Application of Strain Functionals for Physics Informed Machine Learning
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The effect of grain boundary yield and disconnections on grain boundary fracture strength
During high-temperature interfacial strain, e.g., creep or sintering, grain boundaries will sample non-equilibrium states associated with the non-equilibrium disconnections that mediate strain. This work tests the hypothesis that those non-equilibrium states should affect the mechanical properties of the grain boundary. High-temperature bicrystal tensile strain experiments performed on Sc-doped ZrO 2 as a function of strain rate enable the observation of fracture before and after grain boundary yield. Yielded boundaries exhibit a median fracture strength ≈ 50 % lower than those that did not yield. Molecular dynamics simulations performed on boundaries with and without interstitial-type disconnection loops indicate that the presence of those loops reduce the failure stress.
36 MATERIALS SCIENCE↗
Collaborative Research: The Role of Grain Boundary Structure and Chemistry in Materials Failure
Throughout the one year duration of this award significant progress was made in understanding the effect of grain boundaries in polycrystalline materials. The starting point of this work is that each grain boundary can be characterized by an interface energy and respective interface parameter, which depend on the boundary chemical composition and structure. As this is a new point of view for treating grain boundaries, an interdisciplinary approach was followed to prove the existence of such interface terms. Throughout the project, hence, theory, experiments and simulations were used. Molecular dynamics and dislocation density-function dynamics were performed to understand dislocation-grain boundary interactions in pure Al crystalline materials, as potentials for Al are well established. The formation of dislocation pile-ups was observed and the strain profiles were in agreement with interfacial gradient plasticity, which is the theoretical framework that allows the introduction of mechanically induced interface energies. After verifying numerically the existence of mechanically induced interface energies, nanoindentation experiments were performed near grain boundaries of Fe-Si crystals that contained three grain boundaries. By indenting in close proximity to the boundary these experiments allowed for measuring the critical stress at which deformation was transmitted across the boundary to the adjacent grains, either through dislocation transmission or absorption and subsequent emission. This critical stress, also termed grain boundary yield stress, was in accordance with the value predicted by interfacial gradient plasticity, further verifying that mechanically induced interface energies can help define the material response. In the Fe-Si crystals the Si content was kept constant at 3wt%, but three specimen were considered each of which was characterized by a different misorientation at the grain boundary. By relating the experiments with the analytical gradient plasticity expressions it was possible to obtain first estimates for the interface parameter as ~200N/m. This value was not proportional to the misorientation angle, but depended also on the grain boundary plane. The continuation of this project is performing more detailed experiments on additional Fe-Si and Fe-C systems (both nanoindentation and in-situ transmission electron microscopy) to further understand the physical origin of such interface parameters. Furthermore, molecular dynamics nanoindentation simulations are also performed on similar systems to better understand the dislocation grain boundary interactions.
36 MATERIALS SCIENCE↗
Atomistic insights into the synergistic effects of tensile strain and hydroxyl group on increasing the thermal conductivity of monohydric alcohols as latent heat storage materials
The low thermal conductivity of linear monohydric alcohols significantly limits their performance when used as latent heat storage materials. It was found that imposing certain mechanical strains on nanomaterials with highly ordered structures can lead to appreciable thermal conductivity enhancement. To explore the potential of enhancing the intrinsic thermal conductivity of monohydric alcohols, a simplified ideal crystal model was employed for molecular arrangement in this work. The variation of atomistic heat transfer as a function of tensile strains was exploited by non-equilibrium molecular dynamics simulations. Furthermore, the influence of stretching on the vibration density of states and the corresponding molecular morphology were revealed. The results suggested that the thermal conductivity of monohydric alcohols with such simplified ideal crystalline structures can increase by about 170 % at the strain of 0.1. The distance between neighboring interfaces was found to determine the energy of inter-molecular interactions at the crystal grain boundaries. The hydrogen bonds energy has not reached the critical value when increasing tensile strains from 0 to 0.1. In contrast, the strongest van der Walls interactions for alkanes were obtained at the strain of 0.06 where the interfacial distances of alkanes have achieved their equilibrium distances. In addition, the interfacial heat transfer coefficient of ideal crystal monohydric alcohols at hydroxyl interfaces was found to be threefold than that between methyl interfaces, in consistent with the strength of inter-molecular interactions between functional groups at the interfaces.
