Development of predictive model for biochar surface properties based on biomass attributes and pyrolysis conditions using rough set machine learning
Tài liệu tham khảo
Minx, 2018, Negative emissions—Part 1: research landscape and synthesis, Environ. Res. Lett., 13, 10.1088/1748-9326/aabf9b
Woolf, 2010, Sustainable biochar to mitigate global climate change, Nat. Commun., 1, 56, 10.1038/ncomms1053
Joseph, 2021, How biochar works, and when it doesn't: a review of mechanisms controlling soil and plant responses to biochar, Global change biology. Bioenergy, 13, 1731, 10.1111/gcbb.12885
Roberts, 2010, Life cycle assessment of biochar systems: estimating the energetic, economic, and climate change potential, Environ. Sci. Technol., 44, 827, 10.1021/es902266r
Kuppusamy, 2016, Agronomic and remedial benefits and risks of applying biochar to soil: current knowledge and future research directions, Environ. Int., 87, 1, 10.1016/j.envint.2015.10.018
Belmonte, 2017, Biochar systems in the water-energy-food nexus: the emerging role of process systems engineering, Current Opinion Chem. Eng., 18, 32, 10.1016/j.coche.2017.08.005
Bartoli, 2020, A review of non-soil biochar applications, Materials, 13, 261, 10.3390/ma13020261
Yaashikaa, 2020, A critical review on the biochar production techniques, characterization, stability and applications for circular bioeconomy, Biotec. Rep., 28
Lehmann, 2015
Zaman, 2017
Abnisa, 2014, A review on co-pyrolysis of biomass: an optional technique to obtain a high-grade pyrolysis oil, Energy Convers. Manag., 87, 71, 10.1016/j.enconman.2014.07.007
Zhang, 2022, Activation-free synthesis of nitrogen-doped biochar for enhanced adsorption of CO2, J. Clean. Prod.
Awasthi, 2022, Engineered biochar: a multifunctional material for energy and environment, Environ. Pollut., 298, 10.1016/j.envpol.2022.118831
Medeiros, 2022, Pristine and engineered biochar for the removal of contaminants co-existing in several types of industrial wastewaters: a critical review, Sci. Total Environ., 809, 10.1016/j.scitotenv.2021.151120
Xie, 2015, Characteristics and applications of biochar for environmental remediation: a review, Crit. Rev. Environ. Sci. Technol., 45, 939, 10.1080/10643389.2014.924180
Nanda, 2016, Biochar as an exceptional bioresource for energy, agronomy, carbon sequestration, activated carbon and specialty materials, Waste and Biomass Valorization, 7, 201, 10.1007/s12649-015-9459-z
You, 2017, A critical review on sustainable biochar system through gasification: energy and environmental applications, Bioresour. Technol., 246, 242, 10.1016/j.biortech.2017.06.177
Xu, 2016, Chemical transformation of CO2 during its capture by waste biomass derived biochars, Environ. Pollut., 213, 533, 10.1016/j.envpol.2016.03.013
Mukherjee, 2013, Biochar impacts on soil physical properties and greenhouse gas emissions, Agronomy, 3, 313, 10.3390/agronomy3020313
Cely, 2014, Factors driving the carbon mineralization priming effect in a sandy loam soil amended with different types of biochar, Solid Earth, 5, 585, 10.5194/se-5-585-2014
Cheng, 2020, Slow pyrolysis as a platform for negative emissions technology: an integration of machine learning models, life cycle assessment, and economic analysis, Energy Convers. Manag., 223
Pathy, 2020, Predicting algal biochar yield using eXtreme Gradient Boosting (XGB) algorithm of machine learning methods, Algal Res., 50
Radin, 2019, Why are we using black box models in ai when we don't need to? A lesson from an explainable ai competition, Harvard Data Sci. Rev., 1
Rudin, 2019, Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead, Nat. Mach. Intell., 1, 206, 10.1038/s42256-019-0048-x
Lundberg, 2017
Calegari, 2020, On the integration of symbolic and sub-symbolic techniques for XAI: a survey, Intell. Artif., 14, 1
Pawlak, 1982, Rough sets, Int. J. Comput. Inf. Sci., 11, 341, 10.1007/BF01001956
Aviso, 2019, Prediction of CO2 storage site integrity with rough set-based machine learning, Clean Technol. Environ. Policy, 21, 1655, 10.1007/s10098-019-01732-x
Aviso, 2021, Detecting patterns in energy use and greenhouse gas emissions of cities using machine learning, Chem. engi. trans., 88, 403
