11 resultados para engineered nanoparticle

em Massachusetts Institute of Technology


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The goal of this research is to develop the prototype of a tactile sensing platform for anthropomorphic manipulation research. We investigate this problem through the fabrication and simple control of a planar 2-DOF robotic finger inspired by anatomic consistency, self-containment, and adaptability. The robot is equipped with a tactile sensor array based on optical transducer technology whereby localized changes in light intensity within an illuminated foam substrate correspond to the distribution and magnitude of forces applied to the sensor surface plane. The integration of tactile perception is a key component in realizing robotic systems which organically interact with the world. Such natural behavior is characterized by compliant performance that can initiate internal, and respond to external, force application in a dynamic environment. However, most of the current manipulators that support some form of haptic feedback either solely derive proprioceptive sensation or only limit tactile sensors to the mechanical fingertips. These constraints are due to the technological challenges involved in high resolution, multi-point tactile perception. In this work, however, we take the opposite approach, emphasizing the role of full-finger tactile feedback in the refinement of manual capabilities. To this end, we propose and implement a control framework for sensorimotor coordination analogous to infant-level grasping and fixturing reflexes. This thesis details the mechanisms used to achieve these sensory, actuation, and control objectives, along with the design philosophies and biological influences behind them. The results of behavioral experiments with a simple tactilely-modulated control scheme are also described. The hope is to integrate the modular finger into an %engineered analog of the human hand with a complete haptic system.

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We present a technique for the rapid and reliable evaluation of linear-functional output of elliptic partial differential equations with affine parameter dependence. The essential components are (i) rapidly uniformly convergent reduced-basis approximations — Galerkin projection onto a space WN spanned by solutions of the governing partial differential equation at N (optimally) selected points in parameter space; (ii) a posteriori error estimation — relaxations of the residual equation that provide inexpensive yet sharp and rigorous bounds for the error in the outputs; and (iii) offline/online computational procedures — stratagems that exploit affine parameter dependence to de-couple the generation and projection stages of the approximation process. The operation count for the online stage — in which, given a new parameter value, we calculate the output and associated error bound — depends only on N (typically small) and the parametric complexity of the problem. The method is thus ideally suited to the many-query and real-time contexts. In this paper, based on the technique we develop a robust inverse computational method for very fast solution of inverse problems characterized by parametrized partial differential equations. The essential ideas are in three-fold: first, we apply the technique to the forward problem for the rapid certified evaluation of PDE input-output relations and associated rigorous error bounds; second, we incorporate the reduced-basis approximation and error bounds into the inverse problem formulation; and third, rather than regularize the goodness-of-fit objective, we may instead identify all (or almost all, in the probabilistic sense) system configurations consistent with the available experimental data — well-posedness is reflected in a bounded "possibility region" that furthermore shrinks as the experimental error is decreased.

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The discontinuities in the solutions of systems of conservation laws are widely considered as one of the difficulties in numerical simulation. A numerical method is proposed for solving these partial differential equations with discontinuities in the solution. The method is able to track these sharp discontinuities or interfaces while still fully maintain the conservation property. The motion of the front is obtained by solving a Riemann problem based on the state values at its both sides which are reconstructed by using weighted essentially non oscillatory (WENO) scheme. The propagation of the front is coupled with the evaluation of "dynamic" numerical fluxes. Some numerical tests in 1D and preliminary results in 2D are presented.

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We present an immersed interface method for the incompressible Navier Stokes equations capable of handling rigid immersed boundaries. The immersed boundary is represented by a set of Lagrangian control points. In order to guarantee that the no-slip condition on the boundary is satisfied, singular forces are applied on the fluid at the immersed boundary. The forces are related to the jumps in pressure and the jumps in the derivatives of both pressure and velocity, and are interpolated using cubic splines. The strength of singular forces is determined by solving a small system of equations at each time step. The Navier-Stokes equations are discretized on a staggered Cartesian grid by a second order accurate projection method for pressure and velocity.

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In this paper a precorrected FFT-Fast Multipole Tree (pFFT-FMT) method for solving the potential flow around arbitrary three dimensional bodies is presented. The method takes advantage of the efficiency of the pFFT and FMT algorithms to facilitate more demanding computations such as automatic wake generation and hands-off steady and unsteady aerodynamic simulations. The velocity potential on the body surfaces and in the domain is determined using a pFFT Boundary Element Method (BEM) approach based on the Green’s Theorem Boundary Integral Equation. The vorticity trailing all lifting surfaces in the domain is represented using a Fast Multipole Tree, time advected, vortex participle method. Some simple steady state flow solutions are performed to demonstrate the basic capabilities of the solver. Although this paper focuses primarily on steady state solutions, it should be noted that this approach is designed to be a robust and efficient unsteady potential flow simulation tool, useful for rapid computational prototyping.

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We study the preconditioning of symmetric indefinite linear systems of equations that arise in interior point solution of linear optimization problems. The preconditioning method that we study exploits the block structure of the augmented matrix to design a similar block structure preconditioner to improve the spectral properties of the resulting preconditioned matrix so as to improve the convergence rate of the iterative solution of the system. We also propose a two-phase algorithm that takes advantage of the spectral properties of the transformed matrix to solve for the Newton directions in the interior-point method. Numerical experiments have been performed on some LP test problems in the NETLIB suite to demonstrate the potential of the preconditioning method discussed.

