Engineering topics

Devaraj, Arun

Publications and source records attributed to Devaraj, Arun.

94 records · Page 6

DOE OSTI2020

New frontiers in atom probe tomography: a review of research enabled by cryo and/or vacuum transfer systems

There has been a recent surge in the use of cryo and/or vacuum specimen preparation and transfer systems that are broadening the scope of research enabled by the microscopy technique of atom probe tomography. This is driven by the fact that, like for many microscopes, the application of atom probe to air and temperature sensitive materials or wet biological specimens has previously been limited by through-air-transfer and through-vacuum-transfer at room temperature. Here we provide an overview of the critical areas of research that require these new transfer and analysis protocols, as well as a review of current advances in transfer devices, environmental cells and glove boxes for controlled sample manipulation. This includes the study of catalysis and corrosion, the application of atom probe to biological samples, the study of liquid-solid interfaces, natural ageing investigations and the analysis of hydrogen in metals.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Precipitation-site competition in duplex stainless steels: Cu clusters vs spinodal decomposition interfaces as nucleation sites during thermal aging

Competing microstructural evolution mechanisms can exist simultaneously when duplex stainless steels are operating for several decades in a high temperature service environment. Such competition between different microstructural evolution pathways can be difficult to ascertain using simple model alloy systems necessitating detailed structural and compositional analysis of phase transformation mechanisms in complex alloys Thus, in this study duplex stainless steels with complex but well understood chemistries were used to investigate the relative importance of different heterogeneous nucleation sites – specifically spinodal decomposition and Cu clustering – on precipitation of Ni-Si-Mn particles during long term thermal aging. Precipitation of Ni-Si-Mn particles in duplex stainless steels and ferritic steels during thermal aging and irradiation is known to have profound effect on mechanical properties. Using duplex stainless steels with custom modified compositions along with atom probe tomography characterization and first-passage kinetic Monte Carlo (FPKMC) simulations it is revealed that while the interface between Cr and Fe formed during spinodal decomposition can be a pathway for diffusion of Ni, Si, Mn, and Cu, it is not a site that encourages precipitation of Ni-Si-Mn rich particles. Instead, the presence of a higher concentration of Cu in these steels leads to formation of small Cu clusters with high energy interfaces that act as nucleation sites for Ni-Si-Mn particles because of its strong interaction particularly with Ni increasing the chemical driving force for precipitation. These results will help inform predictive models for the use of duplex stainless steels and other precipitation-hardened alloys for extended operation at high temperatures.

Duplex stainless steel, Thermal aging, Precipitati↗

DOE OSTI2020

An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction

Micrograph quantification is an essential component of several materials science studies. Machine learning methods, in particular convolutional neural networks, have previously demonstrated performance in image recognition tasks across several disciplines (e.g. materials science, medical imaging, facial recognition). Here, we apply these well-established methods to develop an approach to microstructure quantification for kinetic modeling of a discontinuous precipitation reaction in a case study on the uranium-molybdenum system. Prediction of material processing history based on image data (classification), calculation of area fraction of phases present in the micrographs (segmentation), and kinetic modeling from segmentation results were performed. Results indicate that convolutional neural networks represent microstructure image data well, and segmentation using the k-means clustering algorithm yields results that agree well with manually annotated images. Classification accuracies of original and segmented images are both 94% for a 5-class classification problem. Kinetic modeling results agree well with previously reported data using manual thresholding. The image quantification and kinetic modeling approach developed and presented here aims to reduce researcher bias introduced into the characterization process, and allows for leveraging information in limited image data sets.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A Mechanistic Understanding of Nonclassical Crystal Growth in Hydrothermally Synthesized Sodium Yttrium Fluoride Nanowires

Sodium yttrium fluoride (NaYF 4 ) is an important upconverting material with many potential uses in chemistry, materials science, and biology, which can be synthesized hydrothermally in both cubic (α) and hexagonal (β) crystallographic polymorphs. Understanding the mechanisms underlying the phase conversion between the cubic and hexagonal polymorphs is of great interest to help inform future synthetic efforts, for example in the design of atomically precise quantum materials with well-defined sizes and morphologies. In this work, we use a combination of analytical transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM), powder X-ray diffraction (XRD), in situ liquid cell TEM, atom probe tomography (APT), and extended X-ray absorption fine structure (EXAFS) measurements to show that the hexagonal NaYF 4 nanowires form through a nonclassical crystal growth mechanism involving the formation and subsequent oriented attachment of mesocrystals consisting of cubic (α) phase units. Additionally, EXAFS measurements suggest that substitutional Yb 3+ point defects within NaYF 4 are distributed evenly throughout the crystal lattice without clustering and also that they may exhibit selective substitution into one of the two possible trivalent yttrium sites in the unit cell for hydrothermally synthesized β-NaYF 4 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