Showing papers by "Rensselaer Polytechnic Institute published in 2011"

Antifouling coatings: recent developments in the design of surfaces that prevent fouling by proteins, bacteria, and marine organisms.

Abstract: The major strategies for designing surfaces that prevent fouling due to proteins, bacteria, and marine organisms are reviewed. Biofouling is of great concern in numerous applications ranging from biosensors to biomedical implants and devices, and from food packaging to industrial and marine equipment. The two major approaches to combat surface fouling are based on either preventing biofoulants from attaching or degrading them. One of the key strategies for imparting adhesion resistance involves the functionalization of surfaces with poly(ethylene glycol) (PEG) or oligo(ethylene glycol). Several alternatives to PEG-based coatings have also been designed over the past decade. While protein-resistant coatings may also resist bacterial attachment and subsequent biofilm formation, in order to overcome the fouling-mediated risk of bacterial infection it is highly desirable to design coatings that are bactericidal. Traditional techniques involve the design of coatings that release biocidal agents, including antibiotics, quaternary ammonium salts (QAS), and silver, into the surrounding aqueous environment. However, the emergence of antibiotic- and silver-resistant pathogenic strains has necessitated the development of alternative strategies. Therefore, other techniques based on the use of polycations, enzymes, nanomaterials, and photoactive agents are being investigated. With regard to marine antifouling coatings, restrictions on the use of biocide-releasing coatings have made the generation of nontoxic antifouling surfaces more important. While considerable progress has been made in the design of antifouling coatings, ongoing research in this area should result in the development of even better antifouling materials in the future.

Impedance-Based Stability Criterion for Grid-Connected Inverters

Abstract: Grid-connected inverters are known to become unstable when the grid impedance is high. Existing approaches to analyzing such instability are based on inverter control models that account for the grid impedance and the coupling with other grid-connected inverters. A new method to determine inverter-grid system stability using only the inverter output impedance and the grid impedance is developed in this paper. It will be shown that a grid-connected inverter will remain stable if the ratio between the grid impedance and the inverter output impedance satisfies the Nyquist stability criterion. This new impedance-based stability criterion is a generalization to the existing stability criterion for voltage-source systems, and can be applied to all current-source systems. A single-phase solar inverter is studied to demonstrate the application of the proposed method.

Ultrathin Planar Graphene Supercapacitors

Abstract: With the advent of atomically thin and flat layers of conducting materials such as graphene, new designs for thin film energy storage devices with good performance have become possible. Here, we report an “in-plane” fabrication approach for ultrathin supercapacitors based on electrodes comprised of pristine graphene and multilayer reduced graphene oxide. The in-plane design is straightforward to implement and exploits efficiently the surface of each graphene layer for energy storage. The open architecture and the effect of graphene edges enable even the thinnest of devices, made from as grown 1−2 graphene layers, to reach specific capacities up to 80 μFcm−2, while much higher (394 μFcm−2) specific capacities are observed multilayer reduced graphene oxide electrodes. The performances of devices with pristine as well as thicker graphene-based structures are examined using a combination of experiments and model calculations. The demonstrated all solid-state supercapacitors provide a prototype for a broad ran...

A large-scale benchmark dataset for event recognition in surveillance video

Abstract: We introduce a new large-scale video dataset designed to assess the performance of diverse visual event recognition algorithms with a focus on continuous visual event recognition (CVER) in outdoor areas with wide coverage. Previous datasets for action recognition are unrealistic for real-world surveillance because they consist of short clips showing one action by one individual [15, 8]. Datasets have been developed for movies [11] and sports [12], but, these actions and scene conditions do not apply effectively to surveillance videos. Our dataset consists of many outdoor scenes with actions occurring naturally by non-actors in continuously captured videos of the real world. The dataset includes large numbers of instances for 23 event types distributed throughout 29 hours of video. This data is accompanied by detailed annotations which include both moving object tracks and event examples, which will provide solid basis for large-scale evaluation. Additionally, we propose different types of evaluation modes for visual recognition tasks and evaluation metrics along with our preliminary experimental results. We believe that this dataset will stimulate diverse aspects of computer vision research and help us to advance the CVER tasks in the years ahead.

Toughening in graphene ceramic composites.

