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Kaysan G, Kräling R, Meier M, Nirschl H, Guthausen G, Kind M. Investigation of the surfactant distribution in oil-in-water emulsions during the crystallization of the dispersed phase via nuclear magnetic resonance relaxometry and diffusometry. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2022; 60:1131-1147. [PMID: 35971669 DOI: 10.1002/mrc.5305] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 08/05/2022] [Accepted: 08/10/2022] [Indexed: 06/15/2023]
Abstract
The crystallization of melt emulsions is of great interest to the food, cosmetic, and pharmaceutical industries. Surfactants are used in emulsions and suspensions to stabilize the dispersed phase; thus, questions arise about the liquid-liquid and solid-liquid interfaces of the droplets or particles and the distribution of the surfactant in the different phases (continuous and dispersed phase, interface). Nuclear magnetic resonance relaxation and diffusion measurements revealed that the internal and rotational mobility of surfactant molecules at the liquid-liquid interface decreases with increasing droplet sizes. Additionally, solid-liquid interfaces have fewer surfactants than liquid-liquid interfaces as a result of the desorption of the surfactant molecules during the crystallization of the droplets. Relaxation rates of surfactant molecules in aqueous solution as single molecules, micelles, and at the liquid-liquid and solid-liquid interface are analyzed for the first time.
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Affiliation(s)
- Gina Kaysan
- Institute for Thermal Process Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Raphael Kräling
- Institute for Thermal Process Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Manuel Meier
- Institute for Mechanical Engineering and Mechanics, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Hermann Nirschl
- Institute for Mechanical Engineering and Mechanics, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Gisela Guthausen
- Institute for Mechanical Engineering and Mechanics, Karlsruhe Institute of Technology, Karlsruhe, Germany
- Engler-Bunte Institut, Water Chemistry and Water Technology, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Matthias Kind
- Institute for Thermal Process Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
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2
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Grabe B, Hiller W. Molar Mass Distribution and Chemical Composition Distribution of PS- b-PMMA Block Copolymers Determined by Diffusion Ordered Spectroscopy. Macromolecules 2022. [DOI: 10.1021/acs.macromol.2c01505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Bastian Grabe
- Faculty of Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Straße 4a, 44227 Dortmund, Germany
| | - Wolf Hiller
- Faculty of Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Straße 4a, 44227 Dortmund, Germany
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3
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Fillbrook LL, Nothling MD, Stenzel MH, Price WS, Beves JE. Rapid Online Analysis of Photopolymerization Kinetics and Molecular Weight Using Diffusion NMR. ACS Macro Lett 2022; 11:166-172. [PMID: 35574764 DOI: 10.1021/acsmacrolett.1c00719] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Online, high-throughput molecular weight analysis of polymerizations is rare, with most studies relying on tedious sampling techniques and batchwise postanalysis. The ability to track both monomer conversion and molecular weight evolution in real time could underpin precision polymer development and facilitate study of rapid polymerization reactions. Here, we use a single time-resolved diffusion nuclear magnetic resonance (NMR) experiment to simultaneously study the kinetics and molecular weight evolution during a photopolymerization, with in situ irradiation inside the NMR instrument. As a model system, we used a photoinduced electron transfer reversible addition-fragmentation chain transfer (PET-RAFT) polymerization. The data allow diffusion coefficients and intensities to be calculated every 14 s from which the polymer size and monomer conversion can be extracted. Key to this approach is (1) the use of shuffled gradient amplitudes in the diffusion NMR experiment to access reactions of any rate, (2) the addition of a relaxation agent to increase achievable time resolution and, (3) a sliding correction that accounts for viscosity changes during polymerization. Diffusion NMR offers a uniquely simple, translatable handle for online monitoring of polymerization reactions.
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Affiliation(s)
| | | | | | - William S. Price
- Nanoscale Group, School of Science, Western Sydney University, Penrith, NSW 2751, Australia
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4
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Rudszuck T, Nirschl H, Guthausen G. Perspectives in process analytics using low field NMR. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 323:106897. [PMID: 33518174 DOI: 10.1016/j.jmr.2020.106897] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 12/15/2020] [Accepted: 12/18/2020] [Indexed: 06/12/2023]
Abstract
Low field NMR is a powerful analytical tool which creates an enormous added value in process analytics. Based on specific applications in process analytics and perspectives for low field NMR in form of spectroscopy, relaxation, diffusion, and imaging in quality control, diverse applications and technical realizations like spectrometers, time domain NMR, mobile NMR sensors and MRI will be discussed.
