Machine Learning of Microscopic Ingredients for Graphene Oxide/Cellulose Interaction

Author(s)

Petry, Romana ; Silvestre, Gustavo H. ; Focassio, Bruno ; de Lima, Felipe Crasto ; Miwa, Roberto H. ; Fazzio, Adalberto

• Document type: Journal article
• Source: Langmuir; v. N/A, p. 7-pg., 2022-01-14.

Abstract

Understanding the role of microscopic attributes in nanocomposites allows one to control and, therefore, accelerate experimental system designs. In this work, we extracted the relevant parameters controlling the graphene oxide binding strength to cellulose by combining first-principles calculations and machine learning algorithms. We were able to classify the systems among two classes with higher and lower binding energies, which are well defined based on the isolated graphene oxide features. Using theoretical X-ray photoelectron spectroscopy analysis, we show the extraction of these relevant features. In addition, we demonstrate the possibility of refined control within a machine learning regression between the binding energy values and the system's characteristics. Our work presents a guiding map to control graphene oxide/cellulose interaction. (AU)

• FAPESP's process: 17/02317-2 - Interfaces in materials: electronic, magnetic, structural and transport properties
• Grantee: Adalberto Fazzio
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 18/25103-0 - Interfaces - functionalized graphenes and organic pollutans: theoretical-experimental approach in environmental nanotechnology
• Grantee: Romana Petry
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• FAPESP's process: 19/04527-0 - Interface between crystalline topological insulators and 2D-trivial materials: defect proximity study
• Grantee: Bruno Focassio
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• FAPESP's process: 19/20857-0 - Two-dimensional materials and topological phases: prediction and control of its properties
• Grantee: Felipe David Crasto de Lima
• Support Opportunities: Scholarships in Brazil - Post-Doctoral