scholarly journals Tracking the time evolution of soft matter systems via topological structural heterogeneity

2022 ◽  
Vol 3 (1) ◽  
Author(s):  
Ingrid Membrillo Solis ◽  
Tetiana Orlova ◽  
Karolina Bednarska ◽  
Piotr Lesiak ◽  
Tomasz R. Woliński ◽  
...  
Keyword(s):  
Time Evolution ◽  
Soft Matter ◽  
Structural Changes ◽  
Persistent Homology ◽  
Soft Materials ◽  
Structural Heterogeneity ◽  
Dynamical Behaviour ◽  
Topological Data Analysis ◽  
Analysis Tool ◽  
Wide Range

AbstractPersistent homology is an effective topological data analysis tool to quantify the structural and morphological features of soft materials, but so far it has not been used to characterise the dynamical behaviour of complex soft matter systems. Here, we introduce structural heterogeneity, a topological characteristic for semi-ordered materials that captures their degree of organisation at a mesoscopic level and tracks their time-evolution, ultimately detecting the order-disorder transition at the microscopic scale. We show that structural heterogeneity tracks structural changes in a liquid crystal nanocomposite, reveals the effect of confined geometry on the nematic-isotropic and isotropic-nematic phase transitions, and uncovers physical differences between these two processes. The system used in this work is representative of a class of composite nanomaterials, partially ordered and with complex structural and physical behaviour, where their precise characterisation poses significant challenges. Our developed analytic framework can provide both a qualitative and quantitative characterisation of the dynamical behaviour of a wide range of semi-ordered soft matter systems.

scholarly journals Mechanical Spectroscopy: Some Applications On Structural Changes And Relaxation Dynamics In Soft Matter

2015 ◽  
Vol 60 (3) ◽  
pp. 2077-2084
Author(s):  
Xuebang Wu ◽  
Changsong Liu
Keyword(s):  
Soft Matter ◽  
Structural Changes ◽  
Three Dimensional ◽  
Low Frequency ◽  
Soft Materials ◽  
Large Temperature ◽  
Relaxation Dynamics ◽  
Mechanical Spectroscopy ◽  
Frequency Scale ◽  
Wide Range

Abstract The general trend in soft matter is to study systems of increasing complexity covering a wide range in time and frequency. Mechanical spectroscopy is a powerful tool for understanding the structure and relaxation dynamics of these materials over a large temperature range and frequency scale. In this work, we collect a few recent applications using low-frequency mechanical spectroscopy for elucidating the structural changes and relaxation dynamics in soft matter, largely based on the author’s group. We illustrate the potential of mechanical spectroscopy with three kinds of soft materials: colloids, polymers and granular systems. Examples include structural changes in colloids, segmental relaxations in amorphous polymers, and resonant dissipation of grain chains in three-dimensional media. The present work shows that mechanical spectroscopy has been applied as a necessary and complementary tool to study the dynamics of such complex systems.

scholarly journals Persistent homology as a new method of the assessment of heart rate variability

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253851
Author(s):  
Grzegorz Graff ◽  
Beata Graff ◽  
Paweł Pilarczyk ◽  
Grzegorz Jabłoński ◽  
Dariusz Gąsecki ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Data Analysis ◽  
Persistent Homology ◽  
Assessment Tools ◽  
Topological Data Analysis ◽  
Topological Descriptors ◽  
Time Interval ◽  
Analysis Tool ◽  
Frequency Domain Methods

Heart rate variability (hrv) is a physiological phenomenon of the variation in the length of the time interval between consecutive heartbeats. In many cases it could be an indicator of the development of pathological states. The classical approach to the analysis of hrv includes time domain methods and frequency domain methods. However, attempts are still being made to define new and more effective hrv assessment tools. Persistent homology is a novel data analysis tool developed in the recent decades that is rooted at algebraic topology. The Topological Data Analysis (TDA) approach focuses on examining the shape of the data in terms of connectedness and holes, and has recently proved to be very effective in various fields of research. In this paper we propose the use of persistent homology to the hrv analysis. We recall selected topological descriptors used in the literature and we introduce some new topological descriptors that reflect the specificity of hrv, and we discuss their relation to the standard hrv measures. In particular, we show that this novel approach provides a collection of indices that might be at least as useful as the classical parameters in differentiating between series of beat-to-beat intervals (RR-intervals) in healthy subjects and patients suffering from a stroke episode.

