Computational characterization of carbazole-benzonitrile derivatives for applications in Organic Light Emitting Diodes

The technology of Organic Light-Emitting Diodes has reached such a high level of reliability that it can be used in various applications. The required light emission efficiency can be achieved by transforming the triplet excitons into singlet states through Reverse InterSystem Crossing (RISC), which is the main process of a general mechanism called thermally activated delayed fluorescence (TADF). In this thesis, we theoretically analyzed two carbazole-benzonitrile (donor-acceptor) derivatives, 2,5-di(9H-carbazol-9-yl)benzonitrile (p-2CzBN) and 2,3,4,5,6-penta(9H-carbazol-9-yl)benzonitrile (5CzBN), and addressed the problem of how donor-acceptor (D-A) or donor-acceptor-donor (D-A-D) flexible molecular architectures influence the nature of the excited states and the emission intensity. Furthermore, we analyzed the RISC rates as a function of the conformation of the carbazole lateral groups, considering the first electronic states, S0, S1, T1 and T2, involved in TADF process. The two prototype molecules, p-2CzBN and 5CzBN, have a similar energy gap between the first singlet and triplet states (∆EST, a key parameter in the RISC rate), but different TADF performances. Therefore, other parameters must be considered to explain their different behavior. The oscillator strength of p-2CzBN, never tested as emitter in OLEDs, is similar to that of 5CzBN, which is an active TADF molecule. We also note that the presence of a second T2 triplet state, lower in energy than S1 only in 5CzBN, and the reorganization energies, associated with RISC processes involving T1 and T2, are important factors in differentiating the rates in p-2CzBN and 5CzBN. For p-2CzBN, the RISC rate from T2 to S1 is surprisingly higher than that from T1 to S1, in disagreement with El-Sayed rules, due to a large reorganization energy associated to the T1 to S1, process; while the contrary occurs for 5CzBN. These insights are important for designing new TADF emitters based on the benzo-carbazole architecture.

Organic photosensitizers and nanostructured semiconductors for photoredox catalysis and artificial photosynthesis

Over the course of evolution, Nature has elegantly learned to use light to drive chemical reactions. On the other hand, humans have only recently started learning how to play with this powerful tool to carry out chemical transformations. In particular, a step forward was possible thanks to molecules and materials that can absorb light and trigger a series of processes that can drive chemical reactions. However, scarce elements are extensively employed in the design of most of these compounds and considerations on their scarcity and toxicity have sparked interest on alternatives based on earth-abundant elements. In this framework, the focus of this thesis has been the development and employment of heavy-metal free chromophores and of earth-abundant oxides. The first chapter regards the functionalization of boron-dipyrromethenes (BODIPYs) so as to allow access to their triplet excited state and tune their redox potentials, which was achieved thanks to the design of orthogonal donor-acceptor dyads. The BODIPY dyads were used to promote a photoredox reaction, and the mechanism of the reaction was clarified. In the second chapter, organic chromophores that display thermally-activated delayed fluorescence (TADF) were studied. These were used to perform enantioselective photoredox reactions, and a mechanistic investigation allowed to elucidate the fate of these photosensitizers in the reaction. Thanks to their stronger reducing power, it was possible to demonstrate the employability of TADF dyes in artificial photosynthesis, as well. Last, the oxidation of biomass-derived compounds was studied in a photoelectrochemical cell. For this purpose, hematite photoanodes were synthesized in collaboration with Prof. Caramori’s group at the University of Ferrara (Italy) and they were tested in the presence of a redox mediator. In addition to this, the possibility of repurposing a copper(II) water oxidation catalyst for the oxidation of biomass was investigated in collaboration with Prof. Llobet’s group at ICIQ (Tarragona, Spain).

New methodologies in organocatalysis: from discovery to application and mechanistic

This PhD thesis deals with three different topics: i) sulfoxonium ylides, ii) donor-acceptor cyclopropanes, and iii) desymmetrization reactions. Catalysis, and in more detail organocatalysis, is the fil rouge linking the three subjects of study. The main focus treated during this doctorate period is the reactivity of sulfoxonium ylides, and in particular stabilized sulfoxonium ylides. Special attention has been dedicated to the behavior of these particular substrates under asymmetric and non-asymmetric reaction conditions. Moreover, also similarities and differences with the related, less stable, sulfonium ylides were fully analyzed, both experimentally and from a theoretical point of view. Two different reactions were developed in full. One conducted under acidic reaction conditions and the second one exploiting the asymmetric aminocatalysis. Subsequently, the reactivity of donor-acceptor cyclopropanes was studied. After different attempts in the development of a new catalytic methodology based on these substrates, a non-conventional reactivity conducted under phase transfer catalysis was discovered and optimized. In particular, a chemodivergent reaction depending on the reaction conditions was developed. Finally, during the period spent abroad, a preliminary study of a desymmetrization reaction was carried out. The studied reaction is based on an asymmetric elimination reaction conducted under asymmetric phosphoric acid catalysis. In summary, this PhD thesis shows the versatility of different organocatalytic methodologies when applied to different reactions and substrates.

