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Papers
61,005 resultsShowing papers similar to A Review of Holography in the Aquatic Sciences: In situ Characterization of Particles, Plankton, and Small Scale Biophysical Interactions
ClearGeometric-Optical Model of Digital Holographic Particle Recording System and Features of Its Application
Not relevant to microplastics — this paper describes a calibrated geometric-optical model for a submersible digital holographic camera used to study plankton in the ocean, improving the accuracy of particle size and position measurements.
Spectroscopic aspects of underwater digital holography of plankton
Researchers demonstrated that underwater digital holography — a technique that captures 3D images of plankton in real time without disturbing them — can monitor the rhythms of plankton populations and detect early signs of ecosystem stress, similar to how spectroscopy reveals the structure of atoms. Shifts in the natural timing patterns of plankton communities can serve as early warning signals of pollution or ecological disruption.
Compact holographic microscope for imaging flowing microplastics
Researchers developed a compact holographic microscope capable of imaging flowing microplastics in aquatic environments, providing a fast, quantitative method for real-time characterization of plastic particle size and shape distributions.
Digital holographic approaches to the detection and characterization of microplastics in water environments
This review examines advances in using digital holography as a high-throughput tool for detecting and characterizing microplastics in water. Researchers discuss both the hardware and software developments, including the growing role of artificial intelligence for classification tasks. The study highlights the emergence of field-portable holographic flow cytometers as a promising technology for real-time water monitoring of microplastic contamination.
Identification of microplastics in a large water volume by integrated holography and Raman spectroscopy
A new technique combining holography and Raman spectroscopy was demonstrated to identify plastic pellets suspended in a large volume of water without physical contact. This non-destructive approach could enable real-time, in-water microplastic detection for environmental monitoring.
Complete holography‐based system for the identification of microparticles in water samples
Researchers developed a comprehensive holography-based system for identifying and classifying microparticles — including microplastics — in water samples using microscopic holographic projections, designed for researchers without specialist holography expertise. The system is deployable as part of an autonomous sailboat robot for large-scale environmental monitoring of diverse microplastic types in water bodies.
Snapshot Polarization-Sensitive Holography for Detecting Microplastics in Turbid Water
Researchers developed a new imaging technique combining holography and polarimetry to detect microplastic particles in turbid water, a setting where traditional detection methods struggle. The approach uses differences in how light polarizes when passing through plastic versus natural particles to distinguish microplastics even in murky conditions. The study demonstrates a promising tool for faster, more practical monitoring of microplastic pollution in real-world water environments.
Underwater Digital Holography of Plankton with Advanced Monitoring Capabilities for Bioindication in Situ
This study presents a submersible digital holographic camera system for monitoring plankton in arctic waters, tracking behavioral characteristics that can indicate ecosystem stress. Long-term time series data from the camera revealed rhythmic patterns in plankton behavior useful as indicators of ecosystem health.
Holographic and polarization features analysis for microplastics characterization and water monitoring
Researchers explored digital holography and polarization imaging as a combined technique for characterizing and classifying microplastics in water, computing features including angle of polarization (AoP) and degree of linear polarization (DoLP) to distinguish microplastics from biological and natural particles. The method demonstrated potential for real-time, non-contact, in situ microplastic detection and water quality monitoring.
Holographic characterization of contaminants in water: Differentiation of suspended particles in heterogeneous dispersions
Researchers used holographic imaging — a technique that measures the size and light-bending properties of individual particles — to simultaneously identify polystyrene microbeads, bacteria, and oil droplets in the same water sample, demonstrating a faster and more informative way to detect and classify multiple types of waterborne contaminants at once.
Intelligent Digital Holographic systems to counteract microplastic pollution in marine waters
Researchers developed a digital holography system capable of detecting and classifying microplastic particles in seawater in a label-free, high-throughput manner. The system can identify plastic particles that are otherwise invisible to the naked eye and can be adapted for use with microfluidic devices. This technology offers a faster and more compact alternative to traditional microscopy methods for marine microplastic monitoring.
