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Condensed Matter
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Complex Nanoscale Geometry and Dynamics at the Frontier between Biology...
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Complex Nanoscale Geometry and Dynamics at the Frontier between Biology and Material Science

A special issue of Condensed Matter (ISSN 2410-3896).

Deadline for manuscript submissions: closed (30 September 2019) | Viewed by 28725

Special Issue Editor

Dr. Gaetano Campi

E-Mail Website
Guest Editor
Institute of Crystallography, CNR, via Salaria Km 29.300, Monterotondo Stazione, I-00016 Roma, Italy
Interests: synchrotron radiation techniques; heterogeneity and complexity in condensed matter; structural fluctuations and dynamics; quantum materials; biophysics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Outstanding structure–function relationships of new complex materials are often due their dynamic heterogeneous structures and compositions. Examples of complex materials include biomaterials, colloids, complex liquids, and strongly correlated materials. These materials are characterized by weak interactions between structural units, giving rise to different supramolecular configurations at nanoscale and mesoscale. While supramolecular assembly occurs widely in nature, it is poorly understood since it takes place at multiple scales. Today it is of high relevance for health care, biological systems, material engineering and photosynthetic processes. It is of high relevance also for polymers and systems at frustrated nanoscale phase separation, where crystalline and amorphous nanoscale regions coexist. The fluctuations between different supramolecular configurations play a central role in the understanding of both the basic principles of condensed matter and the material functionality for new technological applications. The visualization of the arising nano/mesoscale geometry and dynamics with the understanding of correlated phenomena require experimental techniques suitable to provide appropriate spatial and temporal resolution, jointly, to advanced modelling and statistical tools for data analysis. The purpose of this Special Issue is to collect significant works investigating connections between new geometries developing at nano/mesoscale and the emerging macroscopic properties in complex and heterogeneous materials in different fields ranging from material science to biology.

Dr. Gaetano Campi
Guest Editor

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Keywords

  • Complex and heterogeneous materials
  • Supramolecular assembly
  • Patterning at nanoscale and mesoscale
  • Correlated disorder
  • Biomaterials
  • Quantum materials

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Published Papers (7 papers)

