Optimization of fluorescence and surface adsorption of citric acid/ethanolamine carbon nanoparticles for subsurface tracers

Sinclair, Laura; Brown, Joseph S.; Salim, Muhammad; May, Daniel F.; Guilvaiee, Bahareh; Hawkins, Adam J.; Cathles, L. M.

doi:10.1016/j.carbon.2020.07.024

Cited by 8 publications

(20 citation statements)

References 67 publications

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“…Carbon-based phosphors, such as carbon nanoparticles (CNPs), carbon dots, graphene quantum dots, and boron carbon oxynitride (BCNO), have gained scientic interest in various semiconductor applications, such as biosensing, bioimaging, nanomedicine, solar cells, and catalysis. [1][2][3][4][5] Owing to their superior properties (tunable photoluminescence emission, high quantum efficiency, low cytotoxicity, facile production, costeffective preparation, photostability, chemical inertness, and excellent biocompatibility), carbon-based phosphors are expected to be excellent potential substitutes for semiconductor quantum dots and rare earth element-based phosphors. [6][7][8] Among other carbon-based phosphors, carbon nanoparticles (CNPs) are the most promising materials for large-scale production due to their scalable and facile synthesis with superior properties.…”

Section: Introductionmentioning

confidence: 99%

Solid-state nitrogen-doped carbon nanoparticles with tunable emission prepared by a microwave-assisted method

et al. 2021

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Section: Introductionmentioning

confidence: 99%

Solid-state nitrogen-doped carbon nanoparticles with tunable emission prepared by a microwave-assisted method

et al. 2021

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“…A carbon‐cored nanoparticle tracer, or “C‐Dots,” served as an inert tracer for field testing at the AFL in the summer of 2016. This fluorescent tracer consists of a carbon core decorated with a highly fluorescent polymer (Krysmann et al, 2012; Sinclair et al, 2020). It is ideal for groundwater tracer testing, because it is highly water soluble, inert, environmentally benign, and detectable by fluorescence at concentrations as low as ~1 ppb in deionized water (Hawkins, Becker, & Tsoflias, 2017; Ray et al, 2009; Subramanian et al, 2013; Zhao, 2015).…”

Section: Methodsmentioning

confidence: 99%

Predictive Inverse Model for Advective Heat Transfer in a Short‐Circuited Fracture: Dimensional Analysis, Machine Learning, and Field Demonstration

Hawkins

Fox

Koch

et al. 2020

Water Resources Research

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Identifying fluid flow maldistribution in planar geometries is a well-established problem in subsurface science/engineering. Of particular importance to the thermal performance of enhanced (or "engineered") geothermal systems is identifying the existence of nonuniform (i.e., heterogeneous) permeability and subsequently predicting advective heat transfer. Here, machine learning via a genetic algorithm (GA) identifies the spatial distribution of an unknown permeability field in a two-dimensional Hele-Shaw geometry (i.e., parallel plates). The inverse problem is solved by minimizing the L 2 norm between simulated residence time distribution (RTD) and measurements of an inert tracer breakthrough curve (BTC) (C-Dot nanoparticle). Principal component analysis (PCA) of spatially correlated permeability fields enabled reduction of the parameter space by more than a factor of 10 and restricted the inverse search to reservoir-scale permeability variations. Thermal experiments and tracer tests conducted at the mesoscale Altona Field Laboratory (AFL) demonstrate that the method accurately predicts the effects of extreme flow channeling on heat transfer in a single bedding-plane rock fracture. However, this is only true when the permeability distributions provide adequate matches to both tracer RTD and frictional pressure loss. Without good agreement to frictional pressure loss, it is still possible to match a simulated RTD to measurements, but subsequent predictions of heat transfer are grossly inaccurate. The results of this study suggest that it is possible to anticipate the thermal effects of flow maldistribution, but only if both simulated RTDs and frictional pressure loss between fluid inlets and outlets are in good agreement with measurements.

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“…We used the same batch of FCNs produced and characterized by Sinclair et al (2020). Briefly, FCNs were synthesized by continuously stirring citric acid monohydrate (Sigma Aldrich) with ethanolamine (EMD Millipore) with a 1:3 M ratio at 160°C for 30 min to produce a precursor, which was then pyrolyzed at 190°C, 210°C, 230°C, or 250°C for 2 hr (Sinclair et al, 2020). These FCN products were dialyzed for ∼1 week to remove small molecule contaminants and finally lyophilized for >48 hr.…”

Section: Fcn Synthesis and Characteristicsmentioning

confidence: 99%

“…Sinclair et al. (2020) noted that the attachment of these FCNs to quartz surfaces in quartz crystal microbalance experiments increased with their hydrophobicity and that the hydrophobicity of FCNs increased with their pyrolysis temperature due to carbonization and loss of hydrophilic functional groups. Sinclair et al.…”

Section: Introductionmentioning

confidence: 99%

Effect of Hydrophobicity of Fluorescent Carbon Nanoparticles on Transport in Porous Media: Column Experiments and Modeling

May

Hassanpour

Sinclair

et al. 2023

Water Resources Research

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Engineered carbon‐based nanoparticles are increasingly used for environmental, industrial, and medical purposes. Thus, understanding their interaction with and transport through materials is important. We examine the impact of nanoparticle hydrophobicity and porous medium surface area on the transport of carbon nanoparticles through sand‐packed columns under saturated and unsaturated conditions. The fluorescent carbon nanoparticles (FCNs) used in this study, synthesized from citric acid and ethanolamine, exhibit synthesis‐temperature‐dependent hydrophobicity. To quantify the impact of hydrophobicity on retention, we use FCNs synthesized at four temperatures: 190°C (FCN190), 210°C (FCN210), 230°C (FCN230), and 250°C (FCN250). Several observations are noted. First, the more hydrophobic particles (FCN230 and FCN250) attain lower outlet concentrations and mass recovery than more hydrophilic particles (FCN190 and FCN210). For instance, while 77% of the FCN190 was recovered after passing through a fine‐sand‐packed column, only 23% of the FCN250 was recovered. Second, sand surface area significantly impacts FCN recovery. A 17‐fold increase in sand surface area yields a 30% decrease in the recovery of FCN210. Third, no significant difference in the mass recovery of the FCNs was observed between the unsaturated and saturated conditions, which is attributed to the small size of the FCNs relative to the water film thickness surrounding sand grains. Fourth, the particle transport model in HYDRUS‐1D successfully simulated FCN transport, showing approximately a tenfold increase in the attachment coefficient for hydrophobic FCNs. In summary, through experiments and modeling, we show that hydrophobicity is a major factor impacting FCN transport.

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Optimization of fluorescence and surface adsorption of citric acid/ethanolamine carbon nanoparticles for subsurface tracers

Cited by 8 publications

References 67 publications

Solid-state nitrogen-doped carbon nanoparticles with tunable emission prepared by a microwave-assisted method

Solid-state nitrogen-doped carbon nanoparticles with tunable emission prepared by a microwave-assisted method

Predictive Inverse Model for Advective Heat Transfer in a Short‐Circuited Fracture: Dimensional Analysis, Machine Learning, and Field Demonstration

Effect of Hydrophobicity of Fluorescent Carbon Nanoparticles on Transport in Porous Media: Column Experiments and Modeling

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