Impact of Humidity on Silica Nanoparticle Agglomerate Morphology

Jun 26, 2018 - Liquid water bridges induce repulsive capillary forces of about −4 nN ... km, that relate dm to np by (3)To obtain Dfm and km, DMA an...
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Impact of humidity on silica nanoparticle agglomerate morphology and size distribution Georgios A. Kelesidis, Florian M. Furrer, Karsten Wegner, and Sotiris E Pratsinis Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.8b00576 • Publication Date (Web): 26 Jun 2018 Downloaded from http://pubs.acs.org on July 4, 2018

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Langmuir

Impact of humidity on silica nanoparticle agglomerate morphology and size distribution

Georgios A. Kelesidis, Florian M. Furrer, Karsten Wegner and Sotiris E. Pratsinis* Particle Technology Laboratory, Institute of Process Engineering, Department of Mechanical and Process Engineering, ETH Zürich, Sonneggstrasse 3, CH-8092 Zürich, Switzerland. Ph. +41 (0) 44 632 31 80; Fax. +41 (0) 44 632 15 95

Submitted to: Langmuir

*Corresponding author: [email protected]

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Abstract The effect of humidity on flame-made metal oxide agglomerate morphology and size distribution is investigated, for the first time to our knowledge, and compared to that of soot which has been widely studied. Understanding the impact of humidity on such characteristics is essential for storage, handling, processing and eventual performance of nanomaterials. More specifically, broadly-used agglomerates of flame-made silica nanoparticles are humidified at various saturation ratios, S = 0.2 - 1.5 and dried before characterization with a differential mobility analyzer (DMA), an aerosol particle mass (APM) analyzer and transmission electron microscopy. At high humidity, the constituent single and/or aggregated (chemically-bonded) primary particles (PPs) restructure to balance the capillary forces induced by condensation-evaporation of liquid bridges between PPs. Larger agglomerates restructure more than smaller ones, narrowing their mobility size distribution. After humidification at S = 1.5 and drying, agglomerates collapse into compact structures that follow a fractal scaling law with massmobility exponent, Dfm = 3.02 ± 0.11 and prefactor, km = 0.27 ± 0.07. This critical S = 1.5 for silica agglomerates is larger than the 1.26 obtained for soot due to the hydrophilic surface of silica that delays water evaporation. The relative effective density, ρeff/ρ, of collapsed agglomerates becomes invariant of mobility diameter, dm, similar to fluidized and spray dried granules. The average silica ρeff/ρ = 0.28 ± 0.02 is smaller than the 0.36 ± 0.04 measured for humidified-dried soot due to the larger silica aggregate size, dm/dp, and number of constituent primary particles, np, of diameter dp. This is verified by tandem-DMA (TDMA) measurements, yielding maximum dm = 3dp and 5dp and np = 13 and 36 for the soot and silica aggregates studied here, respectively, in good agreement with those reported from microscopy and high pressure agglomerate dispersion. A scaling law relating the initial dm,o to dm, Dfm and km after condensation-drying is developed. The mass-mobility relationship of collapsed silica and soot agglomerates obtained by combining this law with fast TDMA measurements is in excellent agreement with that measured by the direct, but tedious, DMA-APM analysis.

Keywords: humidity, agglomerate restructuring, aging, capillary forces, effective density, mass-mobility exponent

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1. Introduction Fractal-like agglomerates of physically-bonded single primary particles (PPs) and/or chemically bonded ones (aggregates)1 are typically formed by coagulation in flame2 or plasma3 reactors (carbon black, fumed silica, photocatalytic titania and several fumed oxides). Furthermore, such agglomerates are emitted by combustion engines (e.g. soot)4 of concern to human health and environment (e.g. climate forcing). This ramified agglomerate morphology changes drastically during atmospheric aging, storage or industrial processing by granulation,5 spray drying6 or fluidization7 in the presence of vapors, such as water (humidity),8 ethanol,9 oleic10 or sulfuric acid.11 Agglomerates restructure by vapor condensation and evaporation into smaller, more compact entities.12 For instance, spray drying of fumed silica resulted in constant effective density, ρeff, of 1000 kg/m3 for agglomerates with mobility diameters, dm, of 60-150 nm.13 These ρeff are up to 2.5 times larger than that of soot agglomerates14,15 and about 50 % smaller than the material density (for silica ρ = 2200 kg/m3). Such nanoparticle packaging by spray drying minimizes their resuspension during handling (dusting), processing5 and improves their performance (e.g. as battery materials16). On the other hand, more compact structures exhibit increased light scattering11,17-19 and lung deposition,20 affecting nanoparticle impact on health and environment.21 During condensation, liquid bridges are formed and grow between PPs creating agglomerates in the pendular or funicular states of granulation22 and inducing capillary forces between their constituent single or aggregated PPs.23 To balance these forces, PPs gradually restructure to minimize the second moment of the mass distribution with respect to their spatial coordinates.24 The PP cohesion by liquid bridging is enhanced with increasing saturation ratio, S (i.e. the ratio of the partial to the equilibrium vapor pressure), reaching a critical value when all pores within the agglomerate or granule are filled and the capillary state of granulation is attained.25 During condensation above the critical S, agglomerates are fully immersed in fluid, reaching the droplet state of granulation.22 The extent of agglomerate restructuring induced by condensation depends on surface tension23,26 and viscosity27 of the condensed vapor. Upon fluid evaporation, partially restructured agglomerates collapse into even more compact structures.28 Experimental29 and numerical studies26 of controlled condensation of organics on soot demonstrated its partial restructuring solely by condensation. The complete agglomerate collapse was originally attributed to vapor condensation in small angle cavities resulting in asymmetric capillary torque on their agglomerates.30 However, the low fractal dimensions measured by light scattering of soot agglomerates enclosed in water droplets28 indicated that agglomerate restructuring is completed during evaporation by surface tension forces.31 It should be noted that these capillary forces are not large enough to break chemical (covalent) bonds between aggregated PPs. Thus, partial29 or complete compaction28 induced by condensation and evaporation verifies that agglomerates are formed also during flame

