This article was downloaded by: [Weltin, Heather] On: 6 September 2009 Access details: Access Details: [subscription number 914539058] Publisher Informa Healthcare Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Nanotoxicology Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t716100760 Nanomaterials properties vs. biological oxidative damage: Implications for toxicity screening and exposure assessment Dhimiter Bello ab; Shu-Feng Hsieh cd; Daniel Schmidt be; Eugene Rogers bc a Department of Work Environment, School of Health and Environment, b Center for High-Rate Nanomanufacturing, University of Massachusetts Lowell, Lowell, MA, USA c Department of Clinical Laboratory and Nutritional Sciences, School of Health and Environment, d Biomedical Engineering and Biotechnology Program, e Department of Plastics Engineering, First Published on: 02 June 2009 To cite this Article Bello, Dhimiter, Hsieh, Shu-Feng, Schmidt, Daniel and Rogers, Eugene(2009)'Nanomaterials properties vs. biological oxidative damage: Implications for toxicity screening and exposure assessment',Nanotoxicology,3:3,249 — 261 To link to this Article: DOI: 10.1080/17435390902989270 URL: http://dx.doi.org/10.1080/17435390902989270 PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Nanotoxicology, September 2009; 3(3): 249
261 Nanomaterials properties vs. biological oxidative damage: Implications for toxicity screening and exposure assessment DHIMITER BELLO1,5, SHU-FENG HSIEH2,3, DANIEL SCHMIDT4,5, & EUGENE ROGERS2,5 1 Department of Work Environment, School of Health and Environment, 2Department of Clinical Laboratory and Nutritional Sciences, School of Health and Environment, 3Biomedical Engineering and Biotechnology Program, 4Department of Plastics Engineering & 5Center for High-Rate Nanomanufacturing; University of Massachusetts Lowell, Lowell, MA 01854, USA Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 (Received 13 December 2008; accepted 22 April 2009) Abstract Biological oxidative damage (BOD) has been recognized as a key toxicity mechanism with potential as a novel global metric for nanomaterial (NM) exposure and rapid toxicity screening. A ‘Ferric reducing ability of serum (FRAS)’ assay, recently optimized by our group, was used to quantitate the degree of BOD induced by 19 diverse, commercially important NMs, including carbon blacks, fullerenes, carbon nanotubes, and titanium dioxide. This study investigated the relationship between several physico-chemical parameters of NMs and BOD and their relevance to exposure assessment and toxicity screening. FRAS-measured BOD strongly correlated with specific surface area and total content of select transition metals (especially Fe, Cr, Co, Mo and Mn). These two factors combined explained 93% of the BOD. The FRAS BOD potential of NMs appears to be a valid approach for screening purposes. These findings support the use of BOD as a metric for NM exposures. Keywords: Engineered nanomaterials, oxidative stress, FRAS, ROS, dose metrics, specific surface area, CNTs Abbreviations: FRAS, Ferric reducing ability of serum, NMs, Nanomaterials, one or more dimensions B100 nm, BOD, Biological oxidative damage, ROS, Reactive oxygen species, UFP, Ultrafine particles NMs, one or more dimensions B100 nm, TPTZ, 2,4,6-tripyridyl-s-triazine, CNTs, Carbon nanotubes, SWCNTs, Single wall carbon nanotubes, MWCNTs, Multi-wall carbon nanotubes, SWCNHs-ox, H2O2-oxidized Single wall carbon nanohorns, ICP-MS, Inductively coupled plasma-mass spectrometry, INAA, Instrumental neutron activation analysis, OC, Organic carbon, EC, Elemental carbon, TC, Total carbon, TEUs, Trolox Equivalent Units, trolox is a water soluble form of vitamin E. Introduction Development of new nanotechnology-enabled materials and products is at present a fertile field of scientific research and economic promise (Maynard 2007; Hebert 2006). New nanotech-based products are being introduced at a rate of 3
4 per week (Parlini 2008) with several hundreds already on the market (Maynard 2007). The high rate, high volume, and the variety with which some engineered nanomaterials (NMs) are being produced have dramatically outpaced the capacity of current toxicity testing approaches (RCEP 2008) to determine if they are safe or elicit adverse effects on human health or the environment. Meeting this challenge requires the development of robust, inexpensive, and high-throughput screening approaches for new materials at the early development stages to enable a proactive approach to addressing potential health risks, prioritizing NMs (and limited resources) for in-depth toxicity evaluations, and redesigning processes to result in safer yet economically viable manufacturing practices (Maynard et al. 2006). Another related challenge is adequate characterization of NMs exposures as they may occur during handling and processing, the use of nano products, or via incidental environmental exposures (Maynard et al. 2004; Methner et al. 2007; Bello et al. 2009; Tsai et al. 2009). At present, it is not possible to measure simultaneously and in real-time multiple toxicity-relevant physico-chemical parameters of Correspondence: Dhimiter Bello, ScD, MSc, Asst. Professor, Department of Work Environment School of Health and Environment, University of Massachusetts Lowell, One University Ave., Lowell, MA 01854, USA. Tel: 1 978 934 3343. E-mail: dhimiter_bello@uml.edu ISSN 1743-5390 print/ISSN 1743-5404 online # 2009 Informa UK Ltd. DOI: 10.1080/17435390902989270 Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 250 D. Bello et al. NMs, such as specific surface area, bioavailable transition metals, adsorbed organic matter, surface impurities and defects, biosolubility, crystalinity, surface charge, morphology, etc. (Oberdörster et al. 2005a,b). Even with bulk materials