Development and Application of Methods for the Description of Photochemical Processes in Condensed Phase

The interaction of complex molecular systems with light has great relevance in nature as well as for many of the latest technological developments. The process of photosynthesis converts light into chemical energy, thereby providing the primary energy source for life on Earth. Photovoltaic devices, as the technological implementation of this principle, constitute one of the most promising sources of electrical energy for the 21st century, whose application has increased tremendously in the past decade. The reverse process, the controlled emission of light from electronically activated (excited) molecules, is central to many modern technologies, the most prominent of which are presumably the ever smaller yet higher resolving display screens of hand-held computers. For all these applications, a fundamental understanding of the processes taking place at the atomistic scale is of key relevance to allow for a rational design and improvement of new technologies. However, due to the ultra-short time-scales on which the elementary steps of most light-induced phenomena occur and their inherent complexity, an exclusively experimental investigation is often tedious, in particular concerning the interpretation of the results. Here, the combination of experimental techniques and theoretical models can help to gain insights into the involved processes. For this purpose, the electronic structure of ground and light-activated (excited) states of the involved molecules as well as the interaction with their environment has to be approximated, which is the central topic of this work. In the first part, namely chapters 2-4, I present applications of the quantum-mechanical methodology introduced in chapter 1 to study light-induced processes in molecular systems. The so-called caged compounds studied in chapters 2 and 3 constitute an attempt to employ the remarkable spatio-temporal light control of modern lasers to control chemical reactions. For this purpose, the investigated, prototypical molecules nitro-phenylacetate (NPA) and ortho-nitrobenzylacetate (oNBA) serve as precursors for the active compounds CO2 and acetate, respectively. Upon irradiation with UV light, the active compound is released within nano- to microseconds, and may e.g. trigger subsequent reactions. In the above-mentioned sense, my theoretical investigation accompanied and guided an experimental study, which allowed to shed light on the molecular processes and to resolve the detail of the mechanism responsible for the light-induced reactivity. The common structural motif of NPA, oNBA and many other photo-active systems is the nitroaromatic moiety in the form of its smallest representative nitrobenzene (NB). Due to this prototypical character, the photochemistry of NB is relevant for many photochemical applications. In chapter 4, I report an extensive theoretical investigation of ground and excited states as well as the non-radiative decay of NB, which due to its small size and high symmetry allows for an application of a hierarchy of state-of-the-art quantum-chemical methods. Surprisingly, I found this small molecule to pose a serious challenge to electronic structure theory and consequently, some rather sophisticated ab initio methods fail to afford an accurate description, e.g. with respect to the photochemically very important ordering of the lowest triplet states. Nevertheless, I determined the mechanism of non-radiative decay in good agreement with experimental findings and, moreover, suggested an experiment to test my hypothesis. Although there exist a number of accurate and reliable quantum chemical methods that allow for an investigation of the ground and excited states of isolated systems with the molecular size of NPA, oNBA and NB, the environment often plays a crucial role and may decisively influence the light-induced processes, as e.g. in NPA. Hence, the approximate modeling of molecular environments for quantum-chemical problems in condensed phase is a very active field of research, which culminated in the 2013 Nobel Price for Chemistry, which was awarded to Karplus, Levitt and Warshel for their pioneering developments in the field of multiscale models for complex chemical systems. To enable a quantum-chemical description of photo-chemical excitation processes in condensed phase, I extended and implemented a quantum-classical polarizable-continuum model (PCM) for calculation of vertical excitation energies, which is described in chapter \ref{part:pcm}. In general, PCMs allow for an efficient computation of the often dominating electrostatic portion of the solute-solvent interaction by means of the macroscopic descriptors epsilon (dielectric constant) and epsilon_opt = n^2 (optical dielectric or squared refractive index, respectively). The implementation of the method was realized in such a way that its application to any quantum-chemical model that affords electron densities for ground- and excited-states is straightforward. For the systematic evaluation of the method, I composed the first set of experimental Benchmark Data for Solvatochromism in Molecules (xBDSM), and part of the data points were measured by myself. Comparing calculated gas phase to solvent shifts to the xBDSM set, I was able to demonstrate the convincing accuracy of my approach in combination with various levels of electronic structure theory and could shed light on the relation of different flavors of excited state PCMs. Moreover, a close examination of the contributions to the calculated shifts revealed general patterns, which are essential regarding any evaluation of calculated solvent shifts by comparison to the experiment. The implemented methodology will be released with one of the next versions of the Q-Chem quantum-chemical software package

Effect of different seawater Mg2Â + concentrations on calcification in two benthic foraminifers

