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Application of Nanomaterials and Machine Learning to Evaluate Compressive Strength of Oil Well Cement Based on Experimental Data

Year: 2026

Type: article

Source: ACS Applied Engineering Materials

DOI: 10.1021/acsaenm.6c00595

Authors: Edwin E. Nyakilla, Guanhua Sun, Hongliang Hao, Dan Li, Xianyang Yu, Nafouanti Mouigni Baraka, Samwel D. Lupyana, Mtaki T. Maagi, Zahoro A. Athumani, Petro E. Mabeyo, Erasto E. Kasala

Institutions: Chinese Academy of Sciences, Peking University, China University of Geosciences, China University of Geosciences (Beijing), The University of Dodoma, University of Dar es Salaam

Language: English

Topic: Drilling and Well Engineering

Subfield: Ocean Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

Funders: Inner Mongolia Application Technology Research and Development Funding Project, Natural Science Foundation of Hubei Province, Natural Science Foundation of Ningxia Province

Awards: G1065963468, G2915808142, G4885520635

OpenAlex ID: W7208762534

FWCI:

Cites: 62

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