Rheo‐NMR in food science—Recent opportunities

Galvosas, Petrik; Brox, Timothy I.; Kuczera, Stefan

doi:10.1002/mrc.4861

Cited by 14 publications

(11 citation statements)

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“…More in particular, MRI velocimetry experiments performed on samples under deformation (commonly known as rheo‐MRI) have been successfully applied to the characterization of diluted and dense emulsions, identification of non‐local effects, sedimentation, and shear‐induced migration of droplets . It has become clear that the understanding of the complex rheological behavior of emulsions will depend on the accurate spatially resolved determination of the droplets' phase concentration and velocity under shear . In short, we will refer to these spatially resolved images as concentration and velocity profiles.…”

Section: Introductionmentioning

confidence: 99%

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Selective oil‐phase rheo‐MRI velocity profiles to monitor heterogeneous flow behavior of oil/water food emulsions

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Nikolaeva

Vergeldt

et al. 2019

Magnetic Reson in Chemistry

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Section: Introductionmentioning

confidence: 99%

“…[13][14][15] It has become clear that the understanding of the complex rheological behavior of emulsions will depend on the accurate spatially resolved determination of the droplets' phase concentration and velocity under shear. [16] In short, we will refer to these spatially resolved images as concentration and velocity profiles.…”

Section: Introductionmentioning

confidence: 99%

Selective oil‐phase rheo‐MRI velocity profiles to monitor heterogeneous flow behavior of oil/water food emulsions

Serial

Nikolaeva

Vergeldt

et al. 2019

Magnetic Reson in Chemistry

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“…This limitation can be overcome by rheo-MRI velocimetry which can assess spatially resolved velocities of complex fluids with microscopic resolution. − In a label-free, real-time, and noninvasive manner, rheo-MRI can thus uniquely visualize regions governed by different constitutive laws. When rheo-MRI is performed in a concentric cylinder (CC) or Couette geometry with a known spatial stress distribution σ(r) over the gap between the cylinders, the determination of the spatial distribution of the shear rates γ̇( r ) opens up the possibility to deduce the constitutive law in the form of a so-called local flow curve (LFC) σ(γ̇( r )). ,, A main advantage of obtaining LFCs based on rheo-MRI velocimetry is that they can be obtained in a noninvasive real-time manner, which allows monitoring of transient changes in non-Newtonian flow behavior under shear stress.…”

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confidence: 99%

High Field MicroMRI Velocimetric Measurement of Quantitative Local Flow Curves

et al. 2020

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Performing rheo-microMRI velocimetry at a high magnetic field with strong pulsed field gradients has clear advantages in terms of (chemical) sensitivity and resolution in velocities, time, and space. To benefit from these advantages, some artifacts need to be minimized. Significant sources of such artifacts are chemical shift dispersion due to the high magnetic field, eddy currents caused by the pulsed magnetic field gradients, and possible mechanical instabilities in concentric cylinder (CC) rheo-cells. These, in particular, hamper quantitative assessment of spatially resolved velocity profiles needed to construct local flow curves (LFCs) in CC geometries with millimeter gap sizes. A major improvement was achieved by chemical shift selective suppression of signals that are spectroscopically different from the signal of interest. By also accounting for imperfections in pulsed field gradients, LFCs were obtained that were virtually free of artifacts. The approach to obtain quantitative LFCs in millimeter gap CC rheo-MRI cells was validated for Newtonian and simple yield stress fluids, which both showed quantitative agreement between local and global flow curves. No systematic effects of gap size and rotational velocity on the viscosity of a Newtonian fluid and yield stress of a complex fluid could be observed. The acquisition of LFCs during heterogeneous and transient flow of fat crystal dispersion demonstrated that local constitutive laws can be assessed by rheo-microMRI at a high magnetic field in a noninvasive, quantitative, and real-time manner.