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synthesis of soot or inorganic materials, as quantified by discrete element14 and population balance modeling32 and characterized by small angle x-ray spectroscopy.33 The evolution of agglomerate structure and mobility size distribution during vapor condensation and evaporation has been monitored for soot particles.30,34 Their “fresh” agglomerates did not restructure28,35 in the presence of humidity for S ≤ 1.2 and their number of constituent PPs, np, was related to their dm by a massmobility exponent, Dfm,14 of 2.22 and prefactor, km, of 1. These Dfm and km correspond to the open morphology of soot formed by surface growth and agglomeration.14 In contrast to water condensation for S < 1.2,28 soot agglomerates partially restructured after condensation and evaporation of organic vapors10 attaining Dfm of 2.44 ± 0.0629 and fractal dimensions of 2.15-2.39.36 In supersaturated humid conditions with S > 1.2, soot agglomerates also became more compact.28 The agglomerate dm measured by tandem-differential mobility analyzer (TDMA) after restructuring decreased up to 30 % depending on initial dm,o for S > 1.2.28 Combined aerosol particle mass (APM) analyzer and DMA measurements revealed an almost compact soot granule morphology:28 Dfm = 2.79 and constant37 ρeff /ρ of 0.36 ± 0.04. Similar soot Dfm and ρeff /ρ have been measured after restructuring by condensation and evaporation of organic36,38 and inorganic vapors.12 Flame-made metal oxide agglomerates of single and aggregated PPs have distinct surface chemistry and morphology compared to those of soot and, thus, different interaction with water. Liquid water bridges induce repulsive capillary forces of about -4 nN between hydrophobic soot PPs.28 The surface of metal oxides is more hydrophilic than that of soot due to their hydroxyl groups that facilitate water adsorption.39 The attractive capillary force between rather hydrophilic metal oxides, such as titania40,41 alumina42 and silica,43 was measured and/or estimated in the range of 2-8 nN during water condensation for S < 1. Furthermore, colliding soot particles form aggregates by reactions with acetylene44 or polycyclic aromatic hydrocarbon molecules with collision diameter less than 1 nm.45 Once gaseous hydrocarbons are converted to soot, collisions between soot aggregates lead only to formation of agglomerates.14 In contrast, metal oxide aggregates grow by collisionsintering that can take place well beyond the consumption of their precursors.46 Compaction of agglomerates by discrete element modeling showed that their porosity decreases with increasing aggregate size.47 Understanding the evolution of metal oxide agglomerate morphology and dm during condensation and evaporation will facilitate their handling, storage, processing and eventual performance. Here, the restructuring dynamics of flame-made silica agglomerates during water condensation and evaporation are investigated. Therefore, an aerosol of silica agglomerates is mixed with humidified air at various temperatures resulting in S ranging from 0.2 to 1.5. Subsequently, these aerosols are dried through a diffusion dryer and their mobility size distribution and morphology are measured. It is shown that the agglomerates have

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fractal-like structure after condensation-evaporation, as their np is related to dm by the Dfm and the prefactor, km. A scaling law is developed to relate the initial dm,o to the dm, Dfm and km after water condensation-drying. Finally, the evolution of hydrophilic silica agglomerate morphology and size distribution are compared to those for hydrophobic soot agglomerates processed with humid air.28,37

2. Theory When agglomerates of polydisperse single and aggregated PPs are formed by coagulation and surface growth44 or sintering,46 their initial mobility diameter, dm,o (prior to condensation-evaporation), is related to their number of PPs, np, of diameter, dp, by:14

dm ,o dp

= n0.45 p

(1)

and effective density, ρeff, by:

ρeff  dm,o  =  ρ  d p 

−0.78

(2)

where ρ is the material density (2200 kg/m3 for silica; 1800 kg/m3 for mature soot corresponding to a H/C atom ratio48 of about 0.2). Scaling laws similar to Eqs. 1 & 2 have been derived for agglomeration alone, neglecting polydispersity and aggregation by surface growth or sintering.49 The latter overestimate by 37 % the measured dry soot dm,o and underestimate by 44 % its ρeff.14 Equations 1 & 2 derived by discrete element modeling of agglomeration and surface growth are valid for both aggregates [14: Fig. 6, triangles] and agglomerates [14: Fig. 6, squares] in excellent with soot measurements.50-53 When water28 or other compounds26 condense on and/or reevaporate from the agglomerate surface, the constituent PPs and aggregates restructure by capillary forces forming compact structures with smaller mobility diameter, dm. According to scaling analysis of fractal-like silver agglomerates,54 this change in agglomerate morphology can be quantified by the mass-mobility exponent, Dfm, and prefactor, km, that relate dm to np by:

d  np = km  m  d   p

D fm

(3)

To obtain Dfm and km, DMA and APM are coupled to extract the agglomerate mass, m, that is related to ρeff by:

m=

π 6

d m3 ρ eff

(4)

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Since the agglomerate np and dp are conserved after condensation and evaporation, eqs. 1 and 3 can be combined to derive a scaling law relating dm to dm,o: 1

− dm D = k m fm dp

 d m,o   dp

2.22

 D fm  

(5)

This equation can be used with TDMA measurements of dm and dm,o as an alternative to more elaborate DMAAPM ones for m and dm to estimate Dfm, km and, thus, np from eq. 3.

3. Experimental 3.1. Aerosol synthesis and sampling Figure 1 shows the experimental set-up with the flame spray pyrolysis (FSP) reactor, the aerosol sampling, dilution and humidification stages, diffusion dryer and particle analyzers.55 Silica nanoparticles were produced by FSP56 of hexamethyldisiloxane (HMDSO, ≥ 98%, Sigma Aldrich) diluted with xylenes (247642, ≥ 98.5% xylenes + ethylbenzene basis, ACS reagent, Sigma Aldrich) to 1 mol/L Si concentration. This solution was fed at 4 mL/min with a syringe pump (Teledyne-Isco, 1000D) to the FSP nozzle and dispersed by 5 L/min oxygen (≥ 99.95%, PanGas) at 1.7 bar pressure drop.55 The resulting spray was ignited by a supporting ring-shaped premixed flame56 of 1.25 L/min CH4 and 2.5 L/min O2. Constant gas flows were established with calibrated mass flow controllers (Bronkhorst, EL-flow). Figure 1 Silica aerosol was extracted at 60 cm height above the burner along its centerline with a stainless steel straight tube sampler (length: 20 cm, inner diameter: 5 mm).57 The sample flow was rapidly diluted and quenched at 25 oC by mixing with compressed air flowing through the tube. The total flow rate out of this first dilution stage was 14.6 L/min, set by a calibrated mass flow controller (Bronkhorst, EL-flow) and a vacuum pump (Vacuubrand, ME 4C).57 A secondary dilution by a factor of 25 was realized with a rotating disk diluter (Matter Engineering AG, MD 19-1E), decreasing the number concentration down to 105 - 106 cm-3 and limiting further coagulation in the sampling lines.58 3.2. Mixing with water vapor and characterization of silica nanoparticles A diluted aerosol flow of 0.65 L/min was mixed with 0.85 L/min of dry or humidified air that was introduced through 12 openings (diameter: 2 mm) into a torus ring mixing chamber of 3 cm inner diameter (Fig. 1). Addition of dry air resulted in a saturation ratio of S = 0.2 downstream the mixing chamber. Humidifying the air with deionized water vapor (Bronkhorst, CEM) increased S up to 1.5 after the mixing chamber. For example,

