Flame Synthesis of Valuable Nanoparticles: Recent Progress

Xing, Y.; Koylu, U. O.; Rosner, D. E.; Tandon, P. Morphological Evolution of Nano-Particles in Laminar Counterflow Diffusion FlamesMeasuring and Model...
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Ind. Eng. Chem. Res. 2005, 44, 6045-6055

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Flame Synthesis of Valuable Nanoparticles: Recent Progress/ Current Needs in Areas of Rate Laws, Population Dynamics, and Characterization Daniel E. Rosner† High-Temperature Chemical Reaction Engineering Laboratory and Center for Combustion Studies, Department of Chemical Engineering, Yale University, New Haven, Connecticut 06520-8286

We outline the rationale for using combustion techniques to economically synthesize valuable nanopowders, including mixed oxides, non-oxides, fullerenes, and nanotubes. Here “combustion” includes many exothermic reactive systems in which the “fuel” is not a hydrocarbon and the oxidizer is not O2(g), as has also become the norm in the fields of chemical rockets and chemical lasers. Recent theoretical and experimental research studies have clarified many of the fundamental physical issues (e.g., Brownian coagulation, surface-energy-driven sintering, thermophoretic transport, etc.) necessary for the design of larger scale aerosol synthesis reactors and the harvesting/controlled deposition of particles. However, the prediction of “chemical nucleation rates” remains especially elusive. Specifically, even when the chemistry of precursor pyrolysis, oxidation, or hydrolysis is established, there remains the fundamental issue of how stable embryonic particles are actually formed and grow; i.e., what is the nanoparticle “birth rate” and how “large” are the “babies”? More generally, a multivariate description of the nanoaerosol population is required, and we outline recent advances in the simulation of such multivariate populations using systematic moment methods that are sufficiently general and articulate well with a computational fluid dynamics approach to the overall aerosol reactor design/ optimization/control. Of course, the control of flame-synthesized nanoparticle reactors will also require online, real-time probe measurements, often in “hostile” (high temperature, corrosive, etc.) environments. Extending the possibilities inherent in time-resolved laser-induced incandescence (TR-LII) is one of several attractive options, and we conclude with a summary of some recent relevant work/trends/prospects. 1. Introduction: Why (Not) “Flame Synthesis”? Our premise1 is that the combustion synthesis of nanoparticles (using gaseous, liquid, or even solid fuels) would have significant economic advantages over its many rivals, especially if current research continues to provide improved design methods enabling the controlled production of nanoparticles with prespecified “target” properties. This is partly due to the facts that (i) the heat of combustion is available to economically activate precursor pyrolysis, hydrolysis, and/or oxidation or vaporize nanoparticle precursor-containing droplets, (ii) there are many useful control variables [including flame temperature (via diluents), flame structure, stoichiometry, pressure level, RTD, turbulence, concentration of nanoparticle precursor, location of precursor injection, location of particle quenching/extraction, supplementary laser irradiation, external electric fields, etc.], (iii) particle production occurs under essentially “containerless” conditions, (iv) higher purity and temperatures allow better control over crystal state/morphology, (v) flame synthesis/processing can often accomplish in a single step what takes multiple processing steps for wet-chemical methods, (vi) solvent-free processing leads to a smaller environmental “footprint”, and, perhaps most decisive, (vii) such methods are intrinsically “scalable”, i.e., capable of high, continuous production rates. At the outset, it should be said that for some important applications (e.g., large-scale production of titania †

E-mail: [email protected].

(white) pigment and “fumed” silica additive)2,3 hydrocarbon-driven flame processes have already become dominant. Thus, we are discussing here new developments that place greater emphasis on small spherule size (here below 100-nm diameter), reduced aggregation (or aggregate strength; section 5.2), and improved control of spherule properties (electrical, magnetic, optical, and surface chemistry). As emphasized below, to exploit the intrinsic versatility of “flame” reactors to produce valuable nanoparticles other than metal- and semimetal oxides (e.g., sub-100-nm-diameter metals, semimetals, nitrides, carbides, borides, etc.), much greater attention will have to be paid to the use of unconventional “fuels” (non-H/C/O) and unconventional oxidizers. In other words, we must adopt a rather broad interpretation of the word “combustion” (in the spirit of the young Michael Faraday and the more recent pioneers of “chemical rockets” and “chemical lasers”). The following interesting example may help to immediately fix ideas on this point. Consider, say, a steady “spray” combustor in which Na/K(l) microdroplets are formed and continuously injected into in a stream of TiCl4(g) and BCl3(g). Such a “spray flame burner” would continuously produce TiB2(s) nanoparticles, perhaps encapsulated by NaCl/KCl(s).4 After surveying some recent examples of the flame synthesis of various types of nanoparticles (section 2), we turn to fundamental rate processes and simulation methods (sections 3 and 4) and then to a class of laserbased diagnostic methods (section 5) which promise to

10.1021/ie0492092 CCC: $30.25 © 2005 American Chemical Society Published on Web 07/02/2005

