Electronic and Magnetic Interpretation of Linear Transition Metal Ions: Insights From X-ray Spectroscopy

Abstract

Technological advancements progress materials to the atomic level, and single-ion magnets (SIMs) provide several routes of prospective applications within the field of molecular magnetism. SIMs achieve a bi-stability of magnetism due to single-ion magnetic anisotropy that is devoid of long-range magnetic ordering. Li2(Li1-xFex)N achieves remarkable SIM properties that compare favourably with respect to the highest-performing TM- and Ln-SIM systems. The most popular method for preparing SIMs targets coordination chemistry approaches involving bulky organic and inorganic ligand environments encompassing a paramagnetic metal centre to maximise single-ion magnetic anisotropy. However, doping of transition metal ions within a diamagnetic extended solid-state host lattice, such as Li2(Li1-xFex)N, exists as a growing and prospective avenue of scientific pursuit achieving exceptional single ion properties, in spite of the challenges associated with the study of dopant ions. The application of core-level spectroscopic techniques facilitates an element-specific, high-brilliance probe to deduce a plethora of properties beyond laboratory-based methods. This thesis applies an array of inaugural spectroscopic techniques with computational interpretation for a series of monovalent, high symmetry TM systems, Li2(Li1-xTMx)N where TM = Mn, Fe, Co, Ni and Cu. Upon commencing this thesis, conclusive experimental quantification of orbital hybridisation of linear TM ions was contingent on theoretical measures. However, upon conclusion, the isolation and quantification of substantial 3d-4s orbital hybridisation and metal-to-ligand charge-transfer is unravelled through experimental measurements and corroborated through multiplet and ab initio calculations. The measurements and analysis methods developed have a direct view of application to analogue complexes to further support our understanding of high-performing SIMs and continued synthetic achievements within this ever-growing field.

Date of Award	31 Dec 2022
Original language	English
Awarding Institution	The University of Manchester
Supervisor	David Collison (Supervisor) & Michael Baker (Supervisor)