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humidifying the air with 0.08 mL/min of water at 45 oC resulted in S = 1.5 after mixing with the FSP-made silica aerosol, inducing water condensation onto silica. The post-mixing S and temperature were calculated from energy and mass balances and validated with humidity/temperature measurements (Sensirion, SHT75) for S up to 0.9 (Supplementary Information, SI: Figure S1). A heated stainless steel tube (length: 32 cm, inner diameter: 1.2 cm) downstream the mixing chamber kept S approximately constant for a residence time of about 1 s. The aerosol stream then passed through two silica gel diffusion dryers (length: 40 cm each, inner diameter: 1.2 cm, outer diameter: 6 cm) with a humidity/temperature sensor (Sensirion, SHT75) at their outlet. This reduced the S, indicating that aerosols had been dried efficiently as ambient S = 0.2 was attained. The water condensation and evaporation test conditions (i.e. S = 0.2 - 1.5) were selected to be quite similar to those of Ma et al.28 to facilitate a comparison to restructuring of soot nanoparticles. The charge distribution of the dried aerosol was equilibrated with a soft X-ray neutralizer (TSI 3087) before size-classification with a differential mobility analyzer (DMA; TSI 3081) applying a sheath air flow of 6 10 L/min. The resulting monodisperse aerosol was then directed to a condensation particle counter (CPC; TSI 3775) either directly to obtain the mobility size distribution or via an aerosol particle mass analyzer (APM; Kanomax APM-3600) to measure55 average particle mass and ρeff (eq. 4). For the silica agglomerate size distributions measured here, the fraction of doubly-charged agglomerates ranges from 24 to 1 % (SI: Table S1), resulting in, at most, 5 % less mass.51 So, multiple charging effects on the agglomerate mass measured by APM are neglected, consistent with literature.29,55 Monodisperse silica agglomerates classified by DMA were collected also with an electrostatic precipitator (TSI 3089 with mesh 300 Cu grids) for transmission electron microscopy (TEM, FEI Tecnai F30 FEG) analysis. The PP size distribution was calculated by counting manually over 1000 PPs per sample on TEM images in ImageJ.55 In some experiments, a second DMA (TSI 3081) was placed upstream the mixing chamber to sizeselect silica agglomerates with dm,o = 60-140 nm, forming a tandem DMA (TDMA) system. The dm of singlycharged agglomerates was measured after water condensation for S = 1.5 and subsequent evaporation by DMA and CPC. The Dfm and km were estimated from these TDMA data by eq. 5.

4. Results and Discussion 4.1. Silica agglomerate restructuring dynamics in the presence of humidity Figure 2 shows the effective density, ρeff, and TEM images of representative DMA size-selected silica agglomerates with dm = 100 nm after humidification at a) S = 0.2, b) 1.1, c) 1.3 and d) 1.5, followed by drying.

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Figure S2 provides further images of such agglomerates at lower magnification. As-prepared agglomerates (Figure 2a: S = 0.2) have open morphology with ρeff = 427 kg/m3 that is 80 % smaller than the silica density. Their PPs are strongly aggregated, consistent with images of FSP-made silica from different precursors59 at the same feed enthalpy density60,61 of about 13.6 MJ/kg. The PP size distribution had an overall average dp of 11.9 nm and a geometric standard deviation, σg,p, of 1.4, independent of S (SI: Figure S3). That σg,p is consistent with the 1.37 measured for silica PPs produced with laminar diffusion flames62 which is slightly smaller than the 1.45 of the self-preserving size distribution attained by coagulation.63 This is attributed to sintering that narrows the PP size distribution of aggregates.46 The surface of FSP-made silica is hydrophilic having hydroxyl group density of 4-8 #/nm2,61 consistent with simulations of hydrophilic silica.43 Figure 2 As S increases from 0.2 to 1.1, water adsorbs onto the silica agglomerate surface forming pendular or funicular bridges between PPs.22 Increasing S enhances the extent of such bridging (Figure 2b-d),13,64 inducing attractive capillary forces among their constituent single and aggregated PPs.23 Keskinen et al.13 showed that the silica agglomerate dm increases during water condensation due to adsorbed liquid water layers, indicating that restructuring is limited or non-existent. Subsequent water evaporation from such agglomerates humidified at S = 1.1 and 1.3 (Figure 2b,c) gradually increases their ρeff of 445 and 491 kg/m3, respectively. This is consistent with DMA-APM measurements of soot nanoparticles after coating with oleic acid followed by drying.29,36 As S further increases to 1.5 (Figure 2d), more vapor condenses and silica agglomerates reach the capillary and/or droplet states,22 collapsing completely into compact structures upon drying with ρeff = 640 kg/m3. This collapsed morphology is consistent with measurements of soot agglomerates restructuring completely during oleic acid29,36 and water28 condensation followed by evaporation. The critical S = 1.5 measured here for the collapsed silica agglomerates is larger than the S = 1.26 measured for “fresh” soot, but in excellent agreement with S = 1.56 for soot oxidized at 600 and 700 oC.28 Flame-made silica65 and soot oxidized by O366 or OH34 enhance water adsorption on their surface by being more hydrophilic than that of “fresh” soot. If agglomerates had collapsed during water condensation, the critical S should decrease with increasing surface hydrophilicity as the capillary forces between PPs and aggregates increase.42 However, our data and those of Ma et al.28 indicate that this is not the case. Bambha et al.36 showed that restructuring depends on the method used to dry soot agglomerates and, thus, on the evaporation rate of condensed oleic acid. So, the higher critical S for such hydrophilic PPs indicates that agglomerate restructuring and eventual collapse depends on the water evaporation rate that decreases for increasing surface hydrophilicity.67

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Figure 3 shows the mobility size distributions of silica agglomerates after exposure to S = 0.2 (solid line), 1.1 (dotted line), 1.3 (dot-broken line) and 1.5 (broken line) followed by evaporation. The mobility diameter, dm, is normalized by the average dp = 11.9 nm obtained from microscopy (SI: Figure S3). The shaded region shows the maximum variability of the silica agglomerate size distribution at S = 1.5, demonstrating the reproducibility of the process and measurement. For S = 0.2 (solid line, red-framed TEM image), the ramified agglomerates attain a lognormal size distribution with arithmetic average d m = 108 nm and mobility-based geometric standard deviation, σg,m = 1.58, similar to those of FSP-made zirconia nanoparticles of comparable dp.55 For dm/dp ≤ 5, the mobility size distributions are identical for all S and consist mostly of single aggregates (left blue-framed TEM image in Fig. 3) and few, if any PPs. Such aggregates hardly restructure by water condensation-evaporation due to the strong chemical bonding between their constituent PPs. The dm = 5dp is the size of the largest silica aggregate, also obtained here by TDMA measurements (Figure 6: broken line). For dm/dp > 5 (right blue-framed TEM image in Fig. 3) the agglomerates are quite compact reducing the average d m by 15 %. This is consistent with TDMA measurements of soot agglomerates during oleic acid condensation and evaporation.29 The effect of such restructuring is most pronounced for larger agglomerates. This narrows the mobility size distribution and reduces the σg,m to 1.45 for S = 1.5 (broken line). Soot aggregates not affected by condensation and evaporation have been identified by TDMA9,12,28 and microscopy measurements.38 The effect of restructuring on the entire soot mobility size distribution is typically investigated only for large soot agglomerates consisting of several single and aggregated PPs.9,19 This could be a reason why invariant parts of the soot mobility size distribution after water condensation-evaporation have not been reported so far. Figure 3 4.2. Mass-mobility relationship and effective density of humidified agglomerates The morphology of humidified-dried silica agglomerates with dm/dp > 5 is further investigated by DMA-APM measurements. Figure 4 shows the number of PPs, np, by DMA-APM as a function of the normalized mobility diameter, dm/dp, of silica agglomerates processed with S = 0.2 (diamonds, solid line), 1.1 (circles, dotted line), 1.3 (squares, dot-broken line) and 1.5 (triangles, broken line) followed by drying. The APM distribution is typically broader than that of DMA-selected agglomerates.36 Therefore, np was obtained by dividing the mean agglomerate mass selected by APM by the mean PP mass obtained by image analysis (SI: Fig. S3). The Dfm and km are obtained from eq. 3. For S = 0.2 these agglomerates have Dfm = 2.10 ± 0.06, in agreement with the asymptotic Dfm of 2.15 ± 0.10 obtained by Discrete Element Modeling (DEM) of agglomeration of polydisperse

