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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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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The Young Modulus and the Poisson Coefficient of Two-Dimensionally Extended Columnar Graphene
The Young modulus and the Poisson coefficient of two-dimensionally extended columnar graphene are theoretically studied in the uniaxial tension. The effect of length and diameter of nanotubes constituting the composite is considered. The numerical experiments are implemented using the minimum structural link and the periodical boundary conditions via the density functional theory method. The Young moduli of the composite are evaluated upon its extension along the normal to the graphene and along the graphene directions with increasing lengths of carbon nanotubes (CNTs) in the composite. The Poisson coefficient for this type of composites is found to be 0.025.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
3D printed structures for modeling the Young’s modulus of bamboo parenchyma
Not Available
Dixon, P. G.↗
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↗
Durable, Impermeable Brazes for Solid Oxide Fuel Cells (Final Report)
To develop a new braze to replace the current state-of-the-art Ag-CuO reactive air braze (RAB), two approaches were proposed: 1) development of a new, self-passivating, silver-free braze and 2) development of a CuO-free, silver-based braze. For the first approach, an integrated computational-experimental method was used. Thermo-Calc® was utilized to quickly screen through hundreds of alloy systems to identify candidate braze compositions with the appropriate melting ranges. Material compositions, melting ranges, mechanical properties, oxidation resistance, and wetting characteristics of the candidate alloys were then analyzed experimentally. Substrate surface pre-treatments, active element additions, and novel brazing schemes were also investigated. Unfortunately, the current study failed to identify new silver-free braze compositions suitable for SOFC applications. To help measure the passivation characteristics of surface passivating braze oxide coatings, work was conducted to demonstrate, for the first time, that a variety of disparate and technologically-relevant thermal, mechanical, and electrochemical oxygen-exchange thin film material properties could all be obtained from in situ , current-collector-free wafer curvature measurements. Specifically, temperature or oxygen partial pressure induced changes in the curvature of 230 nm thick (100)-oriented Pr 0.1 Ce 0.9 O 1.95_x (10PCO) films atop 200 mm thick single crystal yttria stabilized zirconia or magnesium oxide substrates were used to measure the biaxial modulus, Young’s modulus, thermal expansion coefficient, thermochemical expansion coefficient, oxygen nonstoichiometry, chemical oxygen surface exchange coefficient, oxygen surface exchange resistance, thermal stress, chemical stress, thermal strain, and chemical strain of the model mixed ionic electronic conducting material 10PCO. The (100)-oriented thin film 10PCO thermal expansion coefficient, thermo-chemical expansion coefficient, oxygen nonstoichiometry, and Young’s modulus (which is essentially constant, at ~200 MPa, over the entire 280–700 °C temperature range in air) measured here were similar to those from other bulk and thin film 10PCO studies. In addition, the measured PCO10 oxygen surface coefficients were in agreement with those reported by other in situ , current collector- free techniques. However, the measured PCO10 oxygen surface exchange coefficients were significantly lower than those obtained from literature studies with large amounts of intentional or inadvertent precious metal surface coverage/contamination (suggesting that uncontaminated (100)-oriented 10PCO may not be a desirable SOFC cathode material). Taken together, this highlighted the advantages of using a sample’s mechanical response, instead of the more traditional electrical response, to probe the electrochemical properties of the ion-exchange materials used in solid oxide fuel cell, solid oxide electrolysis cell, gas-sensing, battery, emission control, water splitting, water purification, and other electrochemically-active devices. For the second approach, a novel silver-nickel brazing method was developed. It was demonstrated that transient porous nickel interlayers, instead of reactive element additions, could be used to promote Ag wetting on yttria stabilized zirconia (YSZ) and produce high-quality YSZ stainless steel (SS) braze joints. Mechanical tests on these reactive-element-free, silver-based SOFC braze joints, both before and after 500 hours of 750°C oxidation in air, showed that the braze and braze interface strength were higher than the underlying YSZ|NiO-YSZ substrate. The microstructural and compositional evolution of SS|Ag-Ni|YSZ braze joints exposed to dual atmosphere (air on one side and 4%H 2 -96%N 2 on the other side) for 300 hours of isothermal 750 °C aging and 300 25°C/min 35-830 °C rapid thermal cycles were compared to a Ag-3CuO braze joint. In contrast to conventional Ag-CuO RAB brazes, the Ag-Ni brazes remained pore free and well bonded, suggesting that Ag-Ni brazes may be more suitable for long term SOFC operation than Ag-CuO brazes. Other applications inspired by the silver-nickel wetting process on various ceramic substrates were also explored. In support of efforts to identify new CuO-free Ag-based brazes, density functional theory and ab initio molecular dynamics calculations were performed to 1) understand silver wetting on YSZ, and 2) identify new oxides to promote silver wetting on YSZ. These simulations found that while the formation of dissolved oxygen clusters within molten silver at the YSZ interface promoted wetting, much greater wetting angle reductions came from the formation of metal oxide interlayers at the Ag-YSZ interface. Through the development of a simple descriptor, many simple metal oxides (single cation) were examined. Unfortunately, their ability to promote Ag wetting were less than that of CuO. However, expanding the search to multi-cation oxides led to several promising candidates, such as CuAlO 2 , CuGaO 2 , and Cu 3 TiO 4 ; all of which are also stable in the reducing SOFC conditions. Depending upon their solubility in molten Ag, these newly-identified oxides could either be pre-applied as wetting promoting interlayers or directly incorporated into Ag to form new reactive air brazes.
