Fast custom wavelet analysis technique for single molecule detection and identification.

Many sensors operate by detecting and identifying individual events in a time-dependent signal which is challenging if signals are weak and background noise is present. We introduce a powerful, fast, and robust signal analysis technique based on a massively parallel continuous wavelet transform (CWT) algorithm. The superiority of this approach is demonstrated with fluorescence signals from a chip-based, optofluidic single particle sensor. The technique is more accurate than simple peak-finding algorithms and several orders of magnitude faster than existing CWT methods, allowing for real-time data analysis during sensing for the first time. Performance is further increased by applying a custom wavelet to multi-peak signals as demonstrated using amplification-free detection of single bacterial DNAs. A 4x increase in detection rate, a 6x improved error rate, and the ability for extraction of experimental parameters are demonstrated. This cluster-based CWT analysis will enable high-performance, real-time sensing when signal-to-noise is hardware limited, for instance with low-cost sensors in point of care environments.

Signal-to-noise Enhancement in Optical Detection of Single Viruses with Multi-spot Excitation.

We present fluorescence detection of single H1N1 viruses with enhanced signal to noise ratio (SNR) achieved by multi-spot excitation in liquid-core anti-resonant reflecting optical waveguides (ARROWs). Solid-core Y-splitting ARROW waveguides are fabricated orthogonal to the liquid-core section of the chip, creating multiple excitation spots for the analyte. We derive expressions for the SNR increase after signal processing, and analyze its dependence on signal levels and spot number. Very good agreement between theoretical calculations and experimental results is found. SNR enhancements up to 5x104 are demonstrated.

Improved environmental stability for plasma enhanced chemical vapor deposition SiO2 waveguides using buried channel designs.

Ridge and buried channel waveguides (BCWs) made using plasma-enhanced chemical vapor deposition SiO2 were fabricated and tested after being subjected to long 85°C water baths. The water bath was used to investigate the effects of any water absorption in the ridge and BCWs. Optical mode spreading and power throughput were measured over a period of three weeks. The ridge waveguides quickly absorbed water within the critical guiding portion of the waveguide. This caused a nonuniformity in the refractive index profile, leading to poor modal confinement after only seven days. The BCWs possessed a low index top cladding layer of SiO2, which caused an increase in the longevity of the waveguides, and after 21 days, the BCW samples still maintained ~20% throughput, much higher than the ridge waveguides, which had a throughput under 5%.

Optofluidic wavelength division multiplexing for single-virus detection.

Optical waveguides simultaneously transport light at different colors, forming the basis of fiber-optic telecommunication networks that shuttle data in dozens of spectrally separated channels. Here, we reimagine this wavelength division multiplexing (WDM) paradigm in a novel context--the differentiated detection and identification of single influenza viruses on a chip. We use a single multimode interference (MMI) waveguide to create wavelength-dependent spot patterns across the entire visible spectrum and enable multiplexed single biomolecule detection on an optofluidic chip. Each target is identified by its time-dependent fluorescence signal without the need for spectral demultiplexing upon detection. We demonstrate detection of individual fluorescently labeled virus particles of three influenza A subtypes in two implementations: labeling of each virus using three different colors and two-color combinatorial labeling. By extending combinatorial multiplexing to three or more colors, MMI-based WDM provides the multiplexing power required for differentiated clinical tests and the growing field of personalized medicine.

Electro-optical detection of single λ-DNA.

Single λ-DNA molecules are detected on a nanopore-gated optofluidic chip electrically and optically. Statistical variations in the single particle trajectories are used to predict the intensity distribution of the fluorescence signals.