Exploration of High-Pressure Electride, Polymorphic Transformations, and Superconducting Clathrate Frameworks

The exponential growth of high-performance computing resources has transformed first-principles modeling into a cornerstone of condensed matter research. Today, large-scale density-functional theory calculations, accelerated by machine-learned interatomic potentials and high-throughput workflows, routinely predict phase stability, electronic structure, and functional properties with near-experimental accuracy. These computational insights not only elucidate fundamental bonding and lattice dynamics under extreme conditions but also reliably direct experimental efforts, guiding the synthesis and characterization of novel superconductors, metal-to-insulating materials, and exotic high-pressure phases. This thesis harnesses first-principles and computational methodologies to predict structures and investigate structural, electronic, topological, vibrational, superconducting, and dynamical properties of selected elemental and extended solids. The first project aims to investigate the impact of encapsulating molecular hydrogen within a new dynamically stable boron–carbon clathrate on electron–phonon coupling interactions and the superconducting transition temperature (Tc). A notable characteristic of (H2)B3C3 is the dynamic behavior of the H2 molecules, which exhibit nearly free rotations within the B–C cages, resulting in a dynamic structure that remains cubic on average. The static structure of (H2)B3C3 is calculated to be dynamically stable at ambient and low pressures. The electron counts and electronic structure calculations indicate that (H2)B3C3 is a hole conductor, in which H2 molecules donate a portion of their valence electron density to the metallic cage framework. Electron–phonon coupling calculation predicts that (H2)B3C3 possesses a Tc of 46 K under ambient pressure. The second project unveils the elusive sodium’s tl50 phase and predicts it to be a body-centered tetragonal electride. The research determines the crystal structure of the phase using a data-derived potential-assisted structure search to be a body-centered tetragonal structure with 50 atoms per unit cell, crystallizing in the I4/m space group. The predicted lattice parameters deviate by less than 0.38% from experimental values, and the enthalpy calculation confirms this structure as the ground state for sodium across a ~20 GPa pressure range. The structure features a cage-like polyhedral network with interstitial electride states. Topological analysis of the electron density reveals well-defined non-nuclear attractors (NNAs) inside the ELF basins at four distinct Wyckoff positions, and these NNAs exhibit local maxima of electron density with all three principal curvatures being negative. Resolving this unique structure advances understanding of sodium’s diverse structural behavior under high pressure. The final project deploys a machine learning‐accelerated crystal structure approach to map enthalpy–pressure landscapes of elemental calcium, rapidly identifying stable and low‐lying metastable phases. Two novel energetically favorable phases are predicted at 200 GPa and 250 GPa, respectively. The primitive tetragonal structure with 10 atoms in its unit cell and the primitive trigonal structure containing 20 atoms in its unit cell (P-31c). The two structures are found to be superconducting, and Tc, of the P-31c was calculated to be 31 K, making this the highest calculated Tc of elemental calcium.

Name thesis:degree_name

Doctor of Philosophy (Ph.D.)

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Physics

Grantor

University of Saskatchewan

Year dc:date.issued

2025

Author dc:creator

• Akinpelu, Akinwumi

Advisor dc:contributor.advisor

• Yao, Yansun

Committee members dc:contributor.committeemember

• Moewes, Alexander
• Bourassa, Adam
• Green, Robert
• Abdelrassoul, Amira
• Maosheng, Miao

• Electride, Clathrate, Machine Learning, Superconductivity

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10388/17403

OAI identifier oai:identifier

oai:harvest.usask.ca:10388/17403