Structure and functionality of nanostructured triacylglycerol crystal networks

    Structure and functionality of nanostructured triacylglycerol crystal networks Pere R. Ramel, Edmund D. Co, Nuria C. Acevedo, Alejandro G. Marangoni PII: DOI: Reference:

S0163-7827(16)30031-5 doi:10.1016/j.plipres.2016.09.004 JPLR 928

To appear in: Received date: Revised date: Accepted date:

3 June 2016 28 September 2016 29 September 2016

Please cite this article as: Ramel Pere R., Co Edmund D., Acevedo Nuria C., Marangoni Alejandro G., Structure and functionality of nanostructured triacylglycerol crystal networks, (2016), doi:10.1016/j.plipres.2016.09.004

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ACCEPTED MANUSCRIPT Structure and Functionality of Nanostructured Triacylglycerol Crystal Networks

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Pere R. Ramela, Edmund D. Coa, Nuria C. Acevedob and Alejandro G. Marangonia* Department of Food Science, University of Guelph, 50 Stone Road East, ON N1G 2W1,

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Canada

Department of Food Science and Human Nutrition, Iowa State University, 2312 Food

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Sciences Building, Ames, IA 50011-1061, USA

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*Corresponding author: [email protected] Abstract

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In this review, recent advances in the characterization of the nanoscale structure of fat crystal networks are outlined. The effect of different factors on the properties of crystalline

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nanoplatelets (CNPs) is comprehensively described. These are discussed together with the observed changes in polymorphism and micro- or mesostructural properties so as to have a complete understanding of the influence of different internal and external factors on the material properties of fats. The relationship between the nanostructure and the material properties of fats (i.e., oil binding capacity and rheology) is also described. Characterization of the nanostructure of fats has provided a new dimension to the analysis of fat crystal networks and opportunities for nanoengineering that could result in innovations in the food industry with regards to processing and structuring fatty materials.

1. Introduction

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ACCEPTED MANUSCRIPT Fats and oils are important components of the human diet. As macronutrients, lipids serve as a dense (at 9 kcal/gram) energy source for the human body. In addition, food lipids function

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as precursors for compounds that are essential for metabolism [1–5]. In foods, lipids impart a

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characteristic flavor and act as a delivery system for fat-soluble ingredients and vitamins [6].

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Besides its nutritional and dietary significance, its importance to the mechanical (e.g., hardness and cohesiveness) and rheological properties of food products is also worth

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highlighting [7–10].

Chemically, fats consist chiefly of triacylglycerols or TAGs, which are molecules composed

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of a glycerol backbone with three fatty acid moieties esterified onto it. Depending on the degree of saturation of the fatty acids in the TAGs, the fat will behave either as a solid or a

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liquid at different temperatures. The ratio of the solid crystalline mass to liquid oil will influence its functionality (e.g., plasticity) [11–15]. Besides solid fat content (SFC), the functionality of a fat is also affected by the crystal structure formed by the TAG crystals [9,16–20]. The crystallization of TAGs proceeds in two phases: nucleation and crystal growth. However, before the nucleation process can ocurr, supersaturation (in the case where the crystallizing TAG is in the solution phase) or undercooling (in the case where the crystallizing TAG is in the neat liquid phase, i.e. melt) must be first achieved [9,21]. A state of supersaturation is achieved when the temperature of the solution (i.e. a solution of highmelting TAGs in non-crystallizing TAGs) is low enough such that the concentration of highmelting TAGs in the melt exceeds the solubility limit of these TAGs at the given temperature and in a given system. Supersaturation can be achieved in practice by lowering the 2

ACCEPTED MANUSCRIPT temperature of the solution [9]. In the case of a neat liquid phase of TAGs, nucleation can be initiated by undercooling the system, that is, by lowering the temperature of the melt below

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the melting point (however defined) of the crystallizing species. Once supersaturated or

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undercooled, high-melting TAG molecules can nucleate, that is, form ordered crystalline

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domains up to a stable critical size (Figure 1a and 1b) [9,22,23]. A crystal nucleus is the smallest crystal that can be present in the system, given a specific TAG concentration and

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temperature. On the other hand, embryos are molecular agglomerates of a size smaller than

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the critical radius; embryos are unstable and therefore re-dissolve into the melt. Once a stable nucleus is formed, crystal growth proceeds rapidly and the number of nuclei initially present

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determines the amount and size of the crystals formed (Figure 1c) [9,23–26]. This process is

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essential to the formation of a fat crystal network [9,21,25].

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Knowledge of the crystal network formed by TAGs is necessary for understanding and modifying the various functional properties of fats in food. For example, prevention of bloom formation in chocolate requires an understanding of how the liquid phase migrates in the fat crystal network while modifying the texture of butter requires an understanding of the TAG crystal size and how these crystals bind oil [27–31]. Various techniques can be used to study the different structural levels present in fat crystal networks. These methods include Xray diffraction and microscopy [32,33].

1.1 Polymorphism

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ACCEPTED MANUSCRIPT The structure of a fat crystal network at the molecular level is described by the myriad ways in which TAGs (or subunits thereof) can pack into a crystalline arrangement. The packing of

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the individual TAG molecules relative to the space lattice describes the unit cell of the

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crystal. The ability of ethylene subunits within the long polyethylene-like fatty acid chains in

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the TAG unit cell to pack into multiple geometrical arrangements, the so-called “subcell packing”, is referred to as polymorphism [21,34]. The polymorph that TAGs crystallize into

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greatly affects their melting behavior; i.e., the more stable the polymorph formed, the more

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densely the TAGs pack and thus, the higher the density, melting point and melting enthalpy of the resulting crystal [35]. Three major polymorphs are usually found in fats. In order of

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increasing stability, these are the hexagonal, orthorhombic perpendicular, and triclinic

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subcell packings commonly known as α, βʹ, and β polymorph, respectively (Figure 2a) [21].

