MULTISCALE EXAMINATION AND MODELING OF ELECTRON TRANSPORT IN NANOSCALE MATERIALS AND DEVICES

For half a century the integrated circuits (ICs) that make up the heart of electronic devices have been steadily improving by shrinking at an exponential rate. However, as the current crop of ICs get smaller and the insulating layers involved become thinner, electrons leak through due to quantum mechanical tunneling. This is one of several issues which will bring an end to this incredible streak of exponential improvement of this type of transistor device, after which future improvements will have to come from employing fundamentally different transistor architecture rather than fine tuning and miniaturizing the metal-oxide-semiconductor field effect transistors (MOSFETs) in use today. Several new transistor designs, some designed and built here at Michigan Tech, involve electrons tunneling their way through arrays of nanoparticles. We use a multi-scale approach to model these devices and study their behavior. For investigating the tunneling characteristics of the individual junctions, we use a first-principles approach to model conduction between sub-nanometer gold particles. To estimate the change in energy due to the movement of individual electrons, we use the finite element method to calculate electrostatic capacitances. The kinetic Monte Carlo method allows us to use our knowledge of these details to simulate the dynamics of an entire device— sometimes consisting of hundreds of individual particles—and watch as a device ‘turns on’ and starts conducting an electric current. Scanning tunneling microscopy (STM) and the closely related scanning tunneling spectroscopy (STS) are a family of powerful experimental techniques that allow for the probing and imaging of surfaces and molecules at atomic resolution. However, interpretation of the results often requires comparison with theoretical and computational models. We have developed a new method for calculating STM topographs and STS spectra. This method combines an established method for approximating the geometric variation of the electronic density of states, with a modern method for calculating spin-dependent tunneling currents, offering a unique balance between accuracy and accessibility.

STATE-AND-TRANSITION MODELING AND ADAPTIVE MANAGEMENT: TOOLS FOR FUTURE CO-DEVELOPMENT OF MADAGASCAR’S NATURAL RESOURCES AND PEOPLE

Madagascar’s terrestrial and aquatic ecosystems have long supported a unique set of ecological communities, many of whom are endemic to the tropical island. Those same ecosystems have been a source of valuable natural resources to some of the poorest people in the world. Nevertheless, with pride, ingenuity and resourcefulness, the Malagasy people of the southwest coast, being of Vezo identity, subsist with low development fishing techniques aimed at an increasingly threatened host of aquatic seascapes. Mangroves, sea grass bed, and coral reefs of the region are under increased pressure from the general populace for both food provisions and support of economic opportunity. Besides purveyors and extractors, the coastal waters are also subject to a number of natural stressors, including cyclones and invasive, predator species of both flora and fauna. In addition, the aquatic ecosystems of the region are undergoing increased nutrient and sediment runoff due, in part, to Madagascar’s heavy reliance on land for agricultural purposes (Scales, 2011). Moreover, its coastal waters, like so many throughout the world, have been proven to be warming at an alarming rate over the past few decades. In recognizing the intimate interconnectedness of the both the social and ecological systems, conservation organizations have invoked a host of complimentary conservation and social development efforts with the dual aim of preserving or restoring the health of both the coastal ecosystems and the people of the region. This paper provides a way of thinking more holistically about the social-ecological system within a resiliency frame of understanding. Secondly, it applies a platform known as state-and-transition modeling to give form to the process. State-and-transition modeling is an iterative investigation into the physical makeup of a system of study as well as the boundaries and influences on that state, and has been used in restorative ecology for more than a decade. Lastly, that model is sited within an adaptive management scheme that provides a structured, cyclical, objective-oriented process for testing stakeholders cognitive understanding of the ecosystem through a pragmatic implementation and monitoring a host of small-scale interventions developed as part of the adaptive management process. Throughout, evidence of the application of the theories and frameworks are offered, with every effort made to retool conservation-minded development practitioners with a comprehensive strategy for addressing the increasingly fragile social-ecological systems of southwest Madagascar. It is offered, in conclusion, that the seascapes of the region would be an excellent case study worthy of future application of state-and-transition modeling and adaptive management as frameworks for conservation-minded development practitioners whose multiple projects, each with its own objective, have been implemented with a single goal in mind: preserve and protect the state of the supporting environment while providing for the basic needs of the local Malagasy people.