these requirements are almost never met in practice, and rarely are all of these parameters measured and/or reported (Hansen et al. 2007). Such in-depth characterization requires highly specialized laboratories, expensive instrumentation, skilled operators, and several hundred milligrams NMs. Alternative biologically-relevant metrics, responsive to multiple key parameters involved in NMs toxicity, may provide an opportunity to screen for the inherent toxicity potential of NMs and to be adopted as novel NMs exposure metrics. Biological oxidative damage (BOD) can be one such metric. BOD has being recognized as one of the most important mechanism of toxicity of particulate matter (Kelly 2003; Donaldson et al. 2005; Nel et al. 2006; Kelly and Mudway 2007) and has been proposed as a more responsive, novel metric for NMs exposure (Xia et al. 2006a; Borm et al. 2007; Ayres et al. 2008) and as a basis for rapid toxicity screening of NMs (Jiang et al. 2008; Sauvain et al. 2008; Rogers et al. 2008a). We explored the utility of the ‘Ferric reducing ability of serum (FRAS)’ assay, recently optimized by our group, as a screening tool and used to quantitate the degree of BOD elicited by several NMs in human blood serum (Rogers et al. 2008a). The use of human blood serum as a reagent medium in combination with an assay that measures changes in total antioxidant capacity (by spontaneous chemical oxidation, catalytic redox reactions, and physical adsorption) is arguably a superior test system for BOD (Rogers et al. 2008b) compared to other common chemical systems such as DCFH (dichlorofluorescin). Preliminary testing shows that FRAS is a sensitive test system (Rogers et al. 2008a): A positive FRAS indicates BOD and potential for toxicity. However, a negative FRAS does not preclude the possibility of toxicity by mechanisms other than BOD, such as cancer associated with long fibers, cell injury and death (apoptosis) without inflammation (Xia et al. 2006a) or non-ROS associated immunogenic activity (Kelly and Mudway 2007). This research had two main objectives: (i) To investigate the relationship between several physicochemical parameters of NMs and FRAS-measured BOD in an effort to explain the observed results; and (ii) to investigate the utility of these findings for exposure assessment of NMs. We report here the FRAS results of an extended set of 19 NMs and an analysis of the relationships between FRAS values and physico-chemical properties. Materials and methods Nanomaterials The NMs used in the study, together with their sources and specifications, are summarized in Table I. These materials were chosen because they are of commercial importance and provide a broad range of physico-chemical properties. The materials were a series of carbon blacks, a series of fullerenes, a series of titanium dioxides (nano- and micron-sized anatase and rutile), a series of single and multi-wall carbon nanotubes of variable length and purity, H2O2 oxidized single wall carbon nanohorns (SWCNHs-ox), nano alumina, nano silver, and micron-sized crystalline silica. For simplicity we will refer to the whole set of materials under investigation as NMs, although some are microscopic. The FRAS assay Biological oxidative damage induced by NMs was determined via a FRAS approach, details of which can be found in (Rogers et al. 2008a). The method is based on the reduction of the Fe 3-TPTZ complex to a Fe 2-TPTZ complex at low pH by residual antioxidants present in serum after exposure to nanomaterials under defined conditions and thus measures the decrease in the total pool of serum antioxidants. This is monitored by measuring absorbance at 593 nm (specific to the Fe 2-TPTZ complex) after a 30-min reaction time at room temperature (triplicate measurements). The procedure included pre-incubation of 10 mg NM with 1.0 ml serum at 378C for 90 min with mixing, followed by separation of the NM from the serum via two centrifugation steps (14,500 g and 20 min each) and transferring of 100 ml of the supernatant (NM exposed or unexposed serum) to 1.0 ml of working FRAS reagent. Trolox, a water soluble analog of vitamin E (standard solution in methanol) was used as an antioxidant to calibrate the FRAS results and demonstrated linearity between 25 and 500 mM. The FRAS absorbance as a function of trolox concentration was: Atrolox 4.18 Ctrolox (mM) (r2 0.99, p B0.01; n 16), where Atrolox absorbance at 593 nm (in arbitrary units) and Ctrolox  concentration in mM. The mean antioxidant capacity of unexposed human serum was 525 mmol/l trolox equivalent units (TEUs). The BOD was then calculated as the difference between the total antioxidant capacity (TEUs) of unexposed and NMs exposed serum. A positive BOD represents a Sample Label 1 2 3 4 N110 N550 N990 F_soot 5 F_refined 6 7 F_purified SWCNT_S 8 SWCNT_L 9 MWCNT_S 10 MWCNT_L 11 Description Primary particle sizea SSA m2g 1 Mean BODb (TEUs, mmol L 1 (n3) Cabot Corp., Billerica MA, USA Cabot Corp., Billerica MA, USA Engineered Carbons Inc., Borger, TX, USA M.E.R. Co., Tuscon, AZ, USA; (MRST) 15 nm 44 nm 200 nm 20 nm 110.6 39.2 7.7 194.3 93.7** (79.2
108) 61.4** (48.8
74.0) 41.3* (31.8
50.8) 62.1** (56.2
67.9) M.E.R. Co., Tuscon, AZ, USA; (MRMF) 20 nm 1.3 Source; (CAT #) MWCNT_I Carbon black N110 Carbon black N550 Carbon black N990 Fullerene soot (7% wt fullerenes) Fullerene (refined, 75% C60, 22% C70, 3% C70) Fullerene, purified (99% C60) Short single wall CNTs; 60% wt Long single wall CNTs; 90% wt Short multi-wall CNTs; 95% wt Long multi-wall CNTs; 95% wt Industrial grade multi-wall CNTs; 90% wt Cheap Tubes Inc., Brattleborough, VT, USA 12 SWCNHs-ox Single wall carbon nanohorns, H2O2 oxidized Donated by NEC Co., Japan 13 TiO2_nA Nano TiO2 (Anatase) 14 TiO2_nR Nano TiO2 (Rutile) Nanostructured & Amorphous Materials, Houston, Texas, USA; (5425HT) Sigma-Aldrich; (10024JH) 15 16 17 TiO2_mA TiO2_mR nAg Micro TiO2 (Anatase) Micro TiO2 (Rutile) Nano silver 18 Silica Crystalline silica (Min-U-Sil 5) 19 nAl2O3 Nano alumina M.E.R. Co., Tuscon, AZ, USA; (MR6LP) Cheap Tubes Inc., Brattleborough, VT, USA Cheap Tubes Inc., Brattleborough, VT, USA Cheap Tubes Inc., Brattleborough, VT, USA Cheap Tubes Inc., Brattleborough, VT, USA Sigma-Aldrich; (06618ME) Sigma-Aldrich; (03008JS) NanoDynamics Inc., Buffalo, NY, USA; (1424) US Silica Company, Berkeley Springs, WV, USA; (15071995) Nanotek Instruments Inc., Dayton, OH, USA 20 nm OD 1
