Elastic Properties Research Articles

Effects of component ratios on the properties of sweet potato-oat composite dough and the quality of its steamed cake.

To enhance the value proposition of sweet potato and oat while broadening their applicability in further processing, this study systematically investigated the impact of oat flour incorporation ratios (5%-25% of sweet potato dry weight) on the quality attributes of sweet potato-oat composite dough and its resulting steamed cake products. The results showed that the addition of oat flour could promote the rheological, water retention, and thermomechanical properties of the composite dough and improve the internal microstructure, specific volume, texture, and other processing properties of the steamed cake products. The rheology, water retention, and protein stability of the dough were maximized when the proportion of oat flour was 25%. The textural properties of steamed cakes, hardness, elasticity, cohesion, adhesion, chewiness, and recovery significantly increased (p<0.05) and viscosity significantly decreased (p<0.05) with the addition of oat flour. It is noteworthy that thermodynamic properties, internal structure of the dough, and air holding capacity, which are critical for processing, showed the best results at 20% oat flour addition. Therefore, the addition of 20%-25% oats is recommended to produce composite doughs with optimal quality and processing characteristics. PRACTICAL APPLICATION: As living standards improve, traditional cereals may no longer able to meet people's health needs. Therefore, there is an urgent consumer demand for nutritious, tasty alternatives to staple foods. In this study, oat flour and sweet potato mash were mixed to make sweet potato-oat cake, and the effect of ingredient ratio on the performance and quality of composite dough containing sweet potato-oat flour was analyzed, thus proposing an innovative approach to the research, development, and industrial production of sweet potato and oat food products.

Molecular shape, elastic constants and spontaneous twist in chiral and achiral nematics: insights from a generalised Maier–Saupe framework

ABSTRACT Ordinary nematic liquid crystals have a uniform director field as ground state. However, there are relevant examples of spontaneously twisted nematic states, not only in chiral, but also in achiral materials. Different twist configurations can be found, with the director modulation along the twist axis, as in the cholesteric and in the twist-bend nematic phase, or perpendicular to it, as in blue phases and in skyrmion structures. Here, we develop a generalised Maier–Saupe theory to calculate the thermodynamic and elastic properties, included saddle-splay, of nematics made of particles whose shape can be described as a distorted rod. This turns out to be a powerful approach for screening the relation between the molecular shape and the formation of modulated nematic phases. Application to the paradigmatic models of banana-shaped and helical particles allows us to identify the role of distinct shape features, such as curvature and chirality, and the distinct mechanisms by which these promote twisted configurations.

Nonlinear Elastic Bottlebrush Polymer Hydrogels Modulate Actomyosin Mediated Protrusion Formation in Mesenchymal Stromal Cells.

The nonlinear elasticity of many tissue-specific extracellular matrices is difficult to recapitulate without the use of fibrous architectures, which couple strain-stiffening with stress relaxation. Herein, bottlebrush polymers are synthesized and crosslinked to form poly(ethylene glycol)-based hydrogels and used to study how strain-stiffening behavior affects human mesenchymal stromal cells (hMSCs). By tailoring the bottlebrush polymer length, the critical stress associated with the onset of network stiffening is systematically varied, and a unique protrusion-rich hMSC morphology emerges only at critical stresses within a biologically accessible stress regime. Local cell-matrix interactions are quantified using 3D traction force microscopy and small molecule inhibitors are used to identify cellular machinery that plays a critical role in hMSC mechanosensing of the engineered, strain-stiffening microenvironment. Collectively, this study demonstrates how covalently crosslinked bottlebrush polymer hydrogels can recapitulate strain-stiffening biomechanical cues at biologically relevant stresses and be used to probe how nonlinear elastic matrix properties regulate cellular processes.

