Faculty Publications
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Item Role of ZSM5 catalyst and char susceptor on the synthesis of chemicals and hydrocarbons from microwave-assisted in-situ catalytic co-pyrolysis of algae and plastic wastes(Elsevier Ltd, 2022) Suriapparao, D.V.; Tanneru, T.; Rajasekhar Reddy, B.R.; Yerrayya, A.; Bhasuru, B.A.; Pandian, P.; Prakash, S.R.; Sankar Rao, C.; Sridevi, V.; Desinghu, J.The synergetic effect between algae biomass in co-pyrolysis with synthetic plastics (polypropylene (PP), polyethylene (PE), and expanded polystyrene (EPS)) was investigated in this work. Individual feedstock pyrolysis and co-pyrolysis of algae with PP, PE, and EPS were conducted at a constant supply of microwave energy (420 J/s). Pyrolysis char was used as a susceptor in all the experiments. The average heating rate was varied in the range of ∼50–60 °C/min for achieving the final pyrolysis temperature of 600 °C. In catalytic co-pyrolysis, the ZSM-5 catalyst was used for upgrading the physicochemical properties of pyrolysis oil. The use of catalyst promoted the excessive cracking of biomass in co-pyrolysis, leading to higher gas and coke residue comparatively. The viscosity, density, and flash point of oil obtained in catalytic co-pyrolysis were significantly reduced. While the oil obtained from individual pyrolysis of algae is rich in phenolic derivatives, and that of PP, PE has aliphatic hydrocarbons, and EPS has monoaromatic hydrocarbons as major compounds. The synergistic role of plastic and biomass in co-pyrolysis was observed in the formation of products and oil composition. The bio-oil from catalytic co-pyrolysis is composed of aliphatic oxygenates, aliphatic hydrocarbons, cyclic aliphatic hydrocarbons, and phenolics. The chemicals and hydrocarbons present in the oil have a carbon number in the range of C6 to C30. An increase in carbon and hydrogen elemental composition was observed in bio-oil obtained from co-pyrolysis. © 2021 Elsevier LtdItem Effect of dry torrefaction pretreatment of the microwave-assisted catalytic pyrolysis of biomass using the machine learning approach(Elsevier Ltd, 2022) Ramesh, R.; Suriapparao, D.V.; Sankar Rao, C.S.; Sridevi, V.; Kumar, A.This study employs the Leave-One-Out cross-validation approach to build a machine-learning model using polynomial regression to predict pyro product yield through microwave-assisted pyrolysis of sawdust over KOH catalyst and graphite powder a susceptor. The determination of coefficient (R2) validates the developed models. All the developed models achieved a high prediction accuracy with R2 > 0.93, which signifies that the experimental values are in good agreement with the predicted one. The dependence of the catalyst loading and pretreatment temperature on dominating process parameters such as heating rate, pyrolysis temperature, susceptor thermal energy, and pyro products, namely bio-oil, biochar, and biogas, are explored. The yield of biochar is reduced; however, bio-oil and biogas are enhanced as the catalyst loading increased. On the other hand, increasing the temperature of pretreated sawdust decreased bio-oil and biogas yields while increasing biochar yields. Further, microwave conversion efficiency, and susceptor thermal energy increased with increased catalyst quantity and pretreatment temperatures of sawdust. It was observed that the average heating rate was increased by increasing the catalyst quantity while maintaining the same pyrolysis time until pretreatment temperatures of 150 °C were reached, after which the heating rate dropped due to the continuous microwave energy input to the system. © 2022 Elsevier LtdItem Synergistic effects and product yields in microwave-assisted in-situ co-pyrolysis of rice straw and paraffin wax(Institution of Chemical Engineers, 2024) Hamzah, H.T.; Sridevi, V.; Surya, D.V.; Ramesh, P.; Sankar Rao, C.; Palla, S.; Abdullah, T.A.Microwave-assisted pyrolysis is one of the most efficient methods for solid waste management. This study employed microwave-assisted catalytic co-pyrolysis to convert Paraffin wax (PW) and rice straw (RS) into valuable char, gas, and oil products. KOH and graphite were used as the catalyst and susceptor, respectively. The RS and PW blend served as the feedstock (with a blend ratio of 0–10 g). The yields of co-pyrolysis at different blending ratios of RS: PW exhibited variations in char content (ranging from 9.8% to 22.6% by wt.), oil production (ranging from 34.1% to 76.9% by wt.), and gas formation (ranging from 13.2% to 47.5% by wt.). The effects of the RS: PW ratio on the average heating rate, feedstock