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Amit Cohen

Publications and source records attributed to Amit Cohen.

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Benchmarking Transparent Conductors

Transparent conducting oxides (TCOs) are central to optoelectronic technologies, yet their design is often guided by popular figures of merit that are disconnected from the electrical requirement of actual devices. As a result, widely used metrics guide material design under conditions that can be impractical for devices. Here, we introduce a benchmarking framework to guide TCO development, in which transparent conductors are evaluated at fixed, application-relevant sheet resistance $(R_S)$. The resulting metric, $T_{app}(R_S)$, anchors comparison to device requirements, asking instead: What optical transparency can be obtained at the sheet resistance required by a given application? This approach provides a directly interpretable measure of performance, enabling materials to be benchmarked in terms of absolute transparency gains at a specified $R_S$. Applied to representative conventional and emerging TCOs, the framework defines the sheet-resistance landscape relevant to each application and maps how different materials perform within it. In doing so, it provides an application-rooted guide to material development and selection. More broadly, this approach establishes a general strategy for evaluating materials under fixed operational constraints, bridging the gap between materials design and device integration.

cond-mat.mtrl-sci

Real-time Observation of Thermal Surface Recovery in $SrVO_3$

$SrVO_3$ (SVO), a model correlated metal and a promising transparent conducting oxide, develops a several-nanometer-thick near-surface region (NSR), rich in $V^{5+}$ species under ambient conditions. This oxidized layer obscures the intrinsic correlated-metallic $V^{4+}$ character and limits both fundamental studies of the physics and the material's integration into electronic devices. Here, we demonstrate a direct and controllable approach for recovering the metallic SVO surface by thermally reducing the NSR under ultra-high vacuum. Real-time in-situ X-ray photoelectron spectroscopy (XPS) reveals a sharp transformation from a $V^{5+}$-dominated surface to mixed valence states, dominated by $V^{4+}$, and a recovery of its metallic character. Ex-situ X-ray diffraction (XRD), atomic force microscopy (AFM), and high-resolution scanning electron microscopy (HR-SEM) suggest that this transformation is accompanied by mass redistribution and partial oxygen loss, leading to nanoscale surface reorganization and modest lattice expansion. While thermodynamic considerations motivate evaluation of a $V_2O_5$ volatilization pathway, the combined experimental evidence instead points toward a predominantly structural surface reorganization. These findings establish a practical method for obtaining predominantly $V^{4+}$ SVO surfaces without protective capping layers, a capability that expands the utility of SVO for advanced spectroscopies, interface engineering, and oxide-electronics device integration.

cond-mat.mtrl-sci

Unleashing Automated Congestion Control Customization in the Wild

Congestion control (CC) crucially impacts user experience across Internet services like streaming, gaming, AR/VR, and connected cars. Traditionally, CC algorithm design seeks universal control rules that yield high performance across diverse application domains and networks. However, varying service needs and network conditions challenge this approach. We share operational experience with a system that automatically customizes congestion control logic to service needs and network conditions. We discuss design, deployment challenges, and solutions, highlighting performance benefits through case studies in streaming, gaming, connected cars, and more. Our system leverages PCC Vivace, an online-learning based congestion control protocol developed by researchers. Hence, along with insights from customizing congestion control, we also discuss lessons learned and modifications made to adapt PCC Vivace for real-world deployment.

cs.NI