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Grant: Discovery Grants Program - Individual

The University of British Columbia

$128,000.00

Modelling the dynamics of active matter

EF 2024-25

Résumé
Active matter is a term used to describe matter that is composed of a large number of self-propelled active `particles' that individually convert stored or ambient energy into systematic motion. The interaction of many of these individual active particles with each other or their environment can lead to complex collective dynamics. Biological examples include a flock of birds, a school of fish, or at smaller scales a suspension of bacteria or even the collective motion within a human cell. The study of such active matter is important in many bio-related applications including: the design of synthetic materials (bioengineering), models of population dynamics (bioremediation), the control of biofilm formation (biomedical), and alternative energy production (biofuels). Understanding the dynamics of active matter systems can ultimately lead to the careful design and control of synthetic active matter allowing for applications such as autonomous chemical sensing or the targeted delivery of payloads by synthetic autonomous active particles. The objective of this program is to develop a mathematical modelling and computational framework using fast numerical methods and machine learning to describe, and then design, dense active matter systems for applications ranging from health to energy. This includes scenarios where there are many interacting autonomous active particles exhibiting collective dynamics in fluid environments that may contain complex heterogeneous microstructure.
Programme
Discovery Grants Program - Individual
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2020-04850
Name nom
Elfring, Gwynn
Department département
Mechanical Engineering - Mechanical Engineering
Organization id
2
Institution établissement
The University of British Columbia
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2020
Award amount
128000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1512
Committee name en
Mechanical Engineering
Committee name fr
Génie mécanique
Area of application code
1206
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Engineering
Area of application fr
Génie
Research subject code
2203
Research subject group en
Fluid mechanics
Research subject group fr
Mécanique des fluides
Research subject en
Modelling, simulation
Research subject fr
Modélisation et simulation
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Modelling the dynamics of active matter
Keywords
fluid mechanics; soft matter; stokes flow; complex fluids; active matter; stokesian dynamics
Application summary
Active matter is a term used to describe matter that is composed of a large number of self-propelled active `particles' that individually convert stored or ambient energy into systematic motion. The interaction of many of these individual active particles with each other or their environment can lead to complex collective dynamics. Biological examples include a flock of birds, a school of fish, or at smaller scales a suspension of bacteria or even the collective motion within a human cell. The study of such active matter is important in many bio-related applications including: the design of synthetic materials (bioengineering), models of population dynamics (bioremediation), the control of biofilm formation (biomedical), and alternative energy production (biofuels). Understanding the dynamics of active matter systems can ultimately lead to the careful design and control of synthetic active matter allowing for applications such as autonomous chemical sensing or the targeted delivery of payloads by synthetic autonomous active particles. The objective of this program is to develop a mathematical modelling and computational framework using fast numerical methods and machine learning to describe, and then design, dense active matter systems for applications ranging from health to energy. This includes scenarios where there are many interacting autonomous active particles exhibiting collective dynamics in fluid environments that may contain complex heterogeneous microstructure.