Multiscale morphology design of hybrid halide perovskites through a polymeric template

Hybrid halide perovskites have emerged as promising active constituents of next generation solution processable optoelectronic devices. During their assembling process, perovskite components undergo very complex dynamic equilibria starting in solution and progressing throughout film formation. Finding a methodology to control and affect these equilibria, responsible for the unique morphological diversity observed in perovskite films, constitutes a fundamental step towards a reproducible material processability. Here we propose the exploitation of polymer matrices as cooperative assembling components of novel perovskite CH3NH3PbI3 : polymer composites, in which the control of the chemical interactions in solution allows a predictable tuning of the final film morphology. We reveal that the nature of the interactions between perovskite precursors and polymer functional groups, probed by Nuclear Magnetic Resonance (NMR) spectroscopy and Dynamic Light Scattering (DLS) techniques, allows the control of aggregates in solution whose characteristics are strictly maintained in the solid film, and permits the formation of nanostructures that are inaccessible to conventional perovskite depositions. These results demonstrate how the fundamental chemistry of perovskite precursors in solution has a paramount influence on controlling and monitoring the final morphology of CH3NH3PbI3 (MAPbI3) thin films, foreseeing the possibility of designing perovskite : polymer composites targeting diverse optoelectronic applications.

Carbon nanotube films for flexible electronics

Discovering scalable routes to fabricate large scale electronic devices on flexible substrates has been the goal of the newly emerging field of flexible macroelectronics. Thin film transistors (TFTs) have been fabricated on flexible substrates by using organic small-molecule and polymer-based materials, or thin layers of crystalline inorganic semiconductors. Recently, films of carbon nanotubes have been proposed as electronic materials with superior electrical performance due to exceptional electrical and mechanical properties of single-walled carbon nanotubes (SWCNTs). In this thesis, some aspects of recent research efforts on integrating arrays of carbon nanotubes into macroelectronic devices are described. Carbon nanotube films have two major uses for flexible macroelectronics. The first approach uses carbon nanotube thin films as active semiconducting materials in the channel of flexible TFTs. Even though, high-performance carbon nanotube thin film transistors have been realized, the electronic non-homogeneity of the as-grown carbon nanotubes in the film limits the device performance for some applications. In this thesis, the application of electrochemical functionalization on carbon nanotube films to improve the electronic homogeneity of the film is described. The effect of the crystal quartz substrates on the growth rate of carbon nanotubes, and whether this can be used to sort out as-grown carbon nanotubes by electronic type is also discussed. Finally, I argue that high density carbon nanotube films can also be used as highly conducting stretchable interconnects on mechanically flexible electronic circuits. The sheet resistance and the nature of the buckling of carbon nanotube films on flexible substrates are discussed.

Automated Software Debugging Using Hybrid Static/Dynamic Analysis

With the increasing complexity of today's software, the software development process is becoming highly time and resource consuming. The increasing number of software configurations, input parameters, usage scenarios, supporting platforms, external dependencies, and versions plays an important role in expanding the costs of maintaining and repairing unforeseeable software faults. To repair software faults, developers spend considerable time in identifying the scenarios leading to those faults and root-causing the problems. While software debugging remains largely manual, it is not the case with software testing and verification. The goal of this research is to improve the software development process in general, and software debugging process in particular, by devising techniques and methods for automated software debugging, which leverage the advances in automatic test case generation and replay. In this research, novel algorithms are devised to discover faulty execution paths in programs by utilizing already existing software test cases, which can be either automatically or manually generated. The execution traces, or alternatively, the sequence covers of the failing test cases are extracted. Afterwards, commonalities between these test case sequence covers are extracted, processed, analyzed, and then presented to the developers in the form of subsequences that may be causing the fault. The hypothesis is that code sequences that are shared between a number of faulty test cases for the same reason resemble the faulty execution path, and hence, the search space for the faulty execution path can be narrowed down by using a large number of test cases. To achieve this goal, an efficient algorithm is implemented for finding common subsequences among a set of code sequence covers. Optimization techniques are devised to generate shorter and more logical sequence covers, and to select subsequences with high likelihood of containing the root cause among the set of all possible common subsequences. A hybrid static/dynamic analysis approach is designed to trace back the common subsequences from the end to the root cause. A debugging tool is created to enable developers to use the approach, and integrate it with an existing Integrated Development Environment. The tool is also integrated with the environment's program editors so that developers can benefit from both the tool suggestions, and their source code counterparts. Finally, a comparison between the developed approach and the state-of-the-art techniques shows that developers need only to inspect a small number of lines in order to find the root cause of the fault. Furthermore, experimental evaluation shows that the algorithm optimizations lead to better results in terms of both the algorithm running time and the output subsequence length.

