Phases and Youngs modulus dataset
A useful data for predicting phases and Youngs modulus using machine learning
Phase data of 340 HEAs↗
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Improved Calculation of the Young’s Modulus of Rectangular Prisms from Their Resonant Frequency Overtones by Identifying Appropriate Shear Constants
Young’s modulus is an important parameter for characterizing the strength of, and wave propagation through, a given material. This study improves the estimation of Young’s modulus using the impulse excitation technique based on an experimental analysis of 19 borosilicate glass bars. Analysis of the frequency equations relating Young’s modulus to the out-of-plane and in-plane flexural resonant frequencies of rectangular prisms has been conducted for both the fundamental frequency and its overtones at higher orders of vibration. Furthermore, the Young’s moduli of three novaculite rocks with various porosities were then measured up to the seventh order of vibration to validate the optimum shear constant equation for estimating Young’s modulus. Young’s modulus was found to be nearly frequency independent for these rock samples.
Impulse excitation↗
Phases and Young's modulus dataset for High Entropy alloys
A useful dataset on high entropy alloys for phase and Young's modulus prediction.
Phases of 340 alloys with 11 calculated↗
First-principles study on the mechanical and thermodynamic properties of MoNbTaTiW
Refractory high-entropy alloys (RHEAs) are emerging as new materials for high temperature structural applications because of their stable mechanical and thermal properties at temperatures higher than 2273 K. In this study, the mechanical properties of MoNbTaTiW REDEA are examined by applying calculations based on first-principles density functional theory (DFT) and using a large unit cell with 100 randomized atoms. The phase calculation of MoNbTaTiW with CALPHAD method shows the existence of a stable body-centered cubic structure at a high temperature and a hexagonal closely packed phase at a low temperature. The predicted phase, shear modulus, Young’s modulus, Poisson’s ratio, and hardness values are consistent with available experimental results. The linear thermal expansion coefficient, vibrational entropy, and vibrational heat capacity of MoNbTaTiW RHEA are investigated in accordance with Debye-Grüneisen theory. These results may provide a basis for future research related to the application of RHEAs.
36 MATERIALS SCIENCE↗
Machine learning elastic constants of multi-component alloys
The present manuscript explores application of machine learning methods for determining elastic constants and other derived mechanical properties of multi-component alloys. Here, a number of machine learning models, including linear regression, neural network and random forest based models, are trained and tested on a dataset of binary alloys generated using density functional theory (DFT) calculations and spanning over a large number of elemental species in the periodic table. Starting with a wide range of simple and easily accessible compositionally-averaged elemental features, a correlation-based feature selection strategy was used to systematically down-select a set of most relevant features towards the prediction of the elasticity tensor components. The true predictive performance and the associated uncertainties of the models were established by testing on unseen data and bootstrapping, respectively. A single and pair-wise feature partial dependence analysis was performed to visualize the average property trends in the multi-dimensional feature space in order to further understand the achieved predictive performance. The utility of the trained model is further demonstrated by obtaining sufficiently accurate yet highly efficient approximations for bulk modulus, Young’s modulus, shear modulus and Poisson’s ratio for alloys beyond the binary space (i.e., two-component alloys) on which the model was originally trained. More importantly, we test and validate the predictive performance of the developed model directly against the experimentally measured elastic constants of technologically relevant multi-component alloys (such as, Ni- and Ti-based alloys). Finally, utility of such a data-enabled route is demonstrated by predicting the possible range of various elastic properties for vast composition space available within the five component Ni-Cr-Fe-Mo-W alloy system in a high-throughput manner.
