https://nova.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 The advanced design of bioleaching process for metal recovery: A machine learning approach https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:52163 Wed 04 Oct 2023 10:49:42 AEDT ]]> Application of Machine Learning Algorithms to Estimate Enzyme Loading, Immobilization Yield, Activity Retention, and Reusability of Enzyme-Metal-Organic Framework Biocatalysts https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:42942 R² values of 0.85, 0.77, and 0.91, respectively. Both models are less effective in predicting the enzyme activity retention, however, with R² values of 0.63 or lower. Sensitivity analysis of the input variables revealed the most significant variables for each corresponding output parameter, allowing further optimization of the RFM. The final RFM was then tested with a second unseen dataset collected from experiments. Findings confirmed the validity of the predictive model, including a relative error of less than 25%. Our model can aid in the synthesis of enzyme-MOF biocatalysts by providing valuable estimates of these output parameters for different MOF precursors and enzymes, saving experimental time and cost.]]> Thu 08 Sep 2022 09:00:28 AEST ]]>