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Elizabeth C. Dickey

Publications and source records attributed to Elizabeth C. Dickey.

2 recordsLinked to original sources

Ferroelectric Switching in ZnO/Zn1-xMgxO Heterostructures: Atomistic Insights into Interfacial Coupling and Layer Architecture

Ferroelectric switching in heterostructures couples composition, layer topology, temperature, and interfacial boundary conditions. ReaxFF molecular dynamics isolates these variables in ZnO/ Zn1- xMgxO/ZnO and Zn1-xMgxO/ZnO/ Zn1-xMgxO stacks. Within pristine, initially single-domain models, coupling to switchable Zn1-xMgxO reduces the applied field required to reverse ZnO by up to fivefold. Temperature generally lowers the coercive field, whereas Mg concentration produces a nonmonotonic response. At equal ZnO and Zn1-xMgxO (ZMO) proportions, structures with ZnO at the center switch at lower fields than those with ZMO at the center at all four temperatures examined, demonstrating a topology-dependent response. Layer-resolved trajectories reveal topology-dependent switching sequences with direction-dependent redistribution of normal stress near the heterointerfaces, consistent with a stress-assisted cooperative pathway. Limiting MgO-containing structures exhibit sequential multilevel switching or low-polarity trapping, depending on thickness and temperature. Fixed-charge atomistic simulations complement previous continuum descriptions by resolving structural, energetic, and local stress evolution under a common applied field. TEM and STEM-EDS observations provide experimental structural context for the modeled architectures. Together, the results establish layer topology and interfacial mechanical confinement as design variables for wurtzite ferroelectric heterostructures.

cond-mat.mtrl-sci↗

Accounting for Location Measurement Error in Imaging Data with Application to Atomic Resolution Images of Crystalline Materials

Scientists use imaging to identify objects of interest and infer properties of these objects. The locations of these objects are often measured with error, which when ignored leads to biased parameter estimates and inflated variance. Current measurement error methods require an estimate or knowledge of the measurement error variance to correct these estimates, which may not be available. Instead, we create a spatial Bayesian hierarchical model that treats the locations as parameters, it using the image itself to incorporate positional uncertainty. We lower the computational burden by approximating the likelihood using a non-contiguous block design around the object locations. We apply this model in a materials science setting to study the relationship between the chemistry and displacement of hundreds of atom columns in crystal structures directly imaged via scanning transmission electron microscopy. Greater knowledge of this relationship can lead to engineering materials with improved properties of interest. We find strong evidence of a negative relationship between atom column displacement and the intensity of neighboring atom columns, which is related to the local chemistry. A simulation study shows our method corrects the bias in the parameter of interest and drastically improves coverage in high noise scenarios compared to non-measurement error models.

stat.AP↗