ims ms and ims ims investigation of the structure and ......2014/12/18 · a mass spectrometer is...

IMS−MS and IMS−IMS Investigation of the Structure and Stability ofDimethylamine-Sulfuric Acid NanoclustersHui Ouyang, Siqin He, Carlos Larriba-Andaluz, and Christopher J. Hogan, Jr.*

Department of Mechanical Engineering, University of Minnesota, Minneapolis, Minnesota United States

*S Supporting Information

ABSTRACT: Recent studies of new particle formation events in the atmospheresuggest that nanoclusters (i.e, the species formed during the early stages of particlegrowth which are composed of 101−103 molecules) may consist of amines and sulfuricacid. The physicochemical properties of sub-10 nm amine-sulfuric acid clusters arehence of interest. In this work, we measure the density, thermostability, and extent ofwater uptake of

properties as well as from the properties of larger nano- tosubmicrometer particles, with such deviations not necessarilypredictable from classically derived theories (though suchtheories are used almost universally in modeling nanoclustergrowth13). For example, the capillarity model (i.e., the Kelvineffect)15,16 leads to the prediction that nanoclusters are muchless thermostable than larger species of the same chemicalcomposition and have substantially higher vapor pressures thantheir bulk counterparts. While qualitatively this is true, thecapillarity model is based upon a bulk definition of surfacetension; simulations17 show that for pure phase nanoclusterswhose radii are ≤7 van der Waals radii, quantitatively thecapillarity model leads to extremely inaccurate vapor pressurepredictions. Additional deviations from the capillarity model areto be expected for the vapor pressures of multicomponentnanoclusters, such as DMAS. Furthermore, size dependencies/deviations from bulk behavior are also expected and have beenobserved for the density18 and extent of water uptake ofnanoclusters.19−21

DMAS nanoclusters and larger nanoparticles have beenstudied experimentally and theoretically by several differentapproaches. An overview of the properties of amines andstudies of atmospheric amine chemistry was recently providedby Qiu and Zhang.22 Specifically for DMAS particles, Qiu andZhang also measured the thermostability, density, and extent ofwater vapor uptake for particles in the 80 to 240 nm size(diameter) range.7 Ab initio calculations have been performedby several research groups to study the formation of neutral orcharged DMAS clusters with or without water mole-cules.9,12,23−26 However, experimental measurements in thenanocluster size range are lacking (beyond measurements ofclusters composed of ≤10 sulfuric acids, above a size of ∼1.1nm in diameter). In this study, we thus focus on measurementsof the properties of DMAS nanoclusters in the size (effectivediameter) range of 2−8.5 nm, produced in a laboratory settingvia electrospray ionization (ESI). Of specific interest are thedensity, thermostability, and extent of water uptake by suchnanoclusters, properties which are amenable to laboratoryinvestigation. Three unique measurement systems are em-ployed for measurements of these properties, which aredescribed in detail in the subsequent sections: for densitymeasurement ion mobility spectrometry−mass spectrometrywith a high-resolution differential mobility analyzer coupled toa mass spectrometer is applied;18,27−29 for thermostability atandem differential mobility analyzer system30,31 using modest-to-high resolution differential mobility analyzers32 is utilized;and for heterogeneous water uptake experiments, a differentialmobility analyzer-drift tube mobility analysis system isapplied.21,33 The overarching goal of this work is to betterunderstand what the properties of DMAS nanoclusters wouldbe under atmospherically relevant conditions.

■ EXPERIMENTAL METHODSMaterials. As a source of gas phase DMAS nanoclusters, we

used ESI of methanol based solutions, which, upon methanolevaporation, yielded nanoclusters. Solutions were prepared byadding sulfuric acid (99.999%) and dimethylamine (40 wt % inH2O) to HPLC-grade methanol. All chemicals were purchasedfrom Sigma-Aldrich (Saint Louis, MO). Variable molarconcentrations of sulfuric acid and dimethylamine were used,which are denoted as [H2SO4] and [(CH3)2NH] respectively.Seven molar concentration ratios, R = [H2SO4]/[(CH3)2NH]were employed, specifically, R = 10, 5, 4, 3, 2, 1, and 0.5. These

solutions were used for nanocluster generation with all threeemployed measurement systems.For ESI, a 40 μm i.d. silica capillary (360 μm o.d., Polymicro

Technologies, Phoenix, AZ) was used, as was used previously incluster ion generation experiments.18,27 An applied pressurewas used to drive the solution through the capillary, while apositive voltage was applied directly to the solution to run theelectrospray in a cone-jet mode,34 which was observed to bestable visually with a magnifying lens. DMAS nanoclusters witheither single or multiple excess positive charges were formed viaESI; for IMS−MS measurement, the ESI voltage was floatedover the outer electrode of the parallel-plate differentialmobility analyzer employed, and no charge reduction schemewas employed prior to measurements. Conversely, for tandemdifferential mobility analyzer experiments and differentialmobility-analyzer-drift tube experiments a 0.5 mCi Po-210source was used to reduce the charge level of nanoclusters; aftercharge reduction most nanoclusters were neutral and those thatwere observed were singly charged.35,36

Differential Mobility Analysis−Mass Spectrometry.Differential mobility analysis-mass spectrometry,29 a form ofion mobility spectrometry−mass spectrometry (IMS−MS)37,38was used for measurement of the collision cross sections ofmass-identified nanoclusters in air. From these measurements,nanocluster densities can be inferred.39,40 The parallel platedifferential mobility analyzer (model p5 SEADM, Boecillio,Spain, with a resolving power in mobility near 60) and QSTARXL time-of-flight mass spectrometer (Applied Biosystems,Framingham, MA) combination has been described in detailpreviously18,27,29 and was operated in a similar manner to theseprior works. Briefly, to specify the mobilities of the nanoclusterswhich can traverse the differential mobility analyzer, a potentialdifference was generated between the two electrodes byapplying a voltage on the outer electrode. Singly and multiplycharged nanoclusters were drawn into the classification regionelectrostatically, with the inlet operated in counterflow mode(∼0.1 L min−1 of counterflow). High purity air (Air Gas, UltraZeroG1 ppm, St. Paul, MN) was used as the sheath flow gas,and the sheath flow was operated in recirculating mode using avacuum blower (Domel Inc., Železniki, Slovenia) with thesheath gas temperature in the measurement zone near 303 Kand close to atmospheric pressure. ∼0.2 L min−1 was drawninto the mass spectrometer inlet (at the outlet of theclassification region of the mobility analyzer), to continuouslysupply air for the outlet and for the counterflow a mass flowcontroller (MKS instruments, Andover, MA) was set at 0.3 Lmin−1.To collect combined mass-mobility spectra, a potential

difference of 1000−4000 V was applied in steps of 10 V, andmass spectra were collected at each voltage for an accumulationtime of 2 s. For mass spectra measurements, the quadrupolemass filters were operated in radiofrequency-only mode, andthe time-of-flight section was employed. Between the mobilityanalyzer outlet and the first quadrupole of the massspectrometer, there are several applied declustering andfocusing potential differences; all of these differences were setto minimal values to mitigate the dissociation of nanoclusters inthe mass spectrometer inlet (i.e., to reduce collision induceddissociation). Prior IMS−MS measurements where the IMSwas operated at atmospheric pressure have revealed that in theinlets (where ions/nanoclusters are exposed to high pressuredrop as well as strong electric fields) of mass spectrometers

