Multiscale Investigation of the Structural, Electrical and Photoluminescence Properties of MoS2 Obtained by MoO3 Sulfurization

In this paper, we report a multiscale investigation of the compositional, morphological, structural, electrical, and optical emission properties of 2H-MoS2 obtained by sulfurization at 800 °C of very thin MoO3 films (with thickness ranging from ~2.8 nm to ~4.2 nm) on a SiO2/Si substrate. XPS analyses confirmed that the sulfurization was very effective in the reduction of the oxide to MoS2, with only a small percentage of residual MoO3 present in the final film. High-resolution TEM/STEM analyses revealed the formation of few (i.e., 2–3 layers) of MoS2 nearly aligned with the SiO2 surface in the case of the thinnest (~2.8 nm) MoO3 film, whereas multilayers of MoS2 partially standing up with respect to the substrate were observed for the ~4.2 nm one. Such different configurations indicate the prevalence of different mechanisms (i.e., vapour-solid surface reaction or S diffusion within the film) as a function of the thickness. The uniform thickness distribution of the few-layer and multilayer MoS2 was confirmed by Raman mapping. Furthermore, the correlative plot of the characteristic A1g-E2g Raman modes revealed a compressive strain (ε ≈ −0.78 ± 0.18%) and the coexistence of n- and p-type doped areas in the few-layer MoS2 on SiO2, where the p-type doping is probably due to the presence of residual MoO3. Nanoscale resolution current mapping by C-AFM showed local inhomogeneities in the conductivity of the few-layer MoS2, which are well correlated to the lateral changes in the strain detected by Raman. Finally, characteristic spectroscopic signatures of the defects/disorder in MoS2 films produced by sulfurization were identified by a comparative analysis of Raman and photoluminescence (PL) spectra with CVD grown MoS2 flakes.

Raman Spectroscopy Enables Non-Invasive Identification of Mycotoxins p. Fusarium of Winter Wheat Seeds

Identification of specific mycotoxins p. Fusarium contained in infected winter wheat seeds can be achieved by visually recognizing their distinctive phenotypic species. The visual identification (ID) of species is subjective and usually requires significant taxonomic knowledge. Methods for the determination of various types of mycotoxins of the p. Fusarium are laborious and require the use of chemical invasive research methods. In this research, we investigate the possibility of using Raman spectroscopy (RS) as a tag-free, non-invasive and non-destructive analytical method for the rapid and accurate identification of p. Fusarium. Varieties of the r. Fusarium can produce mycotoxins that directly affect the DNA, RNA and chemical structure of infected seeds. Analysis of spectra by RS methods and chemometric analysis allows the identification of healthy, infected and contaminated seeds of winter wheat with varieties of mycotoxins p. Fusarium. Raman seed analysis provides accurate identification of p. Fusarium in 96% of samples. In addition, we present data on the identification of carbohydrates, proteins, fiber and other nutrients contaminated with p. Fusarium seeds obtained using spectroscopic signatures. These results demonstrate that RS enables rapid, accurate and non-invasive screening of seed phytosanitary status.

Integrative chemo-immune-radiological treatment of HER2 positive breast cancer combined with a review of potential microRNAs involved and analysis of experimental results from sub-THz vibrational spectroscopy

In this paper we present the results of a Breast Cancer study by integrative analysis of a NIH approved treatment for HER2 positive breast cancer. This study is combined with analysis of Micro-RNA involvement from application of sub-THz spectroscopy for visualization of molecules circulating in blood by measuring saliva. The combination of Taxol-Generic Name-Paclitaxel (PT-J9267) and Trastuzumab-ANNS 0/0 and KadcylaTM (Genetic Name Ado-Trastuzumab Emtansine) were used in 3-stages of combined chemotherapeutic and immune-treatments followed by Radiation treatment. The goal of using PT was to stop spread of the disease to other organs outside of the breast and under arm lymph nodes, as well as to shrink the size of the tumor to facilitate surgery and radiology in continuation of the treatment. Trastuzumab (TZ) was added to PT in the 2nd step to prevent the development of chemoresistance. Intravenous infusion of Kadcyla was used mainly to prevent metastasis. Integrative analysis of microRNA participation was conducted based on literature review and sub-Terahertz vibrational spectroscopy measurements of absorption spectra from samples taken weekly before and after each treatment, using Vibratess’ spectrometer. The results from sub-THz spectroscopy in this work demonstrate dramatical modification of spectroscopic signatures from patient samples following disease development and the initial steps in the course of treatment. These changes reflect the deep global regulation (reduction) of the initially participating microRNAs amounts and changes in the microRNAs contributing to the spectra.

