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Ignition and explosion risks of nanopowders
Journal of Hazardous Materials 181 (2010) 873–880
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Journal of Hazardous Materials journal homepage: www.elsevier.com/locate/jhazmat
Ignition and explosion risks of nanopowders J. Bouillard a,∗ , A. Vignes a , O. Dufaud b , L. Perrin b , D. Thomas b a b
INERIS, Parc Technologique ALATA, B.P. 2, F-60550 Verneuil-en-Halatte, France Laboratoire Réactions et Génie des Procédés, Université de Lorraine, CNRS, 1 rue Grandville, B.P. 20451, F-54001 Nancy, France
a r t i c l e
i n f o
Article history: Received 15 February 2010 Received in revised form 13 April 2010 Accepted 19 May 2010 Available online 26 May 2010 Keywords: Nanopowders Ignition Explosion Carbon nanotube Aluminium Carbon blacks
a b s t r a c t Characterization methods with regard to nanopowder flammability and explosivity are presented and illustrated for few nanopowders. Analytical models are developed in order to explain the dependency of the combustion times on the particle diameter. Experimental evidence shows that there exists, for carbonaceous and metallic materials, mainly two combustion regimes that are either kinetically controlled, for small size particles, or diffusion controlled, for large size particles. From the experimentally measured combustion data of those materials, the dependencies of the ignition temperature and the minimal explosive concentration (MEC) with regard to the particle size have been analyzed. We found that the two combustion regimes yield two different tendencies with respect to the particle size. Overall, it is found that as the particle size decreases, minimum ignition temperature (MIT) and minimum ignition energy (MIE) decrease, indicating higher potential inflammation and explosion risks for the use of nanopowders. By contrast, the minimal explosion concentration (MEC) did not show strong variations as the particle size decreases. Rather, a theoretical plateau is observed, which was experimentally confirmed. We also observed that carbon nanopowders exhibit a low propensity to explode while metallic nanopowders can be very reactive, thus delineating high potentials for explosion risks in manufacturing facilities. © 2010 Elsevier B.V. All rights reserved.
1. Introduction
2. Experimental setups and methods
For any powders set in suspension in air, the ease at which they ignite, burn and propagate varies considerably with important factors that have to be characterized so that one can be able to control their explosion propensity. One of them is obviously the particle size, which takes nanopowders now under higher scrutiny for OH&S issues; others are the particle concentration, the degree of agglomeration, and the degree of turbulence [1–4]. So far, literature studies concerning the evaluation of explosion and flammability hazards of powders were essentially carried out on micro-sized powders [5], albeit there are the recent extensive studies performed by the EU NANOSAFE2 project [6] during the 2005–2009 period and more recently by Wu in Taiwan [7,8] in 2009–2010. This work proposes to review measured explosion safety parameters of few nanoparticles and nanofibers (carbon blacks, aluminium and multiwalled carbon nanotubes) performed in course of the EU NANOSAFE2 project.
2.1. Nanopowders considered from the Geldart’s powder classification perspective
∗ Corresponding author. Tel.: +33 3 44556169; fax: +33 3 44556565. E-mail address: [email protected] (J. Bouillard). 0304-3894/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.jhazmat.2010.05.094
Powders can be characterized by their propensity to fluidize in air. Geldart [9] suggested that uniformly sized powders can be classified into four types characterized by the density difference between the particle s and the fluid g and by their mean particle size (Fig. 1). Nanopowders are therefore of Geldart C (Cohesive) type, so they naturally tend to easily agglomerate. Group C powders are difficult to fluidize because the interparticle forces are greater than those that the fluid exerts on the particles. Such powder characteristics may have an impact on the powder dispersion during flammability and explosivity measurements by traditional apparatuses such as those described in Section 2.4. They also exhibit very low bulk apparent density as it is reported in Fig. 2. This figure shows that, because of the high voidage of the bulk nanopowders, their storage may require larger volumes than those conventionally required for micropowders. A low bulk density of nanopowders may also be indicative of low thermal conductivity, which may lead to higher self-heating and ignition risks when such powders are stored in large containers. Such smoldering fire risks will not be treated in this paper but will be covered in a future one.
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Fig. 1. Four groups (A–D) from Geldart’s classification of powders [9].
Fig. 2. Bulk to specific density ratio of various nanopowders as a function of the particle diameter.
2.2. Particle characterization In this study, aluminium, carbon black and multiwalled carbon nanotubes were provided by industrial partners. Particle-size distributions in isopropanol, determined by a laser diffraction analyzer (Mastersizer, Malvern Instrument), were characterized by the d10 , d50 and d90 of the volumetric distribution, as illustrated by the d50 in Table 1. It should be noted that carbon nanotubes seem to form large agglomerates, as confirmed by the transmission electronic microscope analysis (Fig. 3). In fact, TEM observations of carbon nanotubes show particles appearing as large spheres (200–300 m particle size) with embedded nanotubes networks having a diameter ranging between 15 and 20 nm (Fig. 3). The X-ray microanalysis of MWNTs showed that iron is the main residual catalyst. However, MWNTs may contain other impurities reported by Bom [10]
Table 1 Main characteristics of the nanopowders samples. Nanopowders
BET specific surface area (m2 g−1 )
dBET (nm)
d50 (nm) agglomerates
Carbon nanotubes Thermal Black N990 Corax N550 Corax N115 Printex XE2 Aluminium (100 nm) Aluminium (200 nm)
195 9 40 130 950 23 10.5
10 330 75 23 3 100 200
200 000 2000 15 000 23 000 10 000 – –
(MWNTs purity ranges from 92.5% to 97.1%). A total combustion residue of 8% in weight has been measured by thermogravimetry analysis (i.e. an iron content of 5.8%), which confirmed the previously quoted value of Bom [10]. BET specific surface areas and helium pycnometer density have been measured. By coupling the results obtained by BET and helium pycnometer, an average primary grain size can be calculated by considering that particles are isolated, cylindrical (or) spherical with a monodisperse size distribution. For well-dispersed spherical particles the diameter dBET can easily be related to the Sauter diameter. The main particle sizes are reported in the Table 1. From this Table 1, it is seen that the nanopowders considered in this study have a natural tendency to strongly agglomerate with an agglomerate size being several times the primary nanoparticle size. As it will be discussed later, this may have strong impacts on the dispersion propensity of these nanopowders and consequently, on their explosibility. Carbon blacks cover a wide range of specific surface areas, i.e. from 9 to 950 m2 g−1 . Nevertheless, the presence of agglomerates is obvious for this kind of particles. Similar investigations were carried out with three industrial nano-sized aluminium powders (Fig. 3). For these nanometric powders, their surface is covered with an alumina layer representing approximately 20–30% of the particle weight. From MEB and TEM measurements of particle sizes and specific surface area characterizations, it is shown that the carbonaceous powders have a strong propensity to agglomerate or even aggregate. For the case of aluminium powders, the diameters dBET and the Sauter’s diameters d32 are very similar indicating that the degree of agglomeration of aluminium nanoparticles is low. In the following combustion kinetic study, we will consider the dBET diameter for the carbonaceous particles and for the aluminium particles so to capture primary particle size effects and not agglomerate size effects. 2.3. The sample preparation A good reproducibility between the different tests was ensured by systematically drying the samples at 50 ◦ C under vacuum before handling. Particular attention was taken to handle the nanopowders. Nitrile gloves, airflow hood, non-woven coverall and HEPA/ULPA vacuum cleaner have been used in addition to the more classical safety barriers. 2.4. Principle of explosion sensitivity and severity measurements Ignition sensitivity is often referred to as a combination of three parameters characterizing the ability of the particles to be ignited and to generate explosions. These parameters are the following ones: the minimum ignition energy (MIE), the minimum ignition temperature (MIT) and the minimum explosive concentration (MEC) [11,12]. In our study, MIE was determined using a modified Hartmann tube (Kühner AG) in accordance with IEC standard 12412-3. This apparatus also allows the determination of the MEC. MIT in cloud can be tested using a Godbert-Greenwald furnace (Chilworth Technology) (IEC 1241-2-1). The measurements of particle explosion severity, i.e. the maximum Pmax of the maximum overpressure Pm and the maximum rate of pressure rise (dP/dt)max over a wide range of concentration, were performed in a 20 L spherical vessel in accordance with the ASTM method E1226. The experiments were performed with powder concentrations ranging from 15 to 3000 g m−3 and carried out at 23 ◦ C under an atmosphere of 50% relative humidity. It is assumed that the duration of the explosion test is sufficiently small to consider that the sorption equilibrium could not be reached and the sample remains dry.