The Journal of Physical Chemistry A Article

DOI: 10.1021/jp512645gJ. Phys. Chem. A 2015, 119, 2026−2036

2027

http://dx.doi.org/10.1021/jp512645g

with atmospheric pressure ionization, collision-induced dis-sociation of nanoclusters is commonplace.18,28,41,42

As in prior studies using high sheath flow rate (in excess of100 L min−1) parallel-plate differential mobility analyzers, wedid not measure the sheath flow rate directly. Instead, asdifferential mobility analyzers are linear spectrometers (i.e., theapplied voltage is linearly proportional to the inverse mobilityof the selected ions/nanoclusters), we employed a single-pointcalibration technique. Prior to all experiments, we measured theelectrical mobility of the tetraheptylammonium+ (THA+) ion,produced via ESI of a tetraheptylammonium bromide-methanolsolution. The mobility of this ion (ZTHA), measured by Ude andFernańdez de la Mora43 at 293 K was used to determinemobility of observed nanoclusters (Znc) through the relation-ship: Znc = (VTHA/Vnc) × ZTHA, where VTHA is the appliedvoltage at which the THA+ ion was maximally transmitted, andVnc is the voltage at which the nanocluster in question wasmaximally transmitted. Neglecting the influence of the ion-induced dipole potential, for calibration, ZTHA was adjustedfrom Ude and Fernandez de la Mora’s measured value becauseof the difference in temperatures used in measurement here andin their work (303 K vs 293 K, leading to a 1.6% shift in themobility).IMS−IMS Investigation of Thermostability. Tandem

differential mobility analysis, a form of IMS−IMS,44 has beensuccessfully used in thermostability studies for over twodecades.30,45,46 We applied a similar measurement principlehere, using two differential mobility analyzers of modest-to-highresolving power (typically above 20) for measurements. Thetandem differential mobility analysis system employed isdepicted in Figure 1a. In it, industrial-grade dry nitrogen wasused as a carrier gas, and DMAS nanoclusters were generated asdescribed by an electrospray, with subsequent charge reductionin a Po-210 source. A flow of dry nitrogen was subsequentlymixed with the generated nanocluster flow, with a 3.87 L min−1

of aerosol flow entering the first differential mobility analyzer(labeled as IMS-1 in Figure 1a).Both differential mobility analyzers were cylindrical 1/2 mini

models (Nanoengineering Corp., Boca Raton, FL), the designof which is described by Fernandez de la Mora andKozlowski.32 In both, a negative voltage was applied to theinner electrode where the aerosol exit slit is located, while the

outer electrode is grounded. Positively charged nanoclusterswere hence selected and measured. The sheath flows wereoperated in a recirculating mode with Domel Inc. vacuumblowers, and again, the THA+ ion was used for calibration. Thefirst differential mobility analyzer was operated at a fixed voltageto transmit nanoclusters of a specific mobility (and henceradius, as nearly all charged nanoclusters were singly charged).To evaluate thermostability, a microfurnace (UltraCoil RobustRadiator, Micropyretics Heaters International Inc., Cincinnati,OH) was placed between the two differential mobilityanalyzers, and nanoclusters transmitted through the firstdifferential mobility analyzer were sent through the micro-furnace via a 12 in. long sintered silicon carbide round tube (theevaporation tube) with 1/2 in. o.d. and 3/8 in. i.d. (Ortech Inc.,Sacramento, CA). Nanocluster evaporation occurred in theheated zone of the microfurnace, which was a 1.5 in. diameterand 3.5 in. length cylindrical chamber. Two insulating caps withthe thicknesses of 0.75 in. were used to seal the heatingchamber, and a PID controller was connected to athermocouple embedded in the heated zone. The temperatureprofile was varied in the furnace by adjusting PID controllervalues. Four specific temperatures were set with the PIDcontroller: 200, 300, 350, and 400 °C. However, because theflow within the silicon carbide tube was laminar, and heatingwas nonuniform, an axial temperature profile was developed inthe silicon carbide tube (i.e., the PID controller set temperaturewas not the temperature in the evaporation tube). Temperatureprofiles along the length of the evaporation tube were hencemeasured for all experiments and are displayed in Figure 1b.The temperature increased first and then decreased, with thehighest temperature appearing at an axial location two-thirdsdownstream in the microfurnace (because of convective heattransfer). After the evaporation tube, an alumina sampling tube,which only sampled the center streamlines of the evaporationtube (3 L min−1 sampled), transmitted particles exiting themicrofurnace to the second differential mobility analyzer (IMS-2). The second differential mobility analyzer was operated witha stepping applied voltage in the 0 to 4000 V range, with a steprate of 10 V s−1, in order to determine to what extent theselected nanoclusters evaporated when passing through themicrofurnace. The flow at the second differential mobilityanalyzer outlet was split, with half entering a condensation

Figure 1. (a) A depiction of the tandem differential mobility analyzer system employed in thermostability experiments (IMS: differential mobilityanalyzer; CPC: condensation particle counter; Po-210: bipolar ion source). (b) The temperature profiles measured axially in the microfurnacechamber. The position of the furnace heating chamber and the sampling tube are also depicted.



2028


particle counter (CPC, TSI model 3776, Shoreview, MN) andthe other half entering a custom-made Faraday cage electro-meter. The CPC was used primarily for thermostabilitymeasurements (nanocluster detection), while the electrometerwas used for THA+ detection and, hence, mobility calibration(which was repeated at all PID controller set temperatures).IMS−IMS Investigation of Water Uptake. While tandem

differential mobility analyzers can be used to examine thesorption of vapor molecules to nanoparticles, maintaining highsheath flow rates at constant vapor concentrations (i.e.,constant relative humidities) can be difficult. As an alternative,our group has recently developed a drift tube ion mobilityspectrometer (DT-IMS, described in detail previously33) whichcan be uniquely coupled to a CPC for nanoparticle andnanocluster measurements. When using the DT-IMS in tandemwith a differential mobility analyzer upstream, by controllingthe relative humidity of its counterflow (∼0.2 L min−1), shiftsin nanocluster mobilities brought about by vapor uptake can bedirectly observed. Following the experimental setup describedby Oberreit et al.,21 ESI generated and charge reduced DMASnanoclusters were first passed through a 1/2 mini differentialmobility analyzer, which was again operated at a constantapplied voltage to isolate nanoclusters of a specific mobility.The selected nanoclusters then entered the DT-IMS, which wasoperated with clean air as the counterflow and humidified witha custom flow rate controlled nebulizer-heater system. Therelative humidity in the DT-IMS was calculated from dew pointand temperature measurements with a hygrometer (GeneralEastern Hygro M4, Fairfield, CT) and a K type thermocouple,respectively.Without any applied voltage, all nanoclusters entering the