conversion, and product yields were also investigated. Analyses were performed to assess the synergistic impacts on product yields, average heating rates, and conversion factors. Notably, co-pyrolysis synergy led to increased oil and char production. Furthermore, we conducted FTIR analysis on the oil and char produced through the catalytic co-pyrolysis of RS: PW. In conjunction with co-pyrolysis synergy, the catalyst facilitated the formation of amides, alkenes, aliphatic compounds, and aromatic compounds. © 2023 The Institution of Chemical EngineersItem Effect of solvent pre-treatment on microwave assisted pyrolysis of Spirulina (Algal Biomass) and Ficus benghalensis (Lignocellulosic Biomass) for production of biofuels: comparative experimental studies(Springer Science and Business Media Deutschland GmbH, 2025) Varma, J.V.; Sridevi, V.; Musalaiah, M.; King, P.; Hamzah, H.T.; Tanneru, H.K.; Ramesh, R.; Malleswari, G.B.The study focuses on the comparison of microwave-assisted pyrolysis (MAP) of Spirulina, (algal biomass), and aerial roots of Ficus benghalensis (lignocellulosic biomass) as feedstocks for biofuel production. Solvent ethanol was used to pretreat feedstocks. The experiments were carried out using a microwave power of 450 W, considering both fresh and solvent-pretreated feedstocks. Solvent-pretreated Spirulina demonstrated a high bio-oil yield of 56.1 wt. % and a biochar yield of 13.5 wt. %, whereas for solvent-pretreated Ficus benghalensis, the corresponding yields were 35.4 wt. % and 12.3 wt.%. Both solvent-treated and fresh algal biomass feedstocks showed higher yields than lignocellulose biomass. Pre-treatment of feedstocks showed positive results on microwave energy consumption and pyrolysis index. The average heating values were 27.3 0C/min for pretreated Spirulina and 46.2 0C/min for pretreated Ficus benghalensis. Fourier Transform Infrared (FTIR) characterized the obtained bio-oils and biochar. The FTIR results indicated the presence of distinctive functional groups such as N=C=O, O=C=O, N-O, and S=O in MAP of Spirulina bio-oil, and C=C and C-I stretching in MAP of Ficus benghalensis bio-oil. The FTIR results for biochar were consistent across both feedstocks, showing common functional groups such as C-Cl, C=C, C-H, O-H, C-F, and S=O. However, in the case of Spirulina, an extra functional group, C=N, was also detected. Pre-treatment of microalgal biomass is essential for the maximal recovery of biofuel precursors packed inside the complex microalgal cell wall. It was concluded that pre-treatment is an efficient way to improve the yield and composition of bio-oil with low microwave power and short microwave irradiation time. Efforts are still required to develop an economical and environmentally benign pre-treatment approach to facilitate 100% biomass conversion to added-value products. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.Item Predicting synergistic effects on biofuel production from microalgae (Spirulina)/Tire Co-pyrolysis using ensemble machine learning(Elsevier B.V., 2025) Sridevi, V.; Al-Asadi, M.; Adnan Abdullah, T.; Nhat, T.; Sankar Rao, C.; Talib Hamzah, H.; Le, P.-C.This study investigates the synergistic effects of microwave-assisted catalytic co-pyrolysis (MACCP) of microalgae and waste tires (WT) under varying parameters such as catalyst weight, microwave power, and susceptor quantity. Optimal reaction conditions yielded a high-quality bio-oil with a maximum yield of 50.46 wt% with low water content, significantly reducing microwave energy consumption from 810 to 540 kJ. The co-pyrolysis of WT and microalgae enhanced denitrogenation and deoxygenation, improving the quality of the resulting bio-oil. Gas chromatography-mass spectrometry (GC-MS) analysis of bio-oil identified an increase in the complex composition of mono- and polyaromatic hydrocarbons and a decrease in oxygenated compounds. An ensemble machine learning approach has been employed to model and predict outcomes, achieving R2 values between 0.7 and 0.98. The models with the best predicted accuracy were Extreme Gradient Boosting (XGB) and Extra Trees (ET), both of which achieved an R2 of 0.98. The models were rigorously validated using the Leave-One-Out Cross-Validation technique, ensuring robust predictions with minimal bias by training on all but one observation iteratively and testing on the excluded data point. The work highlights the possible use of co-pyrolyzing microalgae and WT for sustainable, high-quality bio-oil production with lower energy consumption. It shows that machine learning can optimize MACCP procedures. © 2025 The Energy Institute