Breakdown of the Wiedemann-Franz law in AB-stacked bilayer graphene

We present a simple theory of thermoelectric transport in bilayer graphene and report our results for the electrical resistivity, the thermal resistivity, the Seebeck coefficient, and the Wiedemann-Franz ratio as functions of doping density and temperature. In the absence of disorder, the thermal resistivity tends to zero as the charge neutrality point is approached; the electric resistivity jumps from zero to an intrinsic finite value, and the Seebeck coefficient diverges in the same limit. Even though these results are similar to those obtained for single-layer graphene, their derivation is considerably more delicate. The singularities are removed by the inclusion of a small amount of disorder, which leads to the appearance of a "window" of doping densities $0<n<n_c$ (with $n_c$ tending to zero in the zero-disorder limit) in which the Wiedemann-Franz law is severely violated.Comment: 5 pages, 2 figures. arXiv admin note: text overlap with arXiv:1811.0891

Frequency-dependent impedance of nanocapacitors from electrode charge fluctuations as a probe of electrolyte dynamics

The frequency-dependent impedance is a fundamental property of electrical components. We show that it can be determined from the equilibrium dynamical fluctuations of the electrode charge in constant-potential molecular simulations, extending in particular a fluctuation-dissipation for the capacitance recovered in the low-frequency limit and provide an illustration on water/gold nanocapacitors. This work opens the way to the interpretation of electrochemical impedance measurements in terms of microscopic mechanisms, directly from the dynamics of the electrolyte, or indirectly via equivalent circuit models as in experiments

Leveraging Drug Repurposing: A Strategic Approach to Combat Bacterial Infections.

Aerospace physiology Leveraging Drug Repurposing: A Strategic Approach to Combat Bacterial Infections. Author Information: Wesley A. Flewelling, Anderson Y. Jeon and Giovanni Benjamin Faculty mentor: Dr. Alba Chavez The emergence of antibiotic resistant bacterial strains poses a critical threat to global public health, necessitating innovative strategies to address this challenge. Drug repurposing, the process of identifying new therapeutic uses for existing drugs, has emerged as a promising approach to Accelerate the development of effective treatments for bacterial infections. This research aims to highlight the importance of drug repurposing in the context of bacterial infections in an effort to emphasize the various advantages it offers over traditional drug discovery methods. We have selected 6 drugs that are not infrequently used to treat infections (including gentamycin sulfate, simvastatin, caspofungin, finasteride, ketorolac and clarithromycin) and tested their efficacy as antibacterial agents using four bacterial strains (Escherichia, Serratia, Micrococcus and Bacillus) as target model systems. We performed a comprehensive high throughput screening using a 96 well microplate approach and determined the Minimum Inhibitory Concentration (MIC) of bacterial growth. Our results indicate that Finasteride and Ketorolac are effective against the gram-negative bacteria Escherichia and Serratia, whereas Caspofungin and Clarithromycin are the most effective against the gram-positive Micrococcus and Bacillus. These results shed light into future perspectives of antimicrobial agents and possible treatments for fastidious infections. Embracing drug repurposing as a complementary strategy to traditional drug discovery efforts holds tremendous potential in the fight against bacterial infections

CAPRICORN: Communication Aware Place Recognition using Interpretable Constellations of Objects in Robot Networks

Using multiple robots for exploring and mapping environments can provide improved robustness and performance, but it can be difficult to implement. In particular, limited communication bandwidth is a considerable constraint when a robot needs to determine if it has visited a location that was previously explored by another robot, as it requires for robots to share descriptions of places they have visited. One way to compress this description is to use constellations, groups of 3D points that correspond to the estimate of a set of relative object positions. Constellations maintain the same pattern from different viewpoints and can be robust to illumination changes or dynamic elements. We present a method to extract from these constellations compact spatial and semantic descriptors of the objects in a scene. We use this representation in a 2-step decentralized loop closure verification: first, we distribute the compact semantic descriptors to determine which other robots might have seen scenes with similar objects; then we query matching robots with the full constellation to validate the match using geometric information. The proposed method requires less memory, is more interpretable than global image descriptors, and could be useful for other tasks and interactions with the environment. We validate our system's performance on a TUM RGB-D SLAM sequence and show its benefits in terms of bandwidth requirements.Comment: 8 pages, 6 figures, 1 table. 2020 IEEE International Conference on Robotics and Automation (ICRA

Catalytic Tile Experiment Flown on EFT-1 to Gather Catalytic Overshoot Data with Increased Spatial Resolution in Laminar and Turbulent Environments

No abstract availabl