Collaborative Research: Multiscale Modeling of Amorphous Solids - Energy Landscapes to Failure Prediction

Harvard University, Cambridge MA

Investigators

Abstract

NONTECHNICAL SUMMARY This award supports theoretical and computational research, and education to advance understanding of how amorphous materials fail or break under mechanical stress. Amorphous solids are a category of materials that share the distinction that they do not exhibit any crystal structure. Examples include colloidal pastes, foams, gels, silicate glasses, like window glass and Gorilla(R) glass, and many consumer plastics. This research will lay the groundwork for understanding how these materials respond to stresses and eventually fail so as to guide the use of existing materials as well as the development of new materials. The research focuses on metallic glass as an exemplary amorphous solid. Metallic glasses are an extremely promising emerging class of high strength metallic materials, but their application is limited by their failure mechanisms and the current inability to predict their behavior when subjected to mechanical loads. Improved predictive capabilities are necessary for guiding the design and utilization of failure tolerant metallic glass alloys that will have broad application in medicine, defense and consumer goods. This research will build mathematical descriptions of metallic glasses based on simulations performed on the atomic scale. Computational methods to implement these mathematical descriptions will then be developed so as to estimate both the material behavior and the reliability of the predictions that result. The techniques developed will be broadly disseminated through open source computer codes. Additionally, the project will be integrated with educational research and outreach activities of the investigators, which include broad systemic engagement within Baltimore City elementary schools, improvement of introductory computing education, outreach focused on improving participation of women and URM students at both the high-school and undergraduate levels in engineering research, and public lectures at libraries. NONTECHNICAL SUMMARY This award supports theoretical and computational research, and education to advance understanding of how amorphous materials fail under mechanical stress. The research team aims to develop physics-based multiscale models of failure processes in amorphous solids, with metallic glass taken as an exemplar material. The physics accessible via atomic scale models of glass structure will be analyzed to obtain statistics of the shear transformation zone defects that control plastic deformation. These will be related to statistical mechanics models of effective temperature that characterize the degree of glass disorder so as to build a constitutive model of plastic deformation. The constitutive model will in turn be incorporated into a high-fidelity 3D viscoplastic finite differencing scheme that adapts techniques originally developed for solving the Navier-Stokes equation. A novel machine learning algorithm will guide the parameterization of the constitutive model from atomistic data so as to inform the continuum method and provide uncertainty quantification. The simulation methods will be pushed to increase the scales on which failure can be modeled by developing a statistical representative-volume element approach incorporating adaptive meshing and resulting in true multiscale simulations of failure in amorphous solids. In doing so, this research is aimed to broadly advance fundamental understanding of how the macroscopic mechanical response of amorphous solid materials is informed by their atomic scale structures. The research will result in the development of methods for making direct connections between atomic scale data and theories applicable on the continuum scale. These will include novel machine learning methods and new numerical schemes for failure prediction that incorporate uncertainty quantification. Ultimately, this work will result in an improved understanding of how amorphous microstructure controls failure on the macro scale. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.