Convolutional neural network-based colloidal self-assembly state classification

Lizano-Villalobos, Andrés F; Tang, Xun

doi:10.1039/d3sm00139c

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Cited by 6 publications

References 57 publications

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Stochastic optimal control of mesostructure of supramolecular assemblies using dissipative particle dynamics and dynamic programming with experimental validation

Pahari,

Lin,

Liu

et al. 2023

Chemical Engineering Journal

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Stochastic optimal control of mesostructure of supramolecular assemblies using dissipative particle dynamics and dynamic programming with experimental validation

Pahari,

Lin,

Liu

et al. 2023

Chemical Engineering Journal

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Active Matter and Artificial Intelligence

Volpe,

Cichos,

Volpe

2024

Active Colloids

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In this chapter, we explore the intersection of active matter and artificial intelligence (AI), providing a brief overview of machine learning principles and their application in understanding and manipulating active matter. We discuss both opportunities and challenges that AI methodologies present in the data acquisition and analysis as well as in the data-driven modelling of active colloids. We then highlight the role of AI in enhancing navigation and search strategies of active colloids, and in understanding their collective dynamics, offering insights into the algorithms that guide these processes. We conclude by addressing the ethical implications and safety guidelines necessary for the responsible use of AI in this field. With this chapter, we aim to equip readers with a thorough understanding of the current state and potential advancements in employing AI to unravel the complexities of active colloids, making it a valuable resource for researchers and enthusiasts alike.

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Convolutional neural networks applied to differential dynamic microscopy reduces noise when quantifying heterogeneous dynamics

Martinez,

Siu,

Dang

et al. 2024

Soft Matter

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Convolutional neural network-based colloidal self-assembly state classification

Abstract: Colloidal self-assembly is a viable solution to making advanced metamaterials. While the physicochemical properties of the particles affect the property of the assembled structures, particle configuration is also a critical...

Cited by 6 publications

References 57 publications

Stochastic optimal control of mesostructure of supramolecular assemblies using dissipative particle dynamics and dynamic programming with experimental validation

Stochastic optimal control of mesostructure of supramolecular assemblies using dissipative particle dynamics and dynamic programming with experimental validation

Active Matter and Artificial Intelligence

Convolutional neural networks applied to differential dynamic microscopy reduces noise when quantifying heterogeneous dynamics

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