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Figure 1. Types of gaseous fuel combustors used for laboratory studies of nanoparticle synthesis: (a) premixed flat flame burner (inverted); (b) counterflow diffusion flame burner (slot type); (c) multiannulus coflow diffusion flame burner. Table 1. Some Examples of Nanoparticle Flame Synthesis: Oxidesa

provide supplementary data to (a) guide the development of improved simulation methods and (b) enable feedback control of future nanoparticle-producing reactors.5 Section 6 concludes this brief overview with comments on current trends and research needs.6 Each of the notions that flame reactors (a) are “too dangerous”, (b) are “too complex (thermal and velocity fields) to analyze”, (c) inevitably will lead to polydispersed, partially sintered agglomerates, and (d) cannot be used to synthesize anything but oxide-ceramic nanoparticles, is contradicted by the (counter)examples assembled here and in ref 1. For the same reason that a chemical engineer confronted with a separation task will frequently start by asking “why not distillation?”, for nanoparticle synthesis, we are approaching a situation in which this writer would suggest starting with the question, “Why not a ‘flame’ (combustion) synthesis process?” 2. Overview of Research Studies of Flame-Synthesized Nanoparticles Burner Types. Most laboratory studies of flamesynthesized nanoparticles reported in the past decade

or so have been carried out in one of the three basic types of burners depicted in Figure 1a-c. In some sense, these are all “locally containerless” flow reactors in that heated sidewalls are not physically present in the particle inception regions of these flames. Useful summaries of such studies prior to about 1997 are contained in the comprehensive reviews of Pratsinis (1998)3 and Wooldridge (1998).7 Even more recent relevant reviews are those of Kammler et al. (2001)8 and Stark and Pratsinis (2002).9 Figure 1 and Tables 1 and 2 give merely an instructive “sampling” of relevant laboratory studies, many in the last 5 years. No claim of “completeness” is made, and the literature should be consulted for many interesting examples not discussed explicitly here. Our restricted goal here is “merely” to provide some valuable perspective on an already large and still rapidly growing field. [In this respect, it is surprising that “flame” synthesis techniques are inexplicably absent from the otherwise useful monograph (on “superfine particle technology”) of Ichinose et al.10 To this writer, this is equivalent to “ignoring the presence of an adult elephant in a small room”!]. For recent surveys of the

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broader field of “aerosol” routes to nanoparticles, see work by Kodas and Hampden-Smith11 and Harfenist.12 Panel a shows a “premixed” fuel/oxidizer (F/O) system,13,14 whereas panels b and c depict “non-premixed”, or so-called “diffusion” flame systems: one class “opposed” (or counter) flow,15-18 and one class (panel c) “coflow”.19 If the feed ducts are cylindrical, these systems produce axisymmetric flames, often under laminar flow conditions. However, near the axis, the mathematical modeling of types 1a and 1b is simpler than that of type 1c because of the possibility of a similarity transformation, which allows the governing balance equations (in r and z) to be written as a system of elliptic ODEs in the axial variable20 z. Each of these burner types allows considerable flexibility with regard to the choice of reagents (F, O, and precursor) and excellent access for probing (optical and/or immersion). Figure 1a depicts a premixed gaseous fuel/oxidizer burner used for oxide powder synthesis under subatmospheric pressure conditions (typically13 ca. 20 Torr ) 2.7 kPa). Here the gas flow is from top to bottom, and the gaseous fuel (presently H2) and oxidizer (O2) mixture is passed over a vaporizing, temperature-controlled inventory of liquid precursor [here Al(CH3)3, abbreviated TMA(l)] before entering the “flat” flame stabilized between the burner and downstream cooled solid substrate. A microparticulate film on the temperaturecontrolled substrate may, indeed, be the (optical film, chemical sensor, etc.) “product” of interest.21 Figure 1b depicts a class of opposed laminar jet “slot” (not axisymmetric) burners developed by Chung and Katz22 and later adapted/used by Xing et al.15-17 for atmospheric pressure studies of oxide nanoparticle synthesis (see the first row of Table 1 and section 3). Here the particle precursor vapor(s) (PV; Tables 1 and 2) is continuously added either to the gaseous fuel stream or to the gaseous oxidizer stream, either of which must be maintained above the prevailing “dew-point” temperature of the precursor/carrier stream being used. Figure 1c depicts a class of axisymmetric coflow diffusion flame burners.19,23-26 Coaxial, multiannulus configurations are commonly used so that the gaseous fuel and oxidizer streams can be separated from the stream that contains the particle precursor. This additional flexibility is exploited to control the location of particle inception and, among other things, control the problem of particle buildup on portions of the burner “lip”. Much of this technology is derived from the successful use of such burners in the generation of doped

silica microdroplets used to deposit/pull commercial optical waveguide fiber.27 Generally speaking, non-premixed systems are safer to work with (free of the problem of “flashback”) and exhibit broader operating ranges (flow rate and mixture ratio) for stable combustion (see, e.g., ref 28, Chapter 7]. Both types of systems ordinarily require an ignition source (not shown) to initiate steady combustion, although several F/O systems exhibit the property of “autoignition” upon molecular mixing even near 300 K and 1 atm of pressure. Combustion reaction zones are typically thin (measured in millimeters) at atmospheric pressure. Indeed, one of the incentives to go to the added expense of operating at subatmospheric pressure is often to “expand” the reaction zone, facilitating probing of the flame structure.13,29,30 Not explicitly shown in Figure 1 are a wide variety of so-called “spray” burners, in which the fuel is injected in the form of a fine spray of liquid droplets, perhaps including a dissolved nanoparticle precursor (“reactive spray pyrolysis”, RSP)31,32 or even a fume of finely divided (e.g., metal) powder. Another variant involving precursors (often several salts simultaneously) dissolved in droplets are so-called “spray pyrolysis” (SP) systems,33,34 in which the precursor solvent (e.g., water or an alcohol) is NOT necessarily a fuel, with the droplets being introduced into a “pre-existing” gaseous flame (either “diffusion” or “premixed”; see, e.g., ref 35). While there may be strong economic incentives to use such salt-spray systems (e.g., in place of a more expensive metal-organic vapor precursor), in many such cases the resulting complexities of metal-atom release will be reflected in more complex downstream particle morphologies (see, e.g., the chromium oxide studies of Kennedy et al.36). Flame-Synthesized Oxides. Table 1 summarizes some examples of oxide nanoparticle flame synthesis studies over the last 10-12 years. The first group deals with important single oxides (e.g., Al2O3,15-17 SiO2,37 TiO2, or SnO2)23,25,38 but also included in Table 1 are “mixed oxide” studies, including GeO2 + SiO2,39,40 BaTiO3,41 Y-stabilized ZrO2,35,42,43 SnO2/TiO2,44 and superconducting oxides.45 Note that all of these particular “oxide” examples were carried out using atmospheric pressure O2-containing diffusion flames under laminar flow conditions (for a recent premixed flame example, see work by Zhao et al.14). However, also note the variety of flow configurations (coflow vs opposed flow), precursor types, and fuel types utilized. Not included in Table 1

