ArticleMicromachines2021
Modeling Brownian Microparticle Trajectories in Lab-on-a-Chip Devices with Time Varying Dielectrophoretic or Optical Forces.
Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- Polarization-Addressable Optical Movement of Plasmonic Nanoparticles and Hotspot Spin Vortices.Nanomaterials (Basel, Switzerland) · 2024Article
- Editorial for the Special Issue on Micromachines for Dielectrophoresis, Volume II.Micromachines · 2023Article
- New Generation Dielectrophoretic-Based Microfluidic Device for Multi-Type Cell Separation.Biosensors · 2023Article
- Controlled Transport of Individual Microparticles Using Dielectrophoresis.Langmuir : the ACS journal of surfaces and colloids · 2023Article
- Trapping of a Single Microparticle Using AC Dielectrophoresis Forces in a Microfluidic Chip.Micromachines · 2023Article
- Dynamically controllable plasmonic tweezers using C-shaped nano-engravings.Applied physics letters · 2022Article
- Protein Albumin Manipulation and Electrical Quantification of Molecular Dielectrophoresis Responses for Biomedical Applications.Micromachines · 2022Review
- Viscoelastic Particle Focusing and Separation in a Spiral Channel.Micromachines · 2022Article
- Microfluidic Point-of-Care (POC) Devices in Early Diagnosis: A Review of Opportunities and Challenges.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Lab-on-a-chip (LOC) devices capable of manipulating micro/nano-sized samples have spurred advances in biotechnology and chemistry. Designing and analyzing new and more advanced LOCs require accurate modeling and simulation of sample/particle dynamics inside such devices. In this work, we present a generalized computational physics model to simulate particle/sample trajectories under the influence of dielectrophoretic or optical forces inside LOC devices. The model takes into account time varying applied forces, Brownian motion, fluid flow, collision mechanics, and hindered diffusion caused by hydrodynamic interactions. We develop a numerical solver incorporating the aforementioned physics and use it to simulate two example cases: first, an optical trapping experiment, and second, a dielectrophoretic cell sorter device. In both cases, the numerical results are found to be consistent with experimental observations, thus proving the generality of the model. The numerical solver can simulate time evolution of the positions and velocities of an arbitrarily large number of particles simultaneously. This allows us to characterize and optimize a wide range of LOCs. The developed numerical solver is made freely available through a GitHub repository so that researchers can use it to develop and simulate new designs.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.