Root Cause Analysis by a Combined Sparse Classification and Monte Carlo Approach

Classification methods with embedded feature selection capability are very appealing for the analysis of complex processes since they allow the analysis of root causes even when the number of input variables is high. In this work, we investigate the performance of three techniques for classification within a Monte Carlo strategy with the aim of root cause analysis. We consider the naive bayes classifier and the logistic regression model with two different implementations for controlling model complexity, namely, a LASSO-like implementation with a L1 norm regularization and a fully Bayesian implementation of the logistic model, the so called relevance vector machine. Several challenges can arise when estimating such models mainly linked to the characteristics of the data: a large number of input variables, high correlation among subsets of variables, the situation where the number of variables is higher than the number of available data points and the case of unbalanced datasets. Using an ecological and a semiconductor manufacturing dataset, we show advantages and drawbacks of each method, highlighting the superior performance in term of classification accuracy for the relevance vector machine with respect to the other classifiers. Moreover, we show how the combination of the proposed techniques and the Monte Carlo approach can be used to get more robust insights into the problem under analysis when faced with challenging modelling conditions.

Density functional and Monte Carlo studies of sulfur. I. Structure and bonding in S-n rings and chains (n=2-18) (vol 118, pg 9257, 2003)

Density functional calculations have been performed for ring isomers of sulfur with up to 18 atoms, and for chains with up to ten atoms. There are many isomers of both types, and the calculations predict the existence of new forms. Larger rings and chains are very flexible, with numerous local energy minima. Apart from a small, but consistent overestimate in the bond lengths, the results reproduce experimental structures where known. Calculations are also performed on the energy surfaces of S8 rings, on the interaction between a pair of such rings, and the reaction between one S8 ring and the triplet diradical S8 chain. The results for potential energies, vibrational frequencies, and reaction mechanisms in sulfur rings and chains provide essential ingredients for Monte Carlo simulations of the liquid–liquid phase transition. The results of these simulations will be presented in Part II.

Density functional and Monte Carlo studies of sulfur. II. Equilibrium polymerization of the liquid phase

The equilibrium polymerization of sulfur is investigated by Monte Carlo simulations. The potential energy model is based on density functional results for the cohesive energy, structural, and vibrational properties as well as reactivity of sulfur rings and chains [Part I, J. Chem. Phys. 118, 9257 (2003)]. Liquid samples of 2048 atoms are simulated at temperatures 450less than or equal toTless than or equal to850 K and P=0 starting from monodisperse S-8 molecular compositions. Thermally activated bond breaking processes lead to an equilibrium population of unsaturated atoms that can change the local pattern of covalent bonds and allow the system to approach equilibrium. The concentration of unsaturated atoms and the kinetics of bond interchanges is determined by the energy DeltaE(b) required to break a covalent bond. Equilibrium with respect to the bond distribution is achieved for 15less than or equal toDeltaE(b)less than or equal to21 kcal/mol over a wide temperature range (Tgreater than or equal to450 K), within which polymerization occurs readily, with entropy from the bond distribution overcompensating the increase in enthalpy. There is a maximum in the polymerized fraction at temperature T-max that depends on DeltaE(b). This fraction decreases at higher temperature because broken bonds and short chains proliferate and, for Tless than or equal toT(max), because entropy is less important than enthalpy. The molecular size distribution is described well by a Zimm-Schulz function, plus an isolated peak for S-8. Large molecules are almost exclusively open chains. Rings tend to have fewer than 24 atoms, and only S-8 is present in significant concentrations at all T. The T dependence of the density and the dependence of polymerization fraction and degree on DeltaE(b) give estimates of the polymerization temperature T-f=450+/-20 K. (C) 2003 American Institute of Physics.

Density functional/Monte Carlo study of ring-opening polymerization

Density functional calculations of the structure, potential energy surface and reactivity for organic systems closely related to bisphenol-A-polycarbonate (BPA-PC) provide the basis for a model describing the ring-opening polymerization of its cyclic oligomers by nucleophilic molecules. Monte Carlo simulations using this model show a strong tendency to polymerize that is increased by increasing density and temperature, and is greater in 3D than in 2D. Entropy in the distribution of inter-particle bonds is the driving force for chain formation. (C) 2002 Elsevier Science B.V. All rights reserved.

Fixed-node diffusion Monte Carlo computations for closed-shell jellium spheres

Fixed-node diffusion Monte Carlo computations are used to determine the ground state energy and electron density for jellium spheres with up to N = 106 electrons and background densities corresponding to the electron gas parameter 1 less than or equal to r(s)less than or equal to5.62. We analyze the density and size dependence of the surface energy, and we extrapolate our data to the thermodynamic limit. The results agree well with the predictions of density functional computations using the local density approximation. In the case of N = 20, we extend our computation to higher densities and identify a transition between atomic- and jelliumlike nodal structures occurring at the background density corresponding to r(s)=0.13. In this case the local density approximation is unable to reproduce the changes in the correlation energy due to the discontinuous transition in the ground state nodal structure. We discuss the relevance of our results for nonlocal approximations to density functional theory.

Monte Carlo simulation of cluster growth in surface defects induced by the tip of a scanning tunnelling microscope

First steps are taken to model the electrochemical deposition of metals in nanometer-sized cavities. In the present work, the electrochemical deposition of Cu atoms in nanometer-sized holes dug on Au(111) is investigated through Monte Carlo simulations using the embedded atom method to represent particle interactions. By sweeping the chemical potential of Cu, a cluster is allowed to grow within the hole rising four atomic layers above the surface. Its lateral extension remains confined to the area defined by the borders of the original defect. (C) 2004 Elsevier B.V. All rights reserved.

Monte Carlo simulation of properties of monolayers and metal islands adsorbed on metallic (111) surfaces

To obtain the surface stress changes due to the adsorption of metal monolayers onto metallic surfaces, a new model derived from thermodynamic considerations is presented. Such a model is based on continuum Monte Carlo simulations with embedded atom method potentials in the canonical ensemble, and it is extended to consider the behavior on different islands adsorbed onto (111) substrate surfaces. Homoepitaxial and heteroepitaxial systems are studied. Pseudomorphic growth is not observed for small metal islands with considerable positive misfit with the substrate. Instead, the islands become compressed upon increase of their size. A simple model is proposed to interpolate between the misfits of atoms in small islands and the pseudomorphic behavior of the monolayer.

Kinetic Monte Carlo study of electrochemical growth in a heteroepitaxial system

Structural and kinetic aspects of 2-D irreversible metal deposition under potentiostatic conditions are analyzed by means of dynamic Monte Carlo simulations employing embedded atom potentials for a model system. Three limiting models, all considering adatom diffusion, were employed to describe adatom deposition. The first model (A) considers adatom deposition on any free substrate site on the surface at the same rate. The second model (B) considers adatom deposition only on substrate sites which exhibit no neighboring sites occupied by adatoms. The third model (C) allows deposition at higher rates on sites presenting neighboring sites occupied by adatoms. Under the proper conditions, the coverage (theta) versus time (t) relationship for the three cases can be heuristically fitted to the functional form theta = 1 - exp(-betat(alpha)), where alpha and beta are parameters. We suggest that the value of the parameter alpha can be employed to distinguish experimentally between the three cases. While model A trivially delivers a = 1, models B and C are characterized by alpha 1, respectively.