Development of molecular-level switches and implementation into novel nanostructures and smart materials

The work presented in this thesis deals with the design, synthesis and investigation of (supra)molecular switches, and their implementation into novel nanostructures and smart devices. Part A deals with investigation of fundamental properties of Donor Acceptor Stenhouse Adducts (DASAs) as well as their implementation into polymer matrices in order to construct novel smart materials. Part B deals with the implementation of azobenzene photoswitches into pseudorotaxanes and the investigation of the effect of light-driven isomerization on the self-assembly and disassembly processes.

Design and study of self-assembled functional organic and hybrid systems for biological applications

The focus of self-assembly as a strategy for the synthesis has been confined largely to molecules, because of the importance of manipulating the structure of matter at the molecular scale. We have investigated the influence of temperature and pH, in addition to the concentration of the capping agent used for the formation of the nano-bio conjugates. For example, the formation of the narrower size distribution of the nanoparticles was observed with the increase in the concentration of the protein, which supports the fact that γ-globulin acts both as a controller of nucleation as well as stabiliser. As analyzed through various photophysical, biophysical and microscopic techniques such as TEM, AFM, C-AFM, SEM, DLS, OPM, CD and FTIR, we observed that the initial photoactivation of γ-globulin at pH 12 for 3 h resulted in small protein fibres of ca. Further irradiation for 24 h, led to the formation of selfassembled long fibres of the protein of ca. 5-6 nm and observation of surface plasmon resonance band at around 520 nm with the concomitant quenching of luminescence intensity at 680 nm. The observation of light triggered self-assembly of the protein and its effect on controlling the fate of the anchored nanoparticles can be compared with the naturally occurring process such as photomorphogenesis.Furthermore,our approach offers a way to understand the role played by the self-assembly of the protein in ordering and knock out of the metal nanoparticles and also in the design of nano-biohybrid materials for medicinal and optoelectronic applications. Investigation of the potential applications of NIR absorbing and water soluble squaraine dyes 1-3 for protein labeling and anti-amyloid agents forms the subject matter of the third chapter of the thesis. The study of their interactions with various proteins revealed that 1-3 showed unique interactions towards serum albumins as well as lysozyme. 69%, 71% and 49% in the absorption spectra as well as significant quenching in the fluorescence intensity of the dyes 1-3, respectively. Half-reciprocal analysis of the absorption data and isothermal titration calorimetric (ITC) analysis of the titration experiments gave a 1:1 stoichiometry for the complexes formed between the lysozyme and squaraine dyes with association constants (Kass) in the range 104-105 M-1. We have determined the changes in the free energy (ΔG) for the complex formation and the values are found to be -30.78, -32.31 and -28.58 kJmol-1, respectively for the dyes 1, 2 and 3. Furthermore, we have observed a strong induced CD (ICD) signal corresponding to the squaraine chromophore in the case of the halogenated squaraine dyes 2 and 3 at 636 and 637 nm confirming the complex formation in these cases. To understand the nature of interaction of the squaraine dyes 1-3 with lysozyme, we have investigated the interaction of dyes 1-3 with different amino acids. These results indicated that the dyes 1-3 showed significant interactions with cysteine and glutamic acid which are present in the side chains of lysozyme. In addition the temperature dependent studies have revealed that the interaction of the dye and the lysozyme are irreversible. Furthermore, we have investigated the interactions of these NIR dyes 1-3 with β- amyloid fibres derived from lysozyme to evaluate their potential as inhibitors of this biologically important protein aggregation. These β-amyloid fibrils were insoluble protein aggregates that have been associated with a range of neurodegenerative diseases, including Huntington, Alzheimer’s, Parkinson’s, and Creutzfeldt-Jakob diseases. We have synthesized amyloid fibres from lysozyme through its incubation in acidic solution below pH 4 and by allowing to form amyloid fibres at elevated temperature. To quantify the binding affinities of the squaraine dyes 1-3 with β-amyloids, we have carried out the isothermal titration calorimetric (ITC) measurements. The association constants were determined and are found to be 1.2 × 105, 3.6× 105 and 3.2 × 105 M-1 for the dyes, 1-3, respectively. To gain more insights into the amyloid inhibiting nature of the squaraine dyes under investigations, we have carried out thioflavin assay, CD, isothermal titration calorimetry and microscopic analysis. The addition of the dyes 1-3 (5μM) led to the complete quenching in the apparent thioflavin fluorescence, thereby indicating the destabilization of β-amyloid fibres in the presence of the squaraine dyes. Further, the inhibition of the amyloid fibres by the squaraine dyes 1-3, has been evidenced though the DLS, TEM AFM and SAED, wherein we observed the complete destabilization of the amyloid fibre and transformation of the fibre into spherical particles of ca. These results demonstrate the fact that the squaraine dyes 1-3 can act as protein labeling agents as well as the inhibitors of the protein amyloidogenesis. The last chapter of the thesis describes the synthesis and investigation of selfassembly as well as bio-imaging aspects of a few novel tetraphenylethene conjugates 4-6.Expectedly, these conjugates showed significant solvatochromism and exhibited a hypsochromic shift (negative solvatochromism) as the solvent polarity increased, and these observations were justified though theoretical studies employing the B3LYP/6-31g method. We have investigated the self-assembly properties of these D-A conjugates though variation in the percentage of water in acetonitrile solution due to the formation of nanoaggregates. Further the contour map of the observed fluorescence intensity as a function of the fluorescence excitation and emission wavelength confirmed the formation of J-type aggregates in these cases. To have a better understanding of the type of self-assemblies formed from the TPE conjugates 4-6, we have carried out the morphological analysis through various microscopic techniques such as DLS, SEM and TEM. 70%, we observed rod shape architectures having ~ 780 nm in diameter and ~ 12 μM in length as evidenced through TEM and SEM analysis. We have made similar observations with the dodecyl conjugate 5 at ca. 70% and 50% water/acetonitrile mixtures, the aggregates formed from 4 and 5 were found to be highly crystalline and such structures were transformed to amorphous nature as the water fraction was increased to 99%. To evaluate the potential of the conjugate as bio-imaging agents, we have carried out their in vitro cytotoxicity and cellular uptake studies though MTT assay, flow cytometric and confocal laser scanning microscopic techniques. Thus nanoparticle of these conjugates which exhibited efficient emission, large stoke shift, good stability, biocompatibility and excellent cellular imaging properties can have potential applications for tracking cells as well as in cell-based therapies. In summary we have synthesized novel functional organic chromophores and have studied systematic investigation of self-assembly of these synthetic and biological building blocks under a variety of conditions. The investigation of interaction of water soluble NIR squaraine dyes with lysozyme indicates that these dyes can act as the protein labeling agents and the efficiency of inhibition of β-amyloid indicate, thereby their potential as anti-amyloid agents.

