Recent Publications

Model-Free Solid State Reaction Kinetics Analysis for Li4SiO4 Formation

Aroh Shrivastava, Shivdatsinh Ghariya, Shital Amin, Swapnil S. Lonare, Vyom Desai, Vilas C. Chaudhari, Paritosh Chaudhuri

Role of turbulence in density buildup during plasma formation in Ohmic discharges of Aditya-U tokamak

Umesh Nagora, Kiran Patel, J. Ghosh, S. K. Pathak, R. L. Tanna, M. B. Chowdhuri, K. Tahiliani, K. A. Jadeja, K. M. Patel, N. Ramaiya, et al.

This study examines density buildup during the plasma formation and burnthrough phases of Ohmic discharges in the Aditya-U tokamak by analyzing density measurements from a 140 GHz real-time heterodyne microwave interferometer. It has been observed that only a small percentage of gas (∼1%–4%) is ionized during the avalanche phase. Furthermore, statistically analyzing several tens of discharges, it has been revealed that the central chord-averaged density and the corresponding ionization fraction during the avalanche phase remain independent of E/Pfill, where E is the externally applied toroidal electric field and Pfill is the prefill pressure in the range of ∼1.7–2.5 × 10−4 Torr. Further density buildup occurs in the burnthrough phase, i.e., after the roll-over of the neutral hydrogen emission (Hα peak), which is highly influenced by the prevailing plasma conditions. This indicates that turbulent magnetic fields significantly influence the ionization after the avalanche process stops and plasma forms during the initial burnthrough phase. Electron motion becomes turbulent in turbulent magnetic fields, which seem to facilitate ionization.

Nonlinear energy transfer analysis between coherent modes in developing plasma turbulence

Sandip Das, Lavkesh Lachhvani, Kunal Singha, Rosh Roy, Tanmay Karmakar, Daniel Raju, Prabal Kumar Chattopadhyay

Energy transfer among various spectral components of fluctuating physical parameters in plasma occurs due to the nonlinear interactions, but these effects are typically not captured by the traditional linear spectral methods. Plasma density fluctuations measured in the Inverse Mirror Plasma Experimental Device (IMPED) have signatures of nonlinear mode interactions among various instabilities, such as Rayleigh–Taylor (RT) and drift-wave (DW) modes. In this paper, the energy transfer among these modes as a result of nonlinear wave interactions (through the quadratic coupling processes) have been investigated in detail. The existing computational methods for a single-field model such as the Ritz method and Kim method have been explored to understand the dynamics of nonlinear interactions between coherent modes. Both methods are applied and validated in simulation as well as experimental data from IMPED for coherent modes in a plasma. We find that the validity and applicability of the methods depend on the statistical nature of the data, particularly higher-order moments such as kurtosis, and on spatial stationarity. Energy transfer analysis using these methods reveals primarily the transfer of energy from a RT mode and a mix mode of DW and RT to a comparatively low-frequency DW mode, demonstrating the capability of the method to quantify spectral energy transport between the coherent modes.

Image processing method for post-discharge plasma wall inspection in tokamaks, with application to ITER

Tarundeep Kaur Lamba, L. Moser, Martin Kocan, Martin Vincent, Yan Rong, Ding Rui, Zhang Wei, Tom Wauter, Richard A. Pitts, Walsh Michael, et al.

Electromagnetic filament coalescence as magnetic island merging with diamagnetic effects

Souvik Mondal, N Bisai, Abhijit Sen, Indranil Bandyopadhyay

We investigate the nonlinear coalescence of two current-carrying ELM filaments using a three-dimensional electromagnetic fluid model. In the flat-density limit, the coalescence exhibits magnetic island-like reconnection, characterized by X-point formation, current-sheet development, and Sweet-Parker-like resistive scaling. Introducing a blob-like density perturbation modifies the reconnection dynamics: while the peak reconnection rate remains nearly unchanged for weak perturbations, it decreases and is increasingly delayed for larger density amplitudes. Analysis of the induction equation reveals a transition from resistive to increasingly density-dependent advective dynamics. Finite density perturbations also enhance the post-compression rebound, or sloshing, of the filaments. The sloshing amplitude increases with the density-gradient pressure force, establishing density perturbation as an additional control parameter for both reconnection and filament sloshing. These results highlight the coupled electromagnetic and pressure-driven dynamics governing the nonlinear evolution of ELM filaments in the tokamak edge.