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Furthermore, TAGs can pack in double (2L) or triple (3L) chain length arrangements (Figure 2b) [9]. These crystal polymorphs have been well characterized using wide and small-angle X-ray diffraction (WAXD and SAXD) techniques [33,36–39]. The effect of internal (e.g., composition, solid to liquid fat ratio) and external variables (e.g., cooling rate, crystallization temperature and shear) on the polymorphic form assumed by TAGs have been comprehensively studied [9,36,40–42].

1.2 Microstructure The structure of a fat crystal network at the microscale structural level is characterized by the morphology (size and shape) of the fat crystals formed. The morphology (and changes thereof) of these fat crystals can be directly observed using polarized light microscopy (PLM) 4

ACCEPTED MANUSCRIPT because they are birefringent [9,26]. Under PLM, crystals appear bright, whereas the liquid oil appears dark. As with polymorphism, the size and shape of fat crystals is greatly affected

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by a number of external and internal variables [43–46]. Ramel and Marangoni [47] were able

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to generate a concentration-temperature map for different fat crystal structures in milk fat

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(Figure 3). The morphological characteristics of these crystals (i.e., size, shape and mass distribution) have been extensively correlated to the observed physical properties of fats,

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such as hardness and spreadability [7,16,48,49].

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1.3. Nanostructure Knowledge Gap: Why Studying the Nanostructure is Important

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For a long time, it was widely assumed that the particles observed in PLM images of fat samples were TAG single crystals formed through the continuous growth of TAG nuclei. A

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natural extension of this assumption was that the polymorphic form adopted by the TAGs in a crystal determines the morphology of the crystal formed. This view is untenable as polymorphic phenomena occur at a length scale that is too small to have any direct correlations with microscale phenomena. Recent scientific evidence has indeed led to a revision of the assumption that the polymorphic form is somehow responsible for determining the crystal morphology. Furthermore, some mechanical and rheological properties arising from the fractal nature of fat crystal networks (e.g., oil-binding capacity) cannot be fully explained by the length scales (i.e., microscale) heretofore studied. A primary limitation in the two traditional methods used to study fat crystal structure (X-ray diffraction and PLM) are the length scales involved. X-ray diffraction is well suited to studying structural features in the 0.1 nm to 10 nm length scale. However, larger structures are 5

ACCEPTED MANUSCRIPT inaccessible due to limitations in X-ray instrumentation. PLM is well suited to studying structural features in the 1 µm to 100 µm length scale. However, smaller structures are

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inaccessible due to the inherently limited resolution of microscopy conducted using visible

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light. Thus, knowledge of structural features in the length scale between 100 nm and 1,000

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nm (the nanoscale) was limited by the available instrumentation of the time. The ability to study the nanoscale can provide a more complete characterization of the

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structure-function relationships in fat crystal networks. Modern techniques such as electron

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microscopy and ultra-small angle X-ray scattering have been utilized to explore structural features at the nanoscale. In essence, these techniques are essentially refinements of X-ray

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diffraction and PLM. In the case of ultra-small angle X-ray scattering, advances in X-ray

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instrumentation and X-ray sources have allowed for the characterization of larger structures.

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In electron microscopy, the use of electrons (which have a de Broglie wavelength of 1.23 nm) allow for a higher resolution such that much smaller particles can be imaged. By removing oil through the use of different solvents and detergents, Poot et al. [50] and Jewell and Meara [51] were able to clearly image fat crystals using electron microscopy. Furthermore, by fixing fat crystals to a thin carbon support film, Heertje and Leunis [52] were able to visualize and measure the size of individual crystals using transmission electron microscopy (TEM). Using similar techniques of oil removal and sample fixation, a procedure for visualizing fat crystals using cryogenic transmission electron microscopy (cryo-TEM) was developed. Through mechanical break-down of large fat crystals and the removal of oil, Acevedo and Marangoni [53] were able to image TAG single crystals, christened crystalline nanonplatelets 6

ACCEPTED MANUSCRIPT (CNPs) (Figure 1b). As previously believed, the particles observed using PLM were not single crystals but rather three-dimensional polycrystalline aggregates consisting of

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crystalline nanoplatelets.

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More recently, through the use of ultra-small angle X-ray scattering (USAXS) studies aided

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by computer simulations and modeling, the surface morphology of individual CNPs and the characteristics of CNP aggregates were described [54–57]. This allowed for a more complete

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characterization of the nanoscale structure of fats and the further establishment of the

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relationship between fractality and the rheological properties of TAG crystal networks described by Marangoni and collaborators [16,58–60].

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In this review, recent work towards the characterization of the nanoscale structure of TAG crystal networks is comprehensively described. This most recent progress in the

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characterization of fat crystal structure could provide further understanding of the rheological properties of fats in food.