Albuquerque, 2021, Large-scale prediction of tropical stream water quality using Rough Sets Theory, Ecol. Inf., 61, 10.1016/j.ecoinf.2021.101226
Zhao, 2019, Prediction of service life of large centrifugal compressor remanufactured impeller based on clustering rough set and fuzzy Bandelet neural network, Appl. Soft Comput., 78, 132, 10.1016/j.asoc.2019.02.018
Akbari, 2018, Building a rough sets-based prediction model for classifying large-scale construction projects based on sustainable success index, Eng. Construct. Architect. Manag., 25, 534, 10.1108/ECAM-05-2016-0110
Tomczyk, 2020, Biochar physicochemical properties: pyrolysis temperature and feedstock kind effects, Rev. Environ. Sci. Biotechnol., 19, 191, 10.1007/s11157-020-09523-3
Zhang, 2013, Critical role of small micropores in high CO2 uptake, Phys. Chem. Chem. Phys., 15, 2523, 10.1039/c2cp44436d
Wen, 2021, Pore Structure Characteristics and Evolution Law of Different-Rank Coal Samples, 10.1155/2021/1505306
Pawlak, 2002, Rough sets, decision algorithms and Bayes' theorem, Eur. J. Oper. Res., 136, 181, 10.1016/S0377-2217(01)00029-7
Pawlak, 1997, Rough set approach to knowledge-based decision support, Eur. J. Oper. Res., 99, 48, 10.1016/S0377-2217(96)00382-7
Jia, 2016, Generalized attribute reduct in rough set theory, Knowl. Base Syst., 91, 204, 10.1016/j.knosys.2015.05.017
Gai, 2014, Effects of feedstock and pyrolysis temperature on biochar adsorption of ammonium and nitrate, PLoS One, 9, e113888, 10.1371/journal.pone.0113888
Li, 2023, Machine learning assisted predicting and engineering specific surface area and total pore volume of biochar, Bioresour. Technol., 369, 10.1016/j.biortech.2022.128417
Chen, 2008, Transitional adsorption and partition of nonpolar and polar aromatic contaminants by biochars of pine needles with different pyrolytic temperatures, Environ. Sci. Technol., 42, 5137, 10.1021/es8002684
Zhao, 2017, Effect of temperature on the structural and physicochemical properties of biochar with apple tree branches as feedstock material, Energies, 10, 1293, 10.3390/en10091293
Rafiq, 2016, Influence of pyrolysis temperature on physico-chemical properties of corn stover (Zea mays L.) biochar and feasibility for carbon capture and energy balance’, PLOS ONE, J. Zheng, 11, e0156894
Zhao, 2018, Effect of pyrolysis temperature, heating rate, and residence time on rapeseed stem derived biochar, J. Clean. Prod., 174, 977, 10.1016/j.jclepro.2017.11.013
Tripathi, 2016, Effect of process parameters on production of biochar from biomass waste through pyrolysis: a review, Renew. Sustain. Energy Rev., 55, 467, 10.1016/j.rser.2015.10.122
Leng, 2021, An overview on engineering the surface area and porosity of biochar, Sci. Total Environ., 763, 10.1016/j.scitotenv.2020.144204
Ghodake, 2021, Review on biomass feedstocks, pyrolysis mechanism and physicochemical properties of biochar: State-of-the-art framework to speed up vision of circular bioeconomy, J. Clean. Prod., Volume 297, 10.1016/j.jclepro.2021.126645
Sun, 2017, Characterization of 60 types of Chinese biomass waste and resultant biochars in terms of their candidacy for soil application, Global change biology. Bioenergy, 9, 1423, 10.1111/gcbb.12435
Leng, 2022, Machine learning predicting and engineering the yield, N content, and specific surface area of biochar derived from pyrolysis of biomass, Biochar, 4, 63, 10.1007/s42773-022-00183-w
Tag, 2016, Effects of feedstock type and pyrolysis temperature on potential applications of biochar, J. Anal. Appl. Pyrol., 120, 200, 10.1016/j.jaap.2016.05.006
Wang, 2015, Physicochemical and sorptive properties of biochars derived from woody and herbaceous biomass, Chemosphere, 134, 257, 10.1016/j.chemosphere.2015.04.062
Pacioni, 2016, Bio-syngas production from agro-industrial biomass residues by steam gasification, Waste Manag., 58, 221, 10.1016/j.wasman.2016.08.021
Chow, 2018, Sludge as a relinquishing catalyst in Co-pyrolysis with palm empty fruit bunch fiber, J. Anal. Appl. Pyrol., 132, 56, 10.1016/j.jaap.2018.03.015
Vasu, 2020, Insight into Co-pyrolysis of palm kernel shell (PKS) with palm oil sludge (POS): effect on bio-oil yield and properties, Waste and Biomass Valorization, 11, 5877, 10.1007/s12649-019-00852-1