| 1 |
Reaction mechanisms and product patterns of Pteris vittata pyrolysis for cleaner energy
Song YY, Hu JW, Evrendilek F, Buyukada M, Liang GJ, Huang WX, Liu JY
Renewable Energy, 167, 600, 2021 |
| 2 |
Uncertainty and sensitivity analyses of co-combustion/pyrolysis of textile dyeing sludge and incense sticks: Regression and machine-learning models
Wen ST, Buyukada M, Evrendilek F, Liu JY
Renewable Energy, 151, 463, 2020 |
| 3 |
Bioenergy and emission characterizations of catalytic combustion and pyrolysis of litchi peels via TG-FTIR-MS and Py-GC/MS
Liu C, Liu JY, Evrendilek F, Xie WM, Kuo JH, Buyukada M
Renewable Energy, 148, 1074, 2020 |
| 4 |
Characterizing and optimizing (co-) pyrolysis as a function of different feedstocks, atmospheres, blend ratios, and heating rates
Liu JY, Huang LM, Xie WM, Kuo JH, Buyukada M, Evrendilek F
Bioresource Technology, 277, 104, 2019 |
| 5 |
Kinetics, thermodynamics, gas evolution and empirical optimization of (co-) combustion performances of spent mushroom substrate and textile dyeing sludge
Huang JL, Liu JY, Kuo JH, Xie WM, Zhang XC, Chang K, Buyukada M, Evrendilek F
Bioresource Technology, 280, 313, 2019 |
| 6 |
Pyrolytic kinetics, reaction mechanisms and products of waste tea via TG-FTIR and Py-GC/MS
Cai HM, Liu JY, Xie WM, Kuo JH, Buyukada M, Evrendilek F
Energy Conversion and Management, 184, 436, 2019 |
| 7 |
TG-FTIR and Py-GC/MS analyses of pyrolysis behaviors and products of cattle manure in CO2 and N-2 atmospheres: Kinetic, thermodynamic, and machine-learning models
Zhang JH, Liu JY, Evrendilek F, Zhang XC, Buyukada M
Energy Conversion and Management, 195, 346, 2019 |
| 8 |
The mixture of sewage sludge and biomass waste as solid biofuels: Process characteristic and environmental implication
Chen JC, He Y, Liu JY, Liu C, Xie WM, Kuo JH, Zhang XC, Li SP, Liang JL, Sun SY, Buyukada M, Evrendilek F
Renewable Energy, 139, 707, 2019 |
| 9 |
Pyrolysis performance, kinetic, thermodynamic, product and joint optimization analyses of incense sticks in N-2 and CO2 atmospheres
Wen ST, Yan YP, Liu JY, Buyukada M, Evrendilek F
Renewable Energy, 141, 814, 2019 |
| 10 |
Co-combustion thermal conversion characteristics of textile dyeing sludge and pomelo peel using TGA and artificial neural networks
Xie CD, Liu JY, Zhang XC, Xie WM, Sun J, Chang KL, Kuo JH, Xie WH, Liu C, Sun SY, Buyukada M, Evrendilek F
Applied Energy, 212, 786, 2018 |