2. Characterization of the nanoscale structure of triacylglycerol networks 2.1. Extraction of CNPs (cold-isobutanol) and image analysis (cryo-TEM) The extraction of CNPs from a fat material was performed by washing fat with cold solvents such as isobutanol at a 1:50 (w/w) fat: solvent ratio. The CNPs suspended in this fat-solvent mixture was then homogenized using a rotostator [53,61]. Depending on the melting point and chemical composition of the fats, homogenization needs to be well-controlled, in terms of speed and temperature [62]. Homogenization of the mixture is necessary to induce de7

ACCEPTED MANUSCRIPT aggregation of the CNP aggregates. The application of low shear causes insufficient deaggregation, while excessive shearing results in a rise in temperature and the melting of the

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CNPs. After homogenization, oil is eliminated by filtering the mixture through a glass fiber

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filter with a 1.0 μm pore size, followed by a second round of washing and homogenization.

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The mixture is then ultra-sonicated for further dispersion of the CNPs. Like homogenization, ultra-sonication must be properly controlled to prevent melting of the CNPs. Observation of

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the CNPs using cryo-TEM is performed by fixing a drop of the sample (CNPs suspended in

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isobutanol) onto a carbon grid with perforated carbon film and coating it with uranyl acetate. Imaging of these CNPs using cryo-TEM allows for the measurement of CNP dimensions

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(length and width). In addition, serendipitous side-views of the CNPs also allow for the

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measurement of the thickness of individual platelets as well as visualizing the inner structure

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of the crystalline nanoplatelets.

CNPs are formed from the growth of TAG lamellae in the c-axis of crystallization (parallel to the fatty acid chain axis) to form a single crystalline domain. This has been borne out by a close agreement between measurements of the crystalline domain size via Scherrer analysis of small-angle X-ray scattering (SAXS) data and the measured thickness of the CNPs using image analysis (Figure 4a, 4b and 4c) [53,61–63]. 2.2. Domain size by SAXS (Scherrer analysis) SAXS analysis was performed to determine the crystalline domain size of CNPs observed using cryo-TEM. From the SAXS patterns (Figure 4c), the crystalline domain size (ξ) can be calculated using the Scherrer formula [53]:

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ACCEPTED MANUSCRIPT 

K FWHM cos 

(1)

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where K is the shape factor, θ is the diffraction angle, FWHM is the full width at half of the

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maximum peak height in radians, and λ is the wavelength of the X-rays, which is 1.54 Å for

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copper source. K is dimensionless and provides information about the “roundness” of the particle. A shape factor of 1 is used for spherical particles while a shape factor of less than 1

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is used for other shapes. For crystallites of unknown shape, a value of 0.9 is usually used.

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As previously mentioned, a good agreement between the crystalline domain size determined

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using Scherrer analysis and the thickness of CNPs using image analysis was reported [62,64].

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2.3. Modeling and computer simulation - USAXS USAXS is a type of X-ray scattering technique commonly used for the characterization of particle size and morphology [65,66]. Its use in the physical characterization of edible fats has grown in popularity due to its ability to characterize structures much larger (up to dimensions of ~15µm) than those previously characterized using more common X-ray techniques [67]. However, in order to interpret scattering patterns obtained using USAXS, an appropriate theoretical model for the material being studied is essential. With the knowledge that fat crystal networks are comprised of CNPs, Pink et al [54] developed computer simulations for understanding the interactions and aggregations of CNPs. These workers treated CNPs as rigid spheres arrayed in a planar arrangement. The diameter of these spheres was approximately 50 nm. Interactions between these spheres were defined using the Hamaker coefficient. Furthermore, by employing Monte Carlo computer simulations, the 9

ACCEPTED MANUSCRIPT characteristics of CNPs as well as CNP aggregates were obtained for fats with simulated solid fat contents [54–57,67–69].

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A USAXS pattern of shea butter is shown in Figure 5 with the corresponding P and Rg

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values. The USAXS pattern was interpreted using the Guinier-Porod and Unified Fit models

B  Pe q

2   q 2 Rgi  1     3  

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I (q)  Ge

2    q 2 Rgi     3  

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[67,70,71]. The Unified Fit equation is written as:

   qR gi  erf  1 / 2     6 

3P

(2)

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The first term describes the Guinier region, valid for q ≤ q1, and the second term, the Porod

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power law region, is valid for q ≥ q1. G is related to the volume of the scatterers while B

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contains specific surface area information and P is the Porod exponent that measures the

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internal structure of the aggregate [72]. The term e

  q 2 Rg2     3   

assumes that all scattering objects

are approximately spherical.

Values of the parameters P and Rg are obtained from fitting the equation to the USAXS pattern and determining the slopes using Irena (Igor Pro 6.36, Wavemetrics, Inc., USA) as described by Ilavsky and Jemian [73]. In fats, up to three structural levels have been identified (indicated by three slopes, P) [62,67]. For low concentration solids (SFC ≤ 40%), P1 gives a description of the surface morphology of the CNPs, and this could be either a smooth, rough or a fuzzy surface; P2 describes the aggregation of CNPs either into long rods, termed TAGwoods (Figure 6) or other identifiable forms; P3, although not found in shea butter in Figure 5, describes the aggregation of TAGwoods and other forms into larger structures. 10

ACCEPTED MANUSCRIPT Slope 1 or |P1| ~ 4 indicates the presence of smooth CNPs; |P1| < 4 indicates that CNPs have rough surfaces; and |P1| > 4 indicates that the CNPs are coated with oil. On the other hand,

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slope 2, or P2 equal to 1, indicates the presence of TAGwoods, while P2 values of 1.7 to 1.9,

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and 2.0 to 2.1 indicate that the CNPs or TAGwoods have aggregated via diffusion-limited

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cluster-cluster aggregation (DLCA) and reaction-limited cluster-cluster aggregation (RLCA), respectively. Lastly, P3 values equal to 3 (slow cooling) and 3.8 (fast cooling) indicate a

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uniform distribution of mass, while 4.1 to 4.3 indicates that the larger aggregates have a

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diffuse interface.

