Viscosity Measurements of Aviation Turbine FuelsTara J. Fortin* and Arno Laesecke

National Institute of Standards and Technology, Material Measurement Laboratory, Applied Chemicals and Materials Division, 325Broadway, Boulder, Colorado 80305-3328, United States

*S Supporting Information

ABSTRACT: Kinematic viscosity has been measured for nine separate aviation turbine fuel samples. The nine samples span therange of fuel types available: conventional petroleum-derived fuels, synthetic fuels derived from the Fischer−Tropsch process,and renewable fuels derived from biomass feedstocks. Results for a tenth sample intended for use in quantifying the total sulfur infuel oils are also included for comparison. All measurements were made at ambient pressure and over the temperature range of293−373 K. A significant degree of variability is observed among the measured viscosities. Measurement data for theconventional fuel samples were also compared to the predictions of two existing surrogate mixture models.

1. INTRODUCTION

According to the International Air Transport Association(IATA), the world’s airlines carried approximately 3 billionpassengers and consumed 73 billion U.S. gallons of fuel in2012.1 Total fuel costs for 2012 were estimated at $209 billion,an approximately $60 billion increase over 2010 costs resultingfrom an increase in fuel prices.1 With fuel costs constitutingapproximately 33% of airline operating costs in 20121 andconsumption expected to keep increasing,2 the industry isactively seeking ways to improve efficiencies and secure stablefuel supplies. These objectives have the potential added benefitof helping the industry implement its vision for mitigatinggreenhouse gas emissions. For example, in 2009, IATA memberairlines adopted the following targets: carbon neutral growthfrom 2020, an average 1.5% per year improvement in fuelefficiency through 2020, and a 50% reduction in carbon dioxide(CO2) emissions relative to 2005 levels by the year 2050.3

Similar goals have been agreed upon by the International CivilAviation Organization (ICAO) Group on InternationalAviation and Climate Change (GIACC).4 The pursuit of lowcarbon, drop-in alternative jet fuels to complement improve-ments in operational and equipment efficiency is a keycomponent of the industry’s strategy.2−8

Jet fuels are complex mixtures consisting of hundreds ofdifferent hydrocarbons; the relative abundance of compoundtype (paraffin, cycloparaffin, etc.) varies depending on the crudeoil from which the fuel was derived and which refining processwas used.9 The most common commercial aviation turbinefuels are Jet A, primarily used within the United States (U.S.),and Jet A-1. The two fuels are similar except that Jet A-1 has alower freeze point and often contains a static dissipateradditive.10 Potential alternatives include synthetic fuelsmanufactured from coal or natural gas using a Fischer−Tropsch process and renewable fuels derived from biomassfeedstocks such as vegetable oils, animal fat, waste grease,switch grass, and algae via a variety of processes.7,11 Currently,Fischer−Tropsch fuels and fuels produced from a hydro-processed esters and fatty acids (HEFA) process (also knownas hydrotreated renewable jet (HRJ) fuels) are certified forcommercial use as blends with conventional fuels;11,12 addi-

tional conversion processes are under development and couldone day be considered for approval.6 Ultimately, whether or nota particular alternative fuel becomes commercially viabledepends on a variety of factors, including feedstock availabilityand processing costs. But more importantly, for a fuel to beconsidered a viable drop-in candidate, it must first exhibitproperties that would allow it to be blended with, or completelyreplace, Jet A without requiring substantial equipmentmodification. Some important properties to consider are itsdensity, speed of sound, thermal stability, volatility, andviscosity; we will be discussing viscosity measurements in thiswork.Viscosity is the measure of a fluid’s ability to transmit

momentum resulting from cohesive forces among molecules.These forces appear as shear stresses between fluid layersmoving at different velocities. Dynamic, or absolute, viscosity isdefined as the ratio between the applied shear stress and therate of shear of a material and can be thought of as themomentum conductivity.13 The kinematic viscosity of a fluid isdefined as the ratio of the dynamic viscosity to the density andcan be thought of as the momentum diffusivity since it is theratio between momentum transport and momentum storage.13

In this work we report measurements of kinematic viscosity atambient pressure for several aviation turbine fuels of varyingorigin (conventional, synthetic, and renewable). Since thetemperature dependence of viscosity is as important as theviscosity itself, measurements were carried out over the range of293−373 K.

2. MATERIALS AND METHODS2.1. Fuel Samples. Nine samples of aviation turbine fuels were

obtained from the Air Force Research Laboratory PropulsionDirectorate at Wright Patterson Air Force Base. These samplesinclude both commercially available and prototype fuels, and theyrepresent both conventional and alternative fuel sources. For each ofthese nine samples, the viscosity data presented here are one

Received: February 26, 2015Revised: July 29, 2015Published: September 3, 2015

Article

pubs.acs.org/EF

This article not subject to U.S. Copyright.Published 2015 by the American ChemicalSociety

5495 DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

Table 1. Top Ten Components (by Area %) of the Measured Fuel Samples

compound CAS no. area %

Jet A 360223

n-undecane 1120-21-4 5.99n-dodecane 112-40-3 5.66n-decane 124-18-5 5.50n-nonane 111-84-2 4.42n-tridecane 629-50-5 4.334-ethyloctane 15869-86-0 2.85n-heptane 142-82-5 2.79cis-1,3-dimethylcyclohexane 638-04-0 2.74n-octane 111-65-9 2.54xylene 1330-20-7 2.51

Jet A 363823

n-undecane 1120-21-4 9.80n-dodecane 112-40-3 8.03n-decane 124-18-5 7.17n-tridecane 629-50-5 4.911,2,3,4-tetrahydro-6-methylnaphthalene 1680-51-9 2.56w,x,y,z-tetramethylcyclohexanea 2.352,6-dimethylundecane 17301-23-4 2.332,2,3,3-tetramethylhexane 13475-81-5 2.23n-nonane 111-84-2 2.121,4-diethylbenzene 105-05-5 1.92

Jet A 465823

n-dodecane 112-40-3 6.23n-tridecane 629-50-5 5.58n-undecane 1120-21-4 5.46n-decane 124-18-5 4.60n-tetradecane 629-59-4 3.571-methyl-3-(1-methylethyl)benzene 535-77-3 2.692-methyldodecane 1560-97-0 2.43n-nonane 111-84-2 2.431-ethyl-2-methylbenzene 611-14-3 2.15(1-methyl-1-butenyl)benzene 53172-84-2 2.12

SRM 1617b41

n-undecane 1120-21-4 11.05n-dodecane 112-40-3 8.77n-tridecane 629-50-5 7.36n-tetradecane 629-59-4 5.83n-decane 124-18-5 4.33decahydro-2-methylnaphthalene 2958-76-1 2.282-methyldecane 6975-98-0 2.133-methyldecane 13151-34-3 1.942,6-dimethylundecane 17301-23-4 1.91n-pentadecane 629-62-9 1.68

S814

n-dodecane 112-40-3 2.434-methyloctane 2216-34-4 2.42n-undecane 1120-21-4 2.28n-decane 124-18-5 1.944-methylnonane 17301-94-9 1.79x,y-dimethylundecanea 1.732,4-dimethylundecane 17312-80-0 1.66n-tridecane 629-50-5 1.635-methylundecane 1632-70-8 1.59n-nonane 111-84-2 1.53

GTL20

n-decane 124-18-5 14.52-methylnonane 871-83-0 12.3n-nonane 111-84-2 10.42-methyldecane 6975-98-0 8.23,6-dimethyloctane 15869-94-0 6.4

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5496

component of a more extensive research effort aimed at characterizingthe chemical and thermophysical properties of aviation fuels.14−24

Three of the nine samples represent conventional, petroleum-basedaviation turbine fuel. These are three separate samples of Jet A,designated 3602, 3638, and 4658. In the U.S., Jet A is the mostcommonly used commercial aviation turbine fuel. For Jet A to beeligible for sale, select characteristics of the fuel, such as composition interms of acidity and aromatic and sulfur content, volatility, and fluidity,among others, must comply with the detailed requirementsenumerated in ASTM-D1655.25 This standard is primarily aperformance specification since variability resulting from differences

in crude sources and manufacturing processes precludes theformulation of a strict compositional specification.25 The three Jet Asamples measured and discussed herein were intended to capturesome of the expected variability, with Jet A 4658 intended as an“average” sample. Specifically, Jet A 4658 is a composite mixture ofapproximately equal volumes of several available batches of Jet A, eachfrom different manufacturers.