Long-Range Pollution Transport: Trans-Atlantic Mechanisms and Lagrangian Modeling Methods

Over the past several decades, it has become apparent that anthropogenic activities have resulted in the large-scale enhancement of the levels of many trace gases throughout the troposphere. More recently, attention has been given to the transport pathway taken by these emissions as they are dispersed throughout the atmosphere. The transport pathway determines the physical characteristics of emissions plumes and therefore plays an important role in the chemical transformations that can occur downwind of source regions. For example, the production of ozone (O3) is strongly dependent upon the transport its precursors undergo. O3 can initially be formed within air masses while still over polluted source regions. These polluted air masses can experience continued O3 production or O3 destruction downwind, depending on the air mass's chemical and transport characteristics. At present, however, there are a number of uncertainties in the relationships between transport and O3 production in the North Atlantic lower free troposphere. The first phase of the study presented here used measurements made at the Pico Mountain observatory and model simulations to determine transport pathways for US emissions to the observatory. The Pico Mountain observatory was established in the summer of 2001 in order to address the need to understand the relationships between transport and O3 production. Measurements from the observatory were analyzed in conjunction with model simulations from the Lagrangian particle dispersion model (LPDM), FLEX-PART, in order to determine the transport pathway for events observed at the Pico Mountain observatory during July 2003. A total of 16 events were observed, 4 of which were analyzed in detail. The transport time for these 16 events varied from 4.5 to 7 days, while the transport altitudes over the ocean ranged from 2-8 km, but were typically less than 3 km. In three of the case studies, eastward advection and transport in a weak warm conveyor belt (WCB) airflow was responsible for the export of North American emissions into the FT, while transport in the FT was governed by easterly winds driven by the Azores/Bermuda High (ABH) and transient northerly lows. In the fourth case study, North American emissions were lofted to 6-8 km in a WCB before being entrained in the same cyclone's dry airstream and transported down to the observatory. The results of this study show that the lower marine FT may provide an important transport environment where O3 production may continue, in contrast to transport in the marine boundary layer, where O3 destruction is believed to dominate. The second phase of the study presented here focused on improving the analysis methods that are available with LPDMs. While LPDMs are popular and useful for the analysis of atmospheric trace gas measurements, identifying the transport pathway of emissions from their source to a receptor (the Pico Mountain observatory in our case) using the standard gridded model output, particularly during complex meteorological scenarios can be difficult can be difficult or impossible. The transport study in phase 1 was limited to only 1 month out of more than 3 years of available data and included only 4 case studies out of the 16 events specifically due to this confounding factor. The second phase of this study addressed this difficulty by presenting a method to clearly and easily identify the pathway taken by only those emissions that arrive at a receptor at a particular time, by combining the standard gridded output from forward (i.e., concentrations) and backward (i.e., residence time) LPDM simulations, greatly simplifying similar analyses. The ability of the method to successfully determine the source-to-receptor pathway, restoring this Lagrangian information that is lost when the data are gridded, is proven by comparing the pathway determined from this method with the particle trajectories from both the forward and backward models. A sample analysis is also presented, demonstrating that this method is more accurate and easier to use than existing methods using standard LPDM products. Finally, we discuss potential future work that would be possible by combining the backward LPDM simulation with gridded data from other sources (e.g., chemical transport models) to obtain a Lagrangian sampling of the air that will eventually arrive at a receptor.

Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

Anisotropic diffusion at the field scale in a 4-year multi-tracer diffusion and retention experiment – I: Insights from the experimental data

Abstract Claystones are considered worldwide as barrier materials for nuclear waste repositories. In the Mont Terri underground research laboratory (URL), a nearly 4-year diffusion and retention (DR) experiment has been performed in Opalinus Clay. It aimed at (1) obtaining data at larger space and time scales than in laboratory experiments and (2) under relevant in situ conditions with respect to pore water chemistry and mechanical stress, (3) quantifying the anisotropy of in situ diffusion, and (4) exploring possible effects of a borehole-disturbed zone. The experiment included two tracer injection intervals in a borehole perpendicular to bedding, through which traced artificial pore water (APW) was circulated, and a pressure monitoring interval. The APW was spiked with neutral tracers (HTO, HDO, H2O-18), anions (Br, I, SeO4), and cations (Na-22, Ba-133, Sr-85, Cs-137, Co-60, Eu-152, stable Cs, and stable Eu). Most tracers were added at the beginning, some were added at a later stage. The hydraulic pressure in the injection intervals was adjusted according to the measured value in the pressure monitoring interval to ensure transport by diffusion only. Concentration time-series in the APW within the borehole intervals were obtained, as well as 2D concentration distributions in the rock at the end of the experiment after overcoring and subsampling which resulted in �250 samples and �1300 analyses. As expected, HTO diffused the furthest into the rock, followed by the anions (Br, I, SeO4) and by the cationic sorbing tracers (Na-22, Ba-133, Cs, Cs-137, Co-60, Eu-152). The diffusion of SeO4 was slower than that of Br or I, approximately proportional to the ratio of their diffusion coefficients in water. Ba-133 diffused only into �0.1 m during the �4 a. Stable Cs, added at a higher concentration than Cs-137, diffused further into the rock than Cs-137, consistent with a non-linear sorption behavior. The rock properties (e.g., water contents) were rather homogeneous at the centimeter scale, with no evidence of a borehole-disturbed zone. In situ anisotropy ratios for diffusion, derived for the first time directly from field data, are larger for HTO and Na-22 (�5) than for anions (�3�4 for Br and I). The lower ionic strength of the pore water at this location (�0.22 M) as compared to locations of earlier experiments in the Mont Terri URL (�0.39 M) had no notable effect on the anion accessible pore fraction for Cl, Br, and I: the value of 0.55 is within the range of earlier data. Detailed transport simulations involving different codes will be presented in a companion paper.

Structural equation modeling of the medical outcome study: Short Form 36 (SF-36)

The factorial validity of the SF-36 was evaluated using confirmatory factor analysis (CFA) methods, structural equation modeling (SEM), and multigroup structural equation modeling (MSEM). First, the measurement and structural model of the hypothesized SF-36 was explicated. Second, the model was tested for the validity of a second-order factorial structure, upon evidence of model misfit, determined the best-fitting model, and tested the validity of the best-fitting model on a second random sample from the same population. Third, the best-fitting model was tested for invariance of the factorial structure across race, age, and educational subgroups using MSEM.^ The findings support the second-order factorial structure of the SF-36 as proposed by Ware and Sherbourne (1992). However, the results suggest that: (a) Mental Health and Physical Health covary; (b) general mental health cross-loads onto Physical Health; (c) general health perception loads onto Mental Health instead of Physical Health; (d) many of the error terms are correlated; and (e) the physical function scale is not reliable across these two samples. This hierarchical factor pattern was replicated across both samples of health care workers, suggesting that the post hoc model fitting was not data specific. Subgroup analysis suggests that the physical function scale is not reliable across the "age" or "education" subgroups and that the general mental health scale path from Mental Health is not reliable across the "white/nonwhite" or "education" subgroups.^ The importance of this study is in the use of SEM and MSEM in evaluating sample data from the use of the SF-36. These methods are uniquely suited to the analysis of latent variable structures and are widely used in other fields. The use of latent variable models for self reported outcome measures has become widespread, and should now be applied to medical outcomes research. Invariance testing is superior to mean scores or summary scores when evaluating differences between groups. From a practical, as well as, psychometric perspective, it seems imperative that construct validity research related to the SF-36 establish whether this same hierarchical structure and invariance holds for other populations.^ This project is presented as three articles to be submitted for publication. ^

