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          <family>Neville</family>
          <given>George</given>
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          <given>Samantha</given>
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        <affiliation>Institut Laue-Langevin</affiliation>
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          <family>Brooks</family>
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        <affiliation>European Spallation Source; Diamond Light Source; University of Bath; Rutherford Appleton Laboratory; ISIS Neutron and Muon Source</affiliation>
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          <family>Welton</family>
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    <title>Dataset for &quot;Interactions of Choline and Geranate (CAGE) and Choline Octanoate (CAOT) Deep Eutectic Solvents with Lipid Bilayers&quot;</title>
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    <keywords>deep eutectic solvents, ionic liquids, lipid bilayers, neutron reflectivity, neutron scattering, transdermal delivery</keywords>
    <note>Details of the data and labelling is available in the README.txt file.</note>
    <abstract>Deep eutectic solvents (DES) and ionic liquids (ILs) are often amphiphilic and interact with phospholipid membranes. Mixtures between choline and gernanic acid, coined &apos;CAGE&apos;, have been found to facilitate the transdermal delivery of larger pharmaceuticals, such as insulin. However, little is known about its mechanism of activity. The purpose for obtaining this data was to characterise aqueous suspensions of choline and germanic acid (CAGE) and choline and octanoic acid (CAOT) and compare their interactions with solid-supported lipid bilayers and vesicle layers. Particularly, dynamic light scattering (DLS) and quartz crystal microbalance with dissipation (QCM-D) measurements were used alongside neutron reflectivity (NR) to evaluate any structure-function relationships contributing to the DES behaviour, aiming towards the rational design of neoteric solvents for transdermal delivery.</abstract>
    <date>2023-10-02</date>
    <publisher>University of Bath</publisher>
    <full_text_status>public</full_text_status>
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        <funder_name>Engineering and Physical Sciences Research Council</funder_name>
        <funder_id>https://doi.org/10.13039/501100000266</funder_id>
        <grant_id>EP/L016354/1</grant_id>
        <project_name>EPSRC Centre for Doctoral Training in Sustainable Chemical Technologies</project_name>
      </item>
      <item>
        <funder_name>GlaxoSmithKline Biologicals</funder_name>
        <funder_id>https://doi.org/10.13039/100020955</funder_id>
      </item>
      <item>
        <funder_name>NIHR Health Protection Research Unit in Chemical and Radiation Threats and Hazards</funder_name>
        <grant_id>NIHR-INF-1654</grant_id>
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    </funding>
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      <item>cent_sus_tech</item>
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    <collection_method>Both 1:1 (IL) and 1:2 (DES) mixtures between choline (Ch) and geranic acid (GA) or octanoic acid (OA) were synthesised using hydrogenated and deuterated species for neutron reflectivity (NR) experiments. The structure of the mixtures were first characterised by dynamic light scattering (DLS), before their behaviour with lipidic phases was assessed by quartz-crystal microbalance with dissipation (QCM-D) measurements alongside NR.

IL/DES preparation:
Briefly, either geranic acid or octanoic acid were dissolved in ethanol and added dropwise to a solution of d9-choline hydroxide or choline bicarbonate in water, as appropriate. This was stirred for 2 h before excess solvent was removed under reduced pressure. Resultant viscous liquids were dried under vacuum for 24 h before use.

SUV preparation:
SUVs were prepared from a thin-film technique where DMPC was initial dissolved in chloroform (1 mg ml-1) and rotary dried under N2 (g). The resulting film was swelled with 2 ml of water heated to 35 oC and vortexed to create a suspension. Whilst the mixture was still warm, suspensions were bath sonicated to clarity indicating the formation of SUVs (~20-100 nm) that do not scatter light. 

Supported Vesicle Layer (SVL) preparation:
DMPC SUVs were incubated with Au-coated substrates for 30 minutes before rinsing with clean solvent.

Supported Lipid Bilayer (SLB) preparation:
SLBs were prepared by SUV collapse. Prior to use, SUV suspensions were centrifuged for 15 mins (16,000 x g) to remove any multi-lamellar vesicles. Separately, an aqueous CaCl2 solution (1 mM) was prepared and used to dilute the vesicles to 0.3 mg ml-1. This solution was then injected over SiO2-coated substrates (0.5 ml min-1, 30 mins), before rinsing with clean solvent.</collection_method>
    <provenance>Beamline data from the FIGARO specular NR instrument is available separately from Institut Laue-Langevin.

1H NMR:
Spectra were analysed using Mestrelab MNova 11.0 software where spectra were baseline corrected to allow integration of peak area.

QCM-D:
Before the relevant injection point, a stable baseline was chosen as the zero reference and the frequency and dissipation data relativised accordingly. Mass deposition was calculated using the Sauerbrey equation. A sensitivity of 17.7 ng Hz-1 cm-2 was used for 5 MHz chips (SiO2-coated) and 4.4 ng Hz-1 cm-2 for 10 MHz (Au-coated) was used.</provenance>
    <techinfo>DFT Calculations:
To estimate molecular volume, DFT calculations of 1:2 CAGE, 1:2 CAOT and their constituent parts were performed using Gaussian 16. All structures were visualised and checked using frequency analysis. 

DLS:
DLS was conducted using a Malvern Zetasizer Nanoseries and plastic cuvettes. Measurements were taken using backscattering and a wavelength of 663 nm. For each sample five sets of measurements were taken, consisting of at least 12 runs each. 

QCM-D:
Measurements were conducted using an OpenQCM Q-1 sensor module with either SiO2-coated (5 MHz) or Au-coated (10 MHz) quartz chips (13.9 mm diameter). Chips were rinsed with ethanol, acetone and water before cleaning under UV/ozone for 15 mins. These were then sealed in flow cells and calibrated in air before incubation with clean solvents. Once a stable baseline occurred, experimental protocols were commenced. 

NR: 
Experiments were conducted at the Institut Laue-Langevin (ILL), France, on the FIGARO specular neutron reflectivity beamline. Before use, Si blocks (8 x 5 cm; 3 Å roughness) were cleaned under UV/ozone for 15 mins, rinsed with ultrafiltered water and then sealed into flow cells flanked by steel plates for temperature control. Resulting multidimensional time-of-flight data were reduced using the COSMOS software available at ILL. Models were fit using the Markov-Chain-Monte-Carlo (MCMC) algorithm within Refnx.</techinfo>
    <language>en</language>
    <version>1</version>
    <doi>10.15125/BATH-01289</doi>
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        <link>https://doi.org/10.1002/adfm.202306644</link>
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