The parameter Rg, is the average radius of gyration of the “scatterer” (i.e., CNP or of a larger

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structure, like TAGwoods or their aggregates) for the particular structural level identified

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with P. Rg1 describes the average size of the CNPs while Rg2 describes the average size of the

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larger aggregates. With the assumption that the CNPs and its aggregates are spherical, the average size (diameter) of the CNPs and the aggregates are computed using the equation: diameterCNP  2

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Rg

(3)

The parameter P has been correlated with the fractal dimension [54,55,57,67,74]. According to Porod’s law, a P value equal to 4 indicates a fractal dimension, D, equal to 2, which characterizes a smooth surface. For 3 ≤ |P| < 4, the fractal dimension is calculated as 6 - |P|, which gives fractal values in the range of 2 < D ≤ 3. Lastly, for 1 ≤ |P| < 3, D is found to be equal to the value of |P|[72,75].

3. Effect of different factors on the nanostructure of fat 11

ACCEPTED MANUSCRIPT Numerous studies have been carried out over the years to determine the effect of different factors on fat crystal structure. Chemical composition and processing conditions have been

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shown to greatly affect the polymorphism and microstructure. The effect of these factors on

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the nanostructure of fat crystal networks is outlined in the following section.

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3.1 Effect of TAG composition

The effect of composition on fat crystal structure is determined by the degree of saturation of

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TAGs present and the resulting supersaturation or undercooling during crystallization. At the

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molecular level, the more saturated and uniform the TAGs, the more stable the polymorphic

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form formed upon nucleation, while the presence of a kink such as in cis-unsaturated fatty acids results in the formation of less stable polymorphic forms [36,41,76–79]. On the other

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hand, at the mesoscale, the higher the degree of supersaturation or undercooling, the smaller the crystals formed, while at lower degrees of supersaturation or undercooling, crystal growth is favored and larger crystals are formed [80,81]. The degree of supersaturation also affects the nanostructure. Acevedo and Marangoni [53] found that a higher amount of fully hydrogenated canola oil (FHCO) in blends of FHCO and high oleic soybean oil (HOSO) (acting as the solvent) results in CNPs with smaller lengths, widths and thicknesses (Figure 7). On the other hand, in more complex mixtures such as cocoa butter and milk fat, a wider crystal size distribution is found with mostly long and thin CNPs (Figure 8). In milk fat, it was found that these CNPs are mainly composed of the

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ACCEPTED MANUSCRIPT higher melting fraction (HMF) as the lower melting fraction is removed during the extraction process.

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Using USAXS, the effect of composition on the properties of CNPs was further characterized.

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By subjecting different blends of fats to USAXS analysis under static cooling, Peyronel et al.

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[74] determined different values for the parameters P and Rg.

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Smooth CNPs were found for systems with tristearin (SSS) in triolein (OOO), and SSS in Shea butter and OOO, therefore, a P1 value of 4 was fixed for these systems. On the other

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hand, CNPs with rough surface (|P1| < 4) were observed in systems with partially hydrogenated canola oil (PHCO) which is a mixture of SSS, SSP (stearin-stearin-palmitin) in

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OOO, PPS and SS_C20:0. Lastly, CNPs coated with oil (|P1| > 4) were found in fats with TAGs that contain polyunsaturated fatty acids such as that in SSS with cotton seed oil, which

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contains substantial amounts of linoleic acid (C18:2), and OOO. Differences were further observed in other parameters such as Rg1, P2, Rg2 and P3 [67].

3.2 Effect of cooling rate and crystallization temperature In most fat systems, the cooling rate is controlled so as to engineer desirable fat crystal structures (polymorphism and crystal size). In general, when crystallizing fats under fast cooling rates, the least stable polymorphic form, α, is formed while at very slow cooling rates, the more stable polymorphic forms (βʹ, β) are formed [36,40]. Independently, at the mesoscale, fast cooling results in the formation of multiple nucleation sites, which grow into

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ACCEPTED MANUSCRIPT numerous small crystals, while at slow cooling rates, nucleation proceeds slowly which allows for increased crystal growth and therefore a smaller amount of large crystals [42].

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At the nanoscale, Acevedo and Marangoni [61] found that subjecting blends of FHCO and

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HOSO to two different cooling rates - 1 and 10ºC/min resulted in CNPs that are large and

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small, respectively. Figure 9a shows CNPs extracted from a 1:1 mixture of FHCO: HOSO that was cooled slowly while Figure 9b shows CNPs extracted from the same mixture when

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it was cooled rapidly.

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Using USAXS, the effect of cooling rate on CNP aggregates was also investigated by subjecting different fats to slow (0.5 ºC/min) and fast cooling (30 ºC/min) [55]. The

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parameter P2 was emphasized in these studies. It was found that under fast cooling, P2 is equal to 1, which means that the CNPs have aggregated into cylindrical structures (i.e.,

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TAGwoods). On the other hand, under slow cooling, P2 values of 1.7 to 2.1 indicate that the CNPs or TAGwoods have aggregated via diffusion-limited cluster-cluster aggregation (DLCA) followed by reaction-limited cluster-cluster aggregation (RLCA).

