Seznam abstraktů 2026: SEKCE C - OCELI, VLASTNOSTI, VÝROBKY Z OCELÍ, TESTOVÁNÍ

Nanocrystalline stainless steels exhibit limited thermal stability due to their high-volume fraction of grain boundaries, making them susceptible to grain growth at elevated temperatures. Enhancing thermal stability is therefore essential to broaden their potential structural applications. In this study, we present recent investigations from our laboratory on the microstructural stability, phase transformations, and hardness of nanocrystalline 304L stainless steels synthesized via high-energy mechanical alloying with solute and nanoscale ceramic additions. The effect of solute element and ceramic particle additions, as well as sintering temperature, on structural and microstructural evolution were systematically investigated using X-ray diffraction (XRD), focused ion beam (FIB) microscopy, and transmission electron microscopy (TEM). The mechanical behavior was evaluated using hardness measurements and correlated with the corresponding microstructural features. The results demonstrate that high-energy mechanical alloying results in a deformation-induced martensitic transformation, followed by a reverse transformation during sintering. Despite substantial grain growth in nanocrystalline 304L stainless steel at elevated sintering temperatures, the addition of solute elements and ceramic particles significantly improves grain size stability and hardness. This research was supported by TENMAK under Grant No. 2071, and the authors gratefully acknowledge this support.

This study presents the results of fatigue investigations performed on additively manufactured austenitic stainless steel 316L produced using the Laser Powder Bed Fusion (LPBF) technique. Fatigue tests were conducted under axial tension-compression loading for three different stress ratios: R = −1, −0.5, and 0. The primary objective of the research was to evaluate the influence of the stress ratio on fatigue life and to assess the applicability of the Smith-Watson-Topper (SWT) parameter and linear model for Sa-Sm diagram with the use of sensitivity on mean stress factor in describing the fatigue behavior of LPBF-manufactured material.
Based on the experimental results, S-N fatigue curves were constructed for each loading condition, and corresponding analytical equations were determined to describe the relationship between stress amplitude and the number of cycles to failure. From these equations, load levels were calculated for three selected fatigue life ranges and subsequently correlated with the SWT parameter, enabling a comparative analysis of the combined effects of maximum stress and strain amplitude on fatigue damage evolution.
In addition to mechanical testing, fracture surface analyses were carried out using scanning electron microscopy (SEM). The fractographic examination focused on identifying crack initiation sites and dominant fatigue damage mechanisms.
The findings provide valuable insight into the fatigue performance of additively manufactured 316L stainless steel under different mean stress conditions and contribute to a better understanding of fatigue assessment methods for metallic materials produced by additive manufacturing technologies.

The present study develops an integrated multi-scale framework to investigate the microstructural origins of edge cracking in DP980 grade dual-phase (DP) steel during cold rolling. Although DP steels are widely employed in the automotive industry due to their favorable strength-ductility balance, their susceptibility to edge cracking under localized deformation remains insufficiently understood. Conventional bulk tensile properties fail to capture the microstructure-dependent mechanisms of strain localization that lead to premature edge failure. To address this gap, a comprehensive methodology combining advanced microstructural characterization, deep learning-based phase segmentation, nanoindentation-driven phase property extraction, and microstructure-resolved finite element (FE) simulations is proposed. High-resolution SEM images of cold-rolled DP980 steel were analyzed using a novel self-supervised and weakly supervised deep learning framework that integrates DINOv2 feature extraction, automated scribble generation, and multi-stage refinement. This user-independent segmentation pipeline enabled robust and reproducible identification of ferrite and martensite phases across heterogeneous microstructures. Phase-specific mechanical properties were determined via nanoindentation and inverse modeling, providing physically consistent stress-strain curves for ferrite and martensite. These properties were assigned to automatically generate 2D FE meshes constructed directly from segmented microstructures. Plane-strain simulations representative of cold-rolling were performed across 50 statistically distinct microstructural regions to quantify local strain partitioning, stress concentrations, and potential damage-initiation “hotspots.” The results reveal that martensite morphology, connectivity, and spatial distribution critically govern the intensity of strain localization and hotspot formation near edges. Continuous martensite networks and banded structures promote severe strain gradients in constrained ferrite regions, increasing the likelihood of interface decohesion and void nucleation. By coupling deep learning segmentation with micromechanical modeling, the study establishes a predictive platform that links microstructure to edge-cracking susceptibility. This framework provides both mechanistic insight and a scalable computational tool for optimizing DP steel design and rolling process parameters.

