Different classes of plasmonic nanoparticles are tested for their SERS signal brightness at the single-particle level.

In this paper, new concepts for continuous 24/7 real-time monitoring of plants and insects with miniaturized terahertz (THz) systems are described and experimentally tested. Thus, for the first time, small-scale insights into the instantaneous plant health but also in their long-term growth can be obtained. Using such compact THz systems, e.g. water uptake, insect infestation and the behavior of pollinators (i.e. honey bees) and pests can be measured dynamically and non-invasively at virtually any position in the close biotope surrounding them. In addition to general understanding, this can be used to optimize crop yield and reduce resource consumption as well as for identifying characteristics of insect-plant interactions induced by potential environmental stressors. Given such holistic a approach, the proposed concepts may provide a significant advancement in environmental monitoring technology.

Terahertz (THz) technology provides precise monitoring capabilities in dynamic environments, offering unique insights into insect habitats. Our study focuses on environmental monitoring of European honey bees (Apis mellifera) through a combination of measurements and simulations. Initially, the dielectric material properties of honey bee body parts are characterized across the spectral range of 1–500 GHz to collect heterogeneous empirical data. To extend the study, honey bee mockups made from polyamide 12 (PA12) and epoxy resin are employed and validated as effective substitutes for real bees through comparative scattering analyses. The research further explores radar cross-section (RCS), imaging, and spectral properties using advanced THz technologies, including resonant tunneling diodes (RTDs) operating at 250 GHz and THz time-domain spectroscopy (THz-TDS) for frequencies exceeding 250 GHz. High-resolution imaging, utilizing a 450 GHz bandwidth, captures intricate anatomical features of both real and 3D-printed bees, showcasing the potential of THz technology for detailed environmental monitoring. Finally, simulations at 300 GHz assess the dosimetry and feasibility of non-invasive, continuous monitoring approaches based on the heterogeneous honey bee model.

We propose the use of one-dimensional semiperiodic front and back gratings based on Thue–Morse, Fibonacci, and Rudin–Shapiro (RS) binary sequences as promising photon management techniques for enhancing ultra-broadband optical absorption in thin-film solar cells. The semiperiodicity allows an aggregate light in-coupling into the active layer within the range of the solar spectrum that is less weak compared to an inherently broadband random grating, but has a much larger bandwidth than the strong in-coupling via a periodic grating configuration. The proper design procedure proposed here deviates from a canonical double grating synthesis as it adheres to an ultra-broadband design where the spectrally integrated absorption in the active material is the proper subject to optimization, leaving the grating perturbations just a measure to perturb and mold the trapped light field in the active layer accordingly. It is shown that by using a well-defined RS double grating in a 400-nm thick crystalline silicon solar cell, a 110.2% enhancement of the spectrally integrated optical absorption can be achieved relative to the reference case without grating.

The possibility of establishing a novel technique for reliably accessing glycemic information in a non-invasive, easy to implement method at THz frequencies via the fingernail bed is investigated. The nail bed’s major content is blood at its various glucose levels and is also partially protected from environmental conditions by the nail plate, making it a desirable platform for non-invasive glucose sensing. The study is based on a 2D computational electromagnetics (EM) model of the layered fingernail in COMSOL Multiphysics, where the required dielectric function (i.e. permittivity and conductivity) of the fingernail plate is measured using THz-Time-Domain- Spectroscopy (THz-TDS), and the glucose-dependend dielectric functions of the fingernail bed are taken from available experimental data in the literature. From this data a material model using a multipole Cole-Cole model is established for both, the nail plate and the nail bed, where the glucose content in the latter is varied from 3.0-19.0 mmol/l. A numerical analysis of the THz reflectometry at the fingernail in the frequency range of 0.1-2.0 THz revealed that the reflectance spectra are sensitive to the glucose content in the nail bed proving that accurate glucose sensing via the fingernail bed may become feasible around 0.2-0.4 THz.

Embedding plasmonic nanoparticles (p-NPs) inside the solar cell’s active layer is capable of enhancing active layer optical absorption; however, such inclusion has some detrimental effects on the electronic properties of the solar cells. In addition, p-NPs are highly catalytic, their presence enables other non-radiative decay channels besides generation of electron–hole pairs, and the electrons usually get absorbed by these p-NPs. This results in the unfavorable fact that the potential enhancement in the carrier generation rate and the generated current is no longer in line with the enhancement in the optical absorption. In this paper, we propose to functionalize p-NPs by adding a dielectric or semiconductor shell, to passivate the p-NP without deteriorating scattering and/or plasmonic effects. $\mathrm{Ag}@{\mathrm{SiO}}_2$ and $\mathrm{Ag}@{\mathrm{TiO}}_2$ core–shell p-NPs have been intensely studied using extensive computational electromagnetic simulations to model the spectral response of the active layer’s optical absorption as well as electronic properties as a function of both shell composition and thickness. It is shown that a 5 nm ${\mathrm{TiO}}_2$ shell is apt to optically passivate the p-NP without any reduction in optical absorption, while improving the short circuit current density ($J_{\mathrm{sc}}$) of the thin-film solar cell by 33.3%.