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At least 181 records · Page 10

Exploring biofiber properties and their influence on biocomposite tensile properties

Biofibers serve as effective reinforcements for neat polylactic acid (PLA) in biocomposites, offering an attractive opportunity to decarbonize the manufacturing sector of the United States by displacing fossil-based reinforcement fibers such as carbon fibers. Also, biofiber production can stimulate economic growth in rural economies, fueling sustainable development. PLA resins are commonly compounded with biofibers to create biocomposites suitable for additive manufacturing. PLA-biofiber composites often exhibit better overall material properties than neat (pure) PLA, but the associations between biofiber properties and the material properties of their biocomposites remain largely unexplored. Hence, this research delves into a comprehensive exploration of diverse biofibers, scrutinizing their physical and chemical attributes, including size, shape, ash content and biochemical composition. The study meticulously analyzes the flow properties of each biofiber and elucidates the ultimate tensile strengths and Young's modulus of corresponding biocomposite samples. Noteworthy correlations between biofiber and biocomposite tensile properties are uncovered, shedding light on critical interrelationships. The study introduces an approach employing regression models to predict the ultimate tensile strength and Young's modulus of biocomposites. These models, validated with a cross-validation technique, exhibit remarkable predictive accuracy, particularly in estimating ultimate tensile strength. © 2024 Oak Ridge National Laboratory managed by UT-Battelle, LLC and The Author(s). Polymer International published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

36 MATERIALS SCIENCE↗

Size-dependent stochastic tensile properties in additively manufactured 316L stainless steel

Recent work in metal additive manufacturing (AM) suggests that mechanical properties may vary with feature size; however, these studies do not provide a statistically robust description of this phenomenon, nor do they provide a clear causal mechanism. Because of the huge design freedom afforded by 3D printing, AM parts typically contain a range of feature sizes, with particular interest in smaller features, so the size effect must be well understood in order to make informed design decisions. This work investigates the effect of feature size on the stochastic mechanical performance of laser powder bed fusion tensile specimens. A high-throughput tensile testing method was used to characterize the effect of specimen size on strength, elastic modulus and elongation in a statistically meaningful way. The effective yield strength, ultimate tensile strength and modulus decreased strongly with decreasing specimen size: all three properties were reduced by nearly a factor of two as feature dimensions were scaled down from 6.25 mm to 0.4 mm. Hardness and microstructural observations indicate that this size dependence was not due to an intrinsic change in material properties, but instead the effects of surface roughness on the geometry of the specimens. Finite element analysis using explicit representations of surface topography shows the critical role surface features play in creating stress concentrations that trigger deformation and subsequent fracture. The experimental and finite element results provide the tools needed to make corrections in the design process to more accurately predict the performance of AM components.

316L stainless steel↗

Reassessing early-age strength development of high-volume fly ash concretes for precast buildings

Increasing beneficial use of fresh or landfilled fly ash as a replacement for Portland cement can be more challenging for the construction of precast buildings or similar applications requiring rapid strength development. Therefore, the framework presented in this paper aims to reassess high-volume fly ash concretes but in the context of facilitating more sustainable precast buildings. More specifically, the framework was used to characterize strength development of concrete mixes with a target minimum 24-hour compressive strength of 24.1 MPa (3500 psi), selected as an example strength development metric to demonstrate the framework, and comprised of 40% Class C, Class F, and landfilled (harvested) fly ash – as a high-volume replacement of Type III or Type IL cement. High-early strength was driven by optimized dosages of commercial grade gypsum and accelerating admixtures, in addition to optimal aggregate packing and mix proportioning strategies. Early-age mechanical properties including compressive strength, modulus of rupture, and modulus of elasticity were reevaluated within 24 hours of batching with respect to common precast production demands. Simple data analyses were then used to highlight cases where currently accepted design provisions for the aforementioned properties are either overly-conservative or unconservative with respect to test data. Furthermore, the framework and demonstration of example mixes presented herein aim to promote confidence for using larger fractions of fresh or landfilled fly ashes for precast buildings to further enhance environmental benefits without sacrificing pertinent early-age structural performance.