36 MATERIALS SCIENCE↗
Magnetic, Mechanical, and Electronic Properties of RhH{sub x} (x = 0, 0.25, 0.75, 1) from First-Principles Calculations
The magnetic, mechanical, and electronic properties of RhH{sub x} (x = 0, 0.25, 0.75, 1) have been investigated by first-principles calculations based on density functional theory. It is shown that RhH{sub x} (x = 0.25, 0.75, 1) in the cubic structure are magnetic except for Rh. The total magnetic moments of RhH{sub x} (x = 0.25, 0.75, 1) decrease with increasing content of H, which mainly results from the change of the Rh moments. The calculated elastic constants indicate that RhH{sub x} (x = 0, 0.25, 0.75, 1) in the cubic structure are mechanically stable. With increasing H content, the bulk modulus, shear modulus, and Young modulus gradually decrease except the bulk modulus of RhH. By means of the values of the B/G ratio, it is concluded that H doping improves the ductile properties of Rh. The strong hybridization between H-s and Rh-d is the origin of magnetism for RhH{sub x} (x = 0.25, 0.75, 1) and decreases with increasing H content.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Effect of Temperature and Pressure on Structural and Magnetic Properties of Strontium-Filled Skutterudites SrT{sub 4}Sb{sub 12}: LDA and LSDA Calculations
The structural, elastic, thermodynamic, magnetic, and electronic properties of strontium-filled skutterudite component SrFe{sub 4}Sb{sub 12} using the full potential-linear muffin-tin orbital (FP-LMTO) calculation were studied. The local density approximation (LDA) and local spin density approximation (LSDA) for predicting the physical properties were used. The internal parameters used to calculate the ground state properties such as lattice constant, bulk modulus, and its derivative pressure were optimized. Then, we have deduced the elastic constants, shear modulus G, Young modulus E, Poisson’s ratio ν, anisotropic parameter A, ratio B/G, and the Debye temperature (𝜃{sub D}). The quasi-harmonic Debye model as implemented in the Gibbs program is applied to determine the thermal properties such as the Debye temperature (𝜃{sub D}), heat capacity C{sub v} and C{sub p}, thermal expansion coefficient α Helmholtz free energy (A), Gibbs free energy (G), entropy (S) and internal energy (U) at different pressures and temperatures.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Effect of interfacial reaction on Young's modulus in CNT/Al nanocomposite: A quantitative analysis
Highlights: • Effect of interfacial reaction on Young’s modulus of CNT/Al composite was quantitatively revealed. • Both qualitative and quantitative characterizations of CNT/Al interfacial reaction were conducted. • Volume expansion induced by CNTs-Al{sub 4}C{sub 3} transformation was the key to modulus increase with greater reaction degree. • The significant role of raw CNTs quality in “Young’s modulus-interfacial reaction” relationship was uncovered. - Abstract: 1.5 wt% CNT/Al nanocomposite with limited, moderate and severe interfacial reaction were prepared by flake PM and annealing to study the effect of interfacial reaction on Young's modulus. Both qualitative and quantitative characterizations of CNT/Al interfacial reaction were conducted through TEM observation and electrochemical dissolution. The results showed that the strong reinforcing effect of reaction-formed Al{sub 4}C{sub 3} and the significant volume expansion effect during CNTs-Al{sub 4}C{sub 3} transformation resulted in Young's modulus increase with greater CNT/Al interfacial reaction degree. The significant role of raw CNTs quality in “Young's modulus-interfacial reaction degree” relationship was discussed. Both raw CNT quality and CNT/Al interfacial reaction need to be well controlled and optimized for fabricating CNT/Al nanocomposite with higher Young's modulus.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Effect of interfacial transition zone on the Young's modulus of carbon nanofiber reinforced cement concrete
Identifying the properties of the region where the cement paste meets the aggregate surface (interfacial transition zone, ITZ) is critical to understanding the strength and fracture behavior of carbon nanofiber (CNF) reinforced cement concrete. In this study, the finite element method is employed to investigate the effect of the ITZ on the Young's modulus of cement concrete made with CNF. The numerical models for cement concrete with and without CNF are constructed based on the digital image processing technique. To consider the interface effect, the concept of ''effective aggregate'' is put forward, namely, the Young's modulus and Poisson's ratio for each aggregate particle are replaced by an effective Young's modulus and effective Poisson's ratio, in which the effect of thickness and the Young's modulus of ITZ is taken into account in an averaged manner. Then, the quantitative