For the first time, neutron tomography was applied for 3D quantitative hydrogen distribution analysis in titanium alloys following thermohydrogen processing.

The optimal SLM conditions of 304L stainless steel were obtained by single factor and orthogonal tests. Results indicated that the optimal hardness (75 HRB) and Relative Density (RD 99.24%) could be obtained when the laser output power was 190 W, the scanning distance was 0.09 mm and the scanning speed was 800 mm/s. The microstructure of fish scales was uniform and compact with a few pores in the optimal sample. The fine particles were randomly distributed near the edge of the molten pool, and some preferred granular columnar crystal structures were formed. Abundant entanglement dislocations were observed between cell structures, forming dislocation clusters. Spherical nano-precipitates, rich in Si, Mn, and O, were also observed near cell structures. The mechanical properties of the specimens were highly anisotropic, and there were obvious necking and ductility at the tensile fracture.

Heat-resistant P91 martensitic steel is used to produce high-temperature steam pipelines in (ultra) critical power plants. However, non-metallic inclusions are inevitably produced in the metallurgical process. The type, composition, morphology, quantities, size and distribution of these inclusions have significant influences on the properties of materials. The present work developed an original position statistical distribution analysis method to characterize non-metallic inclusions in P91 steel based on scanning electron microscopy (SEM) with energy-dispersive spectroscopy (EDS). Two samples from P91 steel pipes fabricated by different processes were examined. The non-metallic inclusions in these samples could be divided into spherical oxides, strand-shaped oxides, spherical sulfides, spherical oxygen–sulfur compounds, strip sulfides and other inclusions. The amount, proportional area, particle sizes, original positions and statistical distribution results of non-metallic inclusions in different processed samples were assessed, and the causes and effects of these inclusions were analyzed. This novel method could provide diversified information on inclusions, which is helpful for the improvement of metallurgical processes and service performance evaluations.