Showing papers by "Georgia Institute of Technology published in 2006"

Model selection and estimation in regression with grouped variables

Abstract: Summary. We consider the problem of selecting grouped variables (factors) for accurate prediction in regression. Such a problem arises naturally in many practical situations with the multifactor analysis-of-variance problem as the most important and well-known example. Instead of selecting factors by stepwise backward elimination, we focus on the accuracy of estimation and consider extensions of the lasso, the LARS algorithm and the non-negative garrotte for factor selection. The lasso, the LARS algorithm and the non-negative garrotte are recently proposed regression methods that can be used to select individual variables. We study and propose efficient algorithms for the extensions of these methods for factor selection and show that these extensions give superior performance to the traditional stepwise backward elimination method in factor selection problems. We study the similarities and the differences between these methods. Simulations and real examples are used to illustrate the methods.

Piezoelectric Nanogenerators Based on Zinc Oxide Nanowire Arrays

Abstract: We have converted nanoscale mechanical energy into electrical energy by means of piezoelectric zinc oxide nanowire (NW) arrays. The aligned NWs are deflected with a conductive atomic force microscope tip in contact mode. The coupling of piezoelectric and semiconducting properties in zinc oxide creates a strain field and charge separation across the NW as a result of its bending. The rectifying characteristic of the Schottky barrier formed between the metal tip and the NW leads to electrical current generation. The efficiency of the NW-based piezoelectric power generator is estimated to be 17 to 30%. This approach has the potential of converting mechanical, vibrational, and/or hydraulic energy into electricity for powering nanodevices.

Cancer Cell Imaging and Photothermal Therapy in the Near-Infrared Region by Using Gold Nanorods

Abstract: Due to strong electric fields at the surface, the absorption and scattering of electromagnetic radiation by noble metal nanoparticles are strongly enhanced. These unique properties provide the potential of designing novel optically active reagents for simultaneous molecular imaging and photothermal cancer therapy. It is desirable to use agents that are active in the near-infrared (NIR) region of the radiation spectrum to minimize the light extinction by intrinsic chromophores in native tissue. Gold nanorods with suitable aspect ratios (length divided by width) can absorb and scatter strongly in the NIR region (650−900 nm). In the present work, we provide an in vitro demonstration of gold nanorods as novel contrast agents for both molecular imaging and photothermal cancer therapy. Nanorods are synthesized and conjugated to anti-epidermal growth factor receptor (anti-EGFR) monoclonal antibodies and incubated in cell cultures with a nonmalignant epithelial cell line (HaCat) and two malignant oral epithelial ...

Electronic Confinement and Coherence in Patterned Epitaxial Graphene

Abstract: Ultrathin epitaxial graphite was grown on single-crystal silicon carbide by vacuum graphitization. The material can be patterned using standard nanolithography methods. The transport properties, which are closely related to those of carbon nanotubes, are dominated by the single epitaxial graphene layer at the silicon carbide interface and reveal the Dirac nature of the charge carriers. Patterned structures show quantum confinement of electrons and phase coherence lengths beyond 1 micrometer at 4 kelvin, with mobilities exceeding 2.5 square meters per volt-second. All-graphene electronically coherent devices and device architectures are envisaged.

Calculated Absorption and Scattering Properties of Gold Nanoparticles of Different Size, Shape, and Composition: Applications in Biological Imaging and Biomedicine

Abstract: The selection of nanoparticles for achieving efficient contrast for biological and cell imaging applications, as well as for photothermal therapeutic applications, is based on the optical properties of the nanoparticles. We use Mie theory and discrete dipole approximation method to calculate absorption and scattering efficiencies and optical resonance wavelengths for three commonly used classes of nanoparticles: gold nanospheres, silica−gold nanoshells, and gold nanorods. The calculated spectra clearly reflect the well-known dependence of nanoparticle optical properties viz. the resonance wavelength, the extinction cross-section, and the ratio of scattering to absorption, on the nanoparticle dimensions. A systematic quantitative study of the various trends is presented. By increasing the size of gold nanospheres from 20 to 80 nm, the magnitude of extinction as well as the relative contribution of scattering to the extinction rapidly increases. Gold nanospheres in the size range commonly employed (∼40 nm)...

