Structural Disorder in Layered Hybrid Halide Perovskites: Types of Stacking Faults, Influence on Optical Properties and Their Suppression by Crystallization Engineering

Layered hybrid halide perovskites (LHHPs) are an emerging type of semiconductor with a set of unique optoelectronic properties. However, the solution processing of high-quality LHHPs films with desired optical properties and phase composition is a challenging task, possibly due to the structural disorder in the LHHP phase. Nevertheless, there is still a lack of experimental evidence and understanding of the nature of the structural disorder in LHHPs and its influence on the optical properties of the material. In the current work, using 2D perovskites (C4H9NH3)2(CH3NH3)n−1PbnI3n+1 (further BA2MAn−1PbnI3n+1) with n = 1–4 as a model system, we demonstrate that deviations in LHHPs optical properties and X-ray diffraction occur due to the presence of continuous defects—Stacking Faults (SFs). Upon analyzing the experimental data and modeled XRD patterns of a possible set of stacking faults (SFs) in the BA2MAPb2I7 phase, we uncover the most plausible type of SFs, featured by the thickness variation within one perovskite slab. We also demonstrate the successful suppression of SFs formation by simple addition of BAI excess into BA2MAn−1PbnI3n+1 solutions.

Do humans prefer cognitive effort over doing nothing?

Humans and other animals find mental (and physical) effort aversive and have the fundamental drive to avoid it. However, exerting no effort, doing nothing, is also aversive: it leads to boredom. Here, we ask whether people choose to exert effort when the alternative is to do nothing at all. Across nine studies, participants completed variants of the demand selection task, in which they repeatedly selected between a cognitively effortful task (e.g., simple addition, Stroop task) and a task that required no effort (e.g., doing nothing, watching the computer complete the Stroop). We then tabulated people’s choices. Across all studies and a mini meta-analysis, we found no evidence of effort avoidance and sometimes even a preference for effort when the alternative was doing nothing. Our findings reveal the limits of effort avoidance, suggesting that people do not seek to completely minimize effort expenditure.

Empirical Determination of Sieve Size Statistics from Grain Measurement

<p>Relationships between sieve grain size and thin section grain size have been determined empirically from the study of 72 artificially created sendstone samples. Modern sands were sieved into size fractions, which were recombined in a log normal distribution to give samples with a range of means and standard deviations, but with similar individual grain properties. Sample splits of these were impregnated with resin, and the size distribution of grain long axes selected by point counter in thin section was compared with that found by sieving the remaining sample. This method attempts to minimise the effects of factors that influence apparent size in thin section. The results have been compared with those of (1958, 1962) who studied the same size relationships in 38 natural sandstones, e.g. This work: Sieve size from Folk = 1.078(thin section mean) + 0.200 phi graphical mean 1/3(Ø16+Ø50+Ø84) Friedman (1958): Sieve size mean from = 0.903(thin section mean) + 0.381 phi combined quartile measures Ø25, Ø50,Ø75 The regression coefficients differ from those of Friedman, probably because of the range of mean sizes investigated in the present work was twice as large (5.7 phi units vs. 2.6 phi units). The correlation coefficient relating sieve to thin section analysis decreases progressively, as Friedman found, from mean (0.992) to standard deviation (0.958), skewness (O.536), and kurtosis (0.249). The correlation for skewness and kurtosis is not significant. The size range was extended to -3.5 phi by the study of the mean size of selected gravel samples measured in sawn slabs. The resulting regression line has a slope of one and an intercept of 0.4 phi and is close to that found for the sands. Grain size in grain mount is also closely related to sieve and thin section size, and a preliminary study of pebble size measured from photographs suggests that this may also be converted to an equivalent sieve size. On qualitative grounds the relationships between the various mean size statistics should involve the simple addition of a constant phi value. However the slopes of the regression equations found in the present work differ slightly from a slope of one. This difference is shown to represent a progressive shape change with size. For a constant b/a ratio of 0.73 or 0.70 conversion of thin section mean size (in phi units) to an equivalent sieve value should therefore be made by the simple addition of a 0.33 or 0.40 phi constant respectively.</p>

