Influence of the Native Oxide Layer on the Silicon Surface During Initial Stages of Nitridation

 Thin SiO₂ layers were produced by thermal oxidation of Si wafer material. To study the effect of nitridation on the oxide layers, the specimens were nitrided in a furnace at high temperature. Non-destructive ion beam analysis was performed to determine changes in the elemental concentrations and depth profiles of the major components. In particular, N and O concentrations were measured using the non-resonant nuclear reactions ¹⁴N(d, α)¹²C and ¹⁶O(d, p)¹⁷O, respectively. To obtain depth profiles of the as-prepared and nitrided specimens, the samples were measured with RBS and heavy ion elastic recoil detection analysis. The ion beam analyses revealed an increase in thickness of the SiO₂ layers with temperature. The specimens nitrided at 1200 °C were almost free of N. Surface topology investigations with scanning electron microscopy revealed concentric annular artificial patterns at the surfaces. In the centre of the pattern, only silicon was measured. Additionally, a band consisting of Si, O, and N surrounding the pattern was discovered. The findings are in agreement with specimens prepared at higher temperatures. Received June 19, 2000. Revision December 9, 2000.     

Opto-thermal Moisture Content and Moisture Depth Profile Measurements in Organic Materials

Opto-thermal transient emission radiometry(OTTER) is a infrared remote sensing technique, which has been successfully used in in vivo skin moisture content and skin moisture depth profiling measurements. In present paper, we extend this moisture content measurement capability to analyze the moisture content of fruit (tomato. grape, etc. ) skins, and to study the relationship between fruits ripening process and their sur-face moisture and moisture depth profiles.     

Phytochemical Profile of Antibacterial Agents from Red Betel Leaf (Piper crocatum Ruiz and Pav) against Bacteria in Dental Caries

Based on data from The Global Burden of Disease Study in 2016, dental and oral health problems, especially dental caries, are a disease experienced by almost half of the world’s population (3.58 billion people). One of the main causes of dental caries is the pathogenesis of Streptococcus mutans. Prevention can be achieved by controlling S. mutans using an antibacterial agent. The most commonly used antibacterial for the treatment of dental caries is chlorhexidine. However, long-term use of chlorhexidine has been reported to cause resistance and some side effects. Therefore, the discovery of a natural antibacterial agent is an urgent need. A natural antibacterial agent that can be used are herbal medicines derived from medicinal plants. Piper crocatum Ruiz and Pav has the potential to be used as a natural antibacterial agent for treating dental and oral health problems. Several studies reported that the leaves of P. crocatum Ruiz and Pav contain secondary metabolites such as essential oils, flavonoids, alkaloids, terpenoids, tannins, and phenolic compounds that are active against S. mutans. This review summarizes some information about P. crocatum Ruiz and Pav, various isolation methods, bioactivity, S. mutans bacteria that cause dental caries, biofilm formation mechanism, antibacterial properties, and the antibacterial mechanism of secondary metabolites in P. crocatum Ruiz and Pav.     

Quantitative Depth Profiling Using Online-Laser Ablation of Solid Samples in Liquid (LASIL) to Investigate the Oxidation Behavior of Transition Metal Borides

The increased demand for sustainability requires, among others, the development of new materials with enhanced corrosion resistance. Transition metal diborides are exceptional candidates, as they exhibit fascinating mechanical and thermal properties. However, at elevated temperatures and oxidizing atmospheres, their use is limited due to the fact of their inadequate oxidation resistance. Recently, it was found that chromium diboride doped with silicon can overcome this limitation. Further improvement of this protective coating requires detailed knowledge regarding the composition of the forming oxide layer and the change in the composition of the remaining thin film. In this work, an analytical method for the quantitative measurement of depth profiles without using matrix-matched reference materials was developed. Using this approach, based on the recently introduced online-LASIL technique, it was possible to achieve a depth resolution of 240 nm. A further decrease in the ablation rate is possible but demands a more sensitive detection of silicon. Two chromium diboride samples with different Si contents suffering an oxidation treatment were used to demonstrate the capabilities of this technique. The concentration profiles resembled the pathway of the formed oxidation layers as monitored with transmission electron microscopy. The stoichiometry of the oxidation layers differed strongly between the samples, suggesting different processes were taking place. The validity of the LASIL results was cross-checked with several other analytical techniques.     

Identification of Anti-Proliferative Compounds from Genista monspessulana Seeds through Covariate-Based Integration of Chemical Fingerprints and Bioactivity Datasets

Genista monspessulana (L.) L.A.S. Johnson (Fabaceae) is a Mediterranean plant introduced to South America and other regions for ornamental purposes. However, it is considered an invasive shrub due to its reproductive vigor in many areas. Unlike other Genista plants, G. monspessulana has few studies disclosing its biologically active components, particularly cytotoxic agents against cancer cells. Thus, as part of our research on anti-proliferative bioactives, a set of ethanolic seed extracts from ten accessions of G. monspessulana, collected in the Bogotá plateau, were evaluated against four cell lines: PC-3 (prostate adenocarcinoma), SiHa (cervical carcinoma), A549 (lung carcinoma), and L929 (normal mouse fibroblasts). Extracts were also analyzed through liquid chromatography coupled with mass spectrometry (LC/MS) to record chemical fingerprints and determine the composition and metabolite variability between accessions. Using multiple covariate statistics, chemical and bioactivity datasets were integrated to recognize patterns and identify bioactive compounds among studied extracts. G. monspessulana seed-derived extracts exhibited dose-dependent antiproliferative activity on PC-3 and SiHa cell lines (>500 µg/mL < IC₅₀ < 26.3 µg/mL). Seven compounds (1–7) were inferred as the compounds most likely responsible for the observed anti-proliferative activity and subsequently isolated and identified by spectroscopic techniques. A tricyclic quinolizidine (1) and a pyranoisoflavone (2) were found to be the most active compounds, exhibiting selectivity against PC-3 cell lines (IC₅₀ < 18.6 µM). These compounds were used as precursors to obtain a quinolizidine-pyranoisoflavone adduct via Betti reaction, improving the activity against PC-3 and comparable to curcumin as the positive control. Results indicated that this composition–activity associative approach is advantageous to finding those bioactive principles efficiently within active extracts. This correlative association can be employed in further studies focused on the targeted isolation of anti-proliferative compounds from Genista plants and accessions.     

