H2020Индивидуална стипендия2017–2019

AggregationKinetics · Emergence of Large Particles in Cluster-Cluster Aggregation

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2017-03-01 → 2019-02-28
Финансиране от ЕС: 183 455 €
Участници: 1
Схема: MSCA-IF-EF-ST

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Накратко на български

Математическите модели на растеж анализират как малки частици се събират в големи клъстери, подобно на процесите при мастилния печат. Разбирането на тези механизми помага да се предвиди поведението на сложни системи и да се подобрят практически приложения.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Emergence of Large Particles in Cluster-Cluster Aggregation

Growth processes are ubiquitous in nature and social sciences. Despite the differences in appearances, the underlying mechanisms are few such as coagulation and exchange. Consequently, the collective properties of these systems share many commonalities. The kinetic theory of growth processes is a vibrant branch of non-equilibrium statistical mechanics that has enjoyed a resurgence of interest in recent years. As far as the mathematically interesting and practically important issues are concerned it is crucial to know the dominant behaviour of the solutions of the equations that describes these growth systems. The dominant behaviour can be manifested either as the special mathematical form (such as self-similar form) or the formation of extremely large clusters. This Action made significant advances in the analysis of such dominant behavior by analysing long time behaviour of the most commonly used growth models (aggregation and exchange). The research program also helped develop an improved understanding of formation of extremely large clusters. In simple terms, the proposal achieved the following high level objectives A. Established, for the first time, fundamental mathematical properties of solutions of exchange-driven growth model (such as existence, uniqueness, non-existence of solutions etc.) B. Analyzed the large time behaviour of exchange-driven growth models and differential aggregation models C. Developed an understanding, based on average dynamics, the mechanism behind the generation of extremely large clusters by identifying the regimes that such abrupt behavior does not take place D. Employed the mathematical advances reached in Parts A,B and C in order to get genuine results in applications in inkjet printing applications.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Cluster-cluster aggregation is a growth process mediated by collisions and subsequent irreversible coagulation events. Surprisingly diverse range of natural and industrial phenomena in physics (formation of rain droplets), astrophysics (star and galaxy formation) and chemistry (polymerization) are essentially driven by the same mechanism. Therefore a sound understanding of these phenomena from theoretical and practical aspects is of utmost importance. We propose a multi-aspect study of dynamics of coagulating systems that undergo irreversible aggregation. The ambitious two-part project will encompass the mathematical analysis, physical derivations and numerical solutions of deterministic and stochastic aggregation models. The first part of the project will have the aim of addressing some of the important problems with regards to gelation, convergence to self-similarity and asymptotic behaviour of solutions of the Smoluchowski equation. The second part of the project will be devoted to the modelling and analysis of large fluctuations in aggregating systems with a focus on generation of exceptionally large clusters where the mean-field description becomes inadequate. To address the latter problem, a theory for the statistics of large clusters within the framework of kinetic theory will be developed which involves derivation of new stochastic models at the particle or continuum level.Dr. Emre Esenturk did his undergraduate education in physics in Ankara. He obtained his MSc in physics and PhD in mathematics at University of Pittsburgh (2011). After this, he did postdoctoral research in the Brown University and Pohang University of Science and Technology. He has worked on a broad range of topics in mathematics and physics including modeling, analysis and computational aspects.

Оригинален текст от CORDIS (на английски).

Участници

UNIVERSITY OF WARWICK · COVENTRYКоординаторОбединеното кралство