Measuring the complexity of micro and nanostructured surfaces

TY - JOUR

T1 - Measuring the complexity of micro and nanostructured surfaces

AU - Arapis, A.

AU - Constantoudis, V.

AU - Kontziampasis, D.

AU - Milionis, A.

AU - Lam, C. W. E.

AU - Tripathy, A.

AU - Poulikakos, D.

AU - Gogolides, E.

N1 - Funding Information: This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 801229 (project Harmonic: HierARchical Multiscale NanoInterfaces for enhanced Condensation processes). Publisher Copyright: © 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conferences & Exhibition on Nanotechnologies, Organic Electronics & Nanomedicine – NANOTEXNOLOGY 2020

PY - 2022

Y1 - 2022

N2 - Nanostructured surfaces usually exhibit complicated morphologies that cannot be described in terms of Euclidean geometry. Simultaneously, they do not constitute fully random noise fields to be characterized by simple stochastics and probability theory. In most cases, nanomorphologies consist of complicated mixtures of order and randomness, which should be described quantitatively if one aims to control their fabrication and properties. In this work, inspired by recent developments in complexity theory, we propose a method to measure nanomorphology complexity that is based on the deviation from the average symmetry of surfaces. We present the methodology for its calculation and the validation of its performance, using a series of synthetic surfaces where the proposed complexity measure obtains a maximum value at the most heterogeneous morphologies between the fully ordered and fully random cases. Additionally, we measure the complexity of experimental micro and nanostructured surfaces (polymeric and metallic), and demonstrate the usefulness of the proposed method in quantifying the impact of processing conditions on their morphologies. Finally, we hint at the relationship between the complexity measure and the functional properties of surfaces.

AB - Nanostructured surfaces usually exhibit complicated morphologies that cannot be described in terms of Euclidean geometry. Simultaneously, they do not constitute fully random noise fields to be characterized by simple stochastics and probability theory. In most cases, nanomorphologies consist of complicated mixtures of order and randomness, which should be described quantitatively if one aims to control their fabrication and properties. In this work, inspired by recent developments in complexity theory, we propose a method to measure nanomorphology complexity that is based on the deviation from the average symmetry of surfaces. We present the methodology for its calculation and the validation of its performance, using a series of synthetic surfaces where the proposed complexity measure obtains a maximum value at the most heterogeneous morphologies between the fully ordered and fully random cases. Additionally, we measure the complexity of experimental micro and nanostructured surfaces (polymeric and metallic), and demonstrate the usefulness of the proposed method in quantifying the impact of processing conditions on their morphologies. Finally, we hint at the relationship between the complexity measure and the functional properties of surfaces.

KW - Aluminium surfaces

KW - Complexity

KW - Entropy

KW - Etching

KW - Nanostructures

KW - PMMA surfaces

UR - https://www.scopus.com/pages/publications/85127706008

U2 - 10.1016/j.matpr.2021.10.120

DO - 10.1016/j.matpr.2021.10.120

M3 - Article

AN - SCOPUS:85127706008

SN - 2214-7853

VL - 54

SP - 63

EP - 72

JO - Materials Today: Proceedings

JF - Materials Today: Proceedings

IS - Part 1

T2 - 2020 International Conferences and Exhibition on Nanotechnologies, Organic Electronics Nanomedicine, NANOTEXNOLOGY 2020

Y2 - 4 July 2020 through 11 July 2020

ER -