First Plasma Commissioning and Operational Highlights from India's First Spherical Tokamak at IPR

Kishore Mishra, Aditya Verma, N. Mansoori, Saurabh Verma, Y. Paravastu, M. S. Khan, Arvind Kumar, S. G. Thatipamula, Vishal Verma, M Sheetal, et al.

A compact Spherical Tokamak(ST) is commissioned at Institute for Plasma Research (IPR) to explore low aspect ratio tokamak physics and technologies that complement to the existing high aspect ratio tokamaks namely ADITYA-U and SST-1 by enabling studies on non-inductive startup, current drive in over dense plasmas, and shaped plasma physics on a low cost platform. The device, India's first spherical tokamak has completed major mechanical, magnetic, and electrical integration, and the coil system has been successfully tested with series of integrated commissioning. First plasma experiments have been carried out with a modest Ohmic system assisted by a 2.45GHz microwave system, supported by a centralized control and data acquisition system. An initial diagnostic set comprising visible imaging, spectroscopy, magnetics, and radiation monitors required for machine operation has been installed. This paper presents the integrated commissioning experiences and first plasma experiments of the newly installed machine.

Interpretable statistical feature engineering for early disruption prediction in the short pulse ADITYA tokamak

Jyoti Agarwal, Kavit Patel, Bhaskar Chaudhury, Abhishek Sharma, Shrichand Jakhar, Manika Sharma

Reliable early disruption prediction is critical for the safe operation and real-time control of tokamaks. However, machine learning based prediction frameworks have predominantly targeted medium and long pulse devices, with comparatively limited attention given to short pulse tokamaks where available warning time is inherently constrained. In this work, an interpretable machine learning framework is developed for feature engineering and early prediction of disruptions in the ADITYA using the initial plasma evolution information, prior to the activation of the negative converter of the ohmic transformer power supply. Statistical descriptors comprising the mean, variance, skewness, kurtosis and wavelet energy entropy are extracted from routinely available plasma diagnostics over different operation time windows. Decision tree based feature selection is employed to identify physically meaningful disruption precursors and to reduce feature dimensionality. These selected features are used to train a random forest classifier. The proposed framework achieves stable predictive performance across different analysis windows, with a maximum ROC-AUC of 0.87 for 0-35 ms and 0-40 ms windows. Comparable and in some cases improved, performance is obtained using the reduced feature set, demonstrating that the selected statistical descriptors retain the essential information required for disruption prediction. The proposed methodology provides an interpretable and computationally efficient framework for real time disruption prediction in short pulse tokamaks and establishes that carefully engineered statistical descriptors can effectively replace raw time series inputs for early disruption prediction, thereby offering a practical pathway toward real time plasma control in short pulse tokamaks similar to ADITYA and ADITYA-U.

Mass Spectrometry Studies of Hydrogen Ions Energy Distributions in an ECR- based Large Volume Plasma Source

Bibekananda Naik, Ramesh Narayanan, Debaprasad Sahu, Mainak Bandyopadhyay, Ashish Ganguli