Multiscale Modeling and Simulation of Stepped Crystal Surfaces

A primary goal of this dissertation is to understand the links between mathematical models that describe crystal surfaces at three fundamental length scales: The scale of individual atoms, the scale of collections of atoms forming crystal defects, and macroscopic scale. Characterizing connections between different classes of models is a critical task for gaining insight into the physics they describe, a long-standing objective in applied analysis, and also highly relevant in engineering applications. The key concept I use in each problem addressed in this thesis is coarse graining, which is a strategy for connecting fine representations or models with coarser representations. Often this idea is invoked to reduce a large discrete system to an appropriate continuum description, e.g. individual particles are represented by a continuous density. While there is no general theory of coarse graining, one closely related mathematical approach is asymptotic analysis, i.e. the description of limiting behavior as some parameter becomes very large or very small. In the case of crystalline solids, it is natural to consider cases where the number of particles is large or where the lattice spacing is small. Limits such as these often make explicit the nature of links between models capturing different scales, and, once established, provide a means of improving our understanding, or the models themselves. Finding appropriate variables whose limits illustrate the important connections between models is no easy task, however. This is one area where computer simulation is extremely helpful, as it allows us to see the results of complex dynamics and gather clues regarding the roles of different physical quantities. On the other hand, connections between models enable the development of novel multiscale computational schemes, so understanding can assist computation and vice versa. Some of these ideas are demonstrated in this thesis. The important outcomes of this thesis include: (1) a systematic derivation of the step-flow model of Burton, Cabrera, and Frank, with corrections, from an atomistic solid-on-solid-type models in 1+1 dimensions; (2) the inclusion of an atomistically motivated transport mechanism in an island dynamics model allowing for a more detailed account of mound evolution; and (3) the development of a hybrid discrete-continuum scheme for simulating the relaxation of a faceted crystal mound. Central to all of these modeling and simulation efforts is the presence of steps composed of individual layers of atoms on vicinal crystal surfaces. Consequently, a recurring theme in this research is the observation that mesoscale defects play a crucial role in crystal morphological evolution.

Hybrid materials based on polyethylene and MCM-41 microparticles functionalized with silanes: catalytic aspects of in situ polymerization, crystalline features and mechanical properties

New nanocomposites based on polyethylene have been prepared by in situ polymerization of ethylene in presence of mesoporous MCM-41. The polymerization reactions were performed using a zirconocene catalyst either under homogenous conditions or supported onto mesoporous MCM-41 particles, which are synthesized and decorated post-synthesis with two silanes before polymerization in order to promote an enhanced interfacial adhesion. The existence of polyethylene chains able to crystallize within the mesoporous channels in the resulting nanocomposites is figured out from the small endothermic process, located at around 80 C, on heating calorimetric experiments, in addition to the main melting endotherm. These results indicate that polyethylene macrochains can grow up during polymerization either outside or inside the MCM-41 channels, these keeping their regular hexagonal arrangements. Mechanical response is observed to be dependent on the content in mesoporous MCM-41 and on the crystalline features of polyethylene. Accordingly, stiffness increases and deformability decreases in the nanocomposites as much as MCM-41 content is enlarged and polyethylene amount within channels is raised. Ultimate mechanical performance improves with MCM-41 incorporation without varying the final processing temperature.

Development of water-soluble polyanionic carbosilane dendrimers as novel and highly potent topical anti-HIV-2 microbicides

This is the author’s version of a work that was accepted for publication in Nanoscale.