2 nm; L0.5
2 mm OD 1
2 nm; L5
30 mm OD10
20 nm; L0.5
2 mm OD10
30 nm; L10
30 mm OD10
30 nm; L10
30 mm OD 1
2 nm; Aggl.50
100 nm 10 nm 10 nm thick, 40 nm laterally 1
5 mm 1
5 mm 60 nm 15.1 (7.2
23.0) 0.2 342.9 4.3 (1.5
10.2) 1236.1** (1163
1309) 510.5 1376.3** (1160
1593) 229.1 706.2** (640
772) 156.1 165.4** (158
172) 99.7 86.3** (63.4
110.3) 1154.0 1725.4** (1285
2165) 274.2 64.9** (58.8
70.9) 189.9 12.6 (1.1
23.6) 9.8 2.5 8.4 12.5 (0.6
25.8) 10.8 (3.6
17.8) 116.4** (99.3
133.5) 0.1
5 mm 5.1 16.2 (8.0
23.4) 45 nm 28.3 9.1 (0.9
17.3) a OD, Outer diameter; L, length; wt, weight; SSA, Specific surface area (m2g 1); TEU, Trolox equivalent unit (mmol l 1 or mM); Particle size was independently confirmed by TEM and calculations based on SSA. bBOD, Biological oxidative damage measured as a decrease in the total antioxidant capacity of human serum by the FRAS assay and expressed in Trolox equivalent units (TEUs, mmol l 1, mM). The mean antioxidant capacity in control serum is 525 TEUs (standard error of the mean SEM4). *p B0.05, **p B0.01. Biological oxidative damage and nanomaterials exposures Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Table I. Summary description of the materials tested in this study. 251 252 D. Bello et al. decrease in the total antioxidant capacity of serum reported in TEUs. Venous blood was obtained from several female and male volunteers (20
55 years of age, healthy, fasted), in anticoagulant-free tubes and allowed to clot for 30 min followed by centrifugation at 2000 g for 20 min to obtain serum. Sera from all individuals were pooled, aliquoted, and frozen at 708C for use as a consistent biological matrix for oxidative stress assessment. All chemicals in the assay were of analytical grade (Sigma-Aldrich St Louis, MO, USA) and used as received. Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Materials characterization Specific surface area. Samples were analyzed via nitrogen sorption at 77 K using a Quantachrome Autosorb-3B gas physisorption unit. Prior to any sorption measurements, all samples were degassed for a minimum of 48 h at 2008C, with the exception of the nano-silver particles, which were found to sinter at temperatures as low as 508C and were therefore degassed for 72 h at room temperature. All specific surface area values come from 11-point BET plots of data obtained over a pressure range of P/ P0 0.05
0.3 (correlation coefficient ]0.998 for all BET fits). Transition metals. Transition metals in bulk NMs were first determined with an automated INAA system (Eby 2008). Following results of INAA analysis a select set of 10 transition metals (Fe, Cr, Co, Ni, Zn, Zr, Mo, Mn, La and Ba) were determined in the bulk NMs following microwave assisted acid digestion (EPA 3051A method) and in the water soluble extract (at 378C with mixing for 90 min, similar to the FRAS assay conditions) with the more specific and more sensitive ICP-MS technique. ICP-MS analyses were conducted at the University of Washington’s environmental health laboratory on an Agilent 7500 CS system. Organic carbon. Organic carbon analysis was used as a surrogate (non-specific) measure for redox-active organic matter (such as quinones) adsorbed onto or deposited on the surface of NMs during the manufacturing process. This fraction may be of particular interest in carbon blacks, fullerenes, CNTs and SWCNHs-ox. The organic and elemental carbon (OC/EC) analyses were conducted at Sunset Laboratories (Tigard, OR, USA) using a modified NIOSH method 5040 for bulk NMs on quartz filters on a Carbon aerosol analysis lab instrument. Surface charge. Surface charge measurements of a suspension of each NM in PBS saline were performed on a ZetaPALS instrument (Particle Characterization Laboratories Inc., Novato, CA, USA). The measured parameters included particle mobility, zeta potential, and the polydispersity index, the last one being a measure of the dispersion uniformity under the test conditions of these experiments. Crystalinity. All samples were analyzed using a Scintag PAD X diffractometer (theta-theta reflection geometry) at Cornell University, using a Cu Ka source operating at 45 kV and 40 mA and a liquid nitrogen-cooled solid state Ge detector. Scans were carried out from 28 to 708 two-theta at a scan rate of 28 per min. Slits used were 18 and 38 for the source and 0.38 and 0.58 for the detector, respectively, with wider angles closer to the sample. Low-background quartz sample holders were used in all cases. The DMSNT software package was used for data analysis, and patterns were indexed according to the JCPDS Powder Diffraction File. Statistical analysis Experimental data were analyzed via two-sided ttest, analysis of variance ANOVA, correlation and regression and stepwise multiple regression using SPSS v16 (SPSS Inc., Chicago. IL, USA). Results Biological oxidative damage potential by FRAS FRAS results for the set of 19 NMs are summarized in Table I. The range of BOD exerted by the test NMs is wide, spanning more than two orders of magnitude. The NMs with the highest BOD values of 1,725, 1,376 and 1,236 mmol TEUs l1 were the oxidized SWCNHs-ox and two SWCNTs (long and short), respectively. At the standard 10 mg ml1 serum protocol