Superradiant Emission from Coherent Excitons in van Der Waals Heterostructures

Recent advancements in isolation and stacking of layered van der Waals materials have created an unprecedented paradigm for demonstrating varieties of 2D quantum materials. Rationally designed van der Waals heterostructures composed of monolayer transition-metal dichalcogenides (TMDs) and few-layer hBN show several unique optoelectronic features driven by correlations. However, entangled superradiant excitonic species in such systems have not been observed before. In this report, it is demonstrated that strong suppression of phonon population at low temperature results in a formation of a coherent excitonic-dipoles ensemble in the heterostructure, and the collective oscillation of those dipoles stimulates a robust phase synchronized ultra-narrow band superradiant emission even at extremely low pumping intensity. Such emitters are in high demand for a multitude of applications, including fundamental research on many-body correlations and other state-of-the-art technologies. This timely demonstration paves the way for further exploration of ultralow-threshold quantum-emitting devices with unmatched design freedom and spectral tunability.     

Fast internal dynamics in polyelectrolyte gels measured by dynamic light scattering

Summary Dynamic light scattering was used to investigate the dynamics of sodium poly(styrene sulfonate) and fully neutralized poly(acrylic acid) gels as a function of the degree of swelling and weight ratio of cross-linking agent. It was shown that the collective diffusion coefficient increases with increasing degree of swelling and that the diffusion coefficient shows stronger concentration dependence than predicted by scaling arguments. For gel samples measured at the swelling equilibrium, the diffusion coefficient increases with increasing gel concentration for both gel systems.     

Modeling tool wear in end-milling using enhanced GMDH learning networks

This paper presents an enhanced approach to predictive modeling for determining tool-wear in end-milling operations based on enhanced-group method of data handling (e-GMDH). Using milling input parameters (speed, feed, and depth-of-cut) and response (tool wear), the data for the model is partitioned into training and testing datasets, and the training dataset is used to realize a predictive model that is a function of the input parameters and the coefficients determined. In our approach, we first present a methodology for modeling, and then develop predictive model(s) of the problem being solved in the form of second-order equations based on the input data and coefficients realized. This approach leads to some generalization because it becomes possible to predict not only the test data obtained during experimentation, but other test data outside the experimental results can also be used. Moreover, this approach makes it easy to present the realized solution in a form that can be further optimized for the input parameters using some optimization techniques. The results realized using our e-GMDH method are promising, and the comparative study presented shows that the e-GMDH outperforms polynomial neural network (PNN); moreover, it is more flexible than the conventional GMDH, which tends to produce nonlinear solutions even for simple problems. In the investigation, the extended particle swarm optimization (PSO) technique was applied to obtain the optimal parameters. Consequently, the modeling approach is extremely useful in realizing a computer-aided process-planning system in an advanced manufacturing environment.     

Is there a direct relationship between oral astringency and human salivary protein binding?

For decades, it is believed that astringency is due to the polyphenol-induced complexation of proline-rich salivary proteins in the oral cavity. In order to compare for the first time the human sensory threshold concentrations and the salivary protein binding activity of a series of astringent stimuli, human saliva protein was incubated for 5 min at 37 °C in the presence of astringent food-derived compounds and, after micro-centrifugation, the amount of the target molecules in the supernatant was quantitatively determined by HPLC-UV/Vis. Significant protein binding was observed for (−)-epigallocatechin-3-gallate, (−)-gallocatechin-3-gallate, (+)-gallocatechin, and (−)-catechin-3-gallate, all of which containing at least one galloyl moiety in the molecule and exhibiting rather high sensory thresholds of more than 200 μmol/L. In comparison, (+)-catechin and procyanidin B2, both lacking in any galloyl function, showed only comparatively low binding activity and, most interestingly, quercetin-3-O-α-l-rhamnopyranosyl-(1 → 6)-β-d-glucopyranoside and 3-carboxymethyl-indole-1-N-β-d-glucopyranoside did not show any protein binding at all, although the later N- and O-glycosides exhibited extraordinarily low sensory threshold concentrations of less than 0.001 and 0.0003 μmol/L, respectively. The data give some first evidence that the quantity of the non-bound, “free” astringent stimulus in the saliva liquid might be more closely related to the sensory perception of astringency than the amount complexed or precipitated by proteins. It is therefore questionable as to whether oral perception of astringency is related to the complexation and/or precipitation of salivary proteins.