Magnesium, incorporated in foraminiferal calcite (Mg/CaCC), is used intensively to reconstruct past seawater temperatures but, in addition to temperature, the Mg/CaCC of foraminiferal tests also depends on the ratio of Mg and Ca in seawater (Mg/CaSW). The physiological mechanisms responsible for these proxy relationships are still unknown. This culture study investigates the impact of different seawater Mg2 + on calcification in two benthic foraminiferal species precipitating contrasting Mg/{CaCC}: Ammonia aomoriensis, producing low-Mg calcite and Amphistegina lessonii, producing intermediate-Mg calcite. Foraminiferal growth and test thickness were determined and, Mg/Ca was analyzed using Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry ({LA}-{ICP}-{MS}). Results show that at present-day seawater Mg/{CaSW} of {\textasciitilde} 5, both species have highest growth rates, reflecting their adaptation to modern seawater element concentrations. Test thickness is not significantly affected by different Mg/{CaSW}. The relationship between Mg/{CaSW} and Mg/{CaCC} shows a distinct positive y-axis intercept, possibly reflecting at least two processes involved in foraminiferal biomineralization. The associated Mg partition ({DMg}) changes non-linearly with increasing Mg/{CaSW}, hence suggesting that the {DMg} is best described by an exponential function approaching an asymptote

Quality-assured training in the evaluation of cochlear implant electrode position: a prospective experimental study

Background The objective of this study was to demonstrate the utility of an approach in training predoctoral medical students, to enable them to measure electrode-to-modiolus distances (EMDs) and insertion-depth angles (aDOIs) in cochlear implant (CI) imaging at the performance level of a single senior rater. Methods This prospective experimental study was conducted on a clinical training dataset comprising patients undergoing cochlear implantation with a Nucleus® CI532 Slim Modiolar electrode (N = 20) or a CI512 Contour Advance electrode (N = 10). To assess the learning curves of a single medical student in measuring EMD and aDOI, interrater differences (senior-student) were compared with the intrarater differences of a single senior rater (test-retest). The interrater and intrarater range were both calculated as the distance between the 0.1th and 99.9th percentiles. A "deliberate practice" training approach was used to teach knowledge and skills, while correctives were applied to minimize faulty data-gathering and data synthesis. Results Intrarater differences of the senior rater ranged from - 0.5 to 0.5 mm for EMD and - 14° to 16° for aDOI (respective medians: 0 mm and 0°). Use of the training approach led to interrater differences that matched this after the 4th (EMD) and 3rd (aDOI) feedback/measurement series had been provided to the student. Conclusions The training approach enabled the student to evaluate the CI electrode position at the performance level of a senior rater. This finding may offer a basis for ongoing clinical quality assurance for the assessment of CI electrode position

9,9-Dimethyl-9-silafluorene

The title compound, C14H14Si, crystallizes with two almost identical mol­ecules (r.m.s. deviation = 0.080 Å for all non-H atoms) in the asymmetric unit. All atoms of the silafluorene moiety lie in a common plane (r.m.s. deviations = 0.049 and 0.035 Å for the two mol­ecules in the asymmetric unit). The Si—Cmeth­yl bonds are significantly shorter [1.865 (4)–1.868 (4) Å] than the Si—Caromatic bonds [1.882 (3)–1.892 (3) Å]. Owing to strain in the five-membered ring, the endocyclic C—Si—C angles are reduced to 91.05 (14) and 91.21 (14)°

Charge-transfer states in triazole linked donor-acceptor materials: Strong effects of chemical modification and solvation

© the Owner Societies 2017. A series of 1,2,3-triazole linked donor-acceptor chromophores are prepared by Click Chemistry from ene-yne starting materials. The effects of three distinct chemical variations are investigated: enhancing the acceptor strength through oxidation of the sulphur atom, alteration of the double bond configuration, and variation of the triazole substitution pattern. A detailed photophysical characterization shows that these alterations have a negligible effect on the absorption while dramatically altering the emission wavelengths. In addition, strong solvatochromism is found leading to significant red shifts in the case of polar solvents. The experimental findings are rationalized and related to the electronic structure properties of the chromophores by time-dependent density functional theory as well as the ab initio algebraic diagrammatic construction method for the polarization propagator in connection with a new formalism allowing to model the influence of solvation onto long-lived excited states and their emission energies. These calculations highlight the varying degree of intramolecular charge transfer character present for the different molecules and show that the amount of charge transfer is strongly modulated by the conducted chemical modifications, by the solvation of the chromophores, and by the structural relaxation in the excited state. It is, furthermore, shown that enhanced charge separation, as induced by chemical modification or solvation, reduces the singlet-triplet gaps and that two of the investigated molecules possess sufficiently low gaps to be considered as candidates for thermally activated delayed fluorescence

