FEATURE OF HIGH-ENTROPY DATABASE

Our database is differentiated with other existing material genome database by solely focusing on high-entropy materials with multiple elements mixing. These materials have a super-large compositional space, leading to massive materials, structures, and properties that require theoretical prediction, high-throughput synthesis, and data mining and machine learning. The online database acts as the data reservoir for both theoretical, experimental and simulated results, and are the starting point for data mining and machine learning.

HIGH-ENTROPY MIXING

High entropy materials (HEM) are defined as materials that mix equal or near equal of five or more elements. A thermodynamic description of HEMs emphasizes the role of their mixing configurational entropy in stabilizing the materials in a single phase solid-solution structure. 

COMPLEX SURFACE CHEMISTRY

Owing to the mixing of many largely dissimilar elements, HEMs possess complex particle structures and especially surface chemistry, allowing bi-continuous tuning of HEMs' chemistry for material discovery and property optimization.

HUGE COMPOSITION SPACE

For metallic HEMs alone, there are at least 200,000 equimolar HEAs . If we further extend the material of choice to ceramics (oxides, nitrides, sulfides etc), and considering different size, structure, or substrates, there has unlimited space for exploration.

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