Study on the Emission Spectroscopy of Plasma and Characterization of Nanofilms During Pulsed Laser Deposition of ZnO

We applied convergent–divergent (C–D) magnetic fields to nonequilibrium argon and hydrogen plasma flows, and investigated the variation of the plasma properties by emission spectroscopy measurements. From the observation of the emission patterns, the C–D magnetic field is found to compress and squeeze the plasma flow, causing the emission region to elongate downstream. It is clearly shown from the captured images that the extent of the compression and squeeze gets larger by applying a stronger magnetic field. Emission spectroscopy of argon plasmas shows that the electronic excitation mode is almost frozen. Emission spectroscopy of hydrogen plasmas shows that the rotational temperature decreases downstream, whereas the vibrational mode is almost frozen. Furthermore, it is demonstrated that the heat loss from the wall can be reduced with the applied C–D magnetic field, because compression and squeeze by the applied magnetic field keeps the plasma away from the wall.

Previous research regarding laser-induced breakdown spectroscopy (LIBS) of titanium normally focuses on the atomic and ionic Ti spectral transition lines. However, after a characteristic time subsequent to laser ablation, these lines are no longer discernable. During this temporal regime, the diatomic molecular transition lines of titanium monoxide (TiO) are prominent in the laser-induced plasma (LIP) emissions. TiO has long been studied in the contexts of stellar emissions, allowing for some of the molecular transition bands to be accurately computed from theory. In this research, optical emission spectroscopy (OES) of laser-induced plasma (LIP) generated by laser ablation of titanium is performed in order to infer temperature as a function of time subsequent to plasma formation. The emission spectra of the resulting ablation plume is imaged as a function of height above the sample surface. Temperatures are inferred over time delays following plasma formation ranging from 20 μs-200 μs. Computed TiO A3Φ – X3Δ, Δv = 0 transition lines are fit to spectral measurements in order to infer temperature. At tdelay = 20 μs-80 μs, the observed plume contains two luminescent regions each with a distinctly different temperature. As the plume evolves in time, the two regions combine and an overall temperature increase is observed.

Fourteen laboratories participated in a collaborative study of 6 homogeneous plant tissue samples to determine the elements P, K, Ca, Mg, Mn, Fe, Al, B, Cu, Zn, and Na by plasma emission spectroscopy. Samples were dry ashed using AOAC method 3.007(a) (13th Ed.). An NBS citrus leaf standard was prepared and a portion of the resulting solution was sent to each collaborator to evaluate sample preparation errors independent of instrument error. Coefficients of variation were better than those obtained in an earlier collaborative study on multielement analysis by spark emission spectroscopy. The plasma emission method has been adopted official first action for determination of P, K, Ca, Mg, Mn, B, Cu, and Zn in plant tissues.

We developed a method for two-dimensional space-resolved emission spectroscopy of laser-induced plasma in water to investigate the spatial distribution of atomic species involved in the plasma. Using this method, the laser ablation plasma produced on a Cu target in 5 mM NaCl aqueous solution was examined. The emission spectrum varied considerably depending on the detecting position. The temperature and the atomic density ratio NNa/NCu at various detecting positions were evaluated by fitting emission spectra to a theoretical model based on the Boltzmann distribution. We are successful in observing even a small difference between the distributions of the plasma parameters along the directions vertical and horizontal to the surface. The present approach gives direct information for sound understanding of the behavior of laser ablation plasma produced on a solid surface in water.

This study presents an explainable artificial intelligence (XAI) vision for optical emission spectroscopy (OES) of plasma in aqueous solution. We aim to characterize the plasma and OES with XAI. Trained with 18000 spectra, a multilayer artificial neural network (ANN) model accurately predicted the solution conductivity. Local interpretable model‐agnostics explanations (LIME), an XAI method, interpreted the model through perturbing spectral features and fitting the feature contribution with a linear model. LIME showed that OH, Hγ, and Hβ emission lines were critical to the model, differing from the lines typically selected by humans. The results demonstrated that machine captured the spectral features neglected by humans. We believe using XAI for plasma OES analysis impacts the fields of plasma and analytical chemistry.