42 ENGINEERING↗

Recent advances in the mechanical characterization of shales at nano-to micro-scales: A review

Understanding geomechanical properties of shales, such as stiffness properties and fracture toughness, is important in different areas of petroleum industry-related activities. Nanoscale to microscale experiments on shale samples require a much smaller sample compared to macroscale experiments. This is a major advantage because irregularly-shaped drill cuttings from shales can be used for experimental analyses, such as nanoindentation or atomic force microscopy (AFM). However, characterization of mechanical properties at the nano- to micro-scale is a relatively new addition to classical geomechanical experiments on shales, and there is still a lack of both fundamental knowledge and standard procedures for conducting experiments at this scale. The theoretical principles of nanoindentation-based (Gridded Nanoindentation and Modulus Mapping) and AFM-based experimental methods (PeakForce QNMTM and AFM-IR), a review of the literature results and the major findings are explained in Sections 2 and 3, respectively. These experimental techniques are compared in Section 4. Overall, nanoindentation experiments reveal the anisotropy of organic matter (OM)-rich shales at the nanoscale, and it is shown that gridded nanoindentation is capable of characterizing different minerals with respect to their stiffness properties. The capability of AFM (PeakForce QNMTM) to differentiate between different minerals within OM-rich shales with distinct mechanical properties, in particular stiffness, is also demonstrated. It is shown that AFM-based methods are more straightforward than gridded-nanoindentation to characterize OM-rich shales based on the stiffness of different constituent minerals of OM-rich shales, but nanoindentation can apply higher loads than AFM-based methods. Therefore, they can measure creep properties and fracture toughness of OM-rich shales. Here, it is shown that the OM is the most compliant part of the OM-rich shales, but it is still unclear if thermal maturation has an impact on the stiffness of OM. It is necessary to investigate if there is a relationship between the OM type (kerogen, bitumen, etc.) and mechanical properties such as Young’s modulus and Creep rate.

36 MATERIALS SCIENCE↗

Predicting Elastic Properties of Materials from Electronic Charge Density Using 3D Deep Convolutional Neural Networks

Materials representation plays a key role in machine learning-based prediction of materials properties and new materials discovery. Currently both graph and three-dimensional (3D) voxel representation methods are based on the heterogeneous elements of the crystal structures. Here, we propose to use electronic charge density (ECD) as a generic unified 3D descriptor for materials property prediction with the advantage of possessing close relation with the physical and chemical properties of materials. We developed an ECD-based 3D convolutional neural networks (CNNs) for predicting the elastic properties of materials, in which CNNs can learn effective hierarchical features with multiple convolving and pooling operations. Extensive benchmark experiments over 2170 $Fm\bar3m$ face-centered-cubic materials show that our ECD-based CNNs can achieve good performance for elasticity prediction. Especially, our CNN models based on the fusion of elemental Materials-Agnostic Platform for Informatics and Exploration features and ECD descriptors achieved the best fivefold cross-validation performance. More importantly, we showed that our ECD-based CNN models can achieve significantly better extrapolation performance when evaluated over nonredundant data sets, where there are few neighbor-training samples around test samples. As an additional validation, we evaluated the predictive performance of our models on 329 materials of space group $Fm\bar3m$ by comparing to density functional theory calculated values, which shows a better prediction power of our model for bulk modulus than shear modulus. Because of the unified representation power of ECD, it is expected that our ECD-based CNN approach can also be applied to predict other physical and chemical properties of crystalline materials.

36 MATERIALS SCIENCE↗

Accelerated Self-Healing and Property Recovery in Brush Particle Solids Featuring Brush Dispersity

Brush particles, hybrid materials consisting of polymer chains tethered to particle surfaces, offer tunable properties that make them promising candidates for advanced functional materials. This study investigated the role of chain dispersity in the viscoelastic self-healing of poly (methyl acrylate) (PMA)-based brush particle solids. Increasing the molecular weight dispersity of grafted chains significantly enhanced both strain-to-fracture and toughness of brush particle solids, while the elastic modulus and glass transition temperature were independent of chain dispersity. Cut-and-adhere testing revealed a significant acceleration of the rate of toughness recovery in high-dispersity systems as compared to low-dispersity analogs for which toughness recovery markedly lagged the recovery of Young’s modulus. The results suggest that structure and property recovery in brush particle solids are sensitive to the dynamical heterogeneity of brush canopies and highlight the role of molecular weight dispersity as a design parameter to enable hybrid materials with advanced self-healing ability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shape Dependence of Pressure-Induced Phase Transition in CdS Semiconductor Nanocrystals

