We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
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.
2-D and 3-D Raman mapping are powerful imaging techniques for creating chemical images and compositional analysis of materials. Nevertheless, integration and implementation of Raman mapping on a microfluidic system turns out to be arduous due to several challenges, including the movement of sample, low efficiency of detection, low signal-to-noise ratio, and long measurement times. This study introduces a multimodal microchip for concurrent measurement of Raman signal in both forward- and backward-scattering modes from microparticles (MPs) in an aqueous environment. The microchip integrates microfluidic, acoustic, and optical components, synergistically manipulating and stabilizing a cluster of MPs through the application of precise local acoustic forces. The optical components orchestrate the laser and Raman signals, effectively addressing the total internal reflection challenge and significantly enhancing the Raman signal collection efficiency by a factor of ≈ 32 in comparison to a conventional microfluidic chip. The adoption of dual-mode measurement of Raman signal facilitates the creation of a 2-D Raman image, offering a representative view of a 3-D volume image. This practical methodology not only expedites the measurement process from 4 days to 1.5 hours, but also provides a comprehensive analysis of the clustered entities. To benchmark the versatility and applicability of the developed microchip, the Raman signal of microplastics of different types and human hepatoma HepG2 cells are fully investigated. The meticulous bottom-up approach presented herein holds great promise for advancing efficient and high-throughput sample monitoring in aqueous conditions using Raman spectroscopy.
More Papers Like This
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.
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.
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.
Microfluidic Detection and Analysis of Microplastics Using Surface Nanodroplets
AI summary Read the abstract
Researchers developed a microfluidic device that uses tiny surface droplets to capture and analyze microplastics as small as 10 micrometers from water samples. The captured particles can be examined under a microscope and identified by type using Raman spectroscopy without removing them from the device. The method offers a simpler, faster, and more affordable way to detect small microplastics compared to conventional filtration techniques.
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.