DC

The data correspond to the results of modelling studies of DC electric arcs at a current of 2 A in air with admixture of copper metal vapour. Experimental findings are used to adjust input parametrs of the model in order to achieve a good match. The simulations are performed strating with a discharge burning with a minimum gap length of 30 µm for a physical time of 11 ms. Then, the separation of the electrodes is followed for further 51 ms and the discharge gap is increased up to 3 mm. The comparision of experimental and modelling data is based on the measured arc voltage.

The results of modelling study of self-pulsing discharges in pure argon at atmospheric pressure in a 1.5 mm gas gap are provided in this dataset. The study investigates the interaction between the electrical circuit and the actual plasma characteristics. A time-dependent, spatially one-dimensional fluid-Poisson model coupled with an equivalent circuit equation is applied to analyse the impact of circuit parameters like resistance and applied negative DC high voltage on basic discharge properties.

The dataset contains results of a unified one-dimensional model of an arc plasma in air dominated by copper metal vapour. The plasma is generated between copper electrodes. The model resembles the microarcs that occur at low-voltage and low-current conditions in switching devices during a contact separation. Data concerning the plasma parameters, including electric potential, temperatures of electron and heavy particles, number densities of charged and neutral species are provided as tables.

The radiative heat transfer in arc plasma models is considered from the point of view of its description in terms of a net emission coefficient, the method of spherical harmonics in its lowest order, and the discrete ordinate method. Net emission coefficients are computed, applying approximate analytical and numerical approaches and a multi-band representation of the spectral absorption coefficient with three kinds of its averaging and two datasets.

The dataset contains results from application of a mid-infrared frequency comb-based Fourier transform spectrometer to measure high-resolution spectra of plasmas containing hydrogen, nitrogen, and a carbon source in the 2800 – 3400 cm–1 range. The spectrally broadband and high-resolution capabilities of this technique enable quantum-state-resolved spectroscopy of multiple plasma-generated species simultaneously, including CH4, C2H2, C2H6, NH3, and HCN, providing detailed information beyond the limitations of current methods.

The dataset contains results of a unified one-dimensional model of an arc plasma in air, between copper electrodes, that includes the change of the gap distance. The occurance of multiple reversals of the electric field and the anode voltage drop is observed. The evolution of the spatial distribution of the electron and heavy particle temperatures with the gap distance and the opening speed is also studied. The model quantitatively predicts a number of plasma properties under conditions that are relevant to the contact separation in low-voltage switching devices.

Plasma-activated chemical transformations promise the efficient synthesis of salient chemical products. However, the reaction pathways that lead to desirable products are often unknown, and key quantum-state-resolved information regarding the involved molecular species is lacking. Here we use quantum cascade laser dual-comb spectroscopy (QCL-DCS) to probe plasma-activated NH3 generation with rotational and vibrational state resolution, quantifying state-specific number densities via broadband spectral analysis.

Laser absorption spectroscopy (LAS) was applied to investigate a low pressure DC-pulsed discharge in N2-H2 gas mixtures with addition of CH4 or O2. The discharge was maintained in an industrial-scale, active screen plasma nitrocarburizing (ASPNC) reactor with a steel active screen (AS). Spectroscopic lines of CH4, NH3, HCN, CO and H2O were recorded. The dataset contains the species densities for different gas mixtures.

The dataset contains the data presented in the paper introducing the FEDM (Finite Element Discharge Modelling) code. The FEDM code was developed using the open-source computing platform FEniCS (https://fenicsproject.org). Building on FEniCS, the FEDM code utilises the finite element method to solve partial differential equations. It extends FEniCS with features that allow the automated implementation and numerical solution of fully-coupled fluid-Poisson models, including an arbitrary number of particle balance equations.