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PPs.68 The respective km of 1.36 ± 0.28 is consistent with that of agglomerates of polydisperse PPs with σg,p = 1.5.68 Figure 4 The restructuring or partial compaction of silica agglomerates humidified at S = 1.1 and 1.3 followed by drying increases Dfm to 2.33 ± 0.14 (dotted line) and 2.40 ± 0.08 (dot-broken line), respectively, similar to those measured for soot agglomerates after condensing oleic acid followed by drying.36 This indicates that similar contact angles and capillary forces act on hydrophilic silica-water and oleophilic soot-oleic acid interfaces. The agglomerate restructuring and eventual agglomerate collapse by humidification at S = 1.5 and drying (Figure 2d) results in a Dfm of 3.02 ± 0.11 (broken line), in agreement with soot agglomerates after condensation-evaporation of water28 and organic compounds.36,38 The km is decreasing down to 0.27 ± 0.07 for S = 1.5 (broken line), indicating the shrinking of agglomerate branches69 by single and aggregated PP restructuring. Figure 5 shows the relative effective density, ρeff/ρ, according to eq. 4 as function of normalized mobility diameter, dm/dp, of silica agglomerates humidified at S = 0.2 (diamonds, red-outlined inset) and 1.5 (triangles, blue-outlined inset) followed by drying based on DMA-APM measurements. This agglomerate ρeff/ρ is compared to eq. 2 (solid line) derived from surface growth and agglomeration dynamics of soot PPs with σg,p = 1.2.14 The silica PPs studied here are more polydisperse than soot having σg,p = 1.4 (Figure S3). For as-prepared silica (S = 0.2: diamonds, red-framed inset), the measured ρeff/ρ decreases with dm/dp according to a power law closely following agglomeration theory14 (solid line). This suggests that agglomeration of aggregates and PPs is taking place at low or high temperatures in rather dry conditions results in identical ρeff/ρ distributions of silica and soot agglomerates regardless of their σg,p and aggregate size, since their distributions are determined by coagulation alone as aggregation by sintering (or for soot surface growth or hydrocarbon condensation) stops at small residence times.44 Figure 5 Silica agglomerates humidified at S = 1.5 (triangles) followed by drying, collapse into compact structures by single and aggregated PP rearrangement (blue-framed inset) resulting in an average ρeff/ρ = 0.28 ± 0.02 that is invariant with mobility diameter (broken line). This reveals a drastic difference between collapsed (triangles, blue-framed inset) and as-prepared or untreated agglomerates (diamonds, red-framed inset). Similar variations of the ρeff/ρ distribution have been observed for soot agglomerates humidified with S > 1.2 (dot-broken line), but also for spray-dried13 and fluidized inorganic nanoparticles.70 Spray-dried silica13 and fluidized titania and alumina nanoparticles70 attained constant average ρeff/ρ = 0.45 ± 0.23 and 0.27 ± 0.1, respectively, in good agreement with humidified-dried silica (broken line) and soot agglomerates (dot-broken line). This indicates that

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agglomerate restructuring during condensation-evaporation determines the morphology of nanoparticles processed by granulation,5 spray drying6,13 and fluidization.7,70 Soot agglomerates humidified at S > 1.237 are more compact (ρeff/ρ = 0.36 ± 0.04, dot-broken line) than the restructured silica agglomerates here. Soot agglomerates completely collapsed after condensation and evaporation of sulfuric,12 oleic acid,36 or secondary organic aerosols38 attaining ρeff/ρ in the range of 0.33 to 0.56, which is also larger than the ρeff/ρ = 0.28 ± 0.02 measured here for silica (broken line) indicating that more open structures are formed by metal oxides than soot after condensation-evaporation. Agglomerate compaction by DEM simulations suggested that ρeff /ρ decreases with increasing size of their constituent aggregates.47 Thus, the difference between the average of silica (broken line) and soot ρeff /ρ (dot-broken line) could be attributed to the larger aggregate size of the former induced by coagulation and partial sintering or coalescence.46 4.3. Monitoring aggregate and agglomerate size and morphology by TDMA The agglomerate size and morphology of silica and soot28 after humidification at S = 1.5 and 1.26, respectively, and drying are quantified by TDMA. Figure 6 compares the normalized mobility diameter, dm/dp, of silica (triangles, broken line, blue-framed TEM images) and soot agglomerates28 (circles, dot-broken line) after humidification-drying as function of initial normalized mobility diameter, dm,o/dp (abscissa). Both dm/dp and dm,o/dp refer to number averages of the rather monodisperse mobility size distributions produced by DMA size selection.36 The reduction of agglomerate dm by condensation-evaporation becomes less pronounced at small dm,o, as these agglomerates consist of few single and aggregated PPs.38 This trend is consistent with TDMA studies on soot restructuring by condensation-evaporation of inorganic12,28 and organic vapors.29,36,38 For silica with dm,o/dp ≤ 5, dm/dp = dm,o/dp (solid line) suggesting that no restructuring takes place by condensationevaporation, as shown also in Figure 3 for different S. This indicates that dm = 5dp is the largest silica agglomerate size below which PPs are connected mostly by sinter-necks that cannot restructure by capillary forces. The silica aggregate dm = 5dp measured here by TDMA is in excellent agreement with the silica aggregate size of dm = 5dp suggested by the mobility size distribution measurements (Figure 3). High-pressure agglomerate dispersion also yielded dm = 5dp for flame-made titania aggregates.71 The largest soot aggregate derived from TDMA (circles, dot-broken line) is dm = 3dp. The variation of soot aggregate size between different combustion sources and condensing vapors was assessed (SI: Fig. S4). The largest soot aggregate size varies from dm = 1.2dp in normal diffusion flames12 to 4.3dp in inverted diffusion flames.38 This indicates that soot aggregate size depends on process conditions controlling surface growth44 or oxidation.72 When silica is made at conditions similar to those of soot (e.g. Ma et al.28) then the silica aggregate size is larger than that of soot. Smaller