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Fig. 3. TEM images of the MWNTs carbon nanotubes (a–c) and aluminium nanoparticles (d) at different resolutions.
3. Results and discussion
and 2 [18], which is typical of a shrinking core combustion model under diffusion control [12]. By treating, the whole experimental data related to the combustion of aluminium micro-particles, Beckstead [18] has proposed the following correlation.
3.1. Dependence of the combustion time with the particle size Two main categories of particle sizes should be considered depending on micro- or nano-sized particles. Such distinction comes from the two basic combustion mechanisms (diffusion and kinetic controlled) that are at play. Intuitively, as will be demonstrated in the following paragraph, for micro-sized particles, the combustion is mainly controlled by the oxygen diffusion whereas for nano-sized particles, the combustion is kinetically controlled. The combustion time b can be estimated through the following equation: s
d(dp3 ) dt
=−
6 ˙C m
(1)
where s is the particle density. In order to determine the com˙ C of the particle must be bustion time, the mass combustion rate m determined. This combustion rate depends on the particle diameter dp but also on the temperature T. 3.1.1. Carbonaceous particles combustion time In the case of a diffusion control mechanism (i.e. for the microsized particle range) and for spherical particles, the combustion time b can be expressed as [13]: b =
s dp2 8g DO2 (YO2 ,∞ )/(Mw,O2 /2Mw,C )
(2)
where g is the gas density, DO2 is the diffusivity of oxygen in air and YO2,∞ is the oxygen mass fraction in air, Mw is the molar weight. This is the well-known dp2 law of combustion. In the case of a kinetically controlled mechanism (i.e. for the nanosized particle range), by considering an oxygen reaction order of 1 (in accordance with high temperature kinetics for carbon particles), the combustion time could be expressed as [13]: b =
s dp 2k1 (Ptot Mw,gas /RTs )(Mw,C /Mw,O2 )YO2 ,s
b =
C1 dp1.8 0.2 0.1 T0 P Xeff
(4)
where P is the total pressure (in atm), T0 the initial temperature in K, dp the particle size in m, C1 a constant which value is 7.35 × 10−3 and Xeff the molar fraction of oxygen. In the case of a combustion in dry air, Xeff is set to 0.2. In the case of nanometric particles and for temperatures lower than 1000 ◦ C, Rai determined that the combustion time obeys the following law [19]: b ∝ dp1.6
(5)
This model would indicate a faster reaction with regard to a dp2 expression which could be imparted to a specific effect of the alumina covering layer [18]. These authors explain this behaviour by a facilitated diffusion of aluminium through this layer, probably due to curvature effects. Another study of nanoparticles shows that the combustion time follows another expression [20]: b ∝ dp0.3
(6)
which would indicate even faster reactions. By studying aluminium particle oxidation using a hydrogen–oxygen–argon burner with a flame temperature ranging from 900 and 2400 K and by varying the argon concentration, the same authors proposed the following expression for the combustion times: b
dp0.3 C2 exp(−Ea /RT )Xeff
(7)
(3)
where k1 is the kinetic constant of combustion, Ptot is the air pressure and Ts is the temperature of the particle and YO2 ,s is the oxygen mass fraction at the particle surface. Under these assumptions, the oxygen mass fraction at the particle surface can be approximated by the oxygen mass fraction in air. Several authors have shown indeed that the combustion of micro-sized particles followed a dn law with n ranging between 1.5 and 2 [4,14–16]. Mulcahy [17] studied low-volatile content coal combustion and experimentally observed that the combustion time followed a dp2 law, which is in accordance with (2). Both combustion regimes obtained from experimental data are shown in the Fig. 4. This figure shows the change of combustion times with the particle diameter for various spherical particles. 3.1.2. Aluminium particles combustion time Various authors have shown that the combustion time of large aluminium particles varies in a dn law with n varying between 1.5
Fig. 4. Combustion times of carbon particles as a function of the particle diameter illustrating the existence of two combustion regimes.
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In the case of one particle, by equating the heat generation to the heat loss by convection and radiation, one can write: 4 ˙ C Hcomb = hdp2 (Ts − Tg ) + εdp2 (Ts4 − Twall ) m
(12)
where Hcomb is the combustion enthalpy, g is the gas conductivity, ε is the particle emissivity, is the Stefan–Botzmann’s constant and Twall is the temperature of the heating surface. By replacing h, the coefficient of heat convection, by its expression through the Nusselt number Nu such as: h=
Nu g dp
(13)
The Eq. (12) then becomes: 4 ˙ C Hcomb = Nu g dp (Ts − Tg ) + εdp2 (Ts4 − Twall m )
Fig. 5. Combustion time versus aluminium particle size [21] illustrating the existence of two combustion regimes.
