Development of a Third Generation Snack of Rice Starch Enriched with Nopal Flour (Opuntia ficus indica).

This study aimed to obtain a third-generation snack from native rice starch (NS), rice starch modified by extrusion (MS), nopal flour (NF) and xanthan gum (XG). These raw materials were characterized by proximal analysis, pH, particle size distribution, water absorption index (WAI) and water solubility index (WSI), degree of substitution (DS), differential scanning calorimetry (DSC), rheology, Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM). The analysis of the response variables in the nine formulations of the snack: expansion index (EI), apparent density (AD), hardness (H), luminosity (L*) and tendency to green-red (a*), was performed through a composite central design (CCD), the selected formulations were characterized by SEM. Results showed an increase in WAI, 4.69 ± 0.04, and WSI, 12.61 ± 0.10, for MS, higher than NS values due to chemical modification. According to the color analysis the NF obtained a value of 60.73 ± 0.008 in L* and -6.51 ± 0.004 in a* with green tendency. The DS value obtained was 0.09 ± 0.005, being within the FDA's permissible range for food use. By FTIR analysis, the acetyl group was corroborated. Finally, employing microwave cooking, snacks made from NS with concentrations of NF (5%) and XG (0%) obtained the highest EI value, 4.47, as well the low Dap and D value (0.37 g/cm3, 2.25 N, respectively), corroborated by SEM analysis.

Development of an Expanded Snack of Rice Starch Enriched with Amaranth by Extrusion Process.

This study aimed to obtain a second-generation snack by extrusion from the by-product of rice milling enriched with amaranth. The raw material used was amaranth flour (AF), rice starch (NS) and modified rice starch (MS), which were evaluated by the analysis of substitution degree (SD), differential scanning calorimetry (DSC), viscosity (RVA), Fourier transform infrared spectroscopy (FT-IR) and X-ray diffraction (XRD). The snacks were expanded by extrusion and microwave oven, as a reference method. The samples were evaluated in hardness (D), expansion index (EI), apparent density (DAP), and protein content (P). Afterward, the optimized samples were evaluated by scanning electron microscopy (SEM) and resistant starch (RS). During the thermal characterization, a clear trend in the decrement in gelatinization temperatures was observed (78.35 to 63.90 °C in NS and MS respectively). The curves obtained in RVA analyses showed typical behavior of native (6.35 Pa.s) and extruded starches (2.88 Pa.s), with a significant decrease in viscosity peak. Through the analysis of FT-IR, the introduction of the functional acetyl group (stretching at a wavelength of 1735 cm-1) was corroborated. Snack samples results showed a maximum hardness in MS, with a value of 121 N, and the NS (100%) presented the highest EI value (1.41). The lowest DAP values were obtained for the MS (0.48 g/cm3, 100%) and AF (0.49 g/cm3, 100%) samples. P increased to a higher concentration of AF. In the optimum formulation, the SEM image showed that the expanded microwave sample increased the porosity and obtained an RS value of 8.2%. The formulation obtained in the present study presents high characteristics to be used in the development of a healthy snack.

Mesoscopic study of the ternary phase diagram of the PS-PB-PtBMA triblock copolymer: modification of the phase structure by the composition effect.

We explored in detail the ordered nanostructures and the ternary phase diagram of the polystyrene-polybutadiene-poly(tert-butyl methacrylate) (PS-PB-PtBMA) triblock copolymer via dissipative particle dynamics (DPD) simulations and coarse-grained models. The mesoscopic simulations show that the PS-PB-PtBMA copolymer in the bulk state can generate eight equilibrium phase regions with well-defined morphologies such as core-shell variations of spheres, cylinders, perforated layers, lamellar, gyroid, as well as cylinder-in-lamella, spheres-in-lamella, and cylinders in hexagonal lattice. The ordered phases exhibit high dependence on the chemical nature and volume fraction, thus portraying specific composition regions with high thermodynamic stability over a ternary phase diagram. The ternary phase diagram, including all equilibrium and metastable nanostructures detected, is described, and analysed in this work in detail. Finally, our dynamic simulation outcomes agree with experimental results. Our aim is to contribute to the understanding of the relationship between block volume fractions and bulk morphologies in ternary polymer systems.

Self-organization process of ordered structures in linear and star poly(styrene)-poly(isoprene) block copolymers: Gaussian models and mesoscopic parameters of polymeric systems.

Mesoscopic simulations of linear and 3-arm star poly(styrene)-poly(isoprene) block copolymers was performed using a representation of the polymeric molecular structures by means of Gaussian models. The systems were represented by a group of spherical beads connected by harmonic springs; each bead corresponds to a segment of the block chain. The quantitative estimation for the bead-bead interaction of each system was calculated using a Flory-Huggins modified thermodynamical model. The Gaussian models together with dissipative particle dynamics (DPD) were employed to explore the self-organization process of ordered structures in these polymeric systems. These mesoscopic simulations for linear and 3-arm star block copolymers predict microphase separation, order-disorder transition, and self-assembly of the ordered structures with specific morphologies such as body-centered-cubic (BCC), hexagonal packed cylinders (HPC), hexagonal perforated layers (HPL), alternating lamellar (LAM), and ordered bicontinuous double diamond (OBDD) phases. The agreement between our simulations and experimental results validate the Gaussian chain models and mesoscopic parameters used for these polymers and allow describing complex macromolecular structures of soft condensed matter with large molecular weight at the statistical segment level.