scholarly journals A dynamically reprogrammable metasurface with self-evolving shape morphing

2021 ◽  
Author(s):  
Xiaoyue Ni ◽  
Yun Bai ◽  
Heling Wang ◽  
Yeguang Xue ◽  
Yuxin Pan ◽  
...  
Keyword(s):  
Flexible Electronics ◽  
Soft Matter ◽  
Response Times ◽  
Control Strategies ◽  
Soft Materials ◽  
Theoretical Models ◽  
Shape Morphing ◽  
Wide Range ◽  
Data Driven Approach ◽  
Actuation Scheme

Abstract Dynamic shape-morphing soft materials systems are ubiquitous in living organisms; they are also of rapidly increasing relevance to emerging technologies in soft machines1–4, flexible electronics5–7, and smart medicines8,9. Soft matter equipped with responsive components can switch between designed shapes or structures, but cannot support the types of dynamic morphing capabilities needed to reproduce natural, continuous processes of interest for many applications10–27. Challenges lie in the development of schemes to reprogram target shapes post fabrication, especially when complexities associated with the operating physics and disturbances from the environment can prohibit the use of deterministic theoretical models to guide inverse design and control strategies3,28–32. Here, we present a mechanical metasurface constructed from a matrix of filamentary metal traces, driven by reprogrammable, distributed Lorentz forces that follow from passage of electrical currents in the presence of a static magnetic field. The resulting system demonstrates complex, dynamic morphing capabilities with response times within 0.1 s. Implementing an in-situ stereo-imaging feedback strategy with a digitally controlled actuation scheme guided by an optimization algorithm, yields surfaces that can self-evolve into a wide range of 3-dimensional (3D) target shapes with high precision, including an ability to morph against extrinsic or intrinsic perturbations. These concepts support a data-driven approach to the design of dynamic, soft matter, with many unique characteristics.

scholarly journals Synchrotron X-ray Scattering techniques for soft matter industrial research and development

2014 ◽  
Vol 70 (a1) ◽  
pp. C1329-C1329
Author(s):  
Michael Sztucki ◽  
Manfred Burghammer ◽  
Oleg Konovalov ◽  
Edward Mitchell ◽  
Theyencheri Narayanan
Keyword(s):  
Soft Matter ◽  
State Of The Art ◽  
Soft Materials ◽  
Real Space ◽  
Consumer Products ◽  
Photon Flux ◽  
X Ray ◽  
X Ray Scattering ◽  
Wide Range ◽  
Ray Scattering

Consumer products based on soft matter technology often exhibit macroscopic properties which are strongly dependent on their micro- and nano-structures extending over multiple size scales. Synchrotron scattering techniques are ideally suited for probing these multilevel structures and deliver complementary and in some cases unique information as compared to real space methods like confocal microscopy, cryo-electron microscopy or atomic force microscopy. The European Synchrotron Radiation Facility (ESRF) is a world-leading synchrotron light source which operates several state-of-the-art instruments for the investigation of soft materials and offers expertise to academic and industrial users. Fast and flexible access for proprietary experiments with a modular, fine-tuned service is guaranteed. A range of dedicated sample environments which mimic industrial processing conditions are available. This presentation will illustrate the state-of-the-art performance of the following synchrotron scattering techniques by recent examples of industrial relevance. Simultaneous small and wide angle X-ray scattering (SAXS/WAXS) is a powerful method to determine the microstructure and phase behavior of multi-component systems like detergents, food products, pharmaceutical components, polymer composites, etc. The high photon flux translates to high throughput measurements, while the high degree of collimation and resolution permit to elucidate a wide range of length scales from a few Angstroms up to micron scale. Scanning microbeam SAXS/WAXS and single micro-crystal/fiber diffraction (µXRD) allows elucidating the local nanostructure of very small objects like micro-specimens of composite organic/inorganic materials, teeth, bones, micromechanical parts, polymer fibers, micro fluidics, etc. with micro/nanometric real space resolution. X-ray reflectivity (XR) and grazing incidence diffraction/scattering (GID /GISAXS) can reveal the nanoscale structure and complexity of nano-structured complex fluids at interfaces, organic films, biological membranes, etc.

scholarly journals Persistent Homology: Application To Monitoring Hydraulic Fracturing