Three additional samples represent synthetic isoparaffinic kerosenes(S-IPK). All three were produced using the Fischer−Tropsch (FT)process wherein a synthesis gas of carbon monoxide and hydrogen isconverted to liquid fuel over a catalyst.26−30 The first, S8, is derived

Table 1. continued

compound CAS no. area %

GTL20

n-undecane 1120-21-4 5.13-methylnonane 5911-09-6 4.74,5-dimethylnonane 17302-23-7 4.22,3,4-trimethylhexane 921-47-1 3.5n-hexane 110-54-3 3.3

CTL20

2,5,6-trimethyloctane 62016-14-2 5.3x-methyldecanea 3.22,3-dimethyloctane 7146-60-3 2.93,7-dimethylnonane 17302-32-8 2.82,4,6-trimethyloctane 62016-37-9 2.2x-methyldecanea 2.2x-methylnonanea 2.1n-decane 124-18-5 2.12,5-dimethyloctane 15869-89-3 2.0x-methylundecanea 1.9

CSK21

cis-1-methyl-4-(1-methylethyl)cyclohexane 6069-98-3 47.14o-, m-, and p-1-methyl-x-(1-methylethyl)benzeneb (ortho) 527-84-4 25.77

(meta) 535-77-3(para) 99-87-6

trans-1-methyl-4-(1-methylethyl)cyclohexane 1678-82-6 22.43x,y-dimethyloctanea,c 4.34

C-HRJ21

4-methyloctane 2216-34-4 10.692-methylnonane 871-83-0 8.492,5-dimethylnonane 17302-27-1 6.152-methyldecane 6975-98-0 5.795-methylundecane 1632-70-8 5.332,5-dimethyloctane 15869-89-3 5.13n-dodecane 112-40-3 4.393,6-dimethyloctane 15869-94-0 4.172,5-dimethylheptane 2216-30-0 4.153-methylnonane 5911-04-6 4.15

Cs-HRJ21

n-decane 124-18-5 7.94n-undecane 1120-21-4 6.722-methylnonane 871-83-0 6.695-methyldecane 13151-35-4 6.043-methylnonane 5911-04-6 3.734-methyloctane 2216-34-4 3.44n-nonane 111-84-2 2.972,5-dimethyloctane 15869-89-3 2.924-methyldecane 2847-72-5 2.283-methyloctane 2216-33-3 2.07

aIt is not always possible to determine the position of methyl substitution. In these instances, the position is indicated with a letter. bThe threeisomers coelute in a peak centered at a retention time of 5.888 min. The value of x is 2, 3, and 4 for the ortho, meta, and para isomers, respectively.cThis component was previously identified as 3,6-dimethyloctane,21 but the manufacturer of the fluid has cited 2,6-dimethyloctane as the more likelyisomer considering the synthesis process. The present designation better reflects the uncertainty in the identification of this component.

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5497

from natural gas.31 It was developed for the United States Air Force asa synthetic substitute for JP-8 and has been certified for use in 50/50blends with JP-8 in B-52 aircraft.31 The second FT fuel sample is alsoderived from natural gas and has been tested in 50/50 blends with JP-8by the U.S. Air Force.31 It will herein be referred to as GTL (gas-to-liquid). The final FT fuel sample is derived from coal.31 This fuel,herein referred to as CTL (coal-to-liquid), has been used in blends atO. R. Tambo International Airport in Johannesburg, South Africa,since 1999.31

The final three aviation turbine fuel samples are derived fromvarious biomass feedstocks. The first of these is obtained from plantisoprenoids via the fermentation reaction of a sugar with arecombinant host cell.21,32 This fuel will herein be referred to ascellular synthetic kerosene, CSK. The remaining two bioderivedsamples are produced from two different oilseed crops, camelina(Camelina sativa)33 and castor (Ricinus communis).34 Both are hardyplants that provide relatively high oil yields making them attractive aspotential energy crops.34−36 In fact, camelina-derived jet fuels havebeen used in blends during test flights by two commercial airlines37,38

and the U.S. military.39 Because the production of the finished fuelrequires hydrodeoxygenation and hydroprocessing, these oilseed-derived fuels are often referred to as hydrotreated renewable jet (HRJ)fuels. Therefore, throughout the remainder of this work, the camelinasample will be referred to as C-HRJ and the castor sample as Cs-HRJ.In addition to the aforementioned fuel samples, a tenth sample was

measured and the results are also included here. That sample wasobtained from the Analytical Chemistry Division of the MaterialMeasurement Laboratory at the National Institute of Standards andTechnology (NIST). The sample is a candidate for a Standard

Reference Material (SRM) to quantify the total sulfur in fuel oils ormaterials of similar matrix.40 As such, it would be part of a suite ofliquid fuel SRMs provided by NIST. Once certified, it will replaceSRM 1617a,40 which is currently out of stock. This sample will bereferred to as SRM 1617b.

As part of earlier research efforts, the chemical composition of eachof the nine jet fuel samples was analyzed using gas chromatography−mass spectrometry (GC-MS) and the results have been publishedelsewhere.14,15,20,21,23 The chemical composition of SRM 1617b wasdetermined in conjunction with the measurements reported here.41

For each of the ten samples, a subset consisting of the top tenobserved components is shown in Table 1. Chemical names andcorresponding CAS registry numbers are listed, sorted by theuncalibrated chromatographic peak area. The one notable exceptionis CSK, which only has four components listed; together, those fourcomponents account for more than 99% of the measured chromato-graphic peak area. For the remaining samples, the components listed inTable 1 account for approximately 19% to 73% of the total measuredchromatographic peak area. As Table 1 shows, all but CSK arecomposed primarily of linear and branched alkanes (or paraffins); CSKis composed primarily of closely boiling cyclic compounds and a smallquantity of x,y-dimethyloctane.

Further comparison among the fuel samples is possible with the aidof a classification method based on ASTM Method D-278942 wheremass spectral fragments are used to classify hydrocarbon samples intosix different types or families: paraffins (P), monocycloparaffins(MCP), dicycloparaffins (DCP), alkylbenzenes (AB), indanes andtetralins (I&T), and naphthalenes (N). A discussion of the limitationsand uncertainties of this method can be found in Smith and Bruno.43

Figure 1. Schematic representation of the hydrocarbon classification analysis of all measured samples.20,21,23,41,44 Analysis is based on ASTM MethodD-2789,42 which classifies hydrocarbon samples into six families: paraffins (P), monocycloparaffins (MCP), dicycloparaffins (DCP), alkylbenzenes(AB), indanes and tetralins (I&T), and naphthalenes (N). Numbers shown represent the measured percent volume fraction for each of the sixfamilies. Volume fractions of less than 1% are not labeled.

