Browsing by Author "Jeeru, L.R."

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    Microwave-assisted In-situ catalytic co-pyrolysis of polypropylene and polystyrene mixtures: Response surface methodology analysis using machine learning
    (Elsevier B.V., 2023) Kamireddi, D.; Terapalli, A.; Sridevi, V.; Tukaram Bai, M.T.; Surya, D.V.; Sankar Rao, C.S.; Jeeru, L.R.
    Polypropylene (PP) and Polystyrene (PS) are the major plastic fractions found in mixed plastic waste. Hence, the current study was focused to convert PP and PS into useful products via microwave-assisted pyrolysis (MAP). In addition, the understanding of feedstock conversion, product yields, and energy requirements in pyrolysis, co-pyrolysis, and catalytic co-pyrolysis was investigated. Experiments were conducted at a constant microwave power of 450 W till the reaction temperature reached up to 600 °C. When PS pyrolyzed, a heating rate of 56 °C/min resulted in 80 wt% of oil yield. Whereas PP pyrolysis produced 42 wt% of oil at a heating rate of 76 °C/min. In the PP: PS co-pyrolysis, the heating rate was decreased to 52 °C/min by yielding 51 wt% of oil. In catalytic co-pyrolysis of PP: PS with KOH resulted in variation in product yields and heating rate. An increase in PS quantity at a constant mass of PP resulted in the enhancement of oil yields from 58 to 84 wt% and a decrease in gas yields. The specific microwave power in the catalytic co-pyrolysis (7–18 W/g) is lower compared to the non-catalytic case (22–30 W/g). Whereas, the pyrolysis time in non-catalytic pyrolysis (7–11 min) is lower compared to catalytic co-pyrolysis (14–37 min). The addition of a catalyst resulted in a decrease (23–50%) in microwave conversion efficiency than that of the non-catalytic case (60–85%). The difference in predicted and actual result analysis proved co-pyrolysis synergy in product formation and energy consumption. © 2023 Elsevier B.V.
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    Prosopis juliflora valorization via microwave-assisted pyrolysis: Optimization of reaction parameters using machine learning analysis
    (Elsevier B.V., 2023) Suriapparao, D.V.; Rajasekhar Reddy, B.R.; Sankar Rao, C.S.; Jeeru, L.R.; Kumar, T.H.
    Microwave power and pyrolysis temperature are essential parameters in optimizing the bio-oil yield and quality in microwave pyrolysis. This study focused on understanding the interactions between the microwave power/heating rate and pyrolysis temperature in microwave-assisted pyrolysis of Prosopis juliflora. For optimum bio-oil yield, a discrete set of microwave powers (280 W, 420 W, and 560 W) and pyrolysis temperatures (200 °C, 350 °C, and 500 °C) were selected. A central composite design (CCD) was adopted to analyze the effect of microwave power and the pyrolysis temperature on product yields, heating rate, microwave conversion efficiency, and heat losses in pyrolysis. Moreover, the effect of heating rate, reaction time, specific microwave power, specific microwave energy, and conductive heat loss on gas, char, and liquid yields was evaluated using statistical machine learning techniques. Moreover, a new parameter, pyrolysis index, is calculated under different conditions to understand the extent of pyrolysis intensity using pyrolysis time, heating value, feedstock mass and conversion, and microwave energy conversion. The yields of bio-oil, biochar, and gas were 25–40 wt%, 25–35 wt%, and 35–40 wt% at different experimental conditions. Bio-oil consists of a mix of organic compounds with methoxy phenols at high selectivity, and the calorific value of bio-oil was in the range of 26–28 MJ/kg. Carbon number analysis revealed higher presence of C5–C9 compounds. This study shows the role of machine learning in understanding the effect of various parameters effectively and optimizing the experimental conditions accordingly. © 2022 Elsevier B.V.