Electrical Transport in Polyvalent Liquid Bismuth and Antimony Metals

Accurate assessment of electrical transport for heavy polyvalent metals pause challenge due to complex electronic band structure, where s-wave scattering theory due to Ziman is failed. Improving schemes like t-matrix resistivity and self-consistent approach are proposed. In the present study, we employ selfconsistent approach to compute electrical resistivity (ρ) in liquid Bi and Sb at different temperatures (T). Structural input is estimated through charged hard-sphere reference system. Electron-ion interaction is modelled by modified empty-core pseudopotential including electron exchange and correlation effects. Since only two parameters are independent, as the core radius RC (= 0.51 RaZ − 1⁄3) is a theoretical input, we have tuned, once and for all, the single parameter to find ρ at melting temperature. The same set of parameters is used to deduce high-T resistivity, thermal conductivity and thermo-electric power. Overall good agreement is observed for transport properties for both metals. The present fitting scheme and so deduced results are discussed in comparison with other findings

Quasiharmonic r–space Computational Scheme for Phonon Dynamics: Case Study of Calcium Oxide

The role of phonons is important in accounting various properties of materials. Crystal potential being an anharmonic function of volume, variations are seen in phonon derived properties with a change in volume. In the present work, we employ an approximate technique of expanding phonon frequencies using Taylor series expansion upto second-order in volume to calculate the volume dependent phonon frequencies of CaO in B1 and B2 phases. Equilibrium properties are obtained by fitting Murnaghan EoS to first principles DFT based results, however. The mode Grüneisen parameter and concavity parameter are computed with the help of present ab initio phonon frequencies for both the phases. Their volume dependence are estimated analytically using the proposed scheme. We find that phonon frequencies increase by decreasing volume. Analytically calculated volume dependent phonon frequencies are compared in reasonable agreement with the frequencies obtained directly using DFT for B1-phase. Thus, the present r–space computational scheme of deriving volume dependent phonon frequency proves to be an alternative to overcome lengthy phonon calculations

Enhanced performance in fusion plasmas through turbulence suppression by megaelectronvolt ions

© 2022, The Author(s), under exclusive licence to Springer Nature Limited.Alpha particles with energies on the order of megaelectronvolts will be the main source of plasma heating in future magnetic confinement fusion reactors. Instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons in the plasma. Furthermore, alpha particles can also excite Alfvénic instabilities, which were previously considered to be detrimental to the performance of the fusion device. Here we report improved thermal ion confinement in the presence of megaelectronvolts ions and strong fast ion-driven Alfvénic instabilities in recent experiments on the Joint European Torus. Detailed transport analysis of these experiments reveals turbulence suppression through a complex multi-scale mechanism that generates large-scale zonal flows. This holds promise for more economical operation of fusion reactors with dominant alpha particle heating and ultimately cheaper fusion electricity.N

DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy

Funding Information: This material is based upon work supported by the US Department of Energy, Office of Science, Office of Fusion Energy Sciences, using the DIII-D National Fusion Facility, a DOE Office of Science user facility, under Awards DE-FC02-04ER54698 and DE-AC52-07NA27344. Publisher Copyright: © 2022 IAEA, Vienna.DIII-D physics research addresses critical challenges for the operation of ITER and the next generation of fusion energy devices. This is done through a focus on innovations to provide solutions for high performance long pulse operation, coupled with fundamental plasma physics understanding and model validation, to drive scenario development by integrating high performance core and boundary plasmas. Substantial increases in off-axis current drive efficiency from an innovative top launch system for EC power, and in pressure broadening for Alfven eigenmode control from a co-/counter-I p steerable off-axis neutral beam, all improve the prospects for optimization of future long pulse/steady state high performance tokamak operation. Fundamental studies into the modes that drive the evolution of the pedestal pressure profile and electron vs ion heat flux validate predictive models of pedestal recovery after ELMs. Understanding the physics mechanisms of ELM control and density pumpout by 3D magnetic perturbation fields leads to confident predictions for ITER and future devices. Validated modeling of high-Z shattered pellet injection for disruption mitigation, runaway electron dissipation, and techniques for disruption prediction and avoidance including machine learning, give confidence in handling disruptivity for future devices. For the non-nuclear phase of ITER, two actuators are identified to lower the L-H threshold power in hydrogen plasmas. With this physics understanding and suite of capabilities, a high poloidal beta optimized-core scenario with an internal transport barrier that projects nearly to Q = 10 in ITER at ∼8 MA was coupled to a detached divertor, and a near super H-mode optimized-pedestal scenario with co-I p beam injection was coupled to a radiative divertor. The hybrid core scenario was achieved directly, without the need for anomalous current diffusion, using off-axis current drive actuators. Also, a controller to assess proximity to stability limits and regulate β N in the ITER baseline scenario, based on plasma response to probing 3D fields, was demonstrated. Finally, innovative tokamak operation using a negative triangularity shape showed many attractive features for future pilot plant operation.Peer reviewe

Disruption prediction with artificial intelligence techniques in tokamak plasmas

In nuclear fusion reactors, plasmas are heated to very high temperatures of more than 100 million kelvin and, in so-called tokamaks, they are confined by magnetic fields in the shape of a torus. Light nuclei, such as deuterium and tritium, undergo a fusion reaction that releases energy, making fusion a promising option for a sustainable and clean energy source. Tokamak plasmas, however, are prone to disruptions as a result of a sudden collapse of the system terminating the fusion reactions. As disruptions lead to an abrupt loss of confinement, they can cause irreversible damage to present-day fusion devices and are expected to have a more devastating effect in future devices. Disruptions expected in the next-generation tokamak, ITER, for example, could cause electromagnetic forces larger than the weight of an Airbus A380. Furthermore, the thermal loads in such an event could exceed the melting threshold of the most resistant state-of-the-art materials by more than an order of magnitude. To prevent disruptions or at least mitigate their detrimental effects, empirical models obtained with artificial intelligence methods, of which an overview is given here, are commonly employed to predict their occurrence—and ideally give enough time to introduce counteracting measures