Eliminating the Reverse ISC Bottleneck of TADF Through Excited State Engineering and Environment‐Tuning Toward State Resonance Leading to Mono‐Exponential Sub‐µs Decay. High OLED External Quantum Efficiency Confirms Efficient Exciton Harvesting

The electronic structure and photophysics of the recently designed organic direct singlet harvesting (DSH) molecule are explored, in which donor (D) and acceptor (A) are held at distance by two bridges. One of the bridges is functionalized with fluorene. This structure leads to an ultrasmall singlet–triplet energy gap of ∆E (S1−T1) ≈ 10 cm−1 (≈1 meV) between the charge transfer states 1,3CT and shows an energetically close-lying 3ππ* state localized on fluorene. Dielectric constant variation of the environment leads to state crossing of 3ππ* and 1,3CT near ε = 2.38 (toluene), as confirmed through time-dependent density functional theory (DFT) and state-specific DFT/polarizable continuum model excited-state calculations. Transient absorption (TA) and time-resolved luminescence in the femtosecond to microsecond regimes show rates of intersystem crossing (ISC) and reverse ISC (rISC) of >109 s–1. Thus, a strictly mono-exponential short-lived photo-luminescence decay (431 ns) is observed, revealing that rISC is no longer the bottleneck responsible for long thermally activated delayed fluorescence. Ultrafast TA displays a time constant of ≈700 fs, representing the relaxation time of DSH and its solvent environment to the relaxed 1CT state with a molecular dipole moment of ≈40 D. Importantly, OLED devices, emitting sky-blue light and showing high external quantum efficiency of 19%, confirm that singlet and triplet excitons are harvested efficiently

Which clustering algorithm is better for predicting protein complexes?

<p>Abstract</p> <p>Background</p> <p>Protein-Protein interactions (PPI) play a key role in determining the outcome of most cellular processes. The correct identification and characterization of protein interactions and the networks, which they comprise, is critical for understanding the molecular mechanisms within the cell. Large-scale techniques such as pull down assays and tandem affinity purification are used in order to detect protein interactions in an organism. Today, relatively new high-throughput methods like yeast two hybrid, mass spectrometry, microarrays, and phage display are also used to reveal protein interaction networks.</p> <p>Results</p> <p>In this paper we evaluated four different clustering algorithms using six different interaction datasets. We parameterized the MCL, Spectral, RNSC and Affinity Propagation algorithms and applied them to six PPI datasets produced experimentally by Yeast 2 Hybrid (Y2H) and Tandem Affinity Purification (TAP) methods. The predicted clusters, so called protein complexes, were then compared and benchmarked with already known complexes stored in published databases.</p> <p>Conclusions</p> <p>While results may differ upon parameterization, the MCL and RNSC algorithms seem to be more promising and more accurate at predicting PPI complexes. Moreover, they predict more complexes than other reviewed algorithms in absolute numbers. On the other hand the spectral clustering algorithm achieves the highest valid prediction rate in our experiments. However, it is nearly always outperformed by both RNSC and MCL in terms of the geometrical accuracy while it generates the fewest valid clusters than any other reviewed algorithm. This article demonstrates various metrics to evaluate the accuracy of such predictions as they are presented in the text below. Supplementary material can be found at: <url>http://www.bioacademy.gr/bioinformatics/projects/ppireview.htm</url></p

Predicting gene function using hierarchical multi-label decision tree ensembles

<p>Abstract</p> <p>Background</p> <p><it>S. cerevisiae</it>, <it>A. thaliana </it>and <it>M. musculus </it>are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challenge, however, to develop methods that assign biological functions to the ORFs in these genomes automatically. Different machine learning methods have been proposed to this end, but it remains unclear which method is to be preferred in terms of predictive performance, efficiency and usability.</p> <p>Results</p> <p>We study the use of decision tree based models for predicting the multiple functions of ORFs. First, we describe an algorithm for learning hierarchical multi-label decision trees. These can simultaneously predict all the functions of an ORF, while respecting a given hierarchy of gene functions (such as FunCat or GO). We present new results obtained with this algorithm, showing that the trees found by it exhibit clearly better predictive performance than the trees found by previously described methods. Nevertheless, the predictive performance of individual trees is lower than that of some recently proposed statistical learning methods. We show that ensembles of such trees are more accurate than single trees and are competitive with state-of-the-art statistical learning and functional linkage methods. Moreover, the ensemble method is computationally efficient and easy to use.</p> <p>Conclusions</p> <p>Our results suggest that decision tree based methods are a state-of-the-art, efficient and easy-to-use approach to ORF function prediction.</p