Optimizing biochar for carbon sequestration: a synergistic approach using machine learning and natural language processing
Abstract Biochar is a promising technology for carbon storage and greenhouse gas (GHG) reduction, but optimizing it is challenging due to the complexity of natural systems. Machine learning (ML) and natural language processing (NLP) offer solutions through enhanced data analysis and pattern recognit...
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | Biochar |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s42773-024-00424-0 |
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| _version_ | 1832585521517297664 |
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| author | Jiayi Li Yixuan Chen Chaojie Wang Hanbo Chen Yurong Gao Jun Meng Zhongyuan Han Lukas Van Zwieten Yi He Caibin Li Gerard Cornelissen Hailong Wang |
| author_facet | Jiayi Li Yixuan Chen Chaojie Wang Hanbo Chen Yurong Gao Jun Meng Zhongyuan Han Lukas Van Zwieten Yi He Caibin Li Gerard Cornelissen Hailong Wang |
| author_sort | Jiayi Li |
| collection | DOAJ |
| description | Abstract Biochar is a promising technology for carbon storage and greenhouse gas (GHG) reduction, but optimizing it is challenging due to the complexity of natural systems. Machine learning (ML) and natural language processing (NLP) offer solutions through enhanced data analysis and pattern recognition, ushering in a new era of biochar research. Graphical Abstract |
| format | Article |
| id | doaj-art-c0c7831344c3428b8b5e80e349b0a2c6 |
| institution | Kabale University |
| issn | 2524-7867 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Biochar |
| spelling | doaj-art-c0c7831344c3428b8b5e80e349b0a2c62025-01-26T12:46:14ZengSpringerBiochar2524-78672025-01-01711810.1007/s42773-024-00424-0Optimizing biochar for carbon sequestration: a synergistic approach using machine learning and natural language processingJiayi Li0Yixuan Chen1Chaojie Wang2Hanbo Chen3Yurong Gao4Jun Meng5Zhongyuan Han6Lukas Van Zwieten7Yi He8Caibin Li9Gerard Cornelissen10Hailong Wang11Agronomy College, Shenyang Agricultural UniversityAgronomy College, Shenyang Agricultural UniversitySchool of Environment and Chemical Engineering, Foshan UniversityKey Laboratory of Recycling and Eco-Treatment of Waste Biomass of Zhejiang Province, School of Environment and Natural Resources, Zhejiang University of Science & TechnologySchool of Environmental Science and Engineering, Guangzhou UniversityAgronomy College, Shenyang Agricultural UniversitySchool of Electronic Information Engineering, Foshan UniversityNSW Department of Primary Industries, Wollongbar Primary Industries InstituteYancao Production Technology Center, Bijie Yancao Company of Guizhou ProvinceYancao Production Technology Center, Bijie Yancao Company of Guizhou ProvinceNorwegian Geotechnical Institute (NGI)Agronomy College, Shenyang Agricultural UniversityAbstract Biochar is a promising technology for carbon storage and greenhouse gas (GHG) reduction, but optimizing it is challenging due to the complexity of natural systems. Machine learning (ML) and natural language processing (NLP) offer solutions through enhanced data analysis and pattern recognition, ushering in a new era of biochar research. Graphical Abstracthttps://doi.org/10.1007/s42773-024-00424-0Artificial intelligenceBiochar optimizationCarbon storageCarbon neutralityBibliometric analysis |
| spellingShingle | Jiayi Li Yixuan Chen Chaojie Wang Hanbo Chen Yurong Gao Jun Meng Zhongyuan Han Lukas Van Zwieten Yi He Caibin Li Gerard Cornelissen Hailong Wang Optimizing biochar for carbon sequestration: a synergistic approach using machine learning and natural language processing Biochar Artificial intelligence Biochar optimization Carbon storage Carbon neutrality Bibliometric analysis |
| title | Optimizing biochar for carbon sequestration: a synergistic approach using machine learning and natural language processing |
| title_full | Optimizing biochar for carbon sequestration: a synergistic approach using machine learning and natural language processing |
| title_fullStr | Optimizing biochar for carbon sequestration: a synergistic approach using machine learning and natural language processing |
| title_full_unstemmed | Optimizing biochar for carbon sequestration: a synergistic approach using machine learning and natural language processing |
| title_short | Optimizing biochar for carbon sequestration: a synergistic approach using machine learning and natural language processing |
| title_sort | optimizing biochar for carbon sequestration a synergistic approach using machine learning and natural language processing |
| topic | Artificial intelligence Biochar optimization Carbon storage Carbon neutrality Bibliometric analysis |
| url | https://doi.org/10.1007/s42773-024-00424-0 |
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