Zoran Jakšić

We present an approach to utilize gold nanoparticles embedded within various semiconductor thin films as a possible solution in bringing plasmonic enhancement to photocatalysis in microreactors. In this manner we aim to ensure a solution that is compatible with continuous laminar flow in the device as well as with planar technologies used in microreactor fabrication for seamless integration with the device. We utilize TiO 2 , SiO 2 and Si materials to optimize optical energy density distributions within the structure and consequently enhance desired carrier generation mechanisms within the metal and the semiconductor. Utilizing thin films instead of core-shell particles offers additional degrees of freedom in terms of material choice as well as multilayer capabilities for any further optimization and increases functionalization of our approach. Furthermore, our solution is compatible with omnidirectional illumination of the microreactor.

The interplay between two paradigms, artificial intelligence (AI) and optical metasurfaces, nowadays appears obvious and unavoidable. AI is permeating literally all facets of human activity, from science and arts to everyday life. On the other hand, optical metasurfaces offer diverse and sophisticated multifunctionalities, many of which appeared impossible only a short time ago. The use of AI for optimization is a general approach that has become ubiquitous. However, here we are witnessing a two-way process—AI is improving metasurfaces but some metasurfaces are also improving AI. AI helps design, analyze and utilize metasurfaces, while metasurfaces ensure the creation of all-optical AI chips. This ensures positive feedback where each of the two enhances the other one: this may well be a revolution in the making. A vast number of publications already cover either the first or the second direction; only a modest number includes both. This is an attempt to make a reader-friendly critical overview of this emerging synergy. It first succinctly reviews the research trends, stressing the most recent findings. Then, it considers possible future developments and challenges. The author hopes that this broad interdisciplinary overview will be useful both to dedicated experts and a general scholarly audience.

The application of artificial intelligence in everyday life is becoming all-pervasive and unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired algorithms for multiparameter optimization, which find their use in a large number of areas. Novel methods and advances are being published at an accelerated pace. Because of that, in spite of the fact that there are a lot of surveys and reviews in the field, they quickly become dated. Thus, it is of importance to keep pace with the current developments. In this review, we first consider a possible classification of bio-inspired multiparameter optimization methods because papers dedicated to that area are relatively scarce and often contradictory. We proceed by describing in some detail some more prominent approaches, as well as those most recently published. Finally, we consider the use of biomimetic algorithms in two related wide fields, namely microelectronics (including circuit design optimization) and nanophotonics (including inverse design of structures such as photonic crystals, nanoplasmonic configurations and metamaterials). We attempted to keep this broad survey self-contained so it can be of use not only to scholars in the related fields, but also to all those interested in the latest developments in this attractive area.

This study discusses the use of a triple material gate (TMG) junctionless tunnel field-effect transistor (JLTFET) as a biosensor to identify different protein molecules. Among the plethora of existing types of biosensors, FET/TFET-based devices are fully compatible with conventional integrated circuits. JLTFETs are preferred over TFETs and JLFETs because of their ease of fabrication and superior biosensing performance. Biomolecules are trapped by cavities etched across the gates. An analytical mathematical model of a TMG asymmetrical hetero-dielectric JLTFET biosensor is derived here for the first time. The TCAD simulator is used to examine the performance of a dielectrically modulated label-free biosensor. The voltage and current sensitivity of the device and the effects of the cavity size, bioanalyte electric charge, fill factor, and location on the performance of the biosensor are also investigated. The relative current sensitivity of the biosensor is found to be about 10¹³. Besides showing an enhanced sensitivity compared with other FET- and TFET-based biosensors, the device proves itself convenient for low-power applications, thus opening up numerous directions for future research and applications.

New materials are of essential importance for the advancement of nanophotonics and nanoplasmonics. Numerous electromagnetic modes, especially various evanescent surface waves, prove themselves useful in multitudinous practical applications. Here we investigate the use of MXenes as alternative plasmonic materials in freestanding (substrateless) planar nanocomposites that support the existence of Tamm plasmon polaritons (TPP). We use finite element simulations to consider the influence of using MXenes on the propagation and distribution of TPP and the difference in their electromagnetic behavior compared to that of commonly used noble metals. While MXenes allow for somewhat weaker coupling between incident light and TPP, even the thinnest MXene layers practically completely screen the structure behind them. Our diffraction grating-enhanced stacks achieved incident light direction-dependent improvement of the coupling strength and polarization-dependent hybridization of electromagnetic states. MXene ensures improvements in functionality, especially spectral, directional, and polarization selectivity, by imparting rich modal behavior. Importantly, we observed high optical asymmetry of reflectance when illuminating the structures from opposite directions and obtained large high-to-low reflection ratios with a very small number of dielectric layers in the capping 1D photonic crystal. We conclude that MXenes represent a viable alternative for TPP-supporting structures, offering many advantages.

Nanomembranes are the most widespread building block of life, as they encompass cell and organelle walls. Their synthetic counterparts can be described as freestanding or free-floating structures thinner than 100 nm, down to monatomic/monomolecular thickness and with giant lateral aspect ratios. The structural confinement to quasi-2D sheets causes a multitude of unexpected and often counterintuitive properties. This has resulted in synthetic nanomembranes transiting from a mere scientific curiosity to a position where novel applications are emerging at an ever-accelerating pace. Among wide fields where their use has proven itself most fruitful are nano-optics and nanophotonics. However, the authors are unaware of a review covering the nanomembrane use in these important fields. Here, we present an attempt to survey the state of the art of nanomembranes in nanophotonics, including photonic crystals, plasmonics, metasurfaces, and nanoantennas, with an accent on some advancements that appeared within the last few years. Unlimited by the Nature toolbox, we can utilize a practically infinite number of available materials and methods and reach numerous properties not met in biological membranes. Thus, nanomembranes in nano-optics can be described as real metastructures, exceeding the known materials and opening pathways to a wide variety of novel functionalities.