DT-IMS were immediately swept out of the inlet by thecounterflow. However, upon timed application of a voltage (3kV in this study) at the inlet, a near-linear electric field formsaxially, driving positively charged nanoclusters down the tube ata speed equal to the difference between their electrophoreticvelocities and the counterflow velocity. Therefore, nanoclusterarrival times at the CPC placed downstream of the DT-IMS aresolely a function of nanocluster mobilities. Specifically, theinverse mobility (Znc

−1) of a nanocluster is linked to its arrivaltime (ta) as measured by a CPC via the equation: Znc

−1 = ata + b,where a and b are constants dependent upon the delay time inCPC detection, the counterflow velocity, the applied voltage,and the drift tube geometry. To minimize signal broadening, afast response CPC (WCPC, model 3786, TSI, Shoreview, MN)was employed in all measurements.The differential mobility analyzer-DTIMS system enabled

the investigation of water vapor uptake by nanoclusters viaobservation of uptake facilitated shifts in inverse mobilities,which was directly inferred from shifts in mobility classifiednanocluster arrival time distributions. Again, we used ESIgenerated THA+ to calibrate the 1/2 mini differential mobilityanalyzer, and subsequently, mobility classified particles wereused to determine the values of a and b in DT-IMS calibration.For uptake experiments, five voltages were applied to the 1/2mini differential mobility analyzer (5 nanocluster sizes) andarrival time distributions were measured correspondingly for 10different relative humidity settings in the 3%−52% range.

■ RESULTS AND DISCUSSIONNanocluster Collision Cross Sections and Inferred

Densities. IMS−MS measurements directly lead to mass-mobility spectra, in which measured signal intensity is displayed

as a function of both mass-to-charge ratio (m/z) and inversemobility (1/Znc, which is directly proportional to the appliedvoltage in the differential mobility analyzer). In IMS−MSexperiments, five solutions with different molar ratios, R =[H2SO4]/[(CH3)2NH] were used to generate DMAS nano-clusters, and each gave rise to their own mass-mobility spectra.Such data can be represented via contour plots; a contour plotfor R = 1 is displayed in Figure 2. In it, signal intensity for each

ion is displayed via a logarithmic color scale, with blue denotingthe most intense signal and yellow denoting the faintest signalabove a prescribed threshold. Signal intensities were massaveraged over 0.3 Da. In the displayed contour plot, short linesegments appear; each line segment denotes an ion of a specificm/z and 1/Znc, and the width of the line represents theresolution of the ion mobility spectrometer. As discussed indetail previously, line segments for electrospray generatednanoclusters are grouped into charge-state specificbands.18,27,47−49 Bands for seven charge states (z = 1 to 7)are labeled in the figure. For several of the singly chargednanoclusters, a zoomed-in plot is inserted in Figure 2.Apparent in this plot is that nanoclusters differ in m/z from

one another by either 98 or 143 Da. For doubly chargedspecies, the mass differences observed are half of these values;together these indicate that nanoclusters are composedpredominantly of [(CH3)2NH·H2SO4] and [H2SO4] baseunits. In several instances, nanoclusters of the same m/z ratiobut varying inverse mobility appear. Such line segments areattributable to neutral ion-pair ([(CH3)2NH·H2SO4] or[H2SO4]) evaporation in the inlet of the mass spectrometer(after mobility classification).28 Charge loss in the massspectrometer inlet (in particular for z = 2 nanoclusters)additionally complicates spectra, giving rise to wider linesegments which appear at neither the m/z nor the inversemobility of the parent nanoclusters.27 Fortunately, neutralevaporation and charge loss are minimal for most multiplycharged nanoclusters, hence the m/z and 1/Znc values, as wellas z, are readily determined from measurements for thesenanoclusters. Subsequently, collision cross sections (CCSs, Ω)can be calculated for nanoclusters from mass-mobility data:

Figure 2. A mass-mobility contour plot inferred from IMS−MSmeasurement of multiply charged DMAS nanolcusters, with measuredsignal intensity expressed via color intensity on a logarithmic scale,with blue the most intense and yellow the least intense. Bands of ionsof different charge states are labeled, from z = 1 to 7.



2029


πρ

Ω = ⎜ ⎟⎛⎝

⎞⎠

mkT

zeZ8

34

red0.5

gas nc (1a)

where mred is the reduced mass of the nanocluster−gasmolecule pair (approximated as the gas molecule mass for allnanoclusters, 28.8 Da), k is Boltzmann’s constant, T istemperature, e is the elementary charge, and ρgas is the bathgas mass density. In examining smaller clusters, structuralanalysis via IMS is best accomplished via comparison ofmeasured CCSs to predictions based upon gas moleculescattering calculations;18,39,41,50−52 the asphericity of suchentities, combined with the non-negligible influence of theion-induced dipole potential (for measurements in air) andsome ambiguity in the manner in which gas molecules impingeand are re-emitted from clusters surfaces (i.e., diffuse versusspecular) often prohibits the use of simple relationships to linkthe CCS to physical structure. However, nanoclusters aresufficiently large, such that they can be approximated asspheres.47 For spherical entities in diatomic gases,41 consideringthe free-molecular limit of the Stokes-Millikan equa-tion39,40,50,53 as well as the influence of the polarizationpotential between gas molecule and charged nanocluster,54 thefollowing relationship can be applied to link the CCS to ananocluster’s radius, rnc:

ξ πΩ = × × + ×r r L( )nc gas2

(1b)

where rgas is the effective gas molecule radius (1.5 Å for air near300 K47), ξ is a dimensionless momentum scatteringcoefficient, found to be ≈1.36 in many instances and takento be so here (though exception have been observed18), and Lis a dimensionless polarization correction factor (a correctionfactor of the ion induced-dipole potential), the calculation ofwhich is described in detail by Larriba-Andaluz and Hogan:39

ϕξ

ϕ ϕ= + + + ≤⎜ ⎟⎡⎣⎢

⎛⎝⎜

⎛⎝

⎞⎠⎞⎠⎟⎤⎦⎥L 1

13.1

1 116

433

if 1e e e(1c)

ϕ ϕξ

ϕ ϕ= + − + −

>

⎜ ⎟⎡⎣⎢

⎛⎝⎜

⎛⎝

⎞⎠⎞⎠⎟⎤⎦⎥L 1

14

2.31000

1 956

6.81000

if

1

e e e e

(1d)

where ϕe = Upol/kT (potential energy to thermal energy ratio),and Upol = −αz2e2/[8πϵϵ0(rnc + rgas)4], with ε0 the permittivityof free space, ε the dielectric constant of the background gas,and α the polarizability of the background gas molecules (∼1.7Å3 in air).For each nanocluster measured, we infer rnc with eqs (1−4).

