Filter features such as high transmission, steep edges, low ripple and deep blocking are important when testing many samples, says Dr. Rance Fortenberry, director of technology at Alluxa
The current Covid-19 pandemic has highlighted the need for rapid and accurate quantitative analysis of dangerous pathogens, particularly Sars-Cov-2. Fortunately, our ability to determine the structure of new and dangerous viruses has continued to improve since the invention of polymerase chain reaction (PCR), which enables the production of billions of copies of a single DNA sample.
AOI and Snell’s Law
Angle of incidence (AOI) refers to the tilt of an optical filter with respect to the incident light (Figures 1a-1c). The simplest case is 0° AOI, where the incident light is normal to the filter.
Figures 1a-1c: Diagrams showing (a) normal AOI for an optical filter, (b) 45° AOI for a dichroic filter, and (c) 45° AOI for a high-reflectivity mirror.
CHA and F-Number
Cone half angle (CHA) describes the extent to which an incident beam is converging or diverging. It is defined as the angle between the AOI of the incident beam and the most oblique marginal ray (Figures 1a-1c). Therefore, a 0˚ CHA is synonymous with collimated light, and larger cone half angles designate a pronounced convergent or divergent beam.
Figures 1a-1c: Diagrams showing uncollimated light and cone half angle for (a) an optical filter at 0° AOI (b) a dichroic filter at 45° AOI, and (c) a high-reflectivity mirror at 45° AOI.
Cut-On and Cut-Off Wavelength
Cut-on wavelength describes an optical filter edge transition where transmission increases sharply over an increasing wavelength range, such as seen with a longpass filter. Conversely, cut-off wavelength describes an edge transition that decreases over a wavelength range, as seen with a shortpass filter. They are defined as the point on each respective edge where transmission reaches 50% of the peak (Figure 1), and are also known as 50% edge points and half-power wavelengths.
Figure 1: Cut-on and cut-off wavelengths, center wavelength (CWL), and full-width at half-maximum (FWHM) for a bandpass filter.
Surface Flatness Interferograms
Surface flatness describes the deviation between the surface of an optical component and a perfectly flat reference plano surface. Optical filter surface flatness is measured using an interferometer (typically a laser Fizeau interferometer) that represents this deviation as a pattern of light and dark bands known as interference fringes. Interference fringes are a visual representation of the destructive interference that results from the difference in phase between light reflected off the optical filter and the reference flat. Once the interferogram is obtained, post-processing software can be used to create a 3D model of the surface.
Interference filter spectra are temperature dependent. Extreme temperatures result in the expansion or contraction of the thin-film layers, resulting in a red shift with increasing temperature and a blue shift with decreasing temperature. This shift can be dramatic unless the filter has been specified and designed to operate in harsh environments, and is an especially important consideration for ultra-narrowband interference filters.
Surface quality specifications refer to the type and amount of allowable imperfections on each of the coated or uncoated surfaces of an optical component. Although some surface imperfections are purely cosmetic, many can introduce unwanted scattering or make the optical filter more susceptible to laser induced damage, resulting in decreased system performance.
Clear Aperture (CA)
Clear aperture (CA) is defined as the dimensional area of an optical component over which the specifications must be met (Figure 1). It is usually specified in terms of diameter for round parts or length and width for square or rectangular parts.
Thin-film optical filters are made by depositing alternating thin layers of materials with special optical properties onto a substrate, such as optical-grade glass. As light makes its way through the optical filter, its direction changes as it passes from one layer to the next, resulting in internal interference. This is due to the differences between the refractive indices of the materials in the dielectric thin-film coating. The configuration of the layers results in an optical filter that manipulates different wavelengths of light in different ways. Depending on the wavelength and type of optical filter, light can be reflected off of the filter, transmitted through it, or absorbed by it.
Figure 1. Diagram illustrating the difference between single and multiple return signals from an aerial laser altimeter.
Image credit: Alluxa
LIDAR (Light Detection and Ranging) is a highly versatile active remote sensing technique that is used in Earth and atmospheric sciences, autonomous vehicles, urban planning, and many other applications. Some of the most important components of LIDAR sensors are the filters that isolate target signals, while preventing sunlight and other extraneous light from reaching the detector. A wide variety of applications and sensor types exist, from laser altimeters to Raman LIDAR systems, all with different return signal strengths and LIDAR filter requirements. Therefore, LIDAR filters must be designed with the specific application and sensor type in mind in order to maximize signal-to-noise ratio.
Figure 1. Diagram illustrating the optical filters and light path of a fluorescence microscope.
Image credit: Alluxa
Fluorescence microscopes and imaging systems utilize fluorescent biomarkers and fluorescence filter sets to create bright, high contrast images of biomolecules, organelles, cells, tissues, organs, and organ systems. Because image quality is highly dependent on the design and overall performance of the fluorescence filters integrated into these systems, optical filter performance is just as important to the final image as sample preparation and fluorophore selection.
Figure 1. Diagram of a flow cytometer.
Image credit: Alluxa
Used across a variety of biological disciplines, fluorescence-based flow cytometers rapidly and accurately quantify cells and cellular components. As one of the most important components of these systems, flow cytometry filters must be specifically designed to maximize signal-to-noise ratios while minimizing crosstalk between fluorophores.