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aggregate sizes attained by soot facilitate the agglomerate restructuring during water condensation and evaporation even at lower S, resulting in larger ρeff/ρ (Figure 5: dot-broken line) and dm reduction compared to those of silica. In fact, the variation of soot ρeff/ρ from 0.33 to 0.56 could be attributed to the aggregate size changing due to process conditions12,38 (Fig. S4). Figure 6 Regressing the TDMA data of silica agglomerates to eq. 5 yield Dfm = 2.88 and km = 0.35 (broken line), in excellent agreement with those measured directly by DMA-APM (Figure 4: broken line), 3.02 ± 0.11 and 0.27 ± 0.07, respectively. For soot the TDMA-obtained Dfm for soot is 2.74, similar to that of silica (as observed by the similar dm/dp slopes) while the km of 0.68 is twice as large. Simulations of spherical agglomerates (Dfm = 3) showed that the fractal prefactor is enhanced by increasing ρeff/ρ.73 Thus, the trend between the soot (dot-broken line) and silica km (broken line) measured here by TDMA is consistent with theory,73 as the restructured soot agglomerates (Figure 5: dot-broken line) have larger ρeff/ρ than that of silica (Figure 5: broken line). Using the TDMA-derived Dfm and km of silica (broken line) and soot (dot-broken line) in eq. 3, the number of PPs per aggregate, np, can be obtained. The largest silica aggregate (dm = 5dp) consists of about 36 PPs, while the largest one for soot (dm = 3dp) has only 13. The latter is in excellent agreement with the soot aggregate np = 10-20 measured by microscopy,38 further validating the use of TDMA with eq. 5 for monitoring the aggregate size and morphology. Figure 7 shows the np of silica (triangles, broken line) and soot agglomerates28 (circles, dot-broken line) after water condensation-evaporation as function of dm/dp from DMA-APM (symbols) that are in good agreement with those from TDMA-derived Dfm and km with Figure 6 in eq. 3 (lines), having maximum deviation of just 8 % at dm/dp = 12. This deviation is within the typical experimental variation of DMA-APM measurements.29 The limitations of eq. 5 are further explored by comparing the np of soot agglomerates produced from normal,12 inverted diffusion38 or premixed flames38 and a diesel soot generator38 measured by TDMA with eq. 5 to those obtained by APM (SI: Fig. S5) after condensation and evaporation of sulfuric acid11 or secondary organic aerosols.38 The np measured by DMA-APM after condensation-evaporation are within 20 % of those obtained by TDMA. This could be attributed to incomplete evaporation and any residues that are not accounted for in eq. 5. Nonetheless, the TDMA-obtained soot np (lines) are in reasonably good agreement with those by DMA-APM (symbols) for all combustion sources and condensed vapors12,38 (SI: Fig. S5). Thus, TDMA can be used with eq. 5 to measure the mass-mobility relationship of agglomerates restructured after condensationevaporation as an alternative to the direct, but laborious, DMA-APM measurements. Finally, agglomerates of single and aggregated soot PPs (circles, dot-broken line) are more compact than those of silica (triangles, broken

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line) having up to 45 % more PPs at dm/dp = 12 due to their smaller aggregate size, consistent with DEM simulations of agglomerate compaction.47 Figure 7

5. Conclusions The effect of water condensation-evaporation on flame-made silica agglomerate morphology and size distribution is quantified for the first time and compared to soot. Silica agglomerates are extracted from the plume of the flame and humidified at saturation ratio, S, ranging from 0.2 to 1.5 before their drying and online characterization by a differential mobility analyzer (DMA), an aerosol particle mass (APM) analyzer and transmission electron microscopy. Due to the hydrophilic surface of silica, such agglomerates restructure between their constituent aggregates and primary particles (PPs) in response to attractive capillary forces induced for S > 1. As a result, these agglomerates are compacted into smaller entities. Larger agglomerates restructure more than smaller ones, decreasing the average mobility diameter, d m , by 15 % and narrowing the mobility size distribution by 20 %. After humidification at critical S = 1.5 and subsequent drying, these agglomerates collapse into even more compact structures and follow a fractal scaling law with mass-mobility exponent, Dfm = 3.02 ± 0.11 and prefactor, km = 0.27 ± 0.07. The critical S = 1.5 measured here for collapsing of silica agglomerates is larger than the 1.26 measured previously for soot due to the hydrophilic surface of flamemade silica that delays water evaporation. A scaling law relating the initial dm,o to dm, Dfm and km after water condensation-evaporation is developed (eq. 5) to monitor the maximum aggregate size and agglomerate morphology during restructuring. The mass-mobility relationships of collapsed silica and soot agglomerates obtained by combining this scaling law with fast tandem-DMA (TDMA) measurements are in excellent agreement with those measured by the direct, but laborious, DMA-APM analysis. The agglomerate ρeff/ρ becomes invariant of dm after water condensation and evaporation, similar to fluidized and spray-dried nanoparticles. The average silica agglomerate ρeff/ρ = 0.28 ± 0.02 is smaller than the 0.36 ± 0.04 measured for soot due to the larger silica aggregate sizes as verified by TDMA. The largest silica aggregate has dm = 5dp and consists of 36 PPs, in excellent agreement with the aggregate size measured from flame-made titania by high pressure dispersion.71 The largest TDMA-derived soot aggregate size of dm = 3dp corresponding to 13 PPs is consistent with soot microscopy measurements38 but smaller than that of silica studied here. Smaller aggregates facilitate the restructuring of agglomerates by water condensation-evaporation, resulting in more compact entities with smaller dm, km and larger ρeff/ρ and Dfm.

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Online diagnostics by TDMA using the scaling law developed here (eq. 5) can be employed to monitor the maximum aggregate size and its impact on the agglomerate structure of atmospheric pollutants in the presence of humidity or other vapors. This method can also facilitate the characterization and control of nanoparticle granule morphology formed by fluidization and spray drying, as well as its optimization for industrial handling, storage, processing and eventual performance in different applications (e.g. battery electrodes, fuel cells etc.).

6. Ackowledgements This research was funded by from the Swiss National Science Foundation (grant no. 200021_149144) and ETH Zurich (grant no. ETH-08 14-2). We gratefully acknowledge the support of Dr. F. Krumeich for TEM imaging and Dr. E. Goudeli for aerosol sampling.

