Основы наноелектроники / Основы наноэлектроники / ИДЗ / Книги и монографии / Наноматериалы, методы, идеи. Сборник научных статей, 2007, c.206

Nanotechnology and Nanoscience:

Science and Engineering in the 21st Century

Jingyue Liu and Thomas F. George

Center for Nanoscience, Department of Chemistry & Biochemistry and Department of Physics & Astronomy, University of Missouri St. Louis St. Louis, Missouri 63121, USA

Nanotechnology is dubbed to provide solutions to the world’s 21st century demands: alternative energy, clean environment, un-met medical needs, and sustainable development and manufacturing. The societal and economic impact of nanotechnology is enormous. The U.S. National Science Foundation stated in its report on “Societal Implications of Nanoscience and Nanotechnology” that the nanotechnology market could reach about $1 trillion by 2015 and that millions of scientists, engineers and technologists would be needed in this new field [1]. The intensive development of nanoscale technologies is going to generate many disruptive technologies which will replace the current technologies and manufacturing practices. Nanotechnology opens up new opportunities for improving the performance of existing products, provides new nanoscale materials with novel or exceptional properties, and enriches our knowledge of nature and life [2]. Applications include optoelectronics and electronic components, ultrasensitive sensors, pharmaceuticals and medicine, agricultural and food chains, and protecting the environment.

Nanoscience is the study of fundamental phenomena on the nanometer scale (~ 1-100 nanometers). Nanotechnology, on the other hand, refers to creating and controlling building blocks on the nanometer scale with the ultimate goal of fabricating systems that have specific desired properties or functions. Nanoscience provides a critical bridge between physical and life sciences; at the nanoscale, all natural sciences converge. For example, atoms and molecules, the fundamental building blocks of nature with dimensions on the nanometer scale, are the focus of research in chemistry and related fields [3,4]. Promising materials include various forms of carbon, like nanotubes and diamondoids [5].

Perhaps the newest frontier in nanoscience/technology is in biology and medicine. The proper self-assembly of atoms and

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molecules on the nanometer scale, however, provides the biological function of complex systems that nature has created to support life on earth. The fundamental understanding of selfor assisted-assembly of atoms and molecules thus provides insights into the nature of biology. The possibility to exploit structures and processes of biomolecules and nanoscale biosystems for novel functional materials, biosensors, bioelectronics and medical applications has created a rapidly-growing field of nanobiotechnology. Applications of new microor nanosystems and devices to understanding biological functions at a subcellular or molecular level will have a profound impact on biological research, disease diagnostics and therapeutics, and medical procedures. Nanoscience has the potential to improve the current understanding of nature and life and is a prerequisite of nanotechnology which can help develop new manufacturing tools, new medical procedures, and, to a certain degree, even new ways of defining societal relationships.

Although the impact of nanoscience and nanotechnology on the quality of life is undoubtedly positive, one should also pay due attention to the possible negative impact of nanotechnology. For example, the toxicity and environmental issues of new nanoscale materials should be thoroughly investigated before any large-scale manufacturing occurs. The long-term impact of novel nanomaterials on nature and life should be considered and evaluated.

[1]M. C. Roco and W. S. Bainbridge, Editors, Nanoscience, Engineering and Technology Workshop Report on “Societal Implications of Nanoscience and Nanotechnology,” (National Science Foundation, Arlington, Virginia, 2001), 280 pages; http://www.wtec.org/loyola/nano/NSET.Societal.Implications.

[2]G. A. Mansoori, Principles of Nanotechnology (World Scientific, Singapore, 2005), 357 pages.

[3]G. A. Mansoori, T. F. George, L. Assoufid and G. P. Zhang, Editors, Molecular Building Blocks for Nanotechnology: From Diamondoids to Nanoscale Materials and Applications

(Springer, New York, 2007), Topics in Applied Physics, Volume 109, 440 pages.

