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Hyperthermia of Magnetic Nanoparticles: An Experimental Study of the Role of Aggregation Clément Guibert, Vincent Dupuis, Veronique Peyre, and Jérôme Fresnais J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.5b07796 • Publication Date (Web): 18 Nov 2015 Downloaded from http://pubs.acs.org on November 23, 2015

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The Journal of Physical Chemistry

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Hyperthermia of Magnetic Nanoparticles: An 5 6 7 8

Experimental Study of the Role of Aggregation 9 10 1 12 13

Clément Guibert, Vincent Dupuis, Véronique Peyre, and Jérôme Fresnais* 15

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Université Pierre et Marie Curie-Paris 6, UMR 8234, PHENIX, CNRS, Paris, F-75005 France

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*Corresponding author. Université Pierre et Marie Curie-Paris 6, UMR 8234, PHENIX, CNRS, Paris, F20

75005 France; Email: [email protected] 2

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ABSTRACT: Magnetic hyperthermia is a promising tool as an adjuvant therapy for multimodal cancer 4 6

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treatment. However, the heating efficiency of magnetic nanoparticles in biological conditions remains 8

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poorly understood, especially regarding the influence of their dispersion state. In this work, dynamic 10

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light scattering (DLS) and hyperthermia experiments were coupled to highlight the role of aggregation of 1 13

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iron oxide nanoparticles on their heating properties. Bare, poly(acrylic acid), and poly(acrylic acid-co15

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maleic acid) coated nanoparticles were studied. Interparticular interactions were investigated by varying 16 17

both ionic strength and pH. Our results show that the specific loss power (SLP) of nanoparticles in small 20

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loose aggregates is similar to that of well dispersed nanoparticles while the formation of large and dense 2

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aggregates observed by DLS leads to a significant decrease of the SLP. However, for intermediate 23 24

aggregation states, DLS experiments alone do not allow to fully grasp the links between heating 27

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properties and aggregation. Small angle X-ray scattering experiments (SAXS) were then performed to 29

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get further information about aggregate structure. It appears that the compactness of aggregates plays a 30 32

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crucial role, closer nanoparticles leading to more important decrease of heating efficiency. 3 34 35 36 37 38 39 40 41 42 43 4 45 46 47 48 49 50 51 52 53 54 5 56 57 58 59 60 ACS Paragon Plus Environment

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INTRODUCTION 4 5 7

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Magnetic hyperthermia has raised a lot of interest in recent years due to its potential use in 9

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materials science and medicine. Indeed, the ability to convert electromagnetic energy into heat at the 10 1

nanoscale using magnetic nanoparticles (NPs) opens up promising perspectives in numerous 12 14

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applications. The most popular one is probably the destruction of tumor cells by heating them up to their 16

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apoptosis threshold. This strategy is currently under development 18

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and it is generally modeled with

simple theoretical models that have been developed during the past decade 4. Alternative strategies in 21

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cancer treatment using heating induced by an alternating magnetic field are also emerging. They propose 23

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to use heating at the nanoscale to release drug molecules into their surrounding environment 5,6. 24 25

At present, most studies rely on the model developed by Rosensweig 5 that is very efficient for 28

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predicting the basic features of hyperthermia. However, such a model does not take into account the 30

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complexity of the surrounding medium in which the NPs are immersed, although various studies have 31 3

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shown the importance of this parameter. For instance, Haase & Nowack 35

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demonstrated that, due to

magnetic dipolar interactions between NPs, increasing NPs concentration in a ferrofluid is detrimental to 36 37

the heating power (also often called specific loss power (SLP)). In contrast, Mehdaoui et al. 38

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showed

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using simulations that the same dipolar interactions between NPs with low magnetic anisotropy could 42

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lead to an increase of the SLP. It then clearly appears that the mean interparticular distance between NPs 43 4

in a medium has a strong influence on their heating efficiency. Still, the underlying mechanisms are 47