Volcanic forcing for climate modeling: a new microphysics-based data set covering years 1600–present

As the understanding and representation of the impacts of volcanic eruptions on climate have improved in the last decades, uncertainties in the stratospheric aerosol forcing from large eruptions are now linked not only to visible optical depth estimates on a global scale but also to details on the size, latitude and altitude distributions of the stratospheric aerosols. Based on our understanding of these uncertainties, we propose a new model-based approach to generating a volcanic forcing for general circulation model (GCM) and chemistry–climate model (CCM) simulations. This new volcanic forcing, covering the 1600–present period, uses an aerosol microphysical model to provide a realistic, physically consistent treatment of the stratospheric sulfate aerosols. Twenty-six eruptions were modeled individually using the latest available ice cores aerosol mass estimates and historical data on the latitude and date of eruptions. The evolution of aerosol spatial and size distribution after the sulfur dioxide discharge are hence characterized for each volcanic eruption. Large variations are seen in hemispheric partitioning and size distributions in relation to location/date of eruptions and injected SO2 masses. Results for recent eruptions show reasonable agreement with observations. By providing these new estimates of spatial distributions of shortwave and long-wave radiative perturbations, this volcanic forcing may help to better constrain the climate model responses to volcanic eruptions in the 1600–present period. The final data set consists of 3-D values (with constant longitude) of spectrally resolved extinction coefficients, single scattering albedos and asymmetry factors calculated for different wavelength bands upon request. Surface area densities for heterogeneous chemistry are also provided.

Extension and Partitioning in an Oblique Subduction Zone, New Zealand: Constraints from Three-Dimensional Numerical Modeling

Contraction, strike slip, and extension displacements along the Hikurangi margin northeast of the North Island of New Zealand coincide with large lateral gradients in material properties. We use a finite- difference code utilizing elastic and elastic-plastic rheologies to build large- scale, three-dimensional numerical models which investigate the influence of material properties on velocity partitioning within oblique subduction zones. Rheological variation in the oblique models is constrained by seismic velocity and attenuation information available for the Hikurangi margin. We compare the effect of weakly versus strongly coupled subduction interfaces on the development of extension and the partitioning of velocity components for orthogonal and oblique convergence and include the effect of ponded sediments beneath the Raukumara Peninsula. Extension and velocity partitioning occur if the subduction interface is weak, but neither develops if the subduction interface is strong. The simple mechanical model incorporating rheological variation based on seismic observations produces kinematics that closely match those published from the Hikurangi margin. These include extension within the Taupo Volcanic Zone, uplift over ponded sediments, and dextral contraction to the south.

Regulation of Phytoplankton Carbon to Chlorophyll Ratio By Light, Nutrients and Temperature in the Equatorial Pacific Ocean: A Basin-Scale Model

The complex effects of light, nutrients and temperature lead to a variable carbon to chlorophyll (C:Chl) ratio in phytoplankton cells. Using field data collected in the Equatorial Pacific, we derived a new dynamic model with a non-steady C:Chl ratio as a function of irradiance, nitrate, iron, and temperature. The dynamic model is implemented into a basin-scale ocean circulation-biogeochemistry model and tested in the Equatorial Pacific Ocean. The model reproduces well the general features of phytoplankton dynamics in this region. For instance, the simulated deep chlorophyll maximum (DCM) is much deeper in the western warm pool (similar to 100 m) than in the Eastern Equatorial Pacific (similar to 50 m). The model also shows the ability to reproduce chlorophyll, including not only the zonal, meridional and vertical variations, but also the interannual variability. This modeling study demonstrates that combination of nitrate and iron regulates the spatial and temporal variations in the phytoplankton C:Chl ratio in the Equatorial Pacific. Sensitivity simulations suggest that nitrate is mainly responsible for the high C:Chl ratio in the western warm pool while iron is responsible for the frontal features in the C:Chl ratio between the warm pool and the upwelling region. In addition, iron plays a dominant role in regulating the spatial and temporal variations of the C:Chl ratio in the Central and Eastern Equatorial Pacific. While temperature has a relatively small effect on the C:Chl ratio, light is primarily responsible for the vertical decrease of phytoplankton C:Chl ratio in the euphotic zone.