where R is the gas law constant, C2 a constant set to 550, Ea an activation energy set to 73.6 kJ/mol and dp the particle diameter in m. These results were summarized by the different previous authors as shown in Fig. 5. Results of Fig. 5 show here again a different combustion mechanism between the nano- and micro-sized particles that can be understood as the result of two different regimes (a diffusion controlled and a kinetically controlled regimes), as also comforted by Huang et al. [22]. Similarly, we conjecture that there exists a similar combustion behaviour for carbon nanoparticles. For aluminium nanoparticles, oxidation at low temperatures (lower than 1000 ◦ C) is ruled by diffusion mechanisms. It should be stressed that the change of combustion regime is observed above the nanometric size range. These results, largely reviewed [22], lay the premises to perform a reliable study on nanopowder ignition and explosivity behaviours, as shown in the next section. 3.2. Ignition temperature of micro-particles and nanoparticles Ignition of isolated particles in a cloud occurs once the heat generation by reaction Qgenerated exceeds the heat losses Qlost . The oxidation kinetics then self-accelerates, leading to Ignition [23]. By setting an energy balance on a particle and by assuming that no phase change occurs, one can write: ms Cps
dT = Qgenerated − Qlost dt
(8)
where ms is the particle weight and Cps its heat capacity. By deriving (8), this expression can be re-written as follows: d2 T ms Cps 2 = dt
dQgenerated dT
dQlost − dT
Qgenerated − Qlost ms Cps
(9)
One of the conditions of ignition could be written as: d2 T =0 dt 2
(10)
Invoking Eq. (10), one can consider that at the ignition temperature, by setting the right hand side of Eq. (9) to zero, one obtains two conditions that are termed the “Van’t Hoff and Taffanel Le Floch” conditions or [24]:
⎧ ⎨ Qlost = Qgenerated
⎩ dQlost = dQgenerated dT
dT
(11)
(14)
One may assess the ignition temperature Tign by the application of the “Van’t Hoff and Taffanel Le Floch” conditions, assuming an ˙ C such as: Arrhenius’s law for the reaction rate m
E a
˙ 0 exp − ˙ C=m m
RT
(15)
One obtains Eq. (16) for the derivative of heat generated with respect to the temperature: dQgenerated dT
=−
˙C dm Ea ˙ C 2 Hcomb Hcomb = m dT RT
= Nu g dp + 4εdp2 Ts3
(16)
and by invoking Eq. (1), this equation becomes: 2 5 s dp2 Ea Hcomb = 6b Nu g RTign + 24b εdp RTign
(17)
By neglecting the radiation term, the ignition temperature could be expressed as follows:
Tign =
s dp2 Ea Hcomb 6b Nu g R
(18)
Eq. (18) illustrates the following notions: • Tign is lower if the density of the particle is lower, • Tign is higher if Hcomb is larger, • Tign is lower if the activation energy Ea is lower, that is indeed reminiscent of usual reaction kinetics in catalysis. Considering the regime of combustion (diffusional or kinetic), b can be expressed either as dpn , with n respectively ranging from 1.5 to 2 or from 0.3 to 1, yielding the following conclusions: (a) Tign is not always size dependent for large particles (diffusional regimes with n = 2), or there exists a limit with regard to the particle size; (b) Tign decreases when the size of the particle decreases as the particle diameter is in the nano-range. For aluminium particles, the ignition temperature dependency with the particle size is plotted in Fig. 6 [21], illustrating indeed the mains remarks inferred from the model developed in Eq. (18). This figure shows that as the particle size decreases in the nano-range, the ignition temperature decreases. This behaviour is important, because it suggests that inflammation or explosion risks are inherently higher for nanopowders. It could be noted that above few hundred microns, because of sedimentation, particles start settling and are difficult to be dispersed in a cloud of particles. For such cases, the notion of ignition temperature retains little bearing. This is the reason why such curves do not go beyond few hundred microns. Due to their Geldart’s classification, discussed in Section 2.2, the dispersion of such particles may be difficult due to the potential formation of agglomerates. In fact, it should be underlined that Eq. (15) does not take into account the ignition of the whole particle
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Fig. 6. Ignition temperature as a function of the particle size, for aluminium particles [21].
cloud, but only the ignition of an isolated particle. In the presence of agglomerated nanoparticles, as for example for the MWNTs or the carbon blacks studied here, the evolution of the ignition temperature could be strongly modified. Such behaviour could be seen in Fig. 7 where the minimum ignition temperatures of clouds of Printex XE2 and Corax N115 are compared to those of larger carbonaceous particles. In fact, at lower particle sizes, there exist stronger attractive interactions between particles and, as a result, agglomeration/aggregation phenomena occur. This amount of energy should be added during the ignition process in order to oxidize the powders; which could explain the increase of the minimum ignition temperature for very small particles (see Eq. (18)). 3.3. Influence of the particle size on the minimum explosible concentration (MEC) Studies of minimal explosive concentrations resulted in various publications [4] that drew their origin in the first theoretical foundations of Jaeckel’s theory [27]. Based on “Van’t Hoff and Taffanel Le Floch” conditions and by introducing the reaction conversion X, which tends towards 1 for small particles, the minimal explosible concentration may be defined as: MEC XHcomb > (Cpg g + Cps MEC)(Tign − Tu ) + Qlost
(19)
where Cpg and g are the heat capacity and the density of the gas, Tu is the temperature of the unburnt gases. As first approximation, Jaeckel proposed to neglect radiation and convection heat losses in
Fig. 7. Dependence of the minimal ignition temperature of a carbonaceous particle cloud as a function of the particle size [25,26].
his analysis. The minimal explosible concentration may be written as [27]: MEC =
Cpg g (Tinf − Tu ) XHcomb − Cps (Tign − Tu )
(20)
The global trend of the minimum explosible concentration with the particle size could be estimated from the combination of Eqs. (18) and (20). Due to the change of oxidation mechanism, a nano-effect with a slight decrease of the MEC could be expected. Experimentally the nano-ffect of the MEC is not observed as shown in the Fig. 8 in the case of aluminium and in the case of carbon. We clearly see that a plateau exists as the particle size decreases from micrometers to nanometers. This observation supports the behaviour of Eq. (20) at small particle sizes. For aluminium, this plateau (MEC) is at about 30 g m−3 . 3.4. Influence of the particle size on the minimum ignition energy (MIE) The minimum ignition energy can be defined as the energy required for a given cloud of particles to sustain ignition and inflammation in a medium at an initial temperature Tu while the burning medium is at a final temperature Tad , the flame adiabatic temperature [31–33]. Hence, one can write over a spherical volume element
Fig. 8. Experimental measurement of the minimal explosible concentration versus the particle size for aluminium particles (a) [26,28–30] and carbon particles (b) [25,26].
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of diameter Dc : Tad
¯ Dc3 Cp dT = 6
Tu
b (Qgenereted + Qignition − Qlost )dt
(21)
0
where ¯ and Cp are respectively the average density and heat capacity of the volume element. For an initial diameter of particle cloud D0 and a final one Dc , this leads to the following expression of the minimum ignition energy, when Qignition equals the MIE: MIE = g
3 D Cp Tad − u D03 Cp Tu 6 c 6
(22)
By considering the mass conservation, one could write: MIE = ¯ g
3¯ D Cp (Tad − Tu ) = ¯ u D03 C¯ p (Tad − Tu ) 6 c 6
(23)
The gas density at a given temperature is related to the (cold or unburnt) gas density through the ideal gas law, that is, for an ignition in an unconfined vessel: ¯ g PMg RTu Tu = ≈ ¯ u RTad PMu Tad
(24) 3/2
where Mg and Mu are the molar weights for the burnt and unburnt gas. Hence, the minimal ignition energy can be expressed as: MIE ≈
Tu (T − Tu )Dc3 ¯ u C¯ p 6 Tad ad
(25)
Thus, Dc is a critical diameter for which the “Van’t Hoff and Taffanel Le Floch” conditions apply. By assuming that Qgenerated equals Qlost on the spherical volume element (see (21) and (22)) and by neglecting the radiative transfers, one can write the Van’t Hoff condition, which reads: 3 Hcomb ¯ g (Tad − Tu ) D ¯ g = NuDc 6 c b
(26)
where b can be assumed to be the time of combustion (see Section 3.1), which is particle size dependent and depends on the combustion regime considered (diffusional or kinetically controlled). From these two latter expressions (25) and (26), one can express the critical diameter Dc and assess the minimal ignition energy (MIE) as being proportional to a function of b : 3/2
MIE ∝ b
Fig. 9. Dependencies of the MIE versus the particle diameter for both regimes (kinetically controlled at small particle sizes and diffusion controlled at larger sizes) [2,26,28,29,34].
