Engineering topics

Long, Min

Publications and source records attributed to Long, Min.

3 records

DOE OSTI2024

Mechanisms of ion irradiation induced ordering in amorphous TiO 2 nanotubes: Effects of ion mass and energy

Here, amorphous TiO 2 nanotubes were irradiated in-situ in a transmission electron microscope (TEM) with Kr + ions at energies of 46 keV, 150 keV, and 1 MeV and with 46 keV Xe + ions, to investigate the structural and morphological evolution of the nanotubes under irradiation. At all irradiation conditions, amorphous TiO 2 nanotubes exhibited significant morphological instability, and tended to undergo volumetric swelling with increasing ion counts, often until collapse of the original nanotube structure. Molecular dynamics (MD) simulations confirmed that irradiation-induced defects can explain the observed swelling. Structurally, nanotubes remain amorphous following all Kr + irradiation conditions, but irradiation with 46 keV Xe + leads to the formation of anatase nanocrystallites. Importantly, through systematically varying ion energy and ion species, we try to elucidate the influence of nuclear and electronic stopping power on ion irradiation induced changes. By contextualizing these results within the existing literature, we propose that the observed changes in TiO 2 nanotube morphology and structure could be due to a competition between two mechanisms: (1) disorder-induced swelling and (2) irradiation-induced amorphous-to-crystalline transformation.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Evaluation of adsorption and mechanical strength of 13X zeolite mixtures with phyllosilicate binders using molecular dynamics simulation and positron annihilation spectroscopy

There is growing interest in developing zeolites with novel internal structures that have optimal adsorptive capacity and high mechanical strength, while offering advantages, such as being light weight. We integrate computational and experimental methods to explore the effect of binder/zeolite types, and weight percentages on the mechanical strength of 13X zeolite and adsorption capacities of N 2 , H 2 O, and CO 2 for additive manufacturing (AM) applications with the goal of maximizing both adsorption and strength. Zeolite 13X mixtures and phyllosilicate binders (either bentonite or kaolin) are combined using molecular dynamics (MD) simulations to create structures with various binder/zeolite weight percentages. Further, adsorption capabilities and mechanical strength are assessed using the grand canonical Monte Carlo (GCMC) and ReaxFF modules, respectively. Our modeling shows that an optimized zeolite/binder ratio for N 2 adsorption is around 15 wt% for kaolin and roughly 10 wt% for bentonite. The resulting parameters can be applied to facilitate macro-scale computational fluid dynamics (CFD) and finite element method (FEM) simulations of an AM zeolite structure. We also performed Positron Annihilation Lifetime Spectroscopy (PALS) measurements on zeolite samples to explore the effect of changes in the internal volume. The results show an inverse relationship between the free volume and the solid loading and adding a binder changes the morphology of the zeolite-binder compound and decreases open-volume area significantly.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Artificial intelligence based analysis of nanoindentation load–displacement data using a genetic algorithm

In this work, we developed an automated tool, Nanoindentation Neo package for the analysis of nanoindentation load–displacement curves using a Genetic Algorithm (GA) applied to the Oliver-Pharr method (Oliver et al.,1992). For some materials, such as polycrystalline isotropic graphites, Least Squares Fitting (LSF) of the unload curve can produce unrealistic fit parameters. These graphites exhibit sharply peaked unloading curves not easily fit using the LSF, which tends to overestimate the indenter tip geometry parameter. To tackle this problem, we extended our general materials characterization tool Neo for EXAFS analysis (Terry et al., 2021) to fit nanoindentation data. Nanoindentation Neo automatically processes and analyzes nanoindentation data with minimal user input while producing meaningful fit parameters. GA, a robust metaheuristic method, begins with a population of temporary solutions using model parameters called chromosomes; from these we evaluate a fitness value for each solution, and select the best solutions to mix with random solutions producing the next generation. A mutation operator then modifies existing solutions by random perturbations, and the optimal solution is selected. We tested the GA method using Silica and Al reference standards. We fit samples of graphite and a high entropy alloy (HEA) consisting of BCC and FCC phases.

42 ENGINEERING↗