Tyndall National Institute - Journal Articles

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    On the multifaceted journey for the invention of epitaxial quantum dots
    (Elsevier Ltd., 2023-10-19) Pelucchi, Emanuele; Science Foundation Ireland
    Epitaxial semiconductor quantum dots have been, in the last 40 years or so, at the center of the research effort of a large community. The focus being on “semiconductor physics and devices”, in view of the broad applications and potential, e.g., for efficient temperature insensitive lasers at telecom wavelengths, or as “artificial atoms” for quantum information processing. Our manuscript aims at addressing, with an historical perspective, the specifics of (III-V) epitaxial quantum dot early developments (largely for light emitting) and subsequent years. We will not only highlight the variety of epitaxial structures and methods, but also, intentionally glancing a didactic approach, discuss aspects that are, in general, little acknowledged or debated in the present literature. The analyses will also naturally bring us to examine some of current challenges, in a field which, despite sensational achievements, is, remarkably, still far from being mature in its developments and applications.
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    Theory and optimisation of radiative recombination in broken-gap InAs/GaSb superlattices
    (IOP Publishing, 2023-10-24) Murphy, Cónal; O’Reilly, Eoin P.; Broderick, Christopher A.; Irish Research Council; Science Foundation Ireland; H2020 Marie Skłodowska-Curie Actions
    We present a theoretical analysis of mid-infrared radiative recombination in InAs/GaSb superlattices (SLs). We employ a semi-analytical plane wave expansion method in conjunction with an 8-band k.p Hamiltonian to compute the SL electronic structure, paying careful attention to the identification and mitigation of spurious solutions. The calculated SL eigenstates are used directly to compute spontaneous emission spectra and the radiative recombination coefficient B. We elucidate the origin of the relatively large B coefficients in InAs/GaSb SLs which, despite the presence of spatially indirect (type-II-like) carrier confinement, are close to that of bulk InAs and compare favourably to those calculated for mid-infrared type-I pseudomorphic and metamorphic quantum well structures having comparable emission wavelengths. Our analysis explicitly quantifies the roles played by carrier localisation (specifically, partial delocalisation of bound electron states) and miniband formation (specifically, miniband occupation and optical selection rules) in determining the magnitude of $B$ and its temperature dependence. We perform a high-throughput optimisation of the room temperature $B$ coefficient in InAs/GaSb SLs across the 3.5–7 $\mu$m wavelength range, quantifying the dependence of $B$ on the relative thickness of the electron-confining InAs and hole-confining GaSb layers. This analysis provides guidance for the growth of optimised SLs for mid-infrared light emitters. Our results, combined with the expected low non-radiative Auger recombination rates in structures having spatially indirect electron and hole confinement, corroborate recently observed high output power in prototype InAs/GaSb SL inter-band cascade light-emitting diodes.
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    Non-invasive assessment of cartilage damage of the human knee using acoustic emission monitoring: A pilot cadaver study
    (Institute of Electrical and Electronics Engineers (IEEE), 2023-03-30) Khokhlova, Liudmila; Komaris, Dimitrios-Sokratis; Davarinos, Nikolaos; Mahalingam, Karuppiah; O'Flynn, Brendan; Tedesco, Salvatore; Science Foundation Ireland; European Regional Development Fund
    Objective: Knee osteoarthritis is currently one of the top causes of disability in older population, a rate that will only increase in the future due to an aging population and the prevalence of obesity. However, objective assessment of treatment outcomes and remote evaluation are still in need of further development. Acoustic emission (AE) monitoring in knee diagnostics has been successfully adopted in the past; however, a wide discrepancy among the adopted AE techniques and analyses exists. This pilot study determined the most suitable metrics to differentiate progressive cartilage damage and the optimal frequency range and placement of AE sensors. Methods: Knee AEs were recorded in the 100–450 kHz and 15–200kH frequency ranges from a cadaver specimen in knee flexion/extension. Four stages of artificially inflicted cartilage damage and two sensor positions were investigated. Results: AE events in the lower frequency range and the following parameters provided better distinction between intact and damaged knee: hit amplitude, signal strength, and absolute energy. The medial condyle area of the knee was less prone to artefacts and unsystematic noise. Multiple reopenings of the knee compartment in the process of introducing the damage negatively affected the quality of the measurements. Conclusion: Results may improve AE recording techniques in future cadaveric and clinical studies. Significance: This was the first study to evaluate progressive cartilage damage using AEs in a cadaver specimen. The findings of this study encourage further investigation of joint AE monitoring techniques.
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    Machine learning based canine posture estimation using inertial data
    (PLoS, 2023-06-21) Marcato, Marinara; Tedesco, Salvatore; O’Mahony, Conor; O’Flynn, Brendan; Galvin, Paul; Mohamed Hammad; European Regional Development Fund; Science Foundation Ireland
    The aim of this study was to design a new canine posture estimation system specifically for working dogs. The system was composed of Inertial Measurement Units (IMUs) that are commercially available, and a supervised learning algorithm which was developed for different behaviours. Three IMUs, each containing a 3-axis accelerometer, gyroscope, and magnetometer, were attached to the dogs’ chest, back, and neck. To build and test the model, data were collected during a video-recorded behaviour test where the trainee assistance dogs performed static postures (standing, sitting, lying down) and dynamic activities (walking, body shake). Advanced feature extraction techniques were employed for the first time in this field, including statistical, temporal, and spectral methods. The most important features for posture prediction were chosen using Select K Best with ANOVA F-value. The individual contributions of each IMU, sensor, and feature type were analysed using Select K Best scores and Random Forest feature importance. Results showed that the back and chest IMUs were more important than the neck IMU, and the accelerometers were more important than the gyroscopes. The addition of IMUs to the chest and back of dog harnesses is recommended to improve performance. Additionally, statistical and temporal feature domains were more important than spectral feature domains. Three novel cascade arrangements of Random Forest and Isolation Forest were fitted to the dataset. The best classifier achieved an f1-macro of 0.83 and an f1-weighted of 0.90 for the prediction of the five postures, demonstrating a better performance than previous studies. These results were attributed to the data collection methodology (number of subjects and observations, multiple IMUs, use of common working dog breeds) and novel machine learning techniques (advanced feature extraction, feature selection and modelling arrangements) employed. The dataset and code used are publicly available on Mendeley Data and GitHub, respectively.
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    Influence of surface passivation on indium arsenide nanowire band gap energies
    (Springer Nature Ltd., 2019-07-31) Razavi, Pedram; Greer, James C.; Seventh Framework Programme; University of Nottingham Ningbo China
    The interplay between surface chemistry and quantum confinement on the band gap energies of indium arsenide (InAs) nanowires is investigated by first principle computations as the surface-to-volume ratio increases with decreasing cross section. Electronic band structures are presented as determined by both density functional and hybrid density functional theory (DFT) calculations; the latter are used to provide improved band gap energy estimates over those from standard approximate DFT methods. Different monovalent chemical species with varying electron affinity are used to eliminate surface states to enable direct comparison between surface chemistry and quantum confinement. The influence of these effects on energy band gaps and electron effective masses is highlighted. It is found that many desirable properties in terms of electronic properties and the elimination of surface states for nanoscale field effect transistors fabricated using [100]-oriented InAs can be achieved.