The interplay between exploration and exploitation

Abstract: Exploration and exploitation have emerged as the twin concepts underpinning organizational adaptation research, yet some central issues related to them remain ambiguous. We address four related que...

Why gold nanoparticles are more precious than pretty gold: noble metal surface plasmon resonance and its enhancement of the radiative and nonradiative properties of nanocrystals of different shapes.

Abstract: This tutorial review presents an introduction to the field of noble metal nanoparticles and their current applications. The origin of the surface plasmon resonance and synthesis procedures are described. A number of applications are presented that take advantage of the electromagnetic field enhancement of the radiative properties of noble metal nanoparticles resulting from the surface plasmon oscillations.

Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research

Abstract: Despite recurring concerns about common method variance (CMV) in survey research, the information systems (IS) community remains largely uncertain of the extent of such potential biases. To address this uncertainty, this paper attempts to systematically examine the impact of CMV on the inferences drawn from survey research in the IS area. First, we describe the available approaches for assessing CMV and conduct an empirical study to compare them. From an actual survey involving 227 respondents, we find that although CMV is present in the research areas examined, such biases are not substantial. The results also suggest that few differences exist between the relatively new marker-variable technique and other well-established conventional tools in terms of their ability to detect CMV. Accordingly, the marker-variable technique was employed to infer the effect of CMV on correlations from previously published studies. Our findings, based on the reanalysis of 216 correlations, suggest that the inflated correlation caused by CMV may be expected to be on the order of 0.10 or less, and most of the originally significant correlations remain significant even after controlling for CMV. Finally, by extending the marker-variable technique, we examined the effect of CMV on structural relationships in past literature. Our reanalysis reveals that contrary to the concerns of some skeptics, CMV-adjusted structural relationships not only remain largely significant but also are not statistically differentiable from uncorrected estimates. In summary, this comprehensive and systematic analysis offers initial evidence that (1) the marker-variable technique can serve as a convenient, yet effective, tool for accounting for CMV, and (2) common method biases in the IS domain are not as serious as those found in other disciplines.

Accurate electrical battery model capable of predicting runtime and I-V performance

Abstract: Low power dissipation and maximum battery runtime are crucial in portable electronics. With accurate and efficient circuit and battery models in hand, circuit designers can predict and optimize battery runtime and circuit performance. In this paper, an accurate, intuitive, and comprehensive electrical battery model is proposed and implemented in a Cadence environment. This model accounts for all dynamic characteristics of the battery, from nonlinear open-circuit voltage, current-, temperature-, cycle number-, and storage time-dependent capacity to transient response. A simplified model neglecting the effects of self-discharge, cycle number, and temperature, which are nonconsequential in low-power Li-ion-supplied applications, is validated with experimental data on NiMH and polymer Li-ion batteries. Less than 0.4% runtime error and 30-mV maximum error voltage show that the proposed model predicts both the battery runtime and I-V performance accurately. The model can also be easily extended to other battery and power sourcing technologies.

Gold and Silver Nanoparticles in Sensing and Imaging: Sensitivity of Plasmon Response to Size, Shape, and Metal Composition

