terms, we propose employing transfer learning to fine-tune the weights, ensuring that the potential surface is smooth for these quantities composed of energy derivatives. This approach markedly improves the accuracy of elastic constants derived from simulations in both empirical potential-based NNPs and relabeled DFT-based NNPs. Overall, this study offers significant insights into leveraging empirical potentials to expedite the development of reliable and robust NNPs at the DFT level.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Analysis of differential scanning calorimetry data for aged plutonium

Differential scanning calorimetry data for samples of a 52 year old plutonium alloy with 3.3 at. % Ga that were heated beyond the melting point is analyzed using transition state theory to find activation energies for the δ to ε and ε to liquid phase transitions. A Bayesian statistical method involving a Gaussian process model is used to find mean values and confidence intervals for the activation energies. The activation energy for the δ to ε phase transition increases by 3.3 ± 3.8% per decade, relative to the case when all age related plutonium lattice point defects have been removed through annealing. The corresponding increase in activation energy for the ε to liquid transition is shown to be 7.1 ± 1.8% per decade. It is postulated that the change in activation energy with age for both phase transitions is caused, in part, by the accumulation of the same type of lattice point defects associated with the observed increase in elastic bulk modulus over time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Proton radiation effects in indium oxide using cascade molecular dynamics simulations

Metal oxide (MO) semiconductors, characterized by their wide band gaps and notable charge transport properties, are promising candidates for electronic applications in extreme environments, including near-Earth space. However, atomistic simulations of radiation–matter interactions in MOs remain challenging due to the limitations of existing interatomic potentials, which often fail to capture both the short-range repulsive forces essential for radiation damage modeling and the long-range electrostatic effects governing defect evolution. In this work, we develop a customized interatomic potential tailored for radiation damage simulations in indium oxide (In 2 O 3 ) as a model system, a representative MO material. Our potential integrates the Ziegler-Biersack-Littmark potential to accurately describe short-range interactions with Buckingham and Coulombic potentials to account for long-range forces. We perform molecular dynamics simulations of low-energy proton irradiation using this custom potential. We employ the primary knock-on atom (PKA) cascade method to study atomic displacements and primary defect formation. Simulations were conducted for 1 keV proton irradiation in four randomly chosen directions, and PKA-driven defect analyses at 5, 10, and 15 keV to examine the effects of direction and energy level on damage generation. Our results provide insight into the impact of irradiation direction and energy level on the cascade evolution and defect formation mechanisms.

Atomistic simulations↗