Abstract: The majority of work in graphene nanocomposites has focused on polymer matrices. Here we report for the first time the use of graphene to enhance the toughness of bulk silicon nitride ceramics. Ceramics are ideally suited for high-temperature applications but suffer from poor toughness. Our approach uses graphene platelets (GPL) that are homogeneously dispersed with silicon nitride particles and densified, at ∼1650 °C, using spark plasma sintering. The sintering parameters are selected to enable the GPL to survive the harsh processing environment, as confirmed by Raman spectroscopy. We find that the ceramic's fracture toughness increases by up to ∼235% (from ∼2.8 to ∼6.6 MPa·m(1/2)) at ∼1.5% GPL volume fraction. Most interestingly, novel toughening mechanisms were observed that show GPL wrapping and anchoring themselves around individual ceramic grains to resist sheet pullout. The resulting cage-like graphene structures that encapsulate the individual grains were observed to deflect propagating cracks in not just two but three dimensions.

A Survey of Link Prediction in Social Networks

Abstract: Link prediction is an important task for analying social networks which also has applications in other domains like, information retrieval, bioinformatics and e-commerce There exist a variety of techniques for link prediction, ranging from feature-based classification and kernel-based method to matrix factorization and probabilistic graphical models These methods differ from each other with respect to model complexity, prediction performance, scalability, and generalization ability In this article, we survey some representative link prediction methods by categorizing them by the type of the models We largely consider three types of models: first, the traditional (non-Bayesian) models which extract a set of features to train a binary classification model Second, the probabilistic approaches which model the joint-probability among the entities in a network by Bayesian graphical models And, finally the linear algebraic approach which computes the similarity between the nodes in a network by rank-reduced similarity matrices We discuss various existing link prediction models that fall in these broad categories and analyze their strength and weakness We conclude the survey with a discussion on recent developments and future research direction

High Sensitivity Gas Detection Using a Macroscopic Three-Dimensional Graphene Foam Network

Abstract: Nanostructures are known to be exquisitely sensitive to the chemical environment and offer ultra-high sensitivity for gas-sensing. However, the fabrication and operation of devices that use individual nanostructures for sensing is complex, expensive and suffers from poor reliability due to contamination and large variability from sample-to-sample. By contrast, conventional solid-state and conducting-polymer sensors offer excellent reliability but suffer from reduced sensitivity at room-temperature. Here we report a macro graphene foam-like three-dimensional network which combines the best of both worlds. The walls of the foam are comprised of few-layer graphene sheets resulting in high sensitivity; we demonstrate parts-per-million level detection of NH3 and NO2 in air at room-temperature. Further, the foam is a mechanically robust and flexible macro-scale network that is easy to contact (without Lithography) and can rival the durability and affordability of traditional sensors. Moreover, Joule-heating expels chemisorbed molecules from the foam's surface leading to fully-reversible and low-power operation.

Nanograssed Micropyramidal Architectures for Continuous Dropwise Condensation

Abstract: Engineering the dropwise condensation of water on surfaces is critical in a wide range of applications from thermal management (e.g. heat pipes, chip cooling etc.) to water harvesting technologies. Surfaces that enable both effi cient droplet nucleation and droplet self-removal (i.e. droplet departure) are essential to accomplish successful dropwise condensation. However it is extremely challenging to design such surfaces. This is because droplet nucleation requires a wettable surface while droplet departure necessitates a super-hydrophobic surface. Here we report that these confl icting requirements can be satisfi ed using a hierarchical (multiscale) nanograssed micropyramid architecture that yield a gobal superhydrophobicity as well as locally wettable nucleation sites, allowing for ˜65% increase in the drop number density and ˜450% increase in the drop self-removal volume as compared to a superhydrophobic surface with nanostructures alone. Further we fi that synergistic co-operation between the hierarchical structures contributes directly to a continuous process of nucleation, coalescence, departure, and re-nucleation enabling sustained dropwise condensation over prolonged periods. Exploiting such multiscale coupling effects can open up novel and exciting vistas in surface engineering leading to optimal condensation surfaces for high performance electronics cooling and water condenser systems.

Faster least squares approximation

Abstract: Least squares approximation is a technique to find an approximate solution to a system of linear equations that has no exact solution. In a typical setting, one lets n be the number of constraints and d be the number of variables, with $${n \gg d}$$. Then, existing exact methods find a solution vector in O(nd 2) time. We present two randomized algorithms that provide accurate relative-error approximations to the optimal value and the solution vector of a least squares approximation problem more rapidly than existing exact algorithms. Both of our algorithms preprocess the data with the Randomized Hadamard transform. One then uniformly randomly samples constraints and solves the smaller problem on those constraints, and the other performs a sparse random projection and solves the smaller problem on those projected coordinates. In both cases, solving the smaller problem provides relative-error approximations, and, if n is sufficiently larger than d, the approximate solution can be computed in O(nd ln d) time.