36 MATERIALS SCIENCE↗
Investigation of γ - ( U , Z r ) structural properties and its interfacial properties with liquid sodium using ab initio molecular dynamics
In this study, the elastic properties, structural parameters, sound velocity, and Debye temperature of γ–(U,Zr) were computed using ab initio molecular dynamics (AIMD) at temperatures between 1000 K and 1400 K and for Zr content between 0 at. % and 100 at. %. UZr is used as a metallic fuel for Sodium Fast Reactors (SFRs). The study of the mechanical and thermal behavior of these alloys leads to a better data-informed fuel design. The bulk modulus, shear modulus, Young's modulus, and Poisson's ratio were calculated from the elastic constants and their dependence on Zr content and temperature was investigated, comparing the results with previous computational work and the available experimental data in the literature. Interfacial properties between UZr (up to 32 at. % which typically exists in nuclear fuel) and liquid sodium are also of interest due to the presence of a sodium bond between the fuel and the cladding in metallic nuclear fuel. The interfacial energy between γ–(U,Zr) and liquid sodium, the surface tension of liquid sodium, and the work of adhesion were computed at different temperatures and Zr concentrations. It was demonstrated that γ–(U,Zr) is completely wetted by liquid sodium at all the investigated temperatures and Zr concentrations. Finally, this work provides the basis for the determination of interfacial resistances in SFRs and their implementation into heat transfer fuel performance simulations, which will be the subject of future work.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Vickers hardness prediction from machine learning methods
Abstract The search for new superhard materials is of great interest for extreme industrial applications. However, the theoretical prediction of hardness is still a challenge for the scientific community, given the difficulty of modeling plastic behavior of solids. Different hardness models have been proposed over the years. Still, they are either too complicated to use, inaccurate when extrapolating to a wide variety of solids or require coding knowledge. In this investigation, we built a successful machine learning model that implements Gradient Boosting Regressor (GBR) to predict hardness and uses the mechanical properties of a solid (bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio) as input variables. The model was trained with an experimental Vickers hardness database of 143 materials, assuring various kinds of compounds. The input properties were calculated from the theoretical elastic tensor. The Materials Project’s database was explored to search for new superhard materials, and our results are in good agreement with the experimental data available. Other alternative models to compute hardness from mechanical properties are also discussed in this work. Our results are available in a free-access easy to use online application to be further used in future studies of new materials at www.hardnesscalculator.com .
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Mechanical Properties of a Solvated Biomolecule: RGD (1FUV) Peptide
The mechanical properties of proteins/peptides play an essential role in their functionalities and implications, as well as their structure and dynamic properties. Understanding mechanical properties is pivotal to our knowledge of protein folding and the molecular basis of diverse cellular processes. Herein, we present a computational approach using ab initio quantum mechanical calculations to determine the mechanical properties—such as bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio—of a solvated Arg-Gly-Asp (RGD) peptide model. Since this peptide serves as the RGD-directed integrin recognition site and may participate in cellular adhesion, it is considered a promising small peptide for medicinal applications. This successful approach paves the way for investigating larger and more complex biomolecules.
Biochemistry & Molecular Biology↗
Nanoscale Polarization-Dependent Young’s Modulus of Ferroelectric BaTiO 3 Single Crystals
Flexoelectric fields produced by strong strain gradients at the nanoscale couple to ferroelectric polarization, promoting changes in the mechanical properties of ferroelectric materials as a function of the direction of the ferroelectric polarization. In this work, we calculate the asymmetry in the Young’s modulus found in oppositely polarized out-of-plane domains of BaTiO 3 single crystals by means of contact resonance AFM, and we evaluate its impact on the electromechanical response as measured by piezoresponse force microscopy, both using band excitation modes. Furthermore, we analyze the electromechanical response of the different BaTiO 3 domains using k-means to build up their mean elastic and electromechanical features and quantify the flexoelectrically induced modulation of the Young’s modulus. Finally, we discuss the use of contact Kelvin probe force microscope measurements to decouple electrostatic artifacts from purely piezoelectric ones when flexoelectric coupling appears.
BaTiO 3 single crystals↗
Method for measuring static Young's modulus of tungsten to 1900 K
An instrument system was developed and tested to measure static Young's modulus of elasticity of refractory metals in tension at temperatures to 1900 K. The extensometer uses capacitance displacement sensors for measuring total elongation of a specimen and incorporates a unique high-resolution remote zero-adjusting mechanism. Details of a method for calibrating capacitance displacement sensors at temperatures to 800 K are included. The system was built to adapt to a vacuum furnace on a tensile machine and was tested on unalloyed tungsten rod specimens. The test results show that the system can measure the modulus of tungsten to 1900 K to within a precision of + or - 5 percent. The uncertainty of the measurement is estimated to be of the same order as the precision.
Harrigill, W. T., Jr.↗
Machine learning assisted prediction of the Young’s modulus of compositionally complex alloys
We identify compositionally complex alloys (CCAs) that offer exceptional mechanical properties for elevated temperature applications by employing machine learning (ML) in conjunction with rapid synthesis and testing of alloys for validation to accelerate alloy design. The advantages of this approach are scalability, rapidity, and reasonably accurate predictions. ML tools were implemented to predict Young’s modulus of refractory-based CCAs by employing different ML models. Our results, in conjunction with experimental validation, suggest that average valence electron concentration, the difference in atomic radius, a geometrical parameter λ and melting temperature of the alloys are the key features that determine the Young’s modulus of CCAs and refractory-based CCAs. The Gradient Boosting model provided the best predictive capabilities (mean absolute error of 6.15 GPa) among the models studied. Our approach integrates high-quality validation data from experiments, literature data for training machine-learning models, and feature selection based on physical insights. It opens a new avenue to optimize the desired materials property for different engineering applications.