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(or Table 2) is essential information about the particle size (distribution), particle morphology (shape, state of aggregation, encapsulation?), or phase “selection” (amorphous?, crystal structures?). The interested reader is directed to the original papers for this essential information, some of which is discussed further below. Flame-Synthesized “Non-Oxides”. Table 2 provides several examples of non-oxide nanoparticle “flame” synthesis studies, including metals,46 nitrides,4 borides,47 fullerenes (C60 and C70),48,49 and C nanotubes.50 With the exception of the fullerene example,48,49 these are laminar atmospheric pressure flame studies, but again we note the variety of “fuels”, oxidizers, and precursors employed. In the case of nanotube (nT) synthesis, inorganic nanoparticle or filament catalysts are evidently necessary; such particles can be provided in situ by cointroducing a suitable catalyst nanoparticle precursor, e.g., an Fe- or Ni-containing metal-organic vapor,51 or the carbon nanotube growth can take place on a suitable catalyst solid screen or filaments introduced into the gaseous mixture.50,52,53 Nanostructured “composites” comprised of both carbon and TiO2 spherules have also been synthesized.54 Flame-Synthesized Metal (on Metal-Oxide Support) Catalysts. Supported metal catalysts, which are demonstrably active for oxidation reactions [such as SO2(g) oxidation in the synthesis of H2SO4], can now be flame-synthesized in “one step” by suitably coseeding and quenching premixed CH4/air flames (see, e.g., Johannessen and Koutsopoulos,24 who produced “composite” particles consisting of Pt nanocrystals supported on TiO2 aggregates, with an active specific surface area on the order of 100 m2/g). For recent reviews of flame reactors for the manufacture of catalytically active nanoparticles, see Kammler et al.8 and Stark and Pratsinis.9 3. Some Fundamental Issues for Flame-Synthesized Nanoparticles In most of the above-mentioned research examples, the flame chemistry (e.g., methane/O2 or H2/O2 combustion) was deliberately uncoupled from the slower processes associated with nanoparticle nucleation [from the products of a “dilute” nanoparticle precursor (“seed” compound) decomposition or hydrolysis], nanoparticle growth, coagulation, and sintering. Of course, for many systems of current and future interest, this “uncoupling” will break down, complicating both measurements and their interpretation (see section 6). Yet, by exploiting weak coupling approximations, essential progress has been made on many, if not all, of the rate processes needed to predict the nanoparticle synthesis reactor performance, especially in the areas (discussed briefly below) of Brownian coagulation of morphologically complex particles, surface-energy-driven sintering, aggregate thermophoresis, and population dynamics in the simultaneous presence of these phenomena. 3.1. Precursor Kinetics (Pyrolysis, Oxidation, and Hydrolysis). The treatment of homogeneous precursor decomposition (“pyrolysis”) kinetics, oxidation kinetics, and/or hydrolysis kinetics is beyond the scope of our present discussion. For important developments in the measurement of such chemical rates, the a priori prediction of such rate constants, and the development of “reduced” reaction mechanisms, see, e.g., refs 11, 55, and 56-59 and relevant papers in the most recent International Combustion Symposia (loc. cit.).

3.2. “Chemical Nucleation”. While unacceptable uncertainties remain in some of the above-mentioned areas (see below), the most serious gaps exist in actually predicting the local nanoparticle “birth rates” (i.e., “chemical nucleation” rates). This is because particle nucleation in flame reactors usually occurs under conditions of local supersaturation for which classical nucleation rate theory (with recent refinements, see, e.g., work by Kashiev60) fails (i.e., the formally predicted critical size nucleus is of submolecular dimensions!). Unfortunately, even for single-component, uncharged quasi-spherical molecular systems under ideal vapor conditions, simple limiting-case predictions (based on calculating the rate of formation and subsequent coagulation of some hypothetical “monomer”) often overpredict the homogeneous nucleation rate and ultimately overpredict the dispersity of the particle population formed by “coagulation-coalescence”.61 For these reasons, the mechanism and rate of “chemical nucleation” at very high supersaturations will have to be clarified,62 with new/general results that can hopefully be cast in a form compatible with the requirements of an aerosol dynamic equation-based reactor simulation scheme (see section 4 and ref 6). Whether this can be accomplished for the case of multivariate aerosol populations evolving under even laminar flame conditions remains an open question. In any case, while we were not able to spatially resolve the submillimeter particle nucleation zone in our 1 atm laminar counterflow diffusion flame studies, we were able to measure what emerges from this (presently) “black box”. 3.3. “Chemical Growth” Laws. A closely related complication is that nanoparticle growth by vapor “scavenging” in chemical reactors is often the result of heterogeneous chemical reactions (i.e., CVD) rather than “physical condensation”. For example, although its kinetics have never been measured on nanoparticle surfaces, the overall CVD reaction on TiO2 surface

TiCl4(g) + O2(g) 98 TiO2(s) + 2Cl2(g) (1a) evidently influences the performance of titania pigment aerosol reactors,38 especially at high particle volume fractions and intermediate TiO2 particle diameters. Such CVD reactions may also result in local “etching” situations, i.e., “negative growth”. An example is the likely (overall) oxidation reaction

Cr2O3(s) + 3/2O2(g) f 2CrO3(g)

