Electronic structure and optical signatures of semiconducting transition metal dichalcogenide nanosheets

CONSPECTUS: Two-dimensional (2D) crystals derived from transition metal dichalcogenides (TMDs) are intriguing materials that offer a unique platform to study fundamental physical phenomena as well as to explore development of novel devices. Semiconducting group 6 TMDs such as MoS2 and WSe2 are known for their large optical absorption coefficient and their potential for high efficiency photovoltaics and photodetectors. Monolayer sheets of these compounds are flexible, stretchable, and soft semiconductors with a direct band gap in contrast to their well-known bulk crystals that are rigid and hard indirect gap semiconductors. Recent intense research has been motivated by the distinct electrical, optical, and mechanical properties of these TMD crystals in the ultimate thickness regime. As a semiconductor with a band gap in the visible to near-IR frequencies, these 2D MX2 materials (M = Mo, W; X = S, Se) exhibit distinct excitonic absorption and emission features. In this Account, we discuss how optical spectroscopy of these materials allows investigation of their electronic properties and the relaxation dynamics of excitons. We first discuss the basic electronic structure of 2D TMDs highlighting the key features of the dispersion relation. With the help of theoretical calculations, we further discuss how photoluminescence energy of direct and indirect excitons provide a guide to understanding the evolution of the electronic structure as a function of the number of layers. We also highlight the behavior of the two competing conduction valleys and their role in the optical processes. Intercalation of group 6 TMDs by alkali metals results in the structural phase transformation with corresponding semiconductor-to-metal transition. Monolayer TMDs obtained by intercalation-assisted exfoliation retains the metastable metallic phase. Mild annealing, however, destabilizes the metastable phase and gradually restores the original semiconducting phase. Interestingly, the semiconducting 2H phase, metallic 1T phase, and a charge-density-wave-like 1T' phase can coexist within a single crystalline monolayer sheet. We further discuss the electronic properties of the restacked films of chemically exfoliated MoS2. Finally, we focus on the strong optical absorption and related exciton relaxation in monolayer and bilayer MX2. Monolayer MX2 absorbs as much as 30% of incident photons in the blue region of the visible light despite being atomically thin. This giant absorption is attributed to nesting of the conduction and valence bands, which leads to diversion of optical conductivity. We describe how the relaxation pathway of excitons depends strongly on the excitation energy. Excitation at the band nesting region is of unique significance because it leads to relaxation of electrons and holes with opposite momentum and spontaneous formation of indirect excitons.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Comedy shows: humour, crisis and the resilience of radio

Being a part of many radio stations' progra

Evaluating balance, stability and gait symmetry of stroke patients using kinematic and dynamic gait lab data

Dissertação de mestrado integrado em Engenharia Biomédica