Simulation of Acoustophoretic Separation of Microplastic Particles in mkFluidic Lab-chip

Matviykiv, Oleh; Klymkovych, Tamara; Bokla, Nataliia; Lobur, Mykhaylo; Melnyk, Mykhaylo; Timofiejczuk, Anna

doi:10.1109/memstech49584.2020.9109452

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…Digital methods of signal processing and analysis allow for the determination of many of its essential features and characteristics in the field of time, frequency and amplitude [8]. Along with the progress in the application of the methods of signal identification being the subject of the observed acoustic phenomenon is justified the description of simultaneous analysis of time and frequency parameters/features.…”

Section: Review Of Drone Detection Methodsmentioning

confidence: 99%

Acoustic-Based Drone Detection Using Neural Networks – A Comprehensive Analysis

Paszkowski,

Gola,

Świć

2024

Adv. Sci. Technol. Res. J.

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The article presents and describes the implementation of research on the detection of a drone in an urban environment using of the sound features. The methods of drone detection were recognized on the basis of modeling and evaluation of the features of the audio and acoustic signal. The authors proposed the use of a neural network model for the needs of drone detection taking into account acoustic measurements in an anechoic chamber and in an urban environment. The final part presents the obtained results of the drone detection. For the purposes of detection, a neural network model was used in order to recognize the obtained images of the spectograms of sound sources.

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Section: Review Of Drone Detection Methodsmentioning

confidence: 99%

Acoustic-Based Drone Detection Using Neural Networks – A Comprehensive Analysis

Paszkowski,

Gola,

Świć

2024

Adv. Sci. Technol. Res. J.

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“…The separation efficiency we reported for PS MPs largely agrees with results obtained by Akiyama et al (2020) [74] for the same size microspheres, although our device construction and operating parameters differed. Prior work, including the experiments of Akiyama et al (2020) [74] and simulations performed by Matviykiv et al (2020) [75] suggest that other common polymers including PP, PET, and PVC can also be extracted with similar efficiencies. However, environmental MPs are collected in water containing a very high abundance of natural microparticles, such as plankton.…”

Section: Acoustophoresismentioning

confidence: 98%

“…Acoustic focusing of Nylon 6 microfibers and PET microfibers toward the center of the microchannel was demonstrated with 99 % efficiency and 95 % efficiency, respectively. Matyikiv et al (2020) proposed acoustic separation for analysis of MPs in drinking water, and simulated the performance of an acoustophoretic device in separating using finite element analysis software [75].…”

Section: Acoustophoresismentioning

confidence: 99%

Field-Portable Microplastic Sensing in Aqueous Environments: A Perspective on Emerging Techniques

Blevins

Allen

Colson

et al. 2021

Sensors

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Microplastics (MPs) have been found in aqueous environments ranging from rural ponds and lakes to the deep ocean. Despite the ubiquity of MPs, our ability to characterize MPs in the environment is limited by the lack of technologies for rapidly and accurately identifying and quantifying MPs. Although standards exist for MP sample collection and preparation, methods of MP analysis vary considerably and produce data with a broad range of data content and quality. The need for extensive analysis-specific sample preparation in current technology approaches has hindered the emergence of a single technique which can operate on aqueous samples in the field, rather than on dried laboratory preparations. In this perspective, we consider MP measurement technologies with a focus on both their eventual field-deployability and their respective data products (e.g., MP particle count, size, and/or polymer type). We present preliminary demonstrations of several prospective MP measurement techniques, with an eye towards developing a solution or solutions that can transition from the laboratory to the field. Specifically, experimental results are presented from multiple prototype systems that measure various physical properties of MPs: pyrolysis-differential mobility spectroscopy, short-wave infrared imaging, aqueous Nile Red labeling and counting, acoustophoresis, ultrasound, impedance spectroscopy, and dielectrophoresis.

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“…Heritage in cell and particle manipulation in microfluidics field[185,225]. Recent studies have demonstrated MP sorting[226,227].Ultrasound Polymer Type*, Size* Performed in a microfluidic device or liquid volume, reducing sample preparation time. Equipment is relatively low-cost and portable.…”

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confidence: 99%

Field-Portable dissolved gas sensing and perspectives in aqueous microplastic detection

Blevins¹

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Global temperature rise and increased atmospheric carbon dioxide (CO2) levels have affected the health of the world’s ocean and water ecosystems, impacting the balances of natural carbon cycling and causing ocean acidification. Additionally, as global temperatures rise, thawing permafrost has stimulated increased release of methane (CH4), a gas with a shorter lifetime in the atmosphere but with even more heat trapping ability than CO2. In situ analysis of dissolved gas content in surface waters is currently performed with large, expensive instruments, such as spectrometers, which are coupled with gas equilibration systems, which extract dissolved gas from water and feed it to the sensor. Accurate, low cost, and portable sensors are needed to measure the dissolved CH4 and CO2 concentration in water systems to quantify their release and understand their relationship to the global carbon budget. At the same time, while greenhouse gases are well established threats to water ecosystems, the ubiquity and potential consequences of microplastics in aqueous environments are just beginning to be recognized by the environmental research community. Microplastics (MPs) are small particles of polymer debris, commonly defined as being between 1 μm and 1000 μm. Despite the pervasiveness of MPs, our ability to characterize MPs in the environment is limited by the lack of technologies for rapidly and accurately identifying and quantifying MPs. This thesis is concerned with the engineering challenges prompted by the need for high quality and quantity environmental data to better study and the impact, cycling, and prevalence of these pollutants in aqueous environments. Three distinct investigations are presented here. First, the design of the Low-Cost Gas Extraction and Measurement System (LC-GEMS) for dissolved CO2 is presented. At just under $600 dollar to build, the LC-GEMS is an ultra-portable, toolbox-sized instrument for dissolved gas sensing in near-surface waters. The LCGEMS was characterized in the lab and demonstrated linear relationships with dissolved CO2 as well as temperature. Lab calibrations and subsequent field testing in the Little Sippewissett Marsh, in Falmouth, Massachusetts showed that the LCGEMS captures both diurnal and minute-time scale trends in dissolved CO2. Second, this thesis presents the novel design of three simple and low-cost planar nanophotonic and plasmonic structures as optical transducers for measuring dissolved CH4. Through simulations, the sensitivity of the structures are evaluated and found to exhibit superior performance in the reflectance intensity readout mode to that of the standard surface-plasmon-polariton-mode Spreeta sensor. A practical, small, and low-cost implementation of this chip with a simple intensity-based measurement scheme is proposed. This design is novel in the space of dissolved gas monitoring because it shows potential to measure directly in the water phase while being robust and low-cost to implement. Finally, this thesis presents a literature review and perspective to motivate the development of field-deployable microplastic sensing techniques. A framework for field-deployable microplastic sensing is presented and seeks to inform the MP community of the potential in both traditional MP analysis techniques and unconventional methods for creating rapid and automated MP sensors. The field-deployabilty framework addresses a full scope of practical/technological trade-offs to be considered for portable MP detection.

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Simulation of Acoustophoretic Separation of Microplastic Particles in mkFluidic Lab-chip

Cited by 5 publications

References 4 publications

Acoustic-Based Drone Detection Using Neural Networks – A Comprehensive Analysis

Acoustic-Based Drone Detection Using Neural Networks – A Comprehensive Analysis

Field-Portable Microplastic Sensing in Aqueous Environments: A Perspective on Emerging Techniques

Field-Portable dissolved gas sensing and perspectives in aqueous microplastic detection

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