(1b)

which evidently causes the disappearance of crystalline Cr2O3 particles immediately downstream of Cr(CO)6seeded H2/air diffusion flames.63 Usable kinetic descriptions relevant to such particle “growth” (() by CVD will be needed for a wide variety of chemical systems leading to “precipitate” (particulate) products.6 3.4. Simultaneous Coagulation, Sintering, and Thermophoretic Transport. Our own research has focused on the issues of particle growth by Brownian coagulation, followed by finite rate coalescence in the highly nonisothermal but well-defined environment of a laminar counterflow diffusion flame reactor.15-17,61 Best understood64 at this point are the consequences of thermophoretic transport, which are highlighted by examining measured versus predicted profiles of the local nanoparticle volume fraction, φ(z) [)M1,0(z); see eq

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Figure 2. Measured and predicted particle volume fraction distribution, φ(z), in a laminar counterflow diffusion flame of CH4(g)/O2(g) seeded with Al(CH3)3 ()TMA) on the fuel side.61

2, section 4]. This is because the rate processes of coagulation and sintering exert only a small effect on the readily measured total particle volume fraction φ(z) [indirectly through the weak dependence of thermophoresis on the particle morphology/size in the freemolecule (Kn . 1) limit].64,68-70 The effects of axial thermophoresis are most readily seen in the immediate vicinity of the flame zone, where φ virtually undergoes a (negative) “jump” (see Figure 2 and refs 61 and 71). Very early in the lifetime of a nanoparticle population, Brownian coagulation rates even at preflame temperatures are probably systematically smaller than those predicted from simple free-molecule (kinetic theory) collision rates with the assumption of a unity “sticking coefficient”.72 When typical particle diameters grow beyond several nanometers, however, the s ) 1 freemolecule approach is probably adequate, especially because rapid coalescence is able to restore the quasispherical geometry before the next nanoparticle encounter. However, coalescence rates are notoriously sizedependent73 (especially for the surface-diffusion masstransfer mechanism18) so that in any given environment, beyond some “threshold” size, partially coalesced shapes, and ultimately fractal-like aggregates (FAs) comprised of many identifiable “primary” particles, should be observed. [Incidentally, the widely used word “primary” here is troublesome and not recommended. This is because the spherules ultimately observed are often the result of many generations of “collision-coalescence events”.] If this mechanism- and environment-dependent threshold size could be predicted, one could predict the spherule size expected in aggregated nanoparticle populations and, hence, the often decisive specific surface area of the aerosol product. On the basis of a preliminary set of measurements and relevant calculations, as well as an assessment of the spherule size data reported by others, we concluded that nanoparticle coalescence by the mechanism of surface diffusion is likely to occur more rapidly than expected for their size

because of anomalously rapid migration across their highly curved (mainly convex) surfaces.18 Nevertheless, alumina powders have been produced with over 100 m2/g in these laminar opposed-flow diffusion flames. For different reasons, coagulation and coalescence rates of the “large” FAs observed approaching our thin CH4/O2 diffusion flames are difficult to predict accurately. While qualitative trends were correctly predicted using a bivariate description of the local aerosol population (section 4), “normalizing” spherule sizes based on TPS/TEM measurements made immediately downstream of the particle inception plane,61 absolute coagulation rates, and inferred activation energies for the sintering process reveal the need for further improvement in these underlying FA rate laws. For many applications, extensive “aggregation” must be avoided, especially those requiring the formation of “dense” granular deposits prior to rapid postprocessing (e.g., to make dense ceramics for structural or optical purposes). However, for some applications, “aggregation” is actually desired or, even if not desired, need not be prevented in high-productivity flame reactors, so long as interspherule bonds in nanoparticle aggregates are not permitted to grow too strong to permit facile subsequent breakup (e.g., by impaction, or hydrodynamic shear when resuspended in a liquid carrier). This strategy underlies our current research (section 5) on new laser-based diagnostic methods, not only to size nanoparticles “online” but also to characterize their mean interspherule binding energy. 4. Multivariate Population Balance (PB) Simulation Methods Progress continues to be made in the areas of multivariate PB simulation methods,61,74-76 along with the rate laws/transport properties that appear in these (integro-PD) equations. It has become clear that any viable PBE simulation method must have the following attributes:76 (A1) free of overly restrictive constraints on JPDF shape, (A2) free of arbitrary restrictions on the functional form of the operative single-particle (or aggregate) rate laws, (A3) amenable to the use of more than one particle “state” variable, (A4) capable of dealing with particle state-dependent diffusion in physical space, and (A5) compatible with current/future multidimensional “elliptic” Eulerian CFD codes. Updating ref 76, we summarize here our most recent experience with promising Gaussian “quadrature-based” moment methods (QMOM) for bivariate problems61,78 and enhancements thereof [principal component analysis79 (PCA), the Jacobian matrix transformation (JMT) of McGraw and Wright;75 applied by Zurita-Gotor and Rosner69] and the closely related “direct” QMOM, in which the PDF weights and abscissae are treated as “pseudospecies” in the Eulerian PDEs expressing local conservation.80 These techniques will be seen to systematically extend QMOM into the multivariate/multifluid Eulerian domain,76 which embraces many problems of current/future technological interest. The accuracy of our QMOM calculations is being tested by comparing selected results (e.g., absence of ongoing nucleation, growth (from the vapor), and negligible Brownian diffusion in physical space) against the corresponding results of Monte Carlo simulations, e.g., for “canonical” bivariate cases.74,81 However, because of attributes A4 and A5, we anticipate that QMOM simulation techniques will be better suited to the

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requirements of reactor modeling/control applications than MC methods82,83 or so-called “sectional” methods.76,84 For recent (but unfortunately not complete) overviews of PBE research activity, the reader should also consult Hounslow85 and Ramkrishna.86 In ref 61, we adopted nanoparticle volume v and nanoparticle surface area a as the basic particle state variables (i.e., the Koch-Friedlander87 choice) and showed that it was possible to represent our bivariate population of alumina nanoparticles by tracking the spatial distribution (z dependence) of nine selected “moments” of the local bivariate number density distribution function n(v,a;z) defined by

