Potential and recycling strategies for LCD panels from WEEE

Indium is one of the strategically important materials, which have been characterized as critical by various industrialized countries. Despite its high relevance, only low recycling rates are realized. Its main application is in indium tin oxide (ITO), which is used in the production of liquid crystal displays (LCD). However, recovery strategies for indium from LCDs are not yet being implemented in recycling practices. Although LCDs consist of a sandwich compound with additional materials such as glass (80% ± 5%) and polarizer foils (20% ± 5%), recently published recycling approaches focus mainly on the recovery of indium exclusively. This study, first of all, provides information about the quantity and quality of the materials applied in the LCD panels of the various equipment types investigated, such as notebooks, tablets, mobile phones, smartphones, PC monitors, and LCD TVs. The highest indium mass fraction per mass of LCD was determined in mobile phones and the least indium was found in smartphones. Additionally, we found the significant use of contaminating metals like antimony, arsenic, lead, and strontium in the glass fraction. Thus, specific recovery strategies should focus on selected equipment types with the highest indium potential, which is directly related to the sales of new devices and the number of collected end-of-life devices. Secondly, we have developed and successfully tested a novel recycling approach for separating the sandwich compound to provide single output fractions of panel glass, polarizer foils, and an indium concentrate for subsequent recycling. Unfortunately, the strongly varying content of contaminating metals jeopardizes the recycling of this output fraction. Nonetheless, economic recycling approaches need to address all materials contained, in particular those with the highest share in LCD panels such as polarizer foils and panel glass

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate

Current Research into Applications of Tomography for Fusion Diagnostics

Retrieving spatial distribution of plasma emissivity from line integrated measurements on tokamaks presents a challenging task due to ill-posedness of the tomography problem and limited number of the lines of sight. Modern methods of plasma tomography therefore implement a-priori information as well as constraints, in particular some form of penalisation of complexity. In this contribution, the current tomography methods under development (Tikhonov regularisation, Bayesian methods and neural networks) are briefly explained taking into account their potential for integration into the fusion reactor diagnostics. In particular, current development of the Minimum Fisher Regularisation method is exemplified with respect to real-time reconstruction capability, combination with spectral unfolding and other prospective tasks