Electronic structure and thermodynamics modeling of complex metal oxides in the environment
Creators: name: Hudson, Blake G.
Publisher: name: University of Iowa
Year: 2024
Subjects: Density Functional Theory
Li-ion cathode
Metal release
Nano agriculture
public abstract

description: Li-ion batteries are found in numerous electronic devices due to their ability to store charge and their rechargeable properties. With rising demands in renewable energy, the production of these materials has been exponentially increasing, however, the infrastructure for properly disposing batteries does not exist. This results in tons of Li-ion batteries being introduced to the environment at their end-of-life. When exposed to aqueous conditions, the cathode material breaks down, releasing toxic ions. Our cathode studied in this work begins with Li(Ni1/3Mn1/3Co1/3)O2 (333-NMC). Another class of nanomaterials that have been gaining interest are those used in agriculture due to their benefits of improving plant immune response in diseased soils, retaining water, and increasing crop yields. This work specifically looks at Cu-based nanomaterials CuO and Cu3(PO4)2. With the very different impacts these materials have on the environment, it is essential to understand what governs metal release so that we can design future materials with desired release properties. In order to understand what features control material stability, we employ a DFT model to calculate vacancy formation energies and combine experimental data to incorporate aqueous effects to the model. First, we tune the composition of the battery cathode and compare changes in release back to the parent equistoichiometric composition 333-NMC. To understand the shifts in release favorability, we can use electronic structure methods to observe changes in metal oxidation states going from the 333-NMC material to a Ni-enriched composition. In addition to adjusting the ratio of metals within a composition, newly proposed equistoichiometric formulations with stable and earth-abundant metals can be substituted in place of the toxic cations to expand our dataset. By maintaining an equistoichiometric composition we can hold the oxidation states of most of our metals constant to deduce other features of the material that can control release beyond oxidation state such as unpaired spins.
description: To test the sensitivity of the model, we move on to doping studies where we only change 10% of the composition in our model where previous studies changed the composition by as much as 50%. Our dopant selected is Al which has shown to have stabilizing effects through improving the cyclability of other battery materials. This dopant is added to a Ni-enriched NC cathode. Here we maintain oxidation states of 3+ for all surface metals but can observe Ni sites that have varying chemical environments to further understand how neighboring metal environments can affect release sites.
description: Further studies consider the charge state of the cathode as it will not always be fully lithiated upon disposal. The functionality of the battery is derived from the redox properties of the transition metals where Ni will oxidize from 2+ to 3+ over the first third of delithiation, 3+ to 4+ over the next third, and Co will oxidize from 3+ to 4+ over the final delithiation steps. This study ties together the two features of oxidation state and unpaired spin as well as understanding how to better model voltages of cathodes at intermediate lithiation states.
description: The final cathode chapter investigates release past the initial vacancy to see if trends persist with the DFT release model. This introduces further complexity as we will have to consider how the proximity to the initial vacancy will affect subsequent release. This complexity causes us to model additional secondary vacancy configurations which can be used as a dataset to build a machine learning model. Through this study we compare the importance our two features will have on release favorability.
description: In addition to material features that control release, we add elementary steps to our model to consider the affect the media composition will have on material stability. In a number of cathode studies the presence of lactate is studied as it has shown to increase the amount of metal release and can shift release favorability from an incongruent trend observed in just water to a congruent release trend. The Cu work has multiple species tested in aqueous media showing that the DFT model produces accurate trends for media dependent release. Through comparing CuO and Cu3(PO4)2 we can learn how the change in anion can affect Cu-OH release and begin collecting data to train a machine learning model to predict release favorability beyond the cathode materials. Ultimately, this work seeks to build a model that can assist in materials design for materials with controlled release properties.