K. D. Machado, R. C. da Silva
This study investigates the magnetic properties of three amorphous Co xNb100− x alloys, namely Co 25Nb75, Co 57Nb43, and Co 80Nb20, produced through the Mechanical Alloying technique starting from elemental powders. We utilized an alternating gradient force magnetometer (AGFM) to determine their magnetic characteristics, including remanent magnetizations, saturation fields, and coercive fields derived from hysteresis loops. The results revealed that the alloys exhibited relatively high saturation fields, which decreased as the cobalt content increased. Notably, the coercivity and remanent magnetization reached optimal values at approximately 57% cobalt content, identifying Co57Nb43 as the hardest magnetic material among the studied alloys. However, further addition of cobalt resulted in a softer alloy, specifically Co80Nb20. These findings underline the significance of composition in influencing the magnetic properties of cobalt-niobium amorphous alloys.
@article{5b33737b-5646-4e87-91e4-7115cc39de45,
title={Magnetic properties of amorphous CoxNb100− x alloys produced by mechanical alloying},
author={K. D. Machado and R. C. da Silva},
year={2002},
language={en}
}TY - JOUR TI - Magnetic properties of amorphous CoxNb100− x alloys produced by mechanical alloying AU - K. D. Machado AU - R. C. da Silva PY - 2002 LA - en ER -
Arthur C. Reardon
This publication, edited by Arthur C. Reardon and published by ASM International®, serves as a comprehensive guide in the field of materials science.
Robert A. Francis
This document serves as a comprehensive introduction to the metallurgy of steel and its alloys, focusing on various aspects of iron and steel manufact
Department of Mechanical Engineering, ESEC
This paper discusses the crucial role of the iron-iron carbide diagram in engineering alloys, particularly in the development of important materials s
Blair Burwell
The exhaustion of current vanadium sources and the emergence of new applications are driving the need for innovative methods of extraction. The aim of
Rajesh Jha, Bimal Kumar Jha
This book describes the application of artificial intelligence (AI) and machine learning (ML) concepts to develop predictive models that can be used t