(27)
For the two different combustion regimes, one obtains an MIE which depends on dp3 for kinetically controlled regime (p ∝ dp2 )
or on dp for the diffusion controlled regime ( p ∝ dp ). These two dependencies are shown in Fig. 9. For aluminium particles, the transition between the oxidation regimes occurs on a diameter range from 400 to 2000 nm. No experimental data are available for the carbonaceous particles, their MIE being greater than 1 J, which exceeds the limit of the modified Hartmann tube. 3.5. Influence of the particle diameter on the explosion severity The evolution of maximum pressures Pm , maximum rates of pressure rise (dP/dt)max and time of combustion have been assessed as a function of particle concentration. Fig. 10a shows the influence of particle concentration on Pm for dried carbon blacks while Fig. 11a shows the evolutions of the same parameter for aluminium nanoparticles. Considering that the specific surface of the particle may play a strong role in the rate of pressure rise, the latter is represented versus the former in Figs. 10 and 11b. From all these curves, it is seen that the powder concentration is an important factor that comes to play in the phenomenology of explosion. The maximum explosion pressure for the carbon nanotubes is 6.6 bar, the maximum rate of pressure rise 227 bar s−1 . If the cube-root law is still valid for such particles [36], the resulting explosion index Kst is 62. This powder can be considered as
Fig. 10. (a) Comparison of experimental explosion pressures with best fit curves. (b) Evolution of pressure rises as a function of the specific surface area for carbon blacks [25,26].
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Fig. 11. Comparison of experimental evolution of explosion pressures (a) [26,29,35] and pressure rises (b) with best curve fit as function of powder concentrations for nano-sized aluminium particles [2,11,26,28–30,36,37]. Table 2 Main explosion characteristics of MWNT and aluminium nanopowders. Explosion severity
Pmax (bar g)
dP/dtmax (bar s−1 )
Presumed Kst (bar m s−1 )
Explosivity class St
MWNTs Aluminium (100 nm) Aluminium (200 nm)
6.6 8.2 9.5
227 1340 3480
62 362 673
St1 St3 St3
St1 explosivity class [4]. Such explosions are considered as weak explosions according to this explosivity classification. The explosion severity of carbon blacks (Corax N115, Corax N550, Thermal Black N990 and the Printex XE2) is also close to that of carbon nanotubes (Table 2), i.e. St1 class. Note that the specific surface area of the particles should not be considered as the main factor influencing the particle explosivity, the chemical composition and structure of the compound should also be taken into account. For instance, MWNTs have a rather high specific surface area compared to Corax or Thermal Black but have the lowest explosivity, which is probably due to the size of their agglomerates (approximately 200 m – Table 1). Both aluminium products have the smallest agglomerates sizes, as shown in Table 2. Once again, as for micro-particle ignition, the agglomeration phenomenon has a major influence on particle explosivity. For aluminium particles, we observed that the 200 nm particles explode more violently than the 100 nm particles. This is probably due to the degree of passivation of the aluminium that could be different for these two kinds of particles, and also due to the degree of agglomeration that is probably more important for the 100 nm particles. 4. Conclusions In this paper, we have developed analytical models explaining the dependency of the combustion times with the particle diameter. We were able, with experimental validation, to show that there exists for carbonaceous and metallic materials mainly two combustion regimes that are kinetically controlled for small size (nano) particles and diffusion controlled for large size (micro) particles. From the combustion data of these materials, we were able to describe the dependency of the ignition temperature and the minimal explosive concentration with regard to the particle size. We found that the two combustion regimes yield two different tendencies of safety parameters with respect to the particle size. Overall, it is found that as the particle size decreases, Tinf and
MIE parameters decrease, implying that the use of nanopowders may develop higher potential inflammation and explosion risks. By contrast, the minimal explosion concentration (MEC) did not show strong variations as the particle sizes decreases. Rather, a theoretical plateau is predicted which has been experimentally confirmed. We have measured explosion sensitivity and severity parameters of selected nanopowders using classical characterization tools. We observed that carbon based nanopowders exhibit some propensity to explode while metallic nanopowders can be very reactive, thus delineating potential high explosion risks for facilities manufacturing such powders. For aluminium particles, we underline that these results could well be under estimated due to the existence of some possible passivation oxide layers on aluminium particles and also due to the propensity of these particles to form agglomerates. Such agglomerates could reduce the reactivity of the powders, and therefore their explosion severity. Hence, it is very probable that monodisperse reactive nanoparticles could even detonate in some particular conditions. This result is of considerable importance for this emerging manufacturing industry because it forms the basis to propose new and proper protection means to make these industrial facilities safer. The impacts of agglomeration on explosion severity and sensitivity for nanopowders are still not fully understood and should be further explored in the future. Acknowledgements This study was carried out with the financial support of the European Commission through the Sixth Framework program for Research and Technological Development NMP2-CT-2005515843 contract “NANOSAFE2” and the French Ministry of Ecology, Energy Transport and Sustained Development and the Ministry of Research. We thank Mr. A. Shakesheff from IntrisiqNanomatérials for providing Aluminium nanopowders and Mr. P. Gaillard from Arkema for providing Multiwall Carbon nanotubes used in this study.
