4.5 Article

Geomaterial-Functionalized Microfluidic Devices Using a Universal Surface Modification Approach

Journal

ADVANCED MATERIALS INTERFACES
Volume 6, Issue 23, Pages -

Publisher

WILEY
DOI: 10.1002/admi.201900995

Keywords

micro- and nanocharacterization; microfluidics; porous media; self-assembly; surface modification

Funding

  1. SENER-CONACYT-Hidrocarburos program [280816]
  2. China Scholarship Council (CSC)
  3. Canadian Foundation for Innovation (CFI)
  4. Natural Sciences and Engineering Council of Canada (NSERC)
  5. CMC Canadian Microsystem
  6. Organic Geochemistry and Petrology Group of Geological Survey of Canada, Calgary
  7. NSERC Canada Research Chair

Ask authors/readers for more resources

The layer-by-layer (LbL) self-assembly technique is used to coat the surface of flow channels in microfluidic chips with geomaterials. The surface modifications diminish the discrepancy between the surface chemistry of synthesized microfluidic devices and those of underground porous rocks. Hence, the use of visual models and, in particular, microfluidic devices is broadened to simulate the multiphase flows and fluid-solid interactions in actual rocks. Glass and quartz substrates are successfully coated with silicon dioxide (SiO2), bentonite, and montmorillonite. On-chip functionalization of polydimethylsiloxane (PDMS) and glass micromodels with SiO2 is also accomplished. The functionalized coatings using confocal laser scanning microscopy (CLSM), atomic force microscopy (AFM), and contact angle measurements are characterized. The surface modification technique is shown to be material-independent, which generates a hydrophilic surface. The surface-coated chips, functionalized by clay particles, are utilized to illustrate the role of water salinity on oil displacement.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Electrochemistry

Standoff and Point Detection of Thin Polymer Layers Using Microcantilever Photothermal Spectroscopy

Yaoli Zhao, Patatri Chakraborty, Nicholas Stavinski, Luis Velarde, Vaishali Maheshkar, Karthik Dantu, Arindam Phani, Seonghwan Kim, Thomas Thundat

Summary: Standoff detection based on optical spectroscopy is a highly selective method for identifying materials at a distance. In this study, we demonstrate that bi-material cantilever-based photothermal spectroscopy can be used for sensitive and selective detection of polymer films. We compare the spectral results obtained from standoff detection with those obtained from point detection, FTIR, and FTIR-ATR. Our results show that the technique can discriminate various polymers and detect thin layers of polymers in real-time. The sensitivity of the technique can be improved by optimizing the thermal sensitivity of the cantilever and increasing the number of photons.

JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2022)

Article Chemistry, Multidisciplinary

Interfacial Assembly of Graphene Oxide: From Super Elastic Interfaces to Liquid-in-Liquid Printing

Milad Kamkar, Elnaz Erfanian, Parisa Bazazi, Ahmadreza Ghaffarkhah, Farbod Sharif, Ganhua Xie, Aadithya Kannan, Mohammad Arjmand, S. Hossein Hejazi, Thomas P. Russell, Gerald G. Fuller, Uttandaraman Sundararaj

Summary: The assembly of graphene oxide (GO) at oil/water or air/water interfaces significantly increases the elasticity of the interface, making it an exceptional candidate for stabilizing the O/W interface. This super elastic character is utilized for all-liquid 2D printing, highlighting the potential applications in electronics, fluidic devices, and controlled release systems.

ADVANCED MATERIALS INTERFACES (2022)

Article Chemistry, Multidisciplinary

Manipulating Active Sites of 2D Metal-Organic Framework Nanosheets with Fluorescent Materials for Enhanced Colorimetric and Fluorescent Ammonia Sensing

Danny Wong, Arindam Phani, Setareh Homayoonnia, Simon S. Park, Seonghwan Kim, Osama Abuzalat

Summary: 2D metal-organic frameworks (MOFs) have high surface area and active adsorption sites, making them appealing for gas sensing applications. In this study, a 2D-MOFs nanosheet, Zn-BTC, with approximately 2.52 nm thickness was synthesized using a fast and facile technique. The introduction of 8-hydroxyquinoline resulted in the formation of fluorescent compound ZnQ, which was encapsulated and decorated onto Zn-BTC. The synthesized material exhibited visible color change and fluorescence quenching upon exposure to ammonia, with detection limits of 0.27 ppm and 60.8 nm in gaseous and liquid phase sensing, respectively.

