The fabrication of top-gate (TG) field-effect transistor structure in amorphous oxide semiconductor systems remains challenging due to interfacial degradation associated with oxygen-deficient states at the gate insulator (GI)/channel interface induced during GI deposition. In this work, we demonstrate back-end-of-line-compatible, ultra-thin (2 nm) indium-tin-oxide (ITO) top-gate thin-film transistors (TFTs) enabled by an interface-engineered process that integrates channel surface treatment with stacked GI architecture. A bilayer Al2O3 GI grown with stacked atomic layer deposition (ALD) structure, consisting of thermal-mode ALD (T-ALD) and plasma-enhanced ALD (PE-ALD), is adopted to enhance gate controllability and suppress interfacial degradation. Additionally, an O2-plasma surface treatment on the channel is applied to further improve the channel–GI interface quality. The resulting devices exhibit an on/off current ratio of 108 (VDS = 1 V), a positive threshold voltage of 0.7 V, a subthreshold swing of 89 mV/decade, and a near-hysteresis-free threshold-voltage shift of only 17 mV. These results confirm that the proposed interface-engineering strategy effectively mitigates TG-process-induced degradation and enables high-performance ITO TG TFTs suitable for oxide-semiconductor-based monolithic 3D integrated circuits.
In this paper, we investigated the extraordinarily complex nonlinear evolution equations [Formula: see text]- and [Formula: see text]-dimensional generalized Camassa–Holm–Kadomtsev–Petviashvili (g-CHKP) equations found in shallow water waves. We use the Jacobi Elliptic Function Expansion (JEFE) method to derive a variety of closed-form analytical soliton solutions, and traveling wave solutions for the nonlinear [Formula: see text]- and [Formula: see text]-dimensional generalized g-CHKP equations. Several new forms of soliton-like solutions to the governing equations, as well as the dynamics of various types of solutions, are shown graphically for selecting the relevant parameters via numerical simulation. The originality of this work arises from the fact that the results mentioned are entirely new and have not before been studied for the given equation. Furthermore, the applied mathematical approach is more efficient and trustworthy for developing newly constructed soliton solutions in various fields of complex nonlinear phenomena. We anticipate that the findings of this work will have important applications in plasma physics, ocean engineering, optical fibers, quantum mechanics, fluid dynamics, nonlinear dynamics, and soliton theory.
In Multiscale Materials Modeling, an enduring vision is to extract the molecular mechanisms governing a certain materials phenomenon of interest in order to predict how the phenomenon will behave at a later time. This goal of predictive simulation has been discussed about a decade ago as a materials research challenge, in the Mesoscale Science Frontier, MSS. To date, it continues to motivate a growing community of computational materials science and technology. Here, we consider several materials phenomena of interest, each well known in their specific areas of application, to note that while molecular dynamics simulation is arguably the most widely used method, MD results have limitations in predicting or explaining the behavior of the phenomenon. For the type of phenomena selected here, we believe that one can raise the issue of whether MD is an appropriate method of molecular simulation in the design and performance testing of complex materials. There exists an alternative to MD, the approach of meta-dynamics simulation based on energy landscape sampling and transition state theory. This approach is notable because it allows predictive molecular simulations over timescales considerably longer than the traditional MD. We are in the process of implementing an enhanced meta-dynamics approach aimed at identifying unknown defect mechanisms, making it particularly well-suited for investigating the deformation processes in engineering alloys at timescales relevant to laboratory measurements of component performance and durability assurance. Our motivation is that such simulation capabilities will find many materials-centric applications. One such application is known as plasma-materials interactions, PMI. In PMI, the phenomenon of nuclear irradiation damage has been a practical challenge, relevant to both nuclear fission and fusion power generation systems. For the present perspective, we will focus on the use of meta-dynamics simulations in collaboration with the research activities at an academic fusion research center.