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rarely described, poorly understood and have been scarcely studied, as underlined in a recent review 9, 49

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even though the interactions between NPs are often considered as the source of unexpected results in 50 52

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complex systems. For instance, it has been reported that NPs highly concentrated in liposomes display 54

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an increase in their SLP 56

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, whereas other authors report a decrease of the SLP of NPs confined in a

polystyrene matrix 11. In addition, de Sousa et al. suggested that the dispersion state of NPs could affect 57

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their SLP by showing that NPs functionalized with citrate ligands exhibit reduced heating efficiency 12. ACS Paragon Plus Environment

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The present paper tries to shed new light on this issue by studying the relationship between the 4 6

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dispersion state of maghemite nanoparticles with an average diameter of approximately 12 nm and their 8

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heating power in water using particles with three different surface states: (i) native surface (positively 10

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charged) (ii) surface functionalized with poly(acrylic acid) and (iii) with poly(acrylic acid-co-maleic 1 13

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acid). The first system will be used as a reference to investigate the role of surface functionalization. The 15

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two other ones are particularly adapted as they exhibit tunable aggregation properties that can be 17

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controlled by pH and display a broad domain of colloidal stability in terms of ionic strength 13. 19

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MATERIALS AND METHODS 23 24 26

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Materials. 28

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Magnetic nanoparticles (NPs). Aqueous dispersions of maghemite NPs (γ-Fe2O3) were 30

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synthesized by coprecipitation following Massart’s synthesis pathway 31

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. NPs size polydispersity was

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then reduced by size sorting based on destabilization of the dispersion by an increase in ionic strength 15. 35

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The final pH around 1.8 is adjusted using nitric acid. 36 37

The size and polydispersity of the NPs were characterized by TEM (Figure 1). Image analysis 38 40

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yielded a normal size distribution with a median diameter d0 = 11.7 nm and a standard deviation value of 42

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3.7 nm. Such values are in good agreement with DLS and magnetization measurements (see SI-1). 43 4 45 46 47 48 49

d0 = 11.7 nm s = 3.7 nm

Probability density 0.04 0.08

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0.00

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57 100 nm

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10 15 20 Diameter (nm)

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Figure 1: Left: TEM picture of the NPs; right: size distribution obtained by TEM pictures analysis 4 5 6

(red line: normal distribution model, with d0 = 11.7 nm and standard deviation of 3.7 nm). 7 8 9

The concentration of maghemite nanoparticles in the dispersions was measured with two 10 1

independent techniques. Atomic absorption spectroscopy (Aanalyst 100, Perkin-Elmer) was used to 12 14

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determine the iron content after dissolution of the NP by concentrated HCl, while UV-visible 16

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spectroscopy (Avaspec 2048/Avalight DHC, Avantes) was used as well for water dispersions using a 17 18

previously determined master-curve (between 450 and 700 nm 21

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). Both methods lead to coherent

results. 23

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Nanoparticles Coating. Two types of functionalization were studied: polyacrylic acid (PAA) and 24 25

poly(acrylic acid-co-maleic acid) (PAAMA) (1:1 mole ratio of (acrylic acid):(maleic acid)) coatings. 28

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PAA (sodium salt, 2100 g.mol-1, Sigma-Aldrich), and PAAMA solution (3000 g.mol-1, 50 wt. % in H2O, 30

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Sigma-Aldrich) were used as received. Both coatings were performed by precipitation-redispersion 31 32

following the procedure described for PAA in 17. 35

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Acidity & Ionic Strength Control. An automatic titrator (MTP2 autotitrator, Malvern) was used 36 37

to adjust the pH or ionic strength of the samples. The acidity of the solutions was adjusted by adding 38 40

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0.10 mol.L-1 nitric acid or tetramethylammonium hydroxide solutions (TMAOH). The ionic strength of 42

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the solutions was adjusted by adding concentrated (1.0 to 5.0 mol.L-1) ammonium chloride solutions. 43 4

