Synthesis and Structure of Dawson Polyoxometalate-Based, Multifunctional, Inorganic–Organic Hybrid Compounds: Organogermyl Complexes with One Terminal Functional Group and Organosilyl Analogues with Two Terminal Functional Groups

2011 ◽  
Vol 50 (19) ◽  
pp. 9606-9619 ◽  
Author(s):  
Kenji Nomiya ◽  
Yoshihiro Togashi ◽  
Yuhki Kasahara ◽  
Shotaro Aoki ◽  
Hideaki Seki ◽  
...  
Keyword(s):  
Functional Groups ◽  
Functional Group ◽  
Organic Hybrid ◽  
Hybrid Compounds ◽  
Terminal Functional Group

scholarly journals Resilience of Epiphytic Lichens to Combined Effects of Increasing Nitrogen and Solar Radiation

2021 ◽  
Vol 7 (5) ◽  
pp. 333
Author(s):  
Lourdes Morillas ◽  
Javier Roales ◽  
Cristina Cruz ◽  
Silvana Munzi
Keyword(s):  
Global Change ◽  
Solar Radiation ◽  
Functional Groups ◽  
Physiological Response ◽  
Functional Group ◽  
Environmental Drivers ◽  
Combined Effects ◽  
Environmental Stressor ◽  
Comprehensive Understanding ◽  
Direct Sunlight

Lichens are classified into different functional groups depending on their ecological and physiological response to a given environmental stressor. However, knowledge on lichen response to the synergistic effect of multiple environmental factors is extremely scarce, although vital to get a comprehensive understanding of the effects of global change. We exposed six lichen species belonging to different functional groups to the combined effects of two nitrogen (N) doses and direct sunlight involving both high temperatures and ultraviolet (UV) radiation for 58 days. Irrespective of their functional group, all species showed a homogenous response to N with cumulative, detrimental effects and an inability to recover following sunlight, UV exposure. Moreover, solar radiation made a tolerant species more prone to N pollution’s effects. Our results draw attention to the combined effects of global change and other environmental drivers on canopy defoliation and tree death, with consequences for the protection of ecosystems.

Inorganic–organic hybrid compounds based on molybdenum oxide chains and tetrazolate-bridged polymeric silver cations

2011 ◽  
Vol 40 (9) ◽  
pp. 1866-1872 ◽  
Author(s):  
Ming-Xing Yang ◽  
Li-Juan Chen ◽  
Shen Lin ◽  
Xiao-Hua Chen ◽  
Hua Huang
Keyword(s):  
Molybdenum Oxide ◽  
Organic Hybrid ◽  
Hybrid Compounds ◽  
Silver Cations

scholarly journals Food Additives Frequency in processed baby products in Cochabamba, Bolivia

2021 ◽  
Vol 17 (Especial) ◽  
pp. 19-27
Author(s):  
Nelcy Aguilar Sasari ◽  
Milenka Alessandra Fernández Ledezma ◽  
Tania Araujo-Burgos
Keyword(s):  
Shelf Life ◽  
Functional Groups ◽  
Frequency Analysis ◽  
Metropolitan Area ◽  
Sodium Nitrate ◽  
Functional Group ◽  
Food Additives ◽  
Processed Food ◽  
Food Labels ◽  
Organoleptic Properties

Additives are necessary substances to improve the nutritional and organoleptic properties and the shelf life of processed food. In addition, their use is regulated, and it must be declared on the food labels. Thus, the objective of this research was to determine the frequency of food additives in processed baby products in Cochabamba metropolitan area (Bolivia). Data were collected by label reading and a frequency analysis was performed by additives and by functional group. 26 baby products were found where 41 food additives were identified with an occurrence of 256 times, and a mean of 9,8 additives per product. Moreover, the functional groups most widely used are antioxidants and colorants. Finally, the most frequent additives are mostly harmless, except for sodium nitrate and copper sulfate.

scholarly journals Phytochemical Screening, Spectrum Profile of Functional Groups, and Effervescent Formulation of Kepok Banana Peels Stem Extract

2021 ◽  
Vol 4 (2) ◽  
pp. 66-72
Author(s):  
Robby Candra Purnama ◽  
Annisa Primadiamanti
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Secondary Metabolites ◽  
Functional Groups ◽  
Functional Group ◽  
Screening Method ◽  
Phytochemical Screening ◽  
Stem Extract ◽  
Group Profile ◽  
Banana Stem

Kepok banana plants contain secondary metabolites such as tannins and flavonoids. Tannins and flavonoids have various properties for human health. Research has been carried out to identify secondary metabolite compounds (tannins, flavonoids, and saponins) by using the phytochemical screening method to see the functional group profile contained in the extract of kepok banana stem waste. Kepok banana stem waste was extracted in 96% ethanol, then evaporated and screened phytochemically. This extract was used to prepare effervescently. Screening results showed that tannin and flavonoids were identified by the appearance of the following color black-green and dark red, respectively. Meanwhile, saponins were negative because the foam formed had a height of 0.3 cm and did not meet the saponins' positive requirements (1-3 cm high foam and stable for 5 minutes). Identification of functional groups in the extract of kepok banana stem waste using Fourier-transform Infrared Spectroscopy (FTIR) showed that C-C stretching in the area 2927.24 cm-1, O-H stretching in the 3423.87 cm-1 area, C=O stretching in the 1648.87 cm-1 area. Also appeared bending CH2 in the region of 1421.45 cm-1, and C-C in the area of 1149.98 cm-1. The characteristics of three different formulas (A, B, and C) of effervescent have been investigated: the moisture content of 2.51%; 2.55%, and 2.52%, respectively. Then, flow rate of 8.81 g/s; 8.83 g/s; and 8.82 g/s, compressibility of 14.5%; 14.4%; and 14.5%, and a pH of 5.97; 5.98; and 5.97 respectively. All parameters are eligible.

scholarly journals Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models

2021 ◽  
Author(s):  
Abigail Enders ◽  
Nicole North ◽  
Chase Fensore ◽  
Juan Velez-Alvarez ◽  
Heather Allen
Keyword(s):  
Machine Learning ◽  
Gas Phase ◽  
Functional Groups ◽  
Functional Group ◽  
Spectroscopic Method ◽  
Group Identification ◽  
Spectroscopic Technique ◽  
Ftir Spectra ◽  
Spectral Interpretation ◽  
Time Required

<p>Fourier Transform Infrared Spectroscopy (FTIR) is a ubiquitous spectroscopic technique. Spectral interpretation is a time-consuming process, but it yields important information about functional groups present in compounds and in complex substances. We develop a generalizable model via a machine learning (ML) algorithm using Convolutional Neural Networks (CNNs) to identify the presence of functional groups in gas phase FTIR spectra. The ML models will reduce the amount of time required to analyze functional groups and facilitate interpretation of FTIR spectra. Through web scraping, we acquire intensity-frequency data from 8728 gas phase organic molecules within the NIST spectral database and transform the data into images. We successfully train models for 15 of the most common organic functional groups, which we then determine via identification from previously untrained spectra. These models serve to expand the application of FTIR measurements for facile analysis of organic samples. Our approach was done such that we have broad functional group models that inference in tandem to provide full interpretation of a spectrum. We present the first implementation of ML using image-based CNNs for predicting functional groups from a spectroscopic method.</p>

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