Globally Optimal Catalysts: Computerbasierte Optimierung von abstrakten katalytischen Einbettungen für beliebige chemische Reaktionen

In the context of inverse design of molecules with desired optimal properties, the long-term goal of this Thesis is to develop a general framework which tackles the design of molecular systems for an optimal catalytic effect onto arbitrary chemical reactions. For any given reaction, an arrangement of an additional molecular framework around this reaction center is sought such that the energetic reaction barrier is lowered as much as possible. As necessary abstraction layer, the so-called globally optimal catalyst (GOCAT) model is introduced, and, furthermore, evolutionary algorithms (EAs) are harnessed as implemented in our global optimization suite for chemical problems, ogolem, which was highly extended to allow for these catalysis optimizations. Starting with a maximally reductionistic approach for studying the non-bonding interactions, electrostatic GOCATs are introduced that consist of arbitrary numbers, distributions and strengths of partial point charges around reacting molecules, mostly surrounding these on a common exposed surface. In the end, two reactions are studied in detail within the general topic of electrostatic catalysis. Some of the initially present model approximations are already sufficiently lifted, still-existing ones are critically assessed and further future extensions to the framework are discussed. Moreover, many method development matters are addressed: They range from optimal shared-memory parallelization, exemplified for global parameter optimization of the reactive force field, ReaxFF, via diversity control parameters for the EAs, applied to a cluster structure optimization problem, to EA operator benchmarks and optimizations of abstract electrostatics.Im Kontext von inversem Design von Molekülen mit optimalen Eigenschaften versucht die vorliegende Arbeit als Langzeitziel eine passende Plattform zu entwickeln, welche das generelle Design molekularer Systeme für einen optimalen Katalyseeffekt auf beliebige chemische Reaktionen projektiert. Für eine gegeben Reaktion soll eine hinzukommende chemische Umgebung komponiert werden, welche die Reaktionsenergiebarriere so weit wie möglich vermindert. Als notwendige Abstraktionsschicht wird das sogenannte Modell des globally optimal catalyst (GOCAT) eingeführt und außerdem kommen Evolutionäre Algorithmen (EAs) zur Anwendung, wie sie bereits in unserem Programmpaket zur Lösung allgemeiner globaler Optimierungsprobleme der Chemie, ogolem, bereitgestellt werden, welches jedoch deutlich für diese Katalyseoptimierungen ergänzt wurde. Angefangen in einem maximal-reduktionistischen Ansatz werden elektrostatische GOCATs erarbeitet, die aus einer beliebigen Anzahl, Verteilung und Stärke von Partialladungen bestehen und rund um die reagierenden Moleküle drapiert werden, meist auf einer gemeinsamen exponierten Oberfläche. Insgesamt werden zwei Reaktionen detailliert untersucht im generellen Kontext von elektrostatischer Katalyse. Einige eingangs vorhandene Modellannahmen werden bereits systematisch verbessert, noch vorhandene kritisch beleuchtet und künftige Erweiterungen auseinandergesetzt. Weiterhin werden unterschiedliche Methodenentwicklungsaspekte angesprochen: Diese reichen von verbesserter Parallelisierung in Mehrprozessorarchitekturen, beispielhaft gezeigt anhand einer globalen Parameteroptimierung des reaktiven Kraftfeldes ReaxFF, über Diversitätskontrollparameter des EAs, illustriert mittels eines Clusterstrukturoptimierungsproblems, bis hin zu EA-Operator-Testevaluationen und allgemeinen abstrakten Elektrostatikoptimierungen

Globally Optimal Catalytic Fields – Inverse Design of Abstract Embeddings for Maximum Reaction Rate Acceleration

The search for, and understanding of, good catalysts for chemical reactions is a central issue for chemists. Here, we present first steps toward developing a general computational framework to better support this task. This framework combines efficient, unbiased global optimization techniques with an abstract representation of the catalytic environment, to shrink the search space. To analyze the resulting catalytic embeddings, we employ dimensionality reduction and clustering techniques. This not only provides an inverse design approach to new catalytic embeddings but also illuminates the actual interactions behind catalytic effects. All this is illustrated here with a strictly electrostatic model for the environment and with two versions of a selected example reaction. We close with detailed discussions of future improvements of our framework

Femtosecond Time-Resolved Dynamics of <i>trans</i>-Azobenzene on Gold Nanoparticles