Graphene–aluminum nanocomposites

Abstract: Composites of graphene platelets and powdered aluminum were made using ball milling, hot isostatic pressing and extrusion. The mechanical properties and microstructure were studied using hardness and tensile tests, as well as electron microscopy, X-ray diffraction and differential scanning calorimetry. Compared to the pure aluminum and multi-walled carbon nanotube composites, the graphene–aluminum composite showed decreased strength and hardness. This is explained in the context of enhanced aluminum carbide formation with the graphene filler.

Recent Advances in Modeling and Online Detection of Stator Interturn Faults in Electrical Motors

Abstract: Online fault diagnosis plays a crucial role in providing the required fault tolerance to drive systems used in safety-critical applications. Short-circuit faults are among the common faults occurring in electrical machines. This paper presents a review of existing techniques available for online stator interturn fault detection and diagnosis (FDD) in electrical machines. Special attention is given to short-circuit-fault diagnosis in permanent-magnet machines, which are fast replacing traditional machines in a wide variety of applications. Recent techniques that use signals analysis, models, or knowledge-based systems for FDD are reviewed in this paper. Motor current is the most commonly analyzed signal for fault diagnosis. Hence, motor current signature analysis is a topic of elaborate discussion in this paper. Additionally, parametric and finite-element models that were designed to simulate interturn-fault conditions are reviewed.

The oxidation state of Hadean magmas and implications for early Earth/'s atmosphere

Abstract: Magmatic outgassing of volatiles from Earth's interior probably played a critical part in determining the composition of the earliest atmosphere, more than 4,000 million years (Myr) ago. Given an elemental inventory of hydrogen, carbon, nitrogen, oxygen and sulphur, the identity of molecular species in gaseous volcanic emanations depends critically on the pressure (fugacity) of oxygen. Reduced melts having oxygen fugacities close to that defined by the iron-wustite buffer would yield volatile species such as CH(4), H(2), H(2)S, NH(3) and CO, whereas melts close to the fayalite-magnetite-quartz buffer would be similar to present-day conditions and would be dominated by H(2)O, CO(2), SO(2) and N(2) (refs 1-4). Direct constraints on the oxidation state of terrestrial magmas before 3,850 Myr before present (that is, the Hadean eon) are tenuous because the rock record is sparse or absent. Samples from this earliest period of Earth's history are limited to igneous detrital zircons that pre-date the known rock record, with ages approaching ∼4,400 Myr (refs 5-8). Here we report a redox-sensitive calibration to determine the oxidation state of Hadean magmatic melts that is based on the incorporation of cerium into zircon crystals. We find that the melts have average oxygen fugacities that are consistent with an oxidation state defined by the fayalite-magnetite-quartz buffer, similar to present-day conditions. Moreover, selected Hadean zircons (having chemical characteristics consistent with crystallization specifically from mantle-derived melts) suggest oxygen fugacities similar to those of Archaean and present-day mantle-derived lavas as early as ∼4,350 Myr before present. These results suggest that outgassing of Earth's interior later than ∼200 Myr into the history of Solar System formation would not have resulted in a reducing atmosphere.

SLPA: Uncovering Overlapping Communities in Social Networks via a Speaker-Listener Interaction Dynamic Process

Abstract: Overlap is one of the characteristics of social networks, in which a person may belong to more than one social group. For this reason, discovering overlapping structures is necessary for realistic social analysis. In this paper, we present a novel, general framework to detect and analyze both individual overlapping nodes and entire communities. In this framework, nodes exchange labels according to dynamic interaction rules. A specific implementation called Speaker-listener Label Propagation Algorithm (SLPA) demonstrates an excellent performance in identifying both overlapping nodes and overlapping communities with different degrees of diversity.

Constant-Power Load System Stabilization by Passive Damping

Abstract: This paper addresses stability problems in power systems with loads that exhibit constant-power behavior. Instability may occur in such systems due to the negative incremental impedance of constant-power loads (CPLs). Existing approaches to stabilizing such systems require modification of the source and/or the load control characteristics, or isolating the CPL from the rest of the system by additional active devices, which are difficult to implement and often conflict with other system requirements such as control bandwidth, size, weight, and cost. In this paper, we investigate passive damping as a general method to stabilize power systems with CPL. Using a representative system model consisting of a voltage source, an LC filter, and an ideal CPL, we demonstrate that a CPL system can be stabilized by a simple passive damping circuit added to one of the filter elements. Three different damping methods are considered and analytical models are developed for each method to define damping parameters required for stabilizing the system. Time- and frequency-domain measurements from an experimental system are presented to validate the methods.

Al-doped zinc oxide nanocomposites with enhanced thermoelectric properties.

