MoS2 Based Photodetectors: A Review.

Photodetectors based on transition metal dichalcogenides (TMDs) have been widely reported in the literature and molybdenum disulfide (MoS2) has been the most extensively explored for photodetection applications. The properties of MoS2, such as direct band gap transition in low dimensional structures, strong light-matter interaction and good carrier mobility, combined with the possibility of fabricating thin MoS2 films, have attracted interest for this material in the field of optoelectronics. In this work, MoS2-based photodetectors are reviewed in terms of their main performance metrics, namely responsivity, detectivity, response time and dark current. Although neat MoS2-based detectors already show remarkable characteristics in the visible spectral range, MoS2 can be advantageously coupled with other materials to further improve the detector performance Nanoparticles (NPs) and quantum dots (QDs) have been exploited in combination with MoS2 to boost the response of the devices in the near ultraviolet (NUV) and infrared (IR) spectral range. Moreover, heterostructures with different materials (e.g., other TMDs, Graphene) can speed up the response of the photodetectors through the creation of built-in electric fields and the faster transport of charge carriers. Finally, in order to enhance the stability of the devices, perovskites have been exploited both as passivation layers and as electron reservoirs.

Modelling the risk of radiation induced alopecia in brain tumor patients treated with scanned proton beams.

PURPOSE: To develop normal tissue complication probability (NTCP) models for radiation-induced alopecia (RIA) in brain tumor patients treated with proton therapy (PT). METHODS AND MATERIALS: We analyzed 116 brain tumor adult patients undergoing scanning beam PT (median dose 54 GyRBE; range 36-72) for CTCAE v.4 grade 2 (G2) acute (≤90 days), late (>90 days) and permanent (>12 months) RIA. The relative dose-surface histogram (DSH) of the scalp was extracted and used for Lyman-Kutcher-Burman (LKB) modelling. Moreover, DSH metrics (Sx: the surface receiving ≥ X Gy, D2%: near maximum dose, Dmean: mean dose) and non-dosimetric variables were included in a multivariable logistic regression NTCP model. Model performances were evaluated by the cross-validated area under the receiver operator curve (ROC-AUC). RESULTS: Acute, late and permanent G2-RIA was observed in 52%, 35% and 19% of the patients, respectively. The LKB models showed a weak dose-surface effect (0.09 ≤ n ≤ 0.19) with relative steepness 0.29 ≤ m ≤ 0.56, and increasing tolerance dose values when moving from acute and late (22 and 24 GyRBE) to permanent RIA (44 GyRBE). Multivariable modelling selected S21Gy for acute and S25Gy, for late G2-RIA as the most predictive DSH factors. Younger age was selected as risk factor for acute G2-RIA while surgery as risk factor for late G2-RIA. D2% was the only variable selected for permanent G2-RIA. Both LKB and logistic models exhibited high predictive performances (ROC-AUCs range 0.86-0.90). CONCLUSION: We derived NTCP models to predict G2-RIA after PT, providing a comprehensive modelling framework for acute, late and permanent occurrences that, once externally validated, could be exploited for individualized scalp sparing treatment planning strategies in brain tumor patients.