We report a first femtosecond time-resolved transient absorption study of the photoinduced ultrafast dynamics of <i>trans</i>-azobenzene (AB) on gold nanoparticles (AuNPs). The observed changes in optical density following excitation at λ = 357 nm were analyzed by using temperature-dependent Mie theory and by Lorentzian band fitting to disentangle the ultrafast relaxation of the local surface plasmon resonance (LSPR) excitation of the Au core and the electronic deactivation of the attached AB ligands. The analysis of the dynamics associated with the AB photochrome yielded lifetime constants of τ₁ = 1.2 ± 0.2 ps and τ₂ = 4.7 ± 1.1 ps. Both values together indicate surprisingly little difference in the dynamics of the AB ligand on the AuNPs vs in solution. Our results thus highlight the extraordinarily efficient electronic decoupling of the azo chromophore and the Au core by the alkyl linker chain

Ultrafast dynamics of a bi-stable azopyridine Ni-porphyrin spin switch after photoexcitation in the porphyrin B-bands

Femtosecond time-resolved absorption measurements of a magnetically bi-stable azopyridine Ni-porphyrin in solution at room temperature show that the photo-induced dynamics are dominated by transient low-spin ⇄ high-spin interconversion involving Ni (d2) and (d, d) states

Evaluation of objective and perceived mental fatigability in older adults with vascular risk

OBJECTIVES: Mental fatigability refers to the failure to sustain participation in tasks requiring mental effort. Older adults with vascular risk are at particular risk for experiencing mental fatigability. The present study (1) tested a new way of measuring objective mental fatigability by examining its association with perceived mental fatigability; and (2) identified psychological, physiological, and situational factors that would be associated with mental fatigability. METHODS: A cross-sectional study was conducted with 49 community-dwelling participants aged 75+ years with vascular risk. A 20-minute fatigability-manipulation task was used to induce mental fatigability and develop objective and perceived mental fatigability measures. Objective fatigability was calculated by the change of reaction time over the course of the task. Perceived fatigability was calculated by the change of fatigue self-reported before and after the task. A set of potential psychological, physiological, and situational predictors were measured. RESULTS: There was a significant increase in reaction time and self-reported fatigue to the fatigability manipulation task, indicating occurrence of objective and perceived mental fatigability. Reaction time and self-reported fatigue were moderately, but significantly correlated. Higher levels of executive control and having a history of more frequently engaging in mental activities were associated with lower objective mental fatigability. None of the examined factors were associated with perceived mental fatigability. CONCLUSION: Objective and perceived mental fatigability were sensitive to our fatigability-manipulation task. While these two measures were correlated, they were not associated with the same factors. These findings need to be validated in a large study with a more heterogeneous sample and a greater variety of fatigability-manipulation tasks

Magnetic resonance spectroscopic imaging and volumetric measurements of the brain in patients with postcancer fatigue: a randomized controlled trial

Contains fulltext : 127313.pdf (publisher's version ) (Open Access)Background Postcancer fatigue is a frequently occurring problem, impairing quality of life. Until now, little is known about (neuro) physiological factors determining postcancer fatigue. For non-cancer patients with chronic fatigue syndrome, certain characteristics of brain morphology and metabolism have been identified in previous studies. We investigated whether these volumetric and metabolic traits are a reflection of fatigue in general and thus also of importance for postcancer fatigue. Methods Fatigued patients were randomly assigned to either the intervention condition (cognitive behavior therapy) or the waiting list condition. Twenty-five patients in the intervention condition and fourteen patients in the waiting list condition were assessed twice, at baseline and six months later. Baseline measurements of 20 fatigued patients were compared with 20 matched non-fatigued controls. All participants had completed treatment of a malignant, solid tumor minimal one year earlier. Global brain volumes, subcortical brain volumes, metabolite tissue concentrations, and metabolite ratios were primary outcome measures. Results Volumetric and metabolic parameters were not significantly different between fatigued and non-fatigued patients. Change scores of volumetric and metabolic parameters from baseline to follow-up were not significantly different between patients in the therapy and the waiting list group. Patients in the therapy group reported a significant larger decrease in fatigue scores than patients in the waiting list group. Conclusions No relation was found between postcancer fatigue and the studied volumetric and metabolic markers. This may suggest that, although postcancer fatigue and chronic fatigue syndrome show strong resemblances as a clinical syndrome, the underlying physiology is different