Insights on finite size effects in Ab-initio study of CO adsorption and dissociation on Fe 110 surface

Adsorption and dissociation of hydrocarbons on metallic surfaces represent crucial steps to carburization of metal. Here, we use density functional theory total energy calculations with the climbing-image nudged elastic band method to estimate the adsorption energies and dissociation barriers for different CO coverages with surface supercells of different sizes. For the absorption of CO, the contribution from van der Waals interaction in the computation of adsorption parameters is found important in small systems with high CO-coverages. The dissociation process involves carbon insertion into the Fe surface causing a lattice deformation that requires a larger surface system for unrestricted relaxation. We show that, in larger surface systems associated with dilute CO-coverages, the dissociation barrier is significantly decreased. The elastic deformation of the surface is generic and can potentially applicable for all similar metal-hydrocarbon reactions and therefore a dilute coverage is necessary for the simulation of these reactions as isolated processes.Comment: 12 pages, 6 figures. Submitted to Journal of Applied Physic

Pressure effect on diffusion of carbon at the 85.91◦ 100 symmetric tilt grain boundary of α-iron

The diffusion mechanism of carbon in iron plays a vital role in carburization processes, steel fabrication, and metal dusting corrosion. In this paper, using the kinetic activation-relaxation technique (k-ART), an off-lattice kinetic Monte Carlo algorithm with on-the-fly catalog building that allows to obtain diffusion properties over large time scales taking full account of chemical and elastic effects coupled with an EAM potential, we investigate the effect of pressure on the diffusion properties of carbon in 85 . 91 ∘ ⟨ 100 ⟩ symmetric tilt grain boundaries (GB) of α -iron up to a pressure of 12 kbar at a single temperature of 600 K. We find that, while the effect of pressure can strongly modify the C stability and diffusivity in the GB in ways that depend closely on the local environment and the nature of the deformation, isotropic and uniaxial pressure can lead to opposite and nonmonotonous effects regarding segregation energy and activation barriers. These observations are relevant to understanding of the evolution of heterogeneous materials, where variations of local pressure can alter the carbon diffusion across the material

Carbon adsorption on and diffusion through the Fe(110) surface and in bulk: Developing a new strategy for the use of empirical potentials in complex material set-ups

Oil and gas infrastructures are submitted to extreme conditions and off-shore rigs and petrochemical installations require expensive high-quality materials to limit damaging failures. Yet, due to a lack of microscopic understanding, most of these materials are developed and selected based on empirical evidence leading to over-qualified infrastructures. Computational efforts are necessary, therefore, to identify the link between atomistic and macroscopic scales and support the development of better targeted materials for this and other energy industry. As a first step towards understanding carburization and metal dusting, we assess the capabilities of an embedded atom method (EAM) empirical force field as well as those of a ReaxFF force field using two different parameter sets to describe carbon diffusion at the surface of Fe, comparing the adsorption and diffusion of carbon into the 110 surface and in bulk of a-iron with equivalent results produced by density functional theory (DFT). The EAM potential has been previously used successfully for bulk Fe-C systems. Our study indicates that preference for C adsorption site, the surface to subsurface diffusion of C atoms and their migration paths over the 110 surface are in good agreement with DFT. The ReaxFF potential is more suited for simulating the hydrocarbon reaction at the surface while the subsequent diffusion to subsurface and bulk is better captured with the EAM potential. This result opens the door to a new approach for using empirical potentials in the study of complex material set-up

Inductive Transfer and Deep Neural Network Learning-Based Cross-Model Method for Short-Term Load Forecasting in Smarts Grids

In a real-world scenario of load forecasting, it is crucial to determine the energy consumption in electrical networks. The energy consumption data exhibit high variability between historical data and newly arriving data streams. To keep the forecasting models updated with the current trends, it is important to fine-tune the models in a timely manner. This article proposes a reliable inductive transfer learning (ITL) method, to use the knowledge from existing deep learning (DL) load forecasting models, to innovatively develop highly accurate ITL models at a large number of other distribution nodes reducing model training time. The outlier-insensitive clustering-based technique is adopted to group similar distribution nodes into clusters. ITL is considered in the setting of homogeneous inductive transfer. To solve overfitting that exists with ITL, a novel weight regularized optimization approach is implemented. The proposed novel cross-model methodology is evaluated on a real-world case study of 1000 distribution nodes of an electrical grid for one-day ahead hourly forecasting. Experimental results demonstrate that overfitting and negative learning in ITL can be avoided by the dissociated weight regularization (DWR) optimizer and that the proposed methodology delivers a reduction in training time by almost 85.6% and has no noticeable accuracy losses.Peer reviewe

