In-line Holography Research Articles

Soft-X-Ray Vortex Beam Detected by Inline Holography

We demonstrate the in-line holography for soft x-ray vortex beam having an orbital angular momentum. A hologram is recorded as an interference between a Bragg diffraction wave from a fork grating and a divergence wave generated by a Fresnel zone plate. The obtained images exhibit fork-shaped interference fringes, which confirms the formation of the vortex beam. By analyzing the interference image, we successfully obtained the spiral phase distribution. The results demonstrate that the in-line holography technique is promising for the characterization of topological magnets, such as magnetic skyrmions.

Short U-net model with average pooling based on in-line digital holography for simultaneous restoration of multiple particles

We propose a short U-net model with average pooling to restore in-focus images of multiple transparent particles at their ground truth z-positions, while simultaneously removing their zero-order images, conjugate images, defocused images of other particles, and the noise associated with the optical system. Subsequently, we obtain the lateral location and diameter of each particle efficiently, thus acquiring the particle density within the captured volume. Simulations and experimental results demonstrate that the particle density can be acquired quickly via the proposed short U-net model. Moreover, average pooling processes piece-wise patterns more effectively than alternative methods.

Automated plankton classification from holographic imagery with deep convolutional neural networks

AbstractIn situ digital inline holography is a technique which can be used to acquire high‐resolution imagery of plankton and examine their spatial and temporal distributions within the water column in a nonintrusive manner. However, for effective expert identification of an organism from digital holographic imagery, it is necessary to apply a computationally expensive numerical reconstruction algorithm. This lengthy process inhibits real‐time monitoring of plankton distributions. Deep learning methods, such as convolutional neural networks, applied to interference patterns of different organisms from minimally processed holograms can eliminate the need for reconstruction and accomplish real‐time computation. In this article, we integrate deep learning methods with digital inline holography to create a rapid and accurate plankton classification network for 10 classes of organisms that are commonly seen in our data sets. We describe the procedure from preprocessing to classification. Our network achieves 93.8% accuracy when applied to a manually classified testing data set. Upon further application of a probability filter to eliminate false classification, the average precision and recall are 96.8% and 95.0%, respectively. Furthermore, the network was applied to 7500 in situ holograms collected at East Sound in Washington during a vertical profile to characterize depth distribution of the local diatoms. The results are in agreement with simultaneously recorded independent chlorophyll concentration depth profiles. This lightweight network exemplifies its capability for real‐time, high‐accuracy plankton classification and it has the potential to be deployed on imaging instruments for long‐term in situ plankton monitoring.

Accurate real-time monitoring of high particulate matter concentration based on holographic speckles and deep learning

Accurate real-time monitoring of particulate matter (PM) has emerged as a global issue due to the hazardous effects of PM on public health and industry. However, conventional PM monitoring techniques are usually cumbersome and require expensive equipments. In this study, Holo-SpeckleNet is proposed as a fast and accurate PM concentration measurement technique with high throughput using a deep learning based holographic speckle pattern analysis. Speckle pattern datasets of PMs for a wide range of PM concentrations were acquired by using a digital in-line holography microscopy system. Deep autoencoder and regression algorithms were trained with the captured speckle pattern datasets to directly measure PM concentration from speckle pattern images without any air intake device and time-consuming post image processing. The proposed technique was applied to predict various PM concentrations using the test datasets, optimize hyperparameters, and compare its performance with a convolutional neural network (CNN) algorithm. As a result, high PM concentration values can be measured over air quality index of 150, above which human exposure is unhealthy. In addition, the proposed technique exhibits higher measurement accuracy and less overfitting than the CNN with a relative error of 7.46 ± 3.92%. It can be applied to design a compact air quality monitoring device for highly accurate and real-time measurement of PM concentrations under hazardous environment, such as factories or construction sites.

Measurement of airblast atomization of low temperature kerosene with 25 kHz digital holography

Atomization of low temperature fuel is of great importance in a jet engine combustor, and its visualization and diagnostics are challenging, especially in the presence of shreds and ligaments. A 25 kHz picosecond pulsed digital inline holography system is applied to measure the spray produced by an airblast atomizer with low temperature kerosene. The breakup process of shreds and ligaments of -37∘C kerosene are visualized and analyzed, revealing the transition of liquid jet disintegrating into droplets under the atomizing air film. Three-dimensional positions and size distributions of droplets in spray are acquired. It is found that a decrease in the kerosene temperature increases shreds and ligaments in the spray, which eventually leads to reduction of droplet density and increase of droplet size, while increasing the air pressure can compensate the degradation. This work also demonstrates that high speed holographic imaging is a powerful tool in spray diagnostics and liquid breakup visualization.