3.3. Effect of shear Shear is often applied to the processing of fat-rich products such as chocolate, margarine, spreads and butter to improve their sensory attributes. Shear, in the form of mixing or agitation, improves heat transfer and nucleation, and imparts homogeneity to the final product. Many authors have described the effects of shear on fat crystallization, especially on cocoa butter [18,82]. These studies showed that high shear rates accelerate the phase 14

ACCEPTED MANUSCRIPT transition from less stable to more stable polymorphic forms in different edible fats. This acceleration in the rate of polymorphic transformation is achieved by reducing the activation

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energy for the phase transformation via shear [18,45,83,84]. Furthermore, at the mesoscale,

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smaller crystals are often observed when shear or agitation is applied during the

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crystallization process [44,80,85,86].

At the nanoscale, Acevedo and Marangoni [64,87] found that shear-dependent behavior was

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characterized by a critical laminar shear value of 300 s-1. At and above this shear rate, the

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CNPs exhibited decreased lengths, widths and thicknesses, relative to their non-sheared counterparts. This effect is independent of their solid mass fraction. This was also observed

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in cocoa butter, where the application of high laminar shear rates (340 s-1) resulted in smaller

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crystalline nanoplatelets in addition to a narrower size distribution [63,88]. This observation

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of smaller nanoplatelets correlates well with the smaller crystals observed using PLM. On the other hand, at low and intermediate shear rates (30 and 240 s-1), nanoplatelets exhibited larger widths and lengths than the non-sheared samples, although the platelet thickness decreased [64,87].

When subjected to turbulent shear fields inside a scraped surface heat exchanger (SSHE), Acevedo and Marangoni [89] showed that at low shear rates of 25 s-1, larger and more elongated nanoplatelets are formed in blends of fully hydrogenated soybean oil (FHSO) and liquid soybean oil (SO). Relative to static crystallization, a two-fold increase in length was observed, however, no significant change was observed in the width and thicknesses of the crystalline nanoplatelets [89].

3.5. Effect of emulsifier addition 15

ACCEPTED MANUSCRIPT Emulsifiers are usually added to food to stabilize oil-in-water (O/W) emulsions. However, over the years, the use of emulsifiers as crystal modifiers in fats has also been studied.

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Emulsifiers have been found to enhance or retard nucleation, crystal growth, and/or

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polymorphic transitions, depending on how well they can be integrated into the TAG lamella

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[78,90–94].

At the nanoscale, Acevedo and Marangoni [95] found that the addition of emulsifiers known

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to enhance nucleation and crystal growth, also increased the size of the nanoplatelets.

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4. Using the nanoscale structure to explain the macro properties of fat

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4.1. Oil-binding capacity

One of the key functionalities of fats is its oil-binding capacity (OBC). The fat crystal

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network formed by TAGs is capable of binding large amounts of oil in its interstitial spaces. The inclusion of oil in an otherwise solid fat lends it plasticity, which is also important for the functionality of the fat. OBC is usually characterized by the amount of oil lost after subjecting the fat to extreme conditions meant to remove oil. These include centrifugation, high temperatures (below melting) or long storage times [64,95–97]. Two mechanisms have been proposed to explain the OBC of fat crystal networks. In the first mechanism, liquid oil is retained by the fat crystal network via capillary forces and physical barriers (i.e., oil is surrounded by the crystal network). In the second mechanism, liquid oil is physically adsorbed onto the solid surface of the crystalline nanoplatelets [14,98]. This is further complicated by the fact that the structure of fats, as discussed above, is greatly affected by

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ACCEPTED MANUSCRIPT various processing conditions which, in turn, affect their oil binding capacity [64,87,95,96,99].

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Polymorphism was found to have no effect on the OBC of fat crystal networks. On the other

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hand, at the micro-/mesoscale structural level, larger crystal diameters were found to increase

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the rate of oil loss [99]. This was also supported by Marty & Marangoni (2009) [100] who found, in studies of oil migration through confections, that larger crystals of cocoa butter

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were associated with higher matrix permeability, and therefore, increased oil loss.

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At the nanoscale structural level, it was found that nanoplatelet size is closely correlated to the OBC of the material [64]. An agreement was found between the micro-/mesoscale and

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nanoscale observations wherein larger crystalline nanoplatelet size was correlated with higher permeability and therefore increased ease of oil migration [64,95]. In these

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experiments, varying the nanoplatelet sizes was achieved via the application of shear. As discussed in the previous section, a critical laminar shear (300 s-1) was needed before a significant decrease in nanoplatelet size can be observed. However, as discussed by these authors, high shear rate is accompanied by damage to the fat crystal network such that the OBC is lowered [64,97].

Using atomic-scale molecular dynamics (AMD) to study model TAG systems, Razul et al. [98] and Macdougall et al. [14] found that the surface properties of CNPs also affected their OBC. They found that oil entrapped between hard spheres (in this case CNPs composed of SSS) resulted in oil expulsion, and therefore, low OBC. On the other hand, soft spheres (CNPs, with a layer of oil composed of mixtures of heterogenous TAGs, e.g. olein, elaidin), show increased OBC. 17

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4.2. Rheological properties As a food ingredient, fats provide essential functionality such as spreadability, melting

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properties and a desirable mouthfeel. Several factors have been shown to affect the

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mechanical properties of fat crystals. These include SFC, polymorphism, particle size and

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interactions and crystal habit [9,12]. An important property of fat crystal networks that aid in understanding their observed rheological properties is their fractal nature [9,12,30,48,101–

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103]. With the imaging and characterization of CNPs, the theory that large polycrystalline aggregates are formed from smaller repeating primary units becomes tenable [64,102,103].