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37. Zangmeister, C. D.; Radney, J. G.; Dockery, L. T.; Young, J. T.; Ma, X. F.; You, R. A.; Zachariah, M. R., Packing density of rigid aggregates is independent of scale. PNAS 2014, 111, 9037-9041. 38. Leung, K. K.; Schnitzler, E. G.; Dastanpour, R.; Rogak, S. N.; Jager, W.; Olfert, J. S., Relationship between Coating-Induced Soot Aggregate Restructuring and Primary Particle Number. Environ. Sci. Technol. 2017, 51, 8376-8383. 39. Iler, R. K., Silanol Groups on Silica-Gel. J. Chromatogr. 1981, 209, 341-342. 40. Laube, J.; Salameh, S.; Kappl, M.; Mädler, L.; Ciacchi, L. C., Contact Forces between TiO2 Nanoparticles Governed by an Interplay of Adsorbed Water Layers and Roughness. Langmuir 2015, 31, 11288-11295. 41. Salameh, S.; Schneider, J.; Laube, J.; Alessandrini, A.; Facci, P.; Seo, J. W.; Ciacchi, L. C.; Mädler, L., Adhesion Mechanisms of the Contact Interface of TiO2 Nanoparticles in Films and Aggregates. Langmuir 2012, 28, 11457-11464. 42. Salameh, S.; van der Veen, M. A.; Kappl, M.; van Ommen, J. R., Contact Forces between Single Metal Oxide Nanoparticles in Gas-Phase Applications and Processes. Langmuir 2017, 33, 2477-2484. 43. Leroch, S.; Wendland, M., Influence of Capillary Bridge Formation onto the Silica Nanoparticle Interaction Studied by Grand Canonical Monte Carlo Simulations. Langmuir 2013, 29, 12410-12420. 44. Kelesidis, G. A.; Goudeli, E.; Pratsinis, S. E., Flame synthesis of functional nanostructured materials and devices: Surface growth and aggregation. Proc. Combust. Inst. 2017, 36, 29-50. 45. Cain, J.; Laskin, A.; Kholghy, M. R.; Thomson, M. J.; Wang, H., Molecular characterization of organic content of soot along the centerline of a coflow diffusion flame. Phys. Chem. Chem. Phys. 2014, 16, 2586225875. 46. Tsantilis, S.; Pratsinis, S. E., Evolution of primary and aggregate particle-size distributions by coagulation and sintering. AIChE J. 2000, 46, 407-415. 47. Martin, C. L.; Bouvard, D.; Delette, G., Discrete element simulations of the compaction of aggregated ceramic powders. J. Am. Ceram. Soc. 2006, 89, 3379-3387. 48. Johansson, K. O.; Gabaly, F. E.; Schrader, P. E.; Campbell, M. F.; Michelsen, H. A., Evolution of maturity levels of the particle surface and bulk during soot growth and oxidation in a flame. Aerosol Sci. Technol. 2017, 12, 1333-144. 49. Sorensen, C. M., The Mobility of Fractal Aggregates: A Review. Aerosol Sci. Technol. 2011, 45, 765-779. 50. Schenk, M.; Lieb, S.; Vieker, H.; Beyer, A.; Golzhauser, A.; Wang, H.; Kohse-Höinghaus, K., Imaging Nanocarbon Materials: Soot Particles in Flames are Not Structurally Homogeneous. ChemPhysChem 2013, 14, 3248-3254.

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51. Rissler, J.; Messing, M. E.; Malik, A. I.; Nilsson, P. T.; Nordin, E. Z.; Bohgard, M.; Sanati, M.; Pagels, J. H., Effective Density Characterization of Soot Agglomerates from Various Sources and Comparison to Aggregation Theory. Aerosol Sci. Technol. 2013, 47, 792-805. 52. Yon, J.; Bescond, A.; Ouf, F. X., A simple semi-empirical model for effective density measurements of fractal aggregates. J. Aerosol Sci. 2015, 87, 28-37. 53. Kholghy, M. R.; Afarin, Y.; Sediako, A. D.; Barba, J.; Lapuerta, M.; Chu, C.; Weingarten, J.; Borshanpour, B.; Chernov, V.; Thomson, M. J., Comparison of multiple diagnostic techniques to study soot formation and morphology in a diffusion flame. Combust. Flame 2017, 176, 567-583. 54. Schmidt-Ott, A.; Baltensperger, U.; Gaggeler, H. W.; Jost, D. T., Scaling Behavior of Physical Parameters Describing Agglomerates. J. Aerosol Sci. 1990, 21, 711-717. 55. Eggersdorfer, M. L.; Gröhn, A. J.; Sorensen, C. M.; McMurry, P. H.; Pratsinis, S. E., Mass-mobility characterization of flame-made ZrO2 aerosols: Primary particle diameter and extent of aggregation. J. Colloid Interf. Sci. 2012, 387, 12-23. 56. Mädler, L.; Stark, W. J.; Pratsinis, S. E., Flame-made ceria nanoparticles. J. Mater. Res. 2002, 17, 13561362. 57. Goudeli, E.; Gröhn, A. J.; Pratsinis, S. E., Sampling and dilution of nanoparticles at high temperature. Aerosol Sci. Technol. 2016, 50, 591-604. 58. Gröhn, A. J.; Eggersdorfer, M. L.; Pratsinis, S. E.; Wegner, K., On-line monitoring of primary and agglomerate particle dynamics. J. Aerosol Sci. 2014, 73, 1-13. 59. Kilian, D.; Engel, S.; Borsdorf, B.; Gao, Y.; Kogler, A. F.; Kobler, S.; Seeger, T.; Will, S.; Leipertz, A.; Peukert, W., Spatially resolved flame zone classification of a flame spray nanoparticle synthesis process by combining different optical techniques. J. Aerosol Sci. 2014, 69, 82-97. 60. Demokritou, P.; Buchel, R.; Molina, R. M.; Deloid, G. M.; Brain, J. D.; Pratsinis, S. E., Development and characterization of a Versatile Engineered Nanomaterial Generation System (VENGES) suitable for toxicological studies. Inhal. Toxicol. 2010, 22, 107-116. 61. Spyrogianni, A.; Herrmann, I. K.; Keevend, K.; Pratsinis, S. E.; Wegner, K., The silanol content and in vitro cytolytic activity of flame-made silica. J. Colloid Interf. Sci. 2017, 507, 95-106. 62. Camenzind, A.; Schulz, H.; Teleki, A.; Beaucage, G.; Narayanan, T.; Pratsinis, S. E., Nanostructure evolution: From aggregated to spherical SiO2 particles made in diffusion flames. Eur. J. Inorg. Chem. 2008, 2008, 911-918.

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63. Vemury, S.; Kusters, K. A.; Pratsinis, S. E., Time-Lag for Attainment of the Self-Preserving Particle-Size Distribution by Coagulation. J. Colloid Interf. Sci. 1994, 165, 53-59. 64. Coelho, M. C.; Harnby, N., Effect of Humidity on Form of Water-Retention in a Powder. Powder Technol. 1978, 20, 197-200. 65. Tricoli, A.; Righettoni, M.; Pratsinis, S. E., Anti-Fogging Nanofibrous SiO2 and Nanostructured SiO2-TiO2 Films Made by Rapid Flame Deposition and In Situ Annealing. Langmuir 2009, 25, 12578-12584. 66. Zuberi, B.; Johnson, K. S.; Aleks, G. K.; Molina, L. T.; Laskin, A., Hydrophilic properties of aged soot. Geophys. Res. Lett. 2005, 32, L01807-1-4. 67. Seisel, S.; Pashkova, A.; Lian, Y.; Zellner, R., Water uptake on mineral dust and soot: A fundamental view of the hydrophilicity of atmospheric particles? Faraday Discuss. 2005, 130, 437-451. 68. Goudeli, E.; Eggersdorfer, M. L.; Pratsinis, S. E., Coagulation of Agglomerates Consisting of Polydisperse Primary Particles. Langmuir 2016, 32, 9276-9285. 69. Heinson, W. R.; Sorensen, C. M.; Chakrabarti, A., Does Shape Anisotropy Control the Fractal Dimension in Diffusion-Limited Cluster-Cluster Aggregation? Aerosol Sci Tech 2010, 44, 1-4. 70. Fabre, A.; Steur, T.; Bouwman, W. G.; Kreutzer, M. T.; van Ommen, J. R., Characterization of the Stratified Morphology of Nanoparticle Agglomerates. J. Phys. Chem. C 2016, 120, 20446-20453. 71. Teleki, A.; Wengeler, R.; Wengeler, L.; Nirschl, H.; Pratsinis, S. E., Distinguishing between aggregates and agglomerates of flame-made TiO2 by high-pressure dispersion. Powder Technol. 2008, 181, 292-300. 72. Ghiassi, H.; Toth, P.; Jaramillo, I. C.; Lighty, J. S., Soot oxidation-induced fragmentation: Part 1: The relationship between soot nanostructure and oxidation-induced fragmentation. Combust. Flame 2016, 163, 179-187. 73. Lapuerta, M.; Martos, F. J.; Martin-Gonzalez, G., Geometrical determination of the lacunarity of agglomerates with integer fractal dimension. J. Colloid Interf. Sci. 2010, 346, 23-31.