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Affiliation(s)
- T Rudszuck
- Institute for Mechanical Engineering and Mechanics, KIT, 76131 Karlsruhe, Germany
| | - H Nirschl
- Institute for Mechanical Engineering and Mechanics, KIT, 76131 Karlsruhe, Germany
| | - G Guthausen
- Institute for Mechanical Engineering and Mechanics, KIT, 76131 Karlsruhe, Germany; Engler-Bunte Institut, Water Science and Technology, KIT, 76131 Karlsruhe, Germany
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5
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6
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Amirkulova DB, Chakraborty M, White AD. Experimentally Consistent Simulation of Aβ 21-30 Peptides with a Minimal NMR Bias. J Phys Chem B 2020; 124:8266-8277. [PMID: 32845146 DOI: 10.1021/acs.jpcb.0c07129] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Misfolded amyloid peptides are neurotoxic molecules associated with Alzheimer's disease. The Aβ21-30 peptide fragment is a decapeptide fragment of the complete Aβ42 peptide which is a hypothesized cause of Alzheimer's disease via amyloid fibrillogenesis. Aβ21-30 is investigated here with a combination of NMR (nuclear magnetic resonance) spectroscopy experiments and molecular dynamics simulations with experiment directed simulation (EDS). EDS is a maximum entropy biasing method that augments a molecular dynamics simulation with experimental data (NMR chemical shifts) to improve agreement with experiments and thus accuracy. EDS molecular dynamics shows that the Aβ21-30 monomer has a β turn stabilized by the following interactions: S26-K28, D23-S26, and D23-K28. NMR, total correlation spectroscopy, and rotating frame Overhauser effect spectroscopy experiments provide independent agreement. Subsequent two- and four-monomer EDS simulations show aggregation. Diffusion coefficients calculated from molecular simulation also agreed with experimentally measured values only after using EDS, providing independent assessment of accuracy. This work demonstrates how accuracy can be improved by directly using experimental data in molecular dynamics of complex processes like self-assembly.
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Affiliation(s)
- Dilnoza B Amirkulova
- Department of Chemical Engineering, University of Rochester, Rochester, New York 14627, United States
| | - Maghesree Chakraborty
- Department of Chemical Engineering, University of Rochester, Rochester, New York 14627, United States
| | - Andrew D White
- Department of Chemical Engineering, University of Rochester, Rochester, New York 14627, United States
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7
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Galdino RV, Benevides CA, Tenório RP. Diffusion maps of Bacillus subtilis biofilms via magnetic resonance imaging highlight a complex network of channels. Colloids Surf B Biointerfaces 2020; 190:110905. [PMID: 32143011 DOI: 10.1016/j.colsurfb.2020.110905] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 02/20/2020] [Accepted: 02/24/2020] [Indexed: 10/24/2022]
Abstract
Bacillus subtilis microorganism when cultivated under chemically-defined conditions developed a biofilm with an unusual pattern of wrinkles on the surface. Some questions were raised about whether there was a special function of these wrinkles for the biofilm itself, since they resembled microchannels that could be involved in the transport of nutrients within the biofilm. Since the diffusion is the main mechanism for nutrient transport to biofilm from the medium, the role of these wrinkled structures in the whole diffusion within the biofilm was investigated using diffusion-weighted magnetic resonance imaging (DW-MRI). Data from these diffusion images was used to generate 2D diffusion maps which highlighted the striking channel features of the biofilm surface. The diffusion maps revealed a network of interconnected channels, with self-diffusion coefficients higher in the microchannels than in other regions of the biofilms. Polar plots made from 2D diffusion maps obtained from the plane of the biofilm show an anisotropy of the diffusion inside the microchannels, with the diffusion higher when along the principal direction of the microchannels. These results agree with the model, that the buckling of the biofilm surface from the B. subtilis creates microchannels that can enhance diffusion throughout the biofilm.
