Core-level photoemission investigations of the CDTE(100) and INSB(100) surface and interfacial structures

Photoemission techniques, utilizing a synchrotron light source, were used to analyze the clean (100) surfaces of the zinc-blende semiconductor materials CdTe and InSb. Several interfacial systems involving the surfaces of these materials were also studied, including the CdTe(lOO)-Ag interface, the CdTe(lOO)-Sb system, and the InSb(lOO)-Sn interface. High-energy electron diffraction was also employed to acquire information about of surface structure. A one-domain (2xl) structure was observed for the CdTe(lOO) surface. Analysis of photoemission spectra of the Cd 4d core level for this surface structure revealed two components resulting from Cd surface atoms. The total intensity of these components accounts for a full monolayer of Cd atoms on the surface. A structural model is discussed commensurate with these results. Photoemission spectra of the Cd and Te 4d core levels indicate that Ag or Sb deposited on the CdTe(l00)-(2xl) surface at room temperature do not bound strongly to the surface Cd atoms. The room temperature growth characteristics for these two elements on the CdTe(lOO)-(2xl) are discussed. The growth at elevated substrate temperatures was also studied for Sb deposition. The InSb(lOO) surface differed from the CdTe(lOO) surface. Using molecular beam epitaxy, several structures could be generated for the InSb(lOO) surface, including a c(8x2), a c(4x4), an asymmetric (lx3), a symmetric (lx3), and a (lxl). Analysis of photoemission intensities and line shapes indicates that the c(4x4) surface is terminated with 1-3/4 monolayers of Sb atoms. The c(8x2) surface is found to be terminated with 3/4 monolayer of In atoms. Structural models for both of these surfaces are proposed based upon the photoemission results and upon models of the similar GaAs(lOO) structures. The room temperature growth characteristics of grey Sn on the lnSb(lOO)-c(4x4) and InSb(l00)-c(8x2) surfaces were studied with photoemission. The discontinuity in the valence band maximum for this semiconductor heterojunction system is measured to be 0.40 eV, independent of the starting surface structure and stoichiometry. This result is reconciled with theoretical predictions for heterostructure behavior.

Soft computing based parameter identification in pavements and geomechanical systems

Accurate estimation of road pavement geometry and layer material properties through the use of proper nondestructive testing and sensor technologies is essential for evaluating pavement’s structural condition and determining options for maintenance and rehabilitation. For these purposes, pavement deflection basins produced by the nondestructive Falling Weight Deflectometer (FWD) test data are commonly used. The nondestructive FWD test drops weights on the pavement to simulate traffic loads and measures the created pavement deflection basins. Backcalculation of pavement geometry and layer properties using FWD deflections is a difficult inverse problem, and the solution with conventional mathematical methods is often challenging due to the ill-posed nature of the problem. In this dissertation, a hybrid algorithm was developed to seek robust and fast solutions to this inverse problem. The algorithm is based on soft computing techniques, mainly Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs) as well as the use of numerical analysis techniques to properly simulate the geomechanical system. A widely used pavement layered analysis program ILLI-PAVE was employed in the analyses of flexible pavements of various pavement types; including full-depth asphalt and conventional flexible pavements, were built on either lime stabilized soils or untreated subgrade. Nonlinear properties of the subgrade soil and the base course aggregate as transportation geomaterials were also considered. A computer program, Soft Computing Based System Identifier or SOFTSYS, was developed. In SOFTSYS, ANNs were used as surrogate models to provide faster solutions of the nonlinear finite element program ILLI-PAVE. The deflections obtained from FWD tests in the field were matched with the predictions obtained from the numerical simulations to develop SOFTSYS models. The solution to the inverse problem for multi-layered pavements is computationally hard to achieve and is often not feasible due to field variability and quality of the collected data. The primary difficulty in the analysis arises from the substantial increase in the degree of non-uniqueness of the mapping from the pavement layer parameters to the FWD deflections. The insensitivity of some layer properties lowered SOFTSYS model performances. Still, SOFTSYS models were shown to work effectively with the synthetic data obtained from ILLI-PAVE finite element solutions. In general, SOFTSYS solutions very closely matched the ILLI-PAVE mechanistic pavement analysis results. For SOFTSYS validation, field collected FWD data were successfully used to predict pavement layer thicknesses and layer moduli of in-service flexible pavements. Some of the very promising SOFTSYS results indicated average absolute errors on the order of 2%, 7%, and 4% for the Hot Mix Asphalt (HMA) thickness estimation of full-depth asphalt pavements, full-depth pavements on lime stabilized soils and conventional flexible pavements, respectively. The field validations of SOFTSYS data also produced meaningful results. The thickness data obtained from Ground Penetrating Radar testing matched reasonably well with predictions from SOFTSYS models. The differences observed in the HMA and lime stabilized soil layer thicknesses observed were attributed to deflection data variability from FWD tests. The backcalculated asphalt concrete layer thickness results matched better in the case of full-depth asphalt flexible pavements built on lime stabilized soils compared to conventional flexible pavements. Overall, SOFTSYS was capable of producing reliable thickness estimates despite the variability of field constructed asphalt layer thicknesses.