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Figures and Captions

Figure 1. Schematic of the experimental set-up with flame spray pyrolysis reactor producing an aerosol of silica agglomerates that is sampled 60 cm above the flame, diluted and then mixed with humidified air of varying temperature to achieve saturation ratios of S = 0.2 to 1.5. The aerosol then passes through a heated tube and a diffusion dryer stage with a humidity sensor at its outlet, before entering the aerosol diagnostics system consisting of neutralizer for charge equilibration, differential mobility analyzer (DMA), aerosol particle mass analyzer (APM) and condensation particle counter (CPC). Size-selected particles are collected with an electrostatic precipitator for transmission electron microscopy (TEM). For tandem-DMA (TDMA) measurements, dry agglomerates with mobility diameter, dm,o, are selected by a second DMA before mixing with humidified air.

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Figure 2. Effective density, ρeff, and TEM images of representative DMA size-selected silica agglomerates with mobility diameter dm = 100 nm after humidification at a) S = 0.2, b) 1.1, c) 1.3 and d) 1.5 followed by drying. For S = 0.2, silica agglomerates are ramified similar to fumed silica with ρeff = 427 kg/m3. For S = 1.1 and 1.3 the agglomerates restructure becoming more compact after drying and having ρeff = 445 and 491 kg/m3, respectively. At higher S, silica agglomerates collapse into rather compact structures with ρeff increasing up to 640 kg/m3, similar to those formed by soot after condensation and evaporation of water and oleic acid.36

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Figure 3. Mobility size distributions of silica agglomerates humidified at S = 0.2 (solid line), 1.1 (dotted line), 1.3 (dot-broken line) and 1.5 (broken line) followed by drying. The mobility diameter, dm, is normalized by the average PP diameter, dp = 11.9 nm, obtained by microscopy (SI: Figure S3). The shaded region shows the maximum variability of the agglomerate size distribution for S = 1.5. The compact structures attained with increasing S (Figure 2) have smaller size, decreasing their average mobility diameter, d m , from 108 nm for S = 0.2 (solid line, red-framed TEM image) to 91 nm for S = 1.5 (broken line). The mobility size distributions are identical for all S for dm/dp ≤ 5 consisting mostly of single aggregates (left blue-framed TEM image) that cannot restructure by condensation-evaporation due to the strong chemical (sinter) bonding between their PPs. For dm/dp > 5 (right blue-framed TEM image), the effect of restructuring is enhanced for larger agglomerates having more aggregates and PPs. This narrows the mobility size distribution and reduces the σg,m down to 1.45 for S = 1.5 (broken line).

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Figure 4. Number of PPs, np, as function of the normalized mobility diameter, dm/dp, of silica agglomerates humidified at S = 0.2 (diamonds, solid line), 1.1 (circles, dotted line), 1.3 (squares, dot-broken line) or 1.5 (triangles, broken line) followed by drying. For S = 0.2, the agglomerates have Dfm = 2.10 ± 0.06, in agreement with the Dfm of 2.2 estimated by Discrete Element Modeling (DEM) of agglomeration of monodisperse PPs in the transition regime.57 The more pronounced restructuring of silica agglomerates with increasing S translates into larger Dfm and smaller km, respectively. The asymptotic morphology obtained after agglomerate collapse at S = 1.5 (Figure 2d) is characterized by Dfm = 3.02 ± 0.11 and km = 0.27 ± 0.07, consistent with the Dfm and km of soot nanoparticles processed with water28 and organic compounds.36,38

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Figure 5. Relative effective density, ρeff/ρ, as function of normalized mobility diameter, dm/dp, of silica agglomerates humidified at S = 0.2 (diamonds, red-framed TEM image) and 1.5 (triangles, blue-framed TEM image) followed by drying. The measured silica agglomerate ρeff/ρ is compared to eq. 2 (solid line) derived from surface growth and agglomeration dynamics of soot PPs with σg,p = 1.2.14 The ρeff/ρ of silica nanoparticles processed with S = 0.2 (diamonds) decreases exponentially with dm/dp, in excellent agreement with agglomeration theory14 (solid line). For S = 1.5, silica PPs and aggregates rearrange by capillary forces, resulting into compact agglomerates (red-outlined inset) with average ρeff/ρ = 0.28 ± 0.02 (broken line), invariant of mobility diameter. This indicates a qualitative change between humidified and dry agglomerates. Soot agglomerates humidified-dried at S > 1.2 followed by drying also attain an average ρeff/ρ = 0.36 ± 0.0437 regardless of mobility diameter (dot-broken line). The smaller average ρeff/ρ of collapsed silica agglomerates compared to that of soot37 could be attributed to their larger aggregate size.47

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Figure 6. Normalized mobility diameter, dm/dp, of silica (triangles, broken line, TEM images) and soot agglomerates28 (circles, dot-broken line) collapsed after water condensation and evaporation for S = 1.5 and 1.26, respectively, as function of their initial normalized mobility diameter, dm,o/dp, measured by tandem-DMA (TDMA). The agglomerate dm reduction by restructuring becomes smaller with decreasing dm,o, as the agglomerates consist of less PPs and aggregates.38 Silica nanoparticles have maximum aggregate size dm/dp = dm,o/dp = 5 (solid line) below which PPs are connected mostly by strong sinter-necks that cannot break by capillary forces. The maximum soot aggregate dm = 3dp measured by TDMA (circles, dot-broken line) is smaller than that of silica, as soot sinter-necks grow only by surface reactions in the absence of sintering44 and shrink by oxidation.72 Regressing the TDMA data of silica agglomerates to eq. 5 yield Dfm = 2.88 and km = 0.35 (broken line), in excellent agreement with those measured directly by DMA-APM (Figure 4: broken line). The TDMAobtained soot Dfm of 2.74 is 5 % smaller than that of silica, while km of 0.68 is two times larger due to its smaller aggregate size and larger ρeff/ρ (Figure 5), consistent with theory.73