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Affiliation(s)
- Ramon V Galdino
- Centro Regional de Ciências Nucleares do Nordeste, Comissão Nacional de Energia Nuclear, Av. Prof. Luiz Freire, 200, Cidade Universitária, 50740-545 Recife, Pernambuco, Brazil; Agência Pernambucana de Vigilância Sanitária, Secretaria Estadual de Saúde de Pernambuco, Praça Osvaldo Cruz, s/n, Boa Vista, 50050-210 Recife, Pernambuco, Brazil
| | - Clayton A Benevides
- Centro Regional de Ciências Nucleares do Nordeste, Comissão Nacional de Energia Nuclear, Av. Prof. Luiz Freire, 200, Cidade Universitária, 50740-545 Recife, Pernambuco, Brazil
| | - Rômulo P Tenório
- Centro Regional de Ciências Nucleares do Nordeste, Comissão Nacional de Energia Nuclear, Av. Prof. Luiz Freire, 200, Cidade Universitária, 50740-545 Recife, Pernambuco, Brazil.
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8
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Hiller W. Quantitative Studies of Block Copolymers and Their Containing Homopolymer Components by Diffusion Ordered Spectroscopy. MACROMOL CHEM PHYS 2019. [DOI: 10.1002/macp.201900255] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Wolf Hiller
- Faculty of Chemistry and Chemical Biology Technical University Dortmund Otto‐Hahn‐Str. 4a D‐44227 Dortmund Germany
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9
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Castañar L, Poggetto GD, Colbourne AA, Morris GA, Nilsson M. The GNAT: A new tool for processing NMR data. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2018; 56:546-558. [PMID: 29396867 PMCID: PMC6001793 DOI: 10.1002/mrc.4717] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 01/15/2018] [Accepted: 01/22/2018] [Indexed: 05/31/2023]
Abstract
The GNAT (General NMR Analysis Toolbox) is a free and open-source software package for processing, visualising, and analysing NMR data. It supersedes the popular DOSY Toolbox, which has a narrower focus on diffusion NMR. Data import of most common formats from the major NMR platforms is supported, as well as a GNAT generic format. Key basic processing of NMR data (e.g., Fourier transformation, baseline correction, and phasing) is catered for within the program, as well as more advanced techniques (e.g., reference deconvolution and pure shift FID reconstruction). Analysis tools include DOSY and SCORE for diffusion data, ROSY T1 /T2 estimation for relaxation data, and PARAFAC for multilinear analysis. The GNAT is written for the MATLAB® language and comes with a user-friendly graphical user interface. The standard version is intended to run with a MATLAB installation, but completely free-standing compiled versions for Windows, Mac, and Linux are also freely available.
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Affiliation(s)
- Laura Castañar
- School of ChemistryUniversity of ManchesterOxford RoadManchesterM13 9PLUK
| | | | - Adam A. Colbourne
- School of ChemistryUniversity of ManchesterOxford RoadManchesterM13 9PLUK
| | - Gareth A. Morris
- School of ChemistryUniversity of ManchesterOxford RoadManchesterM13 9PLUK
| | - Mathias Nilsson
- School of ChemistryUniversity of ManchesterOxford RoadManchesterM13 9PLUK
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10
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Herrling MP, Weisbrodt J, Kirkland CM, Williamson NH, Lackner S, Codd SL, Seymour JD, Guthausen G, Horn H. NMR investigation of water diffusion in different biofilm structures. Biotechnol Bioeng 2017; 114:2857-2867. [PMID: 28755486 DOI: 10.1002/bit.26392] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 06/08/2017] [Accepted: 07/23/2017] [Indexed: 01/19/2023]
Abstract
Mass transfer in biofilms is determined by diffusion. Different mostly invasive approaches have been used to measure diffusion coefficients in biofilms, however, data on heterogeneous biomass under realistic conditions is still missing. To non-invasively elucidate fluid-structure interactions in complex multispecies biofilms pulsed field gradient-nuclear magnetic resonance (PFG-NMR) was applied to measure the water diffusion in five different types of biomass aggregates: one type of sludge flocs, two types of biofilm, and two types of granules. Data analysis is an important issue when measuring heterogeneous systems and is shown to significantly influence the interpretation and understanding of water diffusion. With respect to numerical reproducibility and