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5498

Table

2.MeasuredKinem

atic

Viscosities

forCon

ventionalPetroleum

-Derived

Samples

atAmbientPressurea

JetA3602

JetA3638

JetA4658

SRM

1617b

T(K

)ν (m

m2 ·s

−1 )

t 95b

U(ν)c

(mm

2 ·s−1 )

ν(m

m2 ·s

−1 )

t 95b

U(ν)c

(mm

2 ·s−1 )

ν(m

m2 ·s

−1 )

t 95b

U(ν)c

(mm

2 ·s−1 )

ν(m

m2 ·s

−1 )

t 95b

U(ν)c

(mm

2 ·s−1 )

293.15

1.907

2.006

0.006

1.650

2.011

0.006

1.953

2.007

0.006

1.957

2.012

0.007

298.15

1.750

2.008

0.006

1.523

2.014

0.006

1.790

2.008

0.006

1.794

2.011

0.007

303.15

1.614

2.011

0.006

1.412

2.015

0.006

1.649

2.009

0.006

1.652

2.008

0.007

308.15

1.495

2.009

0.006

1.314

2.015

0.006

1.525

2.011

0.006

1.527

2.008

0.006

313.15

1.391

2.007

0.006

1.232

2.000

0.006

1.418

2.006

0.006

1.419

2.008

0.006

318.15

1.299

2.004

0.006

1.155

1.996

0.007

1.322

2.003

0.006

1.323

2.005

0.006

323.15

1.216

1.998

0.007

1.086

1.994

0.007

1.238

1.999

0.006

1.237

2.004

0.006

328.15

1.143

1.996

0.007

1.023

1.995

0.008

1.162

1.995

0.007

1.159

2.002

0.006

333.15

1.077

1.995

0.007

0.967

2.000

0.009

1.095

1.995

0.007

1.091

1.998

0.007

338.15

1.017

1.995

0.008

0.916

2.004

0.010

1.033

1.995

0.008

1.029

1.996

0.007

343.15

0.963

1.998

0.009

0.869

2.009

0.011

0.978

1.998

0.009

0.973

1.994

0.007

348.15

0.913

2.002

0.009

0.826

2.013

0.012

0.928

2.002

0.009

0.922

1.994

0.007

353.15

0.870

2.009

0.011

0.788

2.018

0.013

0.882

2.007

0.010

0.876

1.995

0.008

358.15

0.829

2.013

0.012

0.752

2.021

0.015

0.840

2.012

0.011

0.834

1.997

0.008

363.15

0.792

2.018

0.013

0.718

2.024

0.016

0.801

2.015

0.013

0.795

2.000

0.009

368.15

0.757

2.021

0.015

0.688

2.028

0.018

0.766

2.021

0.014

0.759

2.003

0.010

373.15

0.725

2.024

0.016

0.660

2.030

0.020

0.734

2.024

0.016

0.726

2.008

0.011

aAmbientpressure

durin

gmeasurements

was

∼83

kPa.bCoveragefactor

from

thet-d

istributionforeach

correspondingdegreesof

freedom

anda95%

levelof

confidence.

c U(ν)istheexpanded

uncertaintyat

the95%

confidencelevelforkinematicviscosity.

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5499

The results of the hydrocarbon classification for the nine jet fuelsamples have previously been reported elsewhere;20,21,23,44 theclassification results for SRM 1617b were determined for inclusionhere.41 The results for all ten samples are represented schematically inFigure 1. For all but CSK, linear and branched paraffins dominate;together they account for approximately 29% to 40% (v/v) of the totalcomposition for the four petroleum-derived samples. Those valuesincrease to approximately 71% to 80% (v/v) for the three syntheticand two HRJ samples. In contrast, paraffins account for just 5% (v/v)of the total composition for CSK, while cycloparaffins dominate atapproximately 45% and 23% (v/v) for monocycloparaffins anddicycloparaffins, respectively. Cycloparaffins are also present insubstantial quantities for the other nine samples. For the three Jet Asamples and SRM 1617b, both monocycloparaffins and dicyclopar-affins are significant, accounting for approximately 25% to 31% (v/v)and 10% to 13% (v/v), respectively. For the remaining five samples,only monocycloparaffins appear to be present in sizable quantities,ranging from approximately 17% to 23% (v/v) of the totalcomposition. However, it should be noted that the apparent quantitiesof monocycloparaffins may be artificially high since some mass spectralfragments, such as CH2CHCH2

• at m/z = 41, can be produced fromparaffinic species but are only included in the monocycloparaffinsummation.45 Finally, while the four conventional samples and CSKhave appreciable quantities of aromatics, the remaining five samplescontain only minor quantities of aromatic compounds.2.2. Kinematic Viscosity Measurements. A commercial

automated open gravitational glass capillary viscometer was usedwith our own measurement protocol to determine kinematic viscosity(ν) at ambient atmospheric pressure (∼83 kPa in Boulder, CO, USA)from 293 to 373 K. The instrument was previously used formeasurements of rocket propellants and biofuel SRMs.46,47 Aphotograph of the instrument with principal components labeled canbe found in Figure A2.1 of the Supporting Information. At the core ofthe instrument is a suspended-level Ubbelohde glass capillarycomprised of two timing bulbs with a combined measurement rangeof approximately 0.3 mm2·s−1 to 30 mm2·s−1. The lower, smaller bulb(bulb 1) is used for liquids with kinematic viscosities of approximately3−30 mm2·s−1, while the upper, larger bulb (bulb 2) is used formeasurements from approximately 0.3−3 mm2·s−1. All measurementsreported herein were made utilizing bulb 2. The capillary tube isimmersed in a thermostated bath filled with silicone oil, thetemperature of which is controlled with the combination of a stirrer,thermoelectric Peltier elements, and an internal temperature sensor.

Additionally, an external platinum resistance thermometer (PRT) issuspended in the bath for use as a temperature reference. Borderingeither side of the two timing bulbs are three thermistor sensors thatdetect the passing of the sample liquid meniscus; the time required forthe meniscus to pass between two corresponding thermistors, theefflux time (τ), is the measurand for this instrument. For measure-ments utilizing bulb 2, τ is determined between the thermistors locatedabove bulb 2 (thermistor 3) and below bulb 1 (thermistor 1).Additional discussion concerning the impedance flow characteristics ofthe instrument can be found in Laesecke et al.47

The measured efflux time is related to kinematic viscosity via theequation

ν τ ετ

= −c 2 (1)

where ν and τ were previously defined and c and ε are parameters thatare specific to each timing bulb and are determined via instrumentcalibration. The instrument is calibrated by measuring several certifiedviscosity reference standards (CVRS) at temperatures from 20 to 100°C. The CVRS used during the calibration of bulb 2 were N.4, N1.0,S3, S6, and N14 obtained from Cannon Instrument Co. Combined,these standards cover the approximate viscosity range of 0.4−3.4mm2·s−1 for measurements using bulb 2; however, it was determinedthat only a subset of the CVRS measurements was needed to optimizecalibration results. Specifically, only those data points with 49 s ≤ τ <140 s, corresponding to certified viscosities between approximately 0.5and 1.3 mm2·s−1, were fit to determine c and ε. By limiting the range offitted points in this manner, we were able to maximize the number ofdata points whose measured values then fell within the reportedexpanded uncertainties of the CVRS samples (0.16% to 0.21%,depending on temperature and viscosity), including those whoseviscosities exceed both the fit range and the range of jet fuel viscositiesmeasured in this work.47 Additional details concerning the calibrationprocedures and the parameter values c and ε used in this work can befound in Appendix A1 of the Supporting Information.

