Hadfield steel (mangalloy, 1.2% C, 13% Mn) is known for its exceptional wear resistance and ability to work-harden under impact loads, yet conventional heat treatment does not increase its hardness. Dynamic alloying in the super-deep penetration (SDP) mode, a process which involves the introduction of high-velocity streams of powder particles into bulk steel, offers a novel approach for the solid-state modification of its properties. The aim of this study was to determine how SDP processing using SiC-based powder mixtures with different metallic additives affects the microstructure and hardness of Hadfield steel.
Cast Hadfield steel samples were dynamically treated with SiC powders (<100 μm) mixed with nickel (Ni) or tin (Sn). The SDP process was performed at an average particle velocity of approximately 3000 m/s, with a penetration depth of up to 100 mm. The microstructure and element distribution were examined using scanning electron microscopy and elemental mapping, while the hardness was measured using Rockwell (HRB) and Brinell (HB) methods before and after processing, as well as following heat treatment.
SDP processing resulted in a deep incorporation of Ni and Sn into the steel matrix and a significant increase in hardness. Compared to the as-cast state (61–62 HRB; 109–112 HB), the SiC+Ni treatment increased hardness to 78–80 HRB (146–149 HB), and the SiC+Sn treatment to 76–77 HRB (143–145 HB), corresponding to improvements of about 29% and 24.5%, respectively. Post-processing heat treatment had minimal effect, confirming that strengthening occurs primarily during dynamic alloying.
These results show that SDP-based dynamic alloying effectively transforms Hadfield steel into a composite-like material with enhanced mechanical performance. The process enables deep, homogeneous alloying in the solid state without melting or quenching, thereby lowering energy consumption and expanding the technological potential of high-manganese steels for wear-resistant components in mining, construction, and heavy machinery.