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[19] A. Rai, K. Park, L. Zhou, M.R. Zachariah, Understanding the mechanism of aluminium nanoparticle oxidation, Combustion Theory and Modelling 10 (2006) 843. [20] T. Parr, C. Johnson, Evaluation of advanced fuels for underwater propulsion, in: Proceedings of 39th JANNAF Combustion Subcommittee Meeting, 2003. [21] Y. Huang, G. Risha, V. Yang, R. Yetter, Flame propagation in bimodal nano/microsized aluminum particles/air mixtures, in: Collection of Technical Papers—44th AIAA Aerospace Sciences Meeting, 2006, pp. 14015–14025. [22] Y. Huang, G. Risha, V. Yang, R. Yetter, Combustion of bimodal nano/microsized aluminum particle dust in air, Proceedings of the Combustion Institute 31 (2007) 2001–2009. [23] T. Kotoyori, Critical Temperatures for the Thermal Explosion of Chemicals, first ed., Elsevier Science, 2005. [24] R. Essenhigh, M. Misra, D. Shaw, Ignition of coal particles: a review, Combustion and Flame 77 (1989) 3–30. [25] W. Kordylewski, M. Seweryniak, Explosion and flammability properties of furnace carbon blacks, Journal of the Thermodynamics and Combustion Committee of the Polish Academy of Sciences 12 (1992) 153–160. [26] A. Vignes, Evaluation of nanopowders flammability and explosivity: an essential step towards risk assessment (in French). Thèse de doctorat, Institut National Polytechnique de Lorraine, 2008. [27] G. Jaeckel, Die Staubexplosionen, Zeitschrift Für Technische Physik (1924) 67–78. [28] P. Field, Dust Explosions, Amsterdam, Elsevier, 1982. [29] M. Traoré, Dusts and hybrid mixtures explosions (in French). Thèse de doctorat, Institut National Polytechnique de Lorraine, 2007. [30] Combustion and explosion characteristics of dusts, Report. HVBG, Sankt Augustin, Germany, 1997. [31] D. Ballal, A. Lefebvre, Ignition and flame quenching of flowing heterogeneous fuel–air mixtures, Combustion and Flame 35 (1979) 155–168. [32] S. Turns, S.R. Turns, An Introduction to Combustion: Concepts and Applications, second ed., McGraw-Hill Science/Engineering/Math, 2000. [33] F.A. Williams, Combustion Theory, second ed., Westview Press, 1994. [34] V. Babrauskas, Ignition Handbook: Principles and Applications to Fire Safety Engineering, Fire Investigation, Risk Management and Forensic Science, Fire Science Publishers, 2003. [35] O. Dufaud, M. Traoré, L. Perrin, S. Chazelet, D. Thomas, Experimental investigation and modelling of aluminum dusts explosions in the 20 L sphere, Journal of Loss Prevention in the Process Industries 23 (2010) 226–236. [36] W. Bartknecht, Dust Explosions: Course, Prevention, Protection, SpringerVerlag, 1990. [37] M Hull, Tetronics: plasma processing hold key to consistent nanopowders, Powder Metallurgy 45 (2002) 8–9.
Contents lists available at ScienceDirect
Journal of Hazardous Materials journal homepage: www.elsevier.com/locate/jhazmat
Ignition and explosion risks of nanopowders J. Bouillard a,∗ , A. Vignes a , O. Dufaud b , L. Perrin b , D. Thomas b a b
INERIS, Parc Technologique ALATA, B.P. 2, F-60550 Verneuil-en-Halatte, France Laboratoire Réactions et Génie des Procédés, Université de Lorraine, CNRS, 1 rue Grandville, B.P. 20451, F-54001 Nancy, France
a r t i c l e
i n f o
Article history: Received 15 February 2010 Received in revised form 13 April 2010 Accepted 19 May 2010 Available online 26 May 2010 Keywords: Nanopowders Ignition Explosion Carbon nanotube Aluminium Carbon blacks
a b s t r a c t Characterization methods with regard to nanopowder flammability and explosivity are presented and illustrated for few nanopowders. Analytical models are developed in order to explain the dependency of the combustion times on the particle diameter. Experimental evidence shows that there exists, for carbonaceous and metallic materials, mainly two combustion regimes that are either kinetically controlled, for small size particles, or diffusion controlled, for large size particles. From the experimentally measured combustion data of those materials, the dependencies of the ignition temperature and the minimal explosive concentration (MEC) with regard to the particle size have been analyzed. We found that the two combustion regimes yield two different tendencies with respect to the particle size. Overall, it is found that as the particle size decreases, minimum ignition temperature (MIT) and minimum ignition energy (MIE) decrease, indicating higher potential inflammation and explosion risks for the use of nanopowders. By contrast, the minimal explosion concentration (MEC) did not show strong variations as the particle size decreases. Rather, a theoretical plateau is observed, which was experimentally confirmed. We also observed that carbon nanopowders exhibit a low propensity to explode while metallic nanopowders can be very reactive, thus delineating high potentials for explosion risks in manufacturing facilities. © 2010 Elsevier B.V. All rights reserved.
1. Introduction
2. Experimental setups and methods
For any powders set in suspension in air, the ease at which they ignite, burn and propagate varies considerably with important factors that have to be characterized so that one can be able to control their explosion propensity. One of them is obviously the particle size, which takes nanopowders now under higher scrutiny for OH&S issues; others are the particle concentration, the degree of agglomeration, and the degree of turbulence [1–4]. So far, literature studies concerning the evaluation of explosion and flammability hazards of powders were essentially carried out on micro-sized powders [5], albeit there are the recent extensive studies performed by the EU NANOSAFE2 project [6] during the 2005–2009 period and more recently by Wu in Taiwan [7,8] in 2009–2010. This work proposes to review measured explosion safety parameters of few nanoparticles and nanofibers (carbon blacks, aluminium and multiwalled carbon nanotubes) performed in course of the EU NANOSAFE2 project.
2.1. Nanopowders considered from the Geldart’s powder classification perspective
∗ Corresponding author. Tel.: +33 3 44556169; fax: +33 3 44556565. E-mail address: [email protected] (J. Bouillard). 0304-3894/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.jhazmat.2010.05.094
Powders can be characterized by their propensity to fluidize in air. Geldart [9] suggested that uniformly sized powders can be classified into four types characterized by the density difference between the particle s and the fluid g and by their mean particle size (Fig. 1). Nanopowders are therefore of Geldart C (Cohesive) type, so they naturally tend to easily agglomerate. Group C powders are difficult to fluidize because the interparticle forces are greater than those that the fluid exerts on the particles. Such powder characteristics may have an impact on the powder dispersion during flammability and explosivity measurements by traditional apparatuses such as those described in Section 2.4. They also exhibit very low bulk apparent density as it is reported in Fig. 2. This figure shows that, because of the high voidage of the bulk nanopowders, their storage may require larger volumes than those conventionally required for micropowders. A low bulk density of nanopowders may also be indicative of low thermal conductivity, which may lead to higher self-heating and ignition risks when such powders are stored in large containers. Such smoldering fire risks will not be treated in this paper but will be covered in a future one.
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Fig. 1. Four groups (A–D) from Geldart’s classification of powders [9].
Fig. 2. Bulk to specific density ratio of various nanopowders as a function of the particle diameter.