For each measurement sample, an aliquot of approximately 15 mL istransferred to a new, clean 20 mL glass vial. The vial is placed in theinstrument’s sample holder and raised into place so that theinstrument’s sampling tube is submerged in the sample. During ameasurement, sample is drawn up into the capillary tube to a levelabove the bulb of interest (bulb 2) and held there for 5 min to allowfor temperature equilibration. The sample holder is equipped with aheater, so to aid in temperature equilibration all samples were

Table 3. Measured Kinematic Viscosities for Synthetic Fuel Samples at Ambient Pressurea

S8 GTL CTL

T (K) ν (mm2·s‑1) t95b U(ν )

c (mm2·s−1) ν (mm2·s−1) t95b U(ν)c (mm2·s−1) ν (mm2·s−1) t95

b U(ν)c (mm2·s−1)

293.15 1.753 2.009 0.006 1.199 2.028 0.006 1.498 2.015 0.006298.15 1.613 2.011 0.006 1.118 2.032 0.021 1.387 2.020 0.006303.15 1.490 2.013 0.006 1.047 2.032 0.022 1.288 2.021 0.006308.15 1.384 2.013 0.006 0.984 2.032 0.022 1.201 2.020 0.006313.15 1.290 2.010 0.006 0.926 2.032 0.022 1.124 2.017 0.006318.15 1.207 2.006 0.006 0.875 2.035 0.022 1.056 2.012 0.006323.15 1.133 2.002 0.006 0.828 2.035 0.022 0.994 2.005 0.006328.15 1.069 1.996 0.007 0.785 2.035 0.022 0.938 2.000 0.007333.15 1.008 1.995 0.007 0.746 2.035 0.023 0.889 1.997 0.007338.15 0.954 1.997 0.008 0.711 2.035 0.023 0.843 1.997 0.008343.15 0.904 1.999 0.009 0.678 2.035 0.023 0.801 1.998 0.008348.15 0.860 2.003 0.010 0.648 2.035 0.023 0.763 2.002 0.009353.15 0.819 2.008 0.011 0.620 2.035 0.023 0.728 2.006 0.010358.15 0.782 2.013 0.012 0.594 2.035 0.023 0.695 2.011 0.011363.15 0.748 2.017 0.013 0.569 2.035 0.023 0.665 2.014 0.012368.15 0.717 2.021 0.014 0.547 2.035 0.024 0.638 2.020 0.014373.15 0.687 2.024 0.016 0.526 2.035 0.024 0.612 2.023 0.015

aAmbient pressure during measurements was ∼83 kPa. bCoverage factor from the t-distribution for each corresponding degrees of freedom and a95% level of confidence. cU(ν) is expanded uncertainty at the 95% confidence level for kinematic viscosity.

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5500

preheated to a temperature of 313 K for all measurements at ≥313 K.After the temperature equilibration period, the liquid is released and itsprogress through the tube is timed. During the measurements reportedhere, each separate 15 mL sample aliquot was measured in aprogrammed scan from 293 to 373 K in 5 K increments. At eachtemperature, efflux time measurements were repeated until threeconsecutive tests agreed within 0.25%. Additionally, for each fueltested, at least one other 15 mL sample was prepared and measured tocheck for reproducibility between sample aliquots. With the exceptionof Cs-HRJ, all kinematic viscosity results reported in the tablesincluded herein are from the final sample aliquot measured; the secondof three samples is reported for Cs-HRJ because a valid measurementresult at 343 K was missing for the third sample. The observed sample-to-sample reproducibility was taken into consideration during thecalculation of reported uncertainties. Because the sample remains opento the atmosphere over the course of a full temperature scan, a periodof 9 h or more, changing sample composition resulting from the loss ofmore volatile components with time and temperature is a concern.Measurements of multiple sample aliquots help us arrive at areasonable estimate of the corresponding uncertainty contribution.This is discussed in further detail in Appendix A3 of the SupportingInformation.The instrument is thoroughly cleaned and dried between each new

measurement sample. Since previous work illustrated the potential forsample cross-contamination when following the manufacturer’srecommended cleaning procedure,48 a more thorough cleaningprocedure combining both a bottom up and top down approachwas implemented during this work. Details are given in Appendix A2of the Supporting Information.

3. RESULTS AND DISCUSSIONKinematic viscosity measurement results are presented inTables 2−4; conventional petroleum-derived samples are inTable 2, synthetic fuel samples are in Table 3, and biomass-derived fuel samples are in Table 4. As was previouslymentioned, tabulated viscosities are an average (ν) of threeconsecutive measurements of a given sample at each temper-ature. Also included in the tables are the associated expandeduncertainty estimates (U(ν )), which are calculated according tothe expression

ν ν = νU t u( ) (df ) ( )95 (2)

where t95(dfν) is the coverage factor taken from the t-distribution for dfν degrees of freedom and 95% confidencelevel, and u(ν ) is the combined standard uncertainty for thekinematic viscosity measurements. In the absence of softwarewith statistical analysis capabilities, the corresponding value oft95(dfν) can be determined from Table G.2 of the Guide to theExpression of Uncertainty in Measurement49 by interpolation. Thecorresponding values of t95(dfν) are included in Tables 2−4 forclarity. Additional details regarding the uncertainty analysisemployed in this work are given in Appendix A3 of theSupporting Information.The expanded uncertainties reported in Tables 2−4 range

from an overall minimum of 0.006 mm2·s−1 to an overallmaximum of 0.024 mm2·s−1. In terms of relative expandeduncertainties, our estimates range from an overall minimum ofapproximately 0.31% (Jet A 4658 at 293 K) to an overallmaximum of approximately 4.5% (GTL at 373 K). While suchvalues may seem larger than perhaps expected, we believe thecomprehensive uncertainty analysis approach outlined inAppendix A3 of the Supporting Information results in areasonable estimate of the uncertainty associated with themeasurement of the volatile samples reported here. In fact, theresulting expanded uncertainties are in alignment with theobserved sample-to-sample variability, which was as low as0.002% and as high as 2.0%.To facilitate fuel-to-fuel comparisons, the kinematic viscosity

results reported in Tables 2−4 are plotted as a function oftemperature in Figure 2. It is clear from this figure that theobserved variability in kinematic viscosity is statisticallysignificant and varies with temperature; the overall spreadamong the ten samples ranges from 38.7% at 293 K to 28.3% at373 K. While the differences in chemical composition amongthe fuels are undoubtedly responsible for the observedvariability, no clear trends are readily apparent when comparingthe viscosity results (Figure 2) with the available compositioninformation (Table 1 and Figure 1). Specifically, it is clear fromFigure 2 that it is not possible to make simple statementsregarding trends in petroleum-derived fuels compared to S-IPKfuels compared to bioderived fuels since not all fuels of a given

Table 4. Measured Kinematic Viscosities for Biomass-Derived Fuel Samples at Ambient Pressurea

CSK C-HRJ Cs-HRJ

T (K) ν (mm2·s−1) t95b U(ν)c (mm2·s−1) ν (mm2·s−1) t95

b U(ν)c (mm2·s−1) ν (mm2·s−1) t95b U(ν)c (mm2·s−1)

