@article { ISI:000369482900019,
	title = {Behaviour of biomass multicomponent ashes as adsorbents},
	journal = {Current Science},
	volume = {110},
	number = {2},
	year = {2016},
	month = {JAN},
	pages = {180-186},
	publisher = {INDIAN ACAD SCIENCES},
	address = {C V RAMAN AVENUE, SADASHIVANAGAR, P B \#8005, BANGALORE 560 080, INDIA},
	abstract = {<p>Physico-chemical characteristics of rice husk ash and baggase fly ash, commonly referred to as biomass ashes enable their use as adsorbents. Contrary to normal expectations, it is observed that larger particles have more number, narrower and deeper pores than smaller particles. As a consequence they have higher pore volume, total surface area and hence adsorption capacity. Also, the uptake rate of adsorption depends on the silica to carbon ratio, which is seen to be smaller for larger particles and hence they take a longer time to reach equilibrium. The extent of carbon content determines the capacity, whereas silica to carbon ratio determines the kinetics of adsorption. Removal of 2,4-dichlorophenoxyacetic acid, from aqueous solution was chosen as a representative case for study and the results obtained are compared with earlier reported results.</p>},
	keywords = {Adsorption capacity, bagasse, biomass ash, rice husk, silica to carbon ratio},
	issn = {0011-3891},
	author = {Deokar, Sunil K. and Mandavgane, Sachin A. and Kulkarni, Bhaskar D.}
}
@article {46983,
	title = {Biomass ashes as potent adsorbent for pesticide: prediction of adsorption capacity by artificial neural network},
	journal = {International Journal of Environmental Science and Technology},
	volume = {17},
	year = {2020},
	month = {JUN},
	pages = {3209-3216},
	type = {Article},
	abstract = {<p>Biomass ashes are used for adsorption of herbicides from aqueous solution. A relationship between physicochemical properties of biomass ashes such as carbon-hydrogen-nitrogen content (CHN analysis), silica content and BET surface area with their adsorption capacity was established and modeled using artificial neural network. 2,4-Dichlorophenoxyacetic acid (2,4-D) a commonly used herbicide is chosen a representative for this study. The artificial neural network model was trained, validated and tested using 35 data sets and was equipped with nine neuron hidden layers having tansig (tangent sigmoid) transfer function and an output layer with purelin (purely linear) transfer function. This model can be used to predict 2,4-D removal efficacy of any biomass ash by knowing its physicochemical properties like C, H, N, Si and BET surface area.</p>
},
	keywords = {2, 4-D, Adsorption capacity, Artificial neural network, Biochar, biomass ash},
	issn = {1735-1472},
	doi = {10.1007/s13762-020-02645-9, Early Access Date = FEB 2020},
	author = {Gokhale, N. A. and Trivedi, N. S. and Mandavgane, S. A. and Kulkarni, B. D.}
}
