Plasmonic core-multi-shell nanomaterials for improving energy efficiency and sensing

In recent times, plasmonics has been a hallmark in improving optoelectronic device performance as well as in improving sensing. Confining light in dimensions below the diffraction limit and subsequently converting the incident photons into localized charge-density oscillations called localized surface plasmons, optical enhancements of the local fields by many orders of magnitude is possible. This dissertation explores the use of such surface plasmon resonances in core multishell nanostructures and demonstrates the values of such structures in energy harvesting and sensing. Additionally, it also shows the use of emerging plasmonic materials like metal nitrides (TiN, ZrN) instead of traditional plasmonic materials (Au, Ag) in the nanostructure designs. Utilizing the localized surface plasmon resonance (LSPR) in metallic components of core multishell nanowires, calculations of the local density of states as a measure of emission were made using a Green’s function method, while the absorption and scattering were simulated using the Mie formalism. Combining both the absorption and the emission, the quantum efficiency of white LEDs was calculated and the optimal material/dimensions for maximal performance was determined for different phosphor components in a white LED. Additionally, the use of ZrN as a plasmonic cloak for noise cancellation in Si photodetectors is shown and the performance is compared with an Au cloak. Using the developed methodology, it is proved that ZrN cloaks can outperform Au cloaks in a certain region of the visible spectrum, showing the benefit of using such plasmonic systems in place of traditional materials. The fabrication of the different components of the core multishell nanowires is also presented, and in particular, fabrication of ultra-thin (sub-10 nm) plasmonic TiN is achieved. Utilizing plasmon hybridization, a tunable double resonance feature is observed in Au/SiO2/Au core shell shell (CSS) nanoparticles, which have been then demonstrated to improve the photocatalytic performance in hematite. In particular, the double resonance peak allows absorption of light beyond the band gap of hematite and subsequent conversion into photocurrent through hot electron injection. Comparison has been made with Au nanoparticles, and it has been shown that the CSS nanoparticles outperform Au nanoparticles significantly. These CSS nanoparticles have also been used for bioimaging, in particular for Raman spectroscopy, with strong results at high densities of the nanoparticles. Utilizing stronger scattering SiO2/Au Nanoshells, it has been possible to work towards single particle imaging of molecules and demonstration of this phenomenon has been shown here through the use of coherent Raman scattering spectroscopy

Transport signatures of Bogoliubov Fermi surfaces in normal metal/time-reversal symmetry broken dd-wave superconductor junctions

In recent times, Bogoliubov Fermi surfaces (BFSs) in superconductors (SCs) have drawn significant attention due to a substantial population of Bogoliubov quasiparticles (BQPs) together with Cooper pairs (CPs) in them. The BQPs as zero energy excitations give rise to captivating and intricate charge dynamics within the BFSs. In this theoretical study, we propose to reveal the unique signatures of the topologically protected BFSs in a normal metal/time-reversal symmetry (TRS) broken $d$-wave SC, in terms of the differential conductance and Fano factor (FF). For an isotropic $d$-wave SC, an enhancement in zero-bias conductance (ZBC) can be identified as a key signature of BFSs. However, for the anisotropic SC, this feature does not replicate due to the presence of the localized Andreev bound state (ABS) at the interface. The interplay of ABS and BFSs gives rise to an anomalous behavior in ZBC. We explain this anomalous behavior by analyzing the effective charge of the carriers in terms of the FF. The simplicity of our setup based on $d$-wave SC makes our proposal persuasive.Comment: 6+6 pages, 4+4 figures, comments welcom

Bı-jagan. ita of bha-skara-ca-rya

The above sentence occurs in the book “Number Theory: An approach through history” (p 81–82) by André Weil (1906–98), one of the giants of 20th century mathematics. The mathematician Pierre de Fermat (1601–65) is regarded as the father of modern number theory. The “problem” referred to by Weil has a grand history. It was posed by Fermat in 1657 as part of his efforts to kindle the interest of contemporary mathematicians in the abstract science of numbers. The problem was t

Beyond Discriminative Regions: Saliency Maps as Alternatives to CAMs for Weakly Supervised Semantic Segmentation

In recent years, several Weakly Supervised Semantic Segmentation (WS3) methods have been proposed that use class activation maps (CAMs) generated by a classifier to produce pseudo-ground truths for training segmentation models. While CAMs are good at highlighting discriminative regions (DR) of an image, they are known to disregard regions of the object that do not contribute to the classifier's prediction, termed non-discriminative regions (NDR). In contrast, attribution methods such as saliency maps provide an alternative approach for assigning a score to every pixel based on its contribution to the classification prediction. This paper provides a comprehensive comparison between saliencies and CAMs for WS3. Our study includes multiple perspectives on understanding their similarities and dissimilarities. Moreover, we provide new evaluation metrics that perform a comprehensive assessment of WS3 performance of alternative methods w.r.t. CAMs. We demonstrate the effectiveness of saliencies in addressing the limitation of CAMs through our empirical studies on benchmark datasets. Furthermore, we propose random cropping as a stochastic aggregation technique that improves the performance of saliency, making it a strong alternative to CAM for WS3.Comment: 24 pages, 13 figures, 4 table