293.15 1.257 2.023 0.006 1.474 2.015 0.006 1.888 1.999 0.007298.15 1.173 2.026 0.006 1.364 2.020 0.006 1.739 2.006 0.007303.15 1.096 2.024 0.006 1.269 2.021 0.006 1.597 2.002 0.006308.15 1.029 2.026 0.006 1.184 2.021 0.006 1.479 2.002 0.006313.15 0.968 2.020 0.006 1.109 2.013 0.006 1.374 2.001 0.006318.15 0.913 2.014 0.006 1.043 2.009 0.006 1.282 1.998 0.006323.15 0.863 2.009 0.006 0.983 2.004 0.006 1.200 1.994 0.007328.15 0.818 2.002 0.006 0.929 1.998 0.007 1.127 1.992 0.007333.15 0.777 1.998 0.007 0.880 1.997 0.007 1.063 1.992 0.008338.15 0.739 1.997 0.008 0.835 1.997 0.008 1.004 1.995 0.009343.15 0.704 1.998 0.008 0.794 1.999 0.008 0.950 1.999 0.009348.15 0.672 2.002 0.009 0.758 2.002 0.009 0.901 2.003 0.010353.15 0.642 2.006 0.010 0.724 2.008 0.010 0.856 2.008 0.011358.15 0.614 2.010 0.011 0.692 2.012 0.011 0.817 2.014 0.013363.15 0.589 2.014 0.012 0.663 2.017 0.013 0.779 2.020 0.014368.15 0.564 2.018 0.014 0.636 2.021 0.014 0.745 2.023 0.016373.15 0.542 2.023 0.015 0.612 2.024 0.016 0.714 2.023 0.018

aAmbient pressure during measurements was ∼83 kPa. bCoverage factor from the t-distribution for each corresponding degrees of freedom and a95% level of confidence. cU(ν) is the expanded uncertainty at the 95% confidence level for kinematic viscosity.

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5501

source type cluster together. For example, while the threesamples exhibiting the highest viscosities (SRM 1617b, Jet A4658, and Jet A 3602) are all derived from petroleum, thefourth petroleum-derived sample (Jet A 3638) exhibitssignificantly lower viscosities. The maximum observed spreadamong the aforementioned three petroleum-derived samplesranges from 2.6% at 293 K to 1.1% at 373 K, yet the maximumspread between the petroleum-derived sample with the highestviscosity and Jet A 3638 ranges from 15.7% at 293 K to 10.1%at 373 K.When trying to relate observed thermophysical properties to

fluid composition, it is necessary to take into consideration allfactors that can contribute to intermolecular interactions. Tothat end, Figure 3 shows the molecular size, shape, and chargedistribution of nine compounds that were chosen to representaromatics, cycloparaffins, and paraffins found in several of thefuels measured in this work. The molecules are shown in termsof their electron density distribution with the electrostaticpotential color-mapped onto it. Details of this rendering havebeen described previously.50 It should be noted that thecolorization of all nine compounds in Figure 3 corresponds tothe same electrostatic potential scale shown in the bottom rightcorner of the figure.In the most general terms, the presence of more larger,

heavier hydrocarbons would be expected to increase theviscosity of a fluid relative to one containing more smaller,lighter compounds. Additionally, viscosity would also beexpected to increase with the presence of aromatics andcycloparaffins. In contrast, branched paraffins would typicallybe expected to decrease viscosity. All three phenomena can beexplained in terms of how molecular size and shape influenceintermolecular interactions. Specifically, the van der Waalsforces primarily responsible for the intermolecular interactionsof nonpolar compounds increase with increased surface area. Inthe case of two straight-chain paraffins such as n-undecane andn-nonane, the larger n-undecane provides a larger surface areathereby increasing the opportunities for molecular interaction.Cyclic structures further enhance the effective surface area byreducing conformational freedom. An acyclic compound can

have numerous conformational possibilities (e.g., zigzag vs syn),which ultimately decreases the likelihood that any twomolecules in the vicinity of one another will have compatibleconformations. However, since cyclic compounds exhibit morelimited conformations, the likelihood of favorable interactions isincreased; this is particularly true for aromatic compounds sincethey are unable to change conformation. In contrast, branchedparaffins are more compact than their unbranched counterpartsand the decreased surface area results in weaker intermolecularinteractions.Unfortunately, while the preceding considerations can

contribute to the discussion of how composition contributesto observed viscosities, they do not necessarily allow for simpleexplanations when dealing with complex mixtures such as fuels.For example, it is tempting to attribute the large differencesbetween Jet A 3638 and the other petroleum-derived samplesto the fact that Jet A 3638 is known to have an unusually lowaromatic content relative to typical Jet A specimens51 or that itcontains more branched compounds than the others, both ofwhich should decrease viscosity. However, in terms ofcontributions that should increase viscosity, the cyclic andaromatic content of Jet A 3638 is comparable to the otherpetroleum-derived samples. Additionally, in terms of theaverage molecular weight of compounds present in each fuel,the expected order for the four petroleum samples from highestto lowest viscosity would be SRM 1617b, Jet A 4658, Jet A3638, and Jet A 3602. Finally, it is interesting to note that thedifferences in composition between the four petroleum-derivedsamples are small relative to the dramatically differentcomposition of S8 compared to Jet A 3638 (Figure 1), yetthese two samples exhibit relatively similar viscosities; thespread between S8 and Jet A 3638 ranges from 5.9% at 293 Kto 4.0% at 373 K.In addition to the preceding observations, the following

general trends are readily apparent in Figure 2. Cs-HRJ exhibits

Figure 2. Ambient pressure kinematic viscosity measurements for 10fuel samples plotted as a function of temperature.

Figure 3. Molecular size, shape, and charge distribution ofrepresentative compounds found in the fuels measured in this study.Representative aromatics include the following: a) 1,2,3,4-tetrahydro-6-methylnaphthalene, b) 1-methyl-3-(1-methylethyl)benzene, and c)(1-methyl-1-butenyl)benzene. Representative mono- and dicyclopar-affins include the following: d) trans-1-methyl-4-(1-methylethyl)-cyclohexane, e) decahydro-2-methylnaphthalene, and f) cis-1,3-dimethylcyclohexane. Representative paraffins include the following:g) 2,2,3,3-tetramethylhexane, h) 2,4,6-trimethyloctane, and i) 2,6-dimethylundecane.

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5502

viscosities that are more similar to Jet A 3602 (1.0% at 293 K)than they are to either C-HRJ (21.9% at 373 K) or CSK (33.4%at 373 K). The deviation relative to CSK may not be surprisinggiven its vastly different chemical composition (Figure 1). Thedeviation relative to C-HRJ is harder to reconcile given theirsimilarities; the one difference apparent in Table 1 is that thereare more straight-chain alkanes present in the top tencomponents of Cs-HRJ. Viscosities for the S-IPK fuels aresimilarly distributed: among the biobased fuels the overallspread is 33.4% at 293 K and 24.0% at 373 K; for the S-IPKfuels those values are 31.6% and 23.5%, respectively.Interestingly, the maximum spread within the S-IPK fuels isbetween S8 and GTL, the two FT fuels derived from naturalgas; the deviations between S8 and CTL are approximately halfthose observed for GTL. The final two clusters of data that areapparent in Figure 2 are CTL and C-HRJ, with a spread of 1.6%at 293 K and 0.1% at 373 K, and the two lowest viscosity fuelsCSK and GTL, with a spread of 4.6% at 293 K and 3.0% at 373K. The similarities between CTL and C-HRJ are possiblyexplained by the fact that for both fuels all but one of the tenmajor components are branched alkanes (Table 1). A similarreasoning cannot be applied in the case of CSK and GTL. Inaddition to a significant number of branched alkanes, GTL alsohas a lower average molecular weight than the other two S-IPKsamples, perhaps explaining why it has the lowest viscosity ofthe three. However, the low observed viscosity of CSK issurprising. While its average molecular weight is similar to thatof GTL, that of Jet A 3602 is even lower and yet that fuel hasone of the highest viscosities. Furthermore, CSK is predom-inantly composed of cyclic and aromatic compounds, whichgenerally increase viscosity.Finally, it is interesting to note that the viscosity trends