[4]L. Tilstra, S. A. Broughton, R. S. Tanke, D. Jelski, V. A. French, G. P. Zhang, A. K. Popov, A. B. Western and T. F. George, The

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Science of Nanotechnology: An Introductory Text (Nova Science Publishers, Hauppauge, New York, 2007), in press.

[5]G. A. Mansoori, T. F. George, G. P. Zhang and L. Assoufid, “Structure and Opto-Electronic Behavior of Diamondoids, with Applications as MEMS and at the Nanoscale Level,” in

Nanotechnology Research Advances (Nova Science Publishers, Hauppauge, New York, 2007), in press

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Coherent control of light via plasmon driven electromagnetic fields Maxim Sukharev and Tamar Seideman

Department of Chemistry, Northwestern University

2145 Sheridan Road, Evanston, IL 6028-3113, USA

Abstract

Several concepts of coherent control are extended to manipulate light propagating along metal nano-particle arrays. A phase-polarization control strategy is proposed and applied to control the electromagnetic energy transport via nano-array constructs with multiple branching intersections, leading to an optical switch or inverter far below the diffraction limit. The proposed schemes are also used to better understand the physics underlying the phenomenon of electromagnetic energy transport via metal nano-constructs. Several applications of the phase-polarization strategy are considered.

1. Introduction

Optical waveguide technology such as optical fiber communication systems, planar waveguides, and photonic crystals are well-understood constructs that can efficiently guide an electromagnetic (EM) energy at optical frequencies in the microscale. Further miniaturization of optical devices as required by emerging technologies, however, require the manipulation of EM radiation in length scales well below the diffraction limit. Control of light propagation in the nano-domain is a rewarding challenge, due to both the new fundamental questions involved and the variety of potential applications of optical and optoelectronic nanodevices [1-4]. A method to that end was proposed several years ago [5], based on the combination of the surface plasmon resonance (SPR) phenomenon and the strong EM coupling between closely spaced metal nano-particles (NPs). Noble metal NPs are known to exhibit SPR in the visible region [6]. The underlying principles trace back to the early work of Mie [7], in which he considered the scattering of EM radiation by small spherical particles. The extinction cross section in the quasi-static regime (R<<λ) is described by the following expression [8]:

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where R denotes the particle radius, m is the dielectric constant of the embedding medium, λ is the wavelength of the incident field, and

function of the particle material, respectively. The cross section (1) exhibits a resonance at a wavelength λSPR, when the first term in the

denominator vanishes, Re 2 m , (the Fröhlich condition). The

physical picture responsible for the SPR is well-understood [8]. Due to the small size of a metal particle in comparison with the incident wavelength, conduction electrons are excited and oscillate in phase throughout the particle volume, resulting in the accumulation of polarization charges on the particle surface. This leads to large induced polarization currents and, hence, strong EM fields localized on a surface of a particle. In the case of a metal NP array, propagation of the excitation along the construct is due to near-field coupling between closely spaced particles [9].

The Fröhlich condition for SPR clearly depends on a wide range of parameters such as the shape of individual NPs, their material, environment, and incident field characteristics. Tremendous progress in the development of fabrication methods of nano-constructs achieved during last decade allows these parameters to be tuned with the high precision [3, 10, 11]. This invites the application of coherent control techniques to manipulate light propagation along NP arrays through phase interference.

Coherent control method [12 – 14] have been successfully applied to systems ranging from atomic physics and femtochemistry, through solid-state physics and semiconductor device technology, to solution chemistry and biology. One approach of specific interest is the optimal control scheme proposed by Judson and Rabtiz [15], where iterative buildup of the spectral composition of the laser pulse is applied to drive a quantum system to a pre-specified target state [16]. Genetic and evolutionary algorithms, widely used in such experiments as black box strategies for searching for optimal solutions, often contain new insights

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regarding the system dynamics. Optimal control techniques can be applied, at least in principle, also to classical systems such as optical devices. Genetic algorithm (GA) optimization procedures along with Monte Carlo technique and simulated annealing have been applied to problems in fields ranging from economics to engineering and artificial intelligence as well as electromagnetics [17]. Successful applications of GA to the design of antenna design and of layered electromagnetic devices, for instance, has been reported [18, 19]. The coherence properties of lasers, however, the property underlying the success of the field of quantum coherent control [12 – 14] has not been utilized in electromagnetics as yet.