Novel synthesis of a micro-mesoporous nitrogen-doped nanostructured carbon from polyaniline

Nanostructured carbons with relatively high nitrogen content (3–8%) and different micro and mesoporosity ratio were prepared by activation of polyaniline (PANI) with a ZnCl2–NaCl mixture in the proportion of the eutectic (melting point 270 °C). It was found that the activated carbons consisted of agglomerated nanoparticles. ZnCl2 plays a key role in the development of microporosity and promotes the binding between PANI nanoparticles during heat treatment, whereas NaCl acts as a template for the development of mesoporosity of larger size. Carbons with high micropore and mesopore volumes, above 0.6 and 0.8 cm3/g, respectively, have been obtained. Furthermore, these materials have been tested for CO2 capture and storage at pressures up to 4 MPa. The results indicate that the nitrogen groups present in the surface do not seem to affect to the amount of CO2 adsorbed, not detecting strong interactions between CO2 molecules and nitrogen functional groups of the carbon, which are mainly pyridinic and pyrrolic groups.

Comb-like acrylic-based polymer latexes containing nano-sized crystalline or liquid crystalline domains

306 p.

The creation and evaluation of novel canine training aids for cocaine using molecularly encapsulated sol-gel polymers and an investigation of canine field accuracy

Biological detectors, such as canines, are valuable tools used for the rapid identification of illicit materials. However, recent increased scrutiny over the reliability, field accuracy, and the capabilities of each detection canine is currently being evaluated in the legal system. For example, the Supreme Court case, State of Florida v. Harris, discussed the need for continuous monitoring of canine abilities, thresholds, and search capabilities. As a result, the fallibility of canines for detection was brought to light, as well as a need for further research and understanding of canine detection. This study is two-fold, as it looks to not only create new training aids for canines that can be manipulated for dissipation control, but also investigates canine field accuracy to objects with similar odors to illicit materials. ^ It was the goal of this research to improve upon current canine training aid mimics. Sol-gel polymer training aids, imprinted with the active odor of cocaine, were developed. This novel training aid improved upon the longevity of currently existing training aids, while also provided a way to manipulate the polymer network to alter the dissipation rate of the imprinted active odors. The manipulation of the polymer network could allow handlers to control the abundance of odors presented to their canines, familiarizing themselves to their canine’s capabilities and thresholds, thereby increasing the canines’ strength in court.^ The field accuracy of detection canines was recently called into question during the Supreme Court case, State of Florida v. Jardines, where it was argued that if cocaine’s active odor, methyl benzoate, was found to be produced by the popular landscaping flower, snapdragons, canines will false alert to said flowers. Therefore, snapdragon flowers were grown and tested both in the laboratory and in the field to determine the odors produced by snapdragon flowers; the persistence of these odors once flowers have been cut; and whether detection canines will alert to both growing and cut flowers during a blind search scenario. Results revealed that although methyl benzoate is produced by snapdragon flowers, certified narcotics detection canines can distinguish cocaine’s odor profile from that of snapdragon flowers and will not alert.^

Photoluminescent materials based on PMMA and a highly-emissive octahedral molybdenum metal cluster complex

Materials that combine photoluminescence, optical transparency and facile processability are of high importance in many applications. This article reports on the development of photoluminescent poly(methyl methacrylate) materials based on novel highly emissive anionic molybdenum cluster complex [{Mo6I8}(OTs)6]2- (where OTs- is the p-toluenesulfonate ion). The materials were obtained by both solution and bulk copolymerisation of methyl methacrylate and (dMDAEMA)2[{Mo6I8}(OTs)6], where dMDAEMA+ is the polymerisable cation [2-(methacryloyloxy)ethyl]dimethyl-dodecylammonium. Evaluation of the resultant hybrid materials showed that one could combine the excellent photoluminescent properties of the cluster complex with the transparency and processability of PMMA.