Understanding structural stability and phase transformation of nanoparticles under high pressure is of great scientific interest, as it is one of the crucial factors for design, synthesis, and application of materials. Even though high-pressure research on nanomaterials has been widely conducted, their shape-dependent phase transition behavior still remains unclear. Examples of phase transitions of CdS nanoparticles are very limited, despite the fact that it is one of the most studied wide band gap semiconductors. Here we have employed in-situ synchrotron wide-angle X-ray scattering (WAXS) and transmission electron microscopy (TEM) to investigate the high-pressure behaviors of CdS nanoparticles as a function of particle shapes. We observed that CdS nanoparticles transform from wurtzite to rocksalt phase at elevated pressure in comparison to their bulk counterpart. Phase transitions also vary with particle shape—rod-shaped particles show a partially reversible phase transition and the onset of the structural phase transition pressure decreases with decreasing surface-to-volume ratios, while spherical particles undergo irreversible phase transition with relatively low phase transition pressure. Additionally, TEM images of spherical particles exhibited sintering-induced morphology change after high-pressure compression. Calculations of the bulk modulus reveals that spheres are more compressible than rods in the wurtzite phase. These results indicate that the shape of the particle plays an important role in determining their high-pressure properties. Our study provides important insights into understanding of the phase-structure-property relationship, guiding future design and synthesis of nanoparticles for promising applications.

36 MATERIALS SCIENCE↗

Tuning to more compressible phase in TiZrHfNb high entropy alloy by pressure

In this work, the starting nominal Ti 25 Zr 25 Hf 25 Nb 25 high entropy alloy (HEA) has two body centered cubic (BCC) phases with a volume percentage about 100:1, with the primary phase having a much larger bulk modulus (incompressible) than the uniform single-phase HEA. We found that these two phases merged into one single BCC phase at pressures beyond 36 GPa, whose bulk modulus dropped to that of the normal homogeneous HEA. After decompressing, the new phase can be sustained to ambient conditions. We note this abnormal pressure-induced softening was largely related to the lattice distortion evolution and interfacial energy during compression.

36 MATERIALS SCIENCE↗

High-pressure high-temperature synthesis and thermal equation of state of high-entropy transition metal boride

High-entropy transition metal boride (Hf 0.2 Ti 0.2 Zr 0.2 Ta 0.2 Mo 0.2 )B 2 sample was synthesized under high-pressure and high-temperature starting from ball-milled oxide precursors (HfO 2 , TiO 2 , ZrO 2 , Ta 2 O 5 , MoO 3 ) mixed with graphite and boron-carbide. Experiments were conducted in a large-volume Paris Edinburgh press combined with an in-situ Energy Dispersive X-ray Diffraction. The hexagonal AlB 2 phase with an ambient pressure volume V 0 = 27.93 ± 0.03 Å 3 was synthesized at a pressure of 0.9 GPa and temperatures above 1373K. High-pressure high-temperature studies on the synthesized high-entropy transition metal boride sample were performed to 7.6 GPa and 1873 K. The thermal equation of state fitted to the experimental data resulted in an ambient pressure bulk-modulus K 0 = 344 ± 39 GPa, dK/dT = –0.108 ± 0.027 GPa/K, and a temperature dependent volumetric thermal expansion coefficient α = α 0 + α 1 T + α 2 T –2 . The thermal stability combined with a high bulk-modulus establishes this high-entropy transition metal boride as an ultrahard high-temperature ceramic material.

36 MATERIALS SCIENCE↗

A robust three-parameter reference curve for condensed phase materials

Many isothermal equations of state lead to numerical problems under tension conditions due to negative bulk modulus. We summarize the properties of four existing models and devise a continuous non-piecewise reference curve to address this issue. The final functional form contains three fitting parameters that are directly related to the bulk modulus and its pressure derivative at the reference state and at infinite pressures. We also include bounds that guarantee the monotonicity of its pressure derivative in all volume space. To demonstrate the qualitative features of each isotherm, we conduct calibrations against experimental data for cyclotetramethylene tetranitramine, magnesium oxide, gold, and platinum. Furthermore, pressure residuals and root mean square deviations show that the proposed functional form is capable of adequately fitting the data compared to other three-parameter models.