36 MATERIALS SCIENCE↗
On the ultimate tensile strength of tantalum
Strain rate, temperature, and microstructure play a significant role in the mechanical response of materials. By using non-equilibrium molecular dynamics simulations, we characterize the ductile tensile failure of a model body-centered cubic metal, tantalum, over six orders of magnitude in strain rate. Molecular dynamics calculations combined with reported experimental measurements show power-law kinetic relationships that vary as a function of dominant defect mechanism and grain size. The maximum sustained tensile stress, or spall strength, increases with increasing strain rate, before ultimately saturating at ultra-high strain rates, i.e. those approaching or exceeding the Debye frequency. The upper limit of tensile strength can be well estimated by the cohesive energy, or the energy required to separate atoms from one another. At strain rates below the Debye frequency, the spall strength of nanocrystalline Ta is less than single crystalline tantalum. This occurs in part due to the decreased flow stress of the grain boundaries; stress concentrations at grain boundaries that arise due to compatibility requirements; and the growing fraction of grain-boundary atoms as grain size is decreased into the nanocrystalline regime. In the present cases, voids nucleate at defect structures present in the microstructure. The exact makeup and distribution of defects is controlled by the initial microstructure and the plastic deformation during both compression and expansion, where grain boundaries and grain orientation play critical roles.
36 MATERIALS SCIENCE↗
Predicted Fracture Tendency of Naturally Occurring Aluminum Surface Coatings under Tensile Loading
Naturally occurring coatings on aluminum metal, such as its oxide or hydroxide, serve to protect the material from corrosion. Understanding the conditions under which these coatings mechanically fail is therefore expected to be an important aspect of predictive models for aluminum component lifetimes. To this end, we develop and apply a molecular dynamics (MD) modeling framework for conducting tension tests that is capable of isolating factors governing the mechanical strength as a function of coating chemistry, defect morphology, and variables associated with the loading path. We consider two representative materials, including γ-Al 2 O 3 and γ-Al(OH) 3 (i.e., oxide and hydroxide), both of which form readily as aluminum surface coatings. Our results indicate that defects have a significant bearing on the strength of aluminum oxide, with grain boundaries serving to reduce the strain at failure from ε zz = 0.300 to 0.219, relative to perfect single crystal. Our simulations also predict that porosity lowers the elastic stiffness and yield strength of the oxide. Relative to perfect crystal, we find porosity factors of 5%, 10% and 20% decrease the yield stress by 26%, 36% and 53%, respectively. MD predicts that perfect hydroxide and oxide single crystal have respective strains at failure of 0.08 and 0.31 under tensile uniaxial strain loading, and that the corresponding yield stresses are respectively 1.6 and 11.1 GPa. These data indicate that the hydroxide is substantially more susceptible to mechanical failure than the oxide. Our results, coupled with literature findings that indicate hot and humid conditions favor formation of hydroxide and defective oxide coatings, indicate the potential for a complicated dependence of aluminum corrosion susceptibility and stress corrosion cracking on aging history.
36 MATERIALS SCIENCE↗
Local structural ordering determines the mechanical damage tolerance of amorphous grain boundary complexions
Amorphous grain boundary complexions act as toughening features within a microstructure because they can absorb dislocations more efficiently than traditional grain boundaries. This toughening effect should be a strong function of the local internal structure of the complexion, which has recently been shown to be determined by grain boundary crystallography. To test this hypothesis, molecular dynamics are used here to simulate dislocation absorption and damage nucleation for complexions with different distributions of structural short-range order. Here, the complexion with a more disordered structure away from the dislocation absorption site is actually found to better resist crack nucleation, as damage tolerance requires delocalized deformation and the operation of shear-transformation zones through the complexion thickness. The more damage tolerant complexion accommodates plastic strain efficiently within the entire complexion, providing the key mechanistic insight that local patterning and asymmetry of structural short-range order controls the toughening effect of amorphous complexions.
36 MATERIALS SCIENCE↗
Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning
While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.
36 MATERIALS SCIENCE↗
Learning from metastable symmetric-tilt grain boundaries using physics-based descriptors
Grain boundaries (GBs) govern critical properties of polycrystalline materials. Although significant advancements have been made in characterizing minimum energy and ordered GBs, real GBs are seldom found in such well-defined states. This diversity of atomic arrangements in metastable states makes it challenging to establish structure-property relationships with physical insights. Here, to address this challenge, we use data-driven methods to explore these relationships and examine the underlying physics. In this study, we utilize a large atomistic database (~5000) of minimum energy and metastable states of symmetric-tilt copper GBs, combined with physically motivated local atomic environment (LAE) descriptors [strain functional descriptors (SFDs)], to predict GB properties and gain physical insights. Our regression models exhibit robust predictive capabilities using only 19 descriptors, generalizing to atomic environments in nanocrystals. A significant highlight of our work is the integration of an unsupervised method with SFDs to elucidate LAEs at GBs and their role in determining properties. The model, trained on these minimum energy and metastable GBs using SFDs, predicts the properties of unseen nanocrystals with good accuracy. Our research underscores the role of a physics-based representation of LAEs and the efficacy of data-driven methods in establishing GB structure-property relationships.
36 MATERIALS SCIENCE↗