Hexagonal boron nitride (h-BN) is a promising material for designing future electronic devices because of its superior dielectric properties. In this study, we fabricated bulk h-BN (sp2-bonded BN nano-network structure) on Si substrates using magnetically confined arc discharge plasma under various conditions. The effects of process gas conditions (Ar/N2 and N2) and impurity [tungsten (W)] incorporation were discussed. Regardless of the gas conditions, the presence of W atoms was found to significantly modulate the optical energy gap, which is supported by first-principles calculations. We investigated time-dependent dielectric breakdown (TDDB) mechanisms under constant voltage stress (CVS) and constant current stress (CCS). The time evolutions of the leakage current and the applied gate voltage during the TDDB measurements were analyzed to clarify the carrier-trapping and defect-generation mechanisms toward the final catastrophic dielectric breakdown. The field acceleration factors in the CVS-TDDB lifetime prediction fell within the general trend of SiO2-based films and were found to be a weak function of the gas condition and W concentration (CW), whereas the carrier-trapping and defect-generation dynamics during electrical stress depend on the gas conditions and CW. Based on the obtained results, we propose a prediction model for bulk h-BN degradation dynamics during CVS. We found that carrier trapping into preexisting sites and the probability of defect generation were enhanced by the bombardment of ions with higher energy during the bulk h-BN formation and a larger number of incorporated W atoms. These findings provide fundamental guidelines for the reliability assessment of bulk h-BN films for various applications.
The streamer dynamic evolution and discharge mode transition of a three-electrode surface dielectric barrier discharge (SDBD) driven by repetitive pulses are studied experimentally and numerically for better plasma-mode control and optimized application. Spatial-temporal plasma morphologic features together with electro-optical behavior are utilized to analyze the streamer dynamic evolution and streamer-to-spark transition. To gain a deep insight into the physical mechanism of the discharge mode transition in repetitive pulses, a 2D fluid model combined with a 0D kinetic model is built and studied. A good agreement between the experimental measurements and numerical simulation in the propagation dynamics and voltage–current characteristics is achieved. The results show that the surface-streamer discharge in the form of primary and transitional streamers can transform into a surface-spark discharge characterized by the primary streamer, transitional streamer and spark phase in repetitive pulses under the high applied electric field. A high gas temperature will result in a large reduced electric field after the transitional streamer, which exceeds the ionization threshold and thus promotes the discharge mode transition. A high number of electrons can be released from the negative charges by oxygen atoms during the inter-pulse period, which is favorable for the re-ignition and ionization process of the subsequent pulse discharge.
Disruptions are abrupt collapses of the configuration that have afflicted all tokamaks ever operated. Reliable observers are a prerequisite to the definition and the deployment of any realistic strategy of countermeasures to avoid or mitigate disruptions. Lacking first principle models of the dynamics leading to disruptions, in the past decades empirical predictors have been extensively studied and some were even installed in JET real time network. Having been conceived as engineering tools, they were often very abstract. In this work, physics and data-driven methodologies are combined to identify the main macroscopic precursors of disruptions: magnetic instabilities, abnormal kinetic profiles and radiation patterns. Machine learning predictors utilising these observers can not only detect and classify these anomalies but also determine their probability of occurrence and estimate the time remaining before their onset. These tools have been applied to a database of about two thousand JET discharges with various isotopic compositions including DT, in conditions simulating in all respects real time deployment. Their performance would meet ITER requirements, and they are expected to be easily transferrable to larger devices, because they rely only on normalised quantities, form factors, and physical/empirical scaling laws.
Direct current (DC) electric arcs are of particular interest because they can produce large volumes of thermal plasmas with controlled energy deposition. When such discharges are applied in a gas flow, convection displaces the top of the arc downstream while the arc roots remain attached to the electrodes, thus increasing the length of the arc over time. However, this growth is limited by a restrike phenomenon, which starts from streamers appearing in high electric field regions and shortcutting the long, stretched electric arc. From a numerical point of view, DC arcs can be efficiently simulated with a resistive magneto-hydrodynamics (MHD) model, with numerical requirements in terms of spatial and temporal discretization that are compatible with classic fluid dynamics and combustion simulations. However, arc restrikes rely on the propagation of streamer discharges that are highly non-neutral phenomena, whereas classical MHD assumes neutrality. To tackle this problem, we propose in this paper a model of restrike that can be used in an MHD approach. After describing the ideas of the model, we perform a parametric study of the input parameters to examine its influence on the discharge dynamics.
A gliding arc plasmatron (GAP) is a promising warm plasma source for the use in gas conversion applications but lacks an understanding of the plasma dynamics. In this paper, the gliding arc plasma conditions of a GAP operated with nitrogen flow (10 slm) are characterized using optical emission spectroscopy (OES) and numerical simulation. A simultaneously two-wavelength OES method and Abel inversion of the measured images with a spatial resolution of 19.6 μm are applied. The collisional radiative model used in this study includes Coulomb collisions of electrons. An iterative method of plasma parameter determination is applied. The determined values of the electric field up to 49 Td and electron density up to 2.5∙1015 cm−3 fit well to the plasma parameters received with different diagnostics methods in comparable plasma sources. Additionally, the electric current, which is calculated using the determined reduced electric field and electron density, is compared with the measured one.