Here we propose and illustrate numerically the application of phase and polarization control approach to guide light in the nanoscale via metal NP arrays. We illustrate the possibility to efficiently control the EM energy transfer along metal NP arrays using only the phase and polarization of an incident field. Utilizing the fact that SPR is a fully coherent phenomenon, we show that in nano-arrays with multiple intersections a controllable superposition of longitudinal and transverse plasmons can be excited, leading to control over the branching of the electromagnetic energy at the array intersections with high efficiency.

2. Computational Approach

The EM energy transport is simulated using a finite-difference timedomain method (FDTD) (Yee’s scheme) [20] to solve the Maxwell equations:

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dielectric permittivity, , within the Drude model [21]. In all

simulations we consider silver nano-particles in vacuum. In the

wavelength range considered ( 300 −500 nm) the dielectric constant of

radius of the spheres is 25 nm, the semiaxes of the ellipsoids are 35 and 25 nm, and the center-to-center distance between spherical particles is 75 nm. We use the cylindrical symmetry of the experiment in mind to

restrict attention to two (x and y) E-components and one (z) H - component (TEz-mode). As an incident source we implement a pointwise elliptically polarized electric field:

is used in the calculations below. Since our approach is based on resonance effects, control improve with , saturating as converges to the resonance lifetime. In order to prevent numerical reflections of waves from the boundaries of the finite spatial grid, we implement PML absorbing boundary conditions. In all simulations we use twodimensional grids ranging from (x, y) = −850 nm to 850 nm. The results are converged to within 0.5% with spatial grid steps dx = dy = 1.1 nm and a temporal step dt=dx/(31/2c), where c denotes the speed of light in vacuum.

Within Yee’s scheme, space is first divided into squares, assumed, for simplicity, to be of equal size [20]. This discretization of space leads to a representation of the Maxwell equations (2) by a set of finitedifference equations. Time propagation of these equations is performed by a leapfrogging technique,20 where all electric field and current

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density components in the modeled space are calculated and stored in memory at each time step using previously stored H -data. With

knowledge of the E-components, all H -components are computed and stored in memory for use in the next time step. The time-stepping process is continued until a predetermined final time has been reached. The calculations are performed in parallel, uniformly distributed among the available processors with respect to the second index j of each component of the EM field and current density. We follow the domain decomposition technique and use message passing interface (MPI) subroutines. All simulations have been performed on distributed memory parallel computers at the National Energy Research Scientific Computing Center and San Diego Supercomputer Center.

3. Phase-Polarization Control Approach

In this section we illustrate the possibility to guide the EM energy into one or the other of two branches of symmetric T- and X-junctions solely by wave interference. The inset of Fig. 1 depicts schematically the T-junction, showing the spatial positions of the incident source (LS) and two detectors (D1, D2). The main frame of Fig. 1 shows (on a logarithmic scale) the ratio of the time averaged EM energies, W1/W2, detected at the upper (D1) and lower (D2) detection points as a function of the polarization parameters, and , at the incident wavelength corresponding to the one of two SPRs (λSPR =300 nm). We note here that the transmission spectrum of the system (the time averaged EM energy at a detector Dn as a function of the incident wavelength) exhibits a double-peak behavior for the elliptically polarized excitation, which the widely used model of interacting Hertzian dipoles [21] does not predict, suggesting the significance of quadrupole interactions between NPs.

In the case of linear polarized source, W1/W2= 1, while nonlinear polarization of LS allows efficient (by two orders of magnitude for the pulse of 15 fs) control over the branching ratio. The physics underlying the phase and polarization control can be understood by study of the time evolution of the EM energy propagation. Essential to our finding is the excitation of a coherent superposition of transverse and longitudinal plasmon modes, whose relative phase and spatial distribution are adjusted by the polarization parameters, and , of the incident field.

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