Additionally, in Figure 3, the masses of all multiply chargednanoclusters are plotted as functions of Ω3/2; for these clusters,polarization influences (though considered in rnc inference) aresmall, and additionally rnc is considerably larger than rgas.Therefore, Ω3/2 scales approximately with nanocluster volume,and the observed linear relationship between nanocluster massand Ω3/2 suggests that the measured nanoclusters are of aconstant density, which is found relatively independent of thesulfuric acid to dimethylamine concentration ratio R in ESIsolutions. As discussed in prior studies,47 high-resolution ionmobility spectrometry of mass-identified ions enables densityinference to within several percent; however, density inferencealone does enable quantification of nanocluster internalstructure or surface structure changes which may be broughtabout by changing R ratios. Via linear regression with all data in

Figure 3, we infer a density, ρDMAS = mnc/(4/3πrnc3 ), of 1567 kg

m−3. Although this value is slightly higher than the 97 nmdiameter particle DMAS density reported by Qiu and Zhang7

(1408 kg m−3), it is bounded by bulk densities of dimethyl-amine (670 kg m−3) and sulfuric acid (1840 kg m−3) andfurther increases in density for nanoclusters (due to capillarityeffects, provided charged clusters are not Coulombicallystretched)47 are expected.

Nanocluster Thermostability. For tandem differentialmobility analysis experiments, we additionally use eq 1b to infernanocluster radii, rnc for the nanoclusters transmitted by boththe first and second differential mobility analyzers, respectively.For all results, L = 1 was assumed, as for the singly chargednanoclusters examined in these experiments, polarizationinfluences are negligible. Measurements result in plots ofmeasured signal intensity (CPC signal) as a function of rnc foreach selected rnc,0 by the first differential mobility analyzer andeach set temperature profile in the furnace. Such plots aredisplayed in Figure 4 for rnc,0 = 3.00, 3.30, 3.66, and 3.95 nmwith 4 different PID settings. Evidenced in this figure, in allinstances, as the PID set temperature was increased, (1) theabsolute detected signal decreased, (2) distributions becamenoticeably broader and asymmetric, and (3) peaks indistributions shifted to smaller inferred radii. The firstobservation is attributable to thermophoretic deposition inthe furnace, while the second and third are attributable toevaporation (monomer dissociation) of nanoclusters at elevatedtemperatures, with broadening presumably arising because ofvariations in the temperature−time history by transmittednanoclusters (spatial effects). Although attempts were made tominimize such broadening and spatial influences on theevaporation process by sampling along the evaporation tubecenterline only, such effects are difficult to completelymitigate31 in a system for sub 10 nm charged entities.While we nonetheless proceed to infer surface vapor

pressures for nanoclusters (Pnc) from these measurements, wecaution that the absolute values obtained have not beencorrected considering a detailed analysis of the temperatureprofile in the evaporation tube and the nanocluster trajectories(i.e., an averaging approaching is taken), and further, theanalysis approach itself utilizes several approximations.

Figure 3. Measured mass of nanoclusters as a function of theircollision cross sections to the 3/2 power, which is approximatelyproportional to nanocluster volume. Different symbols representdifferent molar concentration ratios of initial solution used in ESIsolutions.



2030


However, we will only focus on estimating the surface vaporpressures to within an order of magnitude, which suchapproximations should not mitigate.To analyze tandem differential mobility analyzer data, we

determine the peak rnc values for each measured distributionand assume that all of these nanoclusters were transmittedthrough the evaporation tube with near identical residencetimes (t). The number of vapor molecules evaporating from thesurface of a single nanocluster per unit time (the evaporationrate, dN/dt, in units of molecules per second) is given by theequation:

β= −Nt

ndd v ,nc (2a)

where nv,nc is the vapor molecule number concentration on thesurface of a nanocluster, and β is the collision kernel/collisionrate coefficient, which for nanoclusters in the ballistic regimecan be approximated as (8kT/πmv)

1/2×πrnc2 , where (8kT/

πmv)1/2 is the mean thermal speed of the evaporating vapor

molecules, and mv is the mass of vapor (assumed to be 98 Da,the mass of sulfuric acid, for reasons elaborated upon later on).The surface concentration of vapor molecules, in turn, can be

converted to a nanocluster surface vapor pressure via therelationship nv = Pnc/kT. With the number of vapor moleculesin a nanocluster given by ρVnc/mv, where Vnc is the nanoclustervolume [assuming they are spheres Vnc = (4/3)πrnc

3 ] and ρ thedensity (measured in IMS−MS experiments), it then followsthat dN/dt = (ρ/mv)(dVnc/dt). This relationship coupled withthe assumption that the density and vapor molecule mass arenanocluster size invariant leads to

ππ

ρ= − · · ·

V tt

kT tm

rP T r

kT tmd ( )

d8 ( ) ( , )

( )vvnc

nc2 nc nc

(2b)

In eq 2b, the nanocluster volume and the temperature aredenoted as functions of time, while the nanocluster vaporpressure is denoted as a function of temperature and thenanocluser radius. Measurements provide the initial and finalnanocluster volume, respectively, and the temperature−timerelationship for the centerline of the evaporation tube wasmeasured as discussed previously (at 16 discrete axialdistances). These two pieces of information, combined witheq 2b, enable inference of Pnc(T,rnc). Isolating dVnc on the left-hand side of eq 2b and integrating over the residence time t inthe furnace leads to

∫

π

ρπ

− = Δ

≈ · ·

r r V

r mk

P T r

T tt

43

( )

8 ( , )

( )d

f

vt

nc,03

nc,3

nc,02

0

nc nc,0

(2c)

where rnc,f is the final peak radius of the transmittednanoclusters and ΔV is the volume change due to evaporation.In integrating 2b, for simplicity, we assume that rnc

2 ≈ rnc,02 (i.e.,the projected area of an evaporating nanocluster did not changesubstantially during experiments). In addition, vapor pressuresinferred are assumed to apply for clusters of radius rnc,0.To subsequently determine Pnc(T), for each rnc,0 we used the

fitting function:

= − − −⎛⎝⎜

⎞⎠⎟P T A

BT

CT

DT

( ) expnc2

2 2

1.5

2

0.5(2d)

Figure 4. Nanocluster number concentrations, as measured by a CPC, measured as a function of rnc based on the second differential mobilityanalyzer settings in tandem differential mobility experiments for different temperatures (distinguished by PID setting) and for four initial radii.



