Holograms Of Particles Research Articles

Total Holographic Characterization of Large Particle Contaminants in Chemical Mechanical Polishing (CMP) Slurries

Nanoparticle slurries are widely used in semiconductor CMP processing. Accurately evaluating quality attributes of CMP slurries can be challenging for standard optical methods. Ceria slurries can be too optically dense and inhomogeneous for most optical measurements. Diluting the slurry can induce agglomeration or break up the agglomerates already present in the slurry. Previous studies of silica CMP slurries demonstrated that Total Holographic Characterization (THC) is effective for monitoring agglomeration in slurries. THC uses particle holograms to determine particle size and composition. Ceria nanoparticles have higher refractive indexes than silica nanoparticles, and produce more scattered light, which can reduce the signal of measurements of agglomerates, making accurate, reproducible measurements more challenging. Ceria slurry was successfully analyzed at concentrations typically used in semiconductor processing. Effective-medium theory is used to understand the variation in refractive index of large particle contaminants as compared to native slurry nanoparticles and other contaminants such as pad debris.

Polar optical flow network: extracting overlapped holograms of dynamic particles.

Digital holography with lensless in-line setup has been extensively used in particle field measurements. As particle concentration increases, the holograms of dynamic particles locating at different depths tend to superpose with each other with incoherent overlap, hampering effective measurement of individual particles with incomplete information. Drawing inspiration from suborbicular nature of the in-line holographic fringes, in this study, we propose an optical flow method in polar coordinates to mitigate the overlap issue. The approach employs a radial transformer-enhanced network that leverages both the radial and angular characteristics of the polar hologram. Through ablation tests and experimental results, we have demonstrated the effectiveness and superiority of our proposed method.

Digital In-Line Holography With The Photonic Jet Method For Three-Dimensional Flow Characterization: Numerical Standards And Accuracy Limits

A set of MATLAB® routines and a graphical user interface (GUI) to model holograms of homogeneous, coated and multilayered particles are introduced. Based, on Lorenz-Mie theory, they are thought to be useful to the community working on the characterization of multiphase flows with Digital In-line Holography (DIH). Likewise, they can be used for the development of alternative approaches requiring numerical standards to evaluate their accuracy.

Digital In-Line Holography for Large-Volume Analysis of Vertical Motion of Microscale Marine Plankton and Other Particles

Measuring the distribution, characteristics and dynamics of marine microscale plankton and other particulate matter is essential to understand the vertical flux of elements in the marine environment. Digital holographic microscopy is a powerful approach for measuring these and studying their 3-D trajectories in a relatively large observation volume. This article demonstrates a compact, in-line digital holographic microscope that allows large-volume and high-resolution recording of marine particles through combining a continuous wave laser and a short exposure CMOS camera with efficient global shutters. A resolution of better than 10 μm is demonstrated in air and the minimum distinguishable size of targets recorded in water is approximately 20 μm. The maximum volumetric throughput of the setup is 1904 mL/s. The microscope can take motion blur free holograms of particles moving at up to 490 mm/s in theory, and has been tested in the ∼200-mm/s flowing water. The orientation of the measured volume improves the ability of digital holography in profiling sinking rates and active vertical migration. The system was tested onboard a research vessel to record a range of live plankton and other particles. The motion of some samples, including the sinking motion and swimming motion, was analyzed using custom developed image processing software. The experimental results show that the combination of high resolution and a large volume over which motion of sparse-distribution particles can be tracked, can improve the ability to differentiate between different types of marine particle and identify behaviors of live plankton.

Off-axis digital holography based on the Sagnac interferometer

In this paper an off-axis holography is put forward based on the Sagnac interferometer. The holograms of alumina-dust aerosol particles, an United States Air Force 1951 resolution plate and paramecium were recorded in the experiment. The diffraction integral of a plane hole derived from quantum theory is illustrated by the variation of the thickness of interference fringes. We use an angular spectrum diffraction algorithm to reconstruct the recorded hologram, and the reconstructed image with high resolution is obtained after eliminating the zero-order image and conjugate image. Examples involving alumina-dust aerosols demonstrate the technique’s in situ imaging capability for complex-shaped particles over a size range of roughly 10–50 µm micrometers. The system’s feasibility is analyzed and thus confirmed.