Mkl(z) ≡

∫∫vkaln(v,a;z) dv da

(k ) 0, 1, 2; l ) 3/3, 4/3, 5/3) (2)

where both indicated integrals are from 0 to ∞. In the present case, these nine “mixed” moments satisfied coupled ODEs, which represent the local balance between convection, axial thermophoresis, Brownian coagulation, and sintering (surface-energy-driven area reduction). A Gaussian quadrature-based variant of MOM, hereafter written QMOM,77,78 was used to enable these simulations, using only three Gaussian quadrature points for each of the two state variables. This formulation also has the merit of tracking the morphological evolution of the nanoparticle population without explicitly introducing the (distributed) fractal dimension as a “new” particle state variable.88 Beyond the physical significance of particular Mkl’s,76 “mixed” moments are inherently statistical quantities that provide a convenient/useful set of parameters for characterizing any JPDF. A standard statistical tool, called principal component analysis (PCA), has recently been combined with quadrature concepts to obtain a general multivariate version of the QMOM.79 This reformulation systemizes the QMOM treatment of multivariate aerosol synthesis problems, including those that transcend the present bivariate example.76 These PBE simulation methods, which possess the above-mentioned attributes, are now being combined with recent systematic improvements in the accuracy of laws governing nonspherical particle diffusion (Brownian and thermophoretic),65,67,89 coagulation,69,72,89,90 restructuring (by sintering,18,91-94 nonsteady evaporation (or dissolution),95 and crystallization.96 The stage is now set to examine a number of additional multivariate particle synthesis applications, e.g., modeling the evolution of observed particle product population crystallinity63,96 and particle charge.97 We note here that, in commercial pigment production (e.g., TiO2) alone, there have been many patents granted/ exploited on methods to control crystallinity and aggregation via the use of suitable additives.98 Data Requirements and Extensions. As summarized earlier (section 3), thus far the experimental data needed to guide these theoretical advances have been provided mainly by atmospheric pressure laboratory-scale laminar flame experiments on metal oxide (e.g., Al2O3 and TiO2) nanoparticle populations.15-17 This includes a rather complete set of data on alumina nanoaggregate population evolution using a TMA“seeded” counterflow laminar diffusion flame reactor (row 1, Table 1) with laser-based optical as well as TEM grid thermophoretic sampling.17,99,100 With further development, these multivariate QMOM-based simulation

methods should also lend themselves to future parameter estimation, e.g., inferring a “best-fit” activation energy for alumina nanoparticle sintering by, say, surface diffusion.18 Variants/extensions of these simulation techniques should also enable incorporation into, say, full PDF methods101 for turbulent synthesis reactors of industrial interest.102 However, as noted below, to guide these important extensions, additional experimental data, using new laser-based probing techniques, will be needed, especially for more complex environments (e.g., more highly loaded, higher pressure, turbulent, etc.; see section 6). 5. Laser-Based Nanoparticle Diagnostics: TR-LII and LIABU For quantitative studies in which nanoparticles of materials such as Fe2O3 are synthesized in, say, atmospheric pressure flames, it is attractive to supplement relatively well-developed laser-based “elastic” light scattering (LLS) techniques,17,105 which provide information on aggregation but not spherule size, by those exploiting the absorption of short (ca. 8 ns), high fluence (ca. >0.1 kJ/m2) light pulses (e.g., Nd:YAG laser). The resulting space- and time-resolved particle incandescence (LII) signals (which track the “relaxation” of nanoparticle temperature back to a value near the original local gas temperature) can be “deconvoluted” to yield local spherule size distributions106 and, more straightforwardly, local relative volume fractions (cf. Figure 2). Indeed, we were motivated to develop this TR-LII class of online optical techniques further because they open up the attractive prospect of nearly real-time monitoring/ control of nanospherule size and, hence, particle specific surface area, for high-throughput particle synthesis reactors (e.g., in SiO2 synthesis using a flame reactor like that shown in Figure 1c, BET-equivalent spherule diameters between 15 and 110 nm have been reported, depending on operating conditions23). Here we briefly discuss the results and implications of our recent LII and thermophoretic sampling experiments on seeded laminar flames, comparing this situation to the more familiar use of LII to monitor carbonaceous “soot” spherule sizes and concentrations in unseeded hydrocarbon-fueled flat, premixed flames. The ability of time-resolved laser-induced incandescence (TR-LII) to obtain absolute spherule sizes in atmospheric pressure flames has been demonstrated using 532-nm Nd:YAG pulses of ca. 8-ns duration. For example, by averaging over a hundred TR-LII traces, each of which lasts only ca. 0.2 µs, we were able to unambiguously size absorbing spherules in the ca. 20nm-diameter range, provided the dispersity of the spherule population is sufficiently small.74,107,108 Adequately narrow distributions of alumina spherules have been observed in our counterflow laminar diffusion flame experiments, but because alumina is only weakly absorbing at 532 nm, we have been optically and thermophoretically probing iron oxide (hematite) spherules, and nanoaggregates, in flat premixed flames at temperatures below ca. 1600 K. 5.1. Requirements for the Successful Use of TRLII. On the basis of our experience to date, we have identified the following requirements for accurate nanoparticle sizing using TR-LII. Briefly, these include (i) adequate particle spectral absorptivity and laser fluence (kJ/m2), (ii) laser pulse duration (fwhm) , (tp)h, where (tp)h is the heat-transfer relaxation time of the particles

