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DOE OSTI2025

Materials property changes in ETU-10 graphite due to neutron irradiation at elevated temperatures

Graphite grade ETU-10, from IBIDEN Co., Ltd. Has been irradiated in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The irradiation program was developed to provide a preliminary study the irradiation-induced property changes to the dimensions/volume, elastic properties, strength, electrical resistivity, coefficient of thermal expansion, and thermal diffusivity/conductivity over a range of temperatures and neutron exposures that may be relevant for future nuclear reactors. The irradiation envelope covers a range of irradiation temperatures (300°C–900 °C) and fluences (up to 40 × 10 25 n/m 2 [E > 0.1 MeV] or ~30 dpa) that would be relevant for advanced nuclear reactors. Further, the dimensional change was observed to be anisotropic for an isotropic graphite, the specimen dimensions, volume, Young's modulus, shear modulus, and strength all displayed a parabolic fluence dependence, the electrical resistivity had a rapid rise followed by a decrease and a later increase, at high fluence the mean coefficient of thermal expansions was similar for all irradiation temperatures, and thermal conductivity rapidly decreased followed by a continued loss.

36 MATERIALS SCIENCE↗

DOE OSTI2021

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↗

DOE OSTI2022

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↗

DOE OSTI2022

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↗

DOE OSTI2023

A machine learning framework for elastic constants predictions in multi-principal element alloys

On the one hand, multi-principal element alloys (MPEAs) have created a paradigm shift in alloy design due to large compositional space, whereas on the other, they have presented enormous computational challenges for theory-based materials design, especially density functional theory (DFT), which is inherently computationally expensive even for traditional dilute alloys. In this paper, we present a machine learning framework, namely PREDICT (PRedict properties from Existing Database In Complex alloys Territory), that opens a pathway to predict elastic constants in large compositional space with little computational expense. The framework only relies on the DFT database of binary alloys and predicts Voigt–Reuss–Hill Young’s modulus, shear modulus, bulk modulus, elastic constants, and Poisson’s ratio in MPEAs. We show that the key descriptors of elastic constants are the A–B bond length and cohesive energy. The framework can predict elastic constants in hypothetical compositions as long as the constituent elements are present in the database, thereby enabling property exploration in multi-compositional systems. We illustrate predictions in a FCC Ni-Cu-Au-Pd-Pt system.

Linton, Nathan (ORCID:0000000315485613)↗

DOE OSTI2024

Understanding Twinning and Deformation in High Entropy Alloys

On the one hand, multi-principal element alloys (MPEAs) have created a paradigm shift in alloy design due to large compositional space, whereas on the other, they have presented enormous computational challenges for theory-based materials design, especially density functional theory (DFT), which is inherently computationally expensive even for traditional dilute alloys. In this project, we developed a machine learning framework, namely PREDICT ( PR edict properties from E xisting D atabase I n C omplex alloys T erritory), that opens a pathway to predict elastic constants in large compositional space with little computational expense. The framework only relies on the DFT database of binary alloys and predicts Voigt–Reuss–Hill Young’s modulus, shear modulus, bulk modulus, elastic constants, and Poisson’s ratio in MPEAs. We show that the key descriptors of elastic constants are the A–B bond length and cohesive energy. The framework can predict elastic constants in hypothetical compositions as long as the constituent elements are present in the database, thereby enabling property exploration in multi-compositional systems. We illustrate predictions in a FCC Ni-Cu-Au-Pd-Pt system.

36 MATERIALS SCIENCE↗

DOE OSTI2024

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↗

NASA NTRS1974

Physical property measurements of doped cesium iodide crystals

Mechanical and thermal property values are reported for crystalline cesium iodide doped with sodium and thallium. Young's modulus, bulk modulus, shear modulus, and Poisson's ratio were obtained from ultrasonic measurements. Young's modulus and the samples' elastic and plastic behavior were also measured under tension and compression. Thermal expansion and thermal conductivity were the temperature dependent measurements that were made.

Synder, R. S.↗

NASA NTRS1978

Mechanical and physical properties of modern boron fibers

The results of accurate measurements of the modern boron fiber's Young's modulus, flexural modulus, shear modulus, and Poisson's ratio are reported. Physical property data concerning fiber density, thermal expansion, and resistance obtained during the course of the mechanical studies are also given.

Dicarlo, J. A.↗

NASA NTRS1978

Mechanical and physical properties of modern boron fibers

Measurements of the Young's modulus, flexural modulus, shear modulus and Poisson's ratio for boron fibers prepared by modern deposition techniques are reported. Physical properties of the boron fibers, including density, thermal expansion and resistance, are also surveyed. In addition, prediction of the total deformation strain in an anelastic boron fiber subjected to tensile or flexural stress is discussed.

