A High-Fidelity Electrokinetic Flow Model for the Prediction of Electrophoregrams in On-Chip Eletrophoresis Applications

2005 ◽  
Author(s):  
Hao Lin ◽  
Rajiv Bharadwaj ◽  
Juan G. Santiago ◽  
Bijan Mohammadi
Keyword(s):  
Flow Model ◽  
Flow Behavior ◽  
Computational Cost ◽  
High Fidelity ◽  
Efficient Design ◽  
Complex Flow ◽  
Electrokinetic Flow ◽  
Design And Optimization ◽  
Genomics And Proteomics ◽  
On Chip

On-chip electrophoresis is a growing field with increasing chemical and bioanalytical applications such as genomics and proteomics. The use of multicomponent and heterogeneous electrolyte configurations can often lead to complex flow behavior. In this work, we present a high-fidelity, low computational cost electrokinetic flow model for the modeling and optimization of electrophoretic separations. The model adopts a depth-averaged approach that captures convective-dispersion processes, and includes important physical effects such as electrical body force and fully nonlinear multi-species electromigration. The corresponding numerical scheme is based on a finite volume approach using a monotonic upstream-centered construction (MUSCL). The numerical model can simulate arbitrary electrolyte and sample configurations, and capture the complex evolution of sharp, narrow sample peaks and high pre-concentration (stacking) ratios. Exemplary results showing both field amplified sample stacking and isotachophoresis processes are presented. The development of such models is critical to the efficient design and optimization of on-chip CE methods and devices.

Message Passing Neural Networks for Partial Charge Assignment to Metal-Organic Frameworks

2020 ◽  
Author(s):  
Ali Raza ◽  
Arni Sturluson ◽  
Cory Simon ◽  
Xiaoli Fern
Keyword(s):  
Electronic Structure ◽  
Message Passing ◽  
Gas Adsorption ◽  
Metal Organic Frameworks ◽  
Computational Cost ◽  
Electronic Structure Calculations ◽  
High Fidelity ◽  
Partial Charges ◽  
Metal Organic ◽  
Structure Calculations

Virtual screenings can accelerate and reduce the cost of discovering metal-organic frameworks (MOFs) for their applications in gas storage, separation, and sensing. In molecular simulations of gas adsorption/diffusion in MOFs, the adsorbate-MOF electrostatic interaction is typically modeled by placing partial point charges on the atoms of the MOF. For the virtual screening of large libraries of MOFs, it is critical to develop computationally inexpensive methods to assign atomic partial charges to MOFs that accurately reproduce the electrostatic potential in their pores. Herein, we design and train a message passing neural network (MPNN) to predict the atomic partial charges on MOFs under a charge neutral constraint. A set of ca. 2,250 MOFs labeled with high-fidelity partial charges, derived from periodic electronic structure calculations, serves as training examples. In an end-to-end manner, from charge-labeled crystal graphs representing MOFs, our MPNN machine-learns features of the local bonding environments of the atoms and learns to predict partial atomic charges from these features. Our trained MPNN assigns high-fidelity partial point charges to MOFs with orders of magnitude lower computational cost than electronic structure calculations. To enhance the accuracy of virtual screenings of large libraries of MOFs for their adsorption-based applications, we make our trained MPNN model and MPNN-charge-assigned computation-ready, experimental MOF structures publicly available.<br>

scholarly journals Development of a Mobile Analytical Chemistry Workstation Using a Silicon Electrochromatography Microchip and Capacitively Coupled Contactless Conductivity Detector

Micromachines ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 239
Author(s):  
Yineng Wang ◽  
Xi Cao ◽  
Walter Messina ◽  
Anna Hogan ◽  
Justina Ugwah ◽  
...  
Keyword(s):  
Capillary Electrochromatography ◽  
High Efficiency ◽  
Device Fabrication ◽  
Capacitively Coupled ◽  
Packaging Design ◽  
Design And Optimization ◽  
Nanofabrication Technique ◽  
On Chip ◽  
Silicon Based ◽  
Rapid Separations

Capillary electrochromatography (CEC) is a separation technique that hybridizes liquid chromatography (LC) and capillary electrophoresis (CE). The selectivity offered by LC stationary phase results in rapid separations, high efficiency, high selectivity, minimal analyte and buffer consumption. Chip-based CE and CEC separation techniques are also gaining interest, as the microchip can provide precise on-chip control over the experiment. Capacitively coupled contactless conductivity detection (C4D) offers the contactless electrode configuration, and thus is not in contact with the solutions under investigation. This prevents contamination, so it can be easy to use as well as maintain. This study investigated a chip-based CE/CEC with C4D technique, including silicon-based microfluidic device fabrication processes with packaging, design and optimization. It also examined the compatibility of the silicon-based CEC microchip interfaced with C4D. In this paper, the authors demonstrated a nanofabrication technique for a novel microchip electrochromatography (MEC) device, whose capability is to be used as a mobile analytical equipment. This research investigated using samples of potassium ions, sodium ions and aspirin (acetylsalicylic acid).