these materials and MWCNT_S (short MWCNTs) overwhelmed the serum pool of antioxidants (525 mmol TEUs l1). The tests for these materials were repeated at 6 times dilution (1.67 mg NM ml1 serum) and the results scaled to equivalence with a 10 mg ml1 concentration in order to allow meaningful data comparison between various NMs. Within the CNT series, remarkable differences in the oxidative damage potential are also apparent. In particular, one of the CNTs, namely MWCNT-I, with an oxidative damage potential of 86.3 mmol TEUs l1, was 2 to 16 times less potent than all other CNTs. The short MWCNT (MWCNT_S) was 4.3 times more potent than its long MWCNT counterpart (MWCNT_L). The SWCNHs-ox and both SWCNTs (SWCNT_S and SWCNT_L) exhibited a statistically higher oxidative damage potential compared to the three types of MWCNTs Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Biological oxidative damage and nanomaterials exposures (_S, _L, and _I, ANOVA with post Hoc multiple comparisons, p B0.01). Within the fullerene series, there was a clear trend of increased oxidative damage potential with increasing impurity. The fullerene soot, which is a crude mixture of 7% wt C60 containing a substantial amount of amorphous carbon black, graphite, and other carbonaceous materials exhibited a significantly higher degree of BOD compared to the two purer forms of fullerenes (F_purified and F_refined), which gave results no different than unexposed human serum (ANOVA with post-hoc multiple comparisons, pB0.05). In the carbon black series (N110, N550, and N990), BOD was linearly related to primary particle size/specific surface area (ANOVA with post-hoc multiple comparisons, p B0.05). Only one of the four TiO2 samples (nano-anatase) exhibited statistically significant BOD (ANOVA with post-hoc multiple comparisons, pB0.05). As expected, nano-silver exhibited BOD (Ag for example has high affinity for glutathione and sulfhydryl groups in proteins), whereas nano alumina did not. Crystalline silica, a well known lung toxicant, did not exhibit BOD. It should be noted that this material was manufactured 14 years ago. Materials characterization Specific surface area. SSA (summarized in Table I) spanned more than three orders of magnitude, from a low of 0.2 m2 g1 for purified fullerenes to a high of 1,154 m2 g1 for SWCNHs-ox. Transition metals. Total metal content of NMs by ICP-MS is summarized in Table II. Detailed results of transition metals analyses in the bulk materials (INAA and acid digestion ICP-MS) and water soluble extracts (ICP-MS) can be found in the supplemental information (Table S1, online version only). Good correlation was generally seen between the two methods for the bulk content of most metals (Fe, Cr, Co, Ni, Mo, Zn, Zr, La; Pearson correlation coefficient r 0.7
1.0). Good correlation between the water-extractable and the bulk metal content (both measured by ICP-MS, r 0.83
0.93) for Zn, Mo, Mn, and Ba, and a high soluble-to-total metal fraction (up to 80% for Zn) suggests that these metals existed largely as water soluble species. For all other metals there was poor correlation between the total and soluble fraction (r B0.3) and the soluble-to-total metal ratio was small. Apart from a few metals (Co, Mn, and Ni in CNTs), most other metals in the water extract were near or below the detection limit. For example Fe in the water extract 253 ranged from 0.1
0.6 ppm (parts per million, mg g1). In spite of the generally good correlations between the two analytical methods, large discrepancies in absolute concentrations are obvious for several metals. These discrepancies are metal and material dependent. As a general trend, the INAA produced higher concentrations of transition metals, most notably Fe, Cr, Co, Zn, and Mo in the CNTs series. The most striking discrepancy was for Fe, for which the INAA gave consistently an order of magnitude higher values than the ICP-MS. One main reason for such large discrepancies may be incomplete acid digestion of all Fe species (or other metals species) in the ICP-MS sample preparation protocol. For subsequent analyses and discussions we will use the ICP-MS data as the default metal values as a more conservative approach, although both datasets have been used in the analyses and method-dependent differences have been noted. Quantifiable levels of transition metals were found in all materials at the low ppm range and no significant trends were observed within the NMs series. Only the CNTs had high amounts of several transition metals, especially Ni, Co, Mo, Cr, and Fe, with each CNT material exhibiting its own unique transition metal profile. SWCNTs had large amounts of Co and Mo (1
4 103 ppm) followed by Fe and Cr (up to 740 ppm), whereas MWCNTs had large amounts of Ni (up to 6 104 ppm), followed by Fe and Mo (100
500 ppm). The concentration of metals in the water soluble extract of the majority of NMs was low (50.1
1 ppm), including Fe, Cr and Co in CNTs (Table S1, online version only). Elevated amounts were found only for Ni in MWCNTs (44
233 ppm) and Mo in SWCNTs (31
108 ppm). Organic carbon. The OC and EC contents and the OC/TC ratio for several NMs of interest are presented in Table III. The OC content varied by NM class. The OC for the carbon black series was 3
4 ppm, independent of the material and slightly higher than in TiO2_nA (2 ppm). Among the CNTs, the highest OC was found for the industrial grade MWCNTs (MWCNT_I, 109.4 ppm) and the short SWCNTs (SWCNT_S, 76.6 ppm). Other CNTs and the SWCNHs-ox had 10
20 ppm OC. The OC content in the fullerene series, after subtracting the fullerene peak from the thermograms, varied from 44
62 ppm. The OC/TC ratio for most NMs was in the 0.3