Dicarlo, J. A.↗

NASA NTRS1984

Processing of sintered alpha SiC

Processing methods of sintered alpha SiC for engine applications are developed in a cost effective manner, using a submicron sized powder blended with sintering aids (boron and carbon). The processes for forming a green powder compact, such as dry pressing, cold isostatic pressing and green machining, slip casting, aqueous extrusion, plastic extrusion, and injection molding, are described. Dry pressing is the simplest route to component fabrication, and is carried out at approximately 10,000 psi pressure, while in the cold isostatic method the pressure could go as high as 20,000 psi. Surfactants are added to control settling rates and casting characteristics in the slip casting. The aqueous extrusion process is accomplished by a hydraulic ram forcing the aqueous mixture through a die. The plastic forming processes of extrusion and injection molding offer the potential of greater diversity in shape capacity. The physical properties of sintered alpha SiC (hardness, Young's modulus, shear modulus, and thermal diffusivity) are extensively tested. Corrosion resistance test results of silicon carbide are included.

Storm, R. S.↗

NASA NTRSDate not supplied

Multiscale Modeling of Thermoplastics Using Atomistic-informed Micromechanics

A multiscale model was developed for predicting the thermoelastic behavior of semi-crystalline thermoplastic materials for composite aerospace applications. At the highest scale containing the semi-crystalline spherulite in an amorphous matrix, the generalized method of cells, or high fidelity method of cells, was used to perform the homogenization calculations to obtain the effective properties. Models were developed assuming a cubic, or spherical shape, for the spherulite to understand if the morphology of the spherulite affects the effective thermoelastic properties. The generalized method of cells was used to model at the repeating unit cells at the subscales of the microstructure including the lamellae stacks and granular crystal blocks. The scales are integrated using the multiscale micromechanics method in the NASA Multiscale Analysis Tool. Data from molecular dynamics simulations were used as inputs for the amorphous and crystalline constituents. Convergence studies were performed to determine the best level of discretization for the repeating unit cell at the highest scale. Effective Young’s modulus, shear modulus, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity were predicted for polyether ether ketone and polyether ketone ketone, and very good agreement between the model utilizing the cubic spherulite and the experimental data, where available, was observed for polyether ketone ketone. Normalization of the data for the bulk polyether ketone ketone, against amorphous data, improved the predictions as compared to experimental data. Overall, the high fidelity method of cells predicted a stiffer response then the generalized method of cells as the crystallinity was increased. The shape of the spherulite had a minimal effect on the predicted bulk properties of the polymers.

thermoplastics↗

NASA NTRS2024

Multiscale Modeling of Thermoplastics Using Atomistic-informed Micromechanics

A multiscale repeating unit cell model of a single spherulite containing four disparate length scales was developed to predict the thermoelastic behavior of semicrystalline thermoplastic materials for composite aerospace applications. The continuum level scales were fully coupled and modeled using the generalized method of cells and the high fidelity generalized method of cells micromechanics theories. Data from molecular dynamics simulations were used as inputs for the amorphous and crystalline constituents in the multiscale continuum models. Effective Young’s modulus, shear modulus, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity were predicted for polyether ether ketone and polyether ketone ketone, showing good agreement with the available experimental data from the open literature. Moreover, it is shown that predicted properties are fairly insensitive to the fidelity of the micromechanics model used at the highest continuum scale or the assumed shape of the spherulite.

thermoplastics↗

DOE OSTI2023

AGC-2 Specimen Post Irradiation Data Package Report

This report documents results of the post-irradiation examination material property testing of the creep, control, and piggyback specimens from the irradiation creep capsule Advanced Graphite Creep (AGC)-2 are reported. This is the second of a series of six irradiation test trains planned as part of the AGC experiment to fully characterize the neutron irradiation effects and radiation creep behavior of current nuclear graphite grades. The AGC-2 capsule was irradiated in the Idaho National Laboratory Advanced Test Reactor at a nominal temperature of 600°C and to a peak dose of 5 dpa (displacements per atom). One half of the creep specimens were subjected to mechanical stresses (an applied stress of either 13.8, 17.2, or 20.7 MPa) to induce irradiation creep. All post-irradiation testing and measurement results are reported with the exception of the irradiation mechanical strength testing, which is the last destructive testing stage of the irradiation testing program. Material property tests were conducted on specimens from 15 nuclear graphite grades using a similar loading configuration as the first AGC capsule (AGC-1) to provide easy comparison between the two capsules. However, AGC-2 contained an increased number of specimens (i.e., 487 total specimens irradiated) and replaced specimens of the minor grade 2020 with the newer grade 2114. The data reported include specimen dimensions for both stressed and unstressed specimens to establish the irradiation creep rates, mass and volume data necessary to derive density, elastic constants (Young’s modulus, shear modulus, and Poisson’s ratio) from ultrasonic time of flight velocity measurements, Young’s modulus from the fundamental frequency of vibration, electrical resistivity, and thermal diffusivity and thermal expansion data from 100–500°C. No data outliers were determined after all measurements were completed. A brief statistical analysis was performed on the irradiated data and a limited comparison between pre- and post-irradiation properties is presented. A more complete evaluation of trends in the material property changes, as well as irradiation-induced creep due to irradiation, temperature, and applied load on specimens will be discussed in later AGC-2 post-irradiation examination analysis reports.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

