Bayesian estimations of orientation distribution functions from small-angle scattering enable direct prediction of mechanical stress in anisotropic materials

Corona, Patrick T.; Silmore, Kevin S.; Adkins, Raymond; Lång, Christian; Lettinga, M. P.; Swan, James W.; Leal, L. Gary; Helgeson, Matthew E.

doi:10.1103/physrevmaterials.5.065601

Cited by 9 publications

(9 citation statements)

References 70 publications

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“…Ongoing developments in community-driven software tools such as SasView (www.sasview.org), computational power, and recent statistical methods to determine orientation distribution functions from anisotropic scattering data [205] will help the broader scattering community extract more structural information from two-dimensional scattering projections and with different applied flow fields. Advances in computing, machine learning algorithms, AI pattern recognition, and 3D data visualisation will help meet challenges in extracting, analyzing, and presenting data-rich Rheo-SANS measurements.…”

Section: Advances In Science and Technology To Meet Challengesmentioning

confidence: 99%

Soft matter roadmap^*

Barrat,

Del Gado,

Egelhaaf

et al. 2023

J. Phys. Mater.

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Soft materials are usually defined as materials made of mesoscopic entities, often self-organized, sensitive to thermal fluctuations and to weak perturbations. Archetypal examples are colloids, polymers, amphiphiles, liquid crystals, foams. The importance of soft materials in everyday commodity products, as well as in technological applications, is enormous, and controlling or improving their properties is the focus of many efforts. From a fundamental perspective, the possibility of manipulating soft material properties, by tuning interactions between constituents and by applying external perturbations, gives rise to an almost unlimited variety in physical properties. Together with the relative ease to observe and characterize them, this renders soft matter systems powerful model systems to investigate statistical physics phenomena, many of them relevant as well to hard condensed matter systems. Understanding the emerging properties from mesoscale constituents still poses enormous challenges, which have stimulated a wealth of new experimental approaches, including the synthesis of new systems with, e.g., tailored self-assembling properties, or novel experimental techniques in imaging, scattering or rheology. Theoretical and numerical methods, and coarse-grained models, have become central to predict physical properties of soft materials, while computational approaches that also use machine learning tools are playing a progressively major role in many investigations.This roadmap paper intends to give a broad overview of recent and possible future activities in the field of soft materials, with experts covering various developments and challenges in material synthesis and characterization, instrumental, simulation and theoretical methods as well as general concepts.

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Section: Advances In Science and Technology To Meet Challengesmentioning

confidence: 99%

Soft matter roadmap^*

Barrat,

Del Gado,

Egelhaaf

et al. 2023

J. Phys. Mater.

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“…This expression can be generalized to arbitrary coordinate systems for q, involving previously published procedures. 40,41 With this expression for the scattering from an isolated cylindrical rod with a fixed orientation, the scattering intensity for a dilute ensemble of noninteracting rods [for which the structure factor S(q) = 1 in eq 1] with a general orientation probability distribution function (OPDF) ψ(θ, ϕ) is…”

Section: ■ Theorymentioning

confidence: 99%

Self-Consistent Connected-Rod Model for Small-Angle Scattering from Deformed Semiflexible Chains in Flow

Zhang,

Smith,

Corona

et al. 2023

Macromolecules

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Quantifying the microstructure and dynamics under nonlinear deformations is critical for designing flow processes and rheological models for semiflexible polymers and molecular assemblies. Although flow-small angle neutron and X-ray scattering (flow-SANS/SAXS) are suitable for studying how a material's microstructure deforms in flow, scattering models to describe the molecular anisotropy of semiflexible chains in flow have yet to be developed due to the challenge of describing the coupled effects of global (chain-level) deformation and local (segment-level) orientation. To address this challenge, we develop a detailed scattering model for anisotropic semiflexible chains based on a connected-rod chain model that incorporates an orientation distribution for the segments that is thermodynamically self-consistent with the overall stretch and orientation of the chain. We validate the model by comparing its predictions with flow-SANS experiments on wormlike surfactant micelles and find excellent quantitative agreement for the shape of the scattering anisotropy between experiment and simulation across a large range of shear rates. The development of a thermodynamically consistent scattering model for semiflexible chains in flow opens up new possibilities for obtaining microstructural information from flow-SANS/SAXS experiments that can be compared with molecular theories and simulations of flowing polymers and complex fluids.

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“…It is, in fact, nontrivial to reconstruct the complete three-dimensional orientation distribution of CNFs in flow from scattering data; recent progress demonstrate that scattering from multiple directions is necessary to reconstruct the orientation state correctly. 16 In complex flows where the orientation state varies in space, this quickly becomes overwhelming. Tomographic methods could be considered, but the requirements in terms of experiment design and measurement time needed make them hard to use for in situ measurements in complex flows or extensive parameter variations.…”

Section: Introductionmentioning

confidence: 99%

“…In this context, additional challenges present themselves. It is, in fact, nontrivial to reconstruct the complete three-dimensional orientation distribution of CNFs in flow from scattering data; recent progress demonstrate that scattering from multiple directions is necessary to reconstruct the orientation state correctly . In complex flows where the orientation state varies in space, this quickly becomes overwhelming.…”

Section: Introductionmentioning

confidence: 99%

Nanofibril Alignment during Assembly Revealed by an X-ray Scattering-Based Digital Twin

et al. 2022

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The nanostructure, primarily particle orientation, controls mechanical and functional (e.g., mouthfeel, cell compatibility, optical, morphing) properties when macroscopic materials are assembled from nanofibrils. Understanding and controlling the nanostructure is therefore an important key for the continued development of nanotechnology. We merge recent developments in the assembly of biological nanofibrils, X-ray diffraction orientation measurements, and computational fluid dynamics of complex flows. The result is a digital twin, which reveals the complete particle orientation in complex and transient flow situations, in particular the local alignment and spatial variation of the orientation distributions of different length fractions, both along the process and over a specific cross section. The methodology forms a necessary foundation for analysis and optimization of assembly involving anisotropic particles. Furthermore, it provides a bridge between advanced in operandi measurements of nanostructures and phenomena such as transitions between liquid crystal states and in silico studies of particle interactions and agglomeration.

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Bayesian estimations of orientation distribution functions from small-angle scattering enable direct prediction of mechanical stress in anisotropic materials

Cited by 9 publications

References 70 publications

Soft matter roadmap^*

Soft matter roadmap^*

Self-Consistent Connected-Rod Model for Small-Angle Scattering from Deformed Semiflexible Chains in Flow

Nanofibril Alignment during Assembly Revealed by an X-ray Scattering-Based Digital Twin

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Bayesian estimations of orientation distribution functions from small-angle scattering enable direct prediction of mechanical stress in anisotropic materials

Cited by 9 publications

References 70 publications

Soft matter roadmap*

Soft matter roadmap*

Self-Consistent Connected-Rod Model for Small-Angle Scattering from Deformed Semiflexible Chains in Flow

Nanofibril Alignment during Assembly Revealed by an X-ray Scattering-Based Digital Twin

Contact Info

Product

Resources

About

Soft matter roadmap^*

Soft matter roadmap^*