Figure 6. 4: Single-molecule lines. The laser is scanned over 10 GHz. Vg is kept at -40 V during the whole experiment. Vsd was set at 50 V during 2 minutes before starting the experiment. At t = 0, the source-drain voltage was switched off. After 1 hour, we set it to 50 V and switched it off again after 30 minutes. The first regime exhibits molecules drifting towards a new spectral position over time scales of the order of a few hours (at least). These very slow drifts cover a range exceeding 10 GHz. In contrast with this, some molecules do not show any shift of their absorption frequencies. Similar effects had been reported in a former single-molecule study on silicon carbide (SiC) [21, 22]. However, in this study, the charges were not present in the matrix (which was a Shpol’skii n-hexadecane matrix) but onto the surface of SiC, a large
Figure 6. 6: Spectral shift of a molecule line as a function of the log of time. We previously applied different source-drain voltages for 10 minutes and measured the spectral position of the molecule during 10 minutes. We applied a gate voltage Vg=- 50 V during the whole experiment. We fitted the shift with Eq. 6.4. The inset shows the plot of β as a function of the previously applied Vsd (from 10 to 50 V). The solid line is a guide for the eye. The presented first phenomenological model assumed that the charges get trapped or detrapped in only one jump. A more realistic model should take into account the possibilities to have several jumps, such as the Scher and Montroll model [133–136], presented in the following part. The continuous-time random walk The shift of the absorption frequency of the molecule lines while applying a gate voltage can be related to the shift of the threshold voltage under a gate xxxx applied over an extended period of time. In a previous study, it has been shown that this shift is directly connected to a decrease of the measured current in the device [137]. This decrease of the current is a well-known phenomenon in disordered solids and diverse attempts to give a physical explanation have been conducted. Among them, the continuous-time random-walk (CTRW) theory, developed by Xxxxx and Xxxxxxxx [136], gives the following dependence of the current as a function of time: I ∝ t−(1−α) for t < tτ , (6.5) I ∝ t−(1+α) for t > tτ , ∼ where the parameter α (0 < α < 1) characterises the dispersion and tτ is the transit time. This model has been successful in describing experimental data in the case of dispersive carrier transport in amorphous solids. In the Scher- Montroll model, the transport is represented as a chain of hopping events, based on a distribution of waiting times (ψ(t) t−(1+α)). In that case, all of the essential features of dispersive transport can be described. Small variations of the hopping distance will then introduce a broad distribution in hopping times. Similarly, in the case of multiple trapping transport, broad release time distributions can be obtained for small variations in the trap depth. It has also been shown that hopping between sites which are exponentially distributed in energy also gives rise to dispersive transport [138]. The main difference be- tween these explanations resides in the fact that, in some cases, the dispersion coefficient α will be strongly temperature dependent (for models based on activated transp...
Figure 6. 7: The optimization trajectory leading to the best molecule produced by the fragment-based evolution. The numbers under the structures indicate their fitness score. Note that the SO3C2H3-group of the second parent molecule was modified to a SO2C2H3-group by an error in our program. This bug was later fixed. In later fitness comparisons, not much influence on fitness was found by the presence or absence of the extra oxygen atom, so this glitch will probably not have influenced evolution much. The change in fitness over the generations To study the differences between the atom-based and fragment-based evolution, we first gathered of each generation the maximum fitness value (the fitness of the “best” molecule) and the average fitness value. These values are plotted in Figure 6.8. 85 80 75 70 Fitness 65 60 55 50 45 40 35 30 Generation number Atom average Atom best Fragment average Fragment best Figure 6.8: The average and the best fitness of molecules in each generation for the atom-based and fragment-based evolution. Figure 6.8 shows that both the average fitness and the maximum fitness of the molecules in the population grow as the evolution proceeds. This means that new and better molecules are found, which implies that evolution improves upon pure selection (since pure selection would cause the average and maximum fitnesses of the later generations to approach the maximum of the first generation). However, virtual screening of a large library will also increase maximum fitness, as there is always a probability that a new molecule will improve upon the known compounds. We should therefore analyze our data further to be able to say whether evolution is truly more effective or efficient than random search. Fitting the fitnesses of the randomly generated first generation to a Gaussian (Figure 6.9) results in a best fit with mean value 36.7 and a standard deviation of 4.3. 25 Initial population 20 Final Atom-based Final Fragment-based 15 10 5 0 Docking score Figure 6.9: The distribution of fitness scores of the molecules of three populations fitted to Gaussians. The populations are the initial population, the atom-based population containing the highest-scoring atom-based molecule (8th atom-based generation), and the fragment-based population containing the highest-scoring fragment-based molecule (the 10th fragment- based generation). The best overall result of evolution (score=76) lies about 9 standard deviations from this average. Therefore the probability t...
