CO dissociation on iron nanoparticles: Size and geometry effects

In search of best automated model: Explaining nanoparticle TEM image segmentation

Over the years, computer scientists are working on building models that aid the scientific community in many ways by cutting laboratory expenses or by saving time. Such models find useful applications in microscopy images as well. Determining the morphology of nanoparticles from Transmission Electron Microscopy images is a manual and cumbersome task. In the past years, scientists have tried to build models to automate the process of nanoparticle segmentation in microscopy images. This study focuses on finding the best segmentation model, which achieves high metrics and is robust to microscopy parameters. For this purpose, eight different models have been compared. The training dataset consists of 150 BF-TEM Platinum nanoparticle images containing 3629 nanoparticles of all kinds. Further, we examine the generalizability of the models on E-TEM Gold nanoparticle images. We also describe essential considerations while choosing a network for segmenting nanoparticle images that generalize well across the Platinum BF-TEM and Gold E-TEM nanoparticles dataset. The layer gradients are visualized to further explain the black-box nature of neural networks.

A theoretical study of adsorption on iron sulfides towards nanoparticle modeling

Surface modification of zero-valent iron (nZVI) nanoparticles, which are frequently used in the removal of chlorinated hydrocarbons from contaminated groundwater, can increase their surface stability without significant loss of reactivity. Sulfidation is a process during which thin iron sulfide phases are formed on nZVI particles. In this work, the adsorption capability of two iron sulfide minerals (mackinawite and pyrite) and ZVI with respect to two small polar molecules (H2O and H2S) and trichloroethylene (TCE) was modeled by using the quantum mechanics (QM) approach. High-level QM methods used on cluster models helped in benchmarking and validation of density functional theory methods used on periodic slab models of the (001) surfaces of iron sulfides and the (111) surface of ZVI. This careful computational treatment was necessary for achieving reliable results because modeled iron containing compounds represent computationally demanding systems. The results showed that adsorption was strongly affected by surface topology, accessibility of surface sites, and the shape of adsorbed molecular species. The mackinawite surface is practically hydrophobic having weak interactions with polar molecules (about -5/-6 kcal mol-1), in contrast to the surfaces of pyrite and ZVI (adsorption energies are about three times larger). On the other hand, the adsorption of weakly polar planar TCE molecule is relatively strong and similar for all three surfaces (in the range of -11 to -17 kcal mol-1). Moreover, it was shown that the dominant component of the adsorption energy of TCE had originated from dispersion interactions, which were less important for small polar molecules.

Automatic segmentation of inorganic nanoparticles in BF TEM micrographs

Transmission electron microscopy (TEM) represents a unique and powerful modality for capturing spatial features of nanoparticles, such as size and shape. However, poor statistics arise as a key obstacle, due to the challenge in accurately and automatically segmenting nanoparticles in TEM micrographs. Towards remedying this deficit, we introduce an automatic particle picking device that is based on the concept of variance hybridized mean local thresholding. Validation of this new segmentation model is accomplished by applying a program written in Matlab to a database of 150 bright field TEM micrographs containing approximately 2,000 nanoparticles. We compare the results to global thresholding, local thresholding, and manual segmentation. It is found that this novel automatic particle picking device reduces false positives and false negatives significantly, while increasing the number of individual particles picked on regions of particle overlap.

Computational exploration of Fe55@C240-catalyzed Fischer–Tropsch synthesis

DFT calculations showed possible hydrocarbon chain growth on Fe55@C240 preferentially via a CO insertion mechanism.