The influence of specimen temperature on displacement efficiency was investigated for duplex stainless steel EN 1.4462 using a 20 kHz ultrasonic fatigue testing system. Resonance-controlled tests were conducted over incremental excitation levels defined by the function generator output voltage (VPP), with continuous phase control to maintain stable resonance. Axial displacement amplitude, resonant frequency, phase difference, and specimen temperature were continuously recorded. Displacement efficiency was defined as the ratio of displacement amplitude to excitation level (µm/VPP). During testing, specimen temperature increased from approximately 29 °C to 90-100 °C, depending on excitation level and cooling conditions. Peak temperatures exceeding 100 °C were observed in high-load tests above 1.5 VPP, corresponding to displacement amplitudes above 13 µm. Over this range, a consistent downward shift in resonant frequency of approximately 200-250 Hz (1-1.3%) was measured, indicating temperature-induced reductions in effective dynamic stiffness. Displacement efficiency showed a strong temperature dependence. Under well-cooled conditions, increases in excitation produced substantial displacement gains, while excessive cooling caused resonance instability, whereas at elevated temperatures progressively higher excitation was required to achieve equivalent displacement, indicating diminishing returns due to reduced elastic stiffness and increased dissipation. At fixed excitation levels, displacement amplitudes varied by up to 10% depending on phase, with stable resonance and maximum displacement confined to a narrow phase window of 0-2°. These findings demonstrate that temperature- and phase-dependent effects govern ultrasonic displacement response, underscoring the need for temperature- and phase-aware displacement calibration in ultrasonic VHCF testing of duplex stainless steels.

The purpose of this study is to investigate how the rate of dynamic recrystallization (DRX) during hot-rolling of 2205 duplex stainless steel (DSS) affects mechanical properties. DRX is a restoration mechanism that produces an equiaxed fine-grain microstructure with improved mechanical properties. The DRX process is largely influenced by deformation parameters, such as strain rate, temperature, and strain. Any imbalance in the above-mentioned could lead to incomplete DRX and, subsequently, inconsistent mechanical properties. In this work, a series of single-pass hot compression tests were conducted in a Gleeble 1500 at temperatures and strain rates ranging from 850 °C to 1050 °C and 0.001 to 5/s, respectively. After hot-compression tests, true stress-strain data were extracted to construct flow curves that aid understanding of the flow behaviour of 2205 DSS. The kinetics of DRX were then studied using the Avrami model to calculate the kinetic constants at various deformation parameters. After kinetic modelling, sigmoidal curves were plotted at various deformation parameters to assess how time influences the volume fraction of recrystallized grains. The microstructure was characterised using an optical microscope (OM), a scanning electron microscope (SEM), and micro-Vickers hardness testing. It was observed that high temperatures and low strain rates led to the completion of recrystallisation and the formation of an equiaxed microstructure with high hardness. On the other hand, high temperature and high strain rate appeared to slow DRX kinetics, resulting in an inconsistent microstructure with poor mechanical properties.

This article presents the results of accelerated tests conducted to determine the durability of steel sheets in a salt spray environment. Steel sheets, protected against environmental impacts using various technologies and then cold-formed, were selected for the tests. It was demonstrated that the most important problem to solve to achieve satisfactory corrosion resistance is achieving dimensional stability of the galvanic coating. Sheet samples containing multiple layers, i.e., polymer and galvanic coatings, were characterized by smaller mass changes due to exposure to corrosive conditions. In these cases, corrosion initiation occurred more readily in areas where the thickness of the galvanic coating varied, as observed in the cross-sections of the sheet metal.