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The assembly of smaller CNPs into larger aggregates allows the description of some rheological parameters, such as elastic modulus, as a function of fractal dimension (i.e., how

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these particles are arranged or distributed in space) [60,104,105]. A quantitative description of the structure of aggregates (i.e., mesocrystals) was described by the fractal dimension, D, which quantifies the way in which the mass, M, of a cluster increases with its size R, M ~ RD [106]. The elastic properties of fat crystal networks was then related to the fractal dimension through a power law, Gʹ ~ Φ , where Gʹ is the elastic shear modulus, Φ is the particle volume fraction (often taken to be equivalent to the SFC/100), measured using pulsed nuclear magnetic resonance (NMR) and the exponent  depends on the fractal dimension [107]. These relationships were further expanded through the use of the theory obtained from studying the scaling behavior of the elastic properties of colloidal gels [108]. Using the “weak-link regime” developed by Shih et al. [108], Marangoni and Rousseau [58] were able to quantify the microstructure of fat crystal 18

ACCEPTED MANUSCRIPT networks by measuring the SFC and Gʹ of different fat systems. The weak link regime is usually observed in systems with high SFC or high volume fraction and is given by:

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d 2

(4)

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K ~  d D

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where K is the elastic constant of the system,  is particle concentration, d is the embedding Euclidean dimension (usually 3), and D is the fractal dimension. The exponent term is

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equivalent to m.

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D was calculated by plotting the natural logarithm of SFC and Gʹ: log G '    log SFC

(5)

TE

D

the slope of the line () was obtained via linear regression and was related to the fractal

AC CE P

dimension of the crystal network, assuming a weak-link regime:



d 2 d D

(6)

This formulation was the basis for a series of experiments performed by Narine and Marangoni [16,59] and Awad et al. [109] where they used the particle (Df) and box counting (Db) methods for the determination of fractal dimension on images obtained via PLM to develop a model that describes the rheological properties of fats on the basis of microstructural features. At the mesoscale structural level, larger crystals have been associated with softness and spreadability, while smaller crystals are associated with a harder texture and lower spreadability. Furthermore, the shape of the crystals also influences the functionality of the fat [12,17]. These results correlated well with the predictions made using

19

ACCEPTED MANUSCRIPT the calculated fractal dimensions [16,59,109]. Tang and co-workers then followed up these works by showing the microstructural basis for Df, Db, and D through modeling and

PT

computer simulations [103,110–112]. On the other hand, in terms of polymorphism, β

RI

crystals were found to cause discontinuities in the crystal network, and therefore affect

SC

hardness [113]. However, whether or not polymorphism affects the rheological properties of fats is still in question. These properties of fats highlight the importance of interactions

NU

between particles, such as when there is a high surface area for interaction (e.g. smaller

MA

mesocrystals or compact packing), a harder material is formed while a softer, more spreadable product is formed when there are less intercrystalline interactions [12,114].

D

At the nanoscale, an inverse relationship was found between nanoplatelet size and both the

TE

storage moduli (Gʹ) and yield stress (σ*) [53,61,89]. That is, the smaller the nanoplatelet, the

AC CE P

stronger the network formed (as evidenced by a high storage modulus and yield stress), which is in agreement with previous work in fat rheology [7,17,30,42]. These works also highlighted the effect of shear on the rheological properties of fats, where it was found that high shear rates resulted in the disruption of the fat crystal network, resulting in a softer material [45,53,61,89,97]. These results were explained by Acevedo et al. [53] based on the model formulated by Marangoni and Rogers [60]: 6  d  Df a 1

 

(7)

where the yield stress σ∗ is a function of the crystal-melt interfacial tension (δ), a is the primary particle (or primary crystal) diameter, Φ is the volume fraction of solids (=SFC/100),

20

ACCEPTED MANUSCRIPT d is the Euclidean dimension of the embedding space and Df is the fractal dimension of the fat crystal network.

PT

Given the recent findings that CNPs constitute the primary particles in fat crystal networks,

RI

the parameter a in Equation 7 can be re-interpreted to be the equivalent diameter of CNPs,

SC

which can be determined via USAXS analysis. As mentioned above, parameter P, which describes the CNP aggregates examined using USAXS, has been correlated with the fractal

D

5. Epitaxial Engineering of CNPs

MA

NU

dimension, which can be used to predict the rheological behavior of fats [57,67,74].

TE

Nanoengineering of fat crystal networks through manipulation of the epitaxial stacking of

AC CE P

CNPs is seen as a potential direction for future investigations. As described in previous sections of this review, the surface properties of CNPs greatly affect their functionality and the way they stack epitaxially to form crystalline domains. These can then affect the properties of larger CNP aggregates (micro- or mesostructures) which can impact the macroscopic properties of fat crystal networks. With the use of surface-active molecules such as emulsifiers, the surface energy of TAG CNPs can be modified. As described by Acevedo and Marangoni [95], the addition of specific emulsifiers, in combination with specific crystallization conditions under large temperature gradients and high shear, results in a controlled modulation of the surface energy of CNPs. By changing the nanoplatelets’ surface energy using various emulsifiers, the growth of molecular lamellae can be conducted in a controlled fashion. Results in our lab show a good correlation between surface energy and

21

ACCEPTED MANUSCRIPT crystalline domain size (number of lamellae) (Figure 10). That is, the higher the surface energy, the larger the domain size and the greater the number of lamellas that can be stacked.