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of interest in the prevailing gas mixture, (iii) negligible vaporization (sublimation) cooling or other “latent heat” complications (see, also, refs 109 and 110 and the recent analysis of Michelsen111), and (iv) nondominant contribution to the signal from larger particle “modes” present at comparable volume fractions. The following extensions have also been initiated: (a) generalizations of the underlying TR-LII theory to account for the systematic effects of incomplete energy accommodation during gas impingement cooling,74,107,108,112,113 temperature-dependent gas heat capacity, Cv(T),114 thermal swelling of the laser-heated particles, interspherule “shielding” in aggregates,115 background gas temperature rise107 at particle volume fractions above ca. 3 ppm, and unknown or anomalous optical properties associated with highly defective crystals;116,117 (b) the sensitivity of LII inferences to inevitable uncertainties in gas and particle thermophysical and electronic properties. An important part of any such study must be the intercomparison of complementary techniques, e.g., techniques based on thermophoretic sampling/TEM analysis68,99,100,113 or sampling + electrical mobility analysis.14 5.2. Extensions of LII and LLS: Real-Time In Situ Probing of Interspherule Bond Energies in Nanoaggregates? In an encouraging recent development, we discovered that it is not only possible to do TR-LII spherule sizing at low laser fluences (say, below 0.2 kJ/m2), but we found simultaneous LLS evidence for laser-induced aggregate breakup (LIABU) at somewhat higher laser fluences (still well below the apparent spherule vaporization/sublimation threshold; ca. 1 kJ/ m2 in this case). These techniques/observations may provide the basis for an additional (online “optical”) method to characterize the apparent interspherule bonding in such nanoaggregate structures. Our quantitative interpretation of LIABU observations on hematite nanoaggregates and soot aggregates in atmospheric pressure flames is based on the process of thermal electron emission, leading to a “Coulomb explosion” of these nanoaggregates (when the Coulomb energy associated with a representative spherule pair exceeds the interspherule bond energy). From our preliminary experimental and theoretical studies, we believe that systematic LIABU measurements, when combined with a Coulomb explosion theory currently being refined, will open the door to valuable supplementary real-time information on the “strength” (stability) of such nanoaggregate structures, a previously inaccessible property that will influence the performance of most nanostructured materials formed by their downstream assembly or controlled deposition. 6. Concluding Remarks: Trends and Needs We anticipate that flame synthesis1 will play an everincreasing role in making available sufficient quantities of “tailored” nanopowders/coatings to enable many emerging industrial applications that exploit their remarkable properties (mechanical, chemical, magnetic, electronic, optical, thermal, etc.). As has been outlined here, considerable progress has recently been made on the underlying rate processes needed to predict the nanoparticle synthesis reactor performance, especially in the areas of Brownian coagulation of morphologically complex particles, surface-energy-driven sintering, particle thermophoresis, and nanoparticle population dynamics in the simultaneous presence of these phenom-

ena. However, unacceptable uncertainties remain in some of these areas, perhaps most notably in predicting nanoparticle “birth rates” (i.e., “chemical nucleation” rates) even in steady, laminar flow systems.102 It must also be admitted that the highly developed methodology and database of homogeneous and heterogeneous combustion is the result of a significant multinational investment in numerous quantitative studies of “simple” hydrocarbon/oxygen systems over the past century. However, to achieve our present expanded material synthesis objectives, which necessarily include many high-value non-oxide nanoparticles (cf. Table 2), many new chemical systems (featuring “unusual” fuels and oxidizers and, very likely, unusual combustor designs) will have to be introduced/carefully investigated. Indeed, traditional flame reactors (Figure 1a-c) by themselves may not be capable of satisfying strict “monodispersity” requirements, as is also true for many other (“rival”) nanoparticle synthesis techniques. In such cases, efficient separation devices will have to be developed and “articulated” with such aerosol synthesis reactors. For many such “integrated reactor-separator” applications, the ideal separation method would not be to select particles based on, say, their size, but rather on the property of interest itself (e.g., a particular optical transition). In any case, alternative reactor-compatible methods that can meet the stringent nanoparticle separation requirements at hand will have to be systematically explored before one is selected/optimized. The design of new reactor-separator combinations is a novel ASRE area whose importance is likely to grow as the number of remarkable applications for tailored nanoparticles grows. Quite understandably, most research studies have been carried out using bench-scale equipment operating under laminar flow, atmospheric pressure conditions, often with rather expensive precursors (see Tables 1 and 2). Moreover, particle volume fractions have also been kept conveniently low (usually less that 1 ppm; cf. Figure 2) to simplify the diagnostics/data interpretation. The complexities of relaxing many, if not all, of these conditions will have to be faced in the foreseeable future. For several applications,1-3 we already know that favorable, if not optimal, conditions involve large, turbulent, high-pressure reactors operating with inexpensive precursors and at appreciable nanoparticle volume fractions (perhaps 1000 ppm). Suitable experiments and effective simulation methods will have to be developed to enable these important extensions at tolerable R&D costs. We have been discussing a rather exciting new “offshoot” of the more mature area of chemical reaction engineering (CRE). One of its defining features is the impressive range of physical scales that must be embraced, necessarily some 10 decades in length. Because of this, the pace of further progress will depend on the rate at which rapidly evolving molecular-level and particle-level insights can be articulated with reactorscale modeling efforts. Such advances will have to be guided not merely by scientific curiosity but also by the parallel development/implementation of fundamentally new online nanoparticle characterization techniques in laboratory-, pilot-, and industrial-scale configurations. Acknowledgment This paper was prepared, in part, to acknowledge the valuable early role of Dr. Milorad Dudukovic, who, in concert with Prof. S. K. Friedlander (see, e.g., ref 118),

