arXiv subjects

Laurent Invernizzi

Publications and source records attributed to Laurent Invernizzi.

3 recordsLinked to original sources

arXiv2026

Proof of operation of a micro-hollow cathode discharge driven by a true ns-pulsed high voltage: emission properties and atomic nitrogen production

The implementation of Micro-Hollow Cathode Discharges (MHCDs) for the efficient and controlled dissociation of molecular nitrogen into reactive N-atoms remains a central challenge in the synthesis of strategic materials such as hexagonal boron nitride (h-BN). Traditional MHCDs driven with DC high voltages (HV) can generate N-atoms under low-to-moderate gas pressures. However, they are prone to intrinsic instabilities that eventually induce arcing, increase thermal load and limit significantly their lifetimes. In this work we aim to enhance N2 dissociation efficiency in an Ar/N2 MHCD driven by a true nanosecond (ns) pulsed positive HV which has not been yet considered in MHCDs. A testbed reactor is employed to investigate microplasma behavior under ns-pulsed operation, which is then compared to a conventional DC MHCD. Specifically, we combined optical emission and ns-TALIF diagnostics under suitable operating conditions of each HV regime comprising different gas mixtures, pressures, and electrical parameters. These measurements allowed for the identification of key excited species and mapping of ground-state N-atoms absolute density in the low-pressure chamber of the MHCD reactor. It is demonstrated that ns-pulsed excitation produces a more symmetric discharge expansion on the cathodic surface compared to a standard DC excitation, while generating similar nature of emissive species and consuming up to 2 orders of magnitude lower average power depending on the operating frequency and voltage. Importantly, up to 6-fold enhancement in absolute N-atoms density (maximum value measured: 1.14x10 15 cm -3 ) is achieved with the ns-pulsed MHCD making it very promising for h-BN synthesis.

physics.plasm-ph↗

arXiv2025

Ultrafast ps--TALIF and streak camera diagnostics of atomic hydrogen in a helium microplasma jet

Picosecond two-photon absorption laser induced fluorescence (ps--TALIF) is combined with a streak camera ($\sim$1 ps highest temporal resolution) to probe the effective lifetime ($τ_{eff_{H(n=3)}}$) and absolute density ($N_H$) of atomic hydrogen in the effluent of a helium atmospheric-pressure microplasma jet ($μ$APPJ). This approach allows for improved temporal resolution compared to conventional nanosecond diagnostics, enabling measurements of $τ_{eff_{H(n=3)}}$ as small as 50 ps, the corresponding $N_H$ reaching down to $10^{14} cm^{-3}$. Atomic densities are calibrated by performing identical ps--TALIF measurements in krypton gas contained in a custom-built low-pressure cuvette. Physical mechanisms that may be involved in the TALIF scheme such as photoionisation and/or stimulated emission are also assessed, ensuring reliable studies. The determined $τ_{eff_{H(n=3)}}$ and $N_H$ increase with the helium flow rate ($Q_{He}$) in the range $Q_{He}=0.3-1$ slm. Both quantities are maximized near the exit nozzle of the $μ$APPJ, obtaining values below 400 ps and $6x10^{14} cm^{-3}$, respectively. As the axial distance increases, $τ_{eff_{H(n=3)}}$ declines with a rate of $\approx$65 ps/mm for $Q_{He}=1$ slm which is about 3 times smaller than for $Q_{He}=0.3$ slm. These findings reveal a strong correlation between the experimentally-measured $τ_{eff_{H(n=3)}}$ and the local air entrainment into the jet as indicated by their comparison with calculated effective lifetimes based on published quenching rates. Furthermore, operating the $μ$APPJ in the burst mode allows for the estimation of the residence time ($t_{res}$) of ground state H--atoms in the helium gas channel, which is larger for $Q_{He}=0.3$ slm ($t_{res} \approx 1.2 ms$) compared to $Q_{He}=1$ slm ($t_{res} \approx 0.5 ms$). H-atoms consumption in the gas channel can be affected by diffusion and mechanisms involving neutral ground-state and metastable species among others. Furthermore, based on an error propagation analysis, density uncertainty as high as 64% (depending on the operating condition) is revealed. This mainly originates in the ratio of the two-photon absorption cross sections of Kr and H atoms ( $σ^{(2)}Kr$ / $σ^{(2)}H$) which has not yet been measured in the picosecond regime. Nevertheless, the combined utilisation of ps--TALIF and streak camera diagnostics demonstrates high sensitivity and temporal resolution for directly probing key reactive species in atmospheric pressure microplasmas.

physics.plasm-ph↗

arXiv2024

Machine learning assisted optical diagnostics on a cylindrical atmospheric pressure surface dielectric barrier discharge

The present study explores combining machine learning (ML) algorithms with standard optical diagnostics (such as time-integrated emission spectroscopy and imaging) to accurately predict operating conditions and assess the emission uniformity of a cylindrical surface Dielectric Barrier Discharge (SDBD). It is demonstrated that ML can be complementary with these optical diagnostics and identify peculiarities associated with the discharge emission pattern at different high voltage waveforms (AC and pulsed) and amplitudes. By employing unsupervised (Principal Component Analysis (PCA)) and supervised (Multilayer Perceptron (MLP) neural networks) algorithms, the applied voltage waveform and amplitude are categorised and predicted based on correlations/differences identified within large amounts of corresponding data. PCA allowed us to effectively classify the voltage waveforms and amplitudes applied to the SDBD through a transformation of the spectroscopic/imaging data into principal components (PCs) and their projection to a two-dimensional PC space. Furthermore, an accurate prediction of the voltage amplitude is achieved using the MLP which is trained with PCA-preprocessed data. A particularly interesting aspect of this concept involves examining the uniformity of the emission pattern of the discharge. This is achieved by analysing spectroscopic data recorded at four different regions around the SDBD surface using the two ML-based techniques. These discoveries are instrumental in enhancing plasma-induced processes. They open up new avenues for real-time control, monitoring, and optimization of plasma-based applications across diverse fields such as flow control for the present SDBD.

physics.plasm-ph↗