This study presents the development of an efficient data acquisition platform and discusses machine learning of optical emission spectroscopy (OES) of plasma in aqueous solution to demonstrate the multivariate analysis of spectra. A specially designed platform for efficient acquisition of spectra emanated from plasmas in solutions is developed, and several machine learning algorithms are tested for plasma analysis. This platform enables acquiring up to 10k spectra solutions with various pH values under constant solution conductivity, or vice versa, within 15 min. This rapid acquisition scheme provides a sufficient dataset for testing machine learning algorithms. We test the OES of plasmas ignited in solutions with designated conductivities with pH of 2.2–5.2. A total 40k spectra are collected and tested with principal component analysis (PCA) and an artificial neural network (ANN) to predict the conductivity of the solution. In PCA, the results show that most data points are overlapped in the score plot constructed using principal components 1 and 2, implying that PCA cannot discriminate the conductivity based on the spectra. In an ANN, several network structures are constructed and tested. The results show that the deep ANN significantly improves the accuracy of conductivity prediction in terms of mean squared error by three orders of magnitude compared with the method of using single emission line. Regularization techniques including dropout and early stopping show promise for mitigating overfitting in a deep ANN. Such improvements suggest that a deep ANN considers the nonlinear behaviors of plasma and can handle datasets with high complexity. In addition, the application of a deep ANN with a large number of parameters makes using this experimental platform for efficient spectra acquisition highly desirable.

A novel diagnostic device is developed to obtain spatially resolved emission profiles in plasmas. A ceramic tube is immersed into the plasma and moved along its longitudinal axis. A lens located at the other end of the ceramic tube images light onto an optical fiber which guides the light to a detector. In the case that the plasma emission is detected within a negligible solid angle, simple differentiation of the measured signal yields spatially resolved emission profiles. For non-negligible solid angles, spatial resolution can still be obtained by a more sophisticated evaluation. The design of the probe and the underlying theory are presented. The arrangement of the optics is analyzed in detail. Measurements in an inductively coupled radio-frequency (RF) hydrogen discharge in a GEC cell at different RF powers, neutral gas pressures and axial probe positions are performed. The obtained radial emission profiles of the Balmer-α line exhibit a torus-like structure which reflects the structure of the induced electrical field of the antenna. Furthermore, the transition from H to E mode at lower powers is observed.Based on a corona equilibrium model excitation rates are calculated out of electron energy distribution functions measured by an RF compensated Langmuir probe. A comparison of measured emission profiles with calculated excitation rate profiles shows very good agreement. Integrated emission profiles obtained by camera images are Abel inverted and compared with profiles obtained by the optical probe. The comparison demonstrates the advantage of the optical probe.

In this paper, the indirect monitoring of plasma-induced defect formation within fused silica via plasma emission spectroscopy is presented. It is shown that low-pressure plasma treatment with hydrogen as process gas leads to a decrease in UV transmission of fused silica. This decrease can be directly attributed to oxygen vacancy-related defects and the presence of hydrogen within the silicon dioxide glass network. By the analysis of the plasma composition, it was observed that the amount of oxygen within the plasma increases with increasing treatment duration. Hence, oxygen was continuously released from glass network in the course of the plasma treatment. It was further observed that this release is strongly dependent on the applied plasma power where the lowest process efficiency occurs at the highest plasma power. It is shown that an increase in plasma power leads to a remarkable increase in light emission from the working gas, hydrogen. This observation indicates that the higher the degree of excitation and ionisation of the plasma, the lower the efficiency of plasma-induced formation of oxygen deficiency-related defects. This finding is of mentionable relevance for a better understanding of plasma-induced surface modification and coating processes.

Optimization of a pharmaceutical freeze-dried product and its process using an experimental design approach and innovative process analyzers

Poor quality and low repeatability of additively manufactured parts are key technological obstacles for the widespread adoption of additive manufacturing (AM). In-situ monitoring and control of the AM process is vital to overcome this problem. This paper describes the combined artificial intelligence and plasma emission spectroscopy to identify the porosity of AM parts during the process. The time- and position-synchronized spectra were collected during the directed energy deposition (DED) manufacturing process of a 7075-Al alloy part. Eighteen features extracted from spectra were coupled with the deposition qualities which were characterized by the 3D X-ray Computed Tomography (CT) scan and used to train a Random Forest (RF) classifier. The well-trained RF classifier achieved up to 83% precision for the porosity recognition of depositions. The feature importance recorded by the RF classifier indicates that the intensities of spectra at the wavelength of 414.234 (Fe I) nm and 396.054 (Al I) nm, and the kurtosis of spectra at wavelength ranges of 484–490 nm and 508–518 nm, are the most effective features for porosity recognition. The physical correlations between spectra, porosity formation, and thermal accumulation during the AM process were analyzed. This study demonstrates the great potentials, as well as challenges of plasma emission spectroscopy for in-situ quality monitoring of laser AM which allows the enhancement of AM technique.