Statistical Lagrangian evaporation rate of droplets released in a homogeneous quasi-isotropic turbulence

The effect of turbulence on the evaporation of diethyl ether droplets is investigated by means of digital in-line holography. Lagrangian tracking of thousands of droplets evidences an increase of the mean evaporation rate related not only to the mean relative velocity viewed by the droplets but also to the fluctuations of this velocity.

Effect of particle morphology on dust cloud dynamics

Dust explosions threaten the solids process industry. Parameters influencing dust explosions include particle size, chemical composition, and polydispersity; however, particle morphology is often overlooked. Studies show particle morphology impacts dust cloud minimum ignition energy (MIE) via heat transfer because higher specific surface results in lower conductive heat resistance. However, heat transfer is not the only factor impacting MIE; the effect of particle morphology on cloud dynamics is another important factor. This work focuses on the influence of particle morphology on cloud aerodynamics during MIE testing. A digital in-line holography method has been developed to measure aerodynamics of particles in an MIE apparatus. Results show higher cloud concentration and turbulence for irregularly shaped particles, and the implication on MIE is discussed. The present results aid understanding of particle morphology on cloud dynamics, which is crucial in determining the effect on explosion parameters such as MIE and the resulting risk assessment.

Time-resolved size, velocity, and temperature statistics of aluminum combustion in solid rocket propellants

The study of time-resolved aluminum combustion mechanisms is essential for understanding the deflagration of ammonium perchlorate-based metalized solid rocket propellants. In order to gain further insight into the performance of solid propellants, spatially and temporally resolved aluminum agglomerate particle dynamics are obtained by combining digital in-line holography (DIH) and two-color imaging pyrometry with high-speed acquisition at up to 20 kHz. Holography is used to find the size, three-dimensional position, and three-dimensional velocity evolution of agglomerates over time. Then, the temperature of individual particles is extracted from the high-speed imaging pyrometry. This diagnostic technique not only produces joint size, position, velocity, and temperature statistics over time, but also captures the combustion histories for thousands of particles per experiment. For the first time, these spatial and temporal dynamics of individual aluminum particulates are examined while they travel away from the propellant surface. Initial results demonstrate how aluminum agglomerates of similar size exhibit varying initial acceleration but similar steady-state velocities. Average velocity also decreases as particle size increases, which is consistent with viscous flow dynamics of small particles in convective flow. As they move further away from the propellant surface, large agglomerates also show a convergence to an average projected temperature between the melting point of aluminum oxide and the boiling point of aluminum. The average projected particle surface temperatures were measured to be 2494 ± 231 K. The method outlined in this work demonstrates a new capability for gathering the evolution of joint statistics for aluminum agglomerates in solid-rocket propellants. Future applications of this technique can be used to evaluate the detailed combustion mechanisms of existing or new propellant formulations.

Evaluation of laser diffraction-based particle size measurements using digital inline holography

The measurements of size distribution of small particles (e.g. dusts, droplets, bubbles, etc) are critical for a broad range of applications in environmental science, public health, industrial manufacturing, etc. Laser diffraction (LD), a widely used method for such applications, depends on model-based inversion with underlying assumptions on particle properties. Furthermore, the presence of sampling biases such as velocity differentials are often overlooked in simple ex-situ calibrations, which introduces as an additional source of error. In contrast, digital inline holography (DIH), a single camera coherent imaging technique, can both measure particle size distributions without the need for a model-based inversion and can directly provide information on the shape characteristics of the particles. In this study, we evaluate the performance of an LD system in characterizing polydisperse droplets produced in a flat fan spray using in-situ DIH based imaging as a reference. The systematic differences in the two techniques are examined. A droplet-trajectory-based correction for the LD-inferred size distributions is proposed to compensate for the observed differences. We validate the correction using NIST standard polydisperse particles undergoing differential settling, and then apply the correction to polydisperse spray droplet measurements. The correction improves agreement between LD and DIH size distributions for droplets over two orders of magnitude, but with LD still underestimating the fraction of droplets at sizes above ∼1 mm. This underestimation is possibly linked to the complex oscillatory and rotational motion of droplets which cannot be faithfully captured by measurement or modelled by the correction algorithm without additional information.

