Investigation of island size effect on radiation distribution during attached and detached plasmas in the island divertor of W7-X
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Abstract Interatomic potentials derived with Machine Learning algorithms such as Deep-Neural Networks (DNNs), achieve the accuracy of high-fidelity quantum mechanical (QM) methods in areas traditionally dominated by empirical force fields and allow performing massive simulations. Most DNN potentials were parametrized for neutral molecules or closed-shell ions due to architectural limitations. In this work, we propose an improved machine learning framework for simulating open-shell anions and cations. We introduce the AIMNet-NSE (Neural Spin Equilibration) architecture, which can predict molecular energies for an arbitrary combination of molecular charge and spin multiplicity with errors of about 2–3 kcal/mol and spin-charges with error errors ~0.01e for small and medium-sized organic molecules, compared to the reference QM simulations. The AIMNet-NSE model allows to fully bypass QM calculations and derive the ionization potential, electron affinity, and conceptual Density Functional Theory quantities like electronegativity, hardness, and condensed Fukui functions. We show that these descriptors, along with learned atomic representations, could be used to model chemical reactivity through an example of regioselectivity in electrophilic aromatic substitution reactions.
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In situ X-ray scattering kinetics and population balance modeling of crystal nucleation and growth.
The 3ω method is a well-established thermal technique used to measure the thermal conductivity of materials and the thermal resistance of interfaces. It has significant advantages over other steady state and transient thermal techniques in its ability to provide spatially resolved thermal property measurements over a wide range of thermal conductivity. Despite its advantages, it has been restricted to lab-scale use because of the difficulty involved in sample preparation and sensor fabrication and is limited to non-metallic substrates. High-throughput 3ω measurements with reusable sensors have not been realized yet. In this work, we demonstrate a method of applying reusable 3ω sensors fabricated on flexible polyimide films to measure bulk and spatially resolved thermal properties. Here, we establish the limits of thermal conductivity measurement with the method to be 1 to 200 W/mK, and within the measurement limit, we verify the method by comparing the measured thermal conductivities of standard samples with established values. From the 3ω measurements, we also determine the thermal resistance of an interlayer of thermal grease as a function of pressure and compare it against the resistance calculated from direct thickness measurements to demonstrate the ability of this method to provide spatially resolved subsurface information. The technique presented is general and applicable to both metallic and non-metallic substrates, providing a method for high-throughput 3ω measurements with reusable sensors and without considerable sample preparation.
Abstract Wendelstein 7-X (W7-X), the largest advanced stellarator, is built to demonstrate high power, high performance quasi-continuous operation. Therefore, in the recent campaign, experiments were performed to prepare for long pulse operation, addressing three critical issues: the development of stable detachment, control of the heat and particle exhaust, and the impact of leading edges on plasma performance. The heat and particle exhaust in W7-X is realized with the help of an island divertor, which utilizes large magnetic islands at the plasma boundary. This concept shows very efficient heat flux spreading and favourable scaling with input power. Experiments performed to overload leading edges showed that the island divertor yields good impurity screening. A highlight of the recent campaign was a robust detachment scenario, which allowed reducing power loads even by a factor of ten. At the same time, neutral pressures at the pumping gap entrance yielded the particle removal rate close to the values required for stable density control in steady-state operation.
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