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“…(Goyon, Colin, Ovarlez, Ajdari, & Bocquet, 2008;Masselon, Salmon, & Colin, 2008;Guillaume Ovarlez, Bertrand, & Rodts, 2006;Ragouilliaux, Herzhaft, Bertrand, & Coussot, 2006;Rodts et al, 2010) This limitation can be overcome by rheo-MRI velocimetry which can assess spatially resolved velocities of complex fluids with microscopic resolution. (Britton & Callaghan, 2000;Colbourne et al, 2018;Galvosas, Brox, & Kuczera, 2019; In a label-free, real-time and non-invasive manner, rheo-MRI can thus uniquely visualize regions governed by different constitutive laws. When rheo-MRI is performed in a concentric cylinder (CC) or Couette geometry with a known spatial stress distribution σ (r) over the gap between the cylinders, the determination of the spatial distribution of the shear rates γ̇(r) opens up the possibility to deduce the constitutive law in the form of a so-called local flow curve (LFC) σ(γ̇(r)).…”

Section: Introductionmentioning

confidence: 99%

“…In this respect, rheo-microMRI velocimetry at a high magnetic field strength B0 (7 T) with strong magnetic field gradients (typically of the order of 1 T/m) can offer significant improvements in performance. (Callaghan, Grant, Harris, & Wiley, 2002;Galvosas et al, 2019) The use of a higher B 0 field enhances sensitivity, and temporal resolution. In addition, the strong gradients allow for the acquisition of profiles with high spatial resolution over millimeter sized gaps and in a large dynamic range in rotational velocities.…”

Section: Introductionmentioning

confidence: 99%

Multiscale assessment of food lipid structures

Nikolaeva¹

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In these storage organelles lipids exist in liquid and liquid-crystalline (LC) phases, the latter as interfacial layers. In order to use plant lipids in food ingredients and products, they must undergo several structural and compositional conversions in the "farm-to-fork" chain. These processing routes have schematically been depicted for several fat-continuous food products in Figure 1.1. Industrial processing involving shear, temperature and pressure can significantly modulate the self-assembly of lipids (Leser, Sagalowicz, Michel, & Watzke, 2006; Farnaz Maleky, 2015). Lipids can organise themselves in a wide range of hierarchical crystalline and LC structures, which can span multiple scales from nano-, via meso-to macro (Kulkarni, 2012; Leser et al., 2006; Michalski et al., 2013). The organisation of both multiscale crystalline and LC lipid systems is governed by interplay of molecular and colloidal interactions. These underlie the physical properties of lipid systems when they undergo melting, crystallisation, and flow. Figure 1.1. Schematic example of lipid structures as they occur changes throughout the farm-to-fork supply chain of fat-continuous foods. 10 Chapter 1 colloidal dispersions (water-in-oil (W/O) and oil-in-water (O/W) emulsions) which can present a route for effective manufacturing of emulsified food products (Rousseau, 2000; Sato & Ueno, 2011). Current insights in the hierarchical multiscale architecture of fats are schematically summarized in Figure 1.2 (Farnaz Maleky, 2015; Marangoni et al., 2011). The formation of fat crystal network starts with the self-assembly of the TAG molecules into crystalline lamellar mesostructures. These lamellae stack epitaxially to form a crystalline domain, known as a crystalline nanoplatelet (CNP) (Acevedo & Marangoni, 2014). The CNPs can aggregate to larger microstructures that are plate-like, needle-like or spherulitic. Many factors affect the formation and the properties of fat crystal networks (Marangoni et al., 2011). The structural properties of TAG CNPs are influenced by the molecular properties of TAGs and their composition. Traditionally, formation of fat crystal networks via industrial processing routes involves melting and cooling steps. It is well known that changes in the shear rate and temperature during these steps lead to changes in the multiscale crystal network structures in fat-based systems (Farnaz Maleky & Mazzanti, 2018). They determine an intricate interplay between formation of fat crystals and their aggregation into larger structures. The strong coupling of the crystallisation and aggregation is adding significant complexity to the industrial manufacturing of fat-based food products. Figure 1.2. Structural levels present in a triacylglycerol (TAG) crystal network. Adapted from (Marangoni et al., 2019) with permission from Springer. 12 Chapter 1 1.2. Assessment of multiscale lipid structures The heterogeneous composition and structure of lipid-based foods put them among the most challenging systems to be studied at different length scale...

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Rheo‐NMR in food science—Recent opportunities

Cited by 14 publications

References 63 publications

Selective oil‐phase rheo‐MRI velocity profiles to monitor heterogeneous flow behavior of oil/water food emulsions

Selective oil‐phase rheo‐MRI velocity profiles to monitor heterogeneous flow behavior of oil/water food emulsions

High Field MicroMRI Velocimetric Measurement of Quantitative Local Flow Curves

Multiscale assessment of food lipid structures

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