Nanoindentation in Materials: Fundamentals and Applications
A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Advanced Nanomaterials and Nanotechnology".
Deadline for manuscript submissions: 20 July 2025 | Viewed by 2480
Special Issue Editors
Interests: constitutive parameters acquisition from indentation; dynamic indentation test characterization; nanoindentation deformation mechanism and multi-scale simulation; indentation inversion; machine learning
Interests: nanoindentation in characterization of polymer properties; viscoelastic analysis using indentation; creep properties through indentation; nanoindentation deformation mechanism; crystal plasticity finite element method
Interests: nanoindentation deformation mechanism; high temperature nanoindentation; mechanical testing using nanoindentation; indentation; scratch testing technique
Special Issue Information
Dear Colleagues,
Nanoindentation has been widely utilized for the in situ assessment of material properties. With the rapid development of the fields of micro-nano manufacturing and MEMS, nanoindentation tests combined with related theoretical analyses, multi-scale simulations, and machine learning, etc., will show broad application prospects in the characterization the of mechanical parameters and deformation mechanism of various functional materials. Researchers from the fields of mechanics, materials, and physics, etc., are expected and welcome to contribute to this Special Issue. Related topics of interest include, but are not limited to, the following:
- Mechanical parameters acquisition from indentation;
- Indentation scale effect and strain gradient theory;
- Nanoindentation deformation mechanism and multi-scale simulation;
- Dynamic indentation test device and characterization methods;
- Data-driven indentation characterization and analysis;
- Nanoindentation characterization method dependent on material type.
Dr. Gesheng Xiao
Dr. Erqiang Liu
Dr. Xiaochao Jin
Guest Editors
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Keywords
- nanoindentation
- deformation mechanism
- mechanical parameters
- multi-scale simulation
- indentation scale effect
- machine learning
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