Login

2023 CAP Congress / Congrès de l'ACP 2023

18–23 Jun 2023
University of New Brunswick
America/Halifax timezone
Welcome to the 2023 CAP Congress Program website! / Bienvenue au siteweb du programme du Congrès de l'ACP 2023!

Support

Session

(DCMMP) M3-7 Soft Condensed Matter II | Matière condensée molle II (DPMCM)

M3-7
19 Jun 2023, 16:00
University of New Brunswick

University of New Brunswick

Conveners

(DCMMP) M3-7 Soft Condensed Matter II | Matière condensée molle II (DPMCM)

  • John Dutcher

Presentation materials

There are no materials yet.

  1. 3581. (I) Theory of Ordered Phases Self-Assembled from Soft Matter
    An-Chang Shi
    19/06/2023, 16:00
    Condensed Matter and Materials Physics / Physique de la matière condensée et matériaux (DCMMP-DPMCM)
    Invited Speaker / Conférencier(ère) invité(e)

    Intricate periodic and aperiodic ordered phases have been discovered in various soft matter systems such as supramolecular assemblies, surfactant solutions and block copolymers, underscoring the universality of emergent order in condensed matter. Theoretical study of block copolymer systems has been successful, revealing that the formation of complex ordered phases could be regulated by...

    Go to contribution page
  2. 3725. (G*) Phase behaviour of Polydisperse Diblock Copolymers
    Ms Desiree Rehel (McMaster University)
    19/06/2023, 16:30
    Condensed Matter and Materials Physics / Physique de la matière condensée et matériaux (DCMMP-DPMCM)
    Oral Competition (Graduate Student) / Compétition orale (Étudiant(e) du 2e ou 3e cycle)

    Recent experimental and theoretical studies have shown that many ordered structures, ranging in complexity from simple lamellae to complex Frank-Kasper (FK) phases, can be formed from diblock copolymers. In many of the experimental studies the polymeric samples used in are polydisperse, however most theoretical studies have examined monodisperse systems. Therefore, to conduct theoretical...

    Go to contribution page
  3. 3678. (I) Neural-network-based solver for a few soft matter problems
    Prof. Jeff Z. Y. Chen (University of Waterloo)
    19/06/2023, 16:45
    Condensed Matter and Materials Physics / Physique de la matière condensée et matériaux (DCMMP-DPMCM)
    Invited Speaker / Conférencier(ère) invité(e)

    Many soft matter theoretical problems can be reformulated into minimizing a cost function, in which the field-based physical properties (the target functions) are adjusted to achieve the minimum. The Neural-network approach approximates the target functions by forward-feeding neural networks and the machine-learning techniques adjust the network parameters to produce the approximation to the...

    Go to contribution page
  4. 3930. (I) Using Neural Networks to Solve Partial Differential Equations that Describe Biophysical Systems
    Hendrick W. de Haan
    19/06/2023, 17:15
    Condensed Matter and Materials Physics / Physique de la matière condensée et matériaux (DCMMP-DPMCM)
    Invited Speaker / Conférencier(ère) invité(e)

    AI and machine learning – specifically neural network (NN) based approaches – have become an indispensable tool in many areas of physics research. Nevertheless, there is still much to learn about NNs at the fundamental level and for application specific methodologies. In this talk, I will discuss some of the work we have done both using physics applications to study how neural networks learn...

    Go to contribution page
Building timetable...