Dual-view tomographic particle holography: Modeling and light scattering effects

Dual-view tomographic particle holography, combining tomography and holography, is a promising approach to yield high accurate 3D measurement of particle field. A standard model of particle hologram has been developed in the framework of generalized Lorenz-Mie theory to model and investigate the light scattering effects on three configurations of dual-view tomographic particle holography, that is, dual-beam dual-view Gabor inline holography, single beam dual-view combining Gabor inline holography with off-axis scattering holography, and single beam dual-view off-axis scattering holography. Dual-beam dual-view Gabor inline holography is dominated by the traditional Gabor inline hologram, but the two light scattering fields bring about small amplitude off-axis scattering inline recording hologram, negligible self-reference hologram and lensless Fourier hologram. The off-axis scattering inline recording hologram can produce additional glare points in the reconstructed particle image. The off-axis scattering holography reconstructs multiple glare light, and generates more than one intersections in the merged 3D reconstructed field in tomographic particle holography, leading to possible ghost particle image and implying new algorithm for particle detection to be developed. This model can provide standard hologram to processing algorithm development.

A Novel Method Based on Optofluidic Lensless-Holography for Detecting the Composition of Oil Droplets

A novel method based on optofluidic lensless-holography for detecting the composition of oil droplets is presented in this paper. The three most important characteristic parameters in the holograms of oil droplets and particles with different sizes were compared and analyzed, and the correlation between the characteristic parameters and the molecular structure (different number of carbon-hydrogen bonds) of oil droplet was determined. In addition, the experimental results show that the detection results of the newly developed lensless holographic imaging system are not affected by the surface properties of oil droplets. By detecting PEA (amino-terminated polyoxypropylene, a fuel additive), it is demonstrated that the developed method is sufficiently sensitive to the trace amount of additives or impurities in the oil. To the best of our knowledge, this is the first time that the lensless-holography combined with the optofluidic technology has been used to detect the composition of oil droplets. The portability of the developed device is very suitable for real-time on-site detection.

CATCH: Characterizing and Tracking Colloids Holographically Using Deep Neural Networks.

In-line holographic microscopy provides an unparalleled wealth of information about the properties of colloidal dispersions. Analyzing one colloidal particle's hologram with the Lorenz-Mie theory of light scattering yields the particle's three-dimensional position with nanometer precision while simultaneously reporting its size and refractive index with part-per-thousand resolution. Analyzing a few thousand holograms in this way provides a comprehensive picture of the particles that make up a dispersion, even for complex multicomponent systems. All of this valuable information comes at the cost of three computationally expensive steps: (1) identifying and localizing features of interest within recorded holograms, (2) estimating each particle's properties based on characteristics of the associated features, and finally (3) optimizing those estimates through pixel-by-pixel fits to a generative model. Here, we demonstrate an end-to-end implementation that is based entirely on machine-learning techniques. Characterizing and Tracking Colloids Holographically (CATCH) with deep convolutional neural networks is fast enough for real-time applications and otherwise outperforms conventional analytical algorithms, particularly for heterogeneous and crowded samples. We demonstrate this system's capabilities with experiments on free-flowing and holographically trapped colloidal spheres.

Machine learning holography for 3D particle field imaging

We propose a new learning-based approach for 3D particle field imaging using holography. Our approach uses a U-net architecture incorporating residual connections, Swish activation, hologram preprocessing, and transfer learning to cope with challenges arising in particle holograms where accurate measurement of individual particles is crucial. Assessments on both synthetic and experimental holograms demonstrate a significant improvement in particle extraction rate, localization accuracy and speed compared to prior methods over a wide range of particle concentrations, including highly dense concentrations where other methods are unsuitable. Our approach can be potentially extended to other types of computational imaging tasks with similar features.