To expand on recent work, we introduce collisional terms in the analysis of the warm ion-electron, two-fluid equations for a homogeneous plasma at rest. Consequently, the plasma is now described by six variables: the magnetisation, the ratio of masses over charges, the electron and ion sound speeds, the angle between the wave vector and the magnetic field, and a new parameter describing the electron-ion collision frequency. This additional parameter does not introduce new wave modes compared to the collisionless case, but does result in complex mode frequencies. Both for the backward and forward propagating modes the imaginary components are negative and thus quantify collisional damping. We provide convenient (polynomial) expressions to quantify frequencies and damping rates in all short and long wavelength limits, including the cut-off and resonance limits, whilst the one-fluid magnetohydrodynamic limit is retained with the familiar undamped slow, Alfvén and fast (SAF) waves. As collisions only introduce a damping, the previously introduced labelling of the wave modes S, A, F, M, O and X can be kept and assigned based on their long and short wavelength behaviour. The obtained damping at cut-off and resonance limits is parametrised with the collision frequency, and can be tailored to match known kinetic damping expressions. It is demonstrated that varying the angle can introduce crossings between the wave modes, as was already present in the ideal ion-electron case, but also a collision frequency exceeding a critical collision frequency can lead to crossings at angles where previously only avoided crossings were found.
Collisionless shocks are frequently analyzed using the magnetohydrodynamics (MHD) formalism, even though MHD assumes a small mean free path. Yet, isotropy of pressure, fruit of binary collisions and assumed in MHD, may not apply in collisionless shocks. This is especially true within a magnetized plasma, where the field can stabilize an anisotropy. In a previous article \citep{BretJPP2022b}, a model was presented capable of dealing with the anisotropies that may arise at the front crossing. It was solved for any orientation of the field with respect to the shock front. Yet, for some values of the upstream parameters, several downstream solutions were found. Here, we complete the work started in \cite{BretJPP2022b} by showing how to pick the physical solution out of the ones offered by the algebra. This is achieved by 2 means: 1) selecting the solution that has the downstream field obliquity closest to the upstream one. This criterion is exemplified on the parallel case and backed up by Particle-in-Cell simulations. 2) Filtering out solutions which do not satisfy a criteria already invoked to trim multiple solutions in MHD: the evolutionarity criterion, that we assume valid in the collisionless case. The end result is a model in which a given upstream configuration results in a unique, or none (like in MHD), downstream configuration. The largest departure from MHD is found for the case of a parallel shock.
The advent of data-driven/machine-learning based methods and the increase in data available from high-fidelity simulations and experiments has opened new pathways toward realizing reduced-order models for plasma systems that can aid in explaining the complex, multi-dimensional phenomena and enable forecasting and prediction of the systems’ behavior. In this two-part article, we evaluate the utility and the generalizability of the dynamic mode decomposition (DMD) algorithm for data-driven analysis and reduced-order modeling of plasma dynamics in cross-field E × B configurations. The DMD algorithm is an interpretable data-driven method that finds a best-fit linear model describing the time evolution of spatiotemporally coherent structures (patterns) in data. We have applied the DMD to extensive high-fidelity datasets generated using a particle-in-cell (PIC) code based on the cost-efficient reduced-order PIC scheme. In this part, we first provide an overview of the concept of DMD and its underpinning proper orthogonal and singular value decomposition methods. Two of the main DMD variants are next introduced. We then present and discuss the results of the DMD application in terms of the identification and extraction of the dominant spatiotemporal modes from high-fidelity data over a range of simulation conditions. We demonstrate that the DMD variant based on variable projection optimization (OPT-DMD) outperforms the basic DMD method in identification of the modes underlying the data, leading to notably more reliable reconstruction of the ground-truth. Furthermore, we show in multiple test cases that the discrete frequency spectrum of OPT-DMD-extracted modes is consistent with the temporal spectrum from the fast Fourier transform of the data. This observation implies that the OPT-DMD augments the conventional spectral analyses by being able to uniquely reveal the spatial structure of the dominant modes in the frequency spectra, thus, yielding more accessible, comprehensive information on the spatiotemporal characteristics of the plasma phenomena.
