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Research project

DiG for the Future: taming disorder in self-assembled materials with topology

Project overview

Soft matter systems have some common features, typically showing high susceptibility to deformation under small mechanical or thermal stress, and the significant complexity of their components (liquid crystals, polymers, biological tissues, etc). These characteristics make the mathematical modelling of soft materials challenging and, in most cases, powerful analytic methods are required for accurate and quantitative characterisation of their dynamics.

Topological data analysis is a relatively new tool that uses the shape of the data to obtain meaningful information. Several topological data analytic tools have been successfully applied in the analysis of time-independent data of soft matter systems. These analyses have allowed characterising the morphology of soft materials, the atomic configurations of complex organic molecules and ion aggregation systems.

In this project, funded by the Leverhulme Trust, partially ordered, composite nanomaterials, with complex structural and physical behaviour are investigated. Our analytic framework, based on topological data analysis, provides both a qualitative and quantitative characterisation of the dynamical behaviour of a wide range of semi-ordered soft matter, captures the degree of organisation at a mesoscopic level, tracking their time-evolution and ultimately detecting the order-disorder transition at the microscopic scale.

Staff

Lead researcher

Professor Malgosia Kaczmarek

Professor of Physics And Astronomy
Other researchers

Professor Giampaolo D'Alessandro

Professor

Research interests

  • Liquid crystals
  • Optics
  • Mathematical modelling

Professor Jacek Brodzki

Head of School

Research interests

  • Topological data analysis
  • Applications of topology to medicine, biology, chemistry, physics, computer science
  • Noncommutative Geometry

Collaborating research institutes, centres and groups

Research outputs

Tristan Madeleine,
Nina Podoliak,
Oleksandr Buchnev,
Ingrid Membrillo Solis,
Tetiana Orlova,
Maria van Rossem,
Giampaolo D'Alessandro,
, 2023 , ACS Nano , 18 (1)
Type: article
Tristan Madeleine,
Giampaolo D'Alessandro,
, 2023 , Optics Express , 31 (7) , 11395--11407
Type: article
Francesca Petronella,
Tristan Madeleine,
Vincenzo De Mei,
Federica Zaccagnini,
Marinella Striccoli,
Giampaolo D'alessandro,
Mariacristina Rumi,
Jonathan Slagle,
& Luciano de Sio
, 2023 , ACS Applied Materials and Interfaces , 15 (42) , 49468--49477
Type: article
Ingrid Membrillo Solis,
Tetiana Orlova,
Karolina Bednarska,
Piotr Lesiak,
Tomasz Wolinski,
& Giampaolo D'alessandro
, 2022 , Communications Materials , 3 (1)
Type: article
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