Computational investigation of the structural, elastic, electronic, and thermodynamic properties of chloroperovskites GaXCl3 (X = Be, Ca, or Sr) using DFT framework

In this study, we employed the pseudopotential plane wave approach to examine the influence of the X atom (X = Be, Ca, or Sr) on the physical properties of isostructural chloroperovskites GaXCl3. The GGA-PBEsol functional was employed to simulate the exchange–correlation interactions. The computed equilibrium lattice parameters exhibit a high level of concordance with the existing theoretical findings. The cohesion energy and enthalpy of formation were computed to verify the energetic stability of the materials under consideration. The determined values of the single-crystal elastic constants (Cij) indicate that GaBeCl3 remains mechanically stable up to a hydrostatic pressure of 18 GPa. Similarly, GaCaCl3 preserves its stability up to 5 GPa, while GaSrCl3 remains mechanically stable up to 1.25 GPa. The projected Cij values were used to estimate several elastic moduli and related properties, including the shear and bulk moduli, sound wave speeds, Young’s modulus, Poisson’s ratio, and Debye temperature. The energy band structures of the studied compounds, as predicted by the HSE06 functional, demonstrate their wide bandgap semiconductor nature. Specifically, GaBeCl3 demonstrates an indirect bandgap of 3.828 eV, while GaCaCl3 reveals an indirect bandgap of 4.612 eV and GaSrCl3 has an indirect bandgap of 4.405 eV. The quasiharmonic Debye approach was employed to examine various thermal parameters, including the temperature dependence of the unit cell volume, bulk modulus, expansion coefficient, Debye temperature, isochoric and isobar heat capacities, Grüneisen parameter, and entropy function. It has been shown that GaBeCl3 demonstrates a lower thermal expansion coefficient and a higher Debye temperature in comparison to GaCaCl3 and GaSrCl3.

Study of structural, dynamical stability, electronic magnetic and optical properties of RbSnO3 oxide perovskite compound using the density functional theory approach

This study investigates the structural, phonon, elastic, electronic, magnetic and optical properties of cubic perovskite RbSnO3. The calculations are based on the linearized augmented plane wave method with total potential (FP-LAPW), implemented in the Wien2k code; two approximations are used for calculate properties, PBE-GGA and TB-mBJ . The values of the tolerance factor and the formation energy of this material indicate that it is stable in the cubic structure of Pm3̅m symmetry. The Born criteria for the compound under study confirm its mechanical stability, while its phonon dispersion curves confirm its dynamic stability. The results of the electronic and magnetic properties show that the compound is ferromagnetic (FM) semi-metallic (DM) with semiconductor behavior in the majority spin channel and with an indirect gap in the M → Γ direction and having a total magnetic moment equal to 1 μB and a Curie temperature equal to 527 K. Optical spectra of the compound show high optical conductivity in the infrared region and towards the end of the spectrum at around 6 eV, high reflection in the infrared region with a maximum at 0.25 eV, and high absorption in the ultraviolet region at 6 eV. In view of these results, the RbSnO3 perovskite can be a promising candidate for spintronics applications as it can be used in optical devices working in the ultraviolet (UV) light region.

Multiscale modeling and prediction of elastic properties of MWCNT- and RHA-reinforced AlP0507 matrix composite

Multiscale modeling and prediction of elastic properties of MWCNT- and RHA-reinforced AlP0507 matrix composite

Reprocessable, Highly Transparent Ionic Conductive Elastomers Based on β-Amino Ester Chemistry for Sensing Devices.