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helped bring the innovative field of aerosol science into the industrially important domain of chemical reaction engineering. This marriage, called aerosol reaction engineering (ASRE) in the recent NSF/EPA Workshop6 entitled “Emerging Issues in Nanoaerosol Science and Technology” (Panel No. 4, pp 91-106), seems destined to play an essential, if not dominant, role in the production of high-value nanoparticles using “flame”based techniques, the subject of this short review/ forecast and hopefully useful reference list (section 7) and just one of many applications of combustion in the synthesis and processing of valuable materials.1 The recent work of our group at the Chemical Engineering Department at Yale University was primarily supported under NSF Grants CTS-987 1885 and 998 0747. I thank my research collaborators Drs. R. McGraw, D. Albagli, Y. Xing, A. V. Filippov, S. Yu, U. O. Koylu, B. La Mantia, J. Fernandez de la Mora, A. Gomez, P. GarciaYbarra, J. L. Castillo, S. Jimenez, A. G. Konstandopoulos, M. B. Long, D. W. Mackowski, M. Arias-Zugasti, J. J. Pyykonen, D. H. Papadopoulos, M. Zurita-Gotor, and P. Tandon for their important contributions (loc. cit.) and N. Glumac, R. B. Diemer, Jr., G. Fotou, S. K. Friedlander, R. C. Flagan, J. J. Helble, P. Christofides, C. Sorensen, H. Wang, and S. E. Pratsinis for their timely inputs during the preparation of this overview manuscript, presented verbally as Invited Plenary Lecture at the 2003 European Aerosol Conference (Madrid, Spain), as Paper 33e at the AIChE Annual Meeting (2003) in San Francisco, CA, and as Poster 5I603 at the 30th International Combustion Symposium (2004). Abbreviations and Acronyms ASRE ) aerosol reaction engineering BET ) physical adsorption based method BV ) bivariate (two state variables) CFD ) computational fluid dynamics CNT ) classical nucleation theory CRE ) chemical reaction engineering CVD ) chemical vapor deposition Df ) fractal dimension Diff ) diffusion flame EtOH ) ethanol FA ) fractal-like aggregate fm ) free-molecule (regime) FLP ) flame plane (location); Figure 2 F/O ) fuel/oxidizer fwhm ) full width at half-maximum GSP ) gas stagnation plane JMT ) Jacobian matrix transformation JPDF ) joint probability density function Lam ) laminar LIABU ) laser-induced aggregate breakup LII ) laser-induced incandescence LLS ) laser (elastic) light scattering MC ) Monte Carlo Nd:YAG ) neodymium-yttria/alumina garnet np ) nanoparticle (dp,eff < 100 nm) nT ) nanotube ODE ) ordinary differential equation PBE ) population balance equation PDE ) partial differential equation PIP ) particle inception plane PCA ) principal component analysis PDF ) probability density function PSP ) particle stagnation plane PV ) precursor vapor

QMOM ) quadrature method of moments RTD ) residence time distribution RSP ) reactive spray pyrolysis SP ) spray pyrolysis TEM ) transmission electron microscopy TMA ) trimethylaluminum TPD ) thermocouple particle densitometry TPS ) thermophoretic sampling TR-LII ) time-resolved LII Turb ) turbulent YSZ ) yttrium-stabilized zirconia

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(89) Zurita-Gotor, M. Rational Numerical Simulations in Sol Reaction Engineering. Ph.D. Dissertation, Yale University Graduate School, May 2004. (90) Zurita-Gotor, M.; Rosner, D. E. Effective Diameters for Collisions of Fractal-like Aggregates: Recommendations for Improved Aerosol Coagulation Frequency Calculations. J. Colloid Interface Sci. 2002, 255, 10-26. (91) Tandon, P.; Rosner, D. E. Sintering Kinetics and Transport Property Evolution of Large Multi-particle Aggregates. Chem. Eng. Commun. 1996, 151, 147-168. (92) Garabedian, R. S.; Helble, J. J. A Model for the Viscous Coalescence of Amorphous Particles. J. Colloid Interface Sci. 2001, 234 (2), 248-260. (93) Lehtinen, K. E. J.; Zachariah, M. R. Energy Accumulation in Nano-particle Collision and Coalescence Processes. J. Aerosol Sci. 2002, 33, 357-368. (94) Lee, D.; Choi, M. Coalescence-Enhanced Synthesis of Nanoparticles to Control Size, Morphology and Crystalline Phase at High Concentrations. J. Aerosol Sci. 2002, 33, 1-16. (95) Rosner, D. E. Better Rate Laws/Population Balance Simulation Methods: CRE Applications. Int. J. Chem. React. Eng. 2005, in press. Paper Prepared for CRE-X, Zacatecas City, Mexico, Aug 28-Sept 2, 2005. (96) Rosner, D. E. Nucleation Mechanism for Freezing of Alumina in Solid Propellant Rocket Motor Nozzles. J. Propul. Power 2004, 20 (2, Mar-Apr), 380-383. (97) Karasev, V. V.; et al. Formation of Charged Aggregates of Al2O3 Nano-particles by Combustion of Aluminum Droplets in Air. Combust. Flame 2004, 138, 40-54. (98) Xiong, Y.; Pratsinis, S. E.; Mastrangelo, V. R. The Effect of Ionic Additives on Aerosol Coagulation. J. Colloid Interface Sci. 1992, 153 (1), 106-117. (99) Koylu, U. O.; Xing, Y.; Rosner, D. E. Fractal Morphology Analysis of Combustion-Generated Aggregates Using Angular Light Scattering and Electron Microscope Images. Langmuir 1995, 11 (12), 4848-4854. (100) Dobbins, R. A.; Megaridis, C. Morphology of FlameGenerated Soot As Determined by Thermophoretic Sampling. Langmuir 1987, 3, 254-259. (101) Fox, R. O. Computational Models for Turbulent Reacting Flows; Cambridge University Press: Cambridge, U.K., 2003. (102) If reliable predictions of particle nucleation rates cannot yet be made in steady laminar flows (section 3.2), it should not be surprising that highly transient micromixing, chemical reaction, and nucleation in turbulent, initially unmixed environments remain a daunting, unsolved problem, despite its obvious industrial importance. Results from computationally intensive “direct numerical simulations” are being reported on turbulent mixing layers in which new particle formation via chemical reaction and homogeneous nucleation is taking place.103,104 Such studies are ultimately intended to guide the development of more practical (time-averaged turbulent) simulation methods. Currently, however, they presume either (1) a simple connection between the global rate of precursor vapor oxidation and the embryonic particle formation rate or (2) the local validity of steady-state homogeneous nucleation theory (CNT), even when the Kolmogorov and nucleation time lags are comparable. Under the prevailing conditions, each of these presumptions may produce results that are inadvertently misleading, notwithstanding other transport coefficient idealizations required for numerical implementation. In our view, it will be necessary to go beyond these simple postulates, e.g., including transient nucleation effects involving a cluster/embryo population. This seems to be another example of our contention (section 6 and ref 76) that many frontier problems now involve the dynamical interaction of two or more coexisting populations (here embryos and more “mature” particles). (103) Moody, E. G.; Collins, L. R. Effect of Mixing on the Nucleation and Growth of Titania Particles. Aerosol Sci. Technol. 2003, 37 (5), 403-424. (104) Pyyko¨nen, J. J.; Garrick, S. C. Direct Numerical Simulations of Homogeneous Nucleation in Turbulent Mixing Layers. Manuscript in preparation, 2005; private communication to DER. (105) Kim, H. W.; Choi, M. In Situ Line Measurement of Mean Aggregate Size and Fractal Dimension Along the Flame Axis by Planar Laser Light Scattering. J. Aerosol Sci. 2003, 34, 16331645. (106) Filippov, A. V.; Markus, M. W.; Roth, P. In Situ Characterization of Ultra-fine Particles by Laser-Induced Incandescence: Sizing and Particle Structure Determination. J. Aerosol