2020 ◽  
Vol 23 (6) ◽  
pp. 1192-1212
Author(s):  
Kirill Yurevich Erofeev ◽  
Mansur Tagirovich Ziiatdinov ◽  
Evgenii Vladimirovich Mokshin
Keyword(s):  
Data Analysis ◽  
Hydraulic Fracturing ◽  
Topological Structure ◽  
Prior Information ◽  
Persistent Homology ◽  
Topological Data Analysis ◽  
Analysis Tool ◽  
Data Analysis Tool ◽  
Natural Way ◽  
Topological Data

Persistent homology is a topological data analysis tool which is reflecting changes in topological structure of data along its scale. Application of persistent homology to monitoring hydraulic fracturing which is allowing researchers to consider prior information in a natural way is given in the article

scholarly journals Persistent Homology Analysis of RNA

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Adane L. Mamuye ◽  
Matteo Rucco ◽  
Luca Tesei ◽  
Emanuela Merelli
Keyword(s):  
Data Analysis ◽  
Rna Folding ◽  
Persistent Homology ◽  
Betti Numbers ◽  
Structural Features ◽  
Topological Data Analysis ◽  
Analysis Tool ◽  
Global Features ◽  
Folding Space ◽  
Topological Data

AbstractTopological data analysis has been recently used to extract meaningful information frombiomolecules. Here we introduce the application of persistent homology, a topological data analysis tool, for computing persistent features (loops) of the RNA folding space. The scaffold of the RNA folding space is a complex graph from which the global features are extracted by completing the graph to a simplicial complex via the notion of clique and Vietoris-Rips complexes. The resulting simplicial complexes are characterised in terms of topological invariants, such as the number of holes in any dimension, i.e. Betti numbers. Our approach discovers persistent structural features, which are the set of smallest components to which the RNA folding space can be reduced. Thanks to this discovery, which in terms of data mining can be considered as a space dimension reduction, it is possible to extract a new insight that is crucial for understanding the mechanism of the RNA folding towards the optimal secondary structure. This structure is composed by the components discovered during the reduction step of the RNA folding space and is characterized by minimum free energy.

Plasma surface engineering for manmade soft materials: A review

2021 ◽  
Author(s):  
Dirk Hegemann ◽  
Sandra Gaiser
Keyword(s):  
Soft Matter ◽  
Surface Engineering ◽  
Aqueous Media ◽  
Dissimilar Materials ◽  
Surface Region ◽  
Soft Materials ◽  
Plasma Source ◽  
Plasma Surface ◽  
Wide Range ◽  
Potential Applications

Abstract Manmade soft materials are important in a wide range of technological applications and play a key role in the development of future technologies, mainly at the interface of synthetic and biological components. They include gels and hydrogels, elastomers, structural and packaging materials, micro and nanoparticles as well as biological materials. Soft materials can be distinguished from liquids owing to their defined shape and from hard materials by the deformability of their shape. This review article provides an overview of recent progress on the plasma engineering and processing of softer materials, especially in the area of synthesis, surface modification, etching, and deposition. The article aims to demonstrate the extensive range of plasma surface engineering as used to form, modify, and coat soft materials focusing on material properties and potential applications. In general, the plasma provides highly energetic, non-equilibrium conditions at material surfaces requiring to adjust the conditions for plasma-surface interaction to account for the specifics of soft matter, which holds independent of the used plasma source. Plasma-induced crosslinking and polymerization of liquids is discussed to transform them into gel-like materials as well as to modify the surface region of viscous liquids. A major field covers the plasma surface engineering of manmade soft materials with the help of gaseous reactive species yielding ablation, nanostructuring, functionalization, crosslinking, stiffening, and/or deposition to obtain demanded surface properties or adhesion to dissimilar materials. Finally, plasma engineering of rigid materials is considered to induce surface softening for the enhanced contact with tissues, to allow interaction in aqueous media, and to support bonding to soft matter. The potential and future perspectives of plasma engineering will be discussed in this review to contribute to a higher knowledge of plasma interaction with sensitive materials such as soft matter.

scholarly journals Entangling Lattice-Trapped Bosons with a Free Impurity: Impact on Stationary and Dynamical Properties

