Compared with the most commonly used silicon and germanium, which need to work at cryogenic or low temperatures to decrease their noise levels, wide-bandgap compound semiconductors such as silicon carbide allow the operation of radiation detectors at room temperature, with high performance, and without the use of any bulky and expensive cooling equipment. In this work, we investigated the electrical and spectroscopic performance of an innovative position-sensitive semiconductor radiation detector in epitaxial 4H-SiC. The full depletion of the epitaxial layer (124 µm, 5.2 × 10¹³ cm⁻³) was reached by biasing the detector up to 600 V. For comparison, two different microstrip detectors were fully characterized from −20 °C to +107 °C. The obtained results show that our prototype detector is suitable for high resolution X-ray spectroscopy with imaging capability in a wide range of operating temperatures.

A single-crystal silicon carbide (SiC) detector was used for measurements of soft x rays, electrons, and ion emission from laser-generated plasma obtained with the use of the Prague Asterix Laser System (PALS) at intensities of the order of ${10}^{16}\text{W}/{\text{cm}}^2$ and pulse duration of 300 ps. Measurements were performed by varying the laser intensity and the nature of the irradiated target. The spectra obtained by using the SiC detector show not only the photopeak due to UV and soft x-ray detection, but also various peaks due to the detection of energetic charged particles. Time-of-flight technique was employed to determine the ion kinetic energy of particles emitted from the plasma and to perform a comparison between SiC and traditional ion collectors. The detector was also employed by inserting absorber films of different thickness in front of the SiC surface in order to determine, as a first approximation, the mean energy of the soft x-ray emission from the plasma.

Reducing emissions of the key greenhouse gas methane (CH₄) is increasingly highlighted as being important to mitigate climate change. Effective emission reductions require cost-effective ways to measure CH₄ to detect sources and verify that mitigation efforts work. We present here a novel approach to measure methane at atmospheric concentrations by means of a low-cost electronic nose strategy where the readings of a few sensors are combined, leading to errors down to 33 ppb and coefficients of determination, R², up to 0.91 for in situ measurements. Data from methane, temperature, humidity, and atmospheric pressure sensors were used in customized machine learning models to account for environmental cross-effects and quantify methane in the ppm-ppb range both in indoor and outdoor conditions. The electronic nose strategy was confirmed to be versatile with improved accuracy when more reference data were supplied to the quantification model. Our results pave the way toward the use of networks of low-cost sensor systems for the monitoring of greenhouse gases.