Dataset Information

Impact of Precipitation Parameters on the Specific Surface Area of PuO₂.

ABSTRACT: Controlling the properties of PuO₂ through processing is of vital importance to environmental transport and fate, production of nuclear fuels, nuclear forensic analyses, stockpile stewardship, and storage of nuclear wastes applications. A number of processing conditions have been identified to control final product properties, including specific surface area (SSA), residual carbon content, adsorption of volatile species, morphology, and particle size. In this paper, a novel approach is developed for the prediction of PuO₂ SSA via the synthetic route of Pu(IV) oxalate precipitation followed by calcination. The proposed model utilizes multivariate regression methodology and leave one out formalism to link Savannah River Site (SRS) precipitation and calcination production data to the SSA of the final product. A comparison among the models provides insight into the accuracy and ability to identify variations amongst the processing data. Additionally, the models may also be used to fit new data outside of the parameters explored in a production facility. Finally, the trained model was compared to a similarly trained conventional model form to illustrate the influence of precipitation parameters on the prediction of the final SSA. The models presented here attempt to provide new methods for more accurate prediction of the PuO₂ product properties in a production scale environment for key environmental and nuclear applications.

SUBMITTER: Hoar E

PROVIDER: S-EPMC8756440 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundVeno-venous extracorporeal CO2 removal (vv-ECCO2R) is increasingly being used in the setting of acute respiratory failure. Blood flow rates through the device range from 200 ml/min to more than 1500 ml/min, and the membrane surface areas range from 0.35 to 1.3 m2. The present study in an animal model with similar CO2 production as an adult patient was aimed at determining the optimal membrane lung surface area and technical requirements for successful vv-ECCO2R.MethodsFour different membrane lungs, with varying lung surface areas of 0.4, 0.8, 1.0, and 1.3m2 were used to perform vv-ECCO2R in seven anesthetized, mechanically ventilated, pigs with experimentally induced severe respiratory acidosis (pH 7.0-7.1) using a 20Fr double-lumen catheter with a sweep gas flow rate of 8 L/min. During each experiment, the blood flow was increased stepwise from 250 to 1000 ml/min.ResultsAmelioration of severe respiratory acidosis was only feasible when blood flow rates from 750 to 1000 ml/min were used with a membrane lung surface area of at least 0.8 m2. Maximal CO2 elimination was 150.8 ml/min, with pH increasing from 7.01 to 7.30 (blood flow 1000 ml/min; membrane lung 1.3 m2). The membrane lung with a surface of 0.4 m2 allowed a maximum CO2 elimination rate of 71.7 mL/min, which did not result in the normalization of pH, even with a blood flow rate of 1000 ml/min. Also of note, an increase of the surface area above 1.0 m2 did not result in substantially higher CO2 elimination rates. The pressure drop across the oxygenator was considerably lower (<10 mmHg) in the largest membrane lung, whereas the smallest revealed a pressure drop of more than 50 mmHg with 1000 ml blood flow/min.ConclusionsIn this porcine model, vv-ECCO2R was most effective when using blood flow rates ranging between 750 and 1000 ml/min, with a membrane lung surface of at least 0.8 m2. In contrast, low blood flow rates (250-500 ml/min) were not sufficient to completely correct severe respiratory acidosis, irrespective of the surface area of the membrane lung being used. The converse was also true, low surface membrane lungs (0.4 m2) were not capable of completely correcting severe respiratory acidosis across the range of blood flows used in this study.

Dataset Information

Impact of Precipitation Parameters on the Specific Surface Area of PuO₂.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Impact of Precipitation Parameters on the Specific Surface Area of PuO2.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Impact of Precipitation Parameters on the Specific Surface Area of PuO₂.