These solutions were prepared by dissolving ammonium chloride (NH4Cl, Sigma-Aldrich, used as 47

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received) in distilled water. 49

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Dynamic Light Scattering (DLS) & Specific Loss Power (SLP) Measurements. A DLS 50 52

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apparatus (Malvern Nano-ZS, wavelength λ = 656 nm, scattering angle θ = 173°) and a commercial 54

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generator of oscillating magnetic field (magneTherm, nanoTherics, alternating magnetic field at 333 kHz 56

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with an amplitude of 9 mT) were set up in series. Sample circulation through the two measuring cells 57

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was ensured by the peristaltic pump of the MPT2 autotitrator in order to record concomitantly the ACS Paragon Plus Environment

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hydrodynamic diameter of the objects dispersed in water and their SLP (Figure 2). DLS intensity 4 6

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autocorrelation functions (G2(t)) were fitted by the sum of two exponential functions to extract the 8

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contributions of isolated and aggregated nanoparticles (eq 1). Note that the contributions are thus 10

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considered as intensity weighted ones. 1 12 13

G2 (t) = A0 + A1e-2 D1q t + A2e-2 D2q t 2

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2

(1)

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where A0 is a constant corresponding to uncorrelated fluctuations, A1 and A2 are the intensity weights of 18

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isolated and aggregated NPs, respectively. Coefficient D1 and D2 correspond to the diffusion coefficients 19 20

of isolated and aggregated NPs, respectively. They are related to the hydrodynamic diameter dHi using 2

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Stokes-Einstein equation: d Hi  25

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kT 4p n . q is the scattering vector, defined as q = sin(q / 2) , with n 3Di l

the refractive index of the solvent, λ the laser wavelength, and θ the scattering angle. 28 29

The isolated nanoparticles diameter was set as the first contribution to the fit. A0, A1, A2, and dH2 30 32

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were adjusted to fit the experimental data G2(t) with equation 1. The intensity-weighted contributions of 34

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isolated (%isolated) and aggregated (%aggregated) NPs were determined using equation 2. 35 36 37

%isolated = 38 39

A1 A2 ´100 ; %aggregated = ´100 A1 + A2 A1 + A2

(2)

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The average diameter was then calculated with the intensity-weighted contribution of each diameter (eq. 43

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3). 45

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dH ave = (%isolated ´ d H isolated + %aggregated ´ d H aggregated ) /100 46

(3)

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After adding a solution in the main reservoir, the dispersion was pumped through the whole loop 50

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for about 5 minutes, i.e. approximately 10 times the total sample volume to homogenize the dispersion. 51 53

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The pump was then stopped and the temperature was monitored in the SLP measurement cell. 5

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Temperature equilibration times of at least 30 seconds were used prior to performing DLS and SLP 56 57

measurements. The volume of solution added to the sample was controlled by the autotitrator and 58 59 60 ACS Paragon Plus Environment

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accurately recorded. The dilution induced by the addition of solution was taken into account to calculate 4 6

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the exact NPs concentration during the whole experiment. 8

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A non-metallic optical fiber thermometer (Fluoroptic, Luxtron) was used to record the 10

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temperature evolution in the samples. The initial rise in temperature was approximated by a linear 1 12

increase as a function of time (dT/dt) 1. The SLP of the nanoparticles in the sample was then calculated 15

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according to equation 4: 16 17 18 19

SLP  C P  w  20 21

dT dt

(4)

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where Cp is the specific heat capacity of the solvent and w the weight fraction of NPs in the sample. A 25

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value of Cp = 4184 W.K-1.g-1 was used in water. 26 27 28 29 30 31

acid, base or salt addition 32 3 34 35 36 37 38

pump 39

pH probe 40 42

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main reservoir: addition of acid, base or saline solution, monitoring of the pH 45

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DLS measurement

SLP measurement

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Figure 2: Scheme of the coupling of DLS and SLP measurements. 48 50