Computational polarized holography for automatic monitoring of microplastics in scattering aquatic environments
Researchers developed an integrated imaging system based on computational polarized holography for automatic monitoring of microplastics in aquatic environments. The system enables accurate 3D tracking of dynamic microplastic particles, and a hybrid de-scattering algorithm substantially improves image quality even in turbid water conditions. An unsupervised clustering method was also developed to identify and classify different microplastics based on their multimodal features without manual annotation.
Monitoring Bioindication of Plankton through the Analysis of the Fourier Spectra of the Underwater Digital Holographic Sensor Data
Researchers developed a method to monitor plankton biodiversity using Fourier spectral analysis of plankton images, demonstrating that spectral features of plankton assemblages correlate with species composition and ecosystem health indicators. The approach offers a computationally efficient route to continuous bioindication in marine and freshwater monitoring programs.
An Ultracompact Underwater Pulsed Digital Holographic Camera With Rapid Particle Image Extraction Suite
Researchers designed and successfully deployed an ultracompact 3.5-kilogram underwater digital holographic camera in the North Sea, demonstrating real-time in-situ imaging of particles including potential microplastics in open ocean conditions at a fraction of the size and weight of existing underwater holographic systems.
Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging
Researchers used holographic imaging to reveal hidden nanoscale dynamics in natural photonic structures, demonstrating the potential of optical methods to uncover fine structural details at scales relevant to environmental particle analysis.
A fractal analysis of the holographic diffraction patterns for detecting microplastics among diatoms
Researchers developed a fractal analysis approach applied to holographic diffraction patterns to distinguish microplastics from diatoms in water samples, enabling automated identification of plastic particles in complex biological matrices.
Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging
Researchers used holography and optics to reveal hidden nanoscale dynamics in natural photonic structures — biological surfaces that manipulate light through intricate nano-architectures. These optical techniques could be adapted for characterizing the fine structure of microplastic particles.
In-situ and real-time nano/microplastic coatings and dynamics in water using nano-DIHM: A novel capability for the plastic life cycle research
Researchers used a novel nano-digital inline holographic microscope to study nano- and microplastic particles in real time in water, revealing distinct coating patterns on particle surfaces and dynamic aggregation behaviors that standard offline methods miss.
Polarization-sensitive digital holography for microplastic identification through scattering media
Researchers designed a polarization-sensitive holographic imaging system capable of identifying transparent microplastics through scattering media by measuring the degree of linear polarization (DoLP) as an angle-independent discriminating feature. The system enables non-destructive differentiation of microplastic types in turbid or complex optical environments where conventional imaging methods fail.
Polarization Holographic Imaging for High-throughput Microplastic Analysis
Researchers developed a polarization holography system integrated with deep learning for high-throughput microplastic detection and analysis in aqueous environments. The system enables dynamic, real-time multimodal monitoring of microplastics by leveraging polarization contrast to distinguish particles in liquid samples.
Micro-Objects Classification for Microplastic Pollution Detection using Holographic Images
Researchers developed a machine learning system that uses holographic 3D images to automatically classify microplastics in water samples, distinguishing them from other microscopic particles with high precision. Current microplastic monitoring is slow and labor-intensive, so automated detection tools are essential for large-scale environmental surveillance. This approach could significantly speed up the monitoring of microplastic pollution in aquatic environments.
Detection of microplastic release into water from plastic containers based on lensless digital holography
Researchers used lensless digital holography to detect microplastics released from plastic food delivery containers into water, demonstrating that the technique can differentiate microplastic particles from other impurities and quantify their release under realistic conditions.
Microplastic Identification via Holographic Imaging and Machine Learning
Researchers combined holographic imaging with machine learning algorithms to automatically identify and classify microplastics in water samples, achieving accurate particle detection without manual microscopy. This automated approach could significantly speed up microplastic monitoring in environmental samples.
Identification of Microplastics Based on the Fractal Properties of Their Holographic Fingerprint
Researchers developed an AI-enabled holographic imaging approach to identify microplastics in water using the fractal properties of their holographic fingerprints, offering a fast, label-free identification method.