A RF-driven, Cs-enhanced H(-) ion source feeds the SNS accelerator with a high current (typically >50 mA), ∼1.0 ms pulsed beam at 60 Hz. To achieve the persistent high current beam for several weeks long service cycles, each newly installed ion source undergoes a rigorous conditioning and cesiation processes. Plasma conditioning outgases the system and sputter-cleans the ion conversion surfaces. A cesiation process immediately following the plasma conditioning releases Cs to provide coverage on the ion conversion surfaces. The effectiveness of the ion source conditioning and cesiation is monitored with plasma emission spectroscopy using a high-sensitivity optical spectrometer. Plasma emission spectroscopy is also used to provide a means for diagnosing and confirming a failure of the insulating coating of the ion source RF antenna which is immersed in the plasma. Emissions of composition elements of the antenna coating material, Na emission being the most significant, drastically elevate to signal a failure when it happens. Plasma spectra of the developmental ion source with an AlN (aluminum nitrite) chamber and an external RF antenna are also briefly discussed.

Sulphur was extracted from 48 Finnish soil samples with 0.01 M CaCl2-solution and with 0.5 M CH3COONH4-0.5 M CH3COOH (pH 4.65), abbreviated here as AAAc. Sulphur was determined with plasma emission spectroscopy and with an indirect AAS method. The determination from CaCl2 extracts was also made turbidimetrically and from AAAc extracts gravimetrically. The results were compared with the yield and uptake of sulphur by Italian ryegrass in a pot experiment. AAAc extracted 1/4-1/2 more sulphur than did CaCl2 solution. From both extracts plasma emission spectroscopy yielded considerably higher results than other methods. The amounts of sulphur determined with various methods correlated well with the grass yields (r=0.77∗∗∗-0.87∗∗∗) and plant uptake of sulphur (r=0.81∗∗∗-0.91∗∗∗). The exception, however, were the gravimetric measurements, which were not in agreement with the results of the pot experiment. The determination made with plasma emission spectroscopy produced as practicable results as the more laborious methods. It seems possible to use the AAAc extracts of the usual fertility test in the determination of plant available sulphur of the soil. Field experiments are needed for the determination of the level of sulphur sufficient for normal yield formation.

The emulsion copolymerization of styrene and sodium acrylate is reported using either a water-soluble initiator (potassium persulfate, or KPS), or an oil-soluble one (2,2-azoisobutyronitrile (AIBN)).Reaction rates are fast with both KPS and AIBN. With KPS, conversions u90% are achieved in 50 min, with AIBN, conversions reach 85% in 100 min. Particle size, measured by quasielectric light scattering (QLS), in- creases with conversion. Particle size in final latices isC 70-80 nm. Copolymer forma- tion is confirmed by infrared (IR) spectroscopy, plasma emission spectroscopy (PES), and scanning electron microscopy (SEM). IR and PES indicate that mainly sodium acrylate reacts at the beginning of the reaction and then styrene is incorporated in the copolymer backbone. The copolymer produced with KPS contains more sodium acrylate than the one made with AIBN. These differences can be explained in terms of the reactivities and partitioning (local concentrations) of the monomers and of the type of initiator used. Thermomechanical analysis (TMA) of the copolymers reveals two transitions: one at C 1007C, which is due to the glass transition temperature (Tg )o f polystyrene blocky segments in the copolymer, and another one at higher temperatures, which is associated to the Tg of segments composed of alternated sodium acrylate and styrene units. The higher-temperature transition shifts to lower values as the reaction proceeds because these segments become richer in styrene. q 1997 John Wiley & Sons, Inc. J Appl Polym Sci 66: 879-889, 1997

Nitride-molecule synthesis in plasma produced by reactive laser ablation assisted by RF discharge for thin-film deposition

Deposition of BaTiO3 thin films by a hybrid DC-field enhanced PLD-process