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Research

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15 pages, 3541 KiB  
Article
Efficient Spatial Sampling for AFM-Based Cancer Diagnostics: A Comparison between Neural Networks and Conventional Data Analysis
by Gabriele Ciasca, Alberto Mazzini, Tanya E. Sassun, Matteo Nardini, Eleonora Minelli, Massimiliano Papi, Valentina Palmieri and Marco de Spirito
Condens. Matter 2019, 4(2), 58; https://doi.org/10.3390/condmat4020058 - 21 Jun 2019
Cited by 16 | Viewed by 3571
Abstract
Atomic force microscopy (AFM) in spectroscopy mode receives a lot of attention because of its potential in distinguishing between healthy and cancer tissues. However, the AFM translational process in clinical practice is hindered by the fact that it is a time-consuming technique in [...] Read more.
Atomic force microscopy (AFM) in spectroscopy mode receives a lot of attention because of its potential in distinguishing between healthy and cancer tissues. However, the AFM translational process in clinical practice is hindered by the fact that it is a time-consuming technique in terms of measurement and analysis time. In this paper, we attempt to address both issues. We propose the use of neural networks for pattern recognition to automatically classify AFM force–distance (FD) curves, with the aim of avoiding curve-fitting with the Sneddon model or more complicated ones. We investigated the applicability of this method to the classification of brain cancer tissues. The performance of the classifier was evaluated with receiving operating characteristic (ROC) curves for the approach and retract curves separately and in combination with each other. Although more complex and comprehensive models are required to demonstrate the general applicability of the proposed approach, preliminary evidence is given for the accuracy of the results, and arguments are presented to support the possible applicability of neural networks to the classification of brain cancer tissues. Moreover, we propose a possible strategy to shorten measurement times based on the estimation of the minimum number of FD curves needed to classify a tissue with a confidence level of 0.005. Taken together, these results have the potential to stimulate the design of more effective protocols to reduce AFM measurement times and to get rid of curve-fitting, which is a complex and time-consuming issue that requires experienced staff with a strong data-analysis background. Full article
(This article belongs to the Special Issue Complex Nanoscale Geometry and Dynamics at the Frontier between Biology and Material Science)
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11 pages, 3721 KiB  
Article
Fractal Dimension Analysis of High-Resolution X-Ray Phase Contrast Micro-Tomography Images at Different Threshold Levels in a Mouse Spinal Cord
by Laura Maugeri, Mauro DiNuzzo, Marta Moraschi, Charles Nicaise, Inna Bukreeva, Fabio Mangini, Federico Giove, Alessia Cedola and Michela Fratini
Condens. Matter 2018, 3(4), 48; https://doi.org/10.3390/condmat3040048 - 11 Dec 2018
Cited by 8 | Viewed by 4049
Abstract
Fractal analysis is a powerful method for the morphological study of complex systems that is increasingly applied to biomedical images. Spatial resolution and image segmentation are crucial for the discrimination of tissue structures at the multiscale level. In this work, we have applied [...] Read more.
Fractal analysis is a powerful method for the morphological study of complex systems that is increasingly applied to biomedical images. Spatial resolution and image segmentation are crucial for the discrimination of tissue structures at the multiscale level. In this work, we have applied fractal analysis to high-resolution X-ray phase contrast micro-tomography (XrPCμT) images in both uninjured and injured tissue of a mouse spinal cord. We estimated the fractal dimension (FD) using the box-counting method on tomographic slices segmented at different threshold levels. We observed an increased FD in the ipsilateral injured hemicord compared with the contralateral uninjured tissue, which was almost independent of the chosen threshold. Moreover, we found that images exhibited the highest fractality close to the global histogram threshold level. Finally, we showed that the FD estimate largely depends on the image histogram regardless of tissue appearance. Our results demonstrate that the pre-processing of XrPCμT images is critical to fractal analysis and the estimation of FD. Full article
(This article belongs to the Special Issue Complex Nanoscale Geometry and Dynamics at the Frontier between Biology and Material Science)
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10 pages, 2358 KiB  
Article
On the Nanoscale Structure of KxFe2−yCh2 (Ch = S, Se): A Neutron Pair Distribution Function View
by Panagiotis Mangelis, Hechang Lei, Marshall T. McDonnell, Mikhail Feygenson, Cedomir Petrovic, Emil S. Bozin and Alexandros Lappas
Condens. Matter 2018, 3(3), 20; https://doi.org/10.3390/condmat3030020 - 3 Jul 2018
Cited by 3 | Viewed by 4718
Abstract
Comparative exploration of the nanometer-scale atomic structure of KxFe2−yCh2 (Ch = S, Se) was performed using neutron total scattering-based atomic pair distribution function (PDF) analysis of 5 K powder diffraction data in relation to physical properties. Whereas [...] Read more.
Comparative exploration of the nanometer-scale atomic structure of KxFe2−yCh2 (Ch = S, Se) was performed using neutron total scattering-based atomic pair distribution function (PDF) analysis of 5 K powder diffraction data in relation to physical properties. Whereas KxFe2−ySe2 is a superconductor with a transition temperature of about 32 K, the isostructural sulphide analogue is not, which instead displays a spin glass semiconducting behavior at low temperatures. The PDF analysis explores phase separated and disordered structural models as candidate descriptors of the low temperature data. For both materials, the nanoscale structure is well described by the iron (Fe)-vacancy-disordered K2Fe5−yCh5 (I4/m) model containing excess Fe. An equally good description of the data is achieved by using a phase separated model comprised of I4/m vacancy-ordered and I4/mmm components. The I4/mmm component appears as a minority phase in the structure of both KxFe2−ySe2 and KxFe2−yS2, and with similar contribution, implying that the phase ratio is not a decisive factor influencing the lack of superconductivity in the latter. Comparison of structural parameters of the Fe-vacancy-disordered model indicates that the replacement of selenium (Se) by sulphur (S) results in an appreciable reduction in the Fe-Ch interatomic distances and anion heights, while simultaneously increasing the irregularity of FeCh4 tetrahedra, suggesting the more significant influence of these factors. Structural features are also compared to the non-intercalated FeSe and FeS parent phases, providing further information for the discussion about the influence of the lattice degrees of freedom on the observed properties in layered iron chalcogenides. Full article
(This article belongs to the Special Issue Complex Nanoscale Geometry and Dynamics at the Frontier between Biology and Material Science)
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11 pages, 1715 KiB  
Article
Annealed Low Energy States in Frustrated Large Square Josephson Junction Arrays
by Martijn Lankhorst, Alexander Brinkman, Hans Hilgenkamp, Nicola Poccia and Alexander Golubov
Condens. Matter 2018, 3(2), 19; https://doi.org/10.3390/condmat3020019 - 13 Jun 2018
Cited by 6 | Viewed by 3756
Abstract
Numerical simulations were done to find low energy states in frustrated large square Josephson Junction arrays in a perpendicular magnetic field using simulated annealing on the coupled RSJ model. These simulations were made possible by a new algorithm suitable for parallel gpu computing [...] Read more.
Numerical simulations were done to find low energy states in frustrated large square Josephson Junction arrays in a perpendicular magnetic field using simulated annealing on the coupled RSJ model. These simulations were made possible by a new algorithm suitable for parallel gpu computing and reduced complexity. Free boundary conditions were used so that values of the frustration factor f that are incommensurate with the array size are permitted. The resulting energy as a function of f is continuous with logarithmic discontinuities in the derivative dE/df at rational frustration factors f=p/q with small q, substantiating the mathematical proof that this curve is continuous and further showing that the staircase state hypothesis is incorrect. The solution shows qualitative similarities with the lowest energy branch of the Hofstadter butterfly, which is a closely related problem. Furthermore, it is found that at the edge of an array there are either extra vortices or missing vortices depending the frustration factor, and the width of this region is independent of the array size. Full article
(This article belongs to the Special Issue Complex Nanoscale Geometry and Dynamics at the Frontier between Biology and Material Science)
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10 pages, 19904 KiB  
Article
Formation and Oriented Aggregation of Tabular Hexagonal Silver Particles
by Lorenza Suber
Condens. Matter 2018, 3(2), 13; https://doi.org/10.3390/condmat3020013 - 14 Apr 2018
Cited by 5 | Viewed by 4112
Abstract
Silver tabular hexagonal particles (<diagonal> = 200 nm) were prepared at 40 °C by the reduction of silver nitrate with ascorbic acid in a solution of a polynaphthalene sulphonic dispersant agent, Daxad 19, in strong acidic conditions. By varying the reaction temperature and [...] Read more.
Silver tabular hexagonal particles (<diagonal> = 200 nm) were prepared at 40 °C by the reduction of silver nitrate with ascorbic acid in a solution of a polynaphthalene sulphonic dispersant agent, Daxad 19, in strong acidic conditions. By varying the reaction temperature and thus the dispersion viscosity between 10 °C and 30 °C, mesostructures of silver flat rods and flakes were obtained, the former resulting from linear aggregation of tabular hexagonal particles and the latter formed by intertwined flat rods. The results indicate an easy way to tune the aggregation of particles to obtain ordered mesostructures. Full article
(This article belongs to the Special Issue Complex Nanoscale Geometry and Dynamics at the Frontier between Biology and Material Science)
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1915 KiB  
Article
Correlated Disorder in Myelinated Axons Orientational Geometry and Structure
by Michael Di Gioacchino, Gaetano Campi, Nicola Poccia and Antonio Bianconi
Condens. Matter 2017, 2(3), 29; https://doi.org/10.3390/condmat2030029 - 11 Sep 2017
Cited by 4 | Viewed by 4198
Abstract
While the ultrastructure of myelin is considered a quasi-crystalline stable system, nowadays its multiscale complex dynamics appear to play a key role in its functionality, degeneration and repair processes following neurological diseases and trauma. In this work, we investigated the fluctuation of the [...] Read more.
While the ultrastructure of myelin is considered a quasi-crystalline stable system, nowadays its multiscale complex dynamics appear to play a key role in its functionality, degeneration and repair processes following neurological diseases and trauma. In this work, we investigated the fluctuation of the myelin supramolecular assembly by measuring the spatial distribution of orientation fluctuations of axons in a Xenopus Laevis sciatic nerve associated with nerve functionality. To this end, we used scanning micro X-ray diffraction (SμXRD), a non-invasive technique that has already been applied to other heterogeneous systems presenting complex geometries from microscale to nanoscale. We found that the orientation of the spatial fluctuations of fresh axons show a Levy flight distribution, which is a clear indication of correlated disorder. We found that the Levy flight distribution was missing in the aged nerve prepared in an unfresh state. This result shows that the spatial distribution of axon orientation fluctuations in unfresh nerve state loses the correlated disorder and assumes a random disorder behavior. This work provides a deeper understanding of the ultrastructure-function nerve relation and paves the way for the study of other materials and biomaterials using the SμXRD technique to detect fluctuations in their supramolecular structure. Full article
(This article belongs to the Special Issue Complex Nanoscale Geometry and Dynamics at the Frontier between Biology and Material Science)
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Review

