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This text describes the data presented in the paper: Measuring membrane permeation rates through the optical visualisation of a single pore
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Introductory information
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Files included in the data deposit (include a short description of what data are contained): 

Videos of bubbles within model membranes changing size in response to a change in the external gas composition. File names indicate the assumed initial and final bubble CO2 %.
50% to 0.04%.avi
50% to 10%.avi
0.04% to 50%.avi
50% to 1.1%.avi
1.1% to 50%.avi
10% to 50%.avi

Permeation experiments with multiple-pore real membranes. File names indicate date of experiment and sample (all .xlsx and .csv files are mass spec data, all .txt files are FTIR data). Temperature, feed/permeate gases were changed. Analysis conducted on portions of data. Example of zero gas calibration included.
Fig. 3 multiple-pore membrane.xlsx

Explain the relationship between multiple data sets, if required:

Videos of model membranes were used in the calculation and construction of Fig. 1 and 2 in the manuscript.
Permeation experiments with real membranes were used in the calculation and construction of Fig 3 (with additional data taken from literature as per publication).

Key words used to describe the data:

carbon capture, ceramics, membrane separation

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Methodological information
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A brief method description – what the data is, how and why it was collected or created, and how it was processed:

Experiments were conducted on single-pore single crystal model membranes.
The single pore was infiltrated with molten carbonate.
The infiltrated model membrane was hosted inside an in-situ cell at high temperature (>400C).
The infiltrated model membrane was then subjected to a change in gas composition within the in-situ cell.
In response, gas bubbles within the single pore changed in volume as CO2 permeated in or out of the bubble.
Volume changes were converted to permeation rates using the following equations:

nt = nCO2.t + nN2.t or nt = nCO2.t + nN2.to
where,
nt, is the total number of moles of gas mixture in the bubble at time t.
nCO2t and nN2t is the number of moles of CO2 and N2 in the bubble at time t.
nN2.to is the initial number of moles of N2 in the bubble.
PtVt = PCO2.tVt + PN2to.Vto
where,
Pt is the total pressure in the bubble at time t.
PCO2t is the CO2 partial pressure in the bubble at time t.
Vto is the volume of the gas bubble at time to.
PN2.to is the partial pressure of N2 in the gas bubble at time to.
and,
PCO2.t = Pt - (PN2.to Vto)/Vt
and,
Vt/Vto = PN2.to/PN2t
and,
Permeation Rate = (Pt . (Vt2 - Vt1))/RT(t2 - t1)
Permeation rate was converted to flux using the dimensions of the single pore mouth.

Experiments were conducted on multiple-pore real membranes.
The multiple pores were infiltrated with molten carbonate.
The infiltrated membrane was hosted inside a permeation cell at high temperature (>400C).
The infiltrated membrane was then subjected to permeation experiments with e.g. 90, 77, 50 and 25% CO2/N2 feed gases and 1.1, 0.1, 0.04 and 0% CO2/Ar sweep gases.
Permeation rates were calculated using the following equations:

Permeation Rate = (x'CO2(outlet) - x'CO2(inlet).Q
where,
x'CO2(outlet) = average mole fraction of CO2 at steady state in the oulet of the permeate side
x'CO2(inlet) = average mole fraction of CO2 at steady state in the inlet stream of the permeate side
Q = flow rate
Permeation rate was converted to flux using the dimensions of the multiple pores exposed to the feed gas.

Instruments, hardware and software used: 

Custom-made membrane reactor
Custom-made in-situ cell (based on Linkam TS1500)
Confocal microscope (Olympus, BX41)
20x long-working-distance objective (Olympus, LMPLFLN20x)
Mathematica(TM)
Mass Spectrometer (HIDEN, HALO 100-RC)
CO2 IR Analyser (LI-COR, LI840A)
OriginPro(TM)

Date(s) of data collection: 

11/2014 - 11/2019

Geographic coverage of data:

n/a

Data validation (how was the data checked, proofed and cleaned):

Data was validated by comparison to literature data, mass balance expectations, and repetitions and calibration as well as thermodynamic expectations.
Visual data was binned so that the extracted data had a lower resolution compared to the original video data (i.e. fewer than all frames were analysed).

Overview of secondary data, if used:

n/a

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Data-specific information
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Definitions of names, labels, acronyms or specialist terminology uses for variables, records and their values: 

All labels are explained as above.

Explanation of weighting and grossing variables: 

n/a

Outline any missing data:

A selection of images are used in the publication to convey e.g. the in-situ cell, the membrane permeation apparatus and images of the samples, not included here.

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Contact
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Please contact rdm@ncl.ac.uk for further information