physico-chemical interpretation, different data processing methods were explored: (bi)-exponential data analysis and the Γ distribution model. Furthermore, the diffusion coefficient distribution in relation to relaxation was studied by D-T2 maps obtained by 2D inverse Laplace transform (2D ILT). The results show that the effective diffusion coefficients for all biofilm samples ranged from 0.36 to 0.96 relative to that of water. NMR diffusion was linked to biofilm structure (e.g., biomass density, organic and inorganic matter) as observed by magnetic resonance imaging and to traditional biofilm parameters: diffusion was most restricted in granules with compact structures, and fast diffusion was found in heterotrophic biofilms with fluffy structures. The effective diffusion coefficients in the biomass were found to be broadly distributed because of internal biomass heterogeneities, such as gas bubbles, precipitates, and locally changing biofilm densities. Thus, estimations based on biofilm bulk properties in multispecies systems can be overestimated and mean diffusion coefficients might not be sufficiently informative to describe mass transport in biofilms and the near bulk.
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Affiliation(s)
- Maria P Herrling
- Department of Wastewater Engineering, Institute IWAR, Technische Universität Darmstadt, Darmstadt, Germany.,Department of Water Chemistry and Water Technology, Engler-Bunte-Institute, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Jessica Weisbrodt
- Department of Water Chemistry and Water Technology, Engler-Bunte-Institute, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Catherine M Kirkland
- Center of Biofilm Engineering, Montana State University, Bozeman, Montana.,Department of Mechanical and Industrial Engineering, Montana State University, Bozeman, Montana
| | - Nathan H Williamson
- Future Industries Institute, University of South Australia, Mawson Lakes Campus, Adelaide, Australia
| | - Susanne Lackner
- Department of Wastewater Engineering, Institute IWAR, Technische Universität Darmstadt, Darmstadt, Germany
| | - Sarah L Codd
- Center of Biofilm Engineering, Montana State University, Bozeman, Montana.,Department of Mechanical and Industrial Engineering, Montana State University, Bozeman, Montana
| | - Joseph D Seymour
- Center of Biofilm Engineering, Montana State University, Bozeman, Montana.,Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana
| | - Gisela Guthausen
- Department of Water Chemistry and Water Technology, Engler-Bunte-Institute, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Institute of Mechanical Process Engineering and Mechanics, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Harald Horn
- Department of Water Chemistry and Water Technology, Engler-Bunte-Institute, Karlsruhe Institute of Technology, Karlsruhe, Germany
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11
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Williamson NH, Röding M, Miklavcic SJ, Nydén M. Scaling exponent and dispersity of polymers in solution by diffusion NMR. J Colloid Interface Sci 2017; 493:393-397. [DOI: 10.1016/j.jcis.2017.01.058] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Revised: 01/14/2017] [Accepted: 01/17/2017] [Indexed: 11/30/2022]
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12
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Guo X, Laryea E, Wilhelm M, Luy B, Nirschl H, Guthausen G. Diffusion in Polymer Solutions: Molecular Weight Distribution by PFG-NMR and Relation to SEC. MACROMOL CHEM PHYS 2016. [DOI: 10.1002/macp.201600440] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Xiaoai Guo
- Institute for Chemical Technology and Polymer Chemistry; Karlsruhe Institute of Technology (KIT); Engesserstrasse 18 76128 Karlsruhe Germany
- Pro NMR IBG-4 and MVM; Karlsruhe Institute of Technology (KIT); Adenauerring 20b 76131 Karlsruhe Germany
| | - Esther Laryea
- Institute of Thermal Process Engineering; Karlsruhe Institute of Technology (KIT); Kaiserstrasse 12 76131 Karlsruhe Germany
| | - Manfred Wilhelm
- Institute for Chemical Technology and Polymer Chemistry; Karlsruhe Institute of Technology (KIT); Engesserstrasse 18 76128 Karlsruhe Germany
| | - Burkhard Luy
- Pro NMR IBG-4 and MVM; Karlsruhe Institute of Technology (KIT); Adenauerring 20b 76131 Karlsruhe Germany
| | - Hermann Nirschl
- Pro NMR IBG-4 and MVM; Karlsruhe Institute of Technology (KIT); Adenauerring 20b 76131 Karlsruhe Germany