Figure 6. Model of the stress-strain-curve in the complete elastic-plastic region Model of strip deformation by the coiler tension The calculation starts with an assumed flatness profile of the strip exiting the last stand to which no coiler tension is applied: IU = L(x) − L0 105 L0
Figure 6. The Top 1% of Differential Con- nections between Memory Athletes and Matched Controls Red connections depict stronger and blue con- nections depict weaker FC in memory athletes compared to controls. One hypothesis for the efficacy of mnemonic strategies in- xxxxx their use of naturally evolved skills, such as visuospatial memory and navigation (Xxxxxxx et al., 2003). In the method of loci, abstract and unrelated information units are transformed into concrete and related information patterns that can more easily be processed by memory-related brain structures, such as the hippocampus. The method of loci has been associated with hippocampal place and grid cells (Xxxxxxxxx, 2010), which are also active during mental navigation (Bellmund et al., 2016) and have been involved in episodic memory encoding and retrieval (Xxxxxx et al., 2013; Xxxxxx et al., 2014). Brain regions critical for visuospatial memory and navigation, such as retrosplenial and hippocampal areas, are engaged during mnemonic encoding in memory athletes (Xxxxxxx et al., 2003). Acquisition of the method of loci in novices is related to activation increases in the left hippocampal region; its use during encoding is related with increased activation in the left occipito-parietal cortex, retrosplenial cortex, and DLPFC (Xxxxxx et al., 2003); and its use during recall is related with increased activation in the left parahippocampal gyrus and retrosplenial cortex (Xxxxx et al., 2005). These studies converge with our data in that the left parahippocampal gyrus and bilateral retrosplenial cortex both showed significant changes in network connectivity be- tween memory athletes and controls. We identified the right DLPFC as a hub for a number of con- nections that contributed most strongly to the transfer effect. The DLPFC is more strongly activated when information is en- coded in a more structured way, e.g., by chunking (Bor et al., 2003). In particular, the right DLPFC has been linked to the use of memory strategies: patients with right DLPFC lesions are specifically impaired when using strategies during memory tasks (Chase et al., 2008), and transcranial magnetic stimulation of the right DLPFC interferes with retrieval only in users of encoding strategies (Man- enti et al., 2010). The right DLPFC shows activation increases mainly for the en- coding of visual material (Xxxxxx et al., 1998; Xxxxxxx et al., 2002), particularly during encoding via visuospatial mne- monics, such as the method of loci (Xx...
Figure 6. 1 shows the prevailing winds from ESE direction smoothly pass through the site and along Fanling highway. However, for the prevailing E wind, no potential wind corridors penetrating the development site can be captured in general.
Figure 6. 2 shows the prevailing winds from SE and SSE directions pass through the site to ventilate the downstream areas along multiple wind corridors. No significant wind blockage can be captured along SE and SSE wind directions.
Figure 6. An example of a vignette used to similar effect as the factoid in Figure 5. Pull-Quotes and Factoids select and apply the various techniques to satisfy these goals.