Dense particle tracking using a learned predictive model

The velocity resolution for particle tracking velocimetry is limited by the ability to link multiple instances of the same particle captured over time to form trajectories. This becomes increasingly difficult as the particle speed and concentration increase. To address these concerns, we propose a data-driven approach to generate a learned predictive model capable of accurately estimating future particle behavior. The model uses the long short-term memory (LSTM) recurrent neural network architecture to predict a particle’s velocity from its past positions. The model achieves increased linking performance with a negligible increase in the computational cost. Historical trajectories demonstrating the range of expected behaviors for a given application are used to train the model and can be collected using either of two methods. Manual filtering and selection can be used to select exemplary trajectories produced by an incomplete or inadequate method. Supplemental experiments with reduced tracer concentration can also produce training data. Both methods are demonstrated through experimental validation. The ability of the learned predictor to accurately link particles at tracer concentrations and flow speeds where traditional methods fail is demonstrated using two simulated flow cases. Three experimental cases are presented to demonstrate the performance of the proposed method under challenging conditions. Each case tracks the 3D positions of particles captured using microscopic digital inline holography although the approach is generalizable and can be applied to data obtained with other 2D and 3D PTV techniques. The selected cases—turbulent channel flow, flow through a T-junction, and swimming microorganisms—demonstrate the broad applicability of the proposed method to different fields with unique challenges.

Contrast-tuneable microscopy for single-shot real-time imaging

A novel real image in-line laser holography has enabled a tuneable image contrast, edge sharpness, and visualization of sub-wavelength structures, using a simple pair of filters and large-diameter lenses that can incorporate higher-order scattered beams. Demonstrated also are the accuracy in object sizing and the ease of imaging along the focal depth, based on a single-shot imaging via holographic principle. In addition, the use of broad, collimated laser beam for irradiation has led to a wider field of view, making it particularly useful for an extensive monitoring of, and sweeping search for, cells and microbial colonies and for the real-time imaging of cancer-cell dynamics.

Measuring particle dynamics in a fluidized bed using digital in-line holography

The quantification of three-dimensional (3D) particle behavior in a fluidized bed is crucial for improving the fundamental understanding and engineering design of such multiphase systems commonly used in industry. This work reports recent development and application of digital in-line holography (DIH) on the in-situ measurement of (a) solid circulation rate, (b) particle size distribution, (c) 3D location, and (d) velocity distribution in the particle field. A Hough-transform-based hologram processing algorithm was developed and tested over a range of flow conditions. Using a hopper system for precise control of particle feed rate, real-time solid flow rates and particle size distributions were measured using DIH. These measurements were then compared to high-precision mass flow measurements made using an electronic balance and size-distribution measurements using a QIPIC® particle size and shape analyzer. DIH is then employed to measure particulate flows in a small-scale circulating fluidized bed system by imaging the standpipe region with 12.7 mm ID. Solid circulation rates evolution was measured and its mean value was in good agreement with the pressure-based estimations. Moreover, DIH is demonstrated to be capable of resolving fine particles with 10 – 40 µm in size, resulting from attrition in the bed of solids. Different from large particles that is dominated by gravitational settling, the motion of small particles is mainly affected by the flow, which has great potential to be used to investigate flow conditions around the large particles.

High-speed digital in-line holography for in-situ dust cloud characterization in a minimum ignition energy device

Precise measurement of the minimum ignition energy (MIE) of combustible dust is crucial to safety in the process industries. The development of comprehensive methods for MIE dust cloud characterization is therefore highly desirable. The objective of this study is to investigate the application of high-speed digital in-line holography (DIH) for volumetric and in-situ characterization of dust clouds near the ignition zone of a Kühner MIKE3 MIE device. The dispersion behavior of borosilicate glass and soda-lime glass dust clouds are studied at 20 kHz. Size measurements, with successful detection down to 13 μm, are compared with Beckman Coulter particle size analyzer results. The 5-ms hologram videos also yield new transient particle volume, concentration, and velocity measurements. Sample sizes of 15–150 mg of dust powder are sufficient for each high-speed run. This work showcases new diagnostic capabilities that are accessible to dust explosion research and identifies areas for future research.

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.

Three-dimensional spatial distributions of agglomerated particles on and near the burning surface of aluminized solid propellant using morphological digital in-line holography

The particle size distribution of aluminum particles during combustion plays an important role in predicting the combustion performance of aluminized solid propellants. However, conventional models face difficulties in estimating the distributions of the agglomerated particles in propellants with novel or complex compositions. This study investigated the accuracies of the experimental techniques applied to propellant combustion to obtain the three-dimensional (3D) size distributions of agglomerated particles on the burning surface and particles in the plume. The 3D spatial distributions of aluminum particles on the burning surface and in the plume during solid aluminum composite propellant combustion were obtained using digital in-line holography (DIH) and morphological watershed image segmentation. Overall, 68,321 individual particles at distances of up to approximately 20 mm from the burning surface of the propellant were analyzed under 1 MPa pressure. The field of view results suggest that approximately 7% of the particles were detected on the burning surface, displaying a trimodal distribution in the particle size range of 30–1,200 μm, and almost all the particles (>96%) were agglomerated. The mean diameters and agglomeration fractions in the height range of 0–1 mm were larger than those in the overall combustion field; the mean diameters in this height range were similar to those of the particles on the burning surface. We found that the process of “second mergence” occurred at and up to 1 mm above the burning surface. As the height from the burning surface increased, the mean particle diameter and agglomeration fraction decreased rapidly; however, when the height exceeded 11 mm, the mean diameter did not change significantly, indicating that the particles had almost burned completely and formed condensed combustion products. Significant differences were found between the results obtained from the empirical agglomeration models and those obtained from the 3D DIH because these models were developed based on 2D data. The results presented herein further provided an insight into the agglomeration characteristics of aluminum particle combustion in composite propellants.

