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Understanding how the arrangement of atoms and their interactions determine material behavior has been the dominant paradigm in materials science. A complementary approach is studying the organizational structure of networks of materials, defined on the basis of interactions between materials themselves. In this work, we present the phase diagram of all known inorganic materials, an extremely-dense complex network of nearly $2.1 times 10^4$ stable inorganic materials (nodes) connected with $41 times 10^6$ tie-lines (edges) defining their two-phase equilibria, as computed via high-throughput density functional theory. We show that the degree distribution of this network follows a lognormal form, with each material connected to on average 18% of the other materials in the network via tie-lines. Analyzing the structure and topology of this network has potential to uncover new materials knowledge inaccessible from the traditional bottom-up (atoms to materials) approaches. As an example, we derive a data-driven metric for the reactivity of a material as characterized by its connectedness in the network, and quantitatively identify the noblest materials in nature.
Phase diagrams are an invaluable tool for material synthesis and provide information on the phases of the material at any given thermodynamic condition. Conventional phase diagram generation involves experimentation to provide an initial estimate of
Synthesis of advanced inorganic materials with minimum number of trials is of paramount importance towards the acceleration of inorganic materials development. The enormous complexity involved in existing multi-variable synthesis methods leads to hig
The recently introduced theories of Topological Quantum Chemistry and Symmetry-Based Indicators (SIs) have facilitated the discovery of novel topological phases of matter and large-scale searches for materials with experimentally accessible topologic
Chemical doping is one of the most important strategies for tuning electrical properties of semiconductors, particularly thermoelectric materials. Generally, the main role of chemical doping lies in optimizing the carrier concentration, but there can
Leveraging new data sources is a key step in accelerating the pace of materials design and discovery. To complement the strides in synthesis planning driven by historical, experimental, and computed data, we present an automated method for connecting