Abstract: Plasmonic metal nanoparticles have great potential for chemical and biological sensor applications, due to their sensitive spectral response to the local environment of the nanoparticle surface and ease of monitoring the light signal due to their strong scattering or absorption. In this work, we investigated the dependence of the sensitivity of the surface plasmon resonance (frequency and bandwidth) response to changes in their surrounding environment and the relative contribution of optical scattering to the total extinction, on the size and shape of nanorods and the type of metal, that is, Au vs Ag. Theoretical consideration on the surface plasmon resonance condition revealed that the spectral sensitivity, defined as the relative shift in resonance wavelength with respect to the refractive index change of surrounding materials, has two controlling factors: first the bulk plasma wavelength, a property dependent on the metal type, and second on the aspect ratio of the nanorods which is a geometrical parameter. It is found that the sensitivity is linearly proportional to both these factors. To quantitatively examine the dependence of the spectral sensitivity on the nanorod metal composition and the aspect ratio, the discrete dipole approximation method was used for the calculation of optical spectra of Ag-Au alloy metal nanorods as a function of Ag concentration. It is observed that the sensitivity does not depend on the type of the metal but depends largely on the aspect ratio of nanorods. The direct dependence of the sensitivity on the aspect ratio becomes more prominent as the size of nanorods becomes larger. However, the use of larger nanoparticles may induce an excessive broadening of the resonance spectrum due to an increase in the contribution of multipolar excitations. This restricts the sensing resolution. The insensitivity of the plasmon response to the metal composition is attributable to the fact that the bulk plasma frequency of the metal, which determines the spectral dispersion of the real dielectric function of metals and the surface plasmon resonance condition, has a similar value for the noble metals. On the other hand, nanorods with higher Ag concentration show a great enhancement in magnitude and sharpness of the plasmon resonance band, which gives better sensing resolution despite similar plasmon response. Furthermore, Ag nanorods have an additional advantage as better scatterers compared with Au nanorods of the same size.

On the Nature of the Active Species in Palladium Catalyzed Mizoroki–Heck and Suzuki–Miyaura Couplings – Homogeneous or Heterogeneous Catalysis, A Critical Review

Abstract: A wide array of forms of palladium has been utilized as precatalysts for Heck and Suzuki coupling reactions over the last 15 years. Historically, nearly every form of palladium used has been described as the active catalytic species. However, recent research has begun to shed light on the in situ transformations that many palladium precatalysts undergo during and before the catalytic reaction, and there are now many suggestions in the literature that narrow the scope of types of palladium that may be considered true “catalysts” in these coupling reactions. In this work, for each type of precatalyst, the recent literature is summarized and the type(s) of palladium that are proposed to be truly active are enumerated. All forms of palladium, including discrete soluble palladium complexes, solid-supported metal ligand complexes, supported palladium nano- and macroparticles, soluble palladium nanoparticles, soluble ligand-free palladium, and palladium-exchanged oxides are considered and reviewed here. A considerable focus is placed on solid precatalysts and on evidence for and against catalysis by solid surfaces vs. soluble species when starting with various precatalysts. The review closes with a critical overview of various control experiments or tests that have been used by authors to assess the homogeneity or heterogeneity of catalyst systems.

Factors Predicting the Use of Technology: Findings From the Center for Research and Education on Aging and Technology Enhancement (CREATE)

Abstract: The successful adoption of technology is becoming increasingly important to functional independence. The present article reports findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE) on the use of technology among communitydwelling adults. The sample included 1,204 individuals ranging in age from 18–91 years. All participants completed a battery that included measures of demographic characteristics, self-rated health, experience with technology, attitudes toward computers, and component cognitive abilities. Findings indicate that the older adults were less likely than younger adults to use technology in general, computers, and the World Wide Web. The results also indicate that computer anxiety, fluid intelligence, and crystallized intelligence were important predictors of the use of technology. The relationship between age and adoption of technology was mediated by cognitive abilities, computer self-efficacy, and computer anxiety. These findings are discussed in terms of training strategies to promote technology adoption.

Orthogonal nonnegative matrix t-factorizations for clustering

Abstract: Currently, most research on nonnegative matrix factorization (NMF)focus on 2-factor $X=FG^T$ factorization. We provide a systematicanalysis of 3-factor $X=FSG^T$ NMF. While it unconstrained 3-factor NMF is equivalent to it unconstrained 2-factor NMF, itconstrained 3-factor NMF brings new features to it constrained 2-factor NMF. We study the orthogonality constraint because it leadsto rigorous clustering interpretation. We provide new rules for updating $F,S, G$ and prove the convergenceof these algorithms. Experiments on 5 datasets and a real world casestudy are performed to show the capability of bi-orthogonal 3-factorNMF on simultaneously clustering rows and columns of the input datamatrix. We provide a new approach of evaluating the quality ofclustering on words using class aggregate distribution andmulti-peak distribution. We also provide an overview of various NMF extensions andexamine their relationships.