Abstract: ZnO is a promising high figure-of-merit (ZT) thermoelectric material for power harvesting from heat due to its high melting point, high electrical conductivity σ, and Seebeck coefficient α, but its practical use is limited by a high lattice thermal conductivity κL. Here, we report Al-containing ZnO nanocomposites with up to a factor of 20 lower κL than non-nanostructured ZnO, while retaining bulklike α and σ. We show that enhanced phonon scattering promoted by Al-induced grain refinement and ZnAl2O4 nanoprecipitates presages ultralow κ ∼ 2 Wm −1 K–1 at 1000 K. The high α∼ −300 μV K–1 and high σ ∼ 1–104 Ω–1 m–1 result from an offsetting of the nanostructuring-induced mobility decrease by high, and nondegenerate, carrier concentrations obtained via excitation from shallow Al donor states. The resultant ZT ∼ 0.44 at 1000 K is 50% higher than that for the best non-nanostructured counterpart material at the same temperature and holds promise for engineering advanced oxide-based high-ZT thermoelectrics for appl...

Polysaccharides and phytochemicals: a natural reservoir for the green synthesis of gold and silver nanoparticles

Abstract: Currently, sustainability initiatives that use green chemistry to improve and/or protect our global environment are becoming focal issues in many fields of research. Instead of using toxic chemicals for the reduction and stabilisation of metallic nanoparticles, the use of various biological entities has received considerable attention in the field of nanobiotechnology. Among the many possible natural products, polysaccharides and biologically active plant products represent excellent scaffolds for this purpose. Polysaccharides have hydroxyl groups, a hemiacetal reducing end, and other functionalities that can play important roles in both the reduction and the stabilisation of metallic nanoparticles. Among the various categories of compounds in plants that have potent biological activities, phytochemicals are emerging as an important natural resource for the synthesis of metallic nanoparticles. The focus of this review is the application of polysaccharides and phytochemicals in the green synthesis of gold and silver nanoparticles to afford biocomposites with novel uses in nanomedicine and as nanocomposites.

Stage-specific signaling through TGFβ family members and WNT regulates patterning and pancreatic specification of human pluripotent stem cells

Abstract: The generation of insulin-producing β-cells from human pluripotent stem cells is dependent on efficient endoderm induction and appropriate patterning and specification of this germ layer to a pancreatic fate. In this study, we elucidated the temporal requirements for TGFβ family members and canonical WNT signaling at these developmental stages and show that the duration of nodal/activin A signaling plays a pivotal role in establishing an appropriate definitive endoderm population for specification to the pancreatic lineage. WNT signaling was found to induce a posterior endoderm fate and at optimal concentrations enhanced the development of pancreatic lineage cells. Inhibition of the BMP signaling pathway at specific stages was essential for the generation of insulin-expressing cells and the extent of BMP inhibition required varied widely among the cell lines tested. Optimal stage-specific manipulation of these pathways resulted in a striking 250-fold increase in the levels of insulin expression and yielded populations containing up to 25% C-peptide+ cells.

Graphene edges: a review of their fabrication and characterization

Abstract: The current status of graphene edge fabrication and characterization is reviewed in detail. We first compare different fabrication methods, including the chemical vapor deposition method, various ways of unzipping carbon nanotubes, and lithographic methods. We then summarize the different edge/ribbon structures that have been produced experimentally or predicted theoretically. We discuss different characterization tools, such as transmission electron microscopy and Raman spectroscopy, that are currently used for evaluating the edge quality as well as the atomic structures. Finally, a detailed discussion of defective and folded edges is also presented. Considering the short history of graphene edge research, the progress has been impressive, and many further advances in this field are anticipated.

Room Temperature Ionic Liquids as Emerging Solvents for the Pretreatment of Lignocellulosic Biomass

Abstract: Room temperature ionic liquids (RTILs) are emerging as attractive and green solvents for lignocellulosic biomass pretreatment. The unique solvating properties of RTILs foster the disruption of the 3D network structure of lignin, cellulose, and hemicellulose, which allows high yields of fermentable sugars to be produced in subsequent enzymatic hydrolysis. In the current review, we summarize the physicochemical properties of RTILs that make them effective solvents for lignocellulose pretreatment including mechanisms of interaction between lignocellulosic biomass subcomponents and RTILs. We also highlight several recent strategies that exploit RTILs and generate high yields of fermentable sugars suitable for downstream biofuel production, and address new opportunities for use of lignocellulosic components, including lignin. Finally, we address some of the challenges that remain before large-scale use of RTILs may be achieved.