A two-stage design optimization framework for multifield origami-inspired structures

2021 ◽  
pp. 1045389X2110116
Author(s):  
Wei Zhang ◽  
Saad Ahmed ◽  
Jonathan Hong ◽  
Zoubeida Ounaies ◽  
Mary Frecker
Keyword(s):  
Case Studies ◽  
Computing Time ◽  
Computational Cost ◽  
High Fidelity ◽  
Fe Model ◽  
Two Stage ◽  
Baseline Design ◽  
Optimization Framework ◽  
Highly Nonlinear ◽  
Stage 1

Different types of active materials have been used to actuate origami-inspired self-folding structures. To model the highly nonlinear deformation and material responses, as well as the coupled field equations and boundary conditions of such structures, high-fidelity models such as finite element (FE) models are needed but usually computationally expensive, which makes optimization intractable. In this paper, a computationally efficient two-stage optimization framework is developed as a systematic method for the multi-objective designs of such multifield self-folding structures where the deformations are concentrated in crease-like areas, active and passive materials are assumed to behave linearly, and low- and high-fidelity models of the structures can be developed. In Stage 1, low-fidelity models are used to determine the topology of the structure. At the end of Stage 1, a distance measure [Formula: see text] is applied as the metric to determine the best design, which then serves as the baseline design in Stage 2. In Stage 2, designs are further optimized from the baseline design with greatly reduced computing time compared to a full FEA-based topology optimization. The design framework is first described in a general formulation. To demonstrate its efficacy, this framework is implemented in two case studies, namely, a three-finger soft gripper actuated using a PVDF-based terpolymer, and a 3D multifield example actuated using both the terpolymer and a magneto-active elastomer, where the key steps are elaborated in detail, including the variable filter, metrics to select the best design, determination of design domains, and material conversion methods from low- to high-fidelity models. In this paper, analytical models and rigid body dynamic models are developed as the low-fidelity models for the terpolymer- and MAE-based actuations, respectively, and the FE model of the MAE-based actuation is generalized from previous work. Additional generalizable techniques to further reduce the computational cost are elaborated. As a result, designs with better overall performance than the baseline design were achieved at the end of Stage 2 with computing times of 15 days for the gripper and 9 days for the multifield example, which would rather be over 3 and 2 months for full FEA-based optimizations, respectively. Tradeoffs between the competing design objectives were achieved. In both case studies, the efficacy and computational efficiency of the two-stage optimization framework are successfully demonstrated.

Computational and Experimental Study of Enhanced Laminar Flow Heat Transfer in Three-Dimensional Sinusoidal Wavy-Plate-Fin Channels

2003 ◽  
Author(s):  
Jiehai Zhang ◽  
Arun Muley ◽  
Joseph B. Borghese ◽  
Raj M. Manglik
Keyword(s):  
Heat Transfer ◽  
Flow Behavior ◽  
Computational Simulation ◽  
Three Dimensional ◽  
Heat Fluxes ◽  
Staggered Grid ◽  
Uniform Heat Flux ◽  
Complex Flow ◽  
Constant Property ◽  
Fin Efficiency

Enhanced heat transfer characteristics of low Reynolds number airflows in three-dimensional sinusoidal wavy plate-fin channels are investigated. For the computational simulation, steady state, constant property, periodically developed, laminar forced convection is considered with the channel surface at the uniform heat flux condition; the wavy-fin is modeled by its two asymptotic limits of 100% and zero fin efficiency. The governing equations are solved numerically using finite-volume techniques for a non-orthogonal, non-staggered grid. Computational results for velocity and temperature distribution, isothermal Fanning friction factor f and Colburn factor j are presented for airflow rates in the range of 10 ≤ Re ≤ 1500. The numerical results are further compared with experimental data, with excellent agreement, for two different wavy-fin geometries. The influence of fin density on the flow behavior and the enhanced convection heat transfer are highlighted. Depending on the flow rate, a complex flow structure is observed, which is characterized by the generation, spatial growth and dissipation of vortices in the trough region of the wavy channel. The thermal boundary layers on the fin surface are periodically disrupted, resulting in high local heat fluxes. The overall heat transfer performance is improved considerably, compared to the straight channel with the same cross-section, with a relatively smaller increase in the associated pressure drop penalty.

