Adsorption ability of cell wall (CW) components in roots of Tea Plant (Camellia sinensisL.) to Pband FTIR spectra of their functional groups

In this research work, MFe2O4/CNS was prepared using the hydrothermal–microwave method. The influence of cations (M) toward functional groups of composites and their performance in pesticide degradation were studied. Rice husk was pyrolyzed hydrothermally (200 °C, 6 h) and by microwave (800 W, 40 min). Each product was mixed with MCl2 (Zn, Ni, Mn), FeCl3, KOH, and water, and calcined (600 °C, 15 min) to obtain a composite. Characterization by XRD confirmed the MFe2O4/CNS structure. The FTIR spectra of the composites showed different band sharpness related to C-O and M-O. A mixture of dried paddy farm soil, composite, BPMC (buthylphenylmethyl carbamate) pesticide solution (0.25%), and H2O2 solution (0.15%) was kept under dark conditions for 48 h. The solution above the soil was filtered and measured with a UV-Vis spectrophotometer at 217 nm. Applications without the composite and composite–H2O2 were also conducted. The results reveal that dark BPMC degradation with the composite was 7.5 times larger than that without the composite, and 2.9 times larger than that without the composite–H2O2. There were no significantly different FTIR spectra of the soil, soil–BPMC, soil–BPMC-H2O2, and soil–BPMC-H2O2 composite and no significantly different X-ray diffractograms between the soil after drying and soil after application for pesticide degradation using the composite.

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

10.26434/chemrxiv.14188679 ◽

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

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.

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Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: method development for probabilistic modeling of organic carbon and organic matter concentrations

Atmospheric Measurement Techniques ◽

10.5194/amt-13-1517-2020 ◽

2020 ◽

Vol 13 (3) ◽

pp. 1517-1538

Author(s):

Charlotte Bürki ◽

Matteo Reggente ◽

Ann M. Dillner ◽

Jenny L. Hand ◽

Stephanie L. Shaw ◽

...

Keyword(s):

Cluster Analysis ◽

Organic Matter ◽

Organic Carbon ◽

Functional Groups ◽

Method Development ◽

Estimation Method ◽

Chemical Species ◽

Monitoring Network ◽

Ftir Spectra ◽

Absorption Bands

Abstract. The Fourier transform infrared (FTIR) spectra of fine particulate matter (PM2.5) contain many important absorption bands relevant for characterizing organic matter (OM) and obtaining organic matter to organic carbon (OM∕OC) ratios. However, extracting this information quantitatively – accounting for overlapping absorption bands and relating absorption to molar abundance – and furthermore relating abundances of functional groups to that of carbon atoms poses several challenges. In this work, we define a set of parameters that model these relationships and apply a probabilistic framework to identify values consistent with collocated field measurements of thermal–optical reflectance organic carbon (TOR OC). Parameter values are characterized for various sample types identified by cluster analysis of sample FTIR spectra, which are available for 17 sites in the Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network (7 sites in 2011 and 10 additional sites in 2013). The cluster analysis appears to separate samples according to predominant influence by dust, residential wood burning, wildfire, urban sources, and biogenic aerosols. Functional groups calibrations of aliphatic CH, alcohol COH, carboxylic acid COOH, carboxylate COO, and amine NH2 combined together reproduce TOR OC concentrations with reasonable agreement (r=0.96 for 2474 samples) and provide OM∕OC values generally consistent with our current best estimate of ambient OC. The mean OM∕OC ratios corresponding to sample types determined from cluster analysis range between 1.4 and 2.0, though ratios for individual samples exhibit a larger range. Trends in OM∕OC for sites aggregated by region or year are compared with another regression approach for estimating OM∕OC ratios from a mass closure equation of the major chemical species contributing to PM fine mass. Differences in OM∕OC estimates are observed according to estimation method and are explained through the sample types determined from spectral profiles of the PM.

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FTIR spectral properties affected by OM-cation interactions

10.5194/egusphere-egu2020-18375 ◽

2020 ◽

Author(s):

Ruth Ellerbrock ◽

Horst H. Gerke

Keyword(s):

Functional Groups ◽

Bonding Strength ◽

Ftir Spectra ◽

Correct Interpretation ◽

Interaction Solutions ◽

Chia Seed ◽

Freeze Dried ◽

Similar Range ◽

Wavenumber Region ◽

Seed Mucilage

Soil organic matter (OM) interacts with cations like Ca by using C=O and OH functional groups. Such interactions are known to protect soil OM against decomposition. This process affects the bonding strength of functional groups. Changes in bonding strength are assumed to shift the wavenumber region of OH and C=O absorption band maxima in Fourier transform infrared (FTIR) spectra. The aim is to analyze the extent of such shifts to determine presence and strength of OM&#8211;cation interaction. Solutions of PGA and Chia seed mucilage were mixed at different ratios with CaCl2 solution. The mixtures were freeze dried. FTIR spectra of PGA&#8211;Ca, and mucilage-Ca mixtures indicate that the OH band is affected by the presence of Ca. However, the C=O band maximum and the CH/C=O ratio were not affected. For the PGA&#8211;Ca and mucilage-Ca mixtures the shift in OH band maxima relative to PGA and mucilage, respectively, increases with Ca content. Such shifts in OH band maxima are in a similar range as the ones observed for the outer compared to inner regions of an intact chia seed mucilage droplet. The results suggest that it is necessary to know the relation between OM-cation interactions and band shifts for the correct interpretation of the FTIR spectra of soil and rhizosphere samples.