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Small Angle X-ray Scattering (SAXS) Experiments. Different dispersions were analyzed by 51 52

small angle X-ray scattering (SAXS) measurements on the SWING beamline of the SOLEIL 5

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Synchrotron (Saint Aubin, France). Measurements were performed at an energy of 7 keV (λ = 1.77 Å), 57

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with a two dimensional CCD (Charge-Coupled Device) detector localized at distances of 3.5 or 1 m 58 59 60 ACS Paragon Plus Environment

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from the sample in order to investigate a scattering vector (Q) range of 0.002 Å-1 – 0.3 Å-1. Standard 4 6

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correction procedures were applied for sample thickness, X-ray beam transmission, empty cell signal 8

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subtraction, and detector efficiency to obtain the scattered intensity in absolute scale (cm -1). The 10

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software Foxtrot® was used to achieve such data reduction. 1 12 13

Samples for SAXS were prepared by batch, by adding some base (resp. acid) to initial 15

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dispersions of bare NPs (resp. coated NPs) until the desired pH was reached. 16 17 18 20

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RESULTS 21 2 23

1) Effect of Ionic Strength. Bare NPs are easily destabilized by an increase in ionic strength. 24 25

Typically, for a dispersion containing 4 wt. % NPs, above a concentration of 0.4 mol L-1 of nitric acid, 28

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more than 50% of the NPs are flocculated 30

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. Therefore, only PAA and PAAMA coated NPs will be

described in this paragraph. Their SLP and hydrodynamic diameter are plotted versus NH4Cl 31 3

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concentration on Figure 3. PAA coated NPs are stable on the whole range of investigated ammonium 35

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chloride concentrations since the hydrodynamic diameter remains constant (around 45 nm), from 0.001 37

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to 1.0 mol L-1. This is consistent with previous results 13. Concomitantly, the SLP also remains constant 38 40

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in the whole ionic strength range. Such a stability can be explained by surface charge density that 42

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increases drastically (roughly 20 titrable groups per square nanometer for PAA 4

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) in comparison with

bare NPs (1.5 charge.nm-2). As a consequence, electrostatic repulsions persist even at high ionic strength 47

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. This is an important result, as in vivo conditions often involve high ionic strengths. PAA coating then

clearly appears as a viable solution for stabilizing small magnetic NPs. 50 52

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PAAMA coated NPs display a slightly different behavior as strong aggregation (characterized by 54

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a steep increase in hydrodynamic diameter) occurs when the ionic strength reaches a value between 56

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0.10 mol.L-1 and 0.50 mol.L-1. This event is associated with a simultaneous decrease of 45% of the SLP. 57 58 59 60 ACS Paragon Plus Environment

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This difference in behavior between PAA and PAAMA can be tentatively assigned to differences in 4 5

surface structure and conformation at the NPs surface 19, a point that deserves further attention. 7

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Figure 3: SLP (open circles – right scale) and hydrodynamic diameter, dH, (filled squares – left scale) 27

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versus NH4Cl concentration. Left: PAA coated NPs, right: PAAMA coated NPs, (maghemite mass 28 29

fraction: 0.5 to 0.3 wt. %). 31

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2) Effect of pH. NPs aggregation can also be controlled by varying pH. Indeed, this parameter 35

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modifies the surface charge density through acid-base reactions. It is thus possible to tune the charge of 36 38

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NPs that is responsible for interparticular repulsions. In these experiments, the total ionic concentration 40

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was maintained below 0.05 mol.L-1. Aggregation is then mainly due to pH variations, even for bare 41 42

nanoparticles. 43 45

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a. Bare NPs. Results obtained for bare nanoparticles are reported on Figure 4. Starting from 47

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acidic pH, the dispersion is progressively destabilized by adding a base, TMAOH. DLS was used to 48 49

record correlation functions G2(t) at different pHs. From G2(t), for each pH both the average 52