We present a software aimed at the steel industry to help with and to improve image-based analysis, including but not limited to quality assessment, of various types of steel. Companies producing and/or processing steel need to ensure their product retains the appropriate structure, typically a phase content and their distribution. A traditional tool for such a task is a Light Optical Microscope (LOM). On one hand, it is cheap and it allows for fast imaging and it is not very sensitive to its surroundings. On the other hand, its resolution is limited and it may not suffice to resolve finer features in some types of modern steels. Scanning Electron Microscope (SEM) is another tool that lifts this limit but it has its downsides, e.g. slower imaging, sensitive to surroundings (vibrations and electromagnetic noise) and more expensive. In order to help metallographers using the traditional LOM tool, we provide a machine learning based image transformation. We have collected a multi-modal dataset of several types of steels and tested various AI methods thus far. The model has been trained to transform a LOM image to a SEM-like image, i.e. it represents a style transfer combined with intelligent up-scaling. With further improvements to the model in progress, we plan to provide it using two methods - a cloud-based service (in preparation) and a on-premise/local standalone application.

Metallographic images mapping metal surfaces, including their chemical composition, were obtained with sizes up to 1 Gpix (2×3 mm2) and a digital pixel size of 75 nm, well below the theoretical limit of the optical microscope. These images are part of a global priority discovery (Large-Area Digital Optical Microscopy - LADOM). A new prototype of functional microscope was also built, integrating all the knowledge gained and addressing all existing technical requirements.
In metallographic practice, large-scale images of 1 mm2 are acquired by combining many individual images. That implies the use of algorithms that compensate for mechanical imprecision, optical non-idealities, and smooth image edges. These processes irreversibly destroy the original information, and a true spectral response of the surface may not be obtained. To a large extent, this objection applies to all images stored by conventional algorithms and to all images of larger areas composed of smaller images, including those from electron microscopy. LADOM does not suffer from this problem.
We demonstrate the use of LADOM in the metallographic practice of steel analysis using various etching procedures.

Long-term operation of nuclear power plants requires reliable monitoring of material degradation while minimizing the amount of material removed from components for the assessment of their current condition, residual lifetime, and structural integrity. Monitoring of changes in key material properties should include all degradation mechanisms occurring during operation, with thermal ageing being one of the main factors affecting these properties. To evaluate the rate of property changes, predict their trends, and assess the period of safe operation, it is essential to determine the initial (reference) properties of materials in their unexposed condition.
This paper describes the evaluation procedure and provides data on the initial properties of the base material of new (non-operated) main circulation piping of the new units of the EMO34 nuclear power plant. The study also presents the application of the Small Punch Test (SPT) as an additional mechanical testing method for monitoring the properties of austenitic main circulation piping material.
The initial properties of the unexposed material were determined using a combination of standard mechanical tests (tensile test and Charpy impact test) and SPT performed on small discs with a diameter of 8 mm and a thickness of 0.5 mm in accordance with EN 10371:2021. The SPT methodology was applied to determine yield strength and ultimate tensile strength from characteristic forces on the load-displacement curve, as well as fracture-related SPT energy calculated as the integral under the curve up to specimen perforation.
The presented dataset demonstrates that SPT can be effectively applied in long-term surveillance programs, particularly in cases where only a limited amount of material is available.

Cr-Mo-V grade steel is widely used in steam turbine rotors due to its fatigue resistance, which results from tempered martensitic microstructure. However, conventional post-machining operations, rotor underwent stress reliving heat treatment. Due to higher stress reliving temperature the microstructure result in ferrite and carbide with low martensite, and inferior mechanical properties, including a yield point phenomenon. To address this, heat treatment optimization was performed between 725-1100°C using Thermo-Calc phase diagram simulations. Peak hardness was achieved at 850°C due to fine austenite grains. Optimized tempering further enhanced mechanical performance, resulting in a 2.5-fold increase in yield strength and suppression of the yield point phenomenon. This improvement is attributed to increased dislocation density from a higher martensite phase fraction, confirmed by X-ray diffraction and EBSD analysis. The study demonstrates that optimized heat treatment can effectively restore and enhance both microstructural and mechanical properties while eliminating undesirable yield point behavior in Cr-Mo-V steel.

