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Anna Sacchi

Publications and source records attributed to Anna Sacchi.

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Revealing the Atomic Structure of NiO/Ga$_{2}$O$_{3}$ Interfaces

NiO/Ga$_{2}$O$_{3}$ heterojunctions have garnered significant attention for use in power electronics due to the ultrawide bandgap and wafer-scale availability of Ga$_{2}$O$_{3}$ and the controllable p-type doping of NiO. However, the structure of NiO/Ga$_{2}$O$_{3}$ interfaces remains underexplored, largely due to the complexity of the junction between their dissimilar cubic and monoclinic crystal structures. Here we investigate the atomistic structure of the NiO/Ga$_{2}$O$_{3}$ interface for (100), (-201), and (001) oriented Ga$_{2}$O$_{3}$ substrates using aberration-corrected scanning transmission electron microscopy (STEM) in combination with interface modeling and image simulations. We evaluate the abruptness and consistency of the interfaces and compare them to calculated interface models, proposing precise atomic structures and assessing potential structural variation arising from complexity of the monoclinic Ga$_{2}$O$_{3}$ crystal structure. Our interface analysis supports increased focus on (100) oriented Ga$_{2}$O$_{3}$ as a candidate for fabricating high quality, low defect density NiO/Ga$_{2}$O$_{3}$ heterojunction devices. Importantly, we consider the effects of specimen thickness and 3D-to-2D projection during the STEM imaging process to differentiate such effects from real crystal variations. This work provides insight into the effect of substrate orientation on NiO film and interface quality, creating a pathway to improving heterojunction properties. It further highlights important considerations for interpretation of stability and interlayer phase formation in these interfaces, which is crucial for their integration into reliable and robust power electronic devices.

cond-mat.mtrl-sci

Fast Homoepitaxy on (100) \b{eta}-Ga2O3 Substrates with Large Grown-In Offcut

The choice of crystalline orientation and offcut angle is non-trivial for low-symmetry $\beta\text{-Ga}_2\text{O}_3$, where anisotropy impacts bulk and thin film synthesis, material properties, and power device fabrication and performance. Scalable (100)-oriented $\beta\text{-Ga}_2\text{O}_3$ wafers are desirable for electronic devices but are not typically used due to 10-30x slower growth rates compared to other orientations. Here we report molecular beam epitaxy (MBE) growth rates equal to the fast growth direction by using (100) $Ga_2O_3$ wafers with large grown-in offcuts. The offcuts (up to 13.4{\deg}) are directly grown by Edge-defined Film-fed Growth (EFG) of 2D ribbons with rotated seed crystals, avoiding material loss from crystal boule offcut methods while maintaining high crystalline quality. Chemical-mechanical polishing produces epitaxy-ready substrates, and step flow growth is observed across all offcut angles. We measure an unintentional n-type doping density of $2{\times}10^{15} cm^{-3}$, one of the lowest values reported for MBE-grown films. Planar Schottky barrier diodes on these epilayers without edge termination have an on/off ratio ~10$^5$ and an average breakdown field of 1.56 MV/cm, comparable to or exceeding similar devices fabricated on other orientations. Overall, these results illustrate the importance of both crystal face and offcut angle and validate the use of the scalable (100)-oriented $\beta\text{-Ga}_2\text{O}_3$ wafers.

cond-mat.mtrl-sci

Autonomous Reliability Qualification of Ga$_2$O$_3$-based diode sensors via Safe Active Learning

Ultra-wide bandgap (UWBG) Ga$_2$O$_3$ is a promising semiconductor for high-power and high-temperature electronics. Reliable qualification of these devices under extreme operating conditions is essential, yet conventional reliability testing is inherently time-consuming. Autonomous experimentation offers a new paradigm by enabling measurement planning and model refinement to evolve in parallel in real time. We present a Safe Active Learning (SAL) framework for autonomous reliability characterization of Ga$_2$O$_3$-based diode sensors under coupled thermal and hydrogen stress. We first evaluate SAL in simulation, where it safely expands the explored region while learning the evolving rectification surface. Second, we demonstrate SAL experimentally on an automated high-temperature probe-station platform using a Pt/Cr$_2$O$_3$:Mg/$\beta$-Ga$_2$O$_3$ diode sensor of H$_2$ and temperature, spanning 0-800 ppm H$_2$ and 350-550 {\deg}C. Finally, we use the SAL-generated dataset for offline long-horizon forecasting of the diode current at a target voltage with a structured Gaussian-process model. Its condition-dependent Kohlrausch--Williams--Watts mean and residual covariance kernel were engineered with artificial-intelligence assistance using the SAL data and an auxiliary validation dataset spanning 1,000 hours at 400 {\deg}C across multiple H$_2$ concentrations. This dataset guided kernel design and validation, and the resulting model captures its long-time, saturating degradation trends. Although demonstrated here for a rectifying Ga$_2$O$_3$-based diode, SAL is applicable to other device classes whenever a suitable safety observable can be measured in situ.

physics.app-ph