Particle Shape Effects on Packing Density, Stiffness, and Strength: Natural and Crushed Sands

Abstract: The size and shape of soil particles reflect the formation history of the grains. In turn, the macroscale behavior of the soil mass results from particle level interactions which are affected by particle shape. Sphericity, roundness, and smoothness characterize different scales associated with particle shape. New experimental data and results from published studies are gathered into two databases to explore the effects of particle shape on packing density and on the small-to-large strain mechanical properties of sandy soils. In agreement with previous studies, these data confirm that increased angularity or eccentricity produces an increase in emax and emin. Furthermore, the data show that increasing particle irregularity causes a decrease in stiffness yet heightened sensitivity to the state of stress; an increase in compressibility under zero-lateral strain loading; an increase in the critical state friction angle cs; and an increase in the intercept of the critical state line there is a weak effect on the slope . Therefore, particle shape emerges as a significant soil index property that needs to be properly characterized and documented, particularly in clean sands and gravels. The systematic assessment of particle shape will lead to a better understanding of sand behavior.

The Strong Perfect Graph Theorem

Abstract: A graph G is perfect if for every induced subgraph H, the chromatic number of H equals the size of the largest complete subgraph of H, and G is Berge if no induced subgraph of G is an odd cycle of length at least five or the complement of one. The ?strong perfect graph conjecture? (Berge, 1961) asserts that a graph is perfect if and only if it is Berge. A stronger conjecture was made recently by Conforti, Cornu?ejols and Vuiskovi?c ? that every Berge graph either falls into one of a few basic classes, or admits one of a few kinds of separation (designed so that a minimum counterexample to Berge?s conjecture cannot have either of these properties). In this paper we prove both of these conjectures.

Convex Approximations of Chance Constrained Programs

Abstract: We consider a chance constrained problem, where one seeks to minimize a convex objective over solutions satisfying, with a given close to one probability, a system of randomly perturbed convex constraints. This problem may happen to be computationally intractable; our goal is to build its computationally tractable approximation, i.e., an efficiently solvable deterministic optimization program with the feasible set contained in the chance constrained problem. We construct a general class of such convex conservative approximations of the corresponding chance constrained problem. Moreover, under the assumptions that the constraints are affine in the perturbations and the entries in the perturbation vector are independent-of-each-other random variables, we build a large deviation-type approximation, referred to as “Bernstein approximation,” of the chance constrained problem. This approximation is convex and efficiently solvable. We propose a simulation-based scheme for bounding the optimal value in the chance constrained problem and report numerical experiments aimed at comparing the Bernstein and well-known scenario approximation approaches. Finally, we extend our construction to the case of ambiguous chance constrained problems, where the random perturbations are independent with the collection of distributions known to belong to a given convex compact set rather than to be known exactly, while the chance constraint should be satisfied for every distribution given by this set.