This work focuses on the development and characterization of functionally graded materials (FGM) produced by combining the nickel-based superalloy MoNiCr and the austenitic stainless steel 316L using the DED LB/W additive manufacturing technology. The aim was to verify the technological feasibility of multi-material printing of two metallurgically distinct alloys, evaluate the quality of the interface between them, and assess the influence of deposition order and subsequent heat treatment on the resulting microstructure and hardness distribution.
The results show that the deposition order significantly affects the nature of the transition zone. When depositing 316L steel onto the MoNiCr nickel alloy, a wider mixed layer is formed, which is related to differences in melt pool dynamics and thermal gradients. The opposite order—i.e., depositing MoNiCr onto 316L—results in a more sharply defined interface with a lower degree of chemical mixing. Subsequent heat treatment caused significant homogenization of the microstructure associated with recrystallization and led to the equalization of hardness across both materials, thus minimizing local differences created during printing.
The findings confirm that the combination of MoNiCr and 316L is technologically suitable for the DED LB/W process and enables the production of stable functionally graded structures with a controllable transition between materials. These results represent an important step toward the development of components for the energy sector, where localized tuning of material properties can be utilized—for example—for parts exposed to high temperatures and aggressive fluoride salts in Generation IV systems.

In this work, we investigate the structure and basic mechanical properties of a bimetallic system of high industrial relevance, namely high-strength steels clad with stainless steel. The material was produced by explosion welding, a process capable of joining a wide range of similar and dissimilar metals. Bimetals intended for industrial applications are designed to combine the advantages of two dissimilar materials: a base material (high-strength steel) that fulfils the mechanical requirements, and a cladding material (stainless steel) that provides an H₂ barrier and resistance to hydrogen embrittlement. Such bimetallic combinations could be used for pipes and tubular components to safely and efficiently store and transport H₂, particularly in stationary and potentially mobile applications involving high-pressure gaseous hydrogen (300-700 bar).
After cladding, these bimetals should be heat-treated to relieve residual stresses in both materials. The selected heat-treatment modes are evaluated by comparing their microstructural features and basic mechanical properties. Microstructural analysis of both monolithic materials and clad bimetals is performed using light microscopy and scanning electron microscopy, with local EDS analysis. The comparison of the heat-treated specimens is complemented by basic mechanical characterisation, including hardness profiles/maps and mini-tensile tests. Because the final product consists of two different materials, the heat-treatment modes must be selected in a balanced way so that they are suitable for both constituents. Appropriate heat treatments will therefore be applied to achieve mechanical properties compatible with the intended manufacturing processes.

This work investigates texture evolution in austenitic steels exhibiting TRIP/TWIP effects using a combined experimental-simulation approach. In-situ synchrotron X-ray diffraction (SXRD) and neutron diffraction (ND) are used to track phase fractions and orientation changes during deformation in high-manganese, 304, and 316 steels. The focus is on the interplay between FCC γ-austenite, HCP ε-martensite, and BCC α′-martensite. The experimental results are compared with MTEX-based simulations that incorporate deformation twinning and transformation-induced texture components. The study highlights the strengths of combining SXRD and ND for capturing microstructural changes and demonstrates the potential of MTEX simulations to support a deeper understanding of complex texture evolution in multi-phase steels under mechanical loading.

The effect of chemical segregation on the microstructure of isothermally heat-treated nanobainitic steel containing 0.5C-2.0Mn-1.6Si-1.6Cr-0.55Mo (wt%) is investigated using dilatometry, light microscopy, scanning electron microscopy (SEM), and transmission electron microscopy. The characteristic temperatures Ac₁, Ac₃, and MS were determined for the experimental steel and a part of the time-temperature-transformation diagram was developed within the temperature range of 205-255 °C using various cooling rates of dilatometric specimens from the austenitization temperature. The Si, Mo, Cr, and Mn contents in the segregation zones were analyzed using energy-dispersive spectroscopy-SEM. The average difference in MS values between zones depleted and enriched in alloying elements was approximately 25 °C, whereas the maximum observed gap between the highest MS in the depleted zones and lowest MS in the enriched zones reached 90 °C. The relationship between the microstructure and mechanical properties was analyzed, and heat-treatment parameters that limit the negative impact of chemical segregation on the strength-to-plasticity ratio were proposed. A two-stage isothermal heat treatment at temperatures of 235 and 225 ℃ produced a favorable combination of mechanical properties of the investigated steel: tensile strength of 2.0 GPa, yield strength of 1.3 GPa and total tensile elongation of 14%.