When people think of neutral density (ND) filters, they might consider the effects they have on photography. Photographers will use these filters to reduce or modify the intensity of all wavelengths or colors equally without changing the hue or color rendition. Fundamentally, the ND filter reduces the amount of light entering a lens. Legacy NanoSight systems including the NS300, NS500, and LM10 benefit from using the ND filter when analyzing particles with high refractive indices through nanoparticle tracking analysis (Figure 1). The ND filters that we use have an optical density of 1.0, which means they offer about a 10-11% reduction in the transmitted light passing through the lens across all laser wavelengths.
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When people think of neutral density (ND) filters, they might consider the effects they have on photography. Photographers will use these filters to reduce or modify the intensity of all wavelengths or colors equally without changing the hue or color rendition. Fundamentally, the ND filter reduces the amount of light entering a lens. Legacy NanoSight systems including the NS300, NS500, and LM10 benefit from using the ND filter when analyzing particles with high refractive indices through nanoparticle tracking analysis (Figure 1). The ND filters we use have an optical density of 1.0, which means they offer about a 10-11% reduction in the transmitted light passing through the lens across all laser wavelengths.
Figure 1. Inserting a neutral density filter
Occasionally, particles with high refractive indices start to exhibit undesired “flaring”, especially when imaged with high camera settings. This flaring can affect the legacy NTA software’s ability to distinguish the particle from the flare scattering and place crosshairs accurately on the center of pixels representing true particles (Figure 2). The software might incorrectly identify the bright flare center as a particle, leading to the placement of multiple crosshairs on the flaring around the particles, which results in “the detection” of smaller, non-existent particles. If visible within a specific time, these flare-induced tracks can appear in the size distribution (Fig 3).
The neutral density filter (ND) reduces the appearance of the bright flare scattering and sharpens the image of particles, making them appear more contained. By reducing flaring around particles, a clearer image is generated – this enables more accurate particle identification and thereby improves the determination of mean square displacement (MSD). The MSD is used to calculate the size of the particle through the Stokes-Einstein equation (Equation 1). Particles that benefit from the ND filter include (but are not limited to) nanobubbles and larger silica particles.
Figure 2. Field of view without neutral density filter (A) and with a neutral density filter (B). ND filter mitigates flaring around particles. This is evident by the presence and subsequent absence of extraneous crosshairs.
Equation 1. Stokes-Einstein equation where MSD is the mean-square displacement of particles, KB is Boltzmann Constant, T is temperature, η is viscosity, and dh is the hydrodynamic diameter.
When analyzing particles without the use of ND filters, data can vary drastically across size and concentration depending on changes to detection threshold, camera level, and focus settings. Applying ND filters normalizes the variations, resulting in more consistent data across the various parameters. This improvement can be seen in the distribution plots before and after the application of ND filters (Figure 3 and Video 1).
Figure 3. Particle distribution without a neutral density filter shows undesired particle counts from flaring and is then mitigated once the neutral density filter is inserted.
Video 1: Particles with and without a neutral density filter. View this video online here.
The NanoSight Pro, equipped with NS Xplorer software, minimizes the need for ND filters by leveraging advanced machine learning algorithms that can accurately mark the particle centers. This includes capturing very dim particles, and providing more accurate analysis while simultaneously running additional workflows. NS Xplorer effectively distinguishes particles from the flare scattering to make particle tracking more accurate than ever. Dynamic, frame-to-frame particle identification ensures accurate particle identification. This mitigates confirmation bias and reduces human error. NanoSight Pro’s Particle Detection Neural Network Model (NN) was trained on thousands of NTA images with various levels of complexity. The data was assessed by human counterparts and validated precision and accuracy through the development process.
What’s more, NS Xplorer software saves time when setting processing parameters. While users can select the ND filter to mitigate the effect of flaring, the NS Xplorer software is already doing the heavy lifting.