Gulnur Kanzhigit

Dr. Gulnur Kanzhigit

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Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 August 2026 in Metals
Verified
Journal Article
Open access
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KFKapsalamova Farida
Kapsalamova Farida
АААлия Алимжанова
Алия Алимжанова
ARAkmaral Rakhym
Akmaral Rakhym
GKGulnur Kanzhigit
Gulnur Kanzhigit
RBRenat Beissenov
Renat Beissenov
A combined CALPHAD-guided thermodynamic and experimental approach was employed to investigate the influence of boron on phase evolution and microstructural development in the Fe–Ni–Cr–Cu–Si–B–C alloy system. Thermodynamic calculations were performed using Thermo-Calc (FE13-2025b) and the TTFe thermodynamic database. Vertical phase-diagram sections and response surface analysis were used to evaluate phase stability over the temperature range of 400–1500 °C and to identify temperature–composition domains favorable for the formation of strengthening phases. The calculations predicted complex multiphase equilibrium behavior involving boride-, carbide-, and silicide-containing phases. Within the investigated composition range, approximately 4 wt.% B provided a favorable balance between the metallic matrix and strengthening phases, while 638 °C corresponded to a thermodynamically favorable equilibrium phase constitution. Response surface analysis further demonstrated that temperature governs phase evolution, whereas boron primarily controls phase redistribution. The optimized alloy composition was characterized experimentally using scanning electron microscopy (SEM), wavelength dispersion spectroscopy (WDS), elemental mapping, and X-ray diffraction (XRD). The experimentally observed heterogeneous multiphase microstructure showed good agreement with the CALPHAD-predicted phase evolution at a qualitative level, demonstrating the usefulness of thermodynamic modeling for guiding alloy design. The proposed CALPHAD-guided workflow integrates thermodynamic modeling with targeted experimental characterization and provides a transferable framework for the accelerated design and optimization of complex Fe-based multicomponent alloys.