Intelligent Fault Diagnosis and Prognosis for Engineering Systems

Abstract: PREFACE. ACKNOWLEDGMENTS. PROLOGUE. 1 INTRODUCTION. 1.1 Historical Perspective. 1.2 Diagnostic and Prognostic System Requirements. 1.3 Designing in Fault Diagnostic and Prognostic Systems. 1.4 Diagnostic and Prognostic Functional Layers. 1.5 Preface to Book Chapters. 1.6 References. 2 SYSTEMS APPROACH TO CBM/PHM. 2.1 Introduction. 2.2 Trade Studies. 2.3 Failure Modes and Effects Criticality Analysis (FMECA). 2.4 System CBM Test-Plan Design. 2.5 Performance Assessment. 2.6 CBM/PHM Impact on Maintenance and Operations: Case Studies. 2.7 CBM/PHM in Control and Contingency Management. 2.8 References. 3 SENSORS AND SENSING STRATEGIES. 3.1 Introduction. 3.2 Sensors. 3.3 Sensor Placement. 3.4 Wireless Sensor Networks. 3.5 Smart Sensors. 3.6 References. 4 SIGNAL PROCESSING AND DATABASE MANAGEMENT SYSTEMS. 4.1 Introduction. 4.2 Signal Processing in CBM/PHM. 4.3 Signal Preprocessing. 4.4 Signal Processing. 4.5 Vibration Monitoring and Data Analysis. 4.6 Real-Time Image Feature Extraction and Defect/Fault Classification. 4.7 The Virtual Sensor. 4.8 Fusion or Integration Technologies. 4.9 Usage-Pattern Tracking. 4.10 Database Management Methods. 4.11 References. 5 FAULT DIAGNOSIS. 5.1 Introduction. 5.2 The Diagnostic Framework. 5.3 Historical Data Diagnostic Methods. 5.4 Data-Driven Fault Classification and Decision Making. 5.5 Dynamic Systems Modeling. 5.6 Physical Model-Based Methods. 5.7 Model-Based Reasoning. 5.8 Case-Based Reasoning (CBR). 5.9 Other Methods for Fault Diagnosis. 5.10 A Diagnostic Framework for Electrical/Electronic Systems. 5.11 Case Study: Vibration-Based Fault Detection and Diagnosis for Engine Bearings. 5.12 References. 6 FAULT PROGNOSIS. 6.1 Introduction. 6.2 Model-Based Prognosis Techniques. 6.3 Probability-Based Prognosis Techniques. 6.4 Data-Driven Prediction Techniques. 6.5 Case Studies. 6.6 References. 7 FAULT DIAGNOSIS AND PROGNOSIS PERFORMANCE METRICS. 7.1 Introduction. 7.2 CBM/PHM Requirements Definition. 7.3 Feature-Evaluation Metrics. 7.4 Fault Diagnosis Performance Metrics. 7.5 Prognosis Performance Metrics. 7.6 Diagnosis and Prognosis Effectiveness Metrics. 7.7 Complexity/Cost-Benefit Analysis of CBM/PHM Systems. 7.8 References. 8 LOGISTICS: SUPPORT OF THE SYSTEM IN OPERATION. 8.1 Introduction. 8.2 Product-Support Architecture, Knowledge Base, and Methods for CBM. 8.3 Product Support without CBM. 8.4 Product Support with CBM. 8.5 Maintenance Scheduling Strategies. 8.6 A Simple Example. 8.7 References. APPENDIX. INDEX.

Piezoelectric field effect transistor and nanoforce sensor based on a single ZnO nanowire.

Abstract: Utilizing the coupled piezoelectric and semiconducting dual properties of ZnO, we demonstrate a piezoelectric field effect transistor (PE-FET) that is composed of a ZnO nanowire (NW) (or nanobelt) bridging across two Ohmic contacts, in which the source to drain current is controlled by the bending of the NW. A possible mechanism for the PE-FET is suggested to be associated with the carrier trapping effect and the creation of a charge depletion zone under elastic deformatioin. This PE-FET has been applied as a force/pressure sensor for measuring forces in the nanonewton range and even smaller with the use of smaller NWs. An almost linear relationship between the bending force and the conductance was found at small bending regions, demonstrating the principle of nanowire-based nanoforce and nanopressure sensors.

Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing

Abstract: Solving the SLAM (simultaneous localization and mapping) problem is one way to enable a robot to explore, map, and navigate in a previously unknown environment. Smoothing approaches have been investigated as a viable alternative to extended Kalman filter (EKF)-based solutions to the problem. In particular, approaches have been looked at that factorize either the associated information matrix or the measurement Jacobian into square root form. Such techniques have several significant advantages over the EKF: they are faster yet exact; they can be used in either batch or incremental mode; are better equipped to deal with non-linear process and measurement models; and yield the entire robot trajectory, at lower cost for a large class of SLAM problems. In addition, in an indirect but dramatic way, column ordering heuristics automatically exploit the locality inherent in the geographic nature of the SLAM problem. This paper presents the theory underlying these methods, along with an interpretation of factorization in terms of the graphical model associated with the SLAM problem. Both simulation results and actual SLAM experiments in large-scale environments are presented that underscore the potential of these methods as an alternative to EKF-based approaches.

