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We demonstrate that geometric deformation of flux-surface induced by a magnetic island can trigger the bifurcation to an electron internal transport barrier (eITB) through a novel positive feedback loop arising from the nonlinear coupling between the neoclassical tearing mode (NTM) and collisionless trapped electron mode (CTEM). The magnetic island-induced deformation enhances the precession drift frequency of trapped electrons, resulting in suppression of the CTEM turbulence. The consequent reduction in turbulent heat transport steepens the electron temperature gradient, which in turn amplifies the magnetic island via an increase in bootstrap current, thereby closing and reinforcing the feedback loop. The key features of this NTM-triggered eITB theory are qualitatively consistent with the experimental observations from J-TEXT (Mao et al 2025 Nucl. Fusion 65 066018).

An experimental study on electron cyclotron heating (ECH) pre-ionization has been conducted on J-TEXT in support of the joint experiment research for ITER plasma initiation. In this experiment, ECH power was injected to the vessel before the application of loop voltage ionize the neutral gas and form the initial plasma or so-called pre-plasma. The impact of several significant factors, such as magnetic field configuration, pre-fill gas pressure, ECH toroidal injection angle and ECH power on the evolution of pre-plasma are systematically studied, aiming to identify shared features, clarify their potential relationship and optimize the discharge parameters to generate a rather high pre-plasma density. By separating ECH power from the inductive start-up, the effect of pre-plasma on tokamak start-up can be observed. A dynamic magnetic configuration facilitates the transition of pre-plasma to tokamak plasma. To assess the influence of pre-plasma density on tokamak start-up, two kinds of magnetic field configurations are examined. While the effect of different pre-plasma densities on tokamak start-up is negligible, a significant difference is observed between pure ohmic start-up and start-up with pre-ionization. The studies presented here show evolutionary trends and threshold values needed to optimize ECH pre-ionization and also a feasible way to improve pre-plasma density and a configuration to stabilize pre-plasma for transition. Eventually, these results may contribute to multi-machine research and physics analysis that can assist ITER with its optimal preparation for first plasma operation.

We report on comprehensive experimental studies of turbulence spreading in edge plasmas. These studies demonstrate the relation of turbulence spreading and entrainment to intermittent convective density fluctuation events or bursts (i.e. blobs and holes). The non-diffusive character of turbulence spreading is thus elucidated. The turbulence spreading velocity (or mean jet velocity) manifests a linear correlation with the skewness of density fluctuations, and increases with the auto-correlation time of density fluctuations. Turbulence spreading by positive density fluctuations is outward, while spreading by negative density fluctuations is inward. The degree of symmetry breaking between outward propagating blobs and inward propagating holes increases with the amplitude of density fluctuations. Thus, blob-hole asymmetry emerges as crucial to turbulence spreading. These results highlight the important role of intermittent convective events in conveying the spreading of turbulence, and constitute a fundamental challenge to existing diffusive models of spreading.

Experimental studies of the dynamics of shear flow and turbulence spreading at the edge of tokamak plasmas are reported. Scans of line-averaged density and plasma current are carried out while approaching the Greenwald density limit on the J-TEXT tokamak. In all scans, when the Greenwald fraction fG=n¯/nG=n¯/(Ip/πa2) increases, a common feature of enhanced turbulence spreading and edge cooling is found. The result suggests that turbulence spreading is a good indicator of edge cooling, indeed better than turbulent particle transport is. The normalized turbulence spreading power increases significantly when the normalized E×B shearing rate decreases. This indicates that turbulence spreading becomes prominent when the shearing rate is weaker than the turbulence scattering rate. The asymmetry between positive/negative (blobs/holes) spreading events, turbulence spreading power and shear flow are discussed. These results elucidate the important effects of interaction between shear flow and turbulence spreading on plasma edge cooling.

Understanding the origin of the tokamak thermal quench (TQ) remains a critical unresolved issue, particularly the causal link between initial localized temperature collapse and the final core energy collapse. This work presents a detailed experimental investigation of the TQ process on the J-TEXT tokamak, utilizing high-resolution diagnostics at multiple toroidal locations to observe disruptions with rotating precursor modes. We demonstrate that the initial localized temperature collapse near the q = 2 surface and the core temperature collapse are not independent events but are sequential phases of the continuous evolution of a cold structure (CS), thereby establishing a direct causal link between the two events. This CS originates near the inner separatrix of the pre-existing m / n = 2/1 magnetic island, and it is observed to be in-phase locked with the island. This CS is identified as a helical structure with a dominant m / n = 1/1 character, when it develops towards the core. The continuous radially inward and poloidal expansion of this structure drives an asymmetric temperature collapse. This provides a physical explanation to the increase of measured core electron temperature during TQ, which results from the rotation of remaining helical hot core. The observations are also applicable to auxiliary-heated plasmas on J-TEXT. The initial collapse is discussed, which is likely triggered by the excitation of 3/2 island. Additionally, a reduced model is developed to describe the magnetic topology and to simulate the temperature evolution. These findings indicate that the stochastic field during TQ originates from a localized region during precursors and evolves to the global stochasticity at the final energy loss.

