Computational approach for structure generation of anisotropic particles (CASGAP) with targeted distributions of particle design and orientational order

Abstract

The macroscopic properties of materials are governed by their microscopic structure which depends on the materials’ composition (i.e., building blocks) and processing conditions. In many classes of synthetic, bioinspired, or...

Computational Reverse Engineering Analysis of the Scattering Experiment Method for Interpretation of 2D Small-Angle Scattering Profiles (CREASE-2D)

“…These structural descriptors serve as the structural features for use in this development of the CREASE-2D workflow. While the detailed description of these structural features can be found in the original manuscript, 30 we review some relevant details below: , respectively. The detailed information about their structural features is provided in Table 1.…”

“…We would like to emphasize that our choice of the model system with spheroidal particles and the variation of relevant structural features was motivated by the convenience of generating structures using the existing CASGAP method. 30 To extend CREASE-2D to interpret 2D scattering profiles from other soft material systems (e.g., processed polymers with orientational alignment or structures accessed during rheology in Rheo-SANS experiments), the user should follow similar steps as described for the model system: (1) identify the structural features of relevance (e.g., orientational order parameters, and distribution of domain sizes and shapes);…”

“…To demonstrate our choices of structural features for a representative example of soft materials with structural anisotropy, we consider a model system of spheroidal particles with well-defined distributions of shapes, sizes, and orientations (shown schematically in Figure ), along with variations in the particles’ packing fractions in the material. Generation of such 3D structures is facilitated by our recently developed (open source) computational method called CASGAP (computational approach for structure generation of anisotropic particles) . In the original manuscript, we demonstrated the versatility of the CASGAP method to generate 3D structures for user-provided distribution of particle sizes, shapes, and orientations at or close to the target volume fraction.…”

“…These structural descriptors serve as the structural features for use in this development of the CREASE-2D workflow. While the detailed description of these structural features can be found in the original manuscript, we review some relevant details below: The particle sizes and shapes are expressed by the spheroidal volumetric radius R = a 2 c 3 and the spheroidal aspect ratio γ = c / a , where a and c are the lengths of the semiminor and semimajor axes of the spheroid, respectively. As done in the original manuscript, the variations in the size and shape are modeled by a log–normal distribution, each with their means ( R μ , γ μ ) and standard deviations ( R σ , γ σ ).…”

“…While the detailed description of these structural features can be found in the original manuscript, we review some relevant details below: The particle sizes and shapes are expressed by the spheroidal volumetric radius R = a 2 c 3 and the spheroidal aspect ratio γ = c / a , where a and c are the lengths of the semiminor and semimajor axes of the spheroid, respectively. As done in the original manuscript, the variations in the size and shape are modeled by a log–normal distribution, each with their means ( R μ , γ μ ) and standard deviations ( R σ , γ σ ). These quantities provide us with the first four structural features for CREASE-2D. The orientation in the structure is quantified by a 3D vector pointing along the major axis V of the spheroid.…”