2031


where A, B, C, and D are fitting coefficients, the temperature Tis in Kelvin, and the resulting pressure is in Pascals. Thisfunction is similar in construction to the Antoine equation55 orRiedel equation,56 though it is simply used because of itsflexibility in fitting our results and is not derived fromthermodynamic relationships (i.e., the third and fourth termsare ad-hoc corrections, introduced only to provide flexibility infitting results). With substitution of eq 2d into eq 2c, combinedwith the trapezoidal rule for integration, eq 2c can berearranged to give:

∑ρπ

π

δ

Δ · · ≈− − −

+− − −

·

=

+

+ + +

⎧⎨⎪⎪

⎩⎪⎪

⎛

⎝

⎜⎜⎜⎜

⎛⎝⎜

⎞⎠⎟

⎛⎝⎜

⎞⎠⎟

⎞

⎠

⎟⎟⎟⎟

⎫⎬⎪⎪

⎭⎪⎪

Vr

km

A

T

A

Tt

8

exp

exp/2

inc v j

BT

CT

DT

j i

BT

CT

DT

j i

,02

1

152

,0.5

2

1,0.5

j i j i j i

j i j i j i

2

,

2

,1.5

2

,0.5

2

1,

2

1,1.5

2

1,0.5

(2e)

where i = 1, 2, 3, and 4 denotes the four PID set values (200,300, 350, and 400 °C, respectively), Tj,i denotes thetemperature measured at location j for PID setting i, and δt= t/15. To find the “best-fit” values of A, B, C, and D, for whichthe left-hand side and right-hand side of eq 2e areapproximately equal for all PID settings, we use the solveradd-in of Microsoft Excel (version 2010). A global error isdefined as eG = ∑i=14 [1 − (ai/bi)]2, where ai and bi are left-handand right-hand sides of eq 2e, respectively. Local errors werealso similarly calculated as ei = |1 − (ai/bi)|. Using initial guessesof A = 1, B = 10, C = 100, and D = 10, under all circumstances,the solver minimizes eG while keeping all ei less than 15% as aconstraint, with the exception of the PID setting of 200 °C, forwhich no constraint is placed. Different initial guess values ledto a negligible change in the resulting Pnc values, and this fittingprocedure is applied for six separate initial sizes, and sevenvalues of R, hence 42 separate coefficient sets.

Table S1 of the Supporting Information contains lists ofinferred values A, B, C, and D for all measured rnc,0 and Rvalues. Upon the basis of these values, in Figure 5a we plot thevalues of Pnc extrapolated to 300 K as a function of R, and inFigure 5b we plot Pnc [quantified by log10(Pnc)] as a function ofinverse temperature. Nanocluster vapor pressures near 300 Kare on the order of 10−4−10−3 Pa for nearly all circumstances.These values are substantially higher (by multiple orders ofmagnitude) than ammonium sulfate surface vapor pressuresinferred by Marti et al.,57 for larger nanoparticles (50−300 nmdiameters) under dry conditions and even larger than surfacevapor pressure of larger DMAS particles inferred by Lavi etal.,58 who found that DMAS particles have lower vaporpressures than ammonium sulfate submicrometer particles.However, our surface vapor pressure extrapolations are only anorder of magnitude larger than the vapor pressure of 50−300nm sulfuric acid−water nanoparticles (76% sulfuric acid bymass) estimated by Marti et al. (of order 10−5 Pa). Atatmospheric pressure, our extrapolated vapor pressurescorrespond to nanocluster surface vapor concentrations in theppbv (parts per billion by volume) range. Ambient sulfuric acidconcentrations are typically in the pptv (parts per trillion byvolume range),3,59 and dimethylamine concentrations areexpected to be in a similar, subppbv range.59 Despite theapproximations employed in analysis as well as the extrap-olation used to 300 K, our error in vapor pressure estimation ispresumably not several orders of magnitude, and ourmeasurements strongly suggest the surface vapor pressures ofdry DMAS nanoclusters are higher than ambient vaporpressures for their constituents. We also note the vaporpressures inferred are sensitive to the choice of mv but not to anextent which alters the order of Pnc values. Such high-surfacevapor pressures suggest that it is excess sulfuric acid evaporatingfrom dry clusters, and likely arise because of a Kelvin model-likebehavior for nanoclusters; the Kelvin effect53 predicts that thevapor pressure at the surface of a nanocluster will increase overthe bulk value by a factor of p(2γmv/ρkTrnc), where γ is theeffective surface energy density of the nanocluster (i.e., thesurface tension, expected to high for ionically bonded systems).High surface energy densities can thus lead surface vapor

Figure 5. (a) Extrapolated surface vapor pressures, Pnc, as a function of R = [H2SO4]/[(CH3)2NH]. (b) log10(Pnc) inferred from experiments, basedon fitting eq 2d to experimental results, as a function of 1/T. Different symbols represent different initial particle radii: ◆ (2.68 nm), ▲ (3.05 nm),● (3.38 nm), ■ (3.68 nm), ▼ (3.97 nm) and × (4.23 nm).



2032


pressures enhanced by several orders of magnitude over bulkvalues (hence our measurements are in-line with the vaporpressure estimations of Marti et al.57 for larger, nearly drysulfuric acid particles), creating a barrier to dry nanoclustergrowth. The observation of high surface vapor pressures fornanoclusters is further supported by attempts to analyze R = 0(pure dimethylamine) and R = ∞ (pure sulfuric acid)nanoclusters; in these circumstances, nanoclusters evaporatealmost completely at room temperature prior to transmissionthrough ion mobility spectrometers, such that we could notdetect clusters from pure dimethylamine or pure sulfuric acidsolutions. Interestingly, a clear nanocluster size dependency ofthe vapor pressure (increasing vapor pressure with decreasingsize) is not observed in the nanocluster size range examined, in

fact at large R values an increase in Pnc with increasing radius isobserved. This is likely because of compounding influences ofsize-dependent chemical composition (from the nanoclusterformation process in these experiments) and direct sizeinfluences on the surface vapor pressure and because the sizerange examined itself was relatively narrow. An increase in Pnc isadditionally observed with increasing R, and hence increasingsulfuric acid content was further evidence that sulfuric acid isthe major evaporating species from DMAS nanoclusters.

Nanocluster Water Vapor Uptake. While our thermo-stability measurements suggest that dry DMAS nanoclusters(rnc = 2.5−4 nm) may not grow by condensation purely ofsulfuric acid and dimethylamine under ambient conditions, ourresults do not preclude DMAS constituents from being the

Figure 6. (a−e) Arrival time distributions for five separate dry nanocluster radii and with 10 separate relative humidities (RHs) in the drift tube ionmobility spectrometer. (f) The inferred growth factor for nanoclusters of five different dry radii as a function of relative humidity.



2033


primary species involved in the earlier stages of new particleformation (as smaller clusters have been found stable).2,6

Further, as pure, dry DMAS nanoclusters were examined, ourresults do not preclude other species from condensing ontoDMAS and reducing surface vapor pressures, thus stabilizingthem. One such species that could stabilize nanoclusters iswater vapor. It has been shown (again by Marti et al.57) that thesorption of water vapor by particles composed of sulfuric acidor ammonium sulfate decreases by orders of magnitude, even ininstances where the extent of sorption leads to particles whichare still primarily sulfuric acid or ammonium sulfate. Wetherefore use differential mobility analyzer-DT-IMS experi-ments21,33 to examine the extent of water uptake by DMASnanoclusters as a function of nanocluster dry radius. Arrivaltime distributions, in which CPC inferred nanocluster countsper second are plotted as functions of time required fornanoclusters to arrive at the CPC, are shown in Figure 6(panels a−e) for R = 2 nanoclusters with 5 selected initial sizesand at 10 separate relative humidities. Evident is the shift inspectra to longer arrival times with increasing relative humidityfor all initial nanocluster radii. As a negative control experiment,electrospray-generated cesium iodide nanoclusters18 were alsomeasured (results not shown), and no change in the arrivaltime distributions was observed for these nanoclusters at anyrelative humidity in the range examined. The shift in arrivaltime brought about by increasing relative humidity is thusindicative of a decrease in the electrical mobility of DMASnanoclusters (i.e., water vapor did not change the DT-IMScalibration curve), which, in turn, is indicative of water uptakeby these nanoclusters. Water uptake by larger alkylammoniumsalts has been observed in prior studies;7,58 thus, ourobservation of water uptake by nanoclusters under subsaturatedconditions is not surprising. To quantify the extent of uptake,following prior work,60,61 we calculated the growth factor (GF)for all nanoclusters as a function of relative humidity (RH), viathe equation:

