We propose chiral metamaterial absorber based on four rotated twisted closed ring resonators operative in terahertz frequency range. The resonant features are analyzed by electric field amplitude distributions and surface currents flow generated by the interaction of circularly polarized waves with the chiral structure. The highest field amplitudes at the fundamental resonance are obtained at the gap region of the resonator. Therefore, the efficiency of the proposed absorber is determined through response of absorption spectrum around this resonance with variation of geometrical parameters of the structure. Significant increase of absorption of the left circularly polarized light is obtained with variation of the period size of structure. Consequently, huge circular dichroism and near-unity polarization selective absorption have been provided. This makes the proposed chiral structure a good candidate for designing circular polarization selective absorber.

Scalable and effective calibration is a fundamental requirement for low-cost air quality (AQ) monitoring systems and will enable accurate and pervasive monitoring in cities. Suffering from environmental interferences and fabrication variance, these devices need to encompass sensor-specific and complex calibration processes for reaching a sufficient accuracy to be deployed as indicative measurement devices in AQ monitoring networks. Concept and sensor drift often force the calibration process to be frequently repeated. These issues lead to unbearable calibration costs, which denies their massive deployment when accuracy is a concern. In this work, we propose a zero transfer samples, global calibration methodology as a technological enabler for Internet of Things (IoT) AQ multisensory devices, which relies on low-cost particulate matter (PM) sensors. This methodology is based on field recorded responses from a limited number of IoT AQ multisensors units and machine learning (ML) concepts and can be universally applied to all units of the same type. A multiseason test campaign has shown that, when applied to different sensors, this methodology’s performances match those of state-of-the-art methodology, which requires to derive different calibration parameters for each different unit. If confirmed, these results show that, when properly derived, a global calibration law can be exploited for a large number of networked devices with dramatic cost reduction eventually allowing massive deployment of accurate IoT AQ monitoring devices. Furthermore, this calibration model could be easily embedded onboard of the device or implemented on the edge allowing immediate access to accurate readings for personal exposure monitor applications as well as reducing long-range data transfer needs.

Applying high-power continuous-wave resonant $s$-shell excitation to a single self-assembled InGaAs quantum dot, we demonstrate the generation of postselected single-indistinguishable photons from the Mollow triplet sidebands. A sophisticated spatial filtering technique based on a double Michelson interferometer enabled us to separate the spectrally close lying individual Mollow components and perform almost background-free two-photon interference measurements. Showing high consistency with the results of an independent determination of the emission coherence of $\sim$ $250\pm 30$ ps, our analysis reveals a close to ideal visibility contrast of up to $97\%$. Due to their easy spectral tunability and their distinct advantage of cascaded-photon emission between the individual Mollow sidebands, they resemble a versatile tool for quantum information applications.

Conventional air quality monitoring networks typically tend to be sparse over areas of interest. Because of the high cost of establishing such monitoring systems, some areas are often completely left out of regulatory monitoring networks. Recently, a new paradigm in monitoring has emerged that utilizes low-cost air pollution sensors, thus making it possible to reduce the knowledge gap in air pollution levels for areas not covered by regulatory monitoring networks and increase the spatial resolution of monitoring in others. The benefits of such networks for the community are almost self-evident since information about the level of air pollution can be transmitted in real time and the data can be analysed immediately over the wider area. However, the accuracy and reliability of newly produced data must also be taken into account in order to be able to correctly interpret the results. In this study, we analyse particulate matter pollution data from a large network of low-cost particulate matter monitors that was deployed and placed in outdoor spaces in schools in central and western Serbia under the Schools for Better Air Quality UNICEF pilot initiative in the period from April 2022 to June 2023. The network consisted of 129 devices in 15 municipalities, with 11 of the municipalities having such extensive real-time measurements of particulate matter concentration for the first time. The analysis showed that the maximum concentrations of PM_2.5 and PM₁₀ were in the winter months (heating season), while during the summer months (non-heating season), the concentrations were several times lower. Also, in some municipalities, the maximum values and number of daily exceedances of PM₁₀ (50 μg/m³) were much higher than in the others because of diversity and differences in the low-cost sensor sampling sites. The particulate matter mass daily concentrations obtained by low-cost sensors were analysed and also classified according to the European AQI (air quality index) applied to low-cost sensor data. This study confirmed that the large network of low-cost air pollution sensors can be useful in providing real-time information and warnings about higher pollution days and episodes, particularly in situations where there is a lack of local or national regulatory monitoring stations in the area.

Beam steering is one of the prevailing functions performed by electromagnetic metasurfaces. Its efficiency depends on a large number of physical parameters associated with resonant elements comprising the metasurface and is thus notoriously difficult to optimize. Here we formulate a theoretical model for evaluating the diffraction efficiency of an array of lossy resonant elements whose spectral response is dominated by the coupling between a leaky eigenmode and a single incoming/outgoing channel. We use it to deduce a formula for the maximum attainable diffraction efficiency and the gradient parameter profile for which it is achieved. The optimization procedure is demonstrated on the example of an electrically tunable liquid-crystal terahertz beam steering metasurface. Finally, the proposed model is benchmarked against rigorous metasurface simulations.