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hydrodynamic diameter and the contribution and hydrodynamic diameter of isolated well dispersed (22.2 54

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nm) and aggregated nanoparticles can be calculated. Aggregate size was estimated at 56 nm between pH 5 56

2.1 and 3.8. It then progressively increases from 80 nm at pH = 4.5 up to 230 nm at pH = 5.3. Total 58

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aggregation is observed at pH 7.1, with no isolated detectable nanoparticles and large aggregates that 4 6

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tend to flocculate. Note that at pH 7.1, the micrometric size determined with DLS is meaningless. 7 8

Between pH 2.1 and 3.8, analysis of the correlation functions highlight a growing contribution of 10

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aggregates (from 7% to 47%) and a diminution of the contribution of isolated nanoparticles (from 93% 1 13

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to 53%). For pH values above 3.8, aggregates become larger and their contribution is preponderant. 14 15

Interestingly, the SLP of the nanoparticles remains constant from pH 2.1 to 5.5 (around 20 W.g17

16 1

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). An SLP decrease is detected at pH 7.1, where complete NPs aggregation is observed.

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Figure 4: A: SLP (open circles – right scale) and average hydrodynamic diameter, dH, (filled squares – 4 6

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left scale) versus pH for bare nanoparticles (maghemite mass fraction: 0.40 to 0.37 wt. %) – B: Relative 8

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contributions of isolated NPs (%isolated, open diamonds) and aggregates (%aggregated, triangles) versus pH. 10

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b. PAAMA coated NPs. The same experiment was performed for PAAMA coated NPs, starting 1 13

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from pH 7 down to 1.5. According to the average diameter, PAAMA coated NPs are stable over a large 15

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pH range, from pH 7 down to 2.8 (Figure 5). However, between 3.2 and 2.8, small aggregates (smaller 16 17

than 60 nm) are detected (Figure 5 down). They do not influence the SLP, that remains constant (20 20

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W.g-1) down to pH 2.8. Then, an abrupt decrease of the SLP is measured, from 20 W.g-1 to 6 W.g-1 2

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between pH 2.8 and 1.5, while both size and contribution of aggregates increase drastically. 23 24 25 26 27 28 29 30 31 32 3 34 35 36 37 38 39 40 41 42 43 4 45 46 47 48 49 50 51 52 53 5

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Figure 5 A: SLP (open circles – right scale) and averaged hydrodynamic diameter, dH, (filled squares – 57

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left scale) versus pH for PAAMA coated nanoparticles (maghemite mass fraction: 0.45 to 0.30 wt. %) – 58 59 60 ACS Paragon Plus Environment

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B: Relative contributions of isolated NPs (%isolated, open diamonds) and aggregates (%aggregated, triangles) 4 6

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versus pH. 7 9

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c. PAA coated NPs. Figure 6 displays the results obtained for PAA coated NPs, starting from pH 10 1

8.1. In contrast with bare and PAAMA NPs, aggregates around 70 nm are initially present in the 12 14

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suspension (%aggregated around 30%). Such a size corresponds to very small aggregates of 2-3 NPs, 16

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probably formed during the coating process. They remain stable afterwards. Interestingly, this initial 17 18

slight aggregation does not significantly influence SLP values that are equal to those of well dispersed 21

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bare or PAAMA coated NPs. 23

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The titration of PAA coated NPs induces no further aggregation while decreasing pH from 8.1 to 24 25

4.5 (Figure 6), as evidenced by the constant contribution of aggregates and constant dH. Between pH 4.5 28

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and 3.8, a slight aggregation occurs (%aggregated and dH increase) with no influence on the SLP. The 30

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average hydrodynamic diameter increases sharply from pH 3.8 to 2.5, where flocculation is observed. 31 3

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A decrease of the SLP is only detected when aggregates are large and preponderant in the dispersion, at 35

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pHs lower than 3.5. Contrary to PAAMA coated NPs where the minimum SLP value was 5 W.g-1, the 37

