Project home page: http://www.lce.hut.fi/research/nanotech/.
The commercial integrated electronics is mainly based on silicon, while compound semiconductors (CS), e.g. gallium arsenide, are used in very special applications. For example light detectors, light emitters and very-high frequency devices are usually fabricated using CS due to the better optical and electron mobility properties of these materials. Quantum mechanical devices are a potential application for CS. For quantum mechanical operation phase coherence is crucial and it has been found difficult to obtain long phase coherence lengths in Si structures. This advantages of CS is due to both a different fabrication technique and different electronic properties. We are studying quantum effect electronics both in silicon and CS. The motivations are lower power consumption, faster operation and smaller device size.
The ever-decreasing size of the basic components of information processing will give quantum effects an important role in future technologies. Recent developments such as quantum cryptography and the idea of a quantum computer have shown that, rather than being only harmful, these effects can probably be utilized to a great extent. In communications technologies, optical transmission is setting the trend in the development of the networks. The full harnessing of the huge bandwidth provided by light still requires for replacing the switching, routing and processing electronics by all-optical components. Research on nonlinear optical materials and light-induced quantum effects will be crusial in the development of future all-optical processing technologies. Related to optical communications technology, we are studying all-optical swithing and processing using nonlinear materials, combined with novel material structures such as photonic crystals.
Recently started research of low power biomorphic neural circuits based on floating gate MOS and SET transistors has been continued. In this project neuro-MOS and neuro-SET based neural networks are developed and studied, especially for fast and power efficient signal processing. Neuro-MOS structures, includingMOS capacitor based, and neuro-SET structures, are studied and optimized in deep sub-micron line width processes. Power optimisation will be studied, based on physical and architectual ideas from extremely power-efficient biological neurons. New efficient algorithms utilizing the benefits of neuro-structures are developed. Models for simulation of neuro-SET structures are developed. The applicability of floating gate structures - either MOS or SET - to higher level neural architectures, e.g. recurrent or CNN, will be studied.
Researchers: Fredrik Boxberg, Roman Terechonkov and Jukka Tulkki
The commercial integrated electronics is mainly based on silicon, while compound semiconductors (CS), e.g. gallium arsenide, are used in very special applications. For example light detectors, light emitters and very-high frequency devices are usually fabricated using CS due to the better optical and electron mobility properties of these materials. Quantum mechanical devices are a potential application for CS. For quantum mechanical operation phase coherence is crucial and it has been found difficult to obtain long phase coherence lengths in Si structures. This advantages of CS is due to both a different fabrication technique and different electronic properties. We are studying quantum effect electronics both in silicon and CS. The motivations are lower power consumption, faster operation and smaller device size.
We are developing general tools for strain analysis, band structure calculations and the 33 modeling of photonic processes. The final aim is to model photonic and elctronic devices starting from the structural properties and ending up with more macroscopic properties like the light amplification in the device. We simulate the strain field using the finite element model and the electronic structure using the eight-band model. The materal gain of the laser device is obtained from a numerical integration scheme based on the electronic structure and Fermi distributions of the charge carriers. Hence, the optical properties rely completely on the underlying electronic bands, which in turn depend on the device geometry and crystal orientation.
In particular we have been modelling the material gain in quantum well lasers and its dependence on the polarization of the laser field. We have studied the effect of the carrier concentrations, the temperature, and the orientation of the QW etc. Figure 26(a) and (b) show the temperature dependence of the transverse magnetic (TM) and transverse electric (TE) field polarizations of the gain in a 10 nm wide, lattice-matched (001).
Our model could in future work be extended to dynamic photon and electron processes or many-particle simulations. These kind of simulations would be very valuable for the understanding and development of quantum information processes and related devices.
Figure 26: Material gain in a lattice-matched (001) QW for (a) TM and (b) TE polarizations. The insets show the definitions of the polarization with respect to the quantum well (QW) plane. |
The electronic and optical properties of semiconductor quantum structures are governed by the band structure. The band structure can be used to calculate the transition matrix elements, for example, which then can be used to predict the intensity of photoemission as a function of the wave length and excitation ( injection ) intensity.
