Combination of ensemble machine learning models in photocatalytic studies using nano TiO2 - Lignin based biochar.

Synergizing photocatalytic reactions with machine learning methods can effectively optimize and automate the remediation of pollutants. In this work, commercial Degussa TiO2 nanoparticles and lignin based biochar (LB) where used to prepare TiO2: lignin based biochar (TLB) composites using ultrasound-assisted co-precipitation method. The photocatalytic property of the TLB composites where studied by conducting the photocatalytic degradation of a Basic blue 41 (BB41) dye. The influence of calcination temperature, T:LB compositions, catalyst dosage, initial dye pH, initial dye concentration, and illumination time on photocatalytic dye degradation were experimentally studied. The degradation efficiency of 96.72 % was obtained under optimized conditions for the photocatalyst calcined at 500 °C containing a 1:1 wt percentage of TiO2 and LB. The experimental data was further used to predict the photocatalytic degradation efficiency using Gradient Tree Boosting (GTB) and Extra Trees (ET) models. The GTB model gave the highest prediction accuracy of 94 %. The permutation variable importance revealed catalyst dosage and dye concentration as the most influential parameters in the prediction of the photocatalytic dye degradation efficiency.

Effective electronic waste valorization via microwave-assisted pyrolysis: investigation of graphite susceptor and feedstock quantity on pyrolysis using experimental and polynomial regression techniques.

Waste printed circuit board (WPCB) was subjected to microwave-assisted pyrolysis (MAP) to investigate the energy and pyrolysis products. In MAP, pyrolysis experiments were conducted, and the effects of WPCB to graphite mass ratio on three-phase product yields and their compositions were analyzed. In addition, the role of the initial WPCB mass (10, 55, and 100 g) and susceptor loading (2, 22, and 38 g) on the quality of product yield was also evaluated. By using design of experiments, the effects of graphite susceptor addition and WPCB feedstock quantity was investigated. A significant liquid yield of 38.2 wt.% was achieved at 38 g of graphite and 100 g of WPCB. Several other operating parameters, including average heating rate, pyrolysis time, microwave energy consumption, specific microwave power used, and product yields, were optimized for the MAP of WPCB. Pyrolysis index (PI) was calculated at the blending of fixed quantity WPCB (100 g) and various graphite quantities in the following order: 2 g (21) > 20 g (20.4) > 38 g (19.5). The PI improved by increasing the WPCB quantity (10, 55, and 100 g) with a fixed quantity of graphite. This work proposes the product formation and new reaction pathways of the condensable compounds. GC-MS of the liquid fraction from the MAP of WPCBs without susceptor resulted in the generation of phenolic with 46.1% relative composition. The addition of graphite susceptor aided in the formation of phenolic and the relative composition of phenolics was found to be 83.6%. The area percent of phenol increased from 42.8% (without susceptor) to 78.6% (with susceptor). Without a susceptor, cyclopentadiene derivative was observed in a very high composition (~ 31 area %).