Design and Validation of a Holographic Particle Counter.

An in-line holographic particle counter concept is presented and validated where multiple micrometer sized particles are detected in a three dimensional sampling volume, all at once. The proposed Particle Imaging Unit is capable of detecting holograms of particles which sizes are in the lower m- range. The detection and counting principle is based on common image processing techniques using a customized Hough Transform with a result directly relating to the particle number concentration in the recorded sampling volume. The proposed counting unit is mounted ontop of a Condensation Nucleus Magnifier for comparison with a commercial TSI-3775 Condensation Particle Counter (CPC). The concept does not only allow for a precise in-situ determination of low particle number concentrations but also enables easy upscaling to higher particle densities (e.g., ) through its linear expandability and option of cascading. The impact of coincidence at higher particle densities is shown and two coincidence correction approaches are presented where, at last, its analogy to the coincidence correction methods used in state-of-the-art CPCs is identified.

Machine-learning techniques for fast and accurate feature localization in holograms of colloidal particles.

Holograms of colloidal particles can be analyzed with the Lorenz-Mie theory of light scattering to measure individual particles' three-dimensional positions with nanometer precision while simultaneously estimating their sizes and refractive indexes. Extracting this wealth of information begins by detecting and localizing features of interest within individual holograms. Conventionally approached with heuristic algorithms, this image analysis problem can be solved faster and more generally with machine-learning techniques. We demonstrate that two popular machine-learning algorithms, cascade classifiers and deep convolutional neural networks (CNN), can solve the feature-localization problem orders of magnitude faster than current state-of-the-art techniques. Our CNN implementation localizes holographic features precisely enough to bootstrap more detailed analyses based on the Lorenz-Mie theory of light scattering. The wavelet-based Haar cascade proves to be less precise, but is so computationally efficient that it creates new opportunities for applications that emphasize speed and low cost. We demonstrate its use as a real-time targeting system for holographic optical trapping.

Lifting degeneracy in holographic characterization of colloidal particles using multi-color imaging.

Micrometer sized particles can be accurately characterized using holographic video microscopy and Lorenz-Mie fitting. In this work, we explore some of the limitations in holographic microscopy and introduce methods for increasing the accuracy of this technique with the use of multiple wavelengths of laser illumination. Large high index particle holograms have near degenerate solutions that can confuse standard fitting algorithms. Using a model based on diffraction from a phase disk, we explain the source of these degeneracies. We introduce multiple color holography as an effective approach to distinguish between degenerate solutions and provide improved accuracy for the holographic analysis of sub-visible colloidal particles.

Simultaneous particle size and 3D position measurements of pulverized coal flame with digital inline holography

3D measurements of burning coal particles in the flame are challenging and of great interest. Digital inline holography is applied to perform 3D measurement of coal particle size and 3D position in a laboratory-scale pulverized coal flame. Pulsed laser beam illumination is used to record the coal particle hologram with clear holographic fringes in the presence of high refractive index gradient and strong turbulence. Over 30,000 coal particles have been reconstructed and analyzed. Results show that the particle size, 3D positions and particle number density distribution can be determined simultaneously. Digital inline holography presents to be a powerful tool in the 3D measurement of burning particles in a turbulent and reacting medium.

Effects of particle locations on reconstructed particle images in digital holography.

The intensity and phase reconstructed from digital in-line holograms by the convolution approach are analyzed. Distortions of particle images depending on their position in the plane transverse to the optical axis are identified. For this purpose, the object fields of numerically simulated particle holograms as well as of experimental data are reconstructed. The results of three-dimensional correlations of numerical and experimental data are superior when the numerically generated reference volumes are adapted to the transverse locations of the particle. Thus, proof is given that the characteristics of a particle image change distinctly with the transverse position of the particle and that the numerical model successfully simulates these changes. Hence, this knowledge can be integrated in future particle position detection algorithms.