Insights on the effect of water content in carburizing gas mixtures on the metal dusting corrosion of iron

Constituents of syngas, such as water, carbon monoxide and sulfides, can cause the degradation of the steel pipes they move through, leading to carbon dusting and corrosion. In spite of considerable attention to this process, many questions remain about its origin. We conduct reactive molecular dynamics simulations of multi-grain iron systems exposed to carburizing gas mixtures to investigate the effect of water content on metal dusting corrosion. To simulate carbon monoxide (CO) dissociation followed by carbon diffusion, we employ an extended-ReaxFF potential that allows accounting for both the high C atoms coordination in bulk iron as well as the lower C coordination at the iron surface and interfaces. The reactions happening in the sample at different water con- centrations and at different time frames are explored. We demonstrate that the presence of water on a clean Fe surface promotes different catalytic reactions at the beginning of the simulations that boost the C, H, O diffusion into the sample. At later stage, the formation of oxide scale leads to an elevated concentration of H2O/OH molecules on the surface due to the decrease in Fe affinity to dissociate water. This results into blocking the Fe catalytic sites leading to lower C and O diffusion to the bulk of the sample

Review of Cervix Cancer Classification Using Radiomics on Diffusion-Weighted Imaging

Magnetic Resonance Imaging (MRI) is one of the most used imaging modalities for the identification and quantification of various types of cancers. MRI image analysis is mostly conducted by experts relying on the visual interpretation of the images and some basic semiquantitative parameters. However, it is well known that additional clinical information is available in these images and can be harvested using the field of radiomics. This consists of the extraction of complex unexplored features from these images that can provide underlying functions in disease process. In this paper, we provide a review of the application of radiomics to extract relevant information from MRI Diffusion Weighted Imaging (DWI) for the classification of cervix cancer. The main research findings are the presentation of the state of the art of this application with the description of its main steps and related challenges

Mechanisms behind the immediate effects of Roux-en-Y gastric bypass surgery on type 2 diabetes

BACKGROUND: The most common bariatric surgery, Roux-en-Y gastric bypass, leads to glycemia normalization in most patients long before there is any appreciable weight loss. This effect is too large to be attributed purely to caloric restriction, so a number of other mechanisms have been proposed. The most popular hypothesis is enhanced production of an incretin, active glucagon-like peptide-1 (GLP-1), in the lower intestine. We therefore set out to test this hypothesis with a model which is simple enough to be robust and credible. METHOD: Our method involves (1) setting up a set of time-dependent equations for the concentrations of the most relevant species, (2) considering an “adiabatic” (or quasi-equilibrium) state in which the concentrations are slowly varying compared to reaction rates (and which in the present case is a postprandial state), and (3) solving for the dependent concentrations (of e.g. insulin and glucose) as an independent concentration (of e.g. GLP-1) is varied. RESULTS: Even in the most favorable scenario, with maximal values for (i) the increase in active GLP-1 concentration and (ii) the effect of GLP-1 on insulin production, enhancement of GLP-1 alone cannot account for the observations. I.e., the largest possible decrease in glucose predicted by the model is smaller than reported decreases, and the model predicts no decrease whatsoever in glucose ×insulin, in contrast to large observed decreases in homeostatic model assessment insulin resistance (HOMA-IR). On the other hand, both effects can be accounted for if the surgery leads to a substantial increase in some substance that opens an alternative insulin-independent pathway for glucose transport into muscle cells, which perhaps uses the same intracellular pool of GLUT-4 that is employed in an established insulin-independent pathway stimulated by muscle contraction during exercise. CONCLUSIONS: Glycemia normalization following Roux-en-Y gastric bypass is undoubtedly caused by a variety of mechanisms, which may include caloric restriction, enhanced GLP-1, and perhaps others proposed in earlier papers on this subject. However, the present results suggest that another possible mechanism should be added to the list of candidates: enhanced production in the lower intestine of a substance which opens an alternative insulin-independent pathway for glucose transport

Integration of the End Cap TEC+ of the CMS Silicon Strip Tracker

The silicon strip tracker of the CMS experiment has been completed and inserted into the CMS detector in late 2007. The largest sub-system of the tracker is its end cap system, comprising two large end caps (TEC) each containing 3200 silicon strip modules. To ease construction, the end caps feature a modular design: groups of about 20 silicon modules are placed on sub-assemblies called petals and these self-contained elements are then mounted into the TEC support structures. Each end cap consists of 144 petals, and the insertion of these petals into the end cap structure is referred to as TEC integration. The two end caps were integrated independently in Aachen (TEC+) and at CERN (TEC--). This note deals with the integration of TEC+, describing procedures for end cap integration and for quality control during testing of integrated sections of the end cap and presenting results from the testing