paper-with-me

홈 › Papers

Extraction of electrokinetically separated analytes with on-demand encapsulation

2018-12-30

Microchip electrokinetic methods are capable of increasing the sensitivity of molecular assays by enriching and purifying target analytes. However, their use is currently limited to assays that can be performed under a high external electric field, as spatial separation and focusing is lost when the electric field is removed. We present a novel method that uses two-phase encapsulation to overcome this limitation. The method uses passive filling and pinning of an oil phase in hydrophobic channels to encapsulate electrokinetically separated and focused analytes with a brief pressure pulse. The resulting encapsulated sample droplet maintains its concentration over long periods of time without requiring an electric field and can be manipulated for further analysis, either on- or off- chip. We demonstrate the method by encapsulating DNA oligonucleotides in a 240 pL aqueous segment after isotachophoresis (ITP) focusing, and show that the concentration remains at 60% of the initial value for tens of minutes, a 22-fold increase over free diffusion after 20 minutes. Furthermore, we demonstrate manipulation of a single droplet by selectively encapsulating amplicon after ITP purification from a polymerase chain reaction (PCR) mix, and performing parallel off-chip detection reactions using the droplet. We provide geometrical design guidelines for devices implementing the encapsulation method, and show how the method can be scaled to multiple analyte zones.

📄 PDF Abstract BibTeX arXiv:1812.11497

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

BEOL Electro-Biological Interface for 1024-Channel TFT Neurostimulator with Cultured DRG Neurons

2024-11-16 · Haobin Zhou, Bowen Liu, Taoming Guo, Hanbin Ma 외

The demand for high-quality neurostimulation, driven by the development of brain-computer interfaces, has outpaced the capabilities of passive microelectrode-arrays, which are limited by channel-count and biocompatibilit…

Deep learning of nanopore sensing signals using a bi-path network

2021-05-08 · Dario Dematties, Chenyu Wen, Mauricio David Pérez, Dian Zhou 외

Temporary changes in electrical resistance of a nanopore sensor caused by translocating target analytes are recorded as a sequence of pulses on current traces. Prevalent algorithms for feature extraction in pulse-like si…

ChemTime: Rapid and Early Classification for Multivariate Time Series Classification of Chemical Sensors

2023-12-15 · Alexander M. Moore, Randy C. Paffenroth, Kenneth T. Ngo, Joshua R. Uzarski

Multivariate time series data are ubiquitous in the application of machine learning to problems in the physical sciences. Chemiresistive sensor arrays are highly promising in chemical detection tasks relevant to industri…

BenchmarkingClassificationEarly ClassificationSurvey+2

Capture Agent Free Biosensing using Porous Silicon Arrays and Machine Learning

2022-01-22 · Simon J. Ward, Tengfei Cao, Xiang Zhou, Catie Chang 외

Biosensors are an essential tool for medical diagnostics, environmental monitoring and food safety. Typically, biosensors are designed to detect specific analytes through functionalization with the appropriate capture ag…

BIG-bench Machine LearningDimensionality Reduction

Aprendizado de máquina aplicado na eletroquímica

2024-01-20 · Carlos Eduardo do Egito Araújo, Lívia F. Sgobbi, Iwens Gervasio Sene Jr, Sergio Teixeira de Carvalho

This systematic review focuses on analyzing the use of machine learning techniques for identifying and quantifying analytes in various electrochemical applications, presenting the available applications in the literature…

Articles