2.2. Particle characterization In this study, aluminium, carbon black and multiwalled carbon nanotubes were provided by industrial partners. Particle-size distributions in isopropanol, determined by a laser diffraction analyzer (Mastersizer, Malvern Instrument), were characterized by the d10 , d50 and d90 of the volumetric distribution, as illustrated by the d50 in Table 1. It should be noted that carbon nanotubes seem to form large agglomerates, as confirmed by the transmission electronic microscope analysis (Fig. 3). In fact, TEM observations of carbon nanotubes show particles appearing as large spheres (200–300 m particle size) with embedded nanotubes networks having a diameter ranging between 15 and 20 nm (Fig. 3). The X-ray microanalysis of MWNTs showed that iron is the main residual catalyst. However, MWNTs may contain other impurities reported by Bom [10]
Table 1 Main characteristics of the nanopowders samples. Nanopowders
BET specific surface area (m2 g−1 )
dBET (nm)
d50 (nm) agglomerates
Carbon nanotubes Thermal Black N990 Corax N550 Corax N115 Printex XE2 Aluminium (100 nm) Aluminium (200 nm)
195 9 40 130 950 23 10.5
10 330 75 23 3 100 200
200 000 2000 15 000 23 000 10 000 – –
(MWNTs purity ranges from 92.5% to 97.1%). A total combustion residue of 8% in weight has been measured by thermogravimetry analysis (i.e. an iron content of 5.8%), which confirmed the previously quoted value of Bom [10]. BET specific surface areas and helium pycnometer density have been measured. By coupling the results obtained by BET and helium pycnometer, an average primary grain size can be calculated by considering that particles are isolated, cylindrical (or) spherical with a monodisperse size distribution. For well-dispersed spherical particles the diameter dBET can easily be related to the Sauter diameter. The main particle sizes are reported in the Table 1. From this Table 1, it is seen that the nanopowders considered in this study have a natural tendency to strongly agglomerate with an agglomerate size being several times the primary nanoparticle size. As it will be discussed later, this may have strong impacts on the dispersion propensity of these nanopowders and consequently, on their explosibility. Carbon blacks cover a wide range of specific surface areas, i.e. from 9 to 950 m2 g−1 . Nevertheless, the presence of agglomerates is obvious for this kind of particles. Similar investigations were carried out with three industrial nano-sized aluminium powders (Fig. 3). For these nanometric powders, their surface is covered with an alumina layer representing approximately 20–30% of the particle weight. From MEB and TEM measurements of particle sizes and specific surface area characterizations, it is shown that the carbonaceous powders have a strong propensity to agglomerate or even aggregate. For the case of aluminium powders, the diameters dBET and the Sauter’s diameters d32 are very similar indicating that the degree of agglomeration of aluminium nanoparticles is low. In the following combustion kinetic study, we will consider the dBET diameter for the carbonaceous particles and for the aluminium particles so to capture primary particle size effects and not agglomerate size effects. 2.3. The sample preparation A good reproducibility between the different tests was ensured by systematically drying the samples at 50 ◦ C under vacuum before handling. Particular attention was taken to handle the nanopowders. Nitrile gloves, airflow hood, non-woven coverall and HEPA/ULPA vacuum cleaner have been used in addition to the more classical safety barriers. 2.4. Principle of explosion sensitivity and severity measurements Ignition sensitivity is often referred to as a combination of three parameters characterizing the ability of the particles to be ignited and to generate explosions. These parameters are the following ones: the minimum ignition energy (MIE), the minimum ignition temperature (MIT) and the minimum explosive concentration (MEC) [11,12]. In our study, MIE was determined using a modified Hartmann tube (Kühner AG) in accordance with IEC standard 12412-3. This apparatus also allows the determination of the MEC. MIT in cloud can be tested using a Godbert-Greenwald furnace (Chilworth Technology) (IEC 1241-2-1). The measurements of particle explosion severity, i.e. the maximum Pmax of the maximum overpressure Pm and the maximum rate of pressure rise (dP/dt)max over a wide range of concentration, were performed in a 20 L spherical vessel in accordance with the ASTM method E1226. The experiments were performed with powder concentrations ranging from 15 to 3000 g m−3 and carried out at 23 ◦ C under an atmosphere of 50% relative humidity. It is assumed that the duration of the explosion test is sufficiently small to consider that the sorption equilibrium could not be reached and the sample remains dry.
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Fig. 3. TEM images of the MWNTs carbon nanotubes (a–c) and aluminium nanoparticles (d) at different resolutions.
3. Results and discussion
and 2 [18], which is typical of a shrinking core combustion model under diffusion control [12]. By treating, the whole experimental data related to the combustion of aluminium micro-particles, Beckstead [18] has proposed the following correlation.
3.1. Dependence of the combustion time with the particle size Two main categories of particle sizes should be considered depending on micro- or nano-sized particles. Such distinction comes from the two basic combustion mechanisms (diffusion and kinetic controlled) that are at play. Intuitively, as will be demonstrated in the following paragraph, for micro-sized particles, the combustion is mainly controlled by the oxygen diffusion whereas for nano-sized particles, the combustion is kinetically controlled. The combustion time b can be estimated through the following equation: s
d(dp3 ) dt
=−
6 ˙C m
(1)
where s is the particle density. In order to determine the com˙ C of the particle must be bustion time, the mass combustion rate m determined. This combustion rate depends on the particle diameter dp but also on the temperature T. 3.1.1. Carbonaceous particles combustion time In the case of a diffusion control mechanism (i.e. for the microsized particle range) and for spherical particles, the combustion time b can be expressed as [13]: b =
s dp2 8g DO2 (YO2 ,∞ )/(Mw,O2 /2Mw,C )
(2)
where g is the gas density, DO2 is the diffusivity of oxygen in air and YO2,∞ is the oxygen mass fraction in air, Mw is the molar weight. This is the well-known dp2 law of combustion. In the case of a kinetically controlled mechanism (i.e. for the nanosized particle range), by considering an oxygen reaction order of 1 (in accordance with high temperature kinetics for carbon particles), the combustion time could be expressed as [13]: b =
s dp 2k1 (Ptot Mw,gas /RTs )(Mw,C /Mw,O2 )YO2 ,s
b =
C1 dp1.8 0.2 0.1 T0 P Xeff
(4)
where P is the total pressure (in atm), T0 the initial temperature in K, dp the particle size in m, C1 a constant which value is 7.35 × 10−3 and Xeff the molar fraction of oxygen. In the case of a combustion in dry air, Xeff is set to 0.2. In the case of nanometric particles and for temperatures lower than 1000 ◦ C, Rai determined that the combustion time obeys the following law [19]: b ∝ dp1.6
(5)
This model would indicate a faster reaction with regard to a dp2 expression which could be imparted to a specific effect of the alumina covering layer [18]. These authors explain this behaviour by a facilitated diffusion of aluminium through this layer, probably due to curvature effects. Another study of nanoparticles shows that the combustion time follows another expression [20]: b ∝ dp0.3
(6)
which would indicate even faster reactions. By studying aluminium particle oxidation using a hydrogen–oxygen–argon burner with a flame temperature ranging from 900 and 2400 K and by varying the argon concentration, the same authors proposed the following expression for the combustion times: b
dp0.3 C2 exp(−Ea /RT )Xeff
(7)
(3)
where k1 is the kinetic constant of combustion, Ptot is the air pressure and Ts is the temperature of the particle and YO2 ,s is the oxygen mass fraction at the particle surface. Under these assumptions, the oxygen mass fraction at the particle surface can be approximated by the oxygen mass fraction in air. Several authors have shown indeed that the combustion of micro-sized particles followed a dn law with n ranging between 1.5 and 2 [4,14–16]. Mulcahy [17] studied low-volatile content coal combustion and experimentally observed that the combustion time followed a dp2 law, which is in accordance with (2). Both combustion regimes obtained from experimental data are shown in the Fig. 4. This figure shows the change of combustion times with the particle diameter for various spherical particles. 3.1.2. Aluminium particles combustion time Various authors have shown that the combustion time of large aluminium particles varies in a dn law with n varying between 1.5
Fig. 4. Combustion times of carbon particles as a function of the particle diameter illustrating the existence of two combustion regimes.
