Holographic Video Microscopy Research Articles

Measuring colloidomer hydrodynamics with holographic video microscopy.

In-line holographic video microscopy records a wealth of information about the microscopic structure and dynamics of colloidal materials. Powerful analytical techniques are available to retrieve that information when the colloidal particles are well separated. Large assemblies of close-packed particles create holograms that are substantially more challenging to interpret. We demonstrate that Rayleigh-Sommerfeld back propagation is useful for analyzing holograms of colloidomer chains, close-packed linear assemblies of micrometer-scale emulsion droplets. Colloidomers are fully flexible chains and undergo three-dimensional configurational changes under the combined influence of random thermal forces and hydrodynamic forces. We demonstrate the ability of holographic reconstruction to track these changes as colloidomers sediment through water in a horizontal slit pore. Comparing holographically measured configurational trajectories with predictions of hydrodynamic models both validates the analytical technique for this valuable class of self-organizing materials and also provides insights into the influence of geometric confinement on colloidomer hydrodynamics.

Machine learning enables precise holographic characterization of colloidal materials in real time.

Holographic particle characterization uses in-line holographic video microscopy to track and characterize individual colloidal particles dispersed in their native fluid media. Applications range from fundamental research in statistical physics to product development in biopharmaceuticals and medical diagnostic testing. The information encoded in a hologram can be extracted by fitting to a generative model based on the Lorenz-Mie theory of light scattering. Treating hologram analysis as a high-dimensional inverse problem has been exceptionally successful, with conventional optimization algorithms yielding nanometer precision for a typical particle's position and part-per-thousand precision for its size and index of refraction. Machine learning previously has been used to automate holographic particle characterization by detecting features of interest in multi-particle holograms and estimating the particles' positions and properties for subsequent refinement. This study presents an updated end-to-end neural-network solution called CATCH (Characterizing and Tracking Colloids Holographically) whose predictions are fast, precise, and accurate enough for many real-world high-throughput applications and can reliably bootstrap conventional optimization algorithms for the most demanding applications. The ability of CATCH to learn a representation of Lorenz-Mie theory that fits within a diminutive 200 kB hints at the possibility of developing a greatly simplified formulation of light scattering by small objects.

The Strengths of Total Holographic Video Microscopy in Detecting Sub-Visible Protein Particles in Biopharmaceuticals: A Comparison to Flow Imaging and Resonant Mass Measurement

Determination of subvisible particle (SVP) content in biopharmaceuticals is a prerequisite to ensure the quality of liquid biopharmaceutical products. Here, we present a comparison of the recently introduced holographic video microscopy (total holographic characterization, THC) with two orthogonal and well-established analytical technologies: micro flow imaging (MFI) and resonant mass measurement (RMM). The capabilities of the THC were investigated under conditions commonly applied in drug product development. Three different antibody products were used at different concentrations and formulations to cover a wide range of realistic use-cases. The comparison was particularly focused on protein aggregates to investigate the applicability of THC to this critical class of particles in drug product development. Protein concentrations up to 100 mg/ml were investigated covering a broad range of viscosity and refractive indices, both important parameters in particle detection. The comparison reveals that THC is highly sensitive to detect protein aggregates in a size range from 0.5 µm to 10 µm. THC shows a significant superiority to FI and RMM in detecting heterogenous protein aggregates which often appear as transparent and porous particles. Additionally, THC needs very small sample amount of about 30 µl and short measurement times, making it applicable for early development stages and high-throughput approaches. These results show that THC is a valuable supplement to the existing particle characterization method portfolio in drug product development.

Interpreting holographic molecular binding assays with effective medium theory.

Holographic molecular binding assays use holographic video microscopy to directly detect molecules binding to the surfaces of micrometer-scale colloidal beads by monitoring associated changes in the beads' light-scattering properties. Holograms of individual spheres are analyzed by fitting to a generative model based on the Lorenz-Mie theory of light scattering. Each fit yields an estimate of a probe bead's diameter and refractive index with sufficient precision to watch a population of beads grow as molecules bind. Rather than modeling the molecular-scale coating, however, these fits use effective medium theory, treating the coated sphere as if it were homogeneous. This effective-sphere analysis is rapid and numerically robust and so is useful for practical implementations of label-free immunoassays. Here, we assess how measured effective-sphere properties reflect the actual properties of molecular-scale coatings by modeling coated spheres with the discrete-dipole approximation and analyzing their holograms with the effective-sphere model.

Quantitative Differentiation of Protein Aggregates From Other Subvisible Particles in Viscous Mixtures Through Holographic Characterization

We demonstrate the use of holographic video microscopy to detect individual subvisible particles dispersed in biopharmaceutical formulations and to differentiate them based on material characteristics measured from their holograms. The result of holographic analysis is a precise and accurate measurement of the concentrations and size distributions of multiple classes of subvisible contaminants dispersed in the same product simultaneously. We demonstrate this analytical technique through measurements on model systems consisting of human IgG aggregates in the presence of common contaminants such as silicone oil emulsion droplets and fatty acids. Holographic video microscopy also clearly identifies metal particles and air bubbles. Being able to differentiate and characterize the individual components of such heterogeneous dispersions provides a basis for tracking other factors that influence the stability of protein formulations including handling and degradation of surfactant and other excipients.

