# Optical Tweezers in Emulsion Research: Principles, Advances, and Prospects

**Authors:** Qifei Ma, Huaizhou Jin, Xiaoxiao Shang, Tamas Pardy, Ott Scheler, Simona Bartkova, Dan Cojoc, Denis Garoli, Shangzhong Jin

PMC · DOI: 10.1021/acs.langmuir.5c05654 · Langmuir · 2026-02-05

## TL;DR

Optical tweezers are being used to study emulsions with high precision, offering new insights into droplet interactions and stability.

## Contribution

This review systematically evaluates optical tweezers for emulsion research, highlighting their unique capabilities and future integration with microfluidics and machine learning.

## Key findings

- Optical tweezers enable single-droplet analysis of emulsion stability factors like ionic strength and surfactant architecture.
- Light-driven droplet rotation via angular momentum transfer allows active manipulation of soft matter.
- Integration with microfluidics and machine learning is proposed to enhance throughput and practical feasibility.

## Abstract

Optical tweezers (OTs) have emerged as a powerful tool
for probing
emulsion dynamics with single-droplet precision, enabling quantitative
analysis of interfacial interactions. Recent OT studies have systematically
elucidated the critical factors governing emulsion stability, including
ionic strength, pH, surfactant architecture, temperature, and photo/gas
stimuli. Parallel advances in optofluidic control demonstrate that
light-driven droplet rotation-achieved through angular momentum transfer
and liquid crystal molecular reorientation represents a transformative
approach for active soft matter manipulation. In this review, we conduct
a systematic evaluation of OT systems, encompassing both instrumental
configurations and cost-benefit analyses to assess their practical
feasibility. The review critically examines the unique capabilities
of OTs in emulsion research-including unprecedented spatial resolution
and quantitative force measurement at the single-droplet level while
addressing current limitations in throughput and operational complexity.
Looking forward, the synergistic integration of OT technology with
microfluidic platforms and machine learning algorithms is also presented.

## Full-text entities

- **Genes:** PNLIP (pancreatic lipase) [NCBI Gene 5406] {aka PL, PNLIPD, PTL}
- **Diseases:** adhesion (MESH:D000267)
- **Chemicals:** Salt (MESH:D012492), triolein (MESH:D014304), PTFE (MESH:D011138), O (MESH:D010100), calcite (MESH:D002119), NaCl (MESH:D012965), polymer (MESH:D011108), carbon (MESH:D002244), polyelectrolyte (MESH:D000071228), N2 (MESH:D009584), PEG (MESH:D011092), water (MESH:D014867), tetradecane (MESH:C024713), SDS (MESH:D012967), silica (MESH:D012822), Ba2+ (MESH:C080430), Na+ (MESH:D012964), (3-(2-aminoethyl)aminopropyl)trimethoxysilane (-), oil (MESH:D009821), fluorescein (MESH:D019793), CTAB (MESH:D000077286), lipid (MESH:D008055), W (MESH:D014414), polystyrene (MESH:D011137), CO2 (MESH:D002245), SDBS (MESH:C001114), Oleic acid (MESH:D019301), hydrogen (MESH:D006859)
- **Species:** Escherichia coli (E. coli, species) [taxon 562], Saccharomyces cerevisiae (baker's yeast, species) [taxon 4932], Homo sapiens (human, species) [taxon 9606], Formosa sp. AT (species) [taxon 515984]

## Full text

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## Figures

11 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12922172/full.md

## References

120 references — full list in the complete paper: https://tomesphere.com/paper/PMC12922172/full.md

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Source: https://tomesphere.com/paper/PMC12922172