Vacuum Oxy-nitro carburizing of tool steels: structure and mechanical reliability

5-18AISI H10, H11, H21, and D2 have been vacuum oxy-nitrocarburizing at 570 °C in cycling gas flow manner. Metastable diagram calculations belonging to Fe-N-C and Fe-N-C-X systems (X = Cr, Mo, W), have been performed by using “phase diagram” module of FactSageto predict the steels’ phase compositions. The reactive diffusion of both N and C into the tempered martensite has been discussed on the base of different chemical composition, size, and distribution of phases in the microstructure. The compound layers consisted mainly of not pre-saturated and poreless ε-carbonitride and magnetite (Fe3O4). In D2 steel, nitrogen diffusion caused a complete transformation of the primary carbides in 50 μm depths from the surface affecting the growth of grain boundary carbides. In contrast to the sharp compound/diffusion layer interface of H10, H11, and D2 steels, in H21 carbon and nitrogen were deeply absorbed in the diffusion layer while chromium strongly increased underneath the surface. The vacuum process enhanced the hardness and decreased the friction coefficients down to 0.13-0.15 at 100 N normal load for all samples. Since the compound layer thickness was relatively small for all tool steels, the phase composition and structure of the diffusion layers were found to be crucial for the scratch wear performance

Vacuum Oxy-nitro carburizing of tool steels: structure and mechanical reliability

AISI H10, H11, H21, and D2 have been vacuum oxy-nitrocarburizing at 570 °C in cycling gas flow manner. Metastable diagram calculations belonging to Fe-N-C and Fe-N-C-X systems (X = Cr, Mo, W), have been performed by using “phase diagram” module of FactSageto predict the steels’ phase compositions. The reactive diffusion of both N and C into the tempered martensite has been discussed on the base of different chemical composition, size, and distribution of phases in the microstructure. The compound layers consisted mainly of not pre-saturated and poreless ε-carbonitride and magnetite (Fe3O4). In D2 steel, nitrogen diffusion caused a complete transformation of the primary carbides in 50 μm depths from the surface affecting the growth of grain boundary carbides. In contrast to the sharp compound/diffusion layer interface of H10, H11, and D2 steels, in H21 carbon and nitrogen were deeply absorbed in the diffusion layer while chromium strongly increased underneath the surface. The vacuum process enhanced the hardness and decreased the friction coefficients down to 0.13-0.15 at 100 N normal load for all samples. Since the compound layer thickness was relatively small for all tool steels, the phase composition and structure of the diffusion layers were found to be crucial for the scratch wear performance

Effect of vacuum oxy-nitrocarburizing on the microstructure of tool steels: an experimental and modeling study

The thermochemical treatments of tool steels improve the performance of the components with respect to surface hardness, wear and tribological performance as well as corrosion resistance. Compared to the conventional gas ferritic nitrocarburizing process, the original vacuum oxy-nitrocarburizing is a time-, cost-effective and environmentally-friendly gas process. Because of the oxidizing nature of the gas atmosphere, there is no need to perform subsequent post-oxidation.In this study, a vacuum oxynitrocarburizing process was carried out onto four tool steels (AISI H10, H11, H21 and D2) at 570 °C, after hardening and single tempering. The structural analysis of the compound and diffusion layers was performed by optical and electron microscopy, X-ray diffraction and glow discharge optical emission spectrometry (GDOES) methods. A largely monophase ε- layer is formed with a carbon accumulation at the substrate adjacent area. The overlaying oxides adjacent to the ε-carbonitride phase contained Fe3O4 (magnetite) as a main constituent. A thermodynamic modelling approach was also performed to understand and optimize the process. The “Equilib module” of FactSage software which uses Gibbs energy minimization method, was used to estimate the possible products during vacuum oxynitrocarburising process

Effect of vacuum oxy-nitrocarburizing on the microstructure of tool steels: an experimental and modeling study

The thermochemical treatments of tool steels improve the performance of the components with respect to surface hardness, wear and tribological performance as well as corrosion resistance. Compared to the conventional gas ferritic nitrocarburizing process, the original vacuum oxy-nitrocarburizing is a time-, cost-effective and environmentally-friendly gas process. Because of the oxidizing nature of the gas atmosphere, there is no need to perform subsequent post-oxidation.In this study, a vacuum oxynitrocarburizing process was carried out onto four tool steels (AISI H10, H11, H21 and D2) at 570 °C, after hardening and single tempering. The structural analysis of the compound and diffusion layers was performed by optical and electron microscopy, X-ray diffraction and glow discharge optical emission spectrometry (GDOES) methods. A largely monophase ε- layer is formed with a carbon accumulation at the substrate adjacent area. The overlaying oxides adjacent to the ε-carbonitride phase contained Fe3O4 (magnetite) as a main constituent. A thermodynamic modelling approach was also performed to understand and optimize the process. The “Equilib module” of FactSage software which uses Gibbs energy minimization method, was used to estimate the possible products during vacuum oxynitrocarburising process