Empirical Determination of Sieve Size Statistics from Grain Measurement

<p>Relationships between sieve grain size and thin section grain size have been determined empirically from the study of 72 artificially created sendstone samples. Modern sands were sieved into size fractions, which were recombined in a log normal distribution to give samples with a range of means and standard deviations, but with similar individual grain properties. Sample splits of these were impregnated with resin, and the size distribution of grain long axes selected by point counter in thin section was compared with that found by sieving the remaining sample. This method attempts to minimise the effects of factors that influence apparent size in thin section. The results have been compared with those of (1958, 1962) who studied the same size relationships in 38 natural sandstones, e.g. This work: Sieve size from Folk = 1.078(thin section mean) + 0.200 phi graphical mean 1/3(Ø16+Ø50+Ø84) Friedman (1958): Sieve size mean from = 0.903(thin section mean) + 0.381 phi combined quartile measures Ø25, Ø50,Ø75 The regression coefficients differ from those of Friedman, probably because of the range of mean sizes investigated in the present work was twice as large (5.7 phi units vs. 2.6 phi units). The correlation coefficient relating sieve to thin section analysis decreases progressively, as Friedman found, from mean (0.992) to standard deviation (0.958), skewness (O.536), and kurtosis (0.249). The correlation for skewness and kurtosis is not significant. The size range was extended to -3.5 phi by the study of the mean size of selected gravel samples measured in sawn slabs. The resulting regression line has a slope of one and an intercept of 0.4 phi and is close to that found for the sands. Grain size in grain mount is also closely related to sieve and thin section size, and a preliminary study of pebble size measured from photographs suggests that this may also be converted to an equivalent sieve size. On qualitative grounds the relationships between the various mean size statistics should involve the simple addition of a constant phi value. However the slopes of the regression equations found in the present work differ slightly from a slope of one. This difference is shown to represent a progressive shape change with size. For a constant b/a ratio of 0.73 or 0.70 conversion of thin section mean size (in phi units) to an equivalent sieve value should therefore be made by the simple addition of a 0.33 or 0.40 phi constant respectively.</p>

Z Scores, Standard Scores, and Composite Test Scores Explained

Patients may be assessed using a battery of tests where different tests yield scores in different units, where different tests have different minimum and maximum scores, and where higher or lower scores mean different things in different tests. Therefore, a composite test score cannot be obtained by simple addition or averaging of scores in the individual tests. However, if performances in individual tests are converted to Z scores, the Z scores can be added or averaged to yield a composite score that can be interpreted or processed using conventional statistical methods. This article explains in simple ways how Z scores are calculated, what the properties of Z scores are, how Z scores can be interpreted, and how Z scores can be converted into other standard scores.

Frequency-Mixing Lasing Mode at European XFEL

We demonstrate generation of X-ray Free-Electron Laser (XFEL) pulses in frequency mixing mode at the SASE3 line of the European XFEL. The majority of the SASE3 FEL segments are tuned at two frequencies ω1 and ω2 following an alternate pattern. Leveraging on non-linearities generated through longitudinal dispersion in the system, we obtain electron bunching at a frequency difference ωFM=ω2−ω1. FEL amplification at ωFM follows in a few last radiator segments. We report on the generation of frequency mixing at photon energies between 500 eV and 1100 eV with pulse energies, depending on the length of the radiator, in the mJ level. This method allows generating low photon energies in cases where the FEL runs at high electron energy and the target photon energy cannot be reached in the main undulator, with the simple addition of a short, custom-made afterburner.

Analogy-related Information Can be Accessed by Simple Addition and Subtraction of fMRI Activation Patterns, without Participants Performing any Analogy Task

Analogical reasoning, e.g. inferring that teacher is to chalk as mechanic is to wrench, plays a fundamental role in human cognition. However, whether brain activity patterns of individual words are encoded in a way that could facilitate analogical reasoning is unclear. Recent advances in computational linguistics have shown that information about analogical problems can be accessed by simple addition and subtraction of word embeddings (e.g., wrench = mechanic + chalk – teacher). Critically, this property emerges in artificial neural networks that were not trained to produce analogies but instead were trained to produce general-purpose semantic representations. Here, we test whether such emergent property can be observed in representations in human brains, as well as in artificial neural networks. fMRI activation patterns were recorded while participants viewed isolated words but did not perform analogical reasoning tasks. Analogy relations were constructed from word pairs that were categorically or thematically related, and we tested whether the predicted fMRI pattern calculated with simple arithmetic was more correlated with the pattern of the target word than other words. We observed that the predicted fMRI patterns contain information not only about the identity of the target word but also its category and theme (e.g., teaching-related). In summary, this study demonstrated that information about analogy questions can be reliably accessed with the addition and subtraction of fMRI patterns, and that, similar to word embeddings, this property holds for task-general patterns elicited when participants were not explicitly told to perform analogical reasoning.

Electrophysiological evidence for internalized representations of canonical finger-number gestures and their facilitating effects on adults’ math verification performance

Fingers facilitate number learning and arithmetic processing in early childhood. The current study investigated whether images of early-learned, culturally-typical (canonical), finger montring patterns presenting smaller (2,3,4) or larger (7,8,9) quantities still facilitate adults’ performance and neural processing in a math verification task. Twenty-eight adults verified solutions to simple addition problems that were shown in the form of canonical or non-canonical finger-number montring patterns while measuring Event Related Potentials (ERPs). Results showed more accurate and faster sum verification when sum solutions were shown by canonical (versus non-canonical) finger patterns. Canonical finger montring patterns 2–4 led to faster responses independent of whether they presented correct or incorrect sum solutions and elicited an enhanced early right-parietal P2p response, whereas canonical configurations 7–9 only facilitated performance in correct sum solution trials without evoking P2p effects. The later central-parietal P3 was enhanced to all canonical finger patterns irrespective of numerical range. These combined results provide behavioral and brain evidence for canonical cardinal finger patterns still having facilitating effects on adults’ number processing. They further suggest that finger montring configurations of numbers 2–4 have stronger internalized associations with other magnitude representations, possibly established through their mediating role in the developmental phase in which children acquire the numerical meaning of the first four number symbols.