Impedance Cytometry for Rapid Biosensing of Lipid Content in Algal Cocultures
Kirby, Ahner
Title: ????
• NEED:Because of this, there is an urgent need to extract oil from underground reservoir. We have an unmet need to infer
oil reservoirs underground from inexpensive, reliable, and saline-resistant measurement techniques.
• GAP:We currently do not know how nanoparticles partition at the interface-specifically, we don't know their chemical
potential/gibbs free energy that determines how do they partition dynamically and equilibriumally. We don't know whether
they can act as surfactants.
• IMPORTANCE:Nanoparticle manipulation of underground oil is an important problem because, on a large scale,
increasing energy needs require that existing oil reservoirs be extracted at maximum efficiency to meet demand.
• LONG-TERM GOAL: The long-term goal of the proposed work is a thing that communicates Kirby's continuum of
research.
• OBJECTIVE: The objective of the proposed work is to determine thermodynamics and transport properties of the particles
by interrogating their partitioning, retention, and breakthrough in a controlled microfluidic environment, and then use this
knowledge to demonstrate high-fidelity characterization of underground oil reserves and optimize nanoparticle design for
increased oil recovery.
• CENTRAL HYPOTHESIS: The technological aspect of this proposal is driven by the central hypothesis that hairy
nanoparticles will be salt-tolerant because oil extraction efficiency increases when a brine solvent is used for extraction
instead of a water solvent. In order for hairy nanoparticles to increase extraction efficiency, the hairy nanoparticles must
work with the brine and not hinder the displacement of oil.
• CENTRAL HYPOTHESIS: The scientific aspect of this proposal is driven by the central hypothesis that electrostatic
interactions in the extended EDL associated with nanoparticle hairs play a central role in controlling the chemical
potential/gibbs free energy, and that this informs both design of nanoparticle hairs to control charge density as well as design
of smart water systems to maximize extraction.
• RATIONALE: The rationale of the proposed work is that successful lab-scale characterization of ex• traction and transport
will isolate the various nanoparticle and substrate thermodynamic and transport parameters, whose characterization will allow
nanoparticle oil sensing and extraction systems to be predicted for various rock substrates, extraction fluids, temperatures,
and salinities.
SPECIFIC OBJECTIVE 1: Create a microdevice that mimics the environment of a subsurface porous medium in which
nanoparticles will flow through in the oil or water phase.
• WORKING HYPOTHESIS:
• APPROACH:
In order to mimic the flow through porous subsurface environment in a model, important parameters such as the Peclet
number, average pore size need to be established. The width of the model should be within the range of 10 um- 30um where
10um would be for low permeability and 30 um would be for high permeability based on the average reported pore size
(Sirivithayapakorn 2003, Hendraningrat 2013). From the Stoke’s Einstein equation, diffusivity of nanoparticles can be
calculated for a range of nanoparticle sizes and combined with Pe number to estimate flow rate required. To simulate oil in
crevices, a microdevice would consist of a main straight channel with the specified width and periodic wells filled with oil on
either side of the channel.
To fabricate the microdevice, ???????? (silicon wafer, photoresist, mask, cross-link/hardens on, or get rid of photoresist).
Include apparatus set up? (flow meters, pressure gauges, refractometer)
• JUSTIFICATION:
A microdevice that mimics the subsurface environment eliminates the convolution of many factors that occur subsurface in
porous rock. With the model, one parameter can be changed at a time to delineate the specific affect on partitioning.
For reviewpurposes only
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Impedance Cytometry for Rapid Biosensing of Lipid Content in Algal Cocultures
Kirby, Ahner
• OUTCOME: Devising a process to make models that represent the subsurface environment, where parameters such as
quantity and size of wells are easily changed.
Oil recovery is the highest when divalent versus monovalent ions are used (enge 2014)
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Impedance Cytometry for Rapid Biosensing of Lipid Content in Algal Cocultures
Kirby, Ahner
SPECIFIC OBJECTIVE 2: Compare nanoparticles with and without "hairs" partitioning either at interface and/or in both
phases. Develop model that delineates the partitioning of the particles with hairs versus sans hairs for the parameters: amount
of particles, velocity of flow, particle size, duration of flow rate.
• WORKING HYPOTHESIS: Our working hypotheses are that (a) partitioning at the interface for hairy nanoparticles (HNP)
and nanoparticles will be primarily determine by valence of the solution and solution properties; and (b) adding in hairs will
increase the surfactant ability of nanoparticles
• APPROACH: To determine partitioning of particles, create breakthrough curves by measuring particle concentration at the
inlet and the outlet and track particles with fluorescent imaging in the device. By measuring the concentration of particles in
the water and in the oil, Gibbs free energy can be calculated to develop a model for the partitioning of particles.
• JUSTIFICATION:
The flow through the microdevice will consist of charged particles and the device’s surface will also have a charged
interface. The nanoparticle interactions will primarily be electrostatic in the solution and depend on the solution ionic
strength, zeta potential of the interface and particle, and permittivity. The partitioning at the interface can be modeled with a
thermodynamic model (Bresme 2010). The partitioning of particles is related to effluent concentration through the partition
coefficient.
• OUTCOME: Developing a model for nanoparticles partitioning at the interface for different solution properties. This
method can be applied to hairy nanoparticles to determine its own model.
explains how meets mini-need and/or fills mini-gap?
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Impedance Cytometry for Rapid Biosensing of Lipid Content in Algal Cocultures
Kirby, Ahner
SPECIFIC OBJECTIVE 3: Develop a predictive model that describes which particles perform best and how much is neededspecifically oil recovery (surfactant) for a variety of situations including differing porosity/tortuosity, differing salinity,
differing salt valence, differing fraction of oil below surface. Develop a predictive model that describes which particles
perform best and how much is needed-specifically for determining oil fraction (sensor) for a variety of situations including
temp, pressure, salinity, type of oil, valence.
• WORKING HYPOTHESIS: Our working hypotheses are that solution properties will characterize particle application and
performance, specifically increasing valence will increase extraction efficiency, increasing salinity will increase extraction
efficiency.
• APPROACH: Use data from breakthough curves where parameters of salinity, valence, flow velocity are varied to
determine which characteristics enhance surfactant and sensing properties.
• JUSTIFICATION:
Nanoparticles have been used as a surfactant in oil-water reservoirs to increase extraction efficiency by changing the
wettability. (Zhang 2010, 2009 Ju 2006). Hydrophilic nanoparticles changed hydrophobic walls to hydrophilic, which
displaces oil from crevices (Ju 2006). In addition to changing the wettability, nanoparticles have been used to form pickering
emulsions with oil in water (Chevalier, 2013) where partial wetting of silica is required to form a stable emulsion. With the
addition of hairs, the hairy nanoparticles have the ability to act in several capacities as they can be formulated for specific
situations (Fernandes 2013). The properties of oil reservoirs have high temperature and pressures and amount of oil recovery
increases with using a brine as the flushing fluid rather than water, which some nanoparticles cannot tolerate without special
coatings (Murphy 2013, Saleh 2008, Ogolo 2012). At oil reservoir temperatures, low salinity brines increase oil extraction
(Robertson 2010).
• OUTCOME: For the predictive model, it is expected that increasing the pH will make the nanoparticles more hydrophilic
(Binks 2000). The increasing the ionic concentration will suppress electrostatic reactions and more nanoparticles will be
retained in the solution (Tian et al., 2010) . Hairy nanoparticles may gain a charge if their hairs wrap around ions in the
solution which will cause partitioning based off the acquired charge.
For reviewpurposes only
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