Spatial Imaging and Control of Dark Excitons in Monolayer Transition Metal Dichalcogenides

Dark excitons play a vital role in exciton condensation and optical properties of monolayer transition metal dichalcogenides (MTMDs). Previous literature mainly focuses on the detection of the energy of the dark exciton, while spatial detection and control are equally important but are less studied. Here we report that for MTMD embedded in a semiconductor microcavity and under a uniform in-plane magnetic field the spatial distribution of the dark exciton can be probed by measuring that of the cavity photon for small exciton–exciton interaction energy. Further, we propose to realize the anomalous exciton Hall effect by exploiting spatially inhomogeneous coupling of the bright and dark excitons under a Gaussian excitation beam. This effect occurs regardless of the exciton–exciton interaction, which will strengthen the diffusion of excitons in the excitation region. These results provide an improved understanding of the excitons in MTMDs, thereby facilitating their potential practical applications

Total variance explained in the three sampling seasons.

<p>Total variance explained in the three sampling seasons.</p

Correlations between selected water quality parameters and environmental variables using Pearson analysis.

<p>*indicates significant at <i>p</i><0.05;</p><p>**indicates significant at <i>p</i><0.01.</p

Spatial regression models established in the JRW.

<p>Note: Factor1, 2, 3, and 4 corresponds to the four components identified and presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091528#pone-0091528-g006" target="_blank">Fig. 6</a>.</p><p><i>a</i> denotes the results of spatial error models, <i>b</i> denotes the results of spatial lag models.</p><p>WY: weighted mean of the dependent variable for adjacent sub-basins.</p><p>*indicates significant at <i>p</i><0.05.</p><p>**indicates significant at <i>p</i><0.01.</p

Sampling sites in the watershed studied.

<p>Sampling sites in the watershed studied.</p

Total variance explained for environmental factors.

<p>Total variance explained for environmental factors.</p

Comparison of R², AIC and Moran’s I values between OLS models and spatial regressions.

<p>Comparison of R², AIC and Moran’s I values between OLS models and spatial regressions.</p

Moran’s I values for water quality indicators among the three sampling seasons.

<p>**indicates significant at <i>p</i><0.01;</p><p>*indicates significant at <i>p</i><0.05.</p

The four potential pollution sources identified to explain spatiotemporal variations in water quality for 20 headwater watersheds in the JRW.

<p>(PC1, PC2, PC3, and PC4 represents landscape patterns, urbanization and socioeconomic development, agricultural activity, and natural control, respectively).</p

K independent samples of water quality among the different sampling seasons.

<p>Sample No.  = 60; Asymp. Sig. <0.05 indicates significant variation.</p