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Much effort has been devoted to the synthesis of gold nanoparticles with different shapes, including the zero-dimensional nanospheres, one dimensional nanorods, and two-dimensional nanoplates. Compared to zero or one dimensional nanostructures, the synthesis of two-dimensional nanostructures in high yield has always been more involved, often requiring complex and time-consuming steps such as morphology transformation from the nanospheres, or the seeded growth process. Herein we report a high yield method for gold nanoplate synthesis using the extract of unicellular green alga Chlorella vulgaris, which can be carried out under ambient conditions. More than 90% of the total nanoparticle population is of the platelet morphology, surpassing the previously reported value of 45%. The control of the anisotropic growth of different planes; as well as the lateral size, has also been partially optimized.

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We have discovered that the current protocols to assemble Au nanoparticles based on DNA hybridization do not work well with the small metal nanoparticles (e.g. 5 nm Au, 3.6 nm Pt and 3.2 nm Ru particles). Further investigations revealed the presence of strong interaction between the oligonucleotide backbone and the surface of the small metal nanoparticles. The oligonucleotides in this case are recumbent on the particle surface and are therefore not optimally oriented for hybridization. The nonspecific adsorption of oligonucleotides on small metal nanoparticles must be overcome before DNA hybridization can be accepted as a general assembly method. Two methods have been suggested as possible solutions to this problem. One is based on the use of stabilizer molecules which compete with the oligonucleotides for adsorption on the metal nanoparticle surface. Unfortunately, the reported success of this approach in small Au nanoparticles (using K₂BSPP) and Au films (using 6-mercapto-1-hexanol) could not be extended to the assembly of Pt and Ru nanoparticles by DNA hybridization. The second approach is to simply use larger metal particles. Indeed most reports on the DNA hybridization induced assembly of Au nanoparticles have made use of relatively large particles (>10 nm), hinting at a weaker non-specific interaction between the oligonucleotides and large Au nanoparticles. However, most current methods of nanoparticle synthesis are optimized to produce metal nanoparticles only within a narrow size range. We find that core-shell nanoparticles formed by the seeded growth method may be used to artificially enlarge the size of the metal particles to reduce the nonspecific binding of oligonucleotides. We demonstrate herein a core-shell assisted growth method to assemble Pt and Ru nanoparticles by DNA hybridization. This method involves firstly synthesizing approximately 16 nm core-shell Ag-Pt and 21 nm core-shell Au-Ru nanoparticles from 9.6 nm Ag seeds and 17.2 nm Au seeds respectively by the seed-mediated growth method. The core-shell nanoparticles were then functionalized by complementary thiolated oligonucleotides followed by aging in 0.2 M PBS buffer for 6 hours. The DNA hybridization induced bimetallic assembly of Pt and Ru nanoparticles could then be carried out in 0.3 M PBS buffer for 10 hours.

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Magnetic nanoparticles attract increasing attention because of their current and potential biomedical applications, such as, magnetically targeted and controlled drug delivery, magnetic hyperthermia and magnetic extraction. Increased magnetization can lead to improved performance in targeting and retention in drug delivery and a higher efficiency in biomaterials extraction. We reported an approach to synthesize iron contained magnetic nanoparticles with high magnetization and good oxidation resistibility by pyrolysis of iron pentacarbonyl (Fe(CO)[subscript 5]) in methane (CH[subscript 4]). Using the high reactivity of Fe nanoparticles, decomposition of CH[subscript 4] on the Fe nanoparticles leads to the formation of nanocrystalline iron carbides at a temperature below 260°C. Structural investigation indicated that the as-synthesized nanoparticles contained crystalline bcc Fe, iron carbides and spinel iron oxide. The Mössbauer and DSC results testified that the as-synthesized nanoparticle contained three crystalline iron carbide phases, which converted to Fe[subscript 3]C after a heat treatment. Surface analysis suggested that the as-synthesized and subsequently heated iron-iron carbide particles were coated by iron oxide, which originated from oxidization of surface Fe atoms. The heat-treated nanoparticles exhibited a magnetization of 160 emu/g, which is two times of that of currently used spinel iron oxide nanoparticles. After heating in an acidic solution with a pH value of 5 at 60°C for 20 h, the nanoparticles retained 90 percentage of the magnetization.

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This work presents detailed numerical calculations of the dielectrophoretic force in octupolar traps designed for single-cell trapping. A trap with eight planar electrodes is studied for spherical and ellipsoidal particles using an indirect implementation of the boundary element method (BEM). Multipolar approximations of orders one to three are compared with the full Maxwell stress tensor (MST) calculation of the electrical force on spherical particles. Ellipsoidal particles are also studied, but in their case only the dipolar approximation is available for comparison with the MST solution. The results show that the full MST calculation is only required in the study of non-spherical particles.

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In this paper, a new methodology for predicting fluid free surface shape using Model Order Reduction (MOR) is presented. Proper Orthogonal Decomposition combined with a linear interpolation procedure for its coefficient is applied to a problem involving bubble dynamics near to a free surface. A model is developed to accurately and efficiently capture the variation of the free surface shape with different bubble parameters. In addition, a systematic approach is developed within the MOR framework to find the best initial locations and pressures for a set of bubbles beneath the quiescent free surface such that the resultant free surface attained is close to a desired shape. Predictions of the free surface in two-dimensions and three-dimensions are presented.