scholarly journals Programmable µChopper Device with On-Chip Droplet Mergers for Continuous Assay Calibration

Micromachines ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 620 ◽  
Author(s):  
Nan Shi ◽  
Christopher J. Easley

While droplet-based microfluidics is a powerful technique with transformative applications, most devices are passively operated and thus have limited real-time control over droplet contents. In this report, an automated droplet-based microfluidic device with pneumatic pumps and salt water electrodes was developed to generate and coalesce up to six aqueous-in-oil droplets (2.77 nL each). Custom control software combined six droplets drawn from any of four inlet reservoirs. Using our μChopper method for lock-in fluorescence detection, we first accomplished continuous linear calibration and quantified an unknown sample. Analyte-independent signal drifts and even an abrupt decrease in excitation light intensity were corrected in real-time. The system was then validated with homogeneous insulin immunoassays that showed a nonlinear response. On-chip droplet merging with antibody-oligonucleotide (Ab-oligo) probes, insulin standards, and buffer permitted the real-time calibration and correction of large signal drifts. Full calibrations (LODconc = 2 ng mL−1 = 300 pM; LODamt = 5 amol) required <1 min with merely 13.85 nL of Ab-oligo reagents, giving cost-savings 160-fold over the standard well-plate format while also automating the workflow. This proof-of-concept device—effectively a microfluidic digital-to-analog converter—is readily scalable to more droplets, and it is well-suited for the real-time automation of bioassays that call for expensive reagents.

Author(s):  
Vladimir V. NEKRASOV

Developing a microcontroller-based system for controlling the flywheel motor of high-dynamics spacecraft using Russian-made parts and components made it possible to make statement of the problem of searching control function for a preset rotation rate of the flywheel rotor. This paper discusses one of the possible options for mathematical study of the stated problem, namely, application of structural analysis based on graph theory. Within the framework of the stated problem a graph was constructed for generating the new required rate, while in order to consider the stochastic case option the incidence and adjacency matrices were constructed. The stated problem was solved using a power matrix which transforms a set of contiguous matrices of the graph of admissible solution edge sequences, the real-time control function was found. Based on the results of this work, operational trials were run for the developed control function of the flywheel motor rotor rotation rate, a math model was constructed for the real-time control function, and conclusions were drawn about the feasibility of implementing the results of this study. Key words: Control function, graph, incidence matrix, adjacency matrix, power matrix, microcontroller control of the flywheel motor, highly dynamic spacecraft.


Author(s):  
David R. Selviah ◽  
Janti Shawash

This chapter celebrates 50 years of first and higher order neural network (HONN) implementations in terms of the physical layout and structure of electronic hardware, which offers high speed, low latency, compact, low cost, low power, mass produced systems. Low latency is essential for practical applications in real time control for which software implementations running on CPUs are too slow. The literature review chapter traces the chronological development of electronic neural networks (ENN) discussing selected papers in detail from analog electronic hardware, through probabilistic RAM, generalizing RAM, custom silicon Very Large Scale Integrated (VLSI) circuit, Neuromorphic chips, pulse stream interconnected neurons to Application Specific Integrated circuits (ASICs) and Zero Instruction Set Chips (ZISCs). Reconfigurable Field Programmable Gate Arrays (FPGAs) are given particular attention as the most recent generation incorporate Digital Signal Processing (DSP) units to provide full System on Chip (SoC) capability offering the possibility of real-time, on-line and on-chip learning.


RSC Advances ◽  
2015 ◽  
Vol 5 (105) ◽  
pp. 86490-86496 ◽  
Author(s):  
Tianqi Ma ◽  
Shaohui Guo ◽  
Zhihui Guo ◽  
Qiushi Zhu ◽  
Jinfu Chen

Indicated high pH benefits the accuracy of real-time control strategy, explained why DO as a control parameter is unreliable.


2000 ◽  
Vol 618 ◽  
Author(s):  
D.A. Gajewski ◽  
J.E. Guyer ◽  
J.J. Kopanski ◽  
J.G. Pellegrino

ABSTRACTWe present the real-time pseudodielectric function <ε(E)> of low-temperature-grown GaAs (LT-GaAs) thin films during the growth as a function of growth temperature Tg and thickness. We obtained accurate measurements of the real-time <εc(E)> by using in situspectroscopic ellipsometry (SE) in conjunction with active feedback control of the substrate temperature using diffuse reflectance spectroscopy. We show that for epitaxial LT-GaAs layers, the peak in the imaginary pseudodielectric function <ε2(E)> decreases in amplitude and sharpness systematically with decreasing Tg. We also revealed an abrupt change in <εc(E)> near the critical epitaxial thickness hepi, the value of which decreases with decreasing Tg. Above hepi, the LT-GaAs grows polycrystalline (amorphous) above (below) Tg ∼ 190°C. We also simultaneously monitored the surface roughness and crystallinity by using real-time reflection high-energy electron diffraction (RHEED). These results represent progress in obtaining real-time control over the composition and morphology of LT-GaAs


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