36 MATERIALS SCIENCE↗
Young’s modulus of V 3 O 5 thin films
Vanadium oxide V 3 O 5 exhibits an insulator-to-metal transition (IMT) near 430 K, which is the highest value for all vanadium oxides exhibiting IMTs. This makes it interesting for advanced electronic applications. However, the properties of V 3 O 5 have been little studied, and, in particular, there are no reports of experimentally determined mechanical properties. In this work, Young’s modulus of sputter-deposited V 3 O 5 thin films has been determined by measuring the fundamental resonant frequency of V 3 O 5 -coated silicon microcantilevers using a laser beam deflection technique. After deposition, the films were characterized by x-ray diffraction, resistivity measurements, and atomic force microscopy. The value of Young’s modulus experimentally determined for V 3 O 5 was 198 ± 14 GPa, which is slightly lower than the computationally derived values for bulk crystal V 3 O 5 .
36 MATERIALS SCIENCE↗
Measurements of dynamic Young's modulus in short specimens with the PUCOT
The piezoelectric ultrasonic composite oscillator technique (PUCOT) was used at frequencies in the range 40 to 150 kHz to measure dynamic Young's modulus for short-length single crystals of copper at temperatures in the range 25 to 650 C and for polycrystalline copper at room temperature. Corrections to the modulus for variations in length/diameter resulted in no loss of precision due to wave velocity dispersion.
Wickstrom, S. N.↗
Method for in-situ nondestructive measurement of Young's modulus of plate structures
A method for determining stiffness of a composite laminate plate entails disposing a device for generating an acoustical pulse against a surface of the plate and disposing a detecting device against the same surface spaced a known distance from the pulse-generating device, and using the pulse-generating device to emit a pulse so as to create an extensional wave in the plate. The detecting device is used to determine a time of flight of the wave over the known distance, and the wave velocity is calculated. A Young's modulus of the plate is determined based on the wave velocity. Methods for both anisotropic and quasi-isotropic laminates are disclosed.
Huang, Jerry Qixin↗
Apparatus for in-situ nondestructive measurement of Young's modulus of plate structures
A method and apparatus for determining stiffness of a plate-like structure including a monolithic or composite laminate plate entails disposing a device for generating an acoustical pulse against a surface of the plate and disposing a detecting device against the same surface spaced a known distance from the pulse-generating device, and using the pulse-generating device to emit a pulse so as to create an extensional wave in the plate. The detecting device is used to determine a time of flight of the wave over the known distance, and the wave velocity is calculated. A Young's modulus of the plate is determined by a processor based on the wave velocity. Methods and apparatus for evaluating both isotropic plates and anisotropic laminates are disclosed.
Huang, Jerry Qixin↗
Low-temperature elastic behavior of fourteen compounded elastomers
Low temperature elastic properties of elastomers - modulus of rigidity, brittle temperature, and youngs modulus.
ELASTIC PROPERTY↗
A micromechanics model for the effective Young's modulus of a piecewise-isotropic laminate with wavy patterns
A mathematical model based on the Euler-Bernoulli beam theory is proposed for predicting the effective Young's moduli of piece-wise isotropic composite laminates with wavy patterns in the main load-carrying layers. Strains in corrugated layers, in-phase layers, and out-of-phase layers are predicted for various geometries and material configurations by assuming matrix layers as elastic foundations. Experimental results obtained from corrugated aluminum specimens and aluminum/epoxy specimens with in-phase and out-of-phase wavy patterns coincide very well with the predictions. The work represents a preliminary effort toward further generalization of the model for two-dimensional anisotropic laminates containing wavy patterns in the main load-carrying layers.
Lee, Jong-Won↗
A deformation-formulated micromechanics model of the effective Young's modulus and strength of laminated composites containing local ply curvature
A mathematical model based on the Euler-Bermoulli beam theory is proposed for predicting the effective Young's moduli of piecewise isotropic composite laminates with local ply curvatures in the main load-carrying layers. Strains in corrugated layers, in-phase layers, and out-of-phase layers are predicted for various geometries and material configurations by assuming matrix layers as elastic foundations of different spring constants. The effective Young's moduli measured from corrugated aluminum specimens and aluminum/epoxy specimens with in-phase and out-of-phase wavy patterns coincide very well with the model predictions. Moire fringe analysis of an in-phase specimen and an out-of-phase specimen are also presented, confirming the main assumption of the model related to the elastic constraint due to the matrix layers. The present model is also compared with the experimental results and other models, including the microbuckling models, published in the literature. The results of the present study show that even a very small-scale local ply curvature produces a noticeable effect on the mechanical constitutive behavior of a laminated composite.
Lee, Jong-Won↗