Computational Analysis of the Energetic Stability of High-Entropy Structures of a Prototypical Lanthanide-Based Metal–Organic Framework
Surbhi K. A. Kumar, Dorina F. Sava Gallis, David S. Sholl

TL;DR
This paper uses computational methods to study the stability of high-entropy metal-organic frameworks made with multiple lanthanide metals.
Contribution
The study introduces a computational approach combining DFT and MLIP to explore high-entropy MOF structures with up to five metals.
Findings
MLIP methods enable systematic exploration of thermodynamically stable MOF structures with multiple metals.
DFT and MLIP calculations reveal the energetic stability of high-entropy MOF configurations.
The convex hull analysis identifies stable phases in the complex compositional landscape of high-entropy MOFs.
Abstract
High-entropy materials are characterized by their complex compositions, typically comprising five or more elements in near-equiatomic proportions. Applying this concept to metal ions in metal–organic frameworks (MOFs) has paved the way for exploring a new class of high-entropy MOFs. While the compositional strategy of high-entropy materials leverages configurational entropy to aid thermodynamic stability, it also poses significant analytical challenges due to the vast compositional landscape and diverse phases that these materials can adopt. We present a computational study of several complexities associated with selecting potential high-entropy versions of a prototype lanthanide-based MOF. We compute the energetics of metal mixing of these heterometallic MOFs using density functional theory (DFT) and machine learning interatomic potential (MLIP) methods. The use of MLIP methods allows…
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Taxonomy
TopicsMachine Learning in Materials Science · Catalysis and Oxidation Reactions · Metal-Organic Frameworks: Synthesis and Applications