Lattice Discrete Particle Model (LDPM) for failure behavior of concrete. I: Theory

Abstract: This paper deals with the formulation, calibration, and validation of the Lattice Discrete Particle Model (LDPM) suitable for the simulation of the failure behavior of concrete. LDPM simulates concrete at the meso-scale considered to be the length scale of coarse aggregate pieces. LDPM is formulated in the framework of discrete models for which the unknown displacement field is not continuous but only defined at a finite number of points representing the center of aggregate particles. Size and distribution of the particles are obtained according to the actual aggregate size distribution of concrete. Discrete compatibility and equilibrium equations are used to formulate the governing equations of the LDPM computational framework. Particle contact behavior represents the mechanical interaction among adjacent aggregate particles through the embedding mortar. Such interaction is governed by meso-scale constitutive equations simulating meso-scale tensile fracturing with strain-softening, cohesive and frictional shearing, and nonlinear compressive behavior with strain-hardening. The present, Part I, of this two-part study deals with model formulation leaving model calibration and validation to the subsequent Part II.

Chemoenzymatic Synthesis of Homogeneous Ultralow Molecular Weight Heparins

Abstract: Ultralow molecular weight (ULMW) heparins are sulfated glycans that are clinically used to treat thrombotic disorders. ULMW heparins range from 1500 to 3000 daltons, corresponding from 5 to 10 saccharide units. The commercial drug Arixtra (fondaparinux sodium) is a structurally homogeneous ULMW heparin pentasaccharide that is synthesized through a lengthy chemical process. Here, we report 10- and 12-step chemoenzymatic syntheses of two structurally homogeneous ULMW heparins (MW = 1778.5 and 1816.5) in 45 and 37% overall yield, respectively, starting from a simple disaccharide. These ULMW heparins display excellent in vitro anticoagulant activity and comparable pharmacokinetic properties to Arixtra, as demonstrated in a rabbit model. The chemoenzymatic approach is scalable and shows promise for a more efficient route to synthesize this important class of medicinal agent.

Social consensus through the influence of committed minorities.

Abstract: We show how the prevailing majority opinion in a population can be rapidly reversed by a small fraction p of randomly distributed committed agents who consistently proselytize the opposing opinion and are immune to influence. Specifically, we show that when the committed fraction grows beyond a critical value p(c) ≈ 10%, there is a dramatic decrease in the time T(c) taken for the entire population to adopt the committed opinion. In particular, for complete graphs we show that when p p(c), T(c) ~ ln N. We conclude with simulation results for Erdős-Renyi random graphs and scale-free networks which show qualitatively similar behavior.

Orchestration Processes in Network-Centric Innovation: Evidence From the Field

Abstract: Executive Overview Companies have increasingly shifted from innovation initiatives that are centered on internal resources to those that are centered on external networks (said another way, a shift from firm-centric innovation to network-centric innovation). In this paper, we combine insights from product development and network theory with evidence from an extensive field study to describe the nature of a hub firm's orchestration processes in network-centric innovation. Our analysis indicates that network orchestration processes reflect the interplay between elements of innovation design and network design. Promising directions for future research related to network-centric innovation are discussed.

Real time queue length estimation for signalized intersections using travel times from mobile sensors

Abstract: We study how to estimate real time queue lengths at signalized intersections using intersection travel times collected from mobile traffic sensors. The estimation is based on the observation that critical pattern changes of intersection travel times or delays, such as the discontinuities (i.e., sudden and dramatic increases in travel times) and non-smoothness (i.e., changes of slopes of travel times), indicate signal timing or queue length changes. By detecting these critical points in intersection travel times or delays, the real time queue length can be re-constructed. We first introduce the concept of Queue Rear No-delay Arrival Time which is related to the non-smoothness of queuing delay patterns and queue length changes. We then show how measured intersection travel times from mobile sensors can be processed to generate sample vehicle queuing delays. Under the uniform arrival assumption, the queuing delays reduce linearly within a cycle. The delay pattern can be estimated by a linear fitting method using sample queuing delays. Queue Rear No-delay Arrival Time can then be obtained from the delay pattern, and be used to estimate the maximum and minimum queue lengths of a cycle, based on which the real-time queue length curve can also be constructed. The model and algorithm are tested in a field experiment and in simulation.

Lattice Discrete Particle Model (LDPM) for failure behavior of concrete. II: Calibration and validation

Abstract: The Lattice Discrete Particle Model (LDPM) formulated in the preceding Part I of this study is calibrated and validated in the present Part II. Calibration and validation is performed by comparing the results of numerical simulations with experimental data gathered from the literature. Simulated experiments include uniaxial and multiaxial compression, tensile fracture, shear strength, and cycling compression tests.