We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Advancing Raman imaging in opto-acousto-fluidic microchips
AI summary Read the abstract
This paper presents advances in integrating Raman imaging with opto-acousto-fluidic microchip systems, improving signal collection efficiency and reducing measurement time for chemical imaging of particles in flow, with applications for real-time microplastic identification in water samples.
Two-dimensional (2D) and three-dimensional (3D) Raman mapping are powerful techniques for chemical imaging and compositional analysis of materials. However, their integration with microfluidic systems faces challenges such as low signal collection efficiency, sample movement, long measurement times, and suboptimal detection in aqueous environments. In this study, we present a multimodal opto-acousto-fluidic microchip that enables simultaneous acquisition of forward- and backward-scattering Raman signals from microparticles (MPs) in liquid samples. The microchip combines microfluidic, acoustic, and optical components to achieve stable particle trapping and enhanced signal detection. Acoustic forces are used to manipulate and cluster MPs within the microchannel, ensuring their stable positioning during Raman measurements. To address optical signal losses caused by total internal reflection, the chip is equipped with half-ball lenses and a spherical reflector, significantly improving the Raman signal collection efficiency by a factor of ≈32 compared to conventional microfluidic chips. The dual-scattering mode allows for rapid 2D Raman mapping that accurately represents a 3D Raman image, reducing the total measurement time from four days to 1.5 hours. To evaluate the chip’s performance, the Raman spectra of various microplastics and human hepatoma (HepG2) cells were analyzed. The results demonstrate the capability of the chip for high-throughput and non-destructive analysis of samples in aqueous environments. This approach shows potential for a broad range of applications, including environmental monitoring and biomedical research, where efficient and accurate Raman imaging is essential.
More Papers Like This
An opto-acousto-fluidic microchip for efficient Raman spectroscopy of microparticles in aqueous environment
AI summary Read the abstract
Researchers developed a novel microchip that combines microfluidics with acoustic trapping and Raman spectroscopy to analyze microparticles in water. The device uses sound waves to hold particles in place while laser-based chemical analysis identifies their composition in real time. The technology could improve the speed and accuracy of detecting microplastics in environmental water samples.
A microfluidic chip enables fast analysis of water microplastics by optical spectroscopy
AI summary Read the abstract
Researchers integrated a microfluidic chip with Raman and infrared spectroscopy to rapidly identify and characterize microplastics in drinking water, reducing analysis time compared to conventional methods.
Flow Raman Spectroscopy for the Detection and Identification of Small Microplastics
AI summary Read the abstract
Researchers developed a new method using flow Raman spectroscopy to detect and identify individual microplastic particles as small as 4 micrometers while they move through water. Unlike current methods that require complex sample preparation, this technique could work in real time for monitoring food and drinking water quality. The method can distinguish between different plastic types even after they have been weathered by the environment.
Echobeam: Acoustofluidic Cluster Analysis for Micro and Nanoplastic Identification Using Fluorescence and Raman Spectroscopy
AI summary Read the abstract
Researchers used sound waves to concentrate and levitate clusters of micro- and nanoplastics from water samples, then identified multiple plastic types simultaneously using Raman spectroscopy — a light-based chemical fingerprinting method. The system captured particles as small as 50 nanometers at water-quality-relevant concentrations, representing a significant step toward fast, reliable monitoring of nanoplastics in drinking water.
Backscattering-Based Discrimination of Microparticles Using an Optofluidic Multiangle Scattering Chip
AI summary Read the abstract
Researchers built an optofluidic microchip that can detect and distinguish individual particles in a flowing liquid using a combination of backscattered and forward- or side-scattered light. The chip's sensitivity to refractive index allowed it to differentiate plastic microparticles from other materials. This detection technology could be applied to automated microplastic identification in water samples.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.