Holography and Coherent Diffraction Imaging with Low-(30-250 eV) and High-(80-300 keV) Energy Electrons: History, Principles, and Recent Trends.

In this paper, we present the theoretical background to electron scattering in an atomic potential and the differences between low- and high-energy electrons interacting with matter. We discuss several interferometric techniques that can be realized with low- and high-energy electrons and which can be applied to the imaging of non-crystalline samples and individual macromolecules, including in-line holography, point projection microscopy, off-axis holography, and coherent diffraction imaging. The advantages of using low- and high-energy electrons for particular experiments are examined, and experimental schemes for holography and coherent diffraction imaging are compared.

Tilted illumination in-line holographic velocimetry: Improvements in the axial spatial resolution

Two are the main limitations of in-line holography: the twin image problem and the poor spatial resolution in the optical axis direction. The twin image problem can be solved with the introduction of an imaging lens and a knife-edge aperture located at its focal plane. In this work, a theoretical analysis of the axial resolution with and without aperture is provided from the perspective of the Optical Diffraction Tomography. Theoretical analysis and controlled experiments with the different recording options, demonstrate that a small tilt of the illumination beam, together with a centered rectangular aperture, is a key parameter as it improves the spatial resolution along the optical axis during the location and tracking of a particle field.

A Comparison of Different Counting Methods for a Holographic Particle Counter: Designs, Validations and Results.

Digital Inline Holography (DIH) is used in many fields of Three-Dimensional (3D) imaging to locate micro or nano-particles in a volume and determine their size, shape or trajectories. A variety of different wavefront reconstruction approaches have been developed for 3D profiling and tracking to study particles’ morphology or visualize flow fields. The novel application of Holographic Particle Counters (HPCs) requires observing particle densities in a given sampling volume which does not strictly necessitate the reconstruction of particles. Such typically spherical objects yield circular intereference patterns—also referred to as fringe patterns—at the hologram plane which can be detected by simpler Two-Dimensional (2D) image processing means. The determination of particle number concentrations (number of particles/unit volume [#/cm]) may therefore be based on the counting of fringe patterns at the hologram plane. In this work, we explain the nature of fringe patterns and extract the most relevant features provided at the hologram plane. The features aid the identification and selection of suitable pattern recognition techniques and its parameterization. We then present three different techniques which are customized for the detection and counting of fringe patterns and compare them in terms of detection performance and computational speed.

Resolution-enhanced digital in-line holography by extension of the computational bandwidth

Higher resolution has always been the goal of imaging. Resolution enhancement in most holographic imaging methods are achieved by collecting more object spectrum. As a computational imaging technology, the resolution of digital holography is determined by the utilized bandwidth in both optical recording and numerical reconstruction. There is little study on whether the collected spectrum is effectively utilized during reconstruction. In this work, we propose a resolution-enhanced digital in-line holography under spherical wave illumination. The collected object spectrum, which cannot be fully used by conventional methods, is effectively utilized by the developed band-extended angular spectrum method with improved computational efficiency. Numerical analysis and optical experiments have been performed to demonstrate that the proposed method can effectively enhance the imaging resolution of digital in-line holography by extension of the computational bandwidth.

Three-dimensional measurement of a particle field using phase retrieval digital holography.

Digital inline holography (DIH) has long been used to measure the three-dimensional (3D) distribution of micrometer particles in suspensions. However, DIH experiences a virtual image problem that limits the particle density and the placement of the hologram plane relative to the sample volume. Here, we apply virtual-image-free phase retrieval digital holography (PRDH) to detect opaque particles in 3D volumes that exceed $ 2000\;{\rm particles}/{{\rm mm}^3} $2000particles/mm3. PRDH is based on recording two holograms whose planes are displaced along the optical axis, and then reconstructing the complete optical waves estimated by the iterative phase retrieval algorithm. Both numerical and experimental tests are performed, and results show that PRDH recovers the original 3D particle distributions even when the hologram planes are within the particle suspensions. Moreover, compared to single-hologram-based DIH, PRDH is proved to have better particle detection qualities. The uncertainty in the localization of particle centers is reduced to less than one particle diameter.