Plasma is produced in a Large Volume Plasma Source (LVPS; dia. = 1 m, height = 1m) using CW microwaves (= 400 - 600 W, 2.45 GHz), in a compact ECR plasma source (CEPS) attached to LVPS, at hydrogen gas pressures = 1 - 3 mTorr. Plasma expands along the CEPS magnetic field into LVPS. A Hiden Analytical HPR 60 molecular beam mass spectrometer (MBMS) is used to measure the H^- ion energy distribution functions (IEDFs) in the downstream plasma. Previous plasma characterization studies in LVPS indicated favourable downstream plasma conditions for volume production of H^- ions. Measurements conducted with the MBMS probe aligned facing the plasma flow = 80 cm downstream, gave typical H^- count rates = 3 x 10^5 counts /s, at = 400 W, = 1 mTorr, along with a distinct high energy tail (<= 20 eV). These and other results are analyzed in detail. The positive ion spectrum showed the H_3^+ count to be consistently high in all cases (= 60-70 %); the counts for H_2^+ and H^+ were =30-35 % and a =few %. Combining the Langmuir probe (LP) and MBMS data it is possible to determine the approximate densities in front of the MBMS probe aperture. At = 500 W and = 2 mTorr, one finds: n_(H^+) = 9.6 x 10^9 cm^(-3), n_(H_2^+) = 1.7 x 10^10 cm^(-3) and n_(H_3^+) = 4.3 x 10^10 cm^(-3). The corresponding H^- density, = 80 cm downstream is n_(H^-) = 3.9 x 10^8 cm^(-3). Accounting for all H^- losses due to scattering and destruction, one finds the effective mean free path for H^- loss to be = 12.4 cm. Noting that H^- formation takes place about = 10 - 30 cm downstream of the source exit, the approximate average H^- density in the formation zone is determined as = 5.5 x 10^10 cm^(-3). This value is remarkably encouraging for H^- production in volume mode, considering the large chamber volume and area, as well as the very moderate power used for the experiments.

Effect of confinement anisotropy on particle transport and structural relaxation of finite dust clusters in complex plasma

Hirakjyoti Sarma, Sushree Monalisha Sahu, P. Bandyopadhyay, Ankit Dhaka, A. Sen

A finite dusty plasma cluster of charged microparticles confined in an anisotropic potential well is investigated experimentally and through Langevin dynamics simulations. As the confinement anisotropy is increased, the cluster undergoes a structural transition from near isotropic concentric shells to a linear chain configuration. The spatiotemporal modes of the cluster are analyzed by using Singular Value Decomposition. At weaker confinement anisotropies, two modes are dominant. Mode 1, corresponding to a breathing-type oscillation of the cluster, and mode 2, representing an azimuthal rotational motion of the cluster, together carry around 99$\%$ of the signal energy. With increasing anisotropy, the dominance of mode 2 decreases and that of mode 1 increases. This mode restructuring is accompanied by an increasingly non-Gaussian particle displacement statistics as evidenced by positive values of the Non-Gaussian Parameter maintained over an extended time duration. Simultaneously, the increasing dominance of mode 1 and suppression of mode 2 is accompanied by a significant slowing down of structural relaxation, with the cluster eventually exhibiting signatures of structural arrest. At weaker anisotropy, the experimentally measured dynamical quantities are very sensitive to the initial conditions which account for the discrepancy between the experiment and initial condition averaged simulation results for these observables. This study offers insight into the mechanisms underlying anomalous transport and structural relaxation in anisotropically confined many-body systems.

Hydrogen permeation studies of India-specific reduced activation martensitic (IN-RAFM) steel

Sudhir Rai, Pragnesh B. Dhorajiya, Chandra Shekher Sasmal, Rudreksh B. Patel, R. Bhattacharyay, Chandan Danani, Paritosh Chaudhuri

Nonlinear Dynamics of Current-Carrying ELM Filaments: Spiral Vorticity, Rotation, and Velocity Suppression

Souvik Mondal, N Bisai, Abhijit Sen, Indranil Bandyopadhyay

In this work, we investigate the nonlinear dynamics of isolated current-carrying edge-localized mode (ELM) filaments using a reduced electromagnetic fluid model in slab geometry. Numerical simulations show that unidirectional parallel current significantly suppresses radial filament velocity and reduces the outward propagation velocity by weakening the curvature-driven interchange force. The reduction in radial velocity is found to follow a modified scaling relation, demonstrating that increasing current progressively weakens outward filament propagation. Analysis of the vorticity equation shows that the electromagnetic current source changes from a dipolar structure to a remarkable spiral pattern, and overcomes the conventional curvature drive in the nonlinear phase. This current-driven source directly imprints its topology on the vorticity field, resulting in spiral vorticity, enhanced angular momentum, increased rotational energy, and localized shear layers. The filament therefore undergoes a transition from a conventional propagating state to a rotationally self-organized electromagnetic structure. These findings demonstrate that parallel current acts as an effective electromagnetic vorticity source and provides new insight into the nonlinear dynamics of ELM filaments in tokamak edge plasmas.

