Evaluation of Benzene Adsorption onto Grass-Derived Biochar and Comparison of Adsorption Capacity via RSM (Response Surface Methodology) DOI Open Access

Yuhyeon Na,

Seung Hyeon Weon,

GyuWon Lee

et al.

Journal of Composites Science, Journal Year: 2024, Volume and Issue: 8(4), P. 132 - 132

Published: April 5, 2024

The present study reports the effective removal of benzene in aqueous phase onto biochar. adsorption capacity biochars made at different pyrolytic temperatures (e.g., 350, 550, and 750 °C) from various feedstocks grape pomace, rice husk, Kentucky bluegrass) were investigated. bluegrass-derived biochar (KB-BC) prepared 550 °C for was better than other biochars, owing to higher surface area functional groups. isotherms kinetics model by KB-BC550 fitted Freundlich pseudo-first order, respectively. In addition, results response methodology (RSM) designed with dose, reaction time, concentration showed maximum (ca. 136 mg BZ/g BC) similar that kinetic study. KB-BCs obtained as waste grass biomass may be a valuable adsorbent, RSM useful tool investigation optimal conditions results.

Language: Английский

Probabilistic prediction of phosphate ion adsorption onto biochar materials using a large dataset and online deployment DOI
Sara Iftikhar,

Rehan Ishtiaq,

Nallain Zahra

et al.

Chemosphere, Journal Year: 2024, Volume and Issue: 370, P. 144031 - 144031

Published: Dec. 28, 2024

Language: Английский

Citations

3

Optimizing the Composting Process Emissions – Process Kinetics and Artificial Intelligence Approach DOI Open Access
Joanna Rosik, Sylwia Stegenta-Dąbrowska

Published: April 28, 2024

Although composting has many advantages in the treatment of organic waste, there are still problems and challenges associated with emissions, like NH3, VOCs, H2S, as well greenhouse gases such CO2, CH4, N2O. One promising approach to enhancing conditions is used novel analytical methods bad on artificial intelligence. To predict optimize emissions (CO, NH3) during process kinetics thought mathematical models (MM) machine learning (ML) were utilized. Data about everyday from laboratory compost’s biochar different incubation (50, 60, 70 °C) doses (0, 3, 6, 9, 12, 15% d.m.) for MM ML selections training. not been very effective predicting (R2 0.1 - 0.9), while acritical neural network (ANN, Bayesian Regularized Neural Network; R2 accuracy CO:0,71, CO2:0,81, NH3:0,95, H2S:0,72)) decision tree (DT, RPART; CO:0,693, CO2:0,80, NH3:0,93, H2S:0,65) have demonstrated satisfactory results. For first time CO H2S demonstrated. Further research a semi-scale field study needed improve developments models.

Language: Английский

Citations

2

A review on sulfur trioxide (SO3) removal from coal combustion process: Research progress challenges and suggestions DOI

Liqun Lian,

De-Xing Kong, Yan Wang

et al.

Separation and Purification Technology, Journal Year: 2024, Volume and Issue: 358, P. 130190 - 130190

Published: Oct. 20, 2024

Language: Английский

Citations

2

Adsorption of Dibenzofuran by Modified Biochar Derived from Microwave Gasification: Impact factors and adsorption mechanism DOI
Jiyun Ren,

Yong Zhang,

Hui Wang

et al.

Journal of Analytical and Applied Pyrolysis, Journal Year: 2024, Volume and Issue: unknown, P. 106831 - 106831

Published: Oct. 1, 2024

Language: Английский

Citations

2

Evaluation of Benzene Adsorption onto Grass-Derived Biochar and Comparison of Adsorption Capacity via RSM (Response Surface Methodology) DOI Open Access

Yuhyeon Na,

Seung Hyeon Weon,

GyuWon Lee

et al.

Journal of Composites Science, Journal Year: 2024, Volume and Issue: 8(4), P. 132 - 132

Published: April 5, 2024

The present study reports the effective removal of benzene in aqueous phase onto biochar. adsorption capacity biochars made at different pyrolytic temperatures (e.g., 350, 550, and 750 °C) from various feedstocks grape pomace, rice husk, Kentucky bluegrass) were investigated. bluegrass-derived biochar (KB-BC) prepared 550 °C for was better than other biochars, owing to higher surface area functional groups. isotherms kinetics model by KB-BC550 fitted Freundlich pseudo-first order, respectively. In addition, results response methodology (RSM) designed with dose, reaction time, concentration showed maximum (ca. 136 mg BZ/g BC) similar that kinetic study. KB-BCs obtained as waste grass biomass may be a valuable adsorbent, RSM useful tool investigation optimal conditions results.

Language: Английский

Citations

1