Hall Effect and transient surface photovoltage (SPV) study of Cu3BiS3 thin films

Se presentan las propiedades eléctricas del compuesto Cu3BiS3 depositado por co-evaporación. Este es un nuevo compuesto que puede tener propiedades adecuadas para ser utilizado como capa absorbente en celdas solares. Las muestras fueron caracterizadas a través de medidas de efecto Hall y fotovoltaje superficial transiente (SPV). A través de medidas de efecto Hall se encontró que la concentración de portadores de carga n es del orden de 1016 cm-3 independiente de la relación de masas de Cu/Bi. También se encontró que la movilidad de este compuesto (μ del orden de 4 cm2V -1s-1) varía de acuerdo con los mecanismos de transporte que la gobiernan en dependencia con la temperatura. A partir de las medidas de SPV se encontró alta densidad de defectos superficiales, defectos que son pasivados al superponer una capa buffer sobre el compuesto Cu3BiS3.

Novel and highly informative Capsicum SSR markers and their cross-species transferability.

2016

Hybrid Artificial Intelligence to Extract Patterns and Rules from Argumentative and Legal Texts

This Thesis is composed of a collection of works written in the period 2019-2022, whose aim is to find methodologies of Artificial Intelligence (AI) and Machine Learning to detect and classify patterns and rules in argumentative and legal texts. We define our approach “hybrid”, since we aimed at designing hybrid combinations of symbolic and sub-symbolic AI, involving both “top-down” structured knowledge and “bottom-up” data-driven knowledge. A first group of works is dedicated to the classification of argumentative patterns. Following the Waltonian model of argument and the related theory of Argumentation Schemes, these works focused on the detection of argumentative support and opposition, showing that argumentative evidences can be classified at fine-grained levels without resorting to highly engineered features. To show this, our methods involved not only traditional approaches such as TFIDF, but also some novel methods based on Tree Kernel algorithms. After the encouraging results of this first phase, we explored the use of a some emerging methodologies promoted by actors like Google, which have deeply changed NLP since 2018-19 — i.e., Transfer Learning and language models. These new methodologies markedly improved our previous results, providing us with best-performing NLP tools. Using Transfer Learning, we also performed a Sequence Labelling task to recognize the exact span of argumentative components (i.e., claims and premises), thus connecting portions of natural language to portions of arguments (i.e., to the logical-inferential dimension). The last part of our work was finally dedicated to the employment of Transfer Learning methods for the detection of rules and deontic modalities. In this case, we explored a hybrid approach which combines structured knowledge coming from two LegalXML formats (i.e., Akoma Ntoso and LegalRuleML) with sub-symbolic knowledge coming from pre-trained (and then fine-tuned) neural architectures.

Fabrication and characterization of hybrid ferromagnetic-organic heterostructures for spintronics application

Recent research in the field of organic spintronics highlighted the peculiar spin-dependent properties of the interface formed by an organic semiconductor (OSC) chemisorbed over a 3d ferromagnetic metal, also known as spinterface. The hybridization between the molecular and metallic orbitals, typically π orbitals of the molecule and the d orbitals of the ferromagnet, give rise to spin dependent properties that were not expected by considering the single components of interfaces, as for example the appearance of a magnetic moment on non-magnetic molecules or changes in the magnetic behavior of the ferromagnet. From a technological viewpoint these aspects provide novel engineering schemes for spin memory and for spintronics devices, featuring unexpected interfacial magnetoresistance, spin-filtering effects and even modulated magnetic anisotropy. Applications of these concepts to devices require nevertheless to transfer the spinterface effects from an ideal interface to room temperature operating thin films. In this view, my work presents for the first time how spinterface effects can be obtained even at room temperature on polycrystalline ferromagnetic Co thin films interfaced with organic molecules. The considered molecules were commercial and widely used in the field of organic electronics: Fullerene (C60), Gallium Quinoline (Gaq3) and Sexithiophene (T6). An increase of coercivity, up to 100% at room temperature, has been obtained on the Co ultra-thin films by the deposition of an organic molecule. This effect is accompanied by a change of in-plane anisotropy that is molecule-dependent. Moreover the Spinterface effect is not limited to the interfacial layer, but it extends throughout the whole thickness of the ferromagnetic layer, posing new questions on the nature of the 3d metal-molecule interaction.