A Tale of Two Methods

Abstract: The structural equation modeling approach to testing for mediation is compared to the Baron and Kenny approach. The approaches are essentially the same when the hypothesis being tested predicts par...

Theoretical Results on Sparse Representations of Multiple-Measurement Vectors

Abstract: The sparse representation of a multiple-measurement vector (MMV) is a relatively new problem in sparse representation. Efficient methods have been proposed. Although many theoretical results that are available in a simple case-single-measurement vector (SMV)-the theoretical analysis regarding MMV is lacking. In this paper, some known results of SMV are generalized to MMV. Some of these new results take advantages of additional information in the formulation of MMV. We consider the uniqueness under both an lscr0-norm-like criterion and an lscr1-norm-like criterion. The consequent equivalence between the lscr0-norm approach and the lscr1-norm approach indicates a computationally efficient way of finding the sparsest representation in a redundant dictionary. For greedy algorithms, it is proven that under certain conditions, orthogonal matching pursuit (OMP) can find the sparsest representation of an MMV with computational efficiency, just like in SMV. Simulations show that the predictions made by the proved theorems tend to be very conservative; this is consistent with some recent advances in probabilistic analysis based on random matrix theory. The connections will be discussed

Algorithms for Assigning Substrate Network Resources to Virtual Network Components

Abstract: Recent proposals for network virtualization provide a promising way to overcome the Internet ossification. The key idea of network virtualization is to build a diversified Internet to support a variety of network services and architectures through a shared substrate. A major challenge in network virtualization is the assigning of substrate resources to virtual networks (VN) efficiently and on-demand. This paper focuses on two versions of the VN assignment problem: VN assignment without reconfiguration (VNA-I) and VN assignment with reconfiguration (VNAII). For the VNA-I problem, we develop a basic scheme as a building block for all other advanced algorithms. Subdividing heuristics and adaptive optimization strategies are then presented to further improve the performance. For the VNA-II problem, we develop a selective VN reconfiguration scheme that prioritizes the reconfiguration of the most critical VNs. Extensive simulation experiments demonstrate that the proposed algorithms can achieve good performance under a wide range of network conditions.

Plasmon Coupling in Nanorod Assemblies: Optical Absorption, Discrete Dipole Approximation Simulation, and Exciton-Coupling Model

Abstract: The shape anisotropy of nanorods gives rise to two distinct orientational modes by which nanorods can be assembled, i.e., end-to-end and side-by-side, analogous to the well-known H and J aggregation in organic chromophores. Optical absorption spectra of gold nanorods have earlier been observed to show a red-shift of the longitudinal plasmon band for the end-to-end linkage of nanorods, resulting from the plasmon coupling between neighboring nanoparticles, similar to the assembly of gold nanospheres. We observe, however, that side-by-side linkage of nanorods in solution shows a blue-shift of the longitudinal plasmon band and a red-shift of the transverse plasmon band. Optical spectra calculated using the discrete dipole approximation method were used to simulate plasmon coupling in assembled nanorod dimers. The longitudinal plasmon band is found to shift to lower energies for end-to-end assembly, but a shift to higher energies is found for the side-by-side orientation, in agreement with the optical absorpti...

An extremely rich repertoire of bursting patterns during the development of cortical cultures