The accurate band structure calculations are computationally very intensive. The smart band structure model, discretization and code parallelization are needed for effective electronic structure calculations. The electronic structure of the semiconductor quantum structures we calculate using the eight-band method. In the confinement potential we account for the band edge discontinuity, strain induced deformation potential and piezoelectric potential.
It was observed that for some semiconductor structures the 8-band method gives spurious non-physical eigenstates in addition to the real physical. On the basis of numerical experiments we found that the origin of the non-physical solutions is in the use of 8-band Hamiltonian which is valid close to the -point only. A consistent generic solution of this problem would be to start from a full band model and to use it as the starting point of the envelope wave function method but this requires much more computational resources. We found that it is possible to find tune the material parameters in such a way that the bulk dispersion fits the experiment very and at the same time the spurious states are excluded. This method makes the problem to be computationally feasible.
Fig. 27(a) shows the schematic drawing of the corrugated quantum well embedded in . We used the PARPACK library to diagonalize the Hamiltonian matrix discribing this structure. Fig. 27(b) shows the electron probability density functions calculated for the ground conduction (CB) and valence (VB) band states with confinement energies 0.164 eV and 0.122 eV, correspondingly. Fig. 28 shows the conduction and valence energy bands for the corrugated quantum well structure 27(a). We observed that the spin twice degenerate states at -point are splitted in and directions. This spin-splitting related to the lack of the structure inversion symmetry.
Researchers: Jani Oksanen and Jukka Tulkki
In the long haul network backbone where complex logical operations, like routing, are not needed, electrical components have been superseded by optical ones during the last decade. This has enabled an enormous boost in the data rates of the backbone, but left the electronic solutions in the metropolitan area and access networks slightly outdated. However, to date there are no technologically viable solutions for replacing all the electronics by optics. This project concentrates on constructing models and ideas for new all-optical devices, with the needs of the access networks in mind.
In the project we have this far investigated 1) the differences of the quantum well and dot lasers with respect to their chirp under direct current modulation, 2) the operation of an optical amplifier linearized using gain clamping in vertical direction (also known as linear optical amplifier, or LOA), 3) the use of quantum cascade lasers in free space optical communications and 4) all-optical signal regeneration using partly coherent laser networks. At the moment we are focusing our attention on an all-optical memory element, that could operate faster than the previous bistable systems composed of one or two lasers (See fig. 5.2.3). .
Figure 28: The band diagram of the corrugated quantum wire superlattice Fig. 27(a). The band energy is given with respect to the unstrained valence band edge of bulk |
The above devices are studied using analytical and numerical models ranging from band structure calculations to stochastic rate equations. The obtained information can be used in improving the existing devices and possibly in creating new ones as well.
Researchers: Teppo Häyrynen and Jukka Tulkki
If electrons move trough a conducting device without scattering the transport of electrons is ballistic. Ballistic transport is observed when the length of the channel is small compared to the mean free path of an electron. In the ballistic transport regime a device can be modeled in terms of transmission probabilities which are calculated for different combinations of source and drain eigenmodes
We have used the mode matching (MM) method within the Landauer-Büttiker formalism to calculate the conductance in selected two- and three-dimensional channels (See fig. 30) . Furthermore we calculated the conductance of a silicon on insulator (SOI) quantum point contact (QPC) by using the MM method at small temperatures where the step like behavior of conductance was observed. The calculated result agrees qualitatively with the measured conductance [M. Prunnila et al., Silicon quantum point contact with aluminum gate, Mat. Sci. Eng. B, 74(1-3):193-196,2000]. Currently we are modeling how the strain affects to the conductance in the QPC and in the quantum wire (QWR) structures due to the changes in the electron eigenstates.
Figure 30: Calculated conductance of the QPC at T = 0K and T = 1.5K. |