Metabolite profiling of Huaiyang Medicago polymorpha with different mowing crops

Abstract

The main purpose of our study was to identify and compare secondary metabolites due to different mowing in order to make better use of Huaiyang Medicago polymorpha. The metabolite profiling of Huaiyang Medicago polymorpha with two mowing crops was performed using a rapid resolution liquid chromatography system with quadrupole time-of-flight mass spectrometer (RRLC-QTOFMS) followed by multivariate statistical analyses. Principal Component Analysis (PCA) results showed a clear distinction between two mowing crops. The major metabolites that contributed to mowing discrimination were identified. The results also showed that the content of major active compounds in Medicago polymorpha from the second crop are higher significantly than the first crop. This study suggests that the strategy is a reliable and simple method for the rapid discrimination of subtle variations due to different mowing crops.     

Improvements in lipid suppression for 1H NMR-based metabolomics: Applications to solution-state and HR-MAS NMR in natural and in vivo samples

Proton nuclear magnetic resonance (NMR) spectra of intact biological samples often show strong contributions from lipids, which overlap with signals of interest from small metabolites. Pioneering work by Diserens et al. demonstrated that the relative differences in diffusivity and relaxation of lipids versus small metabolites could be exploited to suppress lipid signals, in high-resolution magic angle spinning (HR-MAS) NMR spectroscopy. In solution-state NMR, suspended samples can exhibit very broad water signals, which are challenging to suppress. Here, improved water suppression is incorporated into the sequence, and the Carr-Purcell-Meiboom-Gill sequence (CPMG) train is replaced with a low-power adiabatic spinlock that reduces heating and spectral artefacts seen with longer CPMG filters. The result is a robust sequence that works well in both HR-MAS as well as static solution-state samples. Applications are also extended to include in vivo organisms. For solution-state NMR, samples containing significant amount of fats such as milk and hemp hearts seeds are used to demonstrate the technique. For HR-MAS, living earthworms (Eisenia fetida) and freshwater shrimp (Hyalella azteca) are used for in vivo applications. Lipid suppression techniques are essential for non-invasive NMR-based analysis of biological samples with a high-lipid content and adds to the suite of experiments advantageous for in vivo environmental metabolomics.     

Accelerating the development of phase-change random access memory with in-fab plasma profiling time-of-flight mass spectrometry

We demonstrate the potential of using plasma profiling time-of-flight mass spectrometry (PP-TOFMS) to accelerate process developments for phase-change random access memory (PCRAM) applications, which require advanced materials with composition-driven properties. We assess the performances of PP-TOFMS for the chemical depth-profiling of GeSbTe phase change materials, first after deposition steps to investigate the top surface layer and the incorporation of silicon into the amorphous matrix, then after the thermal annealing step to refine in situ capping strategies, and finally in close loop with etching process steps. Comparison of reference-free semiquantitative PP-TOFMS analysis based on ion beam ratio with Rutherford backscattering spectrometry shows remarkable agreement (~10% relative). PP-TOFMS proves to be a fast screening tool, which allows process monitoring and selection of samples that indeed need more complex analysis.     

Rational Profiling of Equal-Stress-Reinforced Plates Subjected to Elastoplastic Transverse Bending

The problem of rational profiling of equal-stress-reinforced Kirchhoff plates subjected to purely elastic and elastoplastic transverse bending is formulated. A qualitative analysis of the systems of resolving equations is carried out. It is found that the problem can have two possible solutions, which can be controlled. By particular calculations, it is shown that, through rational profiling of the bent plates, the consumption of phase materials in them can be reduced greatly compared with that in traditional ones, or the load-carrying capacity of the plates can be raised significantly at a fixed consumption of phase materials.     

Advancements in biocatalysis: From computational to metabolic engineering

Through several waves of technological research and un-matched innovation strategies, bio-catalysis has been widely used at the industrial level. Because of the value of enzymes, methods for producing value-added compounds and industrially-relevant fine chemicals through biological methods have been developed. A broad spectrum of numerous biochemical pathways is catalyzed by enzymes, including enzymes that have not been identified. However, low catalytic efficacy, low stability, inhibition by non-cognate substrates, and intolerance to the harsh reaction conditions required for some chemical processes are considered as major limitations in applied bio-catalysis. Thus, the development of green catalysts with multi-catalytic features along with higher efficacy and induced stability are important for bio-catalysis. Implementation of computational science with metabolic engineering, synthetic biology, and machine learning routes offers novel alternatives for engineering novel catalysts. Here, we describe the role of synthetic biology and metabolic engineering in catalysis. Machine learning algorithms for catalysis and the choice of an algorithm for predicting protein-ligand interactions are discussed. The importance of molecular docking in predicting binding and catalytic functions is reviewed. Finally, we describe future challenges and perspectives.