Ionic conductive elastomers (ICEs) exhibit a compelling combination of ionic conductivity and elastic properties, rendering them excellent candidates for stretchable electronics, particularly in applications like sensing devices. Despite their appeal, a significant challenge lies in the reprocessing of ICEs without compromising their performance. To address this issue, we propose a strategy that leverages covalent adaptable networks (CANs) for the preparation of ICEs. Specifically, β-amino ester bonds as dynamic motifs are incorporated into a poly(ethylene oxide) network containing lithium bis(trifluoromethane) sulfonimide (LiTFSI) salt. LiTFSI-containing β-amino ester networks (LBAEs) exhibit superb transparency (94%), thermal stability (>280 °C), and modest conductivity (0.00576 mS·cm-1 at 20 °C), and some LBAEs maintain operational capability across a wide temperature range (-20 to 100 °C). By regulating the lithium salt content, the mechanical properties, conductivities, and viscoelastic behaviors can be tailored. Benefiting from these features, LBAEs have been successfully applied in sensing devices for monitoring human motion (e.g., finger bending, swallowing, and clenching). Notably, even after four reprocessing cycles, LBAEs demonstrate structural integrity and maintain their operational capability. This novel approach represents a promising solution to the reprocessing challenges associated with flexible conductive devices, demonstrating the successful integration of CANs and ICEs.

Molecular dynamics exploration of the temperature-dependent elastic, mechanical, and anisotropic properties of hcp ruthenium

Molecular dynamics calculations were performed for the hitherto unclarified temperature-dependent elastic, mechanical, and anisotropic properties of the hexagonal closed pack (hcp) ruthenium (Ru) between 0 and 1200 K. All elastic stiffness constants were found to decrease with increasing temperature. Under the examined temperature range, hcp Ru obeys Born stability conditions. Further, both Pugh ratio analyses and calculated Poisson ratio values mutually suggest the brittle character of hcp Ru between 0 and 1200 K. The intricate hardness behavior of hcp Ru was also obtained and discussed throughout the work. For the considered temperature range, hcp Ru exhibits apparent elastic anisotropy that exponentially increases with increasing temperature. Moreover, presently obtained ground state (T = 0 K and P = 0 GPa) theoretical data for hcp Ru agree well with the former experimental and theoretical data. The present findings on the temperature-dependent characteristics of this metal may further inspire future applied works.Graphical abstract

DeepNRMS: Unsupervised deep learning for noise-robust CO2 monitoring in time-lapse seismic images

Monitoring stored [Formula: see text] in carbon capture and storage projects is crucial for ensuring safety and effectiveness. We introduce DeepNRMS, a novel noise-robust method that effectively handles time-lapse noise in seismic images. The DeepNRMS leverages unsupervised deep learning to acquire knowledge of time-lapse noise characteristics from preinjection surveys. By using this learned knowledge, our approach accurately discerns [Formula: see text]-induced subtle signals from the high-amplitude time-lapse noise, ensuring fidelity in monitoring while reducing costs by enabling sparse acquisition. We evaluate our method using synthetic data and field data acquired in the Aquistore project. In the synthetic experiments, we simulate time-lapse noise by incorporating random near-surface effects in the elastic properties of the subsurface model. We train our neural networks exclusively on preinjection seismic images and subsequently predict [Formula: see text] locations from postinjection seismic images. In the field data analysis from Aquistore, the images from preinjection surveys are used to train the neural networks with the characteristics of time-lapse noise, followed by identifying [Formula: see text] plumes within two postinjection surveys. The outcomes demonstrate the improved accuracy achieved by DeepNRMS, effectively addressing the strong time-lapse noise.

Toward better understanding of anharmonic structural, thermodynamic, and elastic properties of CaSiO3 perovskite under extreme conditions via statistical moment method

CaSiO3 perovskite is thought to be the third most abundant minerals in both the Earth’s transition zone and lower mantle but its structural, thermodynamic, and elastic properties have not been well characterized. In this work, for the first time, we apply the statistical moment method (SMM) to determine analytical expressions of thermoelastic quantities such as isothermal and adiabatic elastic moduli, Grüneisen parameter, Young’s and shear moduli, compression wave and shear velocities including the full anharmonic effects of thermal lattice vibrations of perovskite crystals with cubic structure. The theoretical results are applied for numerical calculations for cubic CaSiO3 perovskite, which is a strongly anharmonic system, at temperatures and pressures up to 4000 K and 180 GPa corresponding to the extreme conditions of the Earth’s lower mantle. Our results for temperature and pressure dependences of unit cell volume, thermal expansivity, isochoric and isobaric heat capacities, Grüneisen parameter, isothermal and adiabatic elastic moduli, Young’s and shear moduli, compression wave and shear velocities are important signs of anharmonic effects under high temperatures and pressures. The SMM results are compared with experiments and other calculations. The present study provides an effective theoretical approach for finding the structural, thermodynamic, and elastic properties of strongly anharmonic materials under extreme conditions.

