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 Hospital plastic waste valorization through microwave-assisted Pyrolysis: Experimental and modeling studies via machine learning(Elsevier Ltd, 2025) Ramesh, R.; Sankar Rao, C.; Surya, D.V.; Kumar, A.The COVID-19 pandemic generated a global upsurge in hospital plastic waste (HPW) as a consequence of the widespread utilization of personal protective equipment (PPE) composed of diverse polymer materials. The constant demand for PPE worldwide led to the accumulation of substantial volumes of high-polymer-based plastic waste. To tackle this challenge, researchers delved into the conversion of HPW into valuable chemicals through a process known as microwave-assisted pyrolysis (MAP). This method entails the transformation of HPW into high-quality char and liquid oil, which can serve as a source of fuel. In this study, our primary focus was to understand how the ratio of HPW (hospital plastic waste) to susceptor weight influenced the yields and characteristics of the resulting products in the context of the MAP process. To facilitate the experimental setup, a Central Composite Design (CCD) was employed. The impact of varying HPW weights and susceptor quantities on the production of value-added products was investigated. The analysis of condensed organic vapor decomposition revealed an increase in liquid yields (73.6 wt %, 76.6 wt %, 80.7 wt %) as the graphite content increased at a constant 30 g HPW. Conversely, gas yield decreased with higher susceptor and HPW quantity. Keeping the graphite constant at 4g, the gas yield declined (32.5 wt %, 30.7 wt %, and 24.7 wt %) as HPW increased. Additionally, gas yield exhibited a drop (32.5 wt % to 18.1 wt %) with an increase in both graphite and HPW. Furthermore, the residual yield decreased (from 1.7 wt % to 1.2 wt %) with a 30 g increase in HPW. In-depth analysis incorporated machine learning techniques to understand the behavior of response variables about susceptor and HPW quantities. The optimization of the MAP process for HPW encompassed various supplementary operational parameters, including susceptor thermal energy, average heating rate, microwave energy, specific microwave power, and product yields. Moreover, the residue generated from the MAP of HPW underwent characterization through X-ray diffraction (XRD), FTIR, and BET analysis. © 2025 Elsevier LtdItem Microwave assisted catalytic co-pyrolysis of banana peels and polypropylene: experimentation and machine learning optimization(Royal Society of Chemistry, 2025) Rajpurohit, N.S.; Sinha, S.; Ramesh, R.; Sankar Rao, C.; Harshini, H.The growing accumulation of agricultural and plastic waste poses serious environmental challenges, necessitating sustainable and efficient valorization strategies. This study investigates the microwave-assisted catalytic co-pyrolysis of banana peels and polypropylene, using graphite as a susceptor and potassium hydroxide as a catalyst. Experiments were conducted by varying biomass and plastic quantities and microwave power levels to study their effects on product yields and thermal performance. The process effectively converted waste materials into valuable products, with oil yield increasing with microwave power and optimized biomass-to-plastic ratios. The rate of mass loss and heating rate were found to significantly influence overall conversion efficiency. A support vector regression (SVR) model was developed to predict yields based on input parameters, achieving a coefficient of determination ranging from 0.81 to 0.99, which demonstrates the reliability of machine learning in capturing complex thermochemical behavior. 3D plots illustrated the nonlinear effects of process variables on yields. Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Diffraction (XRD) analyses of char confirmed functional groups and crystalline phases, suggesting its suitability for applications like adsorbents or catalysts. Brunauer-Emmett-Teller (BET) analysis showed multilayer adsorption, while thermogravimetric analysis (TGA) highlighted distinct thermal degradation patterns of the feedstocks. These results affirm the promise of integrating experiments with ML for efficient waste-to-energy conversion. © 2025 The Royal Society of Chemistry.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