Abstract: We have collected a comprehensive set of multi-unit data on dissociated cortical cultures. Previous studies of the development of the electrical activity of dissociated cultures of cortical neurons each focused on limited aspects of its dynamics, and were often based on small numbers of observed cultures. We followed 58 cultures of different densities – 3000 to 50,000 neurons on areas of 30 to 75 mm2 – growing on multi-electrode arrays (MEAs) during the first five weeks of their development. Plating density had a profound effect on development. While the aggregate spike detection rate scaled linearly with density, as expected from the number of cells in proximity to electrodes, dense cultures started to exhibit bursting behavior earlier in development than sparser cultures. Analysis of responses to electrical stimulation suggests that axonal outgrowth likewise occurred faster in dense cultures. After two weeks, the network activity was dominated by population bursts in most cultures. In contrast to previous reports, development continued with changing burst patterns throughout the observation period. Burst patterns were extremely varied, with inter-burst intervals between 1 and 300 s, different amounts of temporal clustering of bursts, and different firing rate profiles during bursts. During certain stages of development bursts were organized into tight clusters with highly conserved internal structure. Dissociated cultures of cortical cells exhibited a much richer repertoire of activity patterns than previously reported. Except for the very sparsest cultures, all cultures exhibited globally synchronized bursts, but bursting patterns changed over the course of development, and varied considerably between preparations. This emphasizes the importance of using multiple preparations – not just multiple cultures from one preparation – in any study involving neuronal cultures. These results are based on 963 half-hour-long recordings. To encourage further investigation of the rich range of behaviors exhibited by cortical cells in vitro, we are making the data available to other researchers, together with Matlab code to facilitate access.

Effect of electronic polarization on charge-transport parameters in molecular organic semiconductors.

Abstract: Theoretical investigations of charge transport in organic materials are generally based on the "energy splitting in dimer" method and routinely assume that the transport parameters (site energies and transfer integrals) determined from monomer and dimer calculations can be reliably used to describe extended systems. Here, we demonstrate that this transferability can fail even in molecular crystals with weak van der Waals intermolecular interactions, due to the substantial (but often ignored) impact of polarization effects, particularly on the site energies. We show that the neglect of electronic polarization leads to qualitatively incorrect values and trends for the transfer integrals computed with the energy splitting method, even in simple prototypes such as ethylene or pentacene dimers. The polarization effect in these systems is largely electrostatic in nature and can change dramatically upon transition from a dimer to an extended system. For example, the difference in site energy for a prototypical "face-to-edge" one-dimensional stack of pentacene molecules is calculated to be 30% greater than that in the "face-to-edge" dimer, whereas the site energy difference in the pentacene crystal is vanishingly small. Importantly, when computed directly in the framework of localized monomer orbitals, the transfer integral values for dimer and extended systems are very similar.

High-Accuracy Quantum Mechanical Studies of π−π Interactions in Benzene Dimers

Abstract: Although supramolecular chemistry and noncovalent interactions are playing an increasingly important role in modern chemical research, a detailed understanding of prototype noncovalent interactions remains lacking. In particular, π−π interactions, which are ubiquitous in biological systems, are not fully understood in terms of their strength, geometrical dependence, substituent effects, or fundamental physical nature. However, state-of-the-art quantum chemical methods are beginning to provide answers to these questions. Coupled-cluster theory through perturbative triple excitations in conjunction with large basis sets and extrapolations to the complete basis set limit have provided definitive results for the binding energy of several configurations of the benzene dimer, and benchmark-quality ab initio potential curves are being used to calibrate new density functional and force-field models for π−π interactions. Studies of substituted benzene dimers indicate flaws in the conventional wisdom about substitu...

Wireless underground sensor networks: Research challenges

Abstract: This work introduces the concept of a Wireless Underground Sensor Network (WUSN). WUSNs can be used to monitor a variety of conditions, such as soil properties for agricultural applications and toxic substances for environmental monitoring. Unlike existing methods of monitoring underground conditions, which rely on buried sensors connected via wire to the surface, WUSN devices are deployed completely belowground and do not require any wired connections. Each device contains all necessary sensors, memory, a processor, a radio, an antenna, and a power source. This makes their deployment much simpler than existing underground sensing solutions. Wireless communication within a dense substance such as soil or rock is, however, significantly more challenging than through air. This factor, combined with the necessity to conserve energy due to the difficulty of unearthing and recharging WUSN devices, requires that communication protocols be redesigned to be as efficient as possible. This work provides an extensive overview of applications and design challenges for WUSNs, challenges for the underground communication channel including methods for predicting path losses in an underground link, and challenges at each layer of the communication protocol stack. � 2006 Elsevier B.V. All rights reserved.