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In the case of one particle, by equating the heat generation to the heat loss by convection and radiation, one can write: 4 ˙ C Hcomb = hdp2 (Ts − Tg ) + εdp2 (Ts4 − Twall ) m
(12)
where Hcomb is the combustion enthalpy, g is the gas conductivity, ε is the particle emissivity, is the Stefan–Botzmann’s constant and Twall is the temperature of the heating surface. By replacing h, the coefficient of heat convection, by its expression through the Nusselt number Nu such as: h=
Nu g dp
(13)
The Eq. (12) then becomes: 4 ˙ C Hcomb = Nu g dp (Ts − Tg ) + εdp2 (Ts4 − Twall m )
Fig. 5. Combustion time versus aluminium particle size [21] illustrating the existence of two combustion regimes.
where R is the gas law constant, C2 a constant set to 550, Ea an activation energy set to 73.6 kJ/mol and dp the particle diameter in m. These results were summarized by the different previous authors as shown in Fig. 5. Results of Fig. 5 show here again a different combustion mechanism between the nano- and micro-sized particles that can be understood as the result of two different regimes (a diffusion controlled and a kinetically controlled regimes), as also comforted by Huang et al. [22]. Similarly, we conjecture that there exists a similar combustion behaviour for carbon nanoparticles. For aluminium nanoparticles, oxidation at low temperatures (lower than 1000 ◦ C) is ruled by diffusion mechanisms. It should be stressed that the change of combustion regime is observed above the nanometric size range. These results, largely reviewed [22], lay the premises to perform a reliable study on nanopowder ignition and explosivity behaviours, as shown in the next section. 3.2. Ignition temperature of micro-particles and nanoparticles Ignition of isolated particles in a cloud occurs once the heat generation by reaction Qgenerated exceeds the heat losses Qlost . The oxidation kinetics then self-accelerates, leading to Ignition [23]. By setting an energy balance on a particle and by assuming that no phase change occurs, one can write: ms Cps
dT = Qgenerated − Qlost dt
(8)
where ms is the particle weight and Cps its heat capacity. By deriving (8), this expression can be re-written as follows: d2 T ms Cps 2 = dt
dQgenerated dT
dQlost − dT
Qgenerated − Qlost ms Cps
(9)
One of the conditions of ignition could be written as: d2 T =0 dt 2
(10)
Invoking Eq. (10), one can consider that at the ignition temperature, by setting the right hand side of Eq. (9) to zero, one obtains two conditions that are termed the “Van’t Hoff and Taffanel Le Floch” conditions or [24]:
⎧ ⎨ Qlost = Qgenerated
⎩ dQlost = dQgenerated dT
dT
(11)
(14)
One may assess the ignition temperature Tign by the application of the “Van’t Hoff and Taffanel Le Floch” conditions, assuming an ˙ C such as: Arrhenius’s law for the reaction rate m
E a
˙ 0 exp − ˙ C=m m
RT
(15)
One obtains Eq. (16) for the derivative of heat generated with respect to the temperature: dQgenerated dT
=−
˙C dm Ea ˙ C 2 Hcomb Hcomb = m dT RT
= Nu g dp + 4εdp2 Ts3
(16)
and by invoking Eq. (1), this equation becomes: 2 5 s dp2 Ea Hcomb = 6b Nu g RTign + 24b εdp RTign
(17)
By neglecting the radiation term, the ignition temperature could be expressed as follows:
Tign =
s dp2 Ea Hcomb 6b Nu g R
(18)
Eq. (18) illustrates the following notions: • Tign is lower if the density of the particle is lower, • Tign is higher if Hcomb is larger, • Tign is lower if the activation energy Ea is lower, that is indeed reminiscent of usual reaction kinetics in catalysis. Considering the regime of combustion (diffusional or kinetic), b can be expressed either as dpn , with n respectively ranging from 1.5 to 2 or from 0.3 to 1, yielding the following conclusions: (a) Tign is not always size dependent for large particles (diffusional regimes with n = 2), or there exists a limit with regard to the particle size; (b) Tign decreases when the size of the particle decreases as the particle diameter is in the nano-range. For aluminium particles, the ignition temperature dependency with the particle size is plotted in Fig. 6 [21], illustrating indeed the mains remarks inferred from the model developed in Eq. (18). This figure shows that as the particle size decreases in the nano-range, the ignition temperature decreases. This behaviour is important, because it suggests that inflammation or explosion risks are inherently higher for nanopowders. It could be noted that above few hundred microns, because of sedimentation, particles start settling and are difficult to be dispersed in a cloud of particles. For such cases, the notion of ignition temperature retains little bearing. This is the reason why such curves do not go beyond few hundred microns. Due to their Geldart’s classification, discussed in Section 2.2, the dispersion of such particles may be difficult due to the potential formation of agglomerates. In fact, it should be underlined that Eq. (15) does not take into account the ignition of the whole particle
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Fig. 6. Ignition temperature as a function of the particle size, for aluminium particles [21].
cloud, but only the ignition of an isolated particle. In the presence of agglomerated nanoparticles, as for example for the MWNTs or the carbon blacks studied here, the evolution of the ignition temperature could be strongly modified. Such behaviour could be seen in Fig. 7 where the minimum ignition temperatures of clouds of Printex XE2 and Corax N115 are compared to those of larger carbonaceous particles. In fact, at lower particle sizes, there exist stronger attractive interactions between particles and, as a result, agglomeration/aggregation phenomena occur. This amount of energy should be added during the ignition process in order to oxidize the powders; which could explain the increase of the minimum ignition temperature for very small particles (see Eq. (18)). 3.3. Influence of the particle size on the minimum explosible concentration (MEC) Studies of minimal explosive concentrations resulted in various publications [4] that drew their origin in the first theoretical foundations of Jaeckel’s theory [27]. Based on “Van’t Hoff and Taffanel Le Floch” conditions and by introducing the reaction conversion X, which tends towards 1 for small particles, the minimal explosible concentration may be defined as: MEC XHcomb > (Cpg g + Cps MEC)(Tign − Tu ) + Qlost
(19)
where Cpg and g are the heat capacity and the density of the gas, Tu is the temperature of the unburnt gases. As first approximation, Jaeckel proposed to neglect radiation and convection heat losses in
Fig. 7. Dependence of the minimal ignition temperature of a carbonaceous particle cloud as a function of the particle size [25,26].
his analysis. The minimal explosible concentration may be written as [27]: MEC =
Cpg g (Tinf − Tu ) XHcomb − Cps (Tign − Tu )
(20)
The global trend of the minimum explosible concentration with the particle size could be estimated from the combination of Eqs. (18) and (20). Due to the change of oxidation mechanism, a nano-effect with a slight decrease of the MEC could be expected. Experimentally the nano-ffect of the MEC is not observed as shown in the Fig. 8 in the case of aluminium and in the case of carbon. We clearly see that a plateau exists as the particle size decreases from micrometers to nanometers. This observation supports the behaviour of Eq. (20) at small particle sizes. For aluminium, this plateau (MEC) is at about 30 g m−3 . 3.4. Influence of the particle size on the minimum ignition energy (MIE) The minimum ignition energy can be defined as the energy required for a given cloud of particles to sustain ignition and inflammation in a medium at an initial temperature Tu while the burning medium is at a final temperature Tad , the flame adiabatic temperature [31–33]. Hence, one can write over a spherical volume element
Fig. 8. Experimental measurement of the minimal explosible concentration versus the particle size for aluminium particles (a) [26,28–30] and carbon particles (b) [25,26].
