Structure and functionality of nanostructured triacylglycerol crystal networks

Ramel, P; Co, Edmund D.; Acevedo, Nuria C.; Marangoni, Alejandro G.

doi:10.1016/j.plipres.2016.09.004

Cited by 62 publications

(34 citation statements)

References 104 publications

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“…The lower fractal dimension for MC dispersions indicates that cluster-cluster aggregation mechanisms such as Reaction or Diffusion-Limited Cluster-Cluster Aggregation (RLCCA or DLCCA) are at play. 9,18,[49][50][51] Such mechanisms are in line with the previously observed stacking of nanoplatelets in TAGwoods. 24 The aggregation of TAGwoods will then form networks with a low fractal dimension (D m < 2).…”

Section: Fractal Network Characterisationsupporting

confidence: 90%

“…Under slow crystallization conditions PPP can form pure and smooth crystals, which are prone to stack into TAGwoods. 9,24,47,48 The higher s values for MFC dispersions can be explained by rapid crystallisation during Table 1 Overview of structural parameters derived from 20% MFC and MC dispersions by means of WAXS, SAXS and USAXS using the Scherrer equation (SE) to the first order diffraction line, the Unified Fit (UF) and Guinier-Porod (GP) models. The UF model covered two structural levels and provided the Porod slope, P, and the radius of gyration, R g for each of them.…”

Section: Usaxsmentioning

confidence: 99%

“…8 They can aggregate to larger structures that are plate-like, needle-like or spherulitic. 9,10 These aggregates form a fractal network, with weak-link interactions between them. 11 The viscoelastic and yield stress properties 7,12,13 of networks formed from the melt strongly depend on the processing conditions during cooling, like temperature and shear.…”

Section: Introductionmentioning

confidence: 99%

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Networks of micronized fat crystals grown under static conditions

et al. 2018

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Dispersing micronized fat crystals (MFCs) in oil is a novel route to largely decouple fat crystallisation and network formation and thus to simplify the manufacture of fat-continuous food products. MFCs dispersed in oil form a weak-interaction network organized by crystal aggregates in a continuous net of crystalline nanoplatelets. The rough surface of MFC nanoplatelets hampers stacking into one-dimensional aggregates, which explains the high mass fractal dimensions of the networks formed in MFC dispersions. Applying shear does not have a significant effect on the fractal dimensions of MFC networks, and MFC aggregates in the range of 5-10 μm remain intact. However, shear leads to a significant loss of storage modulus and yield stress over a time frame of an hour. This can be attributed to irreversible disruption of the continuous net of nanoplatelets. Rheo-SAXS revealed that shear releases nanoplatelets from the continuous net, which subsequently align in the shear field and undergo rapid recrystallisation. The release of thin and metastable nanoplatelets from the weak-link network bears relevance for simplified and more effective manufacturing of emulsified food products by effectively decoupling crystallisation, network formation and emulsification.

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Section: Fractal Network Characterisationsupporting

confidence: 90%

Section: Usaxsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Networks of micronized fat crystals grown under static conditions

et al. 2018

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“…Such networks are hierarchically built up from TAG molecules (Acevedo & Marangoni, ), lamellae, crystal nanoplatelets (Acevedo & Marangoni, ; Sato & Ueno, ), clusters, and flocs. The prevailing assumption is that weak interactions between flocs determine the strength of the overall network, i.e., the weak‐link network hypothesis (Awad, Rogers, & Marangoni, ; Ramel, Co, Acevedo, & Marangoni, ). These multiscale weakly linked fat crystal network structures are dependent on molecular composition, cooling rate, shear rate, and aging time (Marangoni & Wesdorp, ; Vreeker, Hoekstra, Den Boer, & Agterof, ).…”

Section: Introductionmentioning

confidence: 99%

“…Most techniques currently used to quantify the structure of fat crystal networks are limited by the fact that no spatial information can be extracted. Electron microscopy can visualize fat crystals at the nanoscale to micronscale but requires intense pretreatment which precludes observation of networks (Ramel et al, ). Polarized light microscopy (PLM) is often used to quantify structural features of fat crystal networks, but only at the level of micronscale aggregates.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Structural Analysis of Fat Crystal Networks by Means of Raman Confocal Imaging

Martens

Dalen

Heussen

et al. 2018

J Americ Oil Chem Soc

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The techniques that are currently available to assess fat crystal networks are compromised with respect to invasive sample preparation and ability to quantify compositional and structural features. Raman confocal hyperspectral imaging coupled to analysis with multivariate curve resolution can address these bottlenecks, as it provides label‐free, noninvasive chemical information in three dimensions (3D). We demonstrate the ability to acquire compositional maps of dispersions of micronized fat crystals (MFC) in oil, which contain local concentrations of liquid oil and solid fat with submicron spatial resolution and with acquisition times in the order of 10 min. From the compositional maps, we can derive quantitative information on the size and porosity of fat crystal flocs, as well as the solid fat content of the embedding continuous phase. Furthermore, the fractal dimension of the fat crystal network could be determined from the compositional maps via the box‐counting method and via the porosities of the crystal flocs. This makes it feasible to assess the validity of the weak‐link network theory under industrial relevant conditions. The confocal imaging mode allows for straightforward acquisition of 3D compositional cubes by recording a stack of two‐dimensional (2D) images. The box‐counting fractal dimension analysis performed on 2D maps can be extended to 3D cubes, which allows for straightforward verification that MFC networks are self‐similar rather than self‐affine.

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Fat Crystal Networks

Co¹,

Marangoni²

2020

Bailey's Industrial Oil and Fat Products

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This article examines the conceptual framework of the crystal network of fat materials in the context of its many hierarchical levels, from the molecular/nanostructural (10 −9 m) level all the way to the submillimeter (10 −6 m) length scale. Included in this article is a discussion on thermal properties of triacylglycerols, phase behavior, crystallization thermodynamics, crystallization into single crystals (crystalline nanoplatelets), aggregation of single crystals, rheology, and derivations of material properties based on the microstructure. Introductory concepts are provided, and for more detailed scholarship, readers are referred to an ample list of specialist texts and papers on the subject.

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Structure and functionality of nanostructured triacylglycerol crystal networks

Cited by 62 publications

References 104 publications

Networks of micronized fat crystals grown under static conditions

Networks of micronized fat crystals grown under static conditions

Quantitative Structural Analysis of Fat Crystal Networks by Means of Raman Confocal Imaging

Fat Crystal Networks

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