Site-specific elastic and viscoelastic biomechanical properties of healthy and osteoarthritic human knee joint articular cartilage

Site-specific elastic and viscoelastic biomechanical properties of healthy and osteoarthritic human knee joint articular cartilage

Sound velocities, elasticity and thermal properties of cBN composite with AlN binder at high pressure

Sound velocities, elasticity and thermal properties of cBN composite with AlN binder at high pressure

INFLUENCE OF GRAPHENE OXIDE PROPERTIES, SUPERPLASTICISER TYPE, AND DISPERSION TECHNIQUE ON MECHANICAL PERFORMANCE OF GRAPHENE OXIDE-ADDED CONCRETE

The incorporation of Graphene Oxide (GO) nanomaterial into concrete has gained significant attention due to its potential to enhance mechanical and durability properties. The addition of GO to concrete creates considerable changes in the morphology of the concrete matrix, creating a densified microstructure. Critical parameters significantly affect these microstructural enhancements and, consequently, the final performance in GO-added concrete. These parameters include GO material properties, superplasticiser (PS) type, and dispersion techniques. Therefore, this study investigates the influence of GO on the mechanical performance of concrete, focusing on these critical factors. Unlike existing studies concentrating on a single parameter's effect, this research comprehensively compares how these parameters impact GO-added concrete. Two commercially available GO types (GO-A and GO-B) and two PS types (PS-A and PS-B) are utilised. At the same time, three commonly used mixing techniques, such as mechanical, high-speed, and ultrasonic mixing techniques, are considered for GO dispersion. GO-A is added to concrete in percentages ranging from 0.02% to 0.14% by weight of cement (bwoc), while GO-B ranges from 0.04% to 0.20% bwoc. Based on compressive strength test results, the optimum GO dosages are 0.08% for GO-A and 0.12% for GO-B. The highest strength results are achieved for GO-B added concrete with PS-A addition and following the ultrasonic dispersion method, highlighting these parameters as optimal for maximising GO-added concrete performance. The optimum concrete mix exhibits 33%, 24%, 25%, and 30% increments for compressive strength, indirect tensile strength, flexural strength, and elastic modulus properties at 28 days. This paper provides a deep theoretical explanation of the effects of GO material properties, dispersion techniques, and PS type on GO-added concrete performance. The findings provide valuable insights into selecting suitable parameters for optimising the mechanical properties of GO-added concrete, contributing to the advancement and effectiveness of construction materials.

Determination of hardness and Young's modulus in fcc Cu-Ni-Sn-Al alloys via high-throughput experiments, CALPHAD approach and machine learning

Hardness and Young's modulus are critical indicators in the design of innovative Cu-Ni-Sn-Al alloys with desired elastic and strength properties. In this study, the composition-dependent hardness and Young's modulus in the fcc Cu-Ni-Sn-Al alloys were determined using high-throughput experiments, the CALPHAD (CALculation of PHAse Diagrams) approach, and machine learning (ML) model. By combining the diffusion-couples tool, nanoindentation, and electron probe microanalysis (EPMA) techniques, the 341 sets of composition-related hardness and Young's modulus in the fcc Cu-Ni-Sn-Al system, as well as its sub-binary and sub-ternary systems, were effectively determined. These measured data were subsequently utilized to establish the relationship of Young's modulus and hardness with respect to composition in the fcc Cu-Ni-Sn-Al system through the combined application of CALPHAD and back propagation (BP) artificial neural network machine learning models. A comparison between the two approaches revealed that the ML method achieves higher accuracy in ternary and quaternary alloys compared to the CALPHAD method. The impact of alloying elements on the values of hardness and Young's modulus was analyzed, demonstrating that the Ni content has the largest effect on hardness, while the Young's modulus increases with addition of Ni but decreases with the addition of Al and Sn. Finally, the effects of solute elements on the nanomechanical properties of aged Cu1-x(Ni3Sn)x and Cu-9Ni-6Sn-xAl alloys were examined.