Ind. Eng. Chem. Res., Vol. 44, No. 16, 2005 6055 Sci. 1999, 30 (1), 71-87. See also: Roth, P.; Filippov, A. V. J. Aerosol Sci. 1996, 27 (1), 95-104. (107) Rosner, D. E.; Schaffer, A.; Long, M. B.; La Mantia, B. In Situ, Real-Time Sizing of Inorganic Nanoparticle Populations in Flames Using Laser-Induced Incandescence; AAAR: Portland, OR, Oct 2001; Abstract 15D1. See also: Filippov, A. V.; et al. Theory of Aerosol Sizing by Laser Induced Incandescence at High Particle Volume Fractions. AAAR1998 (Cincinnati) and Proceedings of the 5th International Aerosol Conference (Edinburgh, Scotland, Sept 1998) papers. (108) Rosner, D. E.; Jimenez, S.; McEnally, C.; Pfefferle, L.; Schaffer, A.; Long, M. B. Time-Resolved LII for Estimating Nanoparticle Size Distributions in Atmospheric Pressure Flames: Recent Observations/Recommendations. Eastern States Section of the Combustion Institute December Meeting, Hilton Head, NC, 2001; Paper 67. (109) Vander Wal, R. L.; Ticich, T. M.; Stephens, A. B. Can Soot Primary Particle Size be Determined Using Laser-Induced Incandescence? Combust. Flame 1999, 116, 291-296. (110) Smallwood, G. J.; Snelling, D. R.; Liu, F.; Gulder, O. L. Clouds Over Soot Evaporation: Errors in Modeling Laser Incandescence of Soot. J. Heat Transfer (ASME) 2001, 123, 814-818. (111) Michelsen, H. A. Understanding and Predicting the Temporal Response of Laser-Induced Incandescence from Carbonaceous Particles. J. Chem. Phys. 2003, 118 (15), 7012-7045. (112) Rosner, D. E.; Papadopoulos, D. H. Jump, Slip and Creep Boundary Conditions at Nonequilibrium Gas/Solid Interfaces. Ind. Eng. Chem. Res. 1996, 35 (9), 3210-3222. (113) Kock, B. F.; Kayan, C.; Knipping, J.; Orthner, H. R.; Roth, P. Comparison of LII and TEM Sizing During Synthesis of Iron

Particle Chains. Proceedings of the 30th International Symposium on Combustion; Combustion Institute: Pittsburgh, PA, 2005; pp 1689-1697. (114) Filippov, A. V.; Rosner, D. E. Energy Transfer Between an Aerosol Particle and Gas at High-Temperature Ratios in the Knudsen Transition Regime. Int. J. Heat Mass Transfer 2000, 43, 127-138. (115) Filippov, A. V.; Zurita-Gotor, M.; Rosner, D. E. Fractallike Aggregates: Relation Between Morphology and Physical Properties. J. Colloid Interface Sci. 2000, 229, 261-273. (116) Altman, I. S. Determination of Particle Temperature From Emission Spectra. Combust., Explos. Shock Waves (Engl. Transl.) 2004, 40 (1), 67-69. See also: Phys. Rev. 2003, B68, 125324 ff. (117) Lehre, T.; Suntz, R.; Bockhorn, H. Time-Resolved TwoColor LII: Size Distributions of Nanoparticles From Gas to Particle Synthesis. Proceedings of the 30th Combustion Symposium on Combustion; Combustion Institute: Pittsburgh, PA, 2005; pp 2585-2593. (118) Pratsinis, S. E.; Kodas, T. T.; Dudukovic, M. P.; Friedlander, S. K. The Effect of Aerosol Reactor Residence Time Distribution on Product Aerosol Characteristics. Chem. Eng. Sci. 1986, 41 (4), 693-700.

Received for review August 27, 2004 Revised manuscript received May 20, 2005 Accepted May 23, 2005 IE0492092