AGC-4 Specimen Post-Irradiation Examination Data Interim Report

This interim report documents preliminary results of the post-irradiation examination material property testing from the fourth advanced graphite creep (AGC), AGC 4, capsule specimens. This is the fourth of a series of six irradiation test trains planned as part of the AGC experiment to fully characterize the neutron irradiation effects and radiation creep behavior of current nuclear graphite grades to moderate dose levels (=7 dpa). The AGC 4 capsule was irradiated in the Idaho National Laboratory Advanced Test Reactor at a nominal temperature of 800°C and to a peak dose of 8 dpa. Half of the AGC-4 specimens were subjected to compressive stresses to induce irradiation creep. Post-irradiation testing and measurement results are reported with the exception of thermal testing, which is still in progress, and irradiation mechanical strength testing. Additionally, some specimens initially deemed too hot to be examined in the ART Graphite laboratory may still be measured. The data reported includes specimen dimensions for both stressed and unstressed specimens to establish the irradiation creep rates, mass and dimensional data necessary to derive density, elastic constants (Young?s modulus, shear modulus, and Poisson?s ratio) from ultrasonic time of flight velocity measurements, Young?s modulus from the fundamental frequency of vibration, and electrical resistivity. A more complete evaluation of trends in the material property changes, as well as irradiation-induced creep due to the irradiation environment and applied load on the specimens, will be discussed later in AGC 4 post-irradiation examination analysis reports.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

AGC-4 Specimen Post-Irradiation Examination Data Interim Report

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1989

Adhesion in ceramics and magnetic media

When a ceramic is brought into contact with a metal or a polymeric material such as a magnetic medium, strong bonds form between the materials. For ceramic-to-metal contacts, adhesion and friction are strongly dependent on the ductility of the metals. Hardness of metals plays a much more important role in adhesion and friction than does the surface energy of metals. Adhesion, friction, surface energy, and hardness of a metal are all related to its Young's modulus and shear modulus, which have a marked dependence on the electron configuration of the metal. An increase in shear modulus results in a decrease in area of contact that is greater than the corresponding increase in surface energy (the fond energy) with shear modulus. Consequently, the adhesion and friction decrease with increasing shear modulus. For ceramics in contact with polymeric magnetic tapes, environment is extremely important. For example, a nitrogen environment reduces adhesion and friction when ferrite contacts polymeric tape, whereas a vacuum environment strengthens the ferrite-to-tape adhesion and increases friction. Adhesion and friction are strongly dependent on the particle loading of the tape. An increase in magnetic particle concentration increases the complex modulus of the tape, and a lower real area of contact and lower friction result.

Miyoshi, Kazuhisa↗

DOE OSTI2022

Effect of Cr and Al on Elastic Constants of FeCrAl Alloys Investigated by Molecular Dynamics Method

The FeCrAl alloy system is recognized as one of the candidate materials for accident-tolerant fuel (ATF) cladding in the nuclear power industry due to its high oxidation resistance under irradiation and high-temperature environments. The concentrations of Cr and Al have a significant effect on elastic properties of the FeCrAl alloy. In this work, elastic constants C 11 , C 12 , C 44 , bulk modulus and shear modulus of FeCrAl alloy were calculated with molecular dynamics methods. We explored compositions with 1–15 wt.% Cr and 1–5 wt.% Al at temperatures from 0 K to 750 K. The results show that the concentrations of Al and Cr have different effects on the elastic constants. When the concentration of Al was fixed, a decrease in bulk modulus and shear modulus with increasing Cr content was observed, consistent with previous experimental results. The dependence of elastic constants on temperature was also the same as in the experiments. Investigations into elastic properties of defect-containing alloys have shown that vacancies, voids, interstitials and Cr-rich precipitations have different effects on elastic properties of FeCrAl alloys. Investigations of elastic properties of defect-containing alloys have shown that vacancies, void, interstitials and Cr-rich precipitations have different effects on elastic properties of FeCrAl alloys. Therefore, the present results indicate that both the Cr and Al concentrations and radiation defects should be considered to develop and apply the FeCrAl alloy in ATF design.

36 MATERIALS SCIENCE↗