Charge generation and recombination in hybrid organic,inorganic solar cells

This thesis deals with the investigation of exciton and charge dynamics in hybrid solar cells by time-resolved optical spectroscopy. Quasi-steady-state and transient absorption spectroscopy, as well as time-resolved photoluminescence spectroscopy, were employed to study charge generation and recombination in solid-state organic dye-sensitized solar cells, where the commonly used liquid electrolyte is replaced by an organic solid hole transporter, namely 2,2′7,7′-tetrakis-(N,N-di-p-methoxyphenyl-amine)-9,9′-spirobifluorene (spiro-MeOTAD), and polymer-metal oxide bulk heterojunction solar cells, where the commonly used fullerene acceptor [6,6]-phenyl C61 butyric acid methyl ester (PCBM) is replaced by zinc oxide (ZnO) nanoparticles. By correlating the spectroscopic results with the photovoltaic performance, efficiency-limiting processes and processes leading to photocurrent generation in the investigated systems are revealed. rnIt is shown that the charge generation from several all-organic donor-π-bridge-acceptor dyes, specifically perylene monoimide derivatives, employed in solid-state dye-sensitized solar cells, is strongly dependent on the presence of a commonly used additive lithium bis(trifluoromethanesulphonyl)imide salt (Li-TFSI) at the interface. rnMoreover, it is shown that charges can not only be generated by electron injection from the excited dye into the TiO2 acceptor and subsequent regeneration of the dye cation by the hole transporter, but also by an alternative mechanism, called preceding hole transfer (or reductive quenching). Here, the excited dye is first reduced by the hole transporter and the thereby formed anion subsequently injects an electron into the titania. This additional charge generation process, which is only possible for solid hole transporters, helps to overcome injection problems. rnHowever, a severe disadvantage of solid-state dye-sensitized solar cells is re-vealed by monitoring the transient Stark effect on dye molecules at the inter-face induced by the electric field between electrons and holes. The attraction between the negative image charge present in TiO2, which is induced by the positive charge carrier in the hole transporter due to the dielectric contrast between the organic spiro-MeOTAD and inorganic titania, is sufficient to at-tract the hole back to the interface, thereby increasing recombination and suppressing the extraction of free charges.rnBy investigating the effect of different dye structures and physical properties on charge generation and recombination, design rules and guidelines for the further advancement of solid-state dye-sensitized solar cells are proposed.rnFinally, a spectroscopic study on polymer:ZnO bulk heterojunction hybrid solar cells, employing different surfactants attached to the metal oxide nanoparticles, was performed to understand the effect of surfactants upon photovoltaic behavior. By applying a parallel pool analysis on the transient absorption data, it is shown that suppressing fast recombination while simultaneously maintaining the exciton splitting efficiency by the right choice of surfactants leads to better photovoltaic performances. Suppressing the fast recombination completely, whilst maintaining the exciton splitting, could lead to a doubling of the power conversion efficiency of this type of solar cell.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Accurate Treatment of Large Supramolecular Complexes by Double-Hybrid Density Functionals Coupled with Nonlocal van der Waals Corrections

