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Thermodynamic bulk phase diagrams have become the roadmap used by researchers to identify alloy compositions and process conditions that result in novel materials with tailored microstructures. On the other hand, recent progress in experimental atomic-scale characterization techniques allows one to study the local chemical composition at individual defects such as interfaces, grain boundaries, dislocations and surfaces. They show that changes in the alloy composition can drive not only transitions in the bulk phases present in a material, but also in the concentration and type of defects they contain. Defect phase diagrams, using chemical potentials as thermodynamics variables, provide a natural route to study these chemically driven defects. Our results show, however, that the direct application of thermodynamic approaches can fail to reproduce the experimentally observed defect formation.
Therefore, we extend the concept to metastable defect phase diagrams to account for kinetic limitations that prevent the system from reaching equilibrium. We use ab initio calculations based on density functional theory to quantify the extension of regions where defect formation is expected. We successfully applied this concept to explain the formation of large concentrations of planar defects in supersaturated Fe2Nb Laves phases. In addition, we identify in a joint study with experiments conditions and structures in Mg-Al-Ca alloys for defect phase occurrence. The concept offers new avenues for designing materials with tailored defect structures.
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. This open-source software package powers the Materials Project.
In this particular contribution, the handling of obital-resolved "ICOHPLIST.lobster" files from Lobster was implemented in the software package (github handle: @JaGeo).
The ease with which an energetic material can be initiated by mechanical impact is a critical parameter directing material safety and application. While impact sensitivity metrics are traditionally derived experimentally, recent developments have highlighted that the phenomenon is amenable to first principles simulation. In this chapter, we will outline a fully ab initio approach to predict the relative impact sensitivities of energetic materials based on the mechanochemical principles that link the impact event to vibrational energy transfer.
This mechanism is key to rationalizing how a mechanical impact—which deposits energy into the low-frequency lattice vibrations—results in a molecular response. By simulating the vibrational energy levels (the so-called phonon density of states, PDOS) using first-principles computational methods (typically dispersion-corrected plane-wave density functional theory, PW-DFT) we can calculate the relative rate of energy propagation from the delocalized low-energy lattice vibrations through to the localized molecular modes. The latter traps the energy, which eventually results in bond rupture through heightened vibrational excitation.
This method, based on vibrational up-pumping, offers a route toward predicting the impact sensitivities of a broad range of energetic materials, provided the crystal structure of the compound (or salt or co-crystal) is known. While it does not offer insight into the sensitizing roles undoubtedly played by crystal defects or grain boundaries, it does provide a level of understanding at the molecular and crystal packing levels. Correspondingly, this approach offers a feedback mechanism to chemists and materials scientists to guide the design of new materials with desired impact sensitivity behavior.