nanomechanical mapping (based on atomic force microscopy) technique is adopted to measure the Young's modulus and thickness of ITZ with and without CNFs, which are further used as the input parameters in the numerical model. The numerical simulation results are verified by experimental testing, which indicates that the ITZ effect should be considered when implementing the numerical simulation. In addition, this analysis shows that compared with the plain cement concrete, CNFs can greatly enhance the mechanical properties of ITZ, which will in turn improve the Young's modulus of cement concrete significantly. Finally, the effect of thickness and Young's modulus of ITZ on the Young's modulus of CNF reinforced cement concrete is also discussed.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
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↗
First-principles study of structural, elastic, electronic, vibrational and thermodynamic properties of uranium aluminides
The structural, elastic, electronic, vibrational and thermodynamic properties of uranium aluminides UAl x (x = 2, 3, 4) were studied by density functional theory calculations. The single crystal elastic constants of UAl x were predicted using the stress-strain method, which were further used to calculate the polycrystalline aggregate properties of UAl x , including bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio, etc. The calculated electronic density of states confirm that UAl x compounds are metallic phases with majority states at the Fermi level contributed by U 5 f electrons. The phonon dispersion relations and density of states show that the low frequency acoustic phonon modes of UAl x are dominated by the lattice vibration of uranium atoms while high frequency optical phonon modes are from the vibration of aluminum atoms. Using quasiharmonic approximation, thermodynamic properties of UAl x , including Gibbs free energy, entropy, heat capacity, and linear thermal expansion coefficient, were predicted by including both lattice vibrational and thermal electronic contributions. The thermal electronic energy was found to be crucial for the description of the temperature dependence of the thermodynamic properties. In conclusion, the derived Gibbs energy functions of UAl x are expected to be useful to the thermodynamic modeling of the ternary U-Mo-Al system.
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↗
Electronic Structure, Mechanical and Dynamical Stability of Hexagonal Subcarbides M{sub 2}C (M = Tc, Ru, Rh, Pd, Re, Os, Ir, and Pt): Ab Initio Calculations
Ab initio calculations were used to study the properties of a series of hexagonal (Fe{sub 2}N-like) subcarbides M{sub 2}C, where M = Tc, Ru, Rh, Pd, Re, Os, Ir, and Pt, and to calculate their equilibrium structural parameters, electronic properties, phase stability, elastic constants, compression modulus, shear modulus, Young’s modulus, compressibility, Pugh’s indicator, Poisson ratio, elastic anisotropy indices, and also hardness, Debye temperature, sound velocity, and low-temperature heat capacity. It is found based on these results that all the subcarbides are mechanically stable; however, their formation energies E{sub form} are positive with respect to a mixture of d-metal and graphite. In addition, the calculation of the phonon spectra of these subcarbides shows the existence of negative modes, which indicates their dynamical instability. Thus, a successful synthesis of these subcarbides at normal conditions is highly improbable.
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↗
A combined machine learning and density functional theory study of binary Ti-Nb and Ti-Zr alloys: Stability and Young’s modulus
The multicomponent Ti alloys, specifically the -phase, have experienced a strong growth over the last decades, due to their outstanding properties of ultra-high strength and low Young’s modulus. These properties play a significant role in many aerospace and biomedical applications. Selection and optimization of multicomponent alloys is challenging due to the vast chemical and compositional space. Here we investigate the use of machine learning techniques informed by density functional calculations to guide the selection of Nb- and Zr-based Ti binary alloys. From the cubic structures obtained from high throughput calculations and literature, we identify several structures with Young’s moduli below 40 GPa. The multivariant decision tree methods provide efficient surrogate models to identify structure variables have high influences on the energetic stability and Young’s modulus. Furthermore, we implement a workflow of incorporating DFT provided results and machine learning method to explore the chemical and composition space of other binary and multicomponent alloys, to eventually accelerate the material design via taking advantages of identified key variables.
36 MATERIALS SCIENCE↗