Advanced Optical Coating Design: An Open-Ended Approach
A Webinar With Dr. Angus MacLeod, President and CEO, Thin Film Center.
Date: 14 August 2018 01:00 PM Eastern Daylight Time
12:00 PM Central Daylight Time
10:00 AM Pacific Daylight Time
17:00 Greenwich Mean Time
Cost: Free to attend. Duration: Approximately one hour. Presented by: Dr. Angus Macleod, President and CEO, Thin Film Center Sponsored by: Alluxa, Eddy Company, PG&O, and Zemax
Alluxa Introduces HELIX™ Spectral Analysis System for Measuring High-Performance Thin-Film Optical Filters
HELIX™ Spectral Analysis System accurately measures the highest-performance optical filters.
The HELIX Spectral Analysis System has redefined measurement capabilities of high performance thin-film optical filters. HELIX is an instrument designed and developed by Alluxa Engineering staff to address the limitations of most commercially available spectrophotometers. The system’s capabilities are four-fold: it is able to track filter edges to OD7 (-70 dB), evaluate blocking to OD9 (-90 dB), resolve edges as steep as 0.4% relative to edge wavelength from 90% transmission to OD7, and resolve passbands that are as narrow as 0.1 nm at full width half maximum (FWHM).
High-performance, ultra-narrowband interference filters improve LIDAR signal-to-noise ratios.
Arguably the most versatile active remote sensing technique, LIDAR (Light Detection and Ranging) is used across platforms and across disciplines. Long known to be one of the most important technologies in Earth and atmospheric sciences, LIDAR is now being utilized for obstacle avoidance in autonomous vehicles, urban planning, security, infrastructure development, and many other applications. This surge of novel uses recently forced an influx of technological advancements and a renewed interest in LIDAR sensors that is driving down the cost and making the technology more accessible.
Dispersion controlled thin films boost the performance of NLO systems that utilize a femtosecond laser.
Some of the greatest recent advances seen in bio-imaging and detection are due to techniques that utilize non-linear optical (NLO) phenomena. These techniques have led to a Nobel prize, super-resolution images, label-free visualization of naturally occurring biomolecules, and greater freedom for working with in-vivo samples. Many NLO systems rely on the high peak pulse intensity of femtosecond lasers for signal generation. For this reason, the optical filters and mirrors integrated into these systems must have an appropriate laser damage rating, and the reflective components must be controlled for both group delay dispersion (GDD) and flatness. Choosing optical components that are specifically designed for NLO systems will ensure optimal signal strength, resolution, and image quality.
Advances in thin-film technology have given rise to new classes of multiband filters that redefine performance standards and drive innovation across a variety of disciplines.
Multiband filters can be categorized into a variety of classes that each presents its own set of fabrication challenges, placing limits on what is practically achievable and affecting the reliability of the thin-film manufacturing process. By understanding the scientific and industrial applications for multiband filters, the various filter classes and manufacturing possibilities are better understood.
Next-generation thin-film optical filters enhance excitation and emission in fluorescence imaging and detection systems.
Fluorescence based systems have revolutionized the way organisms, cells, and biomolecules are visualized and detected. However, challenges that are common in these instruments, such as bleedthrough, background autofluorescence, and poor signal-to-noise ratios (S/N), can reduce performance and lead to frustration.
Fortunately, performance and signal quality can be greatly improved by integrating next-generation thin-film optical filters into fluorescence based instruments. Because proper optical filtering boosts throughput and enables wide-scale blocking, it solves problems like backscatter and poor signal quality, resulting in bright, high-contrast images of the target molecules.
Because system performance greatly depends on filter quality, optical filters are arguably the most important component of any fluorescence based instrument. With that in mind, here are some important concepts that should be considered when selecting optical filters for a fluorescence based system.
Sophisticated monitor and deposition methods enable multi-cavity narrowband filters that push the envelope of performance.
Hard coated ultra-narrowband optical filters made using modern plasma processes offer much improved transmission, temperature stability and out of band blocking as compared to legacy soft coatings. These filters are used in optical systems as diverse as LIDAR (light detection and ranging), Doppler shift detection of plasma velocity, laser cleanup, chemical and gas sensing, as well as for cutting-edge astronomy and instrumentation applications.
A novel computer-controlled deposition system for multicavity filters improves their spectral precision and contrast.
Narrowband filters are a critical technology for a variety of applications such as lidar (light detection and ranging), laser cleanup, chemical and gas sensing, instrumentation, and astronomy. The design principles are well known and relatively simple. All designs rely on stacked Fabry-Pérot resonant cavities with dielectric reflectors composed of layers a quarter of a wavelength thick, spaced apart by cavities multiple half-wavelengths across. Several cavity filters are used in combination to ‘square up’ the spectral wave shape, resulting in the transmitted light having a ‘flat-topped’ spectrum when compared with that from light passed through single-cavity filters, which has a sharp, peaked spectral shape. Such multicavity filters also have much steeper rejection responses than single-cavity filters: the less-steep spectral slopes of single-cavity filters can compromise signal-to-noise in narrowband detection.
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