SPECIAL TOPIC—Non-equilibrium transport and active controlstrategy in low-temperature plasmas
2025, 74 (20): 205206.
doi: 10.7498/aps.74.20251183
Abstract +
Carbon quantum dots, as an emerging zero-dimensional carbon-based nanomaterial, have shown great potential applications in fields such as biomedicine, sensing detection, and LED lighting due to their excellent photoelectric properties, good biocompatibility, and ease of functionalization. Traditional synthesis methods like hydrothermal and microwave approaches often face challenges such as harsh reaction conditions, long reaction times, high energy consumption, and difficulties in controlling the optical properties of the products. The plasma electrochemistry method, which utilizes reactions between carbon source molecules and high-density electrons, ions, photons, and reactive radicals generated during the interaction of plasma with liquid, can efficiently drive the rapid synthesis and modification of carbon quantum dots. This method possesses the advantage of tunable multiple reaction parameters under mild conditions, providing a novel research method for synthesizing and modifying carbon quantum dots. This article first elucidates the growth mechanism of carbon quantum dots synthesized via plasma electrochemical methods and highlights the unique advantages of this approach in controlling product properties by regulating multidimensional parameters. Then, it reviews research progress of the regulation of the fluorescence quantum yield and wavelength of carbon quantum dots based on the adjustment of plasma reaction parameters. Finally, this article presents the application progress and prospects of plasma-prepared and plasma-modified carbon quantum dots in biomedicine, optoelectronic devices, pH sensing, and other fields.
2025, 74 (20): 205201.
doi: 10.7498/aps.74.20250983
Abstract +
In neutral beam injection (NBI), which is a primary auxiliary heating method for tokamak plasmas, the negative hydrogen ion source (NHIS) functions as a critical front-end component governing neutral beam quality. The performance of NHIS remains a key challenge. This work presents a three-dimensional (3D) fluid model, which is developed for a double-driver NHIS to simulate and optimize surface-generated negative hydrogen ion density. A comparison of plasma parameters between the NHIS with Cs and without Cs shows that surface generation yields negative ion density one order of magnitude higher than volume generation. However, the presence of the magnetic filter field induces asymmetry in negative ion density within the extraction region. To improve this asymmetry, two approaches are proposed: 1) increasing the power of one of the drivers and 2) adding a spacer plate to the expansion region. After increasing the power of Driver I from 50 to 56 kW, the H– density asymmetry at the y = 25 cm intercept on the xy-plane (z = –22 cm) decreases from 0.04 to 0.01, and the value of H– density increases. Following the addition of a spacer plate, the H– density asymmetry further decreases to 0.004, but the value of H– density also shows a significant reduction. Finally, adding a magnetic shield to the back plate of the expansion region further optimizes H– density from 1.48×1017 m–3 to 2.50×1017 m–3, yielding a 69% increase downstream. This is because increased plasma transport into the expansion region enhances the dissociation rate of H2 molecules, thereby yielding more H atoms. The attenuation of the magnetic filter field in the driver region after adding a magnetic shield also enhances the symmetry of the H– density.
Diagnosing global properties of dusty plasma based on machine learning from single particle dynamics
2025, 74 (20): 205202.
doi: 10.7498/aps.74.20251129
Abstract +
Currently, it is a great challenge to accurately diagnose global properties of dusty plasmas from limited data. Based on machine learning, a novel diagnostic method for various global properties in dusty plasma experiments is developed from single particle dynamics. It is found that for both two-dimensional (2D) dusty plasma simulations and experiments, the global properties such as the screening parameters κ and the coupling parameter Γ can be accurately determined purely from the position fluctuations of individual particles. Hundreds of independent Langevin dynamical simulations are performed with various specified κ and Γ values, resulting in a great number of individual particle position fluctuation data, which can be used for training, validating, and testing various convolutional neural network (CNN) models. To confirm the feasibility of this diagnostic method, three different CNN models are designed to determin the κ value. For the simulation data, all these CNN models perform excellently in determining the κ value, with the averaged determined κ value almost equal to the specified κ value. For the experiment data, the distribution of the determined κ values always exhibits one prominent peak, which is very consistent with the κ value obtained from the widely accepted phonon spectra fitting method. Furthermore, this diagnostic method is extended to simulatneously determining both the κ and Γ values, achieving satisfactory results by using 2D dusty plasma data from both simulations and experiments. The excellent performance of the CNN models developed here clearly indicates that through machine learning, the global properties of 2D dusty plasmas can be fully characterized purely from single particle dynamics.
