58 research outputs found

    Nanowire Growth for Sensor Arrays

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    A design concept for nanowire-based sensors and arrays is described. The fabrication technique involves electrodeposition to directly grow nanowires between patterned thin film contact electrodes. To prove our concept, we have electrodeposited 1-mm diameter Pd single wires and small arrays. To demonstrate nanowire sensors, we have electrochemically grown metal (Pd, Au, Pt), metal oxide (Sb2O3), and conducting polymer (polyaniline) bundled nanowires. Using Pt bundled nanowires surface modified with glucose oxidase, we have demonstrated glucose detection as a demonstration of a biomolecular sensor.Comment: To appear in Nanofabrication Technologies, Ed. E. A. Dobisz, SPIE Proceedings 5220, pp. xxx (2003, in press

    Physico-electrochemical Characterization of Pluripotent Stem Cells during Self-Renewal or Differentiation by a Multi-modal Monitoring System.

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    Monitoring pluripotent stem cell behaviors (self-renewal and differentiation to specific lineages/phenotypes) is critical for a fundamental understanding of stem cell biology and their translational applications. In this study, a multi-modal stem cell monitoring system was developed to quantitatively characterize physico-electrochemical changes of the cells in real time, in relation to cellular activities during self-renewal or lineage-specific differentiation, in a non-destructive, label-free manner. The system was validated by measuring physical (mass) and electrochemical (impedance) changes in human induced pluripotent stem cells undergoing self-renewal, or subjected to mesendodermal or ectodermal differentiation, and correlating them to morphological (size, shape) and biochemical changes (gene/protein expression). An equivalent circuit model was used to further dissect the electrochemical (resistive and capacitive) contributions of distinctive cellular features. Overall, the combination of the physico-electrochemical measurements and electrical circuit modeling collectively offers a means to longitudinally quantify the states of stem cell self-renewal and differentiation

    Synthesis and Thermoelectric Characterization of Lead Telluride Hollow Nanofibers

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    Lead telluride (PbTe) nanofibers were fabricated by galvanic displacement of electrospun cobalt nanofibers where their composition and morphology were altered by adjusting the electrolyte composition and diameter of sacrificial cobalt nanofibers. By employing Co instead of Ni as the sacrificial material, residue-free PbTe nanofibers were synthesized. The Pb content of the PbTe nanofibers was slightly affected by the Pb2+ concentration in the electrolyte, while the average outer diameter increased with Pb2+ concentration. The surface morphology of PbTe nanofibers was strongly dependent on the diameter of sacrificial nanofibers where it altered from smooth to rough surface as the Pb2+ concentration increased. Some of thermoelectric properties [i.e., thermopower (S) and electrical conductivity(σ)] were systematically measured as a function of temperature. Energy barrier height (Eb) was found to be one of the key factors affecting the thermoelectric properties–that is, higher energy barrier heights increased the Seebeck coefficient, but lowered the electrical conductivity

    Non-destructive characterization of bone mineral content by machine learning-assisted electrochemical impedance spectroscopy

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    Continuous quantitative monitoring of the change in mineral content during the bone healing process is crucial for efficient clinical treatment. Current radiography-based modalities, however, pose various technological, medical, and economical challenges such as low sensitivity, radiation exposure risk, and high cost/instrument accessibility. In this regard, an analytical approach utilizing electrochemical impedance spectroscopy (EIS) assisted by machine learning algorithms is developed to quantitatively characterize the physico-electrochemical properties of the bone, in response to the changes in the bone mineral contents. The system is designed and validated following the process of impedance data measurement, equivalent circuit model designing, machine learning algorithm optimization, and data training and testing. Overall, the systematic machine learning-based classification utilizing the combination of EIS measurements and electrical circuit modeling offers a means to accurately monitor the status of the bone healing process

    Nanowire-Based Electrochemical Biosensors

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    We review recent advances in biosensors based on one‐dimensional (1‐D) nanostructure field‐effect transistors (FET). Specifically, we address the fabrication, functionalization, assembly/alignment and sensing applications of FET based on carbon nanotubes, silicon nanowires and conducting polymer nanowires. The advantages and disadvantages of various fabrication, functionalization, and assembling procedures of these nanosensors are reviewed and discussed. We evaluate how they have been used for detection of various biological molecules and how such devices have enabled the achievement of high sensitivity and selectivity with low detection limits. Finally, we conclude by highlighting some of the challenges researchers face in the 1‐D nanostructures research arena and also predict the direction toward which future research in this area might be directed
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