Vacuum oxy-nitro carburizing of tool steels: Structure and mechanical reliability

AISI H10, H11, H21, and D2 have been vacuum oxy-nitrocarburizing at 570 °C in cycling gas flow manner. Metastable diagram calculations belonging to Fe-N-C and Fe-N-C-X systems (X = Cr, Mo, W), have been performed by using “phase diagram” module of FactSageto predict the steels’ phase compositions. The reactive diffusion of both N and C into the tempered martensite has been discussed on the base of different chemical composition, size, and distribution of phases in the microstructure. The compound layers consisted mainly of not pre-saturated and poreless ε-carbonitride and magnetite (Fe3O4). In D2 steel, nitrogen diffusion caused a complete transformation of the primary carbides in 50 μm depths from the surface affecting the growth of grain boundary carbides. In contrast to the sharp compound/diffusion layer interface of H10, H11, and D2 steels, in H21 carbon and nitrogen were deeply absorbed in the diffusion layer while chromium strongly increased underneath the surface. The vacuum process enhanced the hardness and decreased the friction coefficients down to 0.13-0.15 at 100 N normal load for all samples. Since the compound layer thickness was relatively small for all tool steels, the phase composition and structure of the diffusion layers were found to be crucial for the scratch wear performance

Prediction of Refractive Index of Petroleum Fluids by Empirical Correlations and ANN

The refractive index is an important physical property that is used to estimate the structural characteristics, thermodynamic, and transport properties of petroleum fluids, and to determine the onset of asphaltene flocculation. Unfortunately, the refractive index of opaque petroleum fluids cannot be measured unless special experimental techniques or dilution is used. For that reason, empirical correlations, and metaheuristic models were developed to predict the refractive index of petroleum fluids based on density, boiling point, and SARA fraction composition. The capability of these methods to accurately predict refractive index is discussed in this research with the aim of contrasting the empirical correlations with the artificial neural network modelling approach. Three data sets consisting of specific gravity and boiling point of 254 petroleum fractions, individual hydrocarbons, and hetero-compounds (Set 1); specific gravity and molecular weight of 136 crude oils (Set 2); and specific gravity, molecular weight, and SARA composition data of 102 crude oils (Set 3) were used to test eight empirical correlations available in the literature to predict the refractive index. Additionally, three new empirical correlations and three artificial neural network (ANN) models were developed for the three data sets using computer algebra system Maple, NLPSolve with Modified Newton Iterative Method, and Matlab. For Set 1, the most accurate refractive index prediction was achieved by the ANN model, with %AAD of 0.26% followed by the new developed correlation for Set 1 with %AAD of 0.37%. The best literature empirical correlation found for Set 1 was that of Riazi and Daubert (1987), which had %AAD of 0.40%. For Set 2, the best performers were the models of ANN, and the new developed correlation of Set 2 with %AAD of refractive index prediction was 0.21%, and 0.22%, respectively. For Set 3, the ANN model exhibited %AAD of refractive index prediction of 0.156% followed by the newly developed correlation for Set 3 with %AAD of 0.163%, while the empirical correlations of Fan et al. (2002) and Chamkalani (2012) displayed %AAD of 0.584 and 0.552%, respectively

Correlations of HTSD to TBP and Bulk Properties to Saturate Content of a Wide Variety of Crude Oils

Forty-eight crude oils with variations in specific gravity (0.782 ≤ SG ≤ 1.002), sulphur content (0.03 ≤ S ≤ 5.6 wt.%), saturate content (23.5 ≤ Sat. ≤ 92.9 wt.%), asphaltene content (0.1 ≤ As ≤ 22.2 wt.%), and vacuum residue content (1.4 ≤ VR ≤ 60.7 wt.%) were characterized with HTSD, TBP, and SARA analyses. A modified SARA analysis of petroleum that allows for the attainment of a mass balance ≥97 wt.% for light crude oils was proposed, a procedure for the simulation of petroleum TBP curves from HTSD data using nonlinear regression and Riazi’s distribution model was developed, and a new correlation to predict petroleum saturate content from specific gravity and pour point with an average absolute deviation of 2.5 wt.%, maximum absolute deviation of 6.6 wt.%, and bias of 0.01 wt.% was developed. Intercriteria analysis was employed to evaluate the presence of statistically meaningful relations between the different petroleum properties and to evaluate the extent of similarity between the studied petroleum crudes. It was found that the extent of similarity between the crude oils based on HTSD analysis data could be discerned from data on the Kw characterization factor of narrow crude oil fractions. The results from this study showed that contrary to the generally accepted concept of the constant Kw characterization factor, the Kw factors of narrow fractions differ from that of crude oil. Moreover, the distributions of Kw factors of the different crudes were different

Scientific and Practical Conference "Challenges in the Education of Masters of Pharmacy"

Th conference is organised with the fiancial support of European Social Fund within the Project BG051PO001-3.1.07-0046 `Updating and approbation of the curricula of the Faculty of Pharmacy, Medical University of Varna according to the needs of the pharmaceutical business and the requirements of the labor market