=+

+ =

r r

r rGF

( )

( )nc gas RH

nc gas RH 3.7% (3)

We include the gas molecule radius in GF calculations forconsistency with Oberreit et al.,21 and rnc in eq 3 is inferredusing eq 1 as well as the DT-IMS calibration curve with thepeak in arrival time distributions. The baseline relative humidityof 3.7% was the lowest humidity achievable in experiments.Growth factors as functions of relative humidity are shown inFigure 6f. For nanoclusters of all measured initial radii, growthfactors increase with increasing relative humidity but remain inthe 0.98−1.13 range. With the exception of the smallestnanoclusters examined (rnc = 1.55 nm), we find that for a givenrelative humidity, growth factors increase slightly with initialnanocluster radius, suggesting that larger nanocluster uptakeproportionally more water vapor. For example, at a relativehumidity of 29%, measurements suggest that nanclusters withinitial radii of 2.1 nm uptake ∼174 water vapor molecules onaverage (based on the change in volume) and correspondinglyare ∼8.2% water by mass, while initially 3.05 nm radiusnanoclusters uptake ∼659 water molecules and are 9.9% waterby mass. At the highest relative humidity examined, measure-ments suggest that initially 3.05 nm nanoclusters uptake ∼1860water molecules and are ∼23.7% water by mass. Overall, theevidence for water uptake under conditions resembling ambientair is clear in these IMS−IMS experiments, hence such

nanoclusters should be modeled as partially hydrated species.However, as has been found in quantum mechanicalcalculations for smaller DMAS clusters,24 the extent ofhydration is insufficient to permit modeling nanoclusters asaqueous droplets containing dissolved cations and anions.Future work, both experimental and computational, will benecessary to better resolve the internal structures of suchhydrated nanoclusters.

■ CONCLUSIONSA series ion mobility spectrometry based measured have beenperformed to study the physicochemical properties ofdimethylamine-sulfuric acid (DMAS) nanoclusters in theeffective diameter range of

material is available free of charge via the Internet at http://pubs.acs.org.

■ AUTHOR INFORMATIONCorresponding Author*E-mail: [email protected] authors declare no competing financial interest.

■ ACKNOWLEDGMENTSThis work was supported by National Science FoundationGrant CHE-1011810. H.O. acknowledges support from aUniversity of Minnesota Doctoral Dissertation Fellowship.C.L.A. acknowledges support from a Ramon Areces FoundationFellowship.

■ REFERENCES(1) Paasonen, P.; Olenius, T.; Kupiainen, O.; Kurten, T.; Petaja, T.;Birmili, W.; Hamed, A.; Hu, M.; Huey, L. G.; Plass-Duelmer, C.; et al.On the Formation of Sulphuric Acid - Amine Clusters in VaryingAtmospheric Conditions and its Influence on Atmospheric NewParticle Formation. Atmos. Chem. Phys. 2012, 12, 9113−9133.(2) Kurten, A.; Jokinen, T.; Simon, M.; Sipila, M.; Sarnela, N.;Junninen, H.; Adamov, A.; Almeida, J.; Amorim, A.; Bianchi, F.; et al.Neutral Molecular Cluster Formation of Sulfuric Acid-DimethylamineObserved in Real Time Under Atmospheric Conditions. Proc. Natl.Acad. Sci. U.S.A. 2014, 111, 15019−15024.(3) Zhao, J.; Smith, J. N.; Eisele, F. L.; Chen, M.; Kuang, C.;McMurry, P. H. Observation of Neutral Sulfuric Acid-AmineContaining Clusters in Laboratory and Ambient Measurements.Atmos. Chem. Phys. 2011, 11, 10823−10836.(4) Sorooshian, A.; Murphy, S. N.; Hersey, S.; Gates, H.; Padro, L.T.; Nenes, A.; Brechtel, F. J.; Jonsson, H.; Flagan, R. C.; Seinfeld, J. H.Comprehensive Airborne Characterization of Aerosol from a MajorBovine Source. Atmos. Chem. Phys. 2008, 8, 5489−5520.(5) Ge, X. L.; Wexler, A. S.; Clegg, S. L. Atmospheric Amines: Part I.A Review. Atmos. Environ. 2011, 45, 524−546.(6) Jen, C. N.; McMurry, P. H.; Hanson, D. R. Stabilization ofSulfuric Acid Dimers by Ammonia, Methylamine, Dimethylamine, andTrimethylamine. J. Geophys. Res.: Atmos. 2014, 119, 7502−7514.(7) Qiu, C.; Zhang, R. Y. Physiochemical Properties of AlkylaminiumSulfates: Hygroscopicity, Thermostability, and Density. Environ. Sci.Technol. 2012, 46, 4474−4480.(8) Kurten, T.; Loukonen, V.; Vehkamaki, H.; Kulmala, M. Aminesare Likely to Enhance Neutral and Ion-Induced Sulfuric Acid-WaterNucleation in the Atmosphere more Effectively than Ammonia. Atmos.Chem. Phys. 2008, 8, 4095−4103.(9) Loukonen, V.; Kurten, T.; Ortega, I. K.; Vehkamaki, H.; Padua, A.A. H.; Sellegri, K.; Kulmala, M. Enhancing Effect of Dimethylamine inSulfuric Acid Nucleation in the Presence of Water: A ComputationalStudy. Atmos. Chem. Phys. 2010, 10, 4961−4974.(10) Bzdek, B. R.; Ridge, D. P.; Johnston, M. V. Amine Reactivitywith Charged Sulfuric Acid Clusters. Atmos. Chem. Phys. 2011, 11,8735−8743.(11) Petaja, T.; Sipila, M.; Paasonen, P.; Nieminen, T.; Kurten, T.;Ortega, I. K.; Stratmann, F.; Vehkamaki, H.; Berndt, T.; Kulmala, M.Experimental Observation of Strongly Bound Dimers of Sulfuric Acid:Application to Nucleation in the Atmosphere. Phys. Rev. Lett. 2011,106, 228302.(12) Henschel, H.; Navarro, J. C. A.; Yli-Juuti, T.; Kupiainen-Maäẗta,̈O.; Olenius, T.; Ortega, I. K.; Clegg, S. L.; Kurteń, T.; Riipinen, I.;Vehkamak̈i, H. Hydration of Atmospherically Relevant MolecularClusters: Computational Chemistry and Classical Thermodynamics. J.Phys. Chem. A 2014, 118, 2599−2611.(13) Kulmala, M.; Kerminen, V. M.; Anttila, T.; Laaksonen, A.;O’Dowd, C. D. Organic Aerosol Formation via Sulphate ClusterActivation. J. Geophys. Res.: Atmos. 2004, 109, D04205.