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SLP of PAA coated NPs decreases from 20 to 10 W.g-1 only. 38 39 40 41 42 43 4 45 46 47 48 49 50 51 52 53 54 5 56 57 58 59 60 ACS Paragon Plus Environment

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Figure 6: A: SLP (open circles – right scale) and hydrodynamic diameter, dH, (filled squares – left 35 37

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scale) versus pH for PAA coated nanoparticles (maghemite mass fraction: 0.45 to 0.30 wt. %) – B : 39

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Relative contributions of isolated NPs (%isolated, open diamonds) and aggregates (%aggregated, triangles) 40 41

versus pH. 42 43 4 45 47

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DISCUSSION 48 49 50

At acidic pH (i.e. below the point of zero charge at 7), bare NPs likely mainly bear surface 53

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oxonium groups, –OH2+, that should ensure colloidal stability of the dispersion through electrostatic 5

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repulsive interactions. DLS measurements indicate that this is indeed the case at low pH as aggregation 56 58

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remains very limited below pH 3 (Figure 4). Between pH 3 and 4, the proportion of aggregated particles 59 60 ACS Paragon Plus Environment

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strongly increases but with a limited increase in average size. An increase in pH up to a value above 5 4 6

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leads to a more significant increase in size and finally at pH 7 all oxonium groups are deprotonated and 8

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the surface becomes neutral. The remaining interparticular interactions are then purely attractive (van der 10

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Waals and magnetic interactions) and the NPs strongly flocculate. Interestingly, at pH 5, although 1 13

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around 90% of the NPs are included in aggregated structures (Figure 4B), the SLP remains almost 15

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constant. It is significantly affected only when complete aggregation and important size increase are 16 17

observed. 20

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The two kinds of coated NPs display a similar behavior in terms of colloidal stability, which is 2

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logical considering that they both bear the same functional groups: carboxylic acids. At basic pH, these 24

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groups are deprotonated and display a negative charge (-COO-), ensuring the colloidal stability of the 27

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dispersion through electrostatic repulsive interactions. If PAAMA coated NPs are well dispersed at basic 29

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pH, PAA coated NPs exhibit a contribution to the scattered intensity that can be attributed to the 30 32

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presence of small aggregates made of 2-3 NPs. Their formation does not influence the SLP values, 34

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which is identical to that of uncoated or PAAMA coated NPs when well dispersed (almost 20 W.g-1), a 36

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feature reminiscent of what was observed for bare NPs. For both PAA and PAAMA coated particles, 37 39

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SLP decrease is observed upon strong aggregation that occurs in a narrower pH range than for bare NPs. 41

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It must be pointed out that the final lowered SLP values are significantly different between both 43

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polymers i.e. 10 and 5 W.g-1 for PAA and PAAMA, respectively. 46

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It then clearly appears that DLS experiments are not sufficient to fully explain the relationships 48

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between aggregation state and SLP. Indeed, for bare NPs, 90% aggregation does not lead to a significant 49 50

SLP decrease and, depending on the polymer coating, the decrease in SLP can be significantly different. 53

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Aggregate structure and interparticle interactions may then play a role. For this reason SAXS 5

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experiments were performed at various pHs to get some deeper insight into these two parameters. 56 57 58 59 60 ACS Paragon Plus Environment

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For the three systems, we focused our analysis on the two extreme states, i.e. well dispersed NPs 4 6

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displaying the highest SLP and aggregated NPs displaying the lowest SLP (Figure 7). 8

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The reference diffractogram for non-aggregated non-interacting bare NPs at pH = 1.9 and the 10

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diffractogram for PAAMA coated NPs at pH = 6.0 can both be fitted by the form factor of a normal 1 13

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distribution of polydisperse hard spheres (mean diameter: 10.8 nm, standard deviation 4.1 nm, see SI-2). 15