The influence of papaya shape on its mass model and mechanical properties

AbstractPostharvest handling tasks include fruit grading and minimizing loss. Fruits are often packaged into grades based on size and mass for uniformity and proper handling. Losses caused by mechanical damage can be reduced by understanding the fruit's response to loads. Papaya's (cv. Exotica) irregular shape and short shelf‐life are important factors for proper handling. This study aimed to develop a model for papaya mass based on geometric properties and to characterize its mechanical behavior when compressed along its major axis. For mass prediction, single‐ and multiple‐variable regression models using papaya's geometrical variables were developed. Despite its irregular shape, similar performance was observed in the best single‐ and multiple‐variable mass models (R2 ≈ 0.95, RMSE ≈ 82 g). However, the single‐variable model is likely more practical because only two axial lengths are needed and can be extracted from 2D images. For papaya's mechanical behavior, the results for elastic properties indicate some variations (p &gt; 0.05) in elastic modulus, and failure stress and strain along the major axis, while results for viscoelastic properties indicate significant variation (p &lt; 0.05) in the relaxation moduli. Overall, the bottom section is less resistant to deformation compared to the top. Therefore, reducing compression in the section could potentially reduce damage. Using the mechanical properties described here in computer simulation studies may provide more detailed load distribution. Mass modeling can aid the automation of papaya grading, while mechanical response characterization provides valuable information for designing postharvest handling systems.Practical ApplicationsPostharvest handling tasks include fruit grading and minimizing loss. Fruits are often packaged into grades based on size and mass for uniformity and proper handling. Losses caused by mechanical damage may be reduced by understanding the fruit's response to loads. Papaya's irregular shape and short shelf‐life are important factors for proper postharvest handling. Mass modeling can assist the automation of papaya sorting, while characterizing its mechanical response can assist the design of postharvest handling systems. The mass model result indicates that papaya's mass (cv. Exotica) can be predicted using two axial lengths, which can be easily obtained using 2D images. The advantage is that this task can be combined with other tasks using imaging data. While the mechanical properties of papaya indicate that its bottom section is more susceptible to deformation compared to the top when they are stored in an environment with minimal movements over an extended period. Therefore, in this setup, applying the compression load at the top section while minimizing compression load at the bottom may be more effective in preventing and minimizing mechanical damage.

Tuning the Poisson’s ratio of two-dimensional model network materials with application to 2D-silica bilayer structures

A fundamental understanding of the elastic properties of 2D network structures is highly beneficial for research and applications of 2D materials. In this context, Poisson’s ratio has been studied elaborately for different crystallographic structures of crystalline phases of bilayer silica structures. This paper focuses on the elastic structure–property relationship of crystalline and vitreous polymorphs of plane network materials. We generate defective crystalline network states and seven sets of disordered states, each with a different level of network heterogeneity, using a dual Monte Carlo bond switching algorithm. Firstly, uniaxial tensile deformation is applied to a model material in a two-dimensional framework, concentrating only on the in-plane network topologies. Secondly, uniaxial tensile deformation is applied to bilayer silica structures, considering the out-of-plane morphology of the material. Mechanical testing is performed using the athermal quasistatic deformation protocol, which allows one to study the influence of the network topology exclusively without any thermal disturbances. We show that manipulating the network heterogeneity allows one to directly tune the Poisson’s ratio of the material, creating possibilities for novel mechanical applications.