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Figure 7. Number of PPs, np, of silica (triangles, broken line) and soot agglomerates28 (circles, dot-broken line) as function of their dm/dp from DMA-APM (symbols) and TDMA measurements (lines). Agglomerates of silica PPs (triangles, broken line) contain less np than those of soot (circles, dot-broken line) due to their larger PP polydispersity and normalized aggregate size dm/dp. The TDMA-obtained silica and soot np (lines) are in good agreement with those by DMA-APM (symbols), having a maximum deviation of 8 % at np = 12, within the typical deviation APM measurements.29

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Graphic Abstract

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Figure 1. Schematic of the experimental set-up with flame spray pyrolysis reactor producing an aerosol of silica agglomerates that is sampled 60 cm above the flame, diluted and then mixed with humidified air of varying temperature to achieve saturation ratios of S = 0.2 to 1.5. The aerosol then passes through a heated tube and a diffusion dryer stage with a humidity sensor at its outlet, before entering the aerosol diagnostics system consisting of neutralizer for charge equilibration, differential mobility analyzer (DMA), aerosol particle mass analyzer (APM) and condensation particle counter (CPC). Size-selected particles are collected with an electrostatic precipitator for transmission electron microscopy (TEM). For tandem-DMA (TDMA) measurements, dry agglomerates with mobility diameter, dm,o, are selected by a second DMA before mixing with humidified air. 189x126mm (96 x 96 DPI)

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Figure 2. Effective density, ρeff, and TEM images of representative DMA size-selected silica agglomerates with mobility diameter dm = 100 nm after humidification at a) S = 0.2, b) 1.1, c) 1.3 and d) 1.5 followed by drying. For S = 0.2, silica agglomerates are ramified similar to fumed silica with ρeff = 427 kg/m3. For S = 1.1 and 1.3 the agglomerates restructure becoming more compact after drying and having ρeff = 445 and 491 kg/m3, respectively. At higher S, silica agglomerates collapse into rather compact structures with ρeff increasing up to 640 kg/m3, similar to those formed by soot after condensation and evaporation of water and oleic acid.36 157x164mm (96 x 96 DPI)

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Figure 3. Mobility size distributions of silica agglomerates humidified at S = 0.2 (solid line), 1.1 (dotted line), 1.3 (dot-broken line) and 1.5 (broken line) followed by drying. The mobility diameter, dm, is normalized by the average PP diameter, dp = 11.9 nm, obtained by microscopy (SI: Figure S3). The shaded region shows the maximum variability of the agglomerate size distribution for S = 1.5. The compact structures attained with increasing S (Figure 2) have smaller size, decreasing their average mobility diameter, , from 108 nm for S = 0.2 (solid line, red-framed TEM image) to 91 nm for S = 1.5 (broken line). The mobility size distributions are identical for all S for dm/dp ≤ 5 consisting mostly of single aggregates (left blue-framed TEM image) that cannot restructure by condensation-evaporation due to the strong chemical (sinter) bonding between their PPs. For dm/dp > 5 (right blue-framed TEM image), the effect of restructuring is enhanced for larger agglomerates having more aggregates and PPs. This narrows the mobility size distribution and reduces the σg,m down to 1.45 for S = 1.5 (broken line). 187x160mm (96 x 96 DPI)

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Figure 4. Number of PPs, np, as function of the normalized mobility diameter, dm/dp, of silica agglomerates humidified at S = 0.2 (diamonds, solid line), 1.1 (circles, dotted line), 1.3 (squares, dot-broken line) or 1.5 (triangles, broken line) followed by drying. For S = 0.2, the agglomerates have Dfm = 2.10 ± 0.06, in agreement with the Dfm of 2.2 estimated by Discrete Element Modeling (DEM) of agglomeration of monodisperse PPs in the transition regime.57 The more pronounced restructuring of silica agglomerates with increasing S translates into larger Dfm and smaller km, respectively. The asymptotic morphology obtained after agglomerate collapse at S = 1.5 (Figure 2d) is characterized by Dfm = 3.02 ± 0.11 and km = 0.27 ± 0.07, consistent with the Dfm and km of soot nanoparticles processed with water28 and organic compounds.36,38 190x190mm (96 x 96 DPI)

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Figure 5. Relative effective density, ρeff/ρ, as function of normalized mobility diameter, dm/dp, of silica agglomerates humidified at S = 0.2 (diamonds, red-framed TEM image) and 1.5 (triangles, blue-framed TEM image) followed by drying. The measured silica agglomerate ρeff/ρ is compared to eq. 2 (solid line) derived from surface growth and agglomeration dynamics of soot PPs with σg,p = 1.2.14 The ρeff/ρ of silica nanoparticles processed with S = 0.2 (diamonds) decreases exponentially with dm/dp, in excellent agreement with agglomeration theory14 (solid line). For S = 1.5, silica PPs and aggregates rearrange by capillary forces, resulting into compact agglomerates (red-outlined inset) with average ρeff/ρ = 0.28 ± 0.02 (broken line), invariant of mobility diameter. This indicates a qualitative change between humidified and dry agglomerates. Soot agglomerates humidified-dried at S > 1.2 followed by drying also attain an average ρeff/ρ = 0.36 ± 0.0437 regardless of mobility diameter (dot-broken line). The smaller average ρeff/ρ of collapsed silica agglomerates compared to that of soot37 could be attributed to their larger aggregate size.47 558x400mm (96 x 96 DPI)

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Figure 6. Normalized mobility diameter, dm/dp, of silica (triangles, broken line, TEM images) and soot agglomerates28 (circles, dot-broken line) collapsed after water condensation and evaporation for S = 1.5 and 1.26, respectively, as function of their initial normalized mobility diameter, dm,o/dp, measured by tandem-DMA (TDMA). The agglomerate dm reduction by restructuring becomes smaller with decreasing dm,o, as the agglomerates consist of less PPs and aggregates.38 Silica nanoparticles have maximum aggregate size dm/dp = dm,o/dp = 5 (solid line) below which PPs are connected mostly by strong sinternecks that cannot break by capillary forces. The maximum soot aggregate dm = 3dp measured by TDMA (circles, dot-broken line) is smaller than that of silica, as soot sinter-necks grow only by surface reactions in the absence of sintering44 and shrink by oxidation.72 Regressing the TDMA data of silica agglomerates to eq. 5 yield Dfm = 2.88 and km = 0.35 (broken line), in excellent agreement with those measured directly by DMA-APM (Figure 4: broken line). The TDMA-obtained soot Dfm of 2.74 is 5 % smaller than that of silica, while km of 0.68 is two times larger due to its smaller aggregate size and larger ρeff/ρ (Figure 5), consistent with theory.73 194x139mm (220 x 220 DPI)

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Figure 7. Number of PPs, np, of silica (triangles, broken line) and soot agglomerates28 (circles, dot-broken line) as function of their dm/dp from DMA-APM (symbols) and TDMA measurements (lines). Agglomerates of silica PPs (triangles, broken line) contain less np than those of soot (circles, dot-broken line) due to their larger PP polydispersity and normalized aggregate size dm/dp. The TDMA-obtained silica and soot np (lines) are in good agreement with those by DMA-APM (symbols), having a maximum deviation of 8 % at np = 12, within the typical deviation APM measurements.29 201x144mm (220 x 220 DPI)

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