Periodic collapses at the edge of Ohmic-mode plasma under Resonant Magnetic Perturbation (RMP) have been observed in the J-TEXT tokamak. These collapses occur following the field penetration. During the collapse, particles and heat flow outward through the X-point of the boundary m/n = 3/1 magnetic island, where m and n are the poloidal and toroidal mode number respectively. After the collapse, the magnetic island rapidly expands to its maximum width, then gradually shrinks until it disappears. The reason why the magnetic island cannot sustain itself remains unclear. Afterward, the edge plasma returns to its initial state, and the cycle will repeat with the next collapse. Additionally, the conditions leading to periodic collapses have been identified, the amplitude of RMPs at q = 3 resonant surface is essential. No field penetration exists if the amplitude is too small. If the amplitude is too large, the magnetic island remains after field penetration and collapses no longer happen. Therefore, periodic collapses only appear when applying a moderate amplitude of RMP. Carbon impurities play a significant role in triggering instabilities of edge magnetic island and collapse events. This behavior is different from the pumping-out effect previously observed on J-TEXT, which was caused by a 2/1 magnetic island in the core.

Tokamaks are the most promising way for nuclear fusion reactors. Disruption in tokamaks is a violent event that terminates a confined plasma and causes unacceptable damage to the device. Machine learning models have been widely used to predict incoming disruptions. However, future reactors, with much higher stored energy, cannot provide enough unmitigated disruption data at high performance to train the predictor before damaging themselves. Here we apply a deep parameter-based transfer learning method in disruption prediction. We train a model on the J-TEXT tokamak and transfer it, with only 20 discharges, to EAST, which has a large difference in size, operation regime, and configuration with respect to J-TEXT. Results demonstrate that the transfer learning method reaches a similar performance to the model trained directly with EAST using about 1900 discharge. Our results suggest that the proposed method can tackle the challenge in predicting disruptions for future tokamaks like ITER with knowledge learned from existing tokamaks. Tokamak devices currently hold the technological advance to be considered the most promising approach to fusion energy, but disruption events prediction is a major challenge for larger devices. The authors show that a machine learning model trained on a smaller tokamak holds promises for transfer of knowledge of disrupting violent events prediction to another, larger tokamak.

A Tokamak-Stellarator hybrid configuration has been established on the J-TEXT tokamak by the application of stellarator-like External Rotational Transform (ERT) coils. The hybrid configuration aims to combine the advantages of both tokamak and stellarator, particularly to enhance plasma magnetohydrodynamic stability via magnetic configuration optimization, while avoiding the adverse effects commonly associated with resonant magnetic perturbation penetration. Experimental results demonstrate that the hybrid configuration enables complete suppression of both classical and neoclassical tearing modes (TM) and significantly broadens the operational region, increasing the maximum stable plasma current by approximately 20%. During the TM suppression process, a hysteresis-like, nonlinear relationship between the ERT current and the TM amplitude is observed. These findings demonstrate the effectiveness of the hybrid configuration in improving plasma stability and provide a potential pathway for stable operation in future magnetic confinement fusion devices.

This article presents an in-depth study of the sequence of events leading to density limit disruption in J-TEXT tokamak plasmas, with an emphasis on boundary turbulent transport and the high-field-side high-density (HFSHD) front. These phenomena have been extensively investigated using a Langmuir probe and Polarimeter–interferometer diagnostics. The research reveals a consistent pattern of events as the plasma density ramps up: the collapse of the sheared radial electric field, the enhancement of the boundary quasi-coherent turbulence ( 50∼80kHz), the increase in boundary particle transport induced by this turbulence, edge cooling and the emergence of the HFSHD front. These phenomena occur once the plasma density exceeds a critical value. Importantly, by exploring plasmas with varying edge safety factor ( qa), it is revealed that the density thresholds for these phenomena are all inversely proportional to qa. The findings offer valuable insights into the mechanisms underlying density limit disruptions in tokamak plasmas, suggesting that the enhancement of edge turbulent transport plays a crucial role in the edge cooling and triggering the HFSHD front. For the first time, a strong link between the edge turbulent transport and the HFSHD front has been observed. In addition, the evolution of the boundary electron temperature across various qa plasmas can further validate the link between the edge turbulent transport and the HFSHD formation.

DNA methylation is a critical epigenetic mechanism involved in key cellular processes. Its deregulation has been linked to many human cancers including esophageal squamous cell carcinoma (ESCC). This study was designed to explore the whole methylation status of ESCC and to identify potential plasma biomarkers for early diagnosis. We used Infinium Methylation 450k array to analyze ESCC tissues (n = 4), paired normal surrounding tissues (n = 4) and normal mucosa from healthy individuals (n = 4), and combined these with gene expression data from the GEO database. One hundred and sixty eight genes had differentially methylated CpG sites in their promoter region and a gene expression pattern inverse to the direction of change in DNA methylation. These genes were involved in several cancer-related pathways. Three genes were validated in additional 42 ESCC tissues and paired normal surrounding tissues. The methylation frequency of EPB41L3, GPX3, and COL14A1 were higher in tumor tissues than in normal surrounding tissues (P < 0.017). The higher methylation frequency of EPB41l3 was correlated with large tumor size (P = 0.044) and advanced pT tumor stage (P = 0.001). The higher methylation frequency of GPX3 and COL14A1 were correlated with advanced pN tumor stage (P = 0.001 and P < 0.001). The methylation of EPB41L3, GPX3, and COL14A1 genes were only found in ESCC patients' plasma, but not in normal individuals upon testing 42 ESCC patients and 50 healthy individuals. Diagnostic sensitivity was increased when methylation of any of the 3 genes were counted (64.3% sensitivity and 100% specificity). These differentially methylated genes in plasma may be used as biomarkers for early diagnosis of ESCC.