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 290
Author(s):  
Maxim Pyzh ◽  
Kevin Keiler ◽  
Simeon I. Mistakidis ◽  
Peter Schmelcher
Keyword(s):  
Structural Changes ◽  
Many Body ◽  
Wide Range ◽  
Entropy Measures ◽  
Particle Level ◽  
The Many ◽  
The One ◽  
Tunneling Dynamics ◽  
The Individual ◽  
Trapped Bosons

We address the interplay of few lattice trapped bosons interacting with an impurity atom in a box potential. For the ground state, a classification is performed based on the fidelity allowing to quantify the susceptibility of the composite system to structural changes due to the intercomponent coupling. We analyze the overall response at the many-body level and contrast it to the single-particle level. By inspecting different entropy measures we capture the degree of entanglement and intraspecies correlations for a wide range of intra- and intercomponent interactions and lattice depths. We also spatially resolve the imprint of the entanglement on the one- and two-body density distributions showcasing that it accelerates the phase separation process or acts against spatial localization for repulsive and attractive intercomponent interactions, respectively. The many-body effects on the tunneling dynamics of the individual components, resulting from their counterflow, are also discussed. The tunneling period of the impurity is very sensitive to the value of the impurity-medium coupling due to its effective dressing by the few-body medium. Our work provides implications for engineering localized structures in correlated impurity settings using species selective optical potentials.

scholarly journals Classification of apatite structures via topological data analysis: a framework for a ‘Materials Barcode’ representation of structure maps

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Scott Broderick ◽  
Ruhil Dongol ◽  
Tianmu Zhang ◽  
Krishna Rajan
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Crystal Chemistry ◽  
Persistent Homology ◽  
Hierarchical Classification ◽  
Topological Data Analysis ◽  
Learning Tool ◽  
Coordination Polyhedra ◽  
Machine Learning Tool ◽  
Topological Data

AbstractThis paper introduces the use of topological data analysis (TDA) as an unsupervised machine learning tool to uncover classification criteria in complex inorganic crystal chemistries. Using the apatite chemistry as a template, we track through the use of persistent homology the topological connectivity of input crystal chemistry descriptors on defining similarity between different stoichiometries of apatites. It is shown that TDA automatically identifies a hierarchical classification scheme within apatites based on the commonality of the number of discrete coordination polyhedra that constitute the structural building units common among the compounds. This information is presented in the form of a visualization scheme of a barcode of homology classifications, where the persistence of similarity between compounds is tracked. Unlike traditional perspectives of structure maps, this new “Materials Barcode” schema serves as an automated exploratory machine learning tool that can uncover structural associations from crystal chemistry databases, as well as to achieve a more nuanced insight into what defines similarity among homologous compounds.

scholarly journals Ligand-induced structural changes analysis of ribose-binding protein as studied by molecular dynamics simulations

2021 ◽  
pp. 1-12
Author(s):  
Haiyan Li ◽  
Zanxia Cao ◽  
Guodong Hu ◽  
Liling Zhao ◽  
Chunling Wang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Structural Changes ◽  
Binding Protein ◽  
Network Models ◽  
Md Simulations ◽  
Protein Domain ◽  
Opening Angle ◽  
Conformation Changes ◽  
Wide Range ◽  
Ribose Binding Protein

BACKGROUND: The ribose-binding protein (RBP) from Escherichia coli is one of the representative structures of periplasmic binding proteins. Binding of ribose at the cleft between two domains causes a conformational change corresponding to a closure of two domains around the ligand. The RBP has been crystallized in the open and closed conformations. OBJECTIVE: With the complex trajectory as a control, our goal was to study the conformation changes induced by the detachment of the ligand, and the results have been revealed from two computational tools, MD simulations and elastic network models. METHODS: Molecular dynamics (MD) simulations were performed to study the conformation changes of RBP starting from the open-apo, closed-holo and closed-apo conformations. RESULTS: The evolution of the domain opening angle θ clearly indicates large structural changes. The simulations indicate that the closed states in the absence of ribose are inclined to transition to the open states and that ribose-free RBP exists in a wide range of conformations. The first three dominant principal motions derived from the closed-apo trajectories, consisting of rotating, bending and twisting motions, account for the major rearrangement of the domains from the closed to the open conformation. CONCLUSIONS: The motions showed a strong one-to-one correspondence with the slowest modes from our previous study of RBP with the anisotropic network model (ANM). The results obtained for RBP contribute to the generalization of robustness for protein domain motion studies using either the ANM or PCA for trajectories obtained from MD.

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