Konferenzen  >  Physik  >  Komplexe Systeme und Chaos

Institute of Macromolecular Chemistry of the Czech Academy of Sciences

The PMM 2026 conference will focus on the self-association of stimuli-responsive polymers, drawing inspiration from nature's ability to form complex, adaptive, and functional assemblies. Emphasis will be placed on understanding and designing dynamically reconfigurable polymer systems that respond to specific physical or chemical stimuli-systems that are increasingly relevant for technical innovations, biomedical applications, and sustainable materials development.

Tel.: [+420-296809130];     Email: pmm87@imc.cas.cz

Advanced Synthetic Approaches including Green Chemistry, Application of Physical Stimuli as Driving Force of Polymer Self-Assembly, Application of Chemical Stimuli as Driving Force of Polymer Self-Assembly, Advanced Methods for Characterization of Stimuli-Responsive Supramolecular Self-Assembly, Theoretical Aspects and In Silico Simulations for Studying Stimuli-Responsive Polymer Self-Assembly

Organische Chemie und Polymere,    Nanoteilchen und Emulsionen

University Hassan II Casablanca, Faculty of Science

The objective of the conference is to bring together researchers working on different aspects of nonlinear dynamics to present, discuss and disseminate recent advances in mechanical vibrations, applied physics, and applied dynamical systems.

Email: csndd2026@sciencesconf.org

The conference covers the following topics (but not limited to): Nonlinear Energy Harvesting and Energy Transfer Nonlinear behavior and control of MEMS, NEMS and AFM vibrating Systems Deterministic, Stochastic Dynamics, Control of Oscillating Systems and their Applications to Engineering and Science Systems with Time Delay Experiment in Nonlinear System and Control Modeling, Control and Analysis of Switching Systems Structural Health Monitoring Bifurcation and Stability in Nonlinear Systems Vibrations and Vibro-acoustic of Structures Non-Smooth Dynamics Network Dynamics and Control Neuro and Brain Dynamics Data-Driven and Machine Learning in Vibrations and Dynamics Dynamics in Fractional Order Systems PDEs and their Dynamics