2025, 74 (20): 205203.
doi: 10.7498/aps.74.20251065
Abstract +
Complex plasmas are composed of ionized gases and mesoscopic particles, representing a typical non-equilibrium complex system. The particles are negatively charged due to the higher thermal velocity of the electrons and interact with each other via Yukawa interactions. Due to the easy recording of the individual particles' motion through video microscopy, the generic processes in liquids and solids can be studied at a kinetic level in complex plasmas. Under microgravity conditions, the particles are confined in the bulk plasma and form a three-dimensional cloud. In the PK-4 Laboratory on the International Space Station, melamine formaldehyde particles with diameters of 6.8 μm and 3.4 μm are consecutively injected into the plasma discharge. Due to the electrostatic force and ion drag force, usually, the particles cannot be mixed in the same region, thereby leading to a phase separation. During the particle injections, small particles penetrate into the big particle clouds and self-organize in different ways under different conditions. When the number density of the big particles is low, small particles form a channel in the center of the discharge tube due to the Yukawa repulsion, where the big particle cloud is weakly confined. When the number density of the big particles is moderate, lanes are formed during the penetration of the small particles, representing a typical nonequilibrium self-organization. When the number density of the big particles is high, dust acoustic waves are self-excited due to the two-stream instability. As the small and big particles interact with each other, the number density of particles in the wave crests sharply increases. However, the wave numbers and frequencies remain unchanged. This investigation offers insights into the different self-organizations during the particle injections in three-dimensional binary complex plasmas under microgravity conditions.
2025, 74 (20): 205204.
doi: 10.7498/aps.74.20251096
Abstract +
Low-pressure radio-frequency inductively coupled discharges can produce uniformly distributed monodisperse particles and plasma, making them widely used in nanodevice fabrication. The manufacturing of nanodevices typically requires the generation of particles ranging from nanometer to submicron scales. These particles usually carry negative charges and can significantly influence the discharge characteristics of the plasma. This study investigates the effects of particle size and density on electron bounce resonance heating (BRH) and fundamental plasma properties in low-pressure inductively coupled plasmas (ICPs) by using a hybrid model. The hybrid model consists of kinetic equation, electromagnetic field equation, and global model equation. The simulation results show that as the dust radius or density increases, the BRH effect characterized by the formation of a plateau in the probability function of electron energy, is gradually suppressed and eventually disappears, accompanied by a decrease in electron temperature, an increase in electron density, and an increase in particle surface potential. The dust charge decreases with the increase of particle density, while exhibiting a nonmonotonic variation with particle radius. The results show that the loss of high-energy electrons caused by the dust particles may create a more favorable plasma environment for the growth of monodisperse nanoparticles with low defects. Such an improvement in particle quality is crucial for reducing trap densities and enhancing the electrical performance of nanoparticle-based electronic devices.
2025, 74 (20): 209401.
doi: 10.7498/aps.74.20250788
Abstract +
In low-pressure plasmas, the collisions between particles are weak and insufficient damping from collisions, leading to the gradual development of various waves and instabilities. Thus, the effects of wave-particle interaction are non-negligible in the non-equilibrium transport processes in plasma under low pressure conditions. For example, the heating of ionospheric plasma by high-frequency electromagnetic waves plays an important role in achieving over-the-horizon communication. During the wave propagation through the ionosphere, the electromagnetic radiation changes the local electron temperature and density, and simultaneously, excites various wave modes and instabilities. This study focuses on the interactions between high-power electromagnetic waves emitted from the ground and ionospheric plasma. Based on the plasma fluid model and Zakharov method, a physical-mathematical model is established to describe the wave-wave and wave-particle interactions in the ionospheric plasmas under the excitation of the pump waves. The modeling results of the active heating of ionosphere show that when the ground-emitted waves propagate in the ionospheric plasma, the energy deposition of the electromagnetic waves at the reflection height will excite a strong localized electric field, leading to the parametric instabilities. When the frequency and wave vector matching conditions are satisfied, two different three-wave interactions will be excited, i.e. the parametric decay instability involving the pump wave, Langmuir wave and ion acoustic wave, as well as the parametric instability related to the pump wave, upper hybrid and lower hybrid waves. Within a certain range of pump frequency and power studied in this study, the decrease of the pump frequency will lead to the decrease of the reflection height of the ordinary waves, and simultaneously, the perturbation ratios of the electron temperature will also increase. A higher pump wave power will enhance the energy absorption of the ionospheric plasma by the pump wave, thereby increasing the electron temperature. The modeling results not only reveal the spatiotemporal evolutions of the ionospheric plasma characteristics under various pump parameters and the energy transport processes between waves and particles, but also theoretically explain the parametric instability, stimulated electromagnetic emission and other phenomena observed in experiments.