| | - Gisela Guthausen
- Pro NMR IBG-4 and MVM; Karlsruhe Institute of Technology (KIT); Adenauerring 20b 76131 Karlsruhe Germany
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13
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Williamson NH, Röding M, Galvosas P, Miklavcic SJ, Nydén M. Obtaining T1-T2 distribution functions from 1-dimensional T1 and T2 measurements: The pseudo 2-D relaxation model. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2016; 269:186-195. [PMID: 27344611 DOI: 10.1016/j.jmr.2016.06.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2016] [Revised: 06/14/2016] [Accepted: 06/15/2016] [Indexed: 06/06/2023]
Abstract
We present the pseudo 2-D relaxation model (P2DRM), a method to estimate multidimensional probability distributions of material parameters from independent 1-D measurements. We illustrate its use on 1-D T1 and T2 relaxation measurements of saturated rock and evaluate it on both simulated and experimental T1-T2 correlation measurement data sets. Results were in excellent agreement with the actual, known 2-D distribution in the case of the simulated data set. In both the simulated and experimental case, the functional relationships between T1 and T2 were in good agreement with the T1-T2 correlation maps from the 2-D inverse Laplace transform of the full 2-D data sets. When a 1-D CPMG experiment is combined with a rapid T1 measurement, the P2DRM provides a double-shot method for obtaining a T1-T2 relationship, with significantly decreased experimental time in comparison to the full T1-T2 correlation measurement.
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Affiliation(s)
- Nathan H Williamson
- Future Industries Institute, University of South Australia, Mawson Lakes, SA 5095, Australia.
| | - Magnus Röding
- SP Food and Bioscience, Frans Perssons väg 6, 402 29 Göteborg, Sweden; School of Energy and Resources, UCL Australia, University College London, 220 Victoria Square, Adelaide, SA 5000, Australia.
| | - Petrik Galvosas
- MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Chemical and Physical Sciences, Victoria University of Wellington, PO Box 600, Wellington, New Zealand.
| | - Stanley J Miklavcic
- Phenomics and Bioinformatics Research Centre, School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA 5095, Australia.
| | - Magnus Nydén
- School of Energy and Resources, UCL Australia, University College London, 220 Victoria Square, Adelaide, SA 5000, Australia.
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14
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Williamson NH, Nydén M, Röding M. The lognormal and gamma distribution models for estimating molecular weight distributions of polymers using PGSE NMR. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2016; 267:54-62. [PMID: 27116223 DOI: 10.1016/j.jmr.2016.04.007] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Revised: 03/30/2016] [Accepted: 04/03/2016] [Indexed: 06/05/2023]
Abstract
We present comprehensive derivations for the statistical models and methods for the use of pulsed gradient spin echo (PGSE) NMR to characterize the molecular weight distribution of polymers via the well-known scaling law relating diffusion coefficients and molecular weights. We cover the lognormal and gamma distribution models and linear combinations of these distributions. Although the focus is on methodology, we illustrate the use experimentally with three polystyrene samples, comparing the NMR results to gel permeation chromatography (GPC) measurements, test the accuracy and noise-sensitivity on simulated data, and provide code for implementation.
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Affiliation(s)
- Nathan H Williamson
- Future Industries Institute, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia.
| | - Magnus Nydén
- Future Industries Institute, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; School of Energy and Resources, UCL Australia, University College London, Torrens Building, 220 Victoria Square, Adelaide, SA 5000, Australia.
| | - Magnus Röding
- Future Industries Institute, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; School of Energy and Resources, UCL Australia, University College London, Torrens Building, 220 Victoria Square, Adelaide, SA 5000, Australia; SP Food and Bioscience, Frans Perssons väg 6, 402 29 Göteborg, Sweden.
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