36 MATERIALS SCIENCE↗

Single-beam plasma source deposition of carbon thin films

A single-beam plasma source was developed and used to deposit hydrogenated amorphous carbon (a-C:H) thin films at room temperature. The plasma source was excited by a combined radio frequency and direct current power, which resulted in tunable ion energy over a wide range. The plasma source could effectively dissociate the source hydrocarbon gas and simultaneously emit an ion beam to interact with the deposited film. Using this plasma source and a mixture of argon and C 2 H 2 gas, a-C:H films were deposited at a rate of ~26 nm/min. The resulting a-C:H film of 1.2 µm thick was still highly transparent with a transmittance of over 90% in the infrared range and an optical bandgap of 2.04 eV. Young’s modulus of the a-C:H film was ~80 GPa. The combination of the low-temperature high-rate deposition of transparent a-C:H films with moderately high Young’s modulus makes the single-beam plasma source attractive for many coatings applications, especially in which heat-sensitive and soft materials are involved. Here, the single-beam plasma source can be configured into a linear structure, which could be used for large-area coatings.

14 SOLAR ENERGY↗

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↗

Calibration and validation of the foundation for a multiphase strength model for tin

In this work, the Common Model of Multi-phase Strength and Equation of State (CMMP) model was applied to tin. Specifically, calibrations of the strength-specific elements of the CMMP foundation were developed with a combination of experiments and theory, and then the model was validated experimentally. The first element of the foundation is a multi-phase analytic treatment of the melt temperature and the shear modulus for the solid phases. These models were parameterized for each phase based on ab initio calculations using the software VASP (Vienna Ab initio Simulations Package) based on density functional theory. The shear modulus model for the ambient phase was validated with ultrasonic sound speed measurements as a function of pressure and temperature. The second element of the foundation is a viscoplastic strength model for the phase, upon which strength for inaccessible higher-pressure phases can be scaled as necessary. The stress–strain response of tin was measured at strain rates of 10 -3 to 3 x 10 3 s -1 and temperatures ranging from 87 to 373 K. The Preston–Tonks–Wallace (PTW) strength model was fit to that data using Bayesian model calibration. For validation, six forward and two reverse Taylor impact experiments were performed at different velocities to measure large plastic deformation of tin at strain rates up to ⁠10 5 s -1 . The PTW model accurately predicted the deformed shapes of the cylinders, with modest discrepancies attributed to the inability of PTW to capture the effects of twinning and dynamic recrystallization. Some material in the simulations of higher velocity Taylor cylinders reached the melting temperature, thus testing the multiphase model because of the presence of a second phase, the liquid. In simulations using a traditional modeling approach, the abrupt reduction of strength upon melt resulted in poor predictions of the deformed shape and non-physical temperatures. With CMMP, the most deformed material points evolved gradually to a mixed solid–liquid but never a fully liquid state, never fully lost strength, stayed at the melt temperature as the latent heat of fusion was absorbed, and predicted the deformed shape well.

36 MATERIALS SCIENCE↗

Kohn anomaly and elastic softening in body-centered cubic molybdenum at high pressure

Transition metals in body-centered cubic (bcc) structures under compression can display several novel physical properties because of their complex electronic structures and electron-phonon interactions. Here, we used inelastic x-ray scattering experiments in a diamond-anvil cell up to ∼45 GPa and density-functional theory calculations up to 210 GPa to investigate the phonon dispersions, and electronic and elastic properties of single-crystal molybdenum (Mo). Our results show a pressure-induced Kohn anomaly at 𝑞∼0.5 along the [ξ00] direction in the longitudinal acoustic mode at ∼45 GPa; this anomaly is triggered by the pressure-enhanced Fermi-surface nesting effect. Theoretical calculations show that electron redistributions in the 𝑠-to-𝑑 orbitals of bcc-Mo contribute to the shear modulus anomaly at ∼50 GPa. In contrast, the Young's modulus anomaly in bcc-Mo at ∼210 GPa results from a Lifshitz-type electronic topological transition. In conclusion, our results shed light on the complex electronic behaviors that are associated with macroscopic elastic properties in typical bcc 𝑑-block transition metals under compression.