observed in Figure 2 do not strictly follow trends previouslyobserved in other fuel properties. To illustrate this, the resultsfrom previous measurements of density and speed ofsound18,22,24 are plotted in Figures 4 and 5, respectively, forall but SRM 1617b. As is seen with the viscosity data (Figure2), there is a general order of Jet A samples with the largest

values, GTL with the lowest values, and the rest fallingsomewhere in between. But whereas Jet A 4658 has the highestviscosity values, it is Jet A 3602 that exhibits the highest overallvalues for both density and speed of sound. Furthermore, therelative order of the remaining samples varies with no twoproperties showing the same order of compounds; the greatestdifference is for CSK, which exhibited some of the lowestviscosity values but some of the highest density and speed ofsound values.Very little data could be found in the literature31,52,53 to

which we could compare our viscosity results. What does existis typically reported only at 253 K since the aviation turbinefuel specification allows for a maximum viscosity of 8 mm2·s−1

at that temperature.25 Only Bessee et al.52 report data thatoverlaps at all with the results reported here, two data pointseach for CTL and C-HRJ. Specifically, they report viscosities of1.17 mm2·s−1 at 313 K and 0.62 mm2·s−1 at 373 K for CTL, andviscosities of 1.35 mm2·s−1 at 303 K and 1.10 mm2·s−1 at 313 Kfor C-HRJ.52 The deviations of our data relative to that ofBessee et al.52 range from 0.8% to as much as 6%, with only one(CTL at 373 K) falling within our reported uncertainties. Whendealing with complex fluid mixtures, particularly onescontaining highly volatile components, such as the fuels studiedhere, it is likely that such large discrepancies can be attributedto differences in composition among samples, either as theywere received, due to source variability, or as a result ofdistinctions in handling and measurement practices.In addition to the limited comparisons discussed above,

select viscosity data can be compared to the predictions ofsurrogate mixture models. Figure 6 shows experimental data forthe four petroleum-based samples, Jet A 3602, Jet A 3638, Jet A4658, and SRM 1617b, and one synthetic fuel, S8, along withthe aforementioned model predictions. The models, one for JetA 3638, one for Jet A 4658, and one for S8, were developed atNIST and have been implemented within the framework of theReference Fluid Thermodynamic and Transport Properties(REFPROP) program.16,19,54 Jet A viscosity values from theHandbook of Aviation Fuel Properties9 have also been included inFigure 6 for comparison. A couple of observations are apparent

Figure 4. Previously measured18,22,24 ambient pressure density data fornine fuel samples plotted as a function of temperature.

Figure 5. Previously measured18,22,24 ambient pressure speed of sounddata for nine fuel samples plotted as a function of temperature.

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5503

when looking at Figure 6. First, the Jet A viscosities reported inthe Handbook of Aviation Fuel Properties9 are in very goodagreement with Jet A 3602, SRM 1617b, and particularly withthe composite fuel, Jet A 4658. Second, the viscositypredictions of both Jet A surrogate mixture models are invery good agreement with their respective fuel, while thepredictions of the S8 model are noticeably low relative to themeasurement results reported here.Figure 7 shows more clearly the deviations between the

experimental measurements and their appropriate correspond-ing model. Specifically, the Jet A 3638 measurements arecompared to the Jet A 3638 model and the S8 measurementsare compared to the S8 model, while the remaining samples arecompared to the Jet A 4648 model. This was done since the JetA 4658 and, by extension, its surrogate mixture model aremeant to represent a typical Jet A sample. Also included inFigure 7 are the calculated deviations for the viscosity valuesfrom the Handbook of Aviation Fuel Properties9 compared to theJet A 4658 model. For Jet A 4658, SRM 1617b, and S8, theexperimental values are consistently higher than the Jet A 4658and S8 model predictions. For Jet A and SRM 1617b, a slighttemperature dependence is observed wherein the deviationsprimarily increase with increasing temperature; no significanttemperature dependence is observed for S8. More specifically,the absolute average deviation (AAD) for Jet A 4658 is 0.7%with a maximum deviation of 3.3% and a minimum deviation of0.8%; for SRM 1617b the values are 0.3%, 2.2%, and 0.9% forAAD, maximum, and minimum, respectively. For S8, the AAD,maximum, and minimum deviations are 0.3%, 3.9%, and 2.9%,respectively. For Jet A 3602 and Jet A 3638, experimental valuesare increasingly lower than the corresponding modelpredictions as the temperature decreases from 338 to 293 K,but above 338 K the experimental values are increasingly higherthan model predictions as the temperature increases. Jet A 3602

has an AAD of 0.9% and maximum and minimum deviations of2.1% and −1.3%, respectively. As expected, since the model isspecific to the fuel in question, the deviations are somewhatsmaller for Jet A 3638 with an AAD of 0.6%, a maximum of1.3%, and a minimum of −1.1%. For all five aforementionedsamples, the deviations exceed the corresponding experimentaluncertainties in many cases. However, for all but one point (JetA 4658 at 373 K), the deviations are within the reported modeluncertainty of ≥3%.16,19 In contrast to the experimental datareported here, the viscosity values from the Handbook ofAviation Fuel Properties9 exhibit increasing deviations withdecreasing temperature relative to the Jet A 4658 model. TheAAD for these data is 0.8%, and the maximum and minimumdeviations are 3.5% and −0.1%, respectively. The variabilityobserved in Figure 7, particularly the differences between Jet A4658 and Jet A 3602 relative to the Jet A 4658 model, can betaken as further evidence23 of the need for more flexible modelsthat can account for the compositional sensitivity of fuelproperties. Such work is currently underway.

4. CONCLUSIONSIn this work, viscosity measurements for nine aviation turbinefuel samples, representing both conventional and alternativefuels, have been presented. A tenth, petroleum-derived samplehas also been included for comparison. All measurements weremade at ambient pressure (∼83 kPa) and over the temperaturerange of 293−373 K. Significant variability was observed amongthe ten samples; the overall spread in viscosity ranged from38.7% at 293 K to 28.3% at 373 K. Three of the fourpetroleum-based samples exhibited the highest viscosities, whileCSK and GTL exhibited the lowest. No decisive correspond-ence between sample composition and observed viscositytrends could be found, highlighting the difficulties indefinitively linking composition and properties when dealingwith highly complex fluid mixtures. The situation is likely

Figure 6. Ambient pressure kinematic viscosity measurements for JetA and S8 fuel samples plotted as a function of temperature.Measurement results for SRM 1617b, a conventional keroseneproduct, are included for comparison. Additionally, predictions fromthe surrogate mixture models16,19 for Jet A 3638 (dotted line), Jet A4658 (solid line), and S8 (dashed−dotted line), as well as Jet Aviscosity values from the Handbook of Aviation Fuel Properties9 (dashedline), are included for comparison.

Figure 7. Percent deviations of ambient pressure kinematic viscositymeasurements from Jet A and S8 surrogate mixture models16,19 plottedas a function of temperature. Jet A 3638 and S8 measurements arecompared to their respective models, while Jet A 3602, Jet A 4658, andSRM 1617b are compared to the Jet A 4658 model. Jet A viscosityvalues from the Handbook of Aviation Fuel Properties9 were comparedto the Jet A 4658 model and are included for comparison.