ADVANCED MATERIALS INTERFACES (2022)

Article Environmental Sciences

Identification of odor emission sources in urban areas using machine learning-based classification models

Yelim Choi, Kyunghoon Kim, Seonghwan Kim, Daekeun Kim

Summary: This study proposes a method using machine learning for identifying odor sources in urban areas. The research shows that machine learning can accurately identify odor emission sources with high accuracy and time and cost can be saved by including only 6 important variables.

ATMOSPHERIC ENVIRONMENT-X (2022)

Article Nanoscience & Nanotechnology

Wetting Dynamics of Nanoparticle Dispersions: From Fully Spreading to Non-sticking and the Deposition of Nanoparticle-Laden Surface Droplets

Parisa Bazazi, Seyed Hossein Hejazi

Summary: Controlled transport of liquid droplets on solid surfaces is critical in various practical applications. In this study, non-contact aqueous drops are created on hydrophilic surfaces in an oleic environment and used to deposit submicrometer droplets encapsulating nanoparticles onto solid surfaces. The effect of surfactant and nanoparticle concentrations on wetting dynamics is studied, and a range of droplet spreading regimes is identified. This methodology enables the patterning of droplets in numerous applications, from pharmaceutical carriers to cosmetics and biomedical diagnoses.

ACS APPLIED MATERIALS & INTERFACES (2022)

Article Chemistry, Applied

In situ encapsulation of ZrQ in UiO-66 (Zr-BDC) for pore size control to enhance detection of a nerve agent simulant dimethyl methyl phosphonate

Danny Wong, Seonghwan Kim, Osama Abuzalat

Summary: In this study, a direct synthesis method for manufacturing fluorescent metal organic frameworks (MOFs) with high sensitivity and selectivity is proposed. The fluorescent MOFs show a low detection limit for DMMP and prevent water adsorption.

APPLIED ORGANOMETALLIC CHEMISTRY (2022)

Review Materials Science, Paper & Wood

Suspensions and hydrogels of cellulose nanocrystals (CNCs): characterization using microscopy and rheology

Aref Abbasi Moud, Milad Kamkar, Amir Sanati-Nezhad, Seyed Hossein Hejazi

Summary: This article reviews the microstructural characterization of cellulose nanocrystal (CNC)-based suspensions and hydrogels using imaging and rheological approaches, and introduces new applications of CNC suspensions and gels. Fine-tuning the properties of CNC colloids using existing methods and models is crucial due to the significant potential of CNC-based products in various fields.

CELLULOSE (2022)

Article Environmental Sciences

Rapid detection of ionic contents in water through sensor fusion and convolutional neural network

Min-hyung Lee, Jongho Won, Sehyun Chung, Seonghwan Kim, Simon S. Park

Summary: This study proposes a method for rapid and accurate detection of ionic contents in water through the combination of ultraviolet spectroscopy, electrochemical impedance spectroscopy, and convolutional neural network. The results demonstrate the superiority of this method in predicting ionic concentrations compared to traditional methods such as partial least squares regression and random forest.

CHEMOSPHERE (2022)

Article Engineering, Mechanical

Dynamic drill-string modeling for acoustic telemetry

Hamid Mostaghimi, Jediael R. Pagtalunan, Bryan Moon, Seonghwan Kim, Simon S. Park

Summary: This study improves the data transmission rate and reliability in directional drilling techniques using a finite element model and acoustic telemetry method. Efficient signal transmission and decoding are achieved through techniques such as differential binary phase shift keying and convolutional encoding.

INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES (2022)

Article Multidisciplinary Sciences

Self-assembly of highly ordered micro- and nanoparticle deposits

Hossein Zargartalebi, S. Hossein Hejazi, Amir Sanati-Nezhad

Summary: The authors introduce a passive protocol to suppress the coffee-ring effect and form uniform films at micro- and nanoscales by combining superhydrophilic substrate with a neutral-wetting low-roughness mold. This method has broad applications in fabricating ordered coatings, producing nanofilters, and creating functionalized nanosensors.

NATURE COMMUNICATIONS (2022)

Article Multidisciplinary Sciences

Spongy all-in-liquid materials by in-situ formation of emulsions at oil-water interfaces

Parisa Bazazi, Howard A. Stone, S. Hossein Hejazi

Summary: All-in-liquid printing enables the printing of functional networks in liquid medium, providing vast applications in fields such as functional cell engineering.

NATURE COMMUNICATIONS (2022)

Article Physics, Multidisciplinary

Dynamics of Droplet Pinch-Off at Emulsified Oil-Water Interfaces: Interplay between Interfacial Viscoelasticity and Capillary Forces

Parisa Bazazi, Howard A. Stone, S. Hossein Hejazi

Summary: This study experimentally investigates the break-up of a liquid filament with silica nanoparticles in a surfactant-containing oil phase. It is found that when a viscoelastic layer forms at the interface, the pinch-off dynamics follows exponential decay. A simple approach is introduced to estimate the viscoelastic properties of liquid-fluid interfaces and the thickness of the interfacial layer, where direct measurement of interfacial rheology is not possible.

PHYSICAL REVIEW LETTERS (2023)

Article Chemistry, Multidisciplinary

MOF/MWCNT-Nanocomposite Manipulates High Selectivity to Gas via Different Adsorption Sites with Varying Electron Affinity: A Study in Methane Detection in Parts-per-Billion

Setareh Homayoonnia, Arindam Phani, Seonghwan Kim

Summary: In this study, metal-organic frameworks (MOFs) and multiwall carbon nanotubes (MWCNTs) were synergized to achieve selective gas sensing of methane. This research provides a significant reference for future MOF-related composite materials research to achieve the best sensing performance.

ACS SENSORS (2022)

Article Chemistry, Multidisciplinary

Metal-Organic Framework Reinforced Highly Stretchable and Durable Conductive Hydrogel-Based Triboelectric Nanogenerator for Biomotion Sensing and Wearable Human-Machine Interfaces

Muhammad Toyabur Rahman, Md Sazzadur Rahman, Hitendra Kumar, Keekyoung Kim, Seonghwan Kim

Summary: Flexible triboelectric nanogenerators (TENGs) with multifunctional sensing capabilities offer a solution to energy supply challenges for wearable smart electronics. A highly stretchable and durable electrode for wearable TENG is developed using ZIF-8 as a reinforcing nanofiller in a hydrogel. The optimized ZIF-8-based hydrogel electrodes enhance the output performance of TENG, delivering an excellent power density of 3.47 Wm(-)(2), which is 3.2 times higher than pure hydrogel-based TENG. The developed TENG can scavenge biomechanical energy even at subzero temperatures and serve as self-powered pressure sensors and biomotion sensors.

ADVANCED FUNCTIONAL MATERIALS (2023)

Article Agriculture, Multidisciplinary

Estimation of soil texture by fusion of near-infrared spectroscopy and image data based on convolutional neural network

Mohammad Kazem Vakilzadeh Ebrahimi, Hansaem Lee, Jongho Won, Seonghwan Kim, Simon S. Park

Summary: In this study, a CNN model using fusion data with NIR and image was used to accurately predict sand, silt, and clay fractions of soil samples. The model performance was optimized through various preprocessing methods, image types, and size, resulting in high performance for both NIR and image datasets. The fusion dataset improved the model performance compared to using individual datasets, and the trained model showed better predictive performance than previous models, even with a small amount of training data.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2023)

No Data Available