Time-dependent quantum transport in a resonant tunnel junction coupled to a nanomechanical oscillator

We present a theoretical study of time-dependent quantum transport in a resonant tunnel junction coupled to a nanomechanical oscillator within the non-equilibrium Green's function technique. An arbitrary voltage is applied to the tunnel junction and electrons in the leads are considered to be at zero temperature. The transient and the steady state behavior of the system is considered here in order to explore the quantum dynamics of the oscillator as a function of time. The properties of the phonon distribution of the nanomechnical oscillator strongly coupled to the electrons on the dot are investigated using a non-perturbative approach. We consider both the energy transferred from the electrons to the oscillator and the Fano factor as a function of time. We discuss the quantum dynamics of the nanomechanical oscillator in terms of pure and mixed states. We have found a significant difference between a quantum and a classical oscillator. In particular, the energy of a classical oscillator will always be dissipated by the electrons whereas the quantum oscillator remains in an excited state. This will provide useful insight for the design of experiments aimed at studying the quantum behavior of an oscillator.Comment: 24 pages, 10 figure

Diffusion-induced dephasing in nanomechanical resonators

We study resonant response of an underdamped nanomechanical resonator with fluctuating frequency. The fluctuations are due to diffusion of molecules or microparticles along the resonator. They lead to broadening and change of shape of the oscillator spectrum. The spectrum is found for the diffusion confined to a small part of the resonator and where it occurs along the whole nanobeam. The analysis is based on extending to the continuous limit, and appropriately modifying, the method of interfering partial spectra. We establish the conditions of applicability of the fluctuation-dissipation relations between the susceptibility and the power spectrum. We also find where the effect of frequency fluctuations can be described by a convolution of the spectra without these fluctuations and with them as the only source of the spectral broadening.Comment: 10 page

Spintronics of a Nanoelectromechanical Shuttle

We consider effects of the spin degree of freedom on the nanomechanics of a single-electron transistor (SET) containing a nanometer-sized metallic cluster suspended between two magnetic leads. It is shown that in such a nanoelectromechanical SET(NEM-SET) the onset of an electromechanical instability leading to cluster vibrations and "shuttle" transport of electrons between the leads can be controlled by an external magnetic field. Different stable regimes of this spintronic NEM-SET operation are analyzed. Two different scenarios for the onset of shuttle vibrations are found.Comment: 4 pages, 3 figure

Quantum Shuttle Phenomena in a Nanoelectromechanical Single-Electron Transistor

An analytical analysis of quantum shuttle phenomena in a nanoelectromechanical single-electron transistor has been performed in the realistic case, when the electron tunnelling length is much greater than the amplitude of the zero point oscillations of the central island. It is shown that when the dissipation is below a certain threshold value, the vibrational ground state of the central island is unstable. The steady-state into which this instability develops is studied. It is found that if the electric field ${\cal E}$ between the leads is much greater than a characteristic value ${\cal E}_q$, the quasiclassical shuttle picture is recovered, while if ${\cal E}\ll{\cal E}_q$ a new quantum regime of shuttle vibrations occurs. We show that in the latter regime small quantum fluctuations result in large (i.e. finite in the limit $\hbar \to 0$) shuttle vibrations.Comment: 5 pages, 1 figur

Effect of quantum nuclear motion on hydrogen bonding

This work considers how the properties of hydrogen bonded complexes, D-H....A, are modified by the quantum motion of the shared proton. Using a simple two-diabatic state model Hamiltonian, the analysis of the symmetric case, where the donor (D) and acceptor (A) have the same proton affinity, is carried out. For quantitative comparisons, a parametrization specific to the O-H....O complexes is used. The vibrational energy levels of the one-dimensional ground state adiabatic potential of the model are used to make quantitative comparisons with a vast body of condensed phase data, spanning a donor-acceptor separation (R) range of about 2.4-3.0 A, i.e., from strong to weak bonds. The position of the proton and its longitudinal vibrational frequency, along with the isotope effects in both are discussed. An analysis of the secondary geometric isotope effects, using a simple extension of the two-state model, yields an improved agreement of the predicted variation with R of frequency isotope effects. The role of the bending modes in also considered: their quantum effects compete with those of the stretching mode for certain ranges of H-bond strengths. In spite of the economy in the parametrization of the model used, it offers key insights into the defining features of H-bonds, and semi-quantitatively captures several experimental trends.Comment: 12 pages, 8 figures. Notation clarified. Revised figure including the effect of bending vibrations on secondary geometric isotope effect. Final version, accepted for publication in Journal of Chemical Physic

Development of a technology adoption and usage prediction tool for assistive technology for people with dementia

This article is available open access through the publisher’s website at the link below. Copyright @ The Authors 2013.In the current work, data gleaned from an assistive technology (reminding technology), which has been evaluated with people with Dementia over a period of several years was retrospectively studied to extract the factors that contributed to successful adoption. The aim was to develop a prediction model with the capability of prospectively assessing whether the assistive technology would be suitable for persons with Dementia (and their carer), based on user characteristics, needs and perceptions. Such a prediction tool has the ability to empower a formal carer to assess, through a very limited amount of questions, whether the technology will be adopted and used.EPSR

SemImput: Bridging Semantic Imputation with Deep Learning for Complex Human Activity Recognition

The recognition of activities of daily living (ADL) in smart environments is a well-known and an important research area, which presents the real-time state of humans in pervasive computing. The process of recognizing human activities generally involves deploying a set of obtrusive and unobtrusive sensors, pre-processing the raw data, and building classification models using machine learning (ML) algorithms. Integrating data from multiple sensors is a challenging task due to dynamic nature of data sources. This is further complicated due to semantic and syntactic differences in these data sources. These differences become even more complex if the data generated is imperfect, which ultimately has a direct impact on its usefulness in yielding an accurate classifier. In this study, we propose a semantic imputation framework to improve the quality of sensor data using ontology-based semantic similarity learning. This is achieved by identifying semantic correlations among sensor events through SPARQL queries, and by performing a time-series longitudinal imputation. Furthermore, we applied deep learning (DL) based artificial neural network (ANN) on public datasets to demonstrate the applicability and validity of the proposed approach. The results showed a higher accuracy with semantically imputed datasets using ANN. We also presented a detailed comparative analysis, comparing the results with the state-of-the-art from the literature. We found that our semantic imputed datasets improved the classification accuracy with 95.78% as a higher one thus proving the effectiveness and robustness of learned models