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Uranium recovery from seawater has been investigated for several decades for the purpose of securing nuclear fuel for energy production. In this study, field column experiments have been performed at the Marine Sciences Laboratory of the Pacific Northwest National Laboratory (PNNL) using a laboratory-proven, amidoxime-based polymeric adsorbent developed at the Oak Ridge National Laboratory (ORNL). The adsorbent was packed either in in-line filters or in flow-through columns. The maximum amount of uranium uptake from seawater was 3.3 mg of U/g of adsorbent after 8 weeks of contact between the adsorbent and seawater. This uranium adsorption amount was about 3 times higher than the maximum amount achieved in this study by a leading adsorbent developed at the Japan Atomic Energy Agency (JAEA). Both adsorbents were tested under similar conditions. The results were used to update an assessment of the cost of large-scale recovery of uranium from seawater using the ORNL adsorbent. The updated uranium production cost was estimated to be reduced to $610/kg of U, approximately half the cost estimated for the JAEA technology.

No abstract

This article provides an independent cost estimate for uranium production from seawater through the braid-type adsorbent recovery system proposed by the Japan Atomic Energy Agency (JAEA). Production costs were developed with standard engineering cost estimation techniques using vendor data and plant design and operational data. The analysis includes life cycle discounted cash flows, economies of scale, and propagation of uncertainties. A reference case based on the Japan Atomic Energy Agency assessment, with a fresh adsorbent capacity of 2 kgU/t ads and 6 recycles, yielded a production cost of $1230/kg uranium with a 95 percent confidence interval of [$1030/kg U, $1430/kg U] when component cost uncertainties alone were considered. Sensitivity studies confirmed that adsorbent capacity, number of recycles, and capacity degradation are major cost drivers. If capacity and number of recycles increases to 6 kg U/t ads and 20, respectively, with no degradation and unchanged adsorbent production costs, the uranium production cost drops to $299/kg U.

We formulate the theory for steering an active particle with optimal travel time between two locations and apply it to the Mexican hat potential without brim. For small heights the particle can cross the potential barrier, while for large heights it has to move around it. Thermal fluctuations in the orientation strongly affect the path over the barrier. Then we consider a smart active particle and apply reinforcement learning. We show how the active particle learns in repeating episodes to move optimally. The optimal steering is stored in the optimized action-value function, which is able to rectify thermal fluctuations.