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of diameter Dc : Tad
¯ Dc3 Cp dT = 6
Tu
b (Qgenereted + Qignition − Qlost )dt
(21)
0
where ¯ and Cp are respectively the average density and heat capacity of the volume element. For an initial diameter of particle cloud D0 and a final one Dc , this leads to the following expression of the minimum ignition energy, when Qignition equals the MIE: MIE = g
3 D Cp Tad − u D03 Cp Tu 6 c 6
(22)
By considering the mass conservation, one could write: MIE = ¯ g
3¯ D Cp (Tad − Tu ) = ¯ u D03 C¯ p (Tad − Tu ) 6 c 6
(23)
The gas density at a given temperature is related to the (cold or unburnt) gas density through the ideal gas law, that is, for an ignition in an unconfined vessel: ¯ g PMg RTu Tu = ≈ ¯ u RTad PMu Tad
(24) 3/2
where Mg and Mu are the molar weights for the burnt and unburnt gas. Hence, the minimal ignition energy can be expressed as: MIE ≈
Tu (T − Tu )Dc3 ¯ u C¯ p 6 Tad ad
(25)
Thus, Dc is a critical diameter for which the “Van’t Hoff and Taffanel Le Floch” conditions apply. By assuming that Qgenerated equals Qlost on the spherical volume element (see (21) and (22)) and by neglecting the radiative transfers, one can write the Van’t Hoff condition, which reads: 3 Hcomb ¯ g (Tad − Tu ) D ¯ g = NuDc 6 c b
(26)
where b can be assumed to be the time of combustion (see Section 3.1), which is particle size dependent and depends on the combustion regime considered (diffusional or kinetically controlled). From these two latter expressions (25) and (26), one can express the critical diameter Dc and assess the minimal ignition energy (MIE) as being proportional to a function of b : 3/2
MIE ∝ b
Fig. 9. Dependencies of the MIE versus the particle diameter for both regimes (kinetically controlled at small particle sizes and diffusion controlled at larger sizes) [2,26,28,29,34].
(27)
For the two different combustion regimes, one obtains an MIE which depends on dp3 for kinetically controlled regime (p ∝ dp2 )
or on dp for the diffusion controlled regime ( p ∝ dp ). These two dependencies are shown in Fig. 9. For aluminium particles, the transition between the oxidation regimes occurs on a diameter range from 400 to 2000 nm. No experimental data are available for the carbonaceous particles, their MIE being greater than 1 J, which exceeds the limit of the modified Hartmann tube. 3.5. Influence of the particle diameter on the explosion severity The evolution of maximum pressures Pm , maximum rates of pressure rise (dP/dt)max and time of combustion have been assessed as a function of particle concentration. Fig. 10a shows the influence of particle concentration on Pm for dried carbon blacks while Fig. 11a shows the evolutions of the same parameter for aluminium nanoparticles. Considering that the specific surface of the particle may play a strong role in the rate of pressure rise, the latter is represented versus the former in Figs. 10 and 11b. From all these curves, it is seen that the powder concentration is an important factor that comes to play in the phenomenology of explosion. The maximum explosion pressure for the carbon nanotubes is 6.6 bar, the maximum rate of pressure rise 227 bar s−1 . If the cube-root law is still valid for such particles [36], the resulting explosion index Kst is 62. This powder can be considered as
Fig. 10. (a) Comparison of experimental explosion pressures with best fit curves. (b) Evolution of pressure rises as a function of the specific surface area for carbon blacks [25,26].
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Fig. 11. Comparison of experimental evolution of explosion pressures (a) [26,29,35] and pressure rises (b) with best curve fit as function of powder concentrations for nano-sized aluminium particles [2,11,26,28–30,36,37]. Table 2 Main explosion characteristics of MWNT and aluminium nanopowders. Explosion severity
Pmax (bar g)
dP/dtmax (bar s−1 )
Presumed Kst (bar m s−1 )
Explosivity class St
MWNTs Aluminium (100 nm) Aluminium (200 nm)
6.6 8.2 9.5
227 1340 3480
62 362 673
St1 St3 St3
St1 explosivity class [4]. Such explosions are considered as weak explosions according to this explosivity classification. The explosion severity of carbon blacks (Corax N115, Corax N550, Thermal Black N990 and the Printex XE2) is also close to that of carbon nanotubes (Table 2), i.e. St1 class. Note that the specific surface area of the particles should not be considered as the main factor influencing the particle explosivity, the chemical composition and structure of the compound should also be taken into account. For instance, MWNTs have a rather high specific surface area compared to Corax or Thermal Black but have the lowest explosivity, which is probably due to the size of their agglomerates (approximately 200 m – Table 1). Both aluminium products have the smallest agglomerates sizes, as shown in Table 2. Once again, as for micro-particle ignition, the agglomeration phenomenon has a major influence on particle explosivity. For aluminium particles, we observed that the 200 nm particles explode more violently than the 100 nm particles. This is probably due to the degree of passivation of the aluminium that could be different for these two kinds of particles, and also due to the degree of agglomeration that is probably more important for the 100 nm particles. 4. Conclusions In this paper, we have developed analytical models explaining the dependency of the combustion times with the particle diameter. We were able, with experimental validation, to show that there exists for carbonaceous and metallic materials mainly two combustion regimes that are kinetically controlled for small size (nano) particles and diffusion controlled for large size (micro) particles. From the combustion data of these materials, we were able to describe the dependency of the ignition temperature and the minimal explosive concentration with regard to the particle size. We found that the two combustion regimes yield two different tendencies of safety parameters with respect to the particle size. Overall, it is found that as the particle size decreases, Tinf and
MIE parameters decrease, implying that the use of nanopowders may develop higher potential inflammation and explosion risks. By contrast, the minimal explosion concentration (MEC) did not show strong variations as the particle sizes decreases. Rather, a theoretical plateau is predicted which has been experimentally confirmed. We have measured explosion sensitivity and severity parameters of selected nanopowders using classical characterization tools. We observed that carbon based nanopowders exhibit some propensity to explode while metallic nanopowders can be very reactive, thus delineating potential high explosion risks for facilities manufacturing such powders. For aluminium particles, we underline that these results could well be under estimated due to the existence of some possible passivation oxide layers on aluminium particles and also due to the propensity of these particles to form agglomerates. Such agglomerates could reduce the reactivity of the powders, and therefore their explosion severity. Hence, it is very probable that monodisperse reactive nanoparticles could even detonate in some particular conditions. This result is of considerable importance for this emerging manufacturing industry because it forms the basis to propose new and proper protection means to make these industrial facilities safer. The impacts of agglomeration on explosion severity and sensitivity for nanopowders are still not fully understood and should be further explored in the future. Acknowledgements This study was carried out with the financial support of the European Commission through the Sixth Framework program for Research and Technological Development NMP2-CT-2005515843 contract “NANOSAFE2” and the French Ministry of Ecology, Energy Transport and Sustained Development and the Ministry of Research. We thank Mr. A. Shakesheff from IntrisiqNanomatérials for providing Aluminium nanopowders and Mr. P. Gaillard from Arkema for providing Multiwall Carbon nanotubes used in this study.
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