PT

A major challenge in this study is the difficulty in the quantification of the surface energy of

RI

CNPs after the addition of various emulsifiers (e.g., glyceryl monostearate (GMS), sodium

SC

stearoyl lactylate (SSL) and glyceryl monopalmitate (GMP)). In order to do this, we propose a model based on the modification of the Gibbs-Thomson equation that assumes that the

NU

epitaxial growth of CNPs comes about from a 2D nucleation with the formation of a circular

MA

island of monolayer material on a surface [115–118], given by:  2 r h VM

(8)

D

Gn  ( r 2  2 rh) 

TE

where Gn is the free energy of nucleation, r corresponds to the radius of the island, while h

AC CE P

corresponds to the height of this nucleating monolayer “island”,  is the solid-liquid (crystalmelt) interfacial tension,  is the chemical potential difference between the solid and liquid phases, and VM is the molar volume (=density/MW) of the solid. Here we consider only the extra surface area generated by this nucleation event, hence only half of the surface area of the disc “face” is considered in the treatment. Minimization of the free energy of nucleation with respect to the size of such disc-shaped nucleus,

d (Gn )  0 , allows for the dr

determination of the critical minimal size of a nucleus above which the free energy of nucleation decreases (nucleation process becomes more spontaneous). At this point the free energy of nucleation increases due to increases in surface area are offset by free energy of nucleation decreases due to reductions in the chemical potential of the system. This critical radius could then be reintroduced in to Equation 8 to obtain an expression for the free energy 22

ACCEPTED MANUSCRIPT of activation for nucleation, which in turn could be used to determine a nucleation rate. Replacement of  with (H f / T f )T , which is the chemical potential of a melt rather than a

RI

H f T r  h  T f VM r  h

(9)

SC



PT

solution, and solving for the surface energy yields:

NU

Assuming that the diameter of the nucleating circular island is much larger than the height of the monolayer, i.e., if r>>>h, then this expression simplifies to

MA

H f T T f VM

h

(10)

D



(001) plane, d

(001).

TE

For this case, h would correspond, by necessity, to the lattice parameter, or d-spacing, of the The parameters Hf and Tf correspond, respectively, to the molar

AC CE P

enthalpy and temperature of fusion of the solid, while T corresponds to the degree of undercooling of a substance prior to crystallization (T =T-Tf). The molar volume, VM can also be easily calculated from the material’s density. Thus, from knowledge of the melting behavior, density and solid-state molecular dimensions, it is possible to determine the solidliquid interfacial tension, or surface energy, of a TAG crystalline surface. Simulations were performed and these were supported by experimental results using 30% mass fraction of fully hydrogenated soybean oil in 70% soybean oil added with various emulsifiers and crystallized under different conditions. For the determination of the surface energy of the triclinic polymorph of fully hydrogenated soybean oil (70% SSS, 30% distearylpalmitate), crystallized as a 30% solution in soybean oil at T=303.15 K, we determined experimentally

23

ACCEPTED MANUSCRIPT d(001)=4.08 nm (s.e.=0.086 nm, n=5), VM=9.24x10-4 m3/mol (density900 kg/m3, MW=891.48 g/mol), Hf=187 kJ/mol (s.e.=2.11 kJ/mol, n=17), Tf=333.1 K (s.e.=0.47 K, n=17), as

PT

described in Acevedo and Marangoni [95]. The values reported correspond to means and

RI

standard errors (standard deviation/√𝑛) of n separate experiments. Typical powder X-ray

SC

diffraction patterns for the triclinic polymorph of fully hydrogenated soybean oil are shown in Figure 11a. The lamellar size was estimated from the summit of the reflection peak in the

NU

SAXS region (Figure 11b). The melting of the materials was characterized using differential

MA

scanning calorimetry (Figure 11c). Using Equation 9, we then determined  = 77.0 mJ/m2. This value is higher than values reported in the literature for triglycerides [119].

TE

D

In order to further explore the predictions of this model, we simulated changes in the interfacial energy as a function of the circular island radius (Figure 12) using the parameters

AC CE P

listed above. It was interesting to notice the strong dependence of the interfacial energy on the size of the nucleus on the surface. The smaller the size of the island, the lower the interfacial energy and thus the easier it would be to nucleate material on it. Interfacial energy values predicted here agreed closely with literature values when the diameter of the nucleus was similar to the height of the monolayer (h), i.e., at r=0.5 h, the diameter of the island would be about 4-5 nm for 18-carbon TAGs. At this size, the interfacial tension would be about 10 mJ/m2 [119]. The control of epitaxial growth of TAG nanoplatelets opens the door for the rational design of TAG nanocrystals with epitaxial layers of different compositions, i.e., TAG heterostructures. A similar strategy could work with other materials, like alkanes or fatty acid-metal complexes.

This new crystal nanofabrication strategy will help improve 24

ACCEPTED MANUSCRIPT macroscopic functionality of these materials, including melting behavior, tribological

PT

properties, electrical conductivity and mechanical properties [9].