2.0% range, with higher values for SWCNT_S (8.7%) and MWCNT_I (13.0%). The very high OC/TC ratios for other NMs reflect material peculiarities. 254 D. Bello et al. Table II. The transition metals content (ppm) in tested bulk NMs determined by microwave-assisted acid digestion of samples and ICP-MS. A detailed description of each material is provided in Table I. The data for La and Ba have been omitted from the Table II and Supplemental S1 (online version only) because they were generally non-detectable. Method Limit of Detection varied between 2 and 12 ng/ sample. Metal (ppmmg/g) Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Material N100 N550 N990 F-soot F-refined F-purified SWCNT_S SWCNT_L MWCNT_S MWCNT_L MWCNT-I SWNHs-Ox TiO2_nA TiO2_nR TiO2_mA TiO2_mR nAg Silica nAl2O3 Fe Cr Co Mo Mn Zn Ni 2.41 13.1 2.81 5.73 0.90 B0.01 353 741 172 306 497 4.74 8.19 59.1 2.15 4.20 3.06 0.40 8.24 0.15 0.44 0.10 0.30 0.15 0.15 230 476 10.0 4.15 33.0 1.03 0.81 2.35 0.10 0.44 0.05 1.36 0.59 0.33 0.22 0.10 0.30 0.15 0.15 4217 1798 68.9 9.02 120 0.10 0.15 0.20 0.10 0.05 0.05 0.18 0.10 1.05 0.40 0.65 2.35 1.00 1.20 1472 1672 113 155 192 0.70 1.05 1.55 0.90 0.50 0.20 0.40 0.75 0.38 0.92 0.10 0.30 0.15 0.15 12.7 25.3 5.32 4.69 25.9 0.10 0.75 1.03 0.10 0.05 0.66 3.85 1.40 0.35 0.29 0.20 7.57 4.63 3.54 1.12 4.12 11.8 2.89 8.55 0.53 11.9 7.26 0.62 0.62 0.05 5.94 47.1 0.40 1.22 0.10 0.30 0.15 0.15 52.6 67.3 4738 5890 51867 0.52 0.59 1.13 0.10 0.38 0.05 1.26 0.42 Surface charge. The electrophoretic mobility, zeta potential z, effective particle size and breadth of the effective particle size distribution (polydispersity) in PBS saline are summarized in Table III. For all samples except purified fullerenes (F_purified), the dispersion ranged from fair to excellent as judged by the polydispersity index and the effective diameter. F_purified did not wet and the resultant z measurement was judged to be unreliable as a result. All test materials acquired a negative charge in phosphate buffered saline (PBS). Crystalinity. X-ray powder diffraction serves as a method of positively identifying the presence of specific crystalline phases in these nanomaterials, and gives additional information regarding their relative amounts (in a mixed-phase system) and the size of the crystallites. The XRD patterns and a description of the observations made from these patterns appear in Figure S1 and Table S2 in the supplemental information, respectively (online version only). Most materials gave diffraction patterns consistent with their primary particle size, chemical composition, and purity levels from other analyses. For example, the three fullerene samples contained amorphous carbon and graphite impurities in amounts that decreased progressively from the crude to the purified material. All of the TiO2 particles show the expected phases, however only the rutile nanoparticles (TiO2_nR) were phase-pure. The two most prominent metals, Ni in MWCNTs and Co in SWCNTs (Table II), were present only in the XRD spectra of these materials (Figure S1, online version only). Determinants of FRAS biological oxidative damage (BOD) BOD and SSA. The BOD exerted by NMs was generally significantly correlated to the SSA (Pearson correlation coefficient r 0.82, p B0.01) as shown in Figure 1. The overall relationship appears to be sigmoidal, with a threshold-like BOD at the low end of the curve (SSA B300 m2 g1), increasing sharply for larger SSA values then leveling off at the highest SSA values of 1000 m2 g1. It is also obvious from the spread of the data, especially at the low end of the BOD axis, that SSA alone cannot explain all the observed variability in BOD. The relationships between SSA and FRAS were stronger within the C-based series than other materials. Strong correlations were found for the CNT series (Pearson correlation coefficient r 0.99, pB0.01), as well as carbon black (r 0.99, p B0.05) and fullerenes (r 0.98, p B0.05). For the TiO2 series, there was no association between BOD and SSA; other factors seem to be at play with these materials. BOD and transition metals. Several transition metals, especially Fe, Ni, Cr, Mn, Cu, and Zn, are known to be redox-active. The redox behavior of metals in Biological oxidative damage and nanomaterials exposures 255 Table III. Additional physico-chemical characterization of NMs tested in this study: Organic and elemental carbon (OC, EC) and surface charge, effective particle size and polydispersity index (in phosphate buffered saline [PBS]). Carbon speciationa Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Material N110 N550 N990 F-soot F-refined F-purified SWCNT_S SWCNT_L MWCNT_S MWCNT_L MWCNT-I SWCNHs-ox TiO2_nA TiO2_nR TiO2_mA TiO2_mR nAg Silica nAl2O3 OC (mg g 1) EC (mg g 1) OC/TC Electrophoretic mobility U (mm/s)/(V/cm) 3.3 3.3 3.2 43.9b 61.7b 50.7b 76.6 19.4 17.5 10.4 109.4 18.3 2.2c nad nad nad nad nad 26.8c 895.1 821.6 985.5 793.2 112.7 48.0 801.8 921.7 931.8 925.7 729.9 844.0 0.6




2.4 0.004 0.004 0.003 0.052 0.350 0.510 0.087 0.021 0.018 0.011 0.130 0.021 0.772




0.918 2.13 4.06 3.38 3.06 0.98
e 1.63 0.68 1.19 2.10 0.99 2.30 2.65 1.88 2.01 2.32 2.05 3.23 2.55 Zeta potential z (mV) Effective particle size (nm) Polydispersity 27.3 51.9 43.2 39.1 12.6