Dispersal Modeling of Fish Early Life Stages: Sensitivity with Application to Atlantic Cod in the Western Gulf of Maine

As an initial step in establishing mechanistic relationships between environmental variability and recruitment in Atlantic cod Gadhus morhua along the coast of the western Gulf of Maine, we assessed transport success of larvae from major spawning grounds to nursery areas with particle tracking using the unstructured grid model FVCOM (finite volume coastal ocean model). In coastal areas, dispersal of early planktonic life stages of fish and invertebrate species is highly dependent on the regional dynamics and its variability, which has to be captured by our models. With state-of-the-art forcing for the year 1995, we evaluate the sensitivity of particle dispersal to the timing and location of spawning, the spatial and temporal resolution of the model, and the vertical mixing scheme. A 3 d frequency for the release of particles is necessary to capture the effect of the circulation variability into an averaged dispersal pattern of the spawning season. The analysis of sensitivity to model setup showed that a higher resolution mesh, tidal forcing, and current variability do not change the general pattern of connectivity, but do tend to increase within-site retention. Our results indicate strong downstream connectivity among spawning grounds and higher chances for successful transport from spawning areas closer to the coast. The model run for January egg release indicates 1 to 19 % within-spawning ground retention of initial particles, which may be sufficient to sustain local populations. A systematic sensitivity analysis still needs to be conducted to determine the minimum mesh and forcing resolution that adequately resolves the complex dynamics of the western Gulf of Maine. Other sources of variability, i.e. large-scale upstream forcing and the biological environment, also need to be considered in future studies of the interannual variability in transport and survival of the early life stages of cod.

Simulating Cortical Development as a Self Constructing Process: A Novel Multi-Scale Approach Combining Molecular and Physical Aspects

Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes support. We have explored this collective behavior in the context of neocortical development, by modeling the expansion of a small number of progenitor cells into a laminated cortex with layer and cell type specific projections. The developmental process is steered by a formal language analogous to genomic instructions, and takes place in a physically realistic three-dimensional environment. A common genome inserted into individual cells control their individual behaviors, and thereby gives rise to collective developmental sequences in a biologically plausible manner. The simulation begins with a single progenitor cell containing the artificial genome. This progenitor then gives rise through a lineage of offspring to distinct populations of neuronal precursors that migrate to form the cortical laminae. The precursors differentiate by extending dendrites and axons, which reproduce the experimentally determined branching patterns of a number of different neuronal cell types observed in the cat visual cortex. This result is the first comprehensive demonstration of the principles of self-construction whereby the cortical architecture develops. In addition, our model makes several testable predictions concerning cell migration and branching mechanisms.

Benchmark problems for reactive transport modeling of the generation and attenuation of acid rock drainage