(14) Donahue, N. M.; Trump, E. R.; Pierce, J. R.; Riipinen, I.Theoretical Constraints on Pure Vapor-Pressure Driven Condensationof Organics to Ultrafine Particles. Geophys. Res. Lett. 2011, 38, L16801.(15) Thomson, S. W. On the Equilibrium of Vapour at a CurvedSurface of Liquid. Philos. Mag. Lett. 1871, 4, 448−452.(16) Zhang, K. M.; Wexler, A. S. A Hypothesis for Growth of FreshAtmospheric Nuclei. J. Geophys. Res.: Atmos. 2002, 107, D214577.(17) Thompson, S. M.; Gubbins, K. E.; Walton, J. P. R. B.; Chantry,R. A. R.; Rowlinson, J. S. A Molecular Dynamics Study of LiquidDrops. J. Chem. Phys. 1984, 81, 530−542.(18) Ouyang, H.; Larriba-Andaluz, C.; Oberreit, D. R.; Hogan, C. J.The Collision Cross Sections of Iodide Salt Cluster Ions in Air viaDifferential Mobility Analysis-Mass Spectrometry. J. Am. Soc. MassSpectrom. 2013, 24, 1833−1847.(19) Park, K.; Kim, J. S.; Miller, A. L. A Study on Effects of Size andStructure on Hygroscopicity of Nanoparticles using a TandemDifferential Mobility Analyzer and TEM. J. Nanopart. Res. 2009, 11,175−183.(20) Biskos, G.; Malinowski, A.; Russell, L. M.; Buseck, P. R.; Martin,S. T. Nanosize Effect on the Deliquescence and the Efflorescence ofSodium Chloride Particles. Aerosol Sci. Technol. 2006, 40, 97−106.(21) Oberreit, D. R.; McMurry, P. H.; Hogan, C. J. Analysis ofHeterogeneous Uptake by Nanoparticles via Differential MobilityAnalysis-Drift Tube Ion Mobility Spectrometry. Phys. Chem. Chem.Phys. 2014, 16, 6968−6979.(22) Qiu, C.; Zhang, R. Y. Multiphase Chemistry of AtmosphericAmines. Phys. Chem. Chem. Phys. 2013, 15, 5738−5752.(23) DePalma, J. W.; Bzdek, B. R.; Doren, D. J.; Johnston, M. V.Structure and Energetics of Nanometer Size Clusters of Sulfuric Acidwith Ammonia and Dimethylamine. J. Phys. Chem. A 2012, 116, 1030−1040.(24) DePalma, J. W.; Doren, D. J.; Johnston, M. V. Formation andGrowth of Molecular Clusters Containing Sulfuric Acid, Water,Ammonia, and Dimethylamine. J. Phys. Chem. A 2014, 118, 5464−5473.(25) Ortega, I. K.; Olenius, T.; Kupiainen-Maäẗta,̈ O.; Loukonen, V.;Kurteń, T.; Vehkama ̈ki, H. Electrical Charging Changes theComposition of Sulfuric Acid−Ammonia/Dimethylamine Clusters.Atmos. Chem. Phys. 2014, 14, 7995−8007.(26) Ortega, I. K.; Kupiainen, O.; Kurten, T.; Olenius, T.; Wilkman,O.; McGrath, M. J.; Loukonen, V.; Vehkamaki, H. From QuantumChemical Formation Free Energies to Evaporation Rates. Atmos.Chem. Phys. 2012, 12, 225−235.(27) Hogan, C. J.; Fernandez de la Mora, J. Tandem Ion Mobility-Mass Spectrometry (IMS−MS) Study of Ion Evaporation from IonicLiquid-Acetonitrile Nanodrops. Phys. Chem. Chem. Phys. 2009, 11,8079−8090.(28) Hogan, C. J.; Fernandez de la Mora, J. Ion-Pair Evaporationfrom Ionic Liquid Clusters. J. Am. Soc. Mass Spectrom. 2010, 21, 1382−1386.(29) Rus, J.; Moro, D.; Sillero, J. A.; Royuela, J.; Casado, A.; Estevez-Molinero, F.; Fernandez de la Mora, J. IMS−MS Studies Based onCoupling a Differential Mobility Analyzer (DMA) to Commercial API-MS Systems. Int. J. Mass Spectrom. 2010, 298, 30−40.(30) Rader, D. J.; Mcmurry, P. H. Application of the TandemDifferential Mobility Analyzer to Studies of Droplet Growth orEvaporation. J. Aerosol Sci. 1986, 17, 771−787.(31) Villani, P.; Picard, D.; Michaud, V.; Laj, P.; Wiedensohler, A.Design and Validation of a Volatility Hygroscopic Tandem DifferentialMobility Analyzer (VH-TDMA) to Characterize the Relationshipsbetween the Thermal and Hygroscopic Properties of AtmosphericAerosol Particles. Aerosol Sci. Technol. 2008, 42, 729−741.(32) Fernańdez de la Mora, J.; Kozlowski, J. Hand-Held DifferentialMobility Analyzers of High Resolution for 1−30 nm Particles: Designand Fabrication Considerations. J. Aerosol Sci. 2013, 57, 45−53.(33) Oberreit, D. R.; McMurry, P. H.; Hogan, C. J. Mobility Analysisof 2 to 11 nm Aerosol Particles with an Aspirating Drift Tube IonMobility Spectrometer. Aerosol Sci. Technol. 2014, 48, 108−118.



2035

http://pubs.acs.orghttp://pubs.acs.orgmailto:[email protected]://dx.doi.org/10.1021/jp512645g