e 20.8 8.8 15.2 26.9 12.6 29.5 33.9 24.1 25.7 29.7 26.2 41.3 32.7 354 573 506 327 534 7840 491 994 806 1649 909 644 544 316 336 782 382 640 468 0.26 0.28 0.14 0.14 0.33 0.42 0.30 0.33 0.37 0.39 0.34 0.20 0.15 0.22 0.13 0.32 0.35 0.29 0.21 a Based on NIOSH Method 5040 thermal-optical analysis for C speciation; OC, Organic carbon (mg g 1 or ppm), EC, Elemental carbon; TC, Total carbonOCEC (mg g 1), OC/TC, Organic to total carbon ratio, unitless. bThe fullerene peak was excluded from the OC fraction. In the presence of the fullerene peak, the OC fraction (ppm) for F_soot, F_refined and F_purified were 69.7, 872.7 and 923.2, respectively. cThe refractory residuals for TiO2_nA and nAl2O3 were 87 and 75%, respectively. dNot analyzed, as no significant OC was expected in these samples. eThis sample did not disperse in PBS and measurements were deemed unreliable. mixtures, as is the case with multiple CNTs, is less well understood, making further analyses important. Table IV summarizes the results of correlation analyses between metal content and BOD. In addition to series or metal-specific associations, there are also some general trends. Metals most commonly associated with BOD were Fe, Cr, Co, Mo and Mn. The associations for these metals (as well as total metal content) strengthened when SWCNHs-ox were removed from the analyses (Pearson r increased from 0.5 to r 0.71; p B0.05). Mn was moderately associated with BOD (Pearson correlation coefficient r 0.6, pB0.01). These relationships were slightly stronger for the INAA results than the ICP-MS results. Zn and Zr were strongly associated only within the TiO2 series, but neither one was statistically significant (r 0.88 and 0.71, respectively; p0.05). Association of Ni with BOD was not statistically significant. No significant associations were found between soluble metal content and BOD. While initially counterintuitive, this observation may not be such a surprise given that the species distribution of Ni and other transition metals in NMs, especially CNTs, is complex, as has been documented by Liu et al. (2008, 2007). Correlation between SSA and other parameters. It is conceivable that a larger SSA may also mean more metals on the surface and hence more water soluble metals. In order to discriminate between the effects of SSA and metal contents (total and water soluble) in NMs, we investigated their correlations (Table V). Indeed, total Fe, Cr, Co, Mo, and Mn, metals that were positively associated with BOD, were also associated with SSA. Water soluble metal content did not correlate with SSA, perhaps because this fraction was generally very small and varied by material and metal species. The strong correlations between SSA and the total metal content were more evident when the SWCNHs-ox were excluded from the analyses. Apparently, SWCNHs-ox may be producing a positive FRAS result via other means. No significant generalizable associations were found for all NMs or for the TiO2 series, except for Zn in TiO2. Similarly, no significant generalizable correlations were found between OC and SSA for either the NMs as a whole or various subclasses of NMs reported here. BOD in a multivariate analysis. To further investigate the relationships between FRAS and several physicochemical parameters, each of the NMs were 256 D. Bello et al. Table V. Relationship between specific surface area (SSA) and transition metal content examined via Pearson Correlation Coefficients (r values). Metal (by ICP-MS)a Fe Cr Co Mo Mn Ni Zn Zr All NMs except All NMs SWCNHs-ox 0.24 0.33 0.25 0.32 0.19 0.07 0.12 0.13 0.72** 0.79** 0.63** 0.79** 0.6** 0.01 0.02 0.16 All carbonbased NMs except SWCNHs-ox All TiO2 materials 0.76** 0.88** 0.68* 0.88** 0.64* 0.10 0.18 0.00 0.43 0.57 0.79 0.66 0.88 0.66 0.99** 0.42 a Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Refers to analytical results obtained from acid-digestion of each material. Similar relationships were found for the INAA results. No significant relationships were found in any case between water extractable metal (by ICP-MS) and BOD and these results have been omitted. *pB0.05, **pB0.01. Figure 1. Relationship between biological oxidative damage (BOD, in TEUs, mmol l 1), as measured by the FRAS assay in NM-exposed human serum and NMs specific surface area. Error bars represent the 95% confidence interval around the mean value. classified into one of the three distinct categories based on the results of the FRAS assay: No activity (FRAS value 8.6
20.2 mM TEUs), moderate activity (31.1
165.7 mM TEUs), and high activity (706.2
1,725.4 mM TEUs). The results of the univariate analyses are summarized in Table VI. The SSA, as expected from prior analyses, was significantly associated with BOD (p 0.00): Higher SSA values were associated with greater BOD. Similarly, the Table IV. Relationship between biological oxidative damage (BOD) and transition metal content in tested NMs examined via Pearson Correlation Coefficients (r values). Metal (by ICP-MS)a Fe Cr Co Mo Mn Ni Zn Zr All NMs All NMs except SWCNHs-ox All carbonbased NMs except SWCNHs-ox All TiO2 materials 0.49* 0.63** 0.59* 0.66** 0.41 0.09 0.16 0.16 0.76** 0.89** 0.83** 0.94** 0.65** 0.06 0.10 0.15 0.71* 0.89** 0.82** 0.94** 0.60 0.16 0.07 0.30 0.14 0.03 0.35 0.16 0.47 0.18 0.88 0.73 a Refers to analytical results obtained from acid-digestion of each material. Similar statistical relationships were found for the INAA results. No significant relationships were found in any case between water extractable metal (by ICP-MS) and BOD and these results have been omitted. *pB0.05, **p B0.01. amount of several transition metals, especially Cr, Co, and Mo, was significantly associated with BOD. As expected, higher metal content resulted in a higher BOD. Fe, Mn and Ni to a lesser extend were also associated in a similar fashion, although they did not reach statistical significance. Zn, a metal that may behave as an antioxidant, was negatively associated with BOD; higher amounts of Zn tended to be found in the group generating less BOD. The association, nevertheless, did not reach statistical significance. The indexes of surface charge (Zeta potential, mobility) and OC (ppm) were not associated with BOD. The simultaneous contribution of several physicochemical characteristics of NMs to the induction of BOD were investigated using a stepwise multiple regression model. After controlling for SSA, several individual transition metals from Table V were still significant (data omitted). Since their individual contributions could not be assessed meaningfully due to insufficient statistical power and correlations between variables, concentrations of these metals (Fe, Cr, Co, Mo, and Mn) were summed to create a total metals (TMe) variable. The best model fit, with an R2 of 0.93, was: BOD (TEUs) 0:75SSA (m2 g1 )0:418TMe (ppm) Thus, 93% of the observed FRAS BOD could be explained with two key parameters: SSA and the sum content of several critical transition metals. The new data are plotted in Figure 2. Biological oxidative damage and nanomaterials exposures 257 Table VI. Results of univariate analyses exploring relationships between BOD as measured by FRAS and several physico-chemical properties of NMs, including specific surface area (SSA), metal and organic carbon (OC) content, zeta potential and electrophoretic mobility. Level of BOD (TEUs, mM) None (8.6
20.2 mM) 2 SSA (m /g) Metal content by ICP-MS Fe Cr Co Mo Mn Zn Ni OC (ppm) Zeta potential z (mV) Mobility (mm/s)/(V/cm) Moderate (31.1
165.7 mM) High (706.2
1725.4 mM) 33.9926.3 111.3933.3 559.19206.5 12.599.4 0.790.3 0.190.0 0.990.2 1.090.5 10.096.3 0.590.2 0.0590.01 28.693.4 2.290.3 104.8967.2 4.994.1 16.3914.9 44.1928.4 4.293.1 4.091.7 7219.996.4 0.0390.02 32.694.3 2.690.3 317.69158.0 179.29112.2 1521.09990.3 814.49439.9 10.995.5 4.492.6 1214.591.2 0.0390.01 18.694.4 1.590.3 p-value by ANOVA 0.00** 0.05 0.02* 0.02* 0.01* 0.05 0.05 0.05 0.05 0.05 0.05 *pB0.05, **p B0.01. Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Discussion FRAS and biological oxidative damage potential of NMs The FRAS assay for BOD potential of NMs measures total changes in the antioxidant pool of human serum and should therefore be responsive to multiple oxidative reaction mechanisms. Depletion of antioxidants may result from direct chemical attack by a range of reactive oxygen and nitrogen species, redox-active organic impurities and transition metals, surface catalytic properties, or physical removal of antioxidants from the system through formation of complexes with and adsorption on the surface of NMs. This ability to respond to several Figure 2. Relationship between biological oxidative damage (BOD, in TEUs, mmol l 1), measured as a decrease in the total pool of serum antioxidants by the FRAS assay in NM-exposed human serum, NMs specific surface area (SSA) and total (sum of Fe, Cr, Co, Mo and Mn) transition metal content by ICP-MS, TMe. Abbreviations for NMs are listed in Table I. nA, TiO2_nA; mA, TiO2_mA; nR, TiO2_nR; mR, TiO2_mR, F_s/ r/ p, Fullerene soot/refined/purified. Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 258 D. Bello et al. mechanisms that contribute to a reduction of the biological antioxidant capacity is a desirable property in a BOD screening assay. The FRAS response (both magnitude and sensitivity) to several diverse sets of NMs tested in this study is highly significant. The BOD exerted by these NMs spans three orders of magnitude on a per mass basis. The BOD trends within each category of NMs are also interesting and are indicative of the sensitivity and precision of this approach. Of particular interest are differences within the CNTs series, the high BOD induced by SWCNHs-ox, the size dependent BOD within the carbon blacks, the absence of BOD in purified fullerenes, and significantly higher BOD for TiO2-nA compared to all other TiO2 samples. The FRAS assay provides a quantitative measure of the intrinsic potential of NMs to cause oxidative damage and BOD-mediated toxicity; hence, the higher the FRAS BOD, the greater the potential for toxicity. It is logical that a negative FRAS result for BOD may not rule out potential toxicity for materials that elicit pathology by non-oxidative mechanisms and these should be captured by additional screening assays. Two important questions then follow: Does the acellular FRAS BOD predict oxidative damage in cellular and animal systems? Does a high BOD imply high toxicity? Although a detailed analysis of these questions is beyond the scope of this paper, it is of interest to note that all materials that produced a positive result by FRAS in this study, except SWCNH-ox for which there are no data, have also been confirmed to be toxic in a variety of other studies in cell culture and animals models where oxidative stress was implicated in the observed toxicity (Rogers et al. 2008a). Indeed, the elevated levels of BOD induced by all CNTs in the FRAS assay and the general order of toxicity one would expect from the BOD values have been observed in several in vivo studies (Shvedova et al. 2003, 2007, 2008; Lam et al. 2004). Jia et al. (2005) reported the following order of toxicity on a per-mass basis SWCNTs MWCNTs Quartz Fullerenes in alveolar macrophages. Much higher toxicity was reported for CNTs compared to carbon black in mice (Lam et al. 2004). NMs such as nAg, carbon black, fullerene soot, nano-TiO2 anatase, SWCNTs and MWCNTs have been shown to induce ROS generation, oxidative damage and cytotoxicity (Shvedova et al. 2003; Barlow et al. 2005; Hussain et al. 2005; Manna et al 2005; Kagan et al. 2006; Carlson et al. 2008), whereas fullerenes have not (Gharbi et al. 2005; Jia et al. 2005; Baker et al., 2008). Our findings that oxidative damage varied with particle size/specific surface area in a carbon black series, impurity content in a fullerene series and a combination of particle size/specific surface area and crystalline phase in a TiO2 series are in agreement with several other observations which have shown that fullerene soot but not purified fullerenes (Baierl et al. 1996), anatase but not rutile (Sayes et al. 2006; Warheit et al. 2007; Jiang et al. 2008) and ultrafine (nanoscale) but not micron scale TiO2 (Singh et al. 2007) and carbon black gave rise to the formation