AbstractUnusual thermal self‐focusing of two‐dimensional beams in plasma which axis is parallel to the equilibrium straight magnetic field is considered. The equilibrium parameters of plasma determine scenario of a beam divergence (usual or unusual) which is stronger as compared with a flow without magnetic field. Nonlinear thermal self‐action of a magnetosonic beam behaves differently in the ordinary and unusual cases. Damping of wave perturbations and normal defocusing in gases leads to reduction of the magnitude of initially planar perturbations at the axis of a beam. Additional thermal self‐focusing nonspecific for gases occurs in plasma under some condition which counteracts this reduction. The theory and numerical examples concern thermal self‐action of initially focused (defocused) magnetosonic beam. Dynamics of perturbations in a beam is determined by dimensionless parameters responsible for diffraction, damping of the wave perturbations, initial radius of a beam's front curvature, and the ratio of viscous to thermal damping coefficients.
Complex plasma environments can give insight into the nature of systems that do not obey Newton’s third law. As negatively charged dust particles interact with flowing ions, the ion wake-field forms a positively charged spatial region. The force from the wake-field is non-reciprocal in nature, as only a downstream particle is influenced by the wake. This wake-field interaction gives insight into the conditions and forces needed to create stable dust structures. A molecular dynamics simulation of flowing ions and dust grain is used to model vertically oriented dust chains that have been confined by a glass box placed on the lower electrode in a Gaseous Electronics Conference rf cell to gain insight into the forces acting on these particles. Previous simulations of this structure employing a constant ion number density indicated that the sheath electric field and dust charge is not constant. This model has been extended to include the effect of the ion number density decreasing towards the lower electrode and the effect of multiple chains. This simulation is applied iteratively, minimizing the force balance equation to give insight into the conditions needed for stability.
A three-dimensional fully kinetic particle-in-cell (PIC) simulation strategy has been implemented to simulate the acceleration stage of a magnetically enhanced plasma thruster (MEPT). The study has been performed with the open-source code Spacecraft Plasma Interaction Software (SPIS). The tool has been copiously modified to simulate properly the dynamics of a magnetized plasma plume. A cross-validation of the methodology has been done with Starfish, a two-dimensional open-source PIC software. Two configurations have been compared: (i) in the absence of a magnetic field and (ii) in the presence of a magnetic field generated by a coil with maximum intensity of 300 G at the thruster outlet. The results show a reduction of the plume divergence angle, an increase of ion speed and an increase of the specific impulse in the presence of the magnetic nozzle. The simulations presented in this study are representative of the operative conditions of a 50 W MEPT. Nonetheless, the methodology adopted can be extended to handle the magnetized plasma plume of several other types of thrusters such as electron cyclotron resonance and applied field magnetoplasmadynamic thrusters.
A new method for determining plasma parameters from beam current transients resulting from short pulse 1+ injection into a Charge Breeder Electron Cyclotron Resonance Ion Source (CB-ECRIS) has been developed. The proposed method relies on few assumptions, and yields the ionisation times $1/n_e\left\langleσv\right\rangle^{\text{inz}}_{q\to q+1}$, charge exchange times $1/n_0\left\langleσv\right\rangle^{\text{cx}}_{q\to q-1}$, the ion confinement times $τ^q$, as well as the plasma energy contents $n_e\left\langle E_e\right\rangle$ and the plasma triple products $n_e \left\langle E_e\right\rangle τ^q$. The method is based on fitting the current balance equation on the extracted beam currents of high charge state ions, and using the fitting coefficients to determine the postdictions for the plasma parameters via an optimisation routine. The method has been applied for the charge breeding of injected K$^+$ ions in helium plasma. It is shown that the confinement times of K$^{q+}$ charge states range from 2.6$^{+0.8}_{-0.4}$ ms to 16.4$^{+18.3}_{-6.8}$ ms increasing with the charge state. The ionisation and charge exchange times for the high charge state ions are 2.6$^{+0.5}_{-0.5}$ ms--12.6$^{+2.6}_{-3.2}$ ms and 3.7$^{+5.0}_{-1.6}$ ms--357.7$^{+406.7}_{-242.4}$ ms, respectively. The plasma energy content is found to be $2.5^{+4.3}_{-1.8}\times 10^{15}$ eV/cm$^3$.