Dynamics of phase space vortices in Vlasov plasmas with ion scale inhomogeneity : I Constant frequency drive study

Sanjeev Kumar Pandey, Amudon Chingangbam, Rajaraman Ganesh

Formation dynamics and stability starting from various phase space vortex (PSV) or Bernstein-Greene-Kruskal (BGK) structures i.e electron acoustic wave (EAW), Langmuir (LAN) waves is investigated in the presence of a quasi-stationary ion scale (QSIS) inhomogeneity using high resolution Vlasov-Poisson simulations with VPPM-OMP 1.0 solver. In a one dimensional, collisionless, periodic, unmagnetized plasma with kinetic ions and kinetic electrons, we first create a QSIS inhomogeneity using low amplitude electric field drive at ion acoustic (IA) frequency with k eq = mk min [where m = 2 is the mode number, k min corresponds to the longest scale in the system]. While creating QSIS inhomogeneity, we have demonstrated the existence of ion trapped particle instability (ITPI) which saturates as the amplitude of sideband modes become comparable to that of the primary nonlinear mode (quite analogous to the trapped particle instability in large amplitude electron plasma waves). Also, mode transition from m = 2 to m = 1 is observed during relaxation period due to the energy cascading process. Finally, an electron acoustic (EA) perturbation of scale k p = k min [m = 1] is applied on top of the QSIS inhomogeneity to determine its response in the presence of background ion scale inhomogeneity. Some key observations such as formation of transient PSV, wave-wave mode coupling interaction and various frequency generation alongwith comparative investigation with EA perturbation launched in the absence of ion scale inhomogeneity is also reported.

Dynamics of phase space vortices in Vlasov plasmas with ion scale inhomogeneity : II Chirped frequency drive study

Sanjeev Kumar Pandey, Amudon Chingangbam, Rajaraman Ganesh

In Part I of the companion paper [Ref Part I], we have extensively discussed about the creation of quasi-stationary ion scale (QSIS) inhomogeneity using a constant frequency external drive at ion-acoustic time scales, resulting in ion trapped particle instability (ITPI), wave-wave mode coupling interaction and energy cascading. QSIS thus formed is perturbed by applying small amplitude electron acoustic (EA) mode leading to the several key plasma response features. In this Part II, using electrostatic, unbounded, OpenMP Vlasov-Poisson solver i.e VPPM-OMP 1.0, we have investigated the formation of various phase space vortices (PSV) (generated using two step or one step time dependent downward frequency chirping drives) in the presence of background QSIS inhomogeneity obtained in Part I. In addition, we have also performed one to one comparison of individual cases with their homogeneous counterparts with exact simulation parameters. In presence of QSIS inhomogeneity, we have observed interesting phenomenon such as early onset of Langmuir (LAN) mode, suppression of PSV sizes, omission of PSVs when compared to the homogeneous cases. Also, for different two step or one step downward chirp perturbation cases, particle trapping or untrapping fractions and its response to the increasing chirp intervals are respectively reported.

Deep Learning Models for ADITYA-U MHD Equilibrium

Udaya Maurya, Suman Aich, Indranil Bandyopadhyay, Daniel Raju

This work presents deep learning models to predict magnetohydrodynamic equilibrium parameters and profiles for the ADITYA-U tokamak. A synthetic free-boundary equilibrium dataset consisting of 100,760 cases was generated using the pyIPREQ Grad-Shafranov solver, with inputs derived from 766 ADITYA-U plasma discharges and constrained to experimentally relevant circular limiter plasmas near the flat-top phase. Several deep learning approaches were investigated for predicting scalar equilibrium quantities, one-dimensional safety factor profiles and two-dimensional poloidal flux profiles. These approaches included Dense neural networks, principal component analysis based reduced-order models, one-dimensional and two-dimensional convolutional neural networks, and physics-informed neural networks incorporating Grad-Shafranov residual constraints. In addition, an inverse model was developed to estimate poloidal field coil currents from desired plasma equilibrium conditions. The results demonstrate that key equilibrium parameters and profiles can be accurately estimated within the operational domain represented by the dataset. The developed models provide a computationally efficient alternative to conventional equilibrium estimation and can be useful for real-time plasma control, rapid equilibrium analysis, and experimental planning in ADITYA-U operations.