Bayesian approach to analyzing holograms of colloidal particles.

We demonstrate a Bayesian approach to tracking and characterizing colloidal particles from in-line digital holograms. We model the formation of the hologram using Lorenz-Mie theory. We then use a tempered Markov-chain Monte Carlo method to sample the posterior probability distributions of the model parameters: particle position, size, and refractive index. Compared to least-squares fitting, our approach allows us to more easily incorporate prior information about the parameters and to obtain more accurate uncertainties, which are critical for both particle tracking and characterization experiments. Our approach also eliminates the need to supply accurate initial guesses for the parameters, so it requires little tuning.

Evaluation of Algorithms for Automatic Data Extraction from Digital Holographic Images of Particles

The procedures and algorithms providing a numerical implementation of the physical process of image reconstruction from in-line particle holograms are discussed. The methods are proposed which allow functioning of this process in an automatic mode and ensure data processing and extraction from digital particle holograms in a form convenient for subsequent physical interpretation. The experimental results on realization of these methods are presented, using digital holograms of plankton particles, air bubbles in water, and sand particles, obtained under laboratory conditions as examples.

Method of Digital Hologram Coding–Decoding and Holographic Image Processing Based on the Gabor Wavelet

Special features of an algorithm for coding-decoding of digital particle holograms and restoration of holographic particle images based on the Gabor wavelet are considered. The method involves the application of the decoded wavelet coefficients for the subsequent restoration of images from digital holograms. Results of approbation of the method to numerically calculated holograms and holograms of plankton particles are presented.

3D boundary line measurement of irregular particle with digital holography

The morphology of an irregular particle plays a key role in its interactions with the surroundings, and the 3D characterization of an irregular particle is of essential importance. Digital inline holography in Gabor configuration is applied to measure the 2D shadow texture and 3D position, as well as the 3D boundary line of irregular particles. The depth position of the 3D boundary line can be determined with a criterion of the local deviation of the directional gradient over a small tilted rectangle, which covers the interrogated boundary section. The method is firstly verified by rigorous simulated particle holograms and then by accurate experimental fiber hologram. The 3D boundary line of an irregular coal particle is also measured. Results show that the 3D boundary line of an irregular particle can be accurately retrieved from the reconstructed volumetric optical particle field. This capability of 3D boundary line measurement enables the application of digital inline holography to the 3D diagnostic of the morphology and dynamics of irregular objects, including 3D rotation.

Characterizations of transparent particle holography in near-field using Debye series.

The effects of the individual scattering process on the formations of both the particle hologram and its corresponding reconstructed three-dimensional particle image are investigated using the Debye series. A particle hologram model using the Debye series decomposes the object wave into different scattering modes and thus permits evaluating the effects of the individual scattering process [diffraction, reflection, transmission, refractions with (p-1) internal reflections] on the particle holography quantitatively. In the Gabor inline holography of a transparent droplet, the transmission light causes small discrepancies between the hologram fringes of an opaque particle (diffraction) and a transparent particle near the zero point of the Bessel-like modulation function, eventually giving rise to the glory spot in the center of the reconstructed dark particle image. For off-axis holography, this paper reveals the effects of reflection, particularly total reflection by bubbles, transmission, and refractions with (p-1) internal reflections of the scattered light on the formation and the reconstructed glory spot images of typical forward and backward off-axis holography.

Focal Image Plane Detection Based on Central Coordinate Point Spectral Value in Off-Axis Digital Particle Holography

A method to detect the focal image plane from a single off-axis digital particle hologram is proposed. This method utilizes the central coordinate point spectral value of the reconstructed particle image as focusing criterion to detect the focal image plane. It is found that the central coordinate point spectral values come into maximum when the reconstruction distance is equal to the actual distance that was used in experiment of hologram acquisition. Numerical simulations are given to validate the feasibility and effectiveness of the proposed method. The proposed method is a potential and better option for studying three dimensional particles by using digital holography.