Influence of Silicon Content on Mechanical and Tribological Properties of FeSi Steels

Non-oriented (NO) Fe–Si electrical steels are key materials for magnetic cores of electrical machines, requiring a balance between magnetic and mechanical properties. This study systematically examined the effect of silicon content (1.06 wt%, 2.15 wt%, and 3.09 wt%) on the microstructure, mechanical, and tribological behavior of three produced NO steel grades. Mechanical properties were assessed using tensile tests, microhardness, and nanoindentation, while tribological performance was evaluated under dry reciprocating sliding (ball-on-flat) against a 100Cr6 steel ball at loads of 5 N, 10 N, and 25 N. Increasing silicon content led to larger grain size, higher hardness (227 HV–361 HV) and strength, but lower ductility. Tribological behavior depended on both composition and load. The most stable friction regime occurred at 10 N. The medium-Si steel (N3, 2.15 wt%) exhibited the best performance with a low coefficient of friction (COF ≈ 0.52–0.55); N5 (3.09 wt%) showed a similar COF, while N1 (1.06 wt%) had a slightly higher value. At 25 N, an inverse relationship between hardness and friction appeared: softer N1 had the lowest COF (≈0.68–0.70), whereas harder N3 and N5 reached ≈ 0.74–0.78. Scanning electron microscopy (SEM) observations revealed abrasive wear for N3/N5 and plastic flow (galling) for N1. Overall, an optimal silicon content provides the best compromise between hardness and tribological stability depending on load conditions.

Authors

Institutions

Publication Details

Journal
Crystals
Published
2025-11-22
DOI
https://doi.org/10.3390/cryst15121005
Primary Topic
Magnetic Properties and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Influence of Silicon Content on Mechanical and Tribological Properties of FeSi Steels

Róbert Džunda, Jana Andrejovská, Ivan Petryshynets, Marcela Motýľová
Crystals
Magnetic Properties and Applications
article

Influence of Silicon Content on Mechanical and Tribological Properties of FeSi Steels

Róbert Džunda, Jana Andrejovská, Ivan Petryshynets, Marcela Motýľová
article en

Abstract

Non-oriented (NO) Fe–Si electrical steels are key materials for magnetic cores of electrical machines, requiring a balance between magnetic and mechanical properties. This study systematically examined the effect of silicon content (1.06 wt%, 2.15 wt%, and 3.09 wt%) on the microstructure, mechanical, and tribological behavior of three produced NO steel grades. Mechanical properties were assessed using tensile tests, microhardness, and nanoindentation, while tribological performance was evaluated under dry reciprocating sliding (ball-on-flat) against a 100Cr6 steel ball at loads of 5 N, 10 N, and 25 N. Increasing silicon content led to larger grain size, higher hardness (227 HV–361 HV) and strength, but lower ductility. Tribological behavior depended on both composition and load. The most stable friction regime occurred at 10 N. The medium-Si steel (N3, 2.15 wt%) exhibited the best performance with a low coefficient of friction (COF ≈ 0.52–0.55); N5 (3.09 wt%) showed a similar COF, while N1 (1.06 wt%) had a slightly higher value. At 25 N, an inverse relationship between hardness and friction appeared: softer N1 had the lowest COF (≈0.68–0.70), whereas harder N3 and N5 reached ≈ 0.74–0.78. Scanning electron microscopy (SEM) observations revealed abrasive wear for N3/N5 and plastic flow (galling) for N1. Overall, an optimal silicon content provides the best compromise between hardness and tribological stability depending on load conditions.

CrystalsVol. 15(12)
Technical University of Košice (SK), Slovak Academy of Sciences (SK), Institute of Geotechnics of the Slovak Academy of Sciences (SK)
Openalex Percentile: Top 74%
Magnetic Properties and Applications
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.