3-dimensional systems↗

Chemical vapor infiltration of additively manufactured preforms: Pore-resolved simulations and experimental validation

The densification of additively manufactured porous preforms by chemical vapor infiltration (CVI) is studied using pore-resolved simulations and experiments. Experimentally, 3D printed silicon carbide (SiC) preforms are subject to CVI synthesis using methyltrichlorosilane (MTS) precursor to obtain high purity SiC/SiC composites. Optical images of the cross sections of the processed preforms are analyzed to obtain the spatial porosity distribution. The numerical method is based on a level set formulation to capture the spatial distribution and time evolution of the pore scale microstructural characteristics. The coupled transport and kinetic effects are represented using a dimensionless Thiele modulus. Simulations are initialized using representative synthetic preform geometries comprising of packed particles based on the size distribution of the powder used for 3D printing. The simulation results are validated against the experimental observations in terms of total density and the distribution of residual porosity. The densification characteristics, porosity classification, concentration profiles, and structure functions are analyzed as functions of processing temperature and Thiele modulus.

36 MATERIALS SCIENCE↗

High‐Throughput Evaluation of Hardening Coefficients of Eight Alloying Elements in Magnesium

Liquid–solid diffusion couples (LSDCs) are employed to generate a composition gradient in the single‐phase hexagonal closed‐packed (hcp) solid solution with compositions up to the solubility limit of various solutes in Mg. Nanoindentation scanning across the composition gradient in LSDCs allows effective evaluation of composition‐dependent hardness of eight alloying elements (Al, Ca, Ce, Gd, Li, Sn, Y, and Zn) in the hcp Mg phase. The hardening coefficients, an indicator of the potency of solid‐solution hardening, are evaluated from the measured composition‐hardness data and correlated with various materials properties such as atomic radius, shear modulus, and elastic modulus of the solutes. The rank of hardening potency of Al, Gd, Sn, Y, and Zn measured by nanoindentation is in good agreement with that measured by microindentation reported in the literature. The hardening coefficient (potency) from the strongest to the weakest is Ce > Ca > Y ≈ Gd > Zn > Al ≈ Sn > Li in Mg‐based hcp binary solid solutions. The hardening coefficient is found to be closely correlated with the strengthening potency.

36 MATERIALS SCIENCE↗

A Synthetic Hydrogel Composite with the Mechanical Behavior and Durability of Cartilage

Here, we report the first hydrogel with the strength and modulus of cartilage in both tension and compression, and the first to exhibit cartilage-equivalent tensile fatigue strength at 100 000 cycles. These properties are achieved by infiltrating a bacterial cellulose (BC) nanofiber network with a poly(vinyl alcohol) (PVA)–poly(2-acrylamido-2-methyl-1-propanesulfonic acid sodium salt) (PAMPS) double network hydrogel. The BC provides tensile strength in a manner analogous to collagen in cartilage, while the PAMPS provides a fixed negative charge and osmotic restoring force similar to the role of aggrecan in cartilage. The hydrogel has the same aggregate modulus and permeability as cartilage, resulting in the same time-dependent deformation under confined compression. The hydrogel is not cytotoxic, has a coefficient of friction 45% lower than cartilage, and is 4.4 times more wear-resistant than a PVA hydrogel. The properties of this hydrogel make it an excellent candidate material for replacement of damaged cartilage.

36 MATERIALS SCIENCE↗

Facilitating Large‐Scale Snow Shedding from In‐Field Solar Arrays using Icephobic Surfaces with Low‐Interfacial Toughness

Abstract Large‐scale accrual of snow and ice on solar arrays in northern latitudes can cause significant power generation losses during winter. Depending on environmental conditions, snow can encompass a wide range in physical characteristics from dry snow (modulus ≈100 kPa and density ≈0.1 g cm −3 ) to bulk ice (modulus ≈8 GPa and density ≈0.9 g cm −3 ). This variation in snow morphology has made the development of a passive, broad‐spectrum, snow and ice‐shedding surface challenging. Here, the authors develop one of the first surfaces that simultaneously possesses both low‐interfacial strength ( τ˄ ice < 50 kPa) and toughness (Γ ice < 0.5 J m −2 ) with ice. These surfaces, fabricated via the addition of mobile polymer chains/oils to a thin polymeric coating, require extremely low detachment forces for ice, enabling its passive shedding at virtually any accretion length scale. Preliminary evidence that the new surfaces can shed different forms of snow and ice from field‐deployed solar arrays, over a range of subzero temperatures for several weeks, leading to significant increases in power generation is provided. The optically transparent surfaces are easily scalable and can be widely deployed by the solar industry in areas that see persistent snow. Other applications include automotive windshields, LIDAR covers for autonomous vehicles, and cold climate optical sensors.

Dhyani, Abhishek↗