Holographic molecular binding assays

We demonstrate that holographic particle characterization can directly detect binding of proteins to functionalized colloidal probe particles by monitoring the associated change in the particles’ size. This label-free molecular binding assay uses in-line holographic video microscopy to measure the diameter and refractive index of individual probe spheres as they flow down a microfluidic channel. Pooling measurements on 104 particles yields the population-average diameter with an uncertainty smaller than 0.5 nm, which is sufficient to detect sub-monolayer coverage by bound proteins. We demonstrate this method by monitoring binding of NeutrAvidin to biotinylated spheres and binding of immunoglobulin G to spheres functionalized with protein A.

Above and beyond: holographic tracking of axial displacements in holographic optical tweezers.

How far a particle moves along the optical axis in a holographic optical trap is not simply dictated by the programmed motion of the trap, but rather depends on an interplay of the trap's changing shape and the particle's material properties. For the particular case of colloidal spheres in optical tweezers, holographic video microscopy reveals that trapped particles tend to move farther along the axial direction than the traps that are moving them and that different kinds of particles move by different amounts. These surprising and sizeable variations in axial placement can be explained by a dipole-order theory for optical forces. Their discovery highlights the need for real-time feedback to achieve precise control of colloidal assemblies in three dimensions and demonstrates that holographic microscopy can meet that need.

AC electrophoretic mobility of individual microscale colloidal particles measured using holographic video microscopy

Electrophoretic mobility has been widely used to evaluate the zeta potential of individual colloidal particles, which governs the stability of colloidal dispersions. We demonstrated two experimental methods to measure the AC electrophoretic mobility μ of micron-sized single particles using holographic video microscopy. The three-dimensional position of the particle was estimated by reconstructing the light field from its two-dimensional holographic image, using the Rayleigh-Sommerfeld back-propagation method. In a planar electric field setup, the height dependence of the measured value of μ in the cell enables us to evaluate the actual value of μ, without interference from electroosmotic flow. In a vertical setup, the true value of μ can be directly evaluated by minimizing the influence of the electrode polarization, using a thick cell and a high-frequency electric field. The estimated values of μ obtained using both methods agree with that from conventional electrophoretic light scattering. We also evaluated the distribution of μ values within a colloidal dispersion.

Holographic Characterization of Protein Aggregates in the Presence of Silicone Oil and Surfactants

Characterizing protein aggregates in the presence of silicone oil is a long standing challenge for the pharmaceutical industry. Silicone oil is often used as a lubricant in devices that deliver and store therapeutic protein products and has been linked to protein aggregation, which can compromise a drug’s effectiveness or cause autoimmune responses in patients. Most traditional technologies cannot quantitatively distinguish protein aggregates and silicone oil in their native formulations for sizes less than 5 μm. We use holographic video microscopy to study protein aggregation to demonstrate its capability to quantitatively distinguish protein aggregates and silicone oil in the presence of varying amounts of the surfactants SDS and polysorbate 80 in the size range of 0.5-10 μm without the need for dilution or special sample preparation. We show that SDS denatures proteins and stabilizes silicone oil. We also show that polysorbate 80 may limit protein aggregate formation if it is added to an IgG solution before introducing silicone oil.

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.

Holographic Characterization of Protein Aggregates

We demonstrate how holographic video microscopy can be used to detect, count, and characterize individual micrometer-scale protein aggregates as they flow down a microfluidic channel in their native buffer. Holographic characterization directly measures the radius and refractive index of subvisible protein aggregates and offers insights into their morphologies. The measurement proceeds fast enough to build up population averages for time-resolved studies and lends itself to tracking trends in protein aggregation arising from changing environmental factors. Information on individual particle's refractive indexes can be used to differentiate protein aggregates from such contaminants as silicone droplets. These capabilities are demonstrated through measurements on samples of bovine pancreas insulin aggregated through centrifugation and of bovine serum albumin aggregated by complexation with a polyelectrolyte. Differentiation is demonstrated with samples that have been spiked with separately characterized silicone spheres. Holographic characterization measurements are compared with results obtained with microflow imaging and dynamic light scattering.

Stimulus-responsive colloidal sensors with fast holographic readout

Colloidal spheres synthesized from polymer gels swell by absorbing molecules from solution. The resulting change in size can be monitored with nanometer precision using holographic video microscopy. When the absorbate is chemically similar to the polymer matrix, swelling is driven primarily by the entropy of mixing, and is limited by the surface tension of the swelling sphere and by the elastic energy of the polymer matrix. We demonstrate through a combination of optical micromanipulation and holographic particle characterization that the degree of swelling of a single polymer bead can be used to measure the monomer concentration in situ with spatial resolution comparable to the size of the sphere.