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5504

further complicated by additional contributing factors thatcannot be accounted for utilizing the compositional character-ization discussed herein. For example, a fuel sample’s history(e.g., its exposure to air and heat), as well as the presence ofeven small quantities of oligomers or gums, may affect a fuel’sviscosity. Finally, results for the four petroleum-based samplesand one S-IPK sample were compared to three correspondingsurrogate mixture models,16,19 one for Jet A 4658, representinga typical Jet A sample, one for Jet A 3638, and one for S8. Thecalculated deviations were within the reported modeluncertainties, but the observed discrepancies indicate thedevelopment of a more general, tunable model is warranted.

■ ASSOCIATED CONTENT*S Supporting InformationThe Supporting Information is available free of charge on theACS Publications website at DOI: 10.1021/acs.energy-fuels.5b00423.

Details regarding instrument calibration, the cleaningprotocol, and uncertainty calculations (PDF)

■ AUTHOR INFORMATIONCorresponding Author*Phone: 1-303-497-3522. Fax: 1-303-497-6682. E-mail:tfortin@boulder.nist.gov.NotesThe authors declare no competing financial interest.

■ ACKNOWLEDGMENTSWe thank Dr. John Molloy of NIST Gaithersburg for thesample of SRM 1617b and Dr. Tara Lovestead and Dr. TomBruno of NIST Boulder for performing the chemical analysis ofSRM 1617b. Dr. Benjamin Harvey of the Naval Air WarfareCenter in China Lake is acknowledged for useful commentsthat helped improve the manuscript.

■ REFERENCES(1) World Air Transport Statistics, 57th ed.; International AirTransport Association (IATA): Montreal, Canada, 2013.(2) ICAO Environmental Report 2010: Aviation and Climate Change;International Civil Aviation Organization (ICAO): Montreal, Canada,2010; http://www.icao.int/environmental-protection/Pages/EnvReport10.aspx.(3) A Global Approach to Reducing Aviation Emissions; InternationalAir Transport Association (IATA): Geneva, Switzerland, 2009.(4) Group on International Aviation and Climate Change (GIACC)Report; International Civil Aviation Organization (ICAO): Montreal,Canada, 2009; http://www.icao.int/environmental-protection/GIACC/GiaccReport_Final_en.pdf.(5) Destination 2025; Federal Aviation Administration (FAA):Washington, DC, USA, 2011; http://www.faa.gov/about/plans_reports/media/Destination2025.pdf.(6) IATA 2013 Report on Alternative Fuels; International AirTransport Association (IATA): Montreal, Canada, 2013; http://www.iata.org/publications/Documents/2013-report-alternative-fuels.pdf.(7) Daggett, D. L.; Hendricks, R. C.; Walther, R.; Corporan, E.Alternative Fuels for Use in Commercial Aircraft, NASA/TM-2008-214833; NASA Center for Aerospace Information: Hanover, MD,USA, 2008; http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20080018472.pdf.(8) Lewis, K.; Mitra, S.; Xu, S.; Tripp, L.; Lau, M.; Epstein, A.;Fleming, G.; Roof, C. Alternative Jet Fuel Scenario Analysis Report,DOT-VNTSC-FAA-12-01; John A. Volpe National Transportation

Systems Center: Cambridge, MA, USA, 2012; http://ntl.bts.gov/lib/46000/46500/46597/DOT-VNTSC-FAA-12-01.pdf.(9) Handbook of Aviation Fuel Properties, CRC Report No. 635;Coordinating Research Council (CRC): Alpharetta, GA, USA, 2004.(10) World Jet Fuel Specifications with Avgas Supplement; ExxonMobilAviation: Leatherhead, U.K., 2005; http://www.exxonmobil.com/AviationGlobal/Files/WorldJetFuelSpecifications2005.pdf.(11) Winchester, N.; McConnachie, D.; Wollersheim, C.; Waitz, I.Market Cost of Renewable Jet Fuel Adoption in the United States: APARTNER Project 31 Report, PARTNER-COE-2013-001; ThePartnership for Air Transportation Noise and Emissions Reduction(PARTNER): Cambridge, MA, USA, 2013; http://web.mit.edu/aeroastro/partner/reports/proj31/proj31-jetfuel-market-costs.pdf.(12) Standard Specification for Aviation Turbine Fuel ContainingSynthesized Hydrocarbons. Book of Standards, ASTM StandardD7566-13; American Society for Testing and Materials: WestConshohocken, PA, USA, 2013.(13) Standard Test Method for Kinematic Viscosity of Transparentand Opaque Liquids (and Calculation of Dynamic Viscosity). Book ofStandards, ASTM Standard D445-12; American Society for Testingand Materials: West Conshohocken, PA, USA, 2012.(14) Bruno, T. J.; Smith, B. L. Improvements in the Measurement ofDistillation Curves. 2. Application to Aerospace/Aviation Fuels RP-1and S-8. Ind. Eng. Chem. Res. 2006, 45, 4381−4388.(15) Smith, B. L.; Bruno, T. J. Improvements in the Measurement ofDistillation Curves. 4. Application to the Aviation Turbine Fuel Jet-A.Ind. Eng. Chem. Res. 2007, 46, 310−320.(16) Huber, M. L.; Smith, B. L.; Ott, L. S.; Bruno, T. J. SurrogateMixture Model for the Thermophysical Properties of SyntheticAviation Fuel S-8: Explicit Application of the Advanced DistillationCurve. Energy Fuels 2008, 22, 1104−1114.(17) Widegren, J. A.; Bruno, T. J. Thermal Decomposition Kineticsof the Aviation Turbine Fuel Jet A. Ind. Eng. Chem. Res. 2008, 47,4342−4348.(18) Outcalt, S. L.; Laesecke, A.; Freund, M. B. Density and Speed ofSound Measurements of Jet A and S-8 Aviation Turbine Fuels. EnergyFuels 2009, 23, 1626−1633.(19) Huber, M. L.; Lemmon, E. W.; Bruno, T. J. Surrogate MixtureModels for the Thermophysical Properties of Aviation Fuel Jet-A.Energy Fuels 2010, 24, 3565−3571.(20) Bruno, T. J.; Baibourine, E.; Lovestead, T. M. Comparison ofSynthetic Isoparaffinic Kerosene Turbine Fuels with the Composition-Explicit Distillation Curve Method. Energy Fuels 2010, 24, 3049−3059.(21) Bruno, T. J.; Baibourine, E. Comparison of Biomass-DerivedTurbine Fuels with the Composition-Explicit Distillation CurveMethod. Energy Fuels 2011, 25, 1847−1858.(22) Outcalt, S. L.; Fortin, T. J. Density and Speed of SoundMeasurements of Two Synthetic Aviation Turbine Fuels. J. Chem. Eng.Data 2011, 56, 3201−3207.(23) Burger, J. L.; Bruno, T. J. Application of the AdvancedDistillation Curve Method to the Variability of Jet Fuels. Energy Fuels2012, 26, 3661−3671.(24) Outcalt, S. L.; Fortin, T. J. Density and Speed of SoundMeasurements of Four Bioderived Aviation Fuels. J. Chem. Eng. Data2012, 57, 2869−2877.(25) Standard Specification for Aviation Turbine Fuels. Book ofStandards, ASTM Standard D1655-13; American Society for Testingand Materials: West Conshohocken, PA, USA, 2013.(26) Fischer, F.; Tropsch, H. The Synthesis of Petroleum atAtmospheric Pressures from Gasification Products of Coal. Brennst.-Chem. 1926, 7, 97−104.(27) James, O. O.; Chowdhury, B.; Mesubi, M. A.; Maity, S.Reflections on the Chemistry of the Fischer−Tropsch Synthesis. RSCAdv. 2012, 2, 7347−7366.(28) Jahangiri, H.; Bennett, J.; Mahjoubi, P.; Wilson, K.; Gu, S. AReview of Advanced Catalyst Development for Fischer−TropschSynthesis of Hydrocarbons from Biomass Derived Syn-Gas. Catal. Sci.Technol. 2014, 4, 2210−2229.