Unsupervised Machine Learning for the Identification of Preflare Spectroscopic Signatures

The study of the preflare environment is of great importance to understanding what drives solar flares. k-means clustering, an unsupervised machine-learning technique, has the ability to cluster large data set in a way that would be impractical or impossible for a human to do. In this paper we present a study using k-means clustering to identify possible preflare signatures in spectroscopic observations of the Mg ii h and k spectral lines made by NASA's Interface Region Imaging Spectrometer. Our analysis finds that spectral profiles showing single-peak Mg ii h and k and single-peaked emission in the Mg ii UV triplet lines are associated with preflare activity up to 40 minutes prior to flaring. Subsequent inversions of these spectral profiles reveal increased temperature and electron density in the chromosphere, which suggest that significant heating events in the chromosphere may be associated with precursor signals to flares.

Architecture for microcomb-based GHz-mid-infrared dual-comb spectroscopy

Dual-comb spectroscopy (DCS) offers high sensitivity and wide spectral coverage without the need for bulky spectrometers or mechanical moving parts. And DCS in the mid-infrared (mid-IR) is of keen interest because of inherently strong molecular spectroscopic signatures in these bands. We report GHz-resolution mid-IR DCS of methane and ethane that is derived from counter-propagating (CP) soliton microcombs in combination with interleaved difference frequency generation. Because all four combs required to generate the two mid-IR combs rely upon stability derived from a single high-Q microcavity, the system architecture is both simplified and does not require external frequency locking. Methane and ethane spectra are measured over intervals as short as 0.5 ms, a time scale that can be further reduced using a different CP soliton arrangement. Also, tuning of spectral resolution on demand is demonstrated. Although at an early phase of development, the results are a step towards mid-IR gas sensors with chip-based architectures for chemical threat detection, breath analysis, combustion studies, and outdoor observation of trace gases.

Symmetry, Combinatorics, Artificial Intelligence, Music and Spectroscopy

Symmetry forms the foundation of combinatorial theories and algorithms of enumeration such as Möbius inversion, Euler totient functions, and the celebrated Pólya’s theory of enumeration under the symmetric group action. As machine learning and artificial intelligence techniques play increasingly important roles in the machine perception of music to image processing that are central to many disciplines, combinatorics, graph theory, and symmetry act as powerful bridges to the developments of algorithms for such varied applications. In this review, we bring together the confluence of music theory and spectroscopy as two primary disciplines to outline several interconnections of combinatorial and symmetry techniques in the development of algorithms for machine generation of musical patterns of the east and west and a variety of spectroscopic signatures of molecules. Combinatorial techniques in conjunction with group theory can be harnessed to generate the musical scales, intensity patterns in ESR spectra, multiple quantum NMR spectra, nuclear spin statistics of both fermions and bosons, colorings of hyperplanes of hypercubes, enumeration of chiral isomers, and vibrational modes of complex systems including supergiant fullerenes, as exemplified by our work on the golden fullerene C150,000. Combinatorial techniques are shown to yield algorithms for the enumeration and construction of musical chords and scales called ragas in music theory, as we exemplify by the machine construction of ragas and machine perception of musical patterns. We also outline the applications of Hadamard matrices and magic squares in the development of algorithms for the generation of balanced-pitch chords. Machine perception of musical, spectroscopic, and symmetry patterns are considered.