In this work, we present a thorough assessment of the performance of some representative double-hybrid density functionals (revPBE0-DH-NL and B2PLYP-NL) as well as their parent hybrid and GGA counterparts, in combination with the most modern version of the nonlocal (NL) van der Waals correction to describe very large weakly interacting molecular systems dominated by noncovalent interactions. Prior to the assessment, an accurate and homogeneous set of reference interaction energies was computed for the supramolecular complexes constituting the L7 and S12L data sets by using the novel, precise, and efficient DLPNO-CCSD(T) method at the complete basis set limit (CBS). The correction of the basis set superposition error and the inclusion of the deformation energies (for the S12L set) have been crucial for obtaining precise DLPNO-CCSD(T)/CBS interaction energies. Among the density functionals evaluated, the double-hybrid revPBE0-DH-NL and B2PLYP-NL with the three-body dispersion correction provide remarkably accurate association energies very close to the chemical accuracy. Overall, the NL van der Waals approach combined with proper density functionals can be seen as an accurate and affordable computational tool for the modeling of large weakly bonded supramolecular systems.

Molecular and hybrid systems for solar-to-chemical energy conversion

My Ph.D. thesis was dedicated to the exploration of different paths to convert sunlight into the shape of chemical bonds, by the formation of solar fuels. During the past three years, I have focused my research on two of these, namely molecular hydrogen H2 and the reduced nicotinamide adenine dinucleotide enzyme cofactor NAD(P)H. The first could become the ideal energy carrier for a truly clean energy system; it currently represents the best chance to liberate humanity from its dependence on fossil fuels. To address this, I studied different systems which can achieve proton reduction upon light absorption. More specifically, part of my work was aimed to the development of a cost-effective and stable catalyst in combination with a well-known photochemical cycle. To this extent, I worked on transition metal oxides which, as demonstrated in this work, have been identified as promising H2 evolution catalysts, showing excellent activity, stability, and previously unreported versatility. Another branch of my work on hydrogen production dealt with the use of a new class of polymeric semiconductor materials to absorb light and convert it into H2. The second solar fuel mentioned above is a key component of the most powerful methods for chemical synthesis: enzyme catalysis. The high cost of the reduced forms prohibits large-scale utilization, so artificial photosynthetic approaches for regenerating it are being intensively studied. The first system I developed exploits the tremendous reducing properties of a scarcely known ruthenium complex which is able to reduce NAD+. Lastly, I sought to revert the classical role of the sacrificial electron donor to an active component of the system and, to boost the process, I build up an autonomous microfluidic system able to generate highly reproducible NAD(P)H amount, demonstrating the superior performance of microfluidic reactors over batch and representing another successful photochemical NAD(P)H regeneration system.

Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

A hybrid-mixed finite element formulation for the geometrically exact analysis of three-dimensional framed structures

This paper addresses the development of a hybrid-mixed finite element formulation for the quasi-static geometrically exact analysis of three-dimensional framed structures with linear elastic behavior. The formulation is based on a modified principle of stationary total complementary energy, involving, as independent variables, the generalized vectors of stress-resultants and displacements and, in addition, a set of Lagrange multipliers defined on the element boundaries. The finite element discretization scheme adopted within the framework of the proposed formulation leads to numerical solutions that strongly satisfy the equilibrium differential equations in the elements, as well as the equilibrium boundary conditions. This formulation consists, therefore, in a true equilibrium formulation for large displacements and rotations in space. Furthermore, this formulation is objective, as it ensures invariance of the strain measures under superposed rigid body rotations, and is not affected by the so-called shear-locking phenomenon. Also, the proposed formulation produces numerical solutions which are independent of the path of deformation. To validate and assess the accuracy of the proposed formulation, some benchmark problems are analyzed and their solutions compared with those obtained using the standard two-node displacement/ rotation-based formulation.

