Transition metal oxides that exhibit a metal-to-insulator transition (MIT) as a function of oxygen vacancy concentration are promising systems to realize energy-efficient platforms for neuromorphic computing. However, the current lack of understanding of the microscopic mechanism driving the MIT hinders the realization of effective and stable devices. Here we investigate defective cobaltites and we unravel the structural, electronic, and magnetic changes responsible for the MIT when oxygen vacancies are introduced in the material. We show that, contrary to accepted views, cooperative structural distortions instead of local bonding changes are responsible for the MIT, and we describe the subtle interdependence of structural and magnetic transitions. Finally, we present a model, based on first principles, to predict the required electric bias to drive the transition, showing good agreement with available measurements and providing a paradigm to establish design rules for low-energy cost devices.

Topotactic transformations involve structural changes between related crystal structures due to a loss or gain of material while retaining a crystallographic relationship. The perovskite oxide ${\mathrm{La}}_{0.7}{\mathrm{Sr}}_{0.3}\mathrm{Co}{\mathrm{O}}_3$ (LSCO) is an ideal system for investigating phase transformations due to its high oxygen vacancy conductivity, relatively low oxygen vacancy formation energy, and strong coupling of the magnetic and electronic properties to the oxygen stoichiometry. While the transition between cobaltite perovskite and brownmillerite (BM) phases has been widely reported, further reduction beyond the BM phase lacks systematic studies. In this paper, we study the evolution of the physical properties of LSCO thin films upon exposure to highly reducing environments. We observe the rarely reported crystalline Ruddlesden-Popper phase, which involves the loss of both oxygen anions and cobalt cations upon annealing where the cobalt is found as isolated Co ions or Co nanoparticles. First-principles calculations confirm that the concurrent loss of oxygen and cobalt ions is thermodynamically possible through an intermediary BM phase. The strong correlation of the magnetic and electronic properties to the crystal structure highlights the potential of utilizing ion migration as a basis for emerging applications such as neuromorphic computing.

Transition metal oxides (TMOs) are an important class of materials with diverse applications, ranging from memristors to photoelectrochemical cells. First-principles calculations are critical for understanding these complex materials at an atomic level and establishing relationships between atomic and electronic structures, particularly for probing quantities difficult or inaccessible to experiment. Here, we discuss computational strategies used to understand TMOs by focusing on two examples, a photoanode material, BiVO₄, and an oxide for low-power electronics, La_1−xSr_xCoO₃. We highlight key aspects required for the modeling of TMOs, namely, the descriptions of how oxygen vacancies, extrinsic doping, the magnetic state, and polaron formation impact their electronic and atomic structures and, consequently, many of the observed properties.