(34) Cloupeau, M.; Prunet-Foch, B. Electrostatic Spraying of Liquidsin Cone-Jet Mode. J. Electrost. 1989, 22, 135−159.(35) Chen, D. R.; Pui, D. Y. H.; Kaufman, S. L. Electrospraying ofConducting Liquids for Monodisperse Aerosol Generation in the 4 nmto 1.8 mm Diameter Range. J. Aerosol Sci. 1995, 26, 963−977.(36) Scalf, M.; Westphall, M. S.; Smith, L. M. Charge ReductionElectrospray Mass Spectrometry. Anal. Chem. 2000, 72, 52−60.(37) Guharay, S. K.; Dwivedi, P.; Hill, H. H. Ion MobilitySpectrometry: Ion Source Development and Applications in Physicaland Biological Sciences. IEEE Trans. Plasma Sci. 2008, 36, 1458−1470.(38) Kanu, A. B.; Dwivedi, P.; Tam, M.; Matz, L.; Hill, H. H. IonMobility-Mass Spectrometry. J. Mass Spectrom 2008, 43, 1−22.(39) Larriba, C.; Hogan, C. J. Ion Mobilities in Diatomic Gases:Measurement versus Prediction with Non-Specular Scattering Models.J. Phys. Chem. A 2013, 117, 3887−3901.(40) Ku, B. K.; Fernandez de la Mora, J. Relation between ElectricalMobility, Mass, and Size for Nanodrops 1−6.5 nm in Diameter in Air.Aerosol Sci. Technol. 2009, 43, 241−249.(41) Larriba-Andaluz, C.; Fernandez-Garcia, J.; Hogan, C. J.;Clemmer, D. E. Gas Molecule Scattering & Ion Mobility Measure-ments for Organic Macro-ions in He versus N2 Environments. Phys.Chem. Chem. Phys. 2014, submitted.(42) Larriba, C.; Fernandez de la Mora, J.; Clemmer, D. E.Electrospray Ionization Mechanisms for Large Polyethylene GlycolChains Studied Through Tandem Ion Mobility Spectrometry. J. Am.Soc. Mass Spectrom. 2014, 25, 1332−1345.(43) Ude, S.; Fernańdez de la Mora, J. Molecular MonodisperseMobility and Mass Standards from Electrosprays of Tetra-AlkylAmmonium Halides. J. Aerosol Sci. 2005, 36, 1224−1237.(44) Koeniger, S. L.; Merenbloom, S. I.; Valentine, S. J.; Jarrold, M.F.; Udseth, H. R.; Smith, R. D.; Clemmer, D. E. An IMS−IMSAnalogue of MS-MS. Anal. Chem. 2006, 78, 4161−4174.(45) Rader, D. J.; McMurry, P. H.; Smith, S. Evaporation Rates ofMonodisperse Organic Aerosols in the 0.02-Mu-M-Diameter to 0.2-Mu-M-Diameter Range. Aerosol Sci. Technol. 1987, 6, 247−260.(46) Park, K.; Dutcher, D.; Emery, M.; Pagels, J.; Sakurai, H.;Scheckman, J.; Qian, S.; Stolzenburg, M. R.; Wang, X.; Yang, J.; et al.Tandem Measurements of Aerosol Properties: A Review of MobilityTechniques with Extensions. Aerosol Sci. Technol. 2008, 42, 801−816.(47) Larriba, C.; Hogan, C. J.; Attoui, M.; Borrajo, R.; Fernandez-Garcia, J.; Fernandez de la Mora, J. The Mobility-Volume Relationshipbelow 3.0 nm Examined by Tandem Mobility-Mass Measurement.Aerosol Sci. Technol. 2011, 45, 453−467.(48) Fernańdez-García, J.; Fernańdez de la Mora, J. Measuring theEffect of Ion-Induced Drift-Gas Polarization on the ElectricalMobilities of Multiply-Charged Ionic Liquid Nanodrops in Air. J.Am. Soc. Mass Spectrom. 2013, 24, 1872−1889.(49) Fernańdez-García, J.; Fernańdez de la Mora, J. ElectricalMobilities of Multiply Charged Ionic-Liquid Nanodrops in Air andCarbon Dioxide over a Wide Temperature Range: Influence of Ion-Induced Dipole Interactions. Phys. Chem. Chem. Phys. 2014, 16,20500−20513.(50) Larriba, C.; Hogan, C. J. Free Molecular Collision Cross SectionCalculation Methods for Nanoparticles and Complex Ions with EnergyAccommodation. J. Comput. Phys. 2013, 251, 344−363.(51) Kumar, A.; Kang, S.; Larriba-Andaluz, C.; Ouyang, H.; Hogan,C. J.; Sankaran, R. M. Ligand-free Ni Nanocluster Formation atAtmospheric Pressure via Rapid Quenching in a Microplasma Process.Nanotechnology 2014, 25, 385601.(52) Larriba-Andaluz, C.; Hogan, C. J. Collision Cross SectionCalculations for Polyatomic Ions Considering Rotating Diatomic/Linear Gas Molecules. J. Chem. Phys. 2014, 141, 194107.(53) Friedlander, S. K. Smoke, Dust, and Haze; Oxford UniversityPress; New York, NY, 2000.(54) Tammet, H. Size and Mobility of Nanometer Particles, Clustersand Ions. J. Aerosol Sci. 1995, 26, 459−475.(55) Antoine, C. Tensions des Vapeurs; Nouvelle Relation Entre lesTensions et les Tempeŕatures. C. R. Seances Acad. Sci. 1888, 107, 681−684 778−780, 836−837.

(56) Vetere, A. The Riedel Equation. Ind. Eng. Chem. Res. 1991, 30,2487−2492.(57) Marti, J. J.; Jefferson, A.; Cai, X. P.; Richert, C.; McMurry, P. H.;Eisele, F. H2SO4 Vapor Pressure of Sulfuric Acid and AmmoniumSulfate Solutions. J. Geophys. Res.: Atmos. 1997, 102, 3725−3735.(58) Lavi, A.; Bluvshtein, N.; Segre, E.; Segev, L.; Flores, M.; Rudich,Y. Thermochemical, Cloud Condensation Nucleation Ability, andOptical Properties of Alkyl Aminium Sulfate Aerosols. J. Phys. Chem. C2013, 117, 22412−22421.(59) Almeida, J.; Schobesberger, S.; Kurten, A.; Ortega, I. K.;Kupiainen-Maatta, O.; Praplan, A. P.; Adamov, A.; Amorim, A.;Bianchi, F.; Breitenlechner, M.; et al. Molecular Understanding ofSulphuric Acid-Amine Particle Nucleation in the Atmosphere. Nature2013, 502, 359−363.(60) McMurry, P. H.; Stolzenburg, M. R. On the Sensitivity ofParticle-Size to Relative-Humidity for Los-Angeles Aerosols. Atmos.Environ. 1989, 23, 497−507.(61) Liu, B. Y. H.; Pui, D. Y. H.; Whitby, K. T.; Kittelson, D. B.;Kousaka, Y.; McKenzie, R. L. Aerosol Mobility Chromatograph: NewDetector for Sulfuric-Acid Aerosols. Atmos. Environ. 1978, 12, 99−104.(62) Zhao, J.; Eisele, F. L.; Titcombe, M.; Kuang, C. G.; McMurry, P.H. Chemical Ionization Mass Spectrometric Measurements ofAtmospheric Neutral Clusters using the Cluster-CIMS. J. Geophys.Res.: Atmos. 2010, 115, D08205.(63) Smith, J. N.; Barsanti, K. C.; Friedli, H. R.; Ehn, M.; Kulmala,M.; Collins, D. R.; Scheckman, J. H.; Williams, B. J.; McMurry, P. H.Observations of Aminium Salts in Atmospheric Nanoparticles andPossible Climatic Implications. Proc. Natl. Acad. Sci. U.S.A. 2010, 107,6634−6639.(64) Canagaratna, M. R.; Jayne, J. T.; Jimenez, J. L.; Allan, J. D.;Alfarra, M. R.; Zhang, Q.; Onasch, T. B.; Drewnick, F.; Coe, H.;Middlebrook, A.; et al. Chemical and Microphysical Characterizationof Ambient Aerosols with the Aerodyne Aerosol Mass Spectrometer.Mass Spectrom. Rev. 2007, 26, 185−222.



2036

ims ms and ims ims investigation of the structure and ......2014/12/18 · a mass spectrometer is...

Documents