Toward Optimal Design of Piezoelectric Transducers Based on Multifunctional and Smoothly Graded Hybrid Material Systems

This work explores the design of piezoelectric transducers based on functional material gradation, here named functionally graded piezoelectric transducer (FGPT). Depending on the applications, FGPTs must achieve several goals, which are essentially related to the transducer resonance frequency, vibration modes, and excitation strength at specific resonance frequencies. Several approaches can be used to achieve these goals; however, this work focuses on finding the optimal material gradation of FGPTs by means of topology optimization. Three objective functions are proposed: (i) to obtain the FGPT optimal material gradation for maximizing specified resonance frequencies; (ii) to design piezoelectric resonators, thus, the optimal material gradation is found for achieving desirable eigenvalues and eigenmodes; and (iii) to find the optimal material distribution of FGPTs, which maximizes specified excitation strength. To track the desirable vibration mode, a mode-tracking method utilizing the `modal assurance criterion` is applied. The continuous change of piezoelectric, dielectric, and elastic properties is achieved by using the graded finite element concept. The optimization algorithm is constructed based on sequential linear programming, and the concept of continuum approximation of material distribution. To illustrate the method, 2D FGPTs are designed for each objective function. In addition, the FGPT performance is compared with the non-FGPT one.

Absorption spectrum of a strongly driven atom in a detuned squeezed vacuum

We present numerical and analytical results for the Mollow probe absorption spectrum of a coherently driven two-level system in a narrow bandwidth squeezed vacuum field. The spectra are calculated for the case where the Rabi frequency of the driving field is much larger than the natural linewidth and the squeezed vacuum carrier frequency is detuned from the driving laser frequency. The driving laser is on resonance. We show that in a detuned squeezed vacuum the standard Mellow features are each split into triplets. The central components of each triplet are weakly dependent on the squeezing phase but the sidebands strongly depend on the phase and can have dispersive or absorptive/emissive profiles. We also derive approximate analytical expressions for the spectral features and find that the multi-peak structure of the spectrum can be interpreted either via the eigenfrequencies of a generalized Floquet Hamiltonian or in terms of three-photon transitions between dressed stales involving a probe field photon and a correlated photon pair from the squeezed vacuum field.

Strongly 2-perfect cycle systems and their quasigroups

A recent result of Bryant and Lindner shows that the quasigroups arising from 2-perfect m-cycle systems form a variety only when m = 3, 5 and 7. Here we investigate the situation in the case where the distance two cycles are required to be in the original system.

In familial hyperaldosteronism type I, hybrid gene-induced aldosterone production dominates that induced by wild-type genes

We compared the aldosterone-producing potency of the angiotensin II-sensitive wild-type aldosterone synthase genes and the ACTH-sensitive hybrid 11 beta-hydroxylase/aldosterone synthase gene by examining aldosterone, PRA, and cortisol day-curves (2-hourly levels over 24 h) in patients with familial hyperaldosteronism type I, before and during long-term (0.8-13.5 yr) glucocorticoid treatment. In 8 untreated patients, PRA levels were usually suppressed, and aldosterone correlated strongly with cortisol (r = 0.69-0.99). Fourteen studies were performed on 10 patients receiving glucocorticoid treatment that corrected hypertension, hypokalemia, and PRA suppression in all. ACTH was markedly and continuously suppressed in 6 studies, 3 of which demonstrated strong correlations between aldosterone and PRA (r = 0.77-0.92), ACTH was only partially suppressed in the remaining 8 studies; aldosterone correlated strongly: 1) with cortisol alone in 5 (r = 0.71-0.98); 2) with cortisol (r = 0.90) and PRA (r = 0.74) in one; 3) with PRA only in one (r = 0.80); and 4) with neither PRA nor cortisol in one. Unless ACTH is markedly and continuously suppressed, aldosterone is more responsive to ACTH than to renin/angiotensin II, despite the latter being unsuppressed. This is consistent with the hybrid gene being more powerfully expressed than the wild-type aldosterone synthase genes in familial hyperaldosteronism type I.