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Such a value for bare NPS agrees with TEM analysis. The fact that the same form factor can be applied 16 17

to PAAMA coated NPs shows that the contrast between the polymer and the solvent is not strong 20

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enough to significantly affect the patterns. In contrast, PAA coated NPs at pH 6 cannot be fitted by the 2

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same form factor as an increase of the scattered intensity at small Q is observed. This cannot be due to a 23 24

contrast difference and must then be ascribed to a slight aggregation that was already revealed by DLS 27

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(Figure 6B). More quantitative information on these aggregates can be obtained by dividing the 29

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asymptotic value of the scattered intensity for Q = 0 by the similar value obtained for the form factor. A 30 32

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value of 3 is thus obtained, which is coherent with the DLS measurements. 34

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The SAXS diffractograms of aggregated states indicate for the different systems (bare, PAA, and 36

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PAAMA coated NPs) an aggregation (increase of the intensity at very low Q) into objects that are bigger 37 39

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than 300 nm (the maximal characteristic size reachable with the used SAXS set-up). The exponents n 41

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from the law I Qn at low Q are equal to 2.1 for bare and PAA coated particles, whereas a higher value 42 4

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of 2.4 is obtained for PAAMA coated particles. The 2.1 exponent could indicate a rather low 46

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compactness of fractal aggregates whereas the value of 2.4 could indicate the presence of more compact 48

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aggregates. Further information can be extracted by calculating the experimental structure factors 49 51

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obtained by dividing the diffractograms by the experimental form factor for well dispersed nanoparticles. 53

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For both bare and PAA coated NPs, the structure factors display a smooth interaction peak 5

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confirming the rather loose structure of the aggregates. The corresponding Q* values (around 0.052 Å-1 58

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and 0.049 Å-1 for bare and PAA coated particles, respectively) correlate with distances d* = 2π/Q* of 59 60 ACS Paragon Plus Environment

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12.1 nm and 12.6 nm respectively. d* can be interpreted as the mean contact distance between two NPs, 4 6

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that amounts to the diameter of a single particle for bare NPs (11.7 nm). The higher distance obtained for 8

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PAA coated particles can be assigned to the polymer shell surrounding the particles. In both cases, 10

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aggregation occurs without conspicuous local structuring. 1 12 13 14 15 16 17 18 19 20 21 2 23 24 25 26 27 28 29 30 31 32 3 34 35 36 37 38 39 40 41 43

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Figure 7: SAXS diffractograms (up) and structure factors (down) of bare (left), PAA (middle), and 4 46

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PAAMA (right) coated NPs at two pH values (well dispersed (black circles) and aggregated (red 48

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squares) states). Maghemite mass fraction around 0.5 wt. %. 49 50 51

In contrast, PAAMA coated NPs display a much more defined structure factor that can be 54

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modeled as corresponding to a dispersion of hard spheres of 0.10 - 0.15 volume fraction. This leads to 56

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the appearance of a sharp interaction peak at q* = 0.052 Å-1, corresponding to d* = 12.1 nm. This d* 57 58 59 60 ACS Paragon Plus Environment

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value is again close to the contact distance between two NPs, with a denser packing than for PAA coated 4 6

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NPs. This denser packing appears to explain the significantly lower SLP value observed for this system. 8

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New information about the influence of aggregation on SLP can be drawn from this work. 10

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Firstly, in the systems studied here, coating the NPs does not influence SLP as the same values were 1 13

12

measured for bare, PAA coated and PAAMA coated NPs when well dispersed. In the absence of 15

14

aggregation phenomena, ionic strength does not influence the SLP either. Screening long-range 16 17

electrostatic interactions does not have any effect on heating efficiency, a point that had not been clearly 20

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18

evidenced yet but appears logical as electrostatic repulsions are not explicitly involved in hyperthermia 2

21

mechanisms. 23 24

Secondly, we evidenced a strong correlation between aggregation state and SLP of the NPs. NPs 27

26

25

aggregation induces an increase of magnetic interactions between nanoparticles, resulting in certain 29

28

conditions in a decrease of hyperthermia efficiency. These interactions can be twofold. Magnetic dipole30 31

dipole interactions such as modeled in 7 and 34

3

32

20

can lead to a decrease of the heating efficiency of NPs.

