ABSTRACT
A thermal neutron absorber material composed of Al3Hf particles in an aluminum matrix is under development for the Advanced Test Reactor. This metal matrix composite was fabricated via hot pressing of high-purity aluminum and micrometer-size Al3Hf powders at volume fractions of 20.0, 28.4, and 36.5%. Room temperature tensile and hardness testing of unirradiated specimens revealed a linear relationship between volume fraction and strength, while the tensile data showed a strong decrease in elongation between the 20 and 36.5% volume fraction materials. Tensile tests conducted at 200 °C on unirradiated material revealed similar trends. Evaluations were then conducted on specimens irradiated at 66 to 75 °C to four dose levels ranging from approximately 1 to 4 dpa. Tensile properties exhibited the typical increase in strength and decrease in ductility with dose that are common for metallic materials irradiated at ≤0.4Tm. Hardness also increased with neutron dose. The difference in strength between the three different volume fraction materials was roughly constant as the dose increased. Nanoindentation measurements of Al3Hf particles in the 28.4 vol% material showed the expected trend of increased hardness with irradiation dose. Transmission electron microscopy revealed oxygen at the interface between the Al3Hf particles and aluminum matrix in the irradiated material. Scanning electron microscopy of the exterior surface of tensile tested specimens revealed that deformation of the material occurs via plastic deformation of the Al matrix, cracking of the Al3Hf particles, and to a lesser extent, tearing of the matrix away from the particles. The fracture surface of an irradiated 28.4 vol% specimen showed failure by brittle fracture in the particles and ductile tearing of the aluminum matrix with no loss of cohesion between the particles and matrix. The coefficient of thermal expansion decreased upon irradiation, with a maximum change of -6.3% for the annealed irradiated 36.5 vol% specimen.
ABSTRACT
Atom probe tomography (APT) is a powerful technique to characterize buried three-dimensional nanostructures in a variety of materials. Accurate characterization of those nanometer-scale clusters and precipitates is of great scientific significance to understand the structure-property relationships and the microstructural evolution. The current widely used cluster analysis method, a variant of the density-based spatial clustering of applications with noise algorithm, can only accurately extract clusters of the same atomic density, neglecting several experimental realities, such as density variations within and between clusters and the nonuniformity of the atomic density in the APT reconstruction itself (e.g., crystallographic poles and other field evaporation artifacts). This clustering method relies heavily on multiple input parameters, but ideal selection of those parameters is challenging and oftentimes ambiguous. In this study, we utilize a well-known cluster analysis algorithm, called ordering points to identify the clustering structures, and an automatic cluster extraction algorithm to analyze clusters of varying atomic density in APT data. This approach requires only one free parameter, and other inputs can be estimated or bounded based on physical parameters, such as the lattice parameter and solute concentration. The effectiveness of this method is demonstrated by application to several small-scale model datasets and a real APT dataset obtained from an oxide-dispersion strengthened ferritic alloy specimen.
ABSTRACT
Dislocation imaging using transmission electron microscopy (TEM) has been an invaluable tool for characterizing crystallographic defects in metals. Compared to conventional TEM imaging, diffraction contrast imaging scanning transmission electron microscopy (DCI STEM) with appropriate setting can provide better defect contrast with almost negligible bend contour artifacts, enabling more effective analysis of dislocation structures. Here, we investigated why STEM can suppresses bend contour, and how dislocation contrast behaves along with different STEM imaging parameters. Using a body-centered cubic HT-9 ferritic/martensitic alloy as an example, a simple procedure and operational theory are described at the beginning to help set up DCI STEM experiments. Comparing with conventional TEM and the STEM strictly complying with the principle of reciprocity, we found that a pair of STEM convergence and collection semi-angles, αS and ßS, a few milliradians in size is essential for bend-contour-free defect imaging. It works in concert such that the convergence STEM probe opens up the reciprocal space, and then a comparable collection region evens out the rocking-curve oscillation and alleviates bend contours from the reciprocal space. This fundamental advantage is unique in DCI STEM. Practical guidelines regarding STEM parameters and specimen orientation and thickness are then provided for DCI STEM dislocation imaging. Lastly, we show that coupling DCI STEM with spectrum images of electron energy loss spectroscopy and of energy-dispersive X-ray Spectroscopy offers a comprehensive characterization of crystallographic defects and chemical information of complex microstructures.
ABSTRACT
Accelerator-based ion beam irradiation techniques have been used to study radiation effects in materials for decades. Although carbon contamination induced by ion beams in target materials is a well-known issue in some material systems, it has not been fully characterized nor quantified for studies in ferritic/martensitic (F/M) steels that are candidate materials for applications such as core structural components in advanced nuclear reactors. It is an especially important issue for this class of material because of the strong effect of carbon level on precipitate formation. In this paper, the ability to quantify carbon contamination using three common techniques, namely time-of-flight secondary ion mass spectroscopy (ToF-SIMS), atom probe tomography (APT), and transmission electron microscopy (TEM) is compared. Their effectiveness and shortcomings in determining carbon contamination are presented and discussed. The corresponding microstructural changes related to carbon contamination in ion irradiated F/M steels are also presented and briefly discussed.
ABSTRACT
Urine is universally recognized as one of the best non-invasive matrices for biomonitoring exposure to a broad range of xenobiotics, including toxic metals. Detection of metal ions in urine has been problematic due to the protein competition and electrode fouling. For direct, simple, and field-deployable monitoring of urinary Pb, electrochemical sensors employing superparamagnetic iron oxide (Fe3O4) nanoparticles with a surface functionalization of dimercaptosuccinic acid (DMSA) has been developed. The metal detection involves rapid collection of dispersed metal-bound nanoparticles from a sample solution at a magnetic or electromagnetic electrode, followed by the stripping voltammetry of the metal in acidic medium. The sensors were evaluated as a function of solution pH, the binding affinity of Pb to DMSA-Fe3O4, the ratio of nanoparticles per sample volume, preconcentration time, and Pb concentrations. The effect of binding competitions between the DMSA-Fe3O4 and urine constituents for Pb on the sensor responses was studied. After 90 s of preconcentration in samples containing 25 vol.% of rat urine and 0.1 g L(-1) of DMSA-Fe3O4, the sensor could detect background level of Pb (0.5 ppb) and yielded linear responses from 0 to 50 ppb of Pb, excellent reproducibility (%RSD of 5.3 for seven measurements of 30 ppb Pb), and Pb concentrations comparable to those measured by ICP-MS. The sensor could also simultaneously detect background levels (<1 ppb) of Cd, Pb, Cu, and Ag in river and seawater.