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5505

(29) Zhang, Q. H.; Cheng, K.; Kang, J. C.; Deng, W. P.; Wang, Y.Fischer−Tropsch Catalysts for the Production of Hydrocarbon Fuelswith High Selectivity. ChemSusChem 2014, 7, 1251−1264.(30) Emerging Fuels Technology. The Fischer−Tropsch Archive,http://www.fischer-tropsch.org (accessed Jan. 29, 2015).(31) Moses, C. A. Comparative Evaluation of Semi-Synthetic Jet Fuels:Final Report, CRC Project No. AV-2-04a; Coordinating ResearchCouncil (CRC): Alpharetta, GA, USA, 2008; http://www.crcao.com/r e p o r t s / r e c e n t s t u d i e s 2 0 0 8 /AV - 2 - 0 4 a /AV - 2 - 0 4 a%20 -%20Comparison%20of%20SSJF%20-%20CRC%20Final.pdf.(32) Kirby, J.; Keasling, J. D. Biosynthesis of Plant Isoprenoids:Perspectives for Microbial Engineering. Annu. Rev. Plant Biol. 2009, 60,335−355.(33) Ciubota-Rosie, C.; Ruiz, J. R.; Ramos, M. J.; Perez, A. Biodieselfrom Camelina sativa: A Comprehensive Characterisation. Fuel 2013,105, 572−577.(34) Scholz, V.; da Silva, J. N. Prospects and Risks of the Use ofCastor Oil as a Fuel. Biomass Bioenergy 2008, 32, 95−100.(35) Roseberg, R. J.; Bentley, R. A. Growth, Seed Yield, and OilProduction of Spring Camelina sativa in Response to Irrigation Rate andHarvest Method, in the Klamath Basin, 2011; Oregon State UniversityKlamath Basin Research & Extension Center (KBREC): Corvallis,OR, USA, 2011; http://oregonstate.edu/dept/kbrec/sites/default/files/growth_seed_yield_and_oil_production_of_spring_camelina_sativa_in_response_to_irrigation_rate_and_harvest_method_in_the_klamath_basin_2011.pdf.(36) Shonnard, D. R.; Williams, L.; Kalnes, T. N. Camelina-DerivedJet Fuel and Diesel: Sustainable Advanced Biofuels. Environ. Prog.Sustainable Energy 2010, 29, 382−392.(37) Japan Airlines. JAL Biofuel Demo Flight First to Use Energy CropCamelina, 2008, http://press.jal.co.jp/en/release/200812/001076.html (accessed Sep. 19, 2013).(38) The Green Optimist. Camelina: The Plant That Powerd KLM’sFirst Biofuel Plane, 2009, http://www.greenoptimistic.com/camelina-the-plant-that-powered-kmls-first-biofuel-plane-20091202/ (accessedSep. 19, 2013).(39) U.S. Air Force. Thunderbirds to Perform First Demo withAlternative Fuel, 2011, http://www.af.mil/News/ArticleDisplay/tabid/223/Article/113296/thunderbirds-to-perform-first-demo-with-alternative-fuel.aspx (accessed Sep. 1, 2015).(40) Wise, S. A.; Watters, R. L. Certificate of Analysis - StandardReference Material 1617a, Sulfur in Kerosine (High Level); NationalInstitute of Standards and Technology: Gaithersburg, MD, USA, 2009;https://www-s.nist.gov/srmors/view_detail.cfm?srm=1617A.(41) Lovestead, T. M. Analysis of Standard Reference Material 1617b,Sulfur in Kerosine. Report of Analysis; National Institute of Standardsand Technology: Boulder, CO, USA, 2013.(42) Standard Test Method for Hydrocarbon Types in Low OlefinicGasoline by Mass Spectrometry. Book of Standards, ASTM StandardD2789-04b; American Society for Testing and Materials: WestConshohocken, PA, USA, 2005.(43) Smith, B. L.; Bruno, T. J. Improvements in the Measurement ofDistillation Curves. 3. Application to Gasoline and Gasoline +Methanol Mixtures. Ind. Eng. Chem. Res. 2007, 46, 297−309.(44) Bruno, T. J.; Laesecke, A.; Outcalt, S. L.; Seelig, H. D.; Smith, B.L. Properties of a 50/50 Mixture of Jet-A + S-8, NISTIR 6647; NationalInstitute of Standards and Technology: Boulder, CO, USA, 2007.(45) Leckel, D. Diesel Production from Fischer−Tropsch: The Past,the Present, and New Concepts. Energy Fuels 2009, 23, 2342−2358.(46) Outcalt, S. L.; Laesecke, A.; Brumback, K. J. ThermophysicalProperties Measurements of Rocket Propellants RP-1 and RP-2. J.Propul. Power 2009, 25, 1032−1040.(47) Laesecke, A.; Fortin, T. J.; Splett, J. D. Density, Speed of Sound,and Viscosity Measurements of Reference Materials for Biofuels.Energy Fuels 2012, 26, 1844−1861.(48) Laesecke, A.; Fortin, T. J. Potential for Sample Cross-Contamination in the miniAV Capillary Viscometer: Application Note;National Institute of Standards and Technology: Boulder, CO, USA,2011 (available from authors by request).

(49) Guide to the Expression of Uncertainty in Measurement;International Organization for Standardization (ISO): Geneva,Switzerland, 1995.(50) Outcalt, S. L.; Laesecke, A. Compressed-Liquid Densities ofTwo Highly Polar + Non-Polar Binary Systems. J. Mol. Liq. 2012, 173,91−102.(51) Edwards, T. United States Air Force, Air Force ResearchLaboratory, Propulsion Directorate, Wright Patterson Air Force Base,OH. Personal communication to Bruno, T. J., 2006.(52) Bessee, G. B.; Hutzler, S. A.; Wilson, G. R. Analysis of SyntheticAviation Fuels: Interim Report, AFRL-RZ-WP-TR-2011-2084; Air ForceResearch Laboratory, Propulsion Directorate: Wright-Patterson AirForce Base, OH, USA, 2011.(53) Corporan, E.; Edwards, T.; Shafer, L.; DeWitt, M. J.; Klingshirn,C.; Zabarnick, S.; West, Z.; Striebich, R.; Graham, J.; Klein, J.Chemical, Thermal Stability, Seal Swell, and Emissions Studies ofAlternative Jet Fuels. Energy Fuels 2011, 25, 955−966.(54) Lemmon, E. W.; Huber, M. L.; McLinden, M. O. NIST StandardReference Database 23: Reference Fluid Thermodynamic and TransportProperties (REFPROP), 9.1; National Institute of Standards andTechnology: Gaithersburg, MD, USA, 2010; http://www.nist.gov/srd/nist23.cfm.

Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.5b00423Energy Fuels 2015, 29, 5495−5506

5506