SURFACE ENERGY CHARACTERIZATION OF A SINGLE MICROSPHERE PARTICLE USING PEAKFORCE QUANTITATIVE NANOMECHANICAL MAPPING MODE OF ATOMIC FORCE MICROSCOPE

The composites are typically created by embedding functional fillers in polymeric matrices. The key indicators of reliable performance include homogeneous filler dispersion and optimal interfacial properties between the fillers and matrix. Poor dispersion causes stress concentration, premature failure, and increased filler requirement for achieving functional properties like conductivity. Additionally, interfacial characteristics are governed by surface energy differences and significantly influence the mechanical properties like elongation and rupture stress. Conventional methods for measuring surface energy, such as contact angle or Washburn adsorption, have limitations when applied to microscale powders, including issuers with accurate size handling and bulk material requirements. To overcome these challenges, the PeakForce QNM (quantitative nanomechanical mapping) mode of atomic force microscopy (AFM) was used to measure the surface energy on the surface of the powder microspheres. This method was used to characterize the surface energies of 2–5 μm carbonyl iron powders with various surface coatings. Differences in the surface energies corresponded to variations in the dispersibility and mechanical performances of these powder-based composites. The proposed nanoscale approach provides critical insights into the interfacial mechanisms, enabling enhanced design and optimization of stetchable composites for advanced electronic applications.

Authors

Publication Details

Journal
Facta Universitatis Series Mechanical Engineering
Published
2025-04-11
DOI
https://doi.org/10.22190/fume250114012h
Citations
3
Primary Topic
Force Microscopy Techniques and Applications
Type
article
Field-Weighted Citation Impact
3.74
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SURFACE ENERGY CHARACTERIZATION OF A SINGLE MICROSPHERE PARTICLE USING PEAKFORCE QUANTITATIVE NANOMECHANICAL MAPPING MODE OF ATOMIC FORCE MICROSCOPE

Svetlana Guriyanova, Byungil Hwang, Heebo Ha, Sebastian Mueller
3 citations
Facta Universitatis Series Mechanical Engineering
Force Microscopy Techniques and Applications
3.74
article

SURFACE ENERGY CHARACTERIZATION OF A SINGLE MICROSPHERE PARTICLE USING PEAKFORCE QUANTITATIVE NANOMECHANICAL MAPPING MODE OF ATOMIC FORCE MICROSCOPE

Svetlana Guriyanova, Byungil Hwang, Heebo Ha, Sebastian Mueller
article en
3 citations

Abstract

The composites are typically created by embedding functional fillers in polymeric matrices. The key indicators of reliable performance include homogeneous filler dispersion and optimal interfacial properties between the fillers and matrix. Poor dispersion causes stress concentration, premature failure, and increased filler requirement for achieving functional properties like conductivity. Additionally, interfacial characteristics are governed by surface energy differences and significantly influence the mechanical properties like elongation and rupture stress. Conventional methods for measuring surface energy, such as contact angle or Washburn adsorption, have limitations when applied to microscale powders, including issuers with accurate size handling and bulk material requirements. To overcome these challenges, the PeakForce QNM (quantitative nanomechanical mapping) mode of atomic force microscopy (AFM) was used to measure the surface energy on the surface of the powder microspheres. This method was used to characterize the surface energies of 2–5 μm carbonyl iron powders with various surface coatings. Differences in the surface energies corresponded to variations in the dispersibility and mechanical performances of these powder-based composites. The proposed nanoscale approach provides critical insights into the interfacial mechanisms, enabling enhanced design and optimization of stetchable composites for advanced electronic applications.

Facta Universitatis Series Mechanical Engineering
Openalex Percentile: Top 8%
Force Microscopy Techniques and Applications
3.74
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.