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13 pages, 2650 KiB  
Review
Evolution of Complexity in Out-of-Equilibrium Systems by Time-Resolved or Space-Resolved Synchrotron Radiation Techniques
by Gaetano Campi and Antonio Bianconi
Condens. Matter 2019, 4(1), 32; https://doi.org/10.3390/condmat4010032 - 14 Mar 2019
Cited by 14 | Viewed by 3280
Abstract
Out-of-equilibrium phenomena are attracting high interest in physics, materials science, chemistry and life sciences. In this state, the study of structural fluctuations at different length scales in time and space are necessary to achieve significant advances in the understanding of the structure-functionality relationship. [...] Read more.
Out-of-equilibrium phenomena are attracting high interest in physics, materials science, chemistry and life sciences. In this state, the study of structural fluctuations at different length scales in time and space are necessary to achieve significant advances in the understanding of the structure-functionality relationship. The visualization of patterns arising from spatiotemporal fluctuations is nowadays possible thanks to new advances in X-ray instrumentation development that combine high-resolution both in space and in time. We present novel experimental approaches using high brilliance synchrotron radiation sources, fast detectors and focusing optics, joint with advanced data analysis based on automated statistical, mathematical and imaging processing tools. This approach has been used to investigate structural fluctuations in out-of-equilibrium systems in the novel field of inhomogeneous quantum complex matter at the crossing point of technology, physics and biology. In particular, we discuss how nanoscale complexity controls the emergence of high-temperature superconductivity (HTS), myelin functionality and formation of hybrid organic-inorganic supramolecular assembly. The emergent complex geometries, opening novel venues to quantum technology and to the development of quantum physics of living systems, are discussed. Full article
(This article belongs to the Special Issue Complex Nanoscale Geometry and Dynamics at the Frontier between Biology and Material Science)
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