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Functional group quantification of polymer nanomembranes with soft x-rays.

ABSTRACT: Polyamide nanomembranes are at the heart of water desalination, a process which plays a critical role in clean water production. Improving their efficiency requires a better understanding of the relationship between chemistry, network structure, and performance but few techniques afford compositional information in ultrathin films (<100 nm). Here, we leverage resonant soft x-ray reflectivity, a measurement that is sensitive to the specific chemical bonds in organic materials, to quantify the functional group concentration in these polyamides. We first employ reference materials to establish quantitative relationships between changes in the optical constants and functional group density, and then use the results to evaluate the functional group concentrations of polyamide nanomembranes. We demonstrate that the difference in the amide carbonyl and carboxylic acid group concentrations can be used to calculate the crosslink density, which is shown to vary significantly across three different polyamide chemistries. A clear relationship is established between the functional group density and the permselectivity (?), indicating that more densely crosslinked materials result in a higher ? of the nanomembranes. Finally, measurements on a polyamide/poly(acrylic acid) bilayer demonstrate the ability of this approach to quantify depth-dependent functional group concentrations in thin films.

SUBMITTER: Sunday DF

PROVIDER: S-EPMC5997296 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Functional group quantification of polymer nanomembranes with soft x-rays.

Sunday Daniel F DF Chan Edwin P EP Orski Sara V SV Nieuwendaal Ryan C RC Stafford Christopher M CM

Physical review materials 20180315 3

Polyamide nanomembranes are at the heart of water desalination, a process which plays a critical role in clean water production. Improving their efficiency requires a better understanding of the relationship between chemistry, network structure, and performance but few techniques afford compositional information in ultrathin films (<100 nm). Here, we leverage resonant soft x-ray reflectivity, a measurement that is sensitive to the specific chemical bonds in organic materials, to quantify the fun ...[more]

PMID: 29904750

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Project description:Genomics and proteomics experiments produce a large amount of data that are awaiting functional elucidation. An important step in analyzing such data is to identify functional units, which consist of proteins that play coherent roles to carry out the function. Importantly, functional coherence is not identical with functional similarity. For example, proteins in the same pathway may not share the same Gene Ontology (GO) terms, but they work in a coordinated fashion so that the aimed function can be performed. Thus, simply applying existing functional similarity measures might not be the best solution to identify functional units in omics data.We have designed two scores for quantifying the functional coherence by considering association of GO terms observed in two biological contexts, co-occurrences in protein annotations and co-mentions in literature in the PubMed database. The counted co-occurrences of GO terms were normalized in a similar fashion as the statistical amino acid contact potential is computed in the protein structure prediction field. We demonstrate that the developed scores can identify functionally coherent protein sets, i.e. proteins in the same pathways, co-localized proteins, and protein complexes, with statistically significant score values showing a better accuracy than existing functional similarity scores. The scores are also capable of detecting protein pairs that interact with each other. It is further shown that the functional coherence scores can accurately assign proteins to their respective pathways.We have developed two scores which quantify the functional coherence of sets of proteins. The scores reflect the actual associations of GO terms observed either in protein annotations or in literature. It has been shown that they have the ability to accurately distinguish biologically relevant groups of proteins from random ones as well as a good discriminative power for detecting interacting pairs of proteins. The scores were further successfully applied for assigning proteins to pathways.

Dataset Information

Functional group quantification of polymer nanomembranes with soft x-rays.

Publications

Functional group quantification of polymer nanomembranes with soft x-rays.

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