Mapping Morphological and Structural Properties of Lead Halide Perovskites by Scanning Nanofocus XRD

Scanning nanofocus X-ray diffraction (nXRD) performed at a synchrotron is used to simultaneously probe the morphology and the structural properties of spin-coated CH$_3$NH$_3$PbI$_3$ (MAPI) perovskite films for photovoltaic devices. MAPI films are spin-coated on a Si/SiO$_2$/poly(3,4-ethylenedioxythiophene): polystyrene sulfonate (PEDOT:PSS) substrate held at different temperatures during the deposition in order to tune the perovskite film coverage. The films are then investigated using nXRD and scanning electron microscopy (SEM). The advantages of nXRD over SEM and other techniques are discussed. A method to visualize, selectively isolate, and structurally characterize single perovskite grains buried within a complex, polycrystalline film is developed. The results of nXRD measurements are correlated with solar cell device measurements, and it is shown that spin-coating the perovskite precursor solution at elevated temperatures leads to improved surface coverage and enhanced solar cell performance.This work was funded by the UK Engineering and Physical Sciences Research Council via grants EP/M025020/1 “High resolution mapping of performance and degradation mechanisms in printable photovoltaic devices,” EP/J017361/1 (Supersolar Solar Energy Hub) and the E-Futures Doctoral Training Center in Interdisciplinary Energy Research EP/G037477/1. This work was partially funded by the President of the UAE’s Distinguished Student Scholarship Program (DSS), granted by the Ministry of Presidential Affairs, UAE (M.A. PhD scholarship). This work was also partially funded by the Masdar Institute through the grant Novel Organic Optoelectronic Devices. The authors gratefully acknowledge Manfred Burghammer and Martin Rosenthal at the ID13 – the microfocus beamline at the ESRF for their assistance with the nXRD measurements. XMaS is a mid-range facility supported by the Engineering and Physical Sciences Research Council (EPSRC)

A study of the 2D-Potts model in MATLAB

79 σ.Η παρακάτω διπλωματική εργασία έγινε με σκοπό την ανάπτυξη μίας εφαρμογής που να υλοποιεί προσομοιώσεις Monte Carlo για μαγνητικό σύστημα στα πλαίσια του δισδιάστατου προτύπου Potts σε προγραμματιστικό περιβάλλον MATLAB. Η εργασία χωρίζεται σε τρία μέρη. Στην αρχή του πρώτου μέρους παρατίθεται η σχετική θεωρία όπου αναπτύσσονται συνοπτικά οι βασικές αρχές που διέπουν την στατιστική φυσική και τις προσομοιώσεις Monte Carlo, προς βοήθεια αναγνωστών που δεν είναι πλήρως εξοικειωμένοι με το θέμα. Στη συνέχεια γίνεται μία παρουσίαση των εμπλεκόμενων αλγορίθμων – Metropolis, Heat-bath και Wolff. Το δεύτερο μέρος περιέχει μία περιγραφή της διαδικασίας ανάπτυξης του κώδικα για την εφαρμογή στο MATLAB. Παράλληλα γίνεται σύγκριση της απόδοσης της με μία αντίστοιχη εφαρμογή γραμμένη σε κώδικα C, στηριγμένη στον κώδικα για το πρότυπο Ising των M. E. J. Newman και G. T. Barkema. Το μέρος τελειώνει με ένα σχολιασμό των αποτελεσμάτων της τρίτης και τελευταίας υλοποίησης της εφαρμογής – η εφαρμογή που γράφτηκε στο MATLAB βρέθηκε να υστερεί σε απόδοση από την αντίστοιχη της C –και την εξαγωγή των σχετικών συμπερασμάτων ως προς την καταλληλότητα του MATLAB για την εργασία που του ανατέθηκε. Στο τρίτο μέρος βρίσκονται τα παραρτήματα όπου γίνεται παράθεση όλου του κώδικα που γράφτηκε κατά την ανάπτυξη της εφαρμογής.The goal of the following thesis was the development of a MATLAB application capable of implementing a Monte Carlo simulation of a magnetic system in accordance with the two-dimensional Potts model. The project is divided upon three parts. The first part begins with a brief description of the basic principles that govern statistical physics and Monte Carlo simulations to help non-specialist to familiarize themselves with the subject. Following that, is an introduction to the algorithms involved – Metropolis, Heat-bath and Wolff. In the second part we find a report on the process of developing the application in MATLAB, together with a comparison of its performance with the performance of a similar C application, based on the Ising model code of M. E. J. Newman and G. T. Barkema. The part ends with some comments on the results given by the third and last implementation – the application written in MATLAB was found to perform worse than the one written in C – and a conclusion on the suitability of MATLAB for this kind of work. The third part is the appendices which contain the code written in the development process of the application.Γιάννης Χ. Ασσιώτη

Shared-Space Autoencoders with Randomized Skip Connections for Building Footprint Detection with Missing Views

Recently, a vast amount of satellite data has become available, going beyond standard optical (EO) data to other forms such as synthetic aperture radars (SAR). While more robust, SAR data are often more difficult to interpret, can be of lower resolution, and require intense pre-processing compared to EO data. On the other hand, while more interpretable, EO data often fail under unfavourable lighting, weather, or cloud-cover conditions. To leverage the advantages of both domains, we present a novel autoencoder-based architecture that is able to both (i) fuse multi-spectral optical and radar data in a common shared-space, and (ii) perform image segmentation for building footprint detection under the assumption that one of the data modalities is missing–resembling a situation often encountered under real-world settings. To do so, a novel randomized skip-connection architecture that utilizes autoencoder weight-sharing is designed. We compare the proposed method to baseline approaches relying on network fine-tuning, and established architectures such as UNet. Qualitative and quantitative results show the merits of the proposed method, that outperforms all compared techniques for the task-at-hand