The Hitchhiker’s guide to differential dynamic microscopy

Over nearly two decades, differential dynamic microscopy (DDM) has become a standard technique for extracting dynamic correlation functions from time-lapse microscopy data, with applications spanning classical soft matter systems, such as colloidal suspensions, liquid crystals, polymer solutions, gels and glasses, and active fluids and biological systems. In its most common implementation, DDM analyzes image sequences acquired with a conventional microscope equipped with a digital camera, yielding time- and wavevector-resolved information analogous to that obtained in multi-angle dynamic light scattering. With a widening array of applications and a growing, heterogeneous user base, lowering the technical barrier to performing DDM has become a central objective. In this tutorial article, we provide a step-by-step guide to conducting DDM experiments-from planning and acquisition to data analysis-intended as a resource for both new and experienced practitioners. We also introduce the open-source software package, fastDDM, designed to efficiently process large image datasets using optimized, parallel algorithms that reduce analysis times by up to four orders of magnitude on typical datasets (e.g., 10 000 frames), thereby enabling high-throughput workflows, reproducibility, and broader adoption across disciplines.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2025-10-24
DOI
https://doi.org/10.1063/5.0289471
Citations
4
Primary Topic
Advanced Fluorescence Microscopy Techniques
Type
article
Field-Weighted Citation Impact
6.54
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The Hitchhiker’s guide to differential dynamic microscopy

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4 citations
The Journal of Chemical Physics
Advanced Fluorescence Microscopy Techniques
6.54
article

The Hitchhiker’s guide to differential dynamic microscopy

Maxime Lavaud, Fabio Giavazzi, Enrico Lattuada, Roberto Cerbino, Fabian Krautgasser
article en
4 citations

Abstract

Over nearly two decades, differential dynamic microscopy (DDM) has become a standard technique for extracting dynamic correlation functions from time-lapse microscopy data, with applications spanning classical soft matter systems, such as colloidal suspensions, liquid crystals, polymer solutions, gels and glasses, and active fluids and biological systems. In its most common implementation, DDM analyzes image sequences acquired with a conventional microscope equipped with a digital camera, yielding time- and wavevector-resolved information analogous to that obtained in multi-angle dynamic light scattering. With a widening array of applications and a growing, heterogeneous user base, lowering the technical barrier to performing DDM has become a central objective. In this tutorial article, we provide a step-by-step guide to conducting DDM experiments-from planning and acquisition to data analysis-intended as a resource for both new and experienced practitioners. We also introduce the open-source software package, fastDDM, designed to efficiently process large image datasets using optimized, parallel algorithms that reduce analysis times by up to four orders of magnitude on typical datasets (e.g., 10 000 frames), thereby enabling high-throughput workflows, reproducibility, and broader adoption across disciplines.

The Journal of Chemical PhysicsVol. 163(16)
University of Vienna (AT), University of Milan (IT)
Openalex Percentile: Top 3%
Advanced Fluorescence Microscopy Techniques
6.54
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