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Surface modification of SiO2 nanoparticles and its impact on the properties of PES-based hollow fiber membrane

RSC Advances ◽

10.1039/c5ra07527k ◽

2015 ◽

Vol 5 (72) ◽

pp. 58644-58654 ◽

Cited By ~ 21

Author(s):

Mimi Suliza Muhamad ◽

Mohd Razman Salim ◽

Woei-Jye Lau

Keyword(s):

Surface Modification ◽

Functional Groups ◽

Hollow Fiber ◽

Hollow Fiber Membrane ◽

Sio2 Nanoparticles ◽

Ftir Spectra ◽

Fiber Membrane ◽

Surface Modified

The FTIR spectra for SiO2-SDS nanoparticles clearly show the detection of SDS functional groups in surface-modified SiO2 and confirm the successful modification of the nanoparticles surface.

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Alteration of Chemical Structure of the Active Vegetal Coals

Revista de Chimie ◽

10.37358/rc.08.2.1725 ◽

2008 ◽

Vol 59 (2) ◽

pp. 159-164

Author(s):

Raisa Nastas ◽

Vasile Rusu ◽

Maria Giurginca ◽

Aurelia Meghea ◽

Tudor Lupascu

Keyword(s):

Functional Groups ◽

Activated Carbons ◽

Raw Materials ◽

Chemical Activation ◽

Ftir Spectra ◽

Active Carbons ◽

Grape Seeds ◽

Carboxylic Groups ◽

Acidic Sites ◽

Sulfurous Anhydride

The peculiarities of surface chemistry, functional groups and acid-basic properties of activated carbons obtained from vegetal raw materials by different methods of activation have been emphasized. Active carbons obtained from peach and plum stones by physical-chemical activation (with steam, aqueous solutions of sulfurous anhydride or ammonia) possess predominantly basic functional groups on the surface, although acidic sites in minor quantities are also accumulated. FTIR spectra suggest the presence on the surface of these carbons of alcoholic and phenolic groups, quinones and hydroxy-ketones. Active carbons obtained from plum stones, nut shells and grape seeds by chemical activation with phosphoric acid possess predominantly acidic functional groups on the surface, out of which carboxylic groups are prevailing by 2-3 times the content of phenolic structures. FTIR spectra suggest the presence on the surface of these carbons of a series of organic structures including carboxylic acids, ketones, aldehydes, quinones, lactones and esters, also alcohols and phenols. UV-VIS-NIR spectra also indicate the presence of alcohols and phenols on the surface of these carbons.

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Adsorption of rhodamine B on Rhizopus oryzae: Role of functional groups and cell wall components

Colloids and Surfaces B Biointerfaces ◽

10.1016/j.colsurfb.2008.02.020 ◽

2008 ◽

Vol 65 (1) ◽

pp. 30-34 ◽

Cited By ~ 56

Author(s):

Sujoy K. Das ◽

Piyasa Ghosh ◽

Indrajit Ghosh ◽

Arun K. Guha

Keyword(s):

Cell Wall ◽

Functional Groups ◽

Rhodamine B ◽

Rhizopus Oryzae ◽

Cell Wall Components ◽

Wall Components

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The relationship between fluoride accumulation in tea plant and changes in leaf cell wall structure and composition under different fluoride conditions

Environmental Pollution ◽

10.1016/j.envpol.2020.116283 ◽

2021 ◽

Vol 270 ◽

pp. 116283

Author(s):

Jinlei Luo ◽

Dejiang Ni ◽

Chunlei Li ◽

Yaru Du ◽

Yuqiong Chen

Keyword(s):

Cell Wall ◽

Tea Plant ◽

Cell Wall Structure ◽

Wall Structure ◽

Leaf Cell ◽

Fluoride Accumulation ◽

The Relationship

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Chromosomal mutants of Saccharomyces cerevisiae affecting the cell wall binding site for killer factor

Canadian Journal of Microbiology ◽

10.1139/m78-041 ◽

1978 ◽

Vol 24 (3) ◽

pp. 228-237 ◽

Cited By ~ 59

Author(s):

Karen Al-Aidroos ◽

H. Bussey

Keyword(s):

Saccharomyces Cerevisiae ◽

Cell Wall ◽

Binding Site ◽

Functional Groups ◽

Cell Wall Binding ◽

Mutant Strains

Fifty-two killer, factor-resistant, nuclear mutants were isolated from sensitive strains of yeast and assorted into three functional groups. All but one mutant owed their resistance to an alteration in the cell wall binding site for killer. In several mutant strains, an alteration at the site of killer binding was associated with a change in the susceptibility of the cell wall to degradation by glusulase. The killer-binding site could be inactivated by periodate but not by promise treatment. The nature of the site is discussed.

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