Rapid, High-Throughput Tracking of Bacterial Motility in 3D via Phase-Contrast Holographic Video Microscopy

Tracking fast-swimming bacteria in three dimensions can be extremely challenging with current optical techniques and a microscopic approach that can rapidly acquire volumetric information is required. Here, we introduce phase-contrast holographic video microscopy as a solution for the simultaneous tracking of multiple fast moving cells in three dimensions. This technique uses interference patterns formed between the scattered and the incident field to infer the three-dimensional (3D) position and size of bacteria. Using this optical approach, motility dynamics of multiple bacteria in three dimensions, such as speed and turn angles, can be obtained within minutes. We demonstrated the feasibility of this method by effectively tracking multiple bacteria species, including Escherichia coli, Agrobacterium tumefaciens, and Pseudomonas aeruginosa. In addition, we combined our fast 3D imaging technique with a microfluidic device to present an example of a drug/chemical assay to study effects on bacterial motility.

Celebrating Soft Matter’s 10th Anniversary: Monitoring colloidal growth with holographic microscopy

Holographic video microscopy offers valuable and previously unavailable insights into the progress of colloidal synthesis by providing measurements of the size and refractive index of individual colloidal particles in the dispersion. These measurements are precise enough to track subtle changes in particles' properties and rapid enough for real-time process control. We demonstrate this technique by applying it to the synthesis of monodisperse samples of crosslinked polydimethysiloxane (PDMS) spheres. The measured time dependence of these spheres' most probable radius is consistent with the LaMer model for colloidal growth. The joint distribution of size and refractive index, however, also reveals a small proportion of undersize, lower-density spheres. Trends in the distribution's time evolution offer insights into their origin. Applied over longer time periods, holographic characterization also tracks how the newly-synthesized spheres age, and illuminates the aging mechanism.

Machine-learning approach to holographic particle characterization.

Holograms of colloidal dispersions encode comprehensive information about individual particles' three-dimensional positions, sizes and optical properties. Extracting that information typically is computationally intensive, and thus slow. Here, we demonstrate that machine-learning techniques based on support vector machines (SVMs) can analyze holographic video microscopy data in real time on low-power computers. The resulting stream of precise particle-resolved tracking and characterization data provides unparalleled insights into the composition and dynamics of colloidal dispersions and enables applications ranging from basic research to process control and quality assurance.

Measuring Boltzmann's constant through holographic video microscopy of a single colloidal sphere

The trajectory of a colloidal sphere diffusing in water records a history of the random forces exerted on the sphere by thermally driven fluctuations in the suspending fluid. The trajectory therefore can be used to characterize the spectrum of thermal fluctuations and thus to obtain an estimate for Boltzmann's constant. We demonstrate how to use holographic video microscopy to track a colloidal sphere's three-dimensional motions with nanometer precision while simultaneously measuring its radius to within a few nanometers. The combination of tracking and characterization data reliably yields Boltzmann's constant to within two percent and also provides the basis for many other useful and interesting measurements in statistical physics, physical chemistry, and materials science.

Holographic particle-streak velocimetry

We present a way to measure the positions and instantaneous velocities of micrometer-scale colloidal spheres using a single holographic snapshot obtained through in-line holographic video microscopy. This method builds on previous quantitative analyses of colloidal holograms by accounting for blurring that occurs as a sphere moves during the camera's exposure time. The angular variance of a blurred hologram's radial intensity profile yields both the magnitude and direction of a sphere's in-plane velocity. At sufficiently low speeds, the same hologram also can be used to characterize other properties, such as the sphere's radius and refractive index.

Holographic characterization of individual colloidal spheres' porosities

Holograms of colloidal spheres recorded through holographic video microscopy can be analyzed with the theory of light scattering to measure individual spheres' sizes and refractive indexes with part-per-thousand resolution. This information, in turn, can be interpreted to estimate each sphere's porosity.

Strategies for three-dimensional particle tracking with holographic video microscopy

The video stream captured by an in-line holographic microscope can be analyzed on a frame-by-frame basis to track individual colloidal particles' three-dimensional motions with nanometer resolution. In this work, we compare the performance of two complementary analysis techniques, one based on fitting to the exact Lorenz-Mie theory and the other based on phenomenological interpretation of the scattered light field reconstructed with Rayleigh-Sommerfeld back-propagation. Although Lorenz-Mie tracking provides more information and is inherently more precise, Rayleigh-Sommerfeld reconstruction is faster and more general. The two techniques agree quantitatively on colloidal spheres' in-plane positions. Their systematic differences in axial tracking can be explained in terms of the illuminated objects' light scattering properties.

Rotational and translational diffusion of copper oxide nanorods measured with holographic video microscopy

We use holographic video microscopy to track the three-imensional translational and rotational diffusion of copper oxide nanorods suspended in water. Rayleigh-Sommerfeld back-propagation of a single holographic snapshot yields a volumetric reconstruction of the nanorod's optical scattering pattern, from which we estimate both its dimensions and also its instantaneous position and orientation. Analyzing a video sequence yields measurements of the freely diffusing nanorod's dynamics, from which we estimate the technique's resolution.