Conveners
(DCMMP) M3-7 Soft Condensed Matter II | Matière condensée molle II (DPMCM)
- John Dutcher
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...
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...
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...
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...
