English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Significant amount of uranous nitrate is required for reducing Pu(IV) into inextractable Pu(III) for partitioning of U(VI) and Pu(IV) present in the loaded organic phase in PUREX process. Experiments have been conducted for the preparation of uranous nitrate by reducing uranyl nitrate present in nitric acid solution using hydrogen over Pt/SiO 2  catalyst. The effect of process variables such as U(VI) concentration, H 2  pressure, nitric acid concentration, catalyst quantity, temperature, mixing speed, and hydrazine concentration (for stabilizing U(IV)) on the yield of U(IV) was studied. The process variables were optimized by a two-step statistical approach namely design of experiments. The initial screening of process variables and determination of important variables that affect the production of U(IV) was determined by definitive screening design (DSD) methodology. The DSD yielded three variables affecting the U(VI) reduction to a significant extent were U(VI) concentration, H 2  pressure and mixing speed. These significant variables were further optimized using five-level full factorial central composite design (CCD) methodology for understanding the intricate interactions between the variables and the combined effect of all variables at a time influencing the U(VI) reduction. A second-order polynomial equation derived from CCD was subjected to analysis of variance (ANOVA) for estimating the validity of the model and statistical significance of the terms involved in the polynomial. The results revealed that the model can predict the yield of U(IV) generation with 95% confidence in the proposed experimental range.

Design of experiments for the optimization of U(VI) reduction with hydrogen over Pt/SiO 2