Investigation of the variation of mechanical and durability properties of elements manufactured with rubber substituted SCMs with element height

Controlling the homogeneous distribution of granulated rubber materials added to self-compacting concrete/mortars along the height is of great importance in terms of preserving and defining the holistic behavior of structural elements. In this study, the effect of EPDMGR (ethylene propylene diene monomer granulated rubber) ratio (0 %, 5 %, 10 %, 15 %, 20 % and 25 %), test age, L/D (slenderness ratio) and element test zone (bottom, middle and top) on the mechanical properties (flexural and compressive), durability properties (porosity and sorptivity) of the elements produced with SCM were evaluated. The results obtained were statistically evaluated by GLM-ANOVA. It was observed that flexural tensile strength was strengthened up to 5 % substitution rate due to the hydrophobic properties and elasticity properties of EPDMGR used, while porosity values increased with height in the upper regions compared to the lower regions due to the placement properties of SCM. Differences in compressive strength appeared in the upper and lower sections after 5 % EPDMGR substitution. This indicates that for the mixture properties used, the properties examined in terms of mechanical and durability test results may have different properties with limited variability in terms of L/D ratio depending on the EPDMGR ratio used and the region where the element was taken.

Tuning the Piezoelectric Performance of K0.5Na0.5NbO3 through Li Doping: Insights from Structural, Elastic and Electronic Analyses

The structural, elastic, piezoelectric, and electronic properties of Li-doped K0.5Na0.5NbO3 (K0.5−xNa0.5−yLix+yNbO3, KNN-L) are calculated. The properties of KNN-L are related to the Li-doping content and the replaced K or Na atoms. The bulk modulus, the shear modulus, and Young’s modulus of KNN-L are mostly higher than those of KNN, and the hardness value increases. The Poisson ratio of KNN-L is lower than that of most KNN, and the ductility is reduced. All doped structures are direct band gap semiconductors. K0.5Na0.375Li0.125NbO3 has the largest piezoelectric charge constant, d33 = 44.72 pC/N, in the respective structures, which is 1.5 fold that of K0.5Na0.5NbO3 (29.15 pC/N). The excellent piezoelectric performance of Li-doping KNN-L was analyzed from the insights of elastic and electronic properties.

Castor‐oil derived polyurethane/barium titanate piezoelectric smart composite coatings for energy harvesting applications: Prediction and experimental characterization of electro‐elastic properties

Castor‐oil derived polyurethane/barium titanate piezoelectric smart composite coatings for energy harvesting applications: Prediction and experimental characterization of electro‐elastic properties

Structural, band profiles and optical reflectivity studies of ALi2B (A = Cu, Ag; B = Ge, Sn, Pb) compounds

Abstract The subject of given project is to highlight the basic elastic, electronic and optical reflectivity of ALi2B (A = Cu, Ag; B = Ge, Sn, Pb). For the calculation of these properties, we used the full potential linearized augmented plane wave (FP-LAPW) procedures carry through Wien2k package. Specifically, the Perdew, Burke and Ernzerhof’s generalized gradient approximation (PBE-GGA) and Wu and Cohen generalized gradient approximation (WC-GGA) have been used. The obtained results fit well with existing experimental data. Different elastic parameters, such as constant of elasticity, elastic moduli, Poisson’s ratio, anisotropy factor and Cauchy pressure, are calculated for the first time for the compounds. The elastic properties clearly summarized the compound’s elastically stability and brittleness in both zinc blend phase. The band structure results for ALi2B shows that the compounds are metallic having overlapping bands across the electron chemical potential. The valance band highest energy state is composed from combination of Cu-d and Sn-p state, disclosed through these compound’s total (DOS) plots, whereas the conduction band primarily constitution is from Li-p, Sn-s Cu-s and Sn-p states. The intraband transitions play vital rule in the description of the optical reflectivity of the ALi2B compounds.