Fluorine (F) recovery from wet process phosphoric acid (WPA) is essential for sustainable resource utilization and environmental protection. This work systematically investigates the F recovery mechanism by air stripping from three simulated systems: H3PO4- H2SiF6-H2O, H3PO4- HF-H2O, H3PO4- H2SiF6-HF-Al3+-H2O, and from two industrial systems: WPA and WPA-Al3+ under different stripping temperatures (60–110 ℃) and stripping times (0–120 min). The influence on the existence form of F, the content of Al3+ cations and the addition of active silica on the F removal rate in the phosphoric acid solution is studied by analyzing the changes in the contents of F, P and Si. The results indicate that the F in the form of H2SiF6 is more easily released from the phosphoric acid solution than that in the form of HF. While, the release of F is inhibited in the presence of the Al3+ in the solution due to the formation of Al-F complexes that are characterized by 19F NMR, 31Si NMR and FTIR techniques. Interestingly, the addition of active silica can promote the conversion of HF to H2SiF6 in the solution and significantly improve the release rate of F. The researching results can provide an important guidance for industrial practice of WPA.

To improve the performance of wide-issue superscalar processors, it is essential to increase the width of instruction fetch and the issue rate. Removal of control hazard has been put forward as a significant new source of instruction-level parallelism for superscalar processors and the conditional branch prediction is an important technique for improving processor performance. Branch mispredictions, however, waste a large number of cycles, inhibit out-of-order execution, and waste electric power on mis-speculated instructions. Hence, the branch predictor with higher accuracy is necessary for good processor performance. In global-history-based predictors like gshare and GAg, many mispredictions come from commit update of the branch history. Some works on this subject have discussed the need for speculative update of the history and recovery mechanisms for branch mispredictions. In this paper, we present a new mechanism for recovering the branch history after a misprediction. The proposed mechanism adds an age_counter to the original predictor and doubles the size of the branch history register. The age_counter counts the number of outstanding branches and uses it to recover the branch history register. Simulation results on the SimpleScalar 3.0/PISA tool set and the SPECINT95 benchmarks show that gshare and GAg with the proposed recovery mechanism improved the average prediction accuracy by 2.14% and 9.21%, respectively and the average IPC by 8.75% and 18.08%, respectively over the original predictor.