Acid rock drainage (ARD) is a problem of international relevance with substantial environmental and economic implications. Reactive transport modeling has proven a powerful tool for the process-based assessment of metal release and attenuation at ARD sites. Although a variety of models has been used to investigate ARD, a systematic model intercomparison has not been conducted to date. This contribution presents such a model intercomparison involving three synthetic benchmark problems designed to evaluate model results for the most relevant processes at ARD sites. The first benchmark (ARD-B1) focuses on the oxidation of sulfide minerals in an unsaturated tailing impoundment, affected by the ingress of atmospheric oxygen. ARD-B2 extends the first problem to include pH buffering by primary mineral dissolution and secondary mineral precipitation. The third problem (ARD-B3) in addition considers the kinetic and pH-dependent dissolution of silicate minerals under low pH conditions. The set of benchmarks was solved by four reactive transport codes, namely CrunchFlow, Flotran, HP1, and MIN3P. The results comparison focused on spatial profiles of dissolved concentrations, pH and pE, pore gas composition, and mineral assemblages. In addition, results of transient profiles for selected elements and cumulative mass loadings were considered in the intercomparison. Despite substantial differences in model formulations, very good agreement was obtained between the various codes. Residual deviations between the results are analyzed and discussed in terms of their implications for capturing system evolution and long-term mass loading predictions.

Millennial to orbital-scale variations of drought intensity in the Eastern Mediterranean

Millennial to orbital-scale rainfall changes in the Mediterranean region and corresponding variations in vegetation patterns were the result of large-scale atmospheric reorganizations. In spite of recent efforts to reconstruct this variability using a range of proxy archives, the underlying physical mechanisms have remained elusive. Through the analysis of a new high-resolution sedimentary section from Lake Van (Turkey) along with climate modeling experiments, we identify massive droughts in the Eastern Med- iterranean for the past four glacial cycles, which have a pervasive link with known intervals of enhanced North Atlantic glacial iceberg calving, weaker Atlantic Meridional Overturning Circulation and Dansgaard-Oeschger cold conditions. On orbital timescales, the topographic effect of large Northern Hemisphere ice sheets and periods with minimum insolation seasonality further exacerbated drought intensities by suppressing both summer and winter precipitation.

The position effect in a Rasch-homogenous test: A fixed-links modeling approach.

The position effect describes the influence of just-completed items in a psychological scale on subsequent items. This effect has been repeatedly reported for psychometric reasoning scales and is assumed to reflect implicit learning during testing. One way to identify the position effect is fixed-links modeling. With this approach, two latent variables are derived from the test items. Factor loadings of one latent variable are fixed to 1 for all items to represent ability-related variance. Factor loadings on the second latent variable increase from the first to the last item describing the position effect. Previous studies using fixed-links modeling on the position effect investigated reasoning scales constructed in accordance with classical test theory (e.g., Raven’s Progressive Matrices) but, to the best of our knowledge, no Rasch-scaled tests. These tests, however, meet stronger requirements on item homogeneity. In the present study, therefore, we will analyze data from 239 participants who have completed the Rasch-scaled Viennese Matrices Test (VMT). Applying a fixed-links modeling approach, we will test whether a position effect can be depicted as a latent variable and separated from a latent variable representing basic reasoning ability. The results have implications for the assumption of homogeneity in Rasch-homogeneous tests.

Early Life History and a Modeling Framework for Lobster (Homarus Americanus) Populations in the Gulf of Maine

Beginning in the late 1980s, lobster (Homarus americanus) landings for the state of Maine and the Bay of Fundy increased to levels more than three times their previous 20-year means. Reduced predation may have permitted the expansion of lobsters into previously inhospitable territory, but we argue that in this region the spatial patterns of recruitment and the abundance of lobsters are substantially driven by events governing the earliest life history stages, including the abundance and distribution of planktonic stages and their initial settlement as Young-of-Year (YOY) lobsters. Settlement densities appear to be strongly driven by abundance of the pelagic postlarvae. Postlarvae and YOY show large-scale spatial patterns commensurate with coastal circulation, but also multi-year trends in abundance and abrupt shifts in abundance and spatial patterns that signal strong environmental forcing. The extent of the coastal shelf that defines the initial settlement grounds for lobsters is important to future population modeling. We address one part of this definition by examining patterns of settlement with depth, and discuss a modeling framework for the full life history of lobsters in the Gulf of Maine.