Microfluidic Channel Fabrication With Tailored Wall Roughness

2012 ◽  
Author(s):  
Jing Ren ◽  
Sriram Sundararajan
Keyword(s):  
Flow Behavior ◽  
Surface Texturing ◽  
Microfluidic Channel ◽  
Dip Coating ◽  
Etch Depth ◽  
Wall Roughness ◽  
Random Surface ◽  
Lab On Chip ◽  
On Chip ◽  
Autocorrelation Length

Realistic random roughness of channel surfaces is known to affect the fluid flow behavior in microscale fluidic devices. This has relevance particularly for applications involving non-Newtonian fluids, such as biomedical lab-on-chip devices. In this study, a surface texturing process was developed and integrated into microfluidic channel fabrication. The process combines colloidal masking and Reactive Ion Etching (RIE) for generating random surfaces with desired roughness parameters on the micro/nanoscale. The surface texturing process was shown to be able to tailor the random surface roughness on quartz. A Large range of particle coverage (around 6% to 67%) was achieved using dip coating and drop casting methods using a polystyrene colloidal solution. A relation between the amplitude roughness, autocorrelation length, etch depth and particle coverage of the processed surface was built. Experimental results agreed reasonably well with model predictions. The processed substrate was further incorporated into microchannel fabrication. Final device with designed wall roughness was tested and proved a satisfying sealing performance.

Analysis of Thermal Properties of Power Multifinger HEMT Devices

2018 ◽  
Author(s):  
Aleš Chvála ◽  
Robert Szobolovszký ◽  
Jaroslav Kováč ◽  
Martin Florovič ◽  
Juraj Marek ◽  
...  
Keyword(s):  
Temperature Distribution ◽  
Thermal Management ◽  
High Electron Mobility Transistor ◽  
Structure Design ◽  
High Electron ◽  
Design And Optimization ◽  
Chip Temperature ◽  
Materials Used ◽  
On Chip ◽  
Measurement Approach

In this paper, several methods suitable for real time on-chip temperature measurements of power AlGaN/GaN based high-electron mobility transistor (HEMT) grown on SiC substrate are presented. The measurement of temperature distribution on HEMT surface using Raman spectroscopy is presented. We have deployed a temperature measurement approach utilizing electrical I-V characteristics of the neighboring Schottky diode under different dissipated power of the transistor heat source. These methods are verified by measurements with micro thermistors. The results show that these methods have a potential for HEMT analysis in thermal management. The features and limitations of the proposed methods are discussed. The thermal parameters of materials used in the device are extracted from temperature distribution in the structure with the support of 3-D device thermal simulation. The thermal analysis of the multifinger power HEMT is performed. The effects of the structure design and fabrication processes from semiconductor layers, metallization, and packaging up to cooling solutions are investigated. The analysis of thermal behavior can help during design and optimization of power HEMT.

Self-assembly with colloidal clusters: facile crystal design using connectivity landscape analysis

Soft Matter ◽  
2017 ◽  
Vol 13 (39) ◽  
pp. 7098-7105 ◽  
Author(s):  
Mehdi B. Zanjani ◽  
John C. Crocker ◽  
Talid Sinno
Keyword(s):  
Self Assembly ◽  
Landscape Analysis ◽  
Efficient Design ◽  
Geometrical Analysis ◽  
Design And Optimization ◽  
Colloidal Clusters ◽  
Crystal Design

Geometrical analysis of connectivity enables efficient design and optimization of colloidal cluster assemblies.

Gas Carry-Under in GLCC for Separated and Recombined Outlet Configurations

2018 ◽  
Author(s):  
Srinivas Swaroop Kolla ◽  
Ram S. Mohan ◽  
Ovadia Shoham
Keyword(s):  
Volume Fraction ◽  
Swirling Flow ◽  
Control Strategies ◽  
Flow Behavior ◽  
Jet Impingement ◽  
Test Facility ◽  
Experimental Investigations ◽  
Level Control ◽  
Complex Flow ◽  
Control Configuration

Gas Carry-Under (GCU) is one of the undesirable phenomena that exists in the GLCC©1 even within the Operational Envelope (OPEN) for liquid carry-over. Few studies that are available on GLCC© GCU have been carried out when the GLCC© is operated in a metering loop configuration characterized by recombined outlets. In such configurations the gas and the liquid outlets of the GLCC are recombined downstream which acts as passive level control. However, studies have shown that the GLCC© OPEN increases significantly when active control strategies are employed. There has not been a systematic study aimed at analyzing the effect of control on the GCU in the GLCC. This study compares the previously published GLCC GCU swirling flow mechanism under recombination outlet configuration with data taken under the separated outlet configuration (control configuration). Experimental investigations for GCU are conducted in a state-of-the-art test facility for air-water and air-oil flow incorporating pressure and level control configurations. The experiments are carried out using a 3″ diameter GLCC© equipped with 3 sequential trap sections to measure simultaneously the Gas Volume Fraction (GVF) and gas evolution in the lower part of the GLCC. Also, gas trap sections are installed in the liquid leg of the GLCC© to measure simultaneously the overall GCU. The liquid level was controlled at 6″ below the GLCC© inlet for all experiments using various control strategies. Tangential wall jet impingement is the cause for entrainment of gas, thereby leading to GCU. 3 different flow mechanisms have been identified in the lower part of the GLCC and have significant effect on the GCU. Viscosity and surface tension are observed to affect the GCU. The extensive acquired data shed light on the complex flow behavior in the lower part of the GLCC© and its effect on the GCU of the GLCC©.

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