SC

RI

6. Conclusion

Characterization of the nanostructure of fat crystal networks has provided a new

NU

understanding of the overall structure of fats. With the development of computer simulations and modeling of CNP aggregations, electron microscopy, and the use of USAXS, the

MA

nanoscale structural level is now accessible to study. Furthermore, as shown in previous

D

works, the properties of these CNPs can be modified through the control of different

TE

variables such as chemical composition (e.g. addition of emulsifiers), cooling rate and external shear fields. These advances allow the methodical engineering of the fat crystal

products.

AC CE P

structure with an aim towards improving the functional properties of fats and fat-containing

7. Acknowledgements

This research has been funded by the Natural Sciences and Engineering Research Council of Canada grant 05715-2015.

25

ACCEPTED MANUSCRIPT

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Figure Legends

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Figure 1. Structural hierarchy in a polycrystalline triacylglycerol crystal network: a)

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homoepitaxial growth of near 2-dimensional triacylglycerol crystalline lamellae; b)

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cryogenic transmission electron (cryo-TEM) micrograph of crystalline nanoplatelets (CNPs); and c) large mesocrystals imaged using polarized light microscopy and phase contrast

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microscopy.

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Figure 2. a) Three major subcell structures observed in fats: α - hexagonal, βʹ - orthorhombic perpendicular and β – triclinic. b) Lamellar stacking of triacylglycerols in different chain

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length configurations: 2L – double and 3L - triple chain lengths. Figure 3. Polarized light (PLM) micrographs of binary and ternary mixtures of milk fat

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fractions crystallized isothermally at different temperatures: a) 90% high melting fraction (HMF): 10% low melting fraction (LMF) at 10 ºC; b) 80% HMF: 10% middle melting fraction (MMF): 10% LMF at 15 ºC; c) 10 % HMF: 60% MMF : 10% LMF at 20ºC and d) 10% HMF: 70 % MMF: 20% LMF at 22.5 ºC. Scale bars correspond to 100 µm. Figure 4. a) Cross-sectional view of a tristearin crystalline nanoplatelet (CNP) extracted using cold isobutanol and imaged using cryogenic transmission electron microscopy (cryoTEM). b) Fast Fourier Transform of the image shown in panel (a) displaying a characteristic frequency in the orientation corresponding to the stacking of triglyceride lamellae. This point in the frequency domain (inverse space) was transformed back to real space using an inverse FFT routine and the value of 4.53 nm shown in the FFT image corresponds to the

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c) Powder X-ray diffraction pattern of neat tristearin

showing the (001) plane reflection in the small angle region at 4.57 nm. Both cryo-TEM and

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powder XRD yielded the same value for the lattice parameter that characterizes the average

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dimension of epitaxially stacked TAG lamellae.

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Figure 5. Ultra small-angle x-ray scattering (USAXS) pattern of shea butter with

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corresponding slopes or Porod exponents, P and radius of gyration, Rg. Figure 6. Cryogenic transmission electron micrograph (cryo-TEM) of crystalline

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nanoplatelets (CNPs) stacked in a cylindrical manner, termed as TAGwood.

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Figure 7. Cryogenic transmission electron micrographs (cryo-TEM) of crystalline

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nanoplatelets (CNPs) extracted from blends of fully hydrogenated canola oil (FHCO) in high

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oleic soybean oil (HOSO) with increasing concentrations of FHCO – a) 30% b) 50% and c) 100%. Adapted with permission from N.C. Acevedo, A.G. Marangoni, Characterization of the Nanoscale in Triacylglycerol Crystal Networks, Cryst. Growth Des. 10 (2010) 3334– 3339. Copyright 2010 American Chemical Society. Figure 8. Cryogenic transmission electron micrographs (cryo-TEM) of crystalline nanoplatelets (CNPs) extracted from cocoa butter. Scale bars correspond to 1 µm (left and middle) and 2 µm (right),

Adapted with permission from F. Maleky, A.K. Smith, A.

Marangoni, Laminar shear effects on crystalline alignments and nanostructure of a triacylglycerol crystal network, Cryst. Growth Des. 11 (2011) 2335–2345. Copyright 2011 American Chemical Society.

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oleic soybean oil (HOSO) cooled at a) 1 ºC/min and b) 10 ºC/min.

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Figure 10. Effect of surfactant addition on the surface energy of triacylglycerol crystalline

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nanoplatelets. a & b) Two separate experiments displaying changes in crystalline domain

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size (triglyceride nanoplatelet thickness) for tristearin co-crystallized with a series of surfaceactive molecules; c & d) corresponding changes in the TAG lamellae per nanoplatelet .

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Figure 11. Solid state structural and thermal characteristics of FHSBO (fully hydrogenated soybean oil). a) Wide-angle powder x-ray diffraction spectrum of FHSBO oil in the beta

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polymorphic form; b) small-angle powder x-ray diffraction spectrum of fully FHSBO showing the (001) plane reflection, with its characteristic position and full width half

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maximum; and c) differential scanning calorimetric trace of FHSBO in the beta polymorphic form showing the peak melting temperature and the melting enthalpy of the material. Figure 12. Simulation of changes in interfacial energy () as a function of the radius of the disc-shaped nucleus forming on a flat surface. Here, h represents the height of a monolayer of triacylglycerols (4.08nm), which was fixed as constant, while the radius of the island nucleus (r) was varied. Values for the other constants are defined in the text. Simulation was carried out for 30% fully hydrogenated soybean oil in soybean oil. The same trends are observed for the other systems.

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Graphical abstract

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