The local concentration of NPs in the aggregates deduced from the SAXS (volume fraction around 0.1036

35

0.15) corresponds to a concentration at which a significant decrease of the SLP can be expected, 37 39

38

according to the simulations performed by Tan & al. 41

40

20

. An additional factor should also be taken into

account: the demagnetization field. It is indeed induced inside the aggregates by their own magnetization 42 43

and it reduces the local magnetic field, which leads, therefore, to a decrease of the SLP. 45

4 46 48

47

CONCLUSION 49 50 51

In this study, the coupling between DLS and SLP measurements led to the discovery of a 52 54

53

correlation between the aggregation state and the heating properties of the NPs. Indeed, we showed that, 56

5

whatever the nature of the surface of the NPs (coated or not), their colloidal stability and the morphology 57

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of the aggregates must be taken into account to understand the evolution of their SLP. When only small ACS Paragon Plus Environment

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1 3

2

oligomers made of a few particles are formed, the SLP does not differ significantly from a well4 6

5

dispersed state. This is the case for bare NPs at pHs around 4-5 and for PAA NPs that exhibit an 8

7

aggregation number of 3. In such a situation, the NPs are not numerous enough in the aggregates to 10

9

cause strong enough interactions to affect the SLP. The information derived from DLS experiments 1 13

12

about aggregation is however not detailed enough to properly predict the evolution of SLP upon 15

14

aggregation. Aggregate structure that can be approached from SAXS experiments provide 16 17

complementary information. It reveals the importance of compactness. In loose aggregates, the decrease 20

19

18

in SLP remains moderate. This may be due to a relatively large distance between NPs. Indeed, the 2

21

magnetic dipolar interaction energy decreases as a function of the distance between the particles centers 24

23

to a power of 3 21. In the limit case of strong magnetic coupling, for 10 nm particles, this interaction can 27

26

25

be estimated at -1.2 kT when NPs are in contact and at -0.15 kT for distances of 20 nm. In contrast, 29

28

increased compactness leads to a drastic decrease of the SLP. Magnetic dipolar interactions between NPs 30 32

31

in the aggregates are then maximized. 34

3

Complementary studies are still necessary to obtain a more quantitative link between the extent 36

35

of the aggregation and the decrease of the SLP. Such results that could be obtained from a detailed 37 39

38

SAXS analysis, coupled with numerical simulations could be significant for future biological 41

40

applications of hyperthermia. Regarding that latter point, it must also be pointed out that the use of PAA 42 43

coating appears as a promising way in the therapeutic use of magnetic NPs. 45

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46

ASSOCIATED CONTENT 48 50

49

Supporting Information 51 53

52

SI-1: Magnetization curve for bare nanoparticles. Langevin fit of the magnetization curve. SI-2: 5

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Dynamic light scattering correlation function for bare nanoparticles with corresponding fit at three pH 57

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values. Table containing the fit parameters. SI-3: Form factor of bare nanoparticles obtain by SAXS, and 58 59 60 ACS Paragon Plus Environment

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the fit corresponding to normal distribution of polydisperse hard spheres. This material is available free 4 6

5

of charge via the Internet at http://pubs.acs.org. 7 8 9 1

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ACKNOWLEDGMENTS: 12 13

We acknowledge SOLEIL for provision of synchrotron radiation facilities and we would like to thank 16

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Dr. Javier Perez for assistance in using beamline SWING. Dr. Laurent Michot is sincerely and warmly 18

17

thanked to have read and clarified this article. 19 20 21 23

2

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Hyperthermia of Magnetic Nanoparticles - ACS Publications

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