of ROS with subsequent oxidative damage (Koike and Kobayashi 2006; Foucaud et al. 2007). Micron-sized TiO2 and nano-alumina are often used as negative controls when studying NM toxicity due to their low toxicity, making the lack of BOD for these materials as detected by FRAS a consistent result as well. The high BOD of SWCNHs-ox is impressive and surprising in light of its composition and may be a result of its modified surface chemistry caused by oxidative opening of the as-produced SWCNHs via H2O2 treatment, which produces carbonyl and hydroxyl functional groups (Yudasaka et al. 2008 and our own analyses). In contrast, the as-produced SWCNHs exhibit little toxicity (Lynch et al. 2007; Miyawaki et al. 2008). The fact that crystalline silica (Min-U-Sil 5) did not induce oxidative stress in the FRAS assay is consistent with several other reports which have observed size dependent cytotoxicity without oxidative stress generation (Limbach et al. 2007; Carlson et al. 2008). However, the aging of this material (15 years from its production) may also play some role in the observed lack of BOD. The quantitative relationships between the BOD exerted by NMs as observed in the FRAS assay and the degree of toxicity in an organism remains to be determined. The data in Figure 2 suggest a possible biological threshold beyond which the BOD increases tremendously (300 m2g1 SSA or 100 ppm TMe content). While this observation is interesting, its interpretation, relationship with and significance to biological systems needs to be determined. Threshold effects have also been observed in other systems (Stoeger et al. 2006; Monteiller et al. 2007; Jiang et al. 2008) and they represent an attractive concept to pursue for several endpoints, and in particular for risk assessment purposes. The lack of significant associations with BOD of OC, surface charge, soluble metals and select total metals (such as Ni) may be due to several factors, including no real effect on BOD, lack of sufficient variability in these parameters within the set of tested NMs, small sample number (hence insufficient statistical power to detect any effects) and the acellular nature of the assay itself. Biological oxidative damage and nanomaterials exposures The FRAS assay measures absorbance of the Fe2-TPTZ complex, which results from the conversion of added Fe3 to Fe2 in the presence of residual serum antioxidants. Since Fe was present in several NMs, this raises the question of possible interferences of this Fe with the assay itself. The chemical analysis measures total Fe, not specific Fe species, and the exact amount of Fe2 is not known. Even if all soluble Fe were Fe2, this additional Fe is of the order of 50.1% of the Fe content of the assay itself, making it unlikely to introduce significant errors into the FRAS results. Furthermore, the direction of this error would be towards a null result, i.e., a smaller measured BOD value. Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Utility of FRAS for toxicity screening A hierarchical (acellular, cellular, animal) toxicity testing approach has been proposed for NMs with the measurement of ROS generation as one possible test (Balbus et al. 2007). The diversity of NMs and the desire for redundancy in the initial screening tests demand the use of several complementary assays. FRAS measured BOD has utility as an assay for rapid screening and prioritization of NMs in risk/ health assessment. By examining Figure 1, broad tiers of materials can be discerned based on the FRAS values which can be approached with different levels of priority. NMs with very high BOD, such as several CNTs are likely to exhibit high toxicity. Prevention of exposures to such materials and materials redesign to suppress this behavior should be given the highest priority. NMs with moderate oxidative damage potential, such as F_soot, carbon black (N110 and N550), nAg and TiO2_nA, would represent a second tier for which the past toxicological experience suggests that the observed adverse health effects at today’s workplace exposure levels will likely be chronic in nature. For such materials, longer-term epidemiological studies will likely be required to evaluate the nature and extent of adverse health effects in humans and the dose-response relationships. The third tier, BOD-free materials, would in general represent little toxicity (at least via BOD mechanism/s) and the emphasis should be placed on confirming the lack/ presence of toxicity by other mechanisms through other complementary tests (such as for biopersistence). Important also is documentation of the prevalence of such phenomena for a more diverse set of NMs. Crystalline silica is the only obvious material in this tested set (1/19) with no BOD and known lung toxicity and perhaps other materials may fall into this category. 259 Implications for exposure assessment of NMs The significance of oxidative stress in mediating disease has prompted several researchers to endorse a novel exposure metric concept for airborne particulate matter and NMs: Direct measurement of oxidative stress potential (Xia et al. 2006b; Borm et al. 2007; Ayres et al. 2008). This work supports the validity of this concept for engineered NMs in addition to airborne air pollution (e.g., Ntziachristos et al. 2007). Not only is BOD a biologically meaningful exposure metric, it is also superior to most other measurements because it is an integrated response to several physico-chemical parameters, including specific surface area, transition metals, redox-active organics, etc., not all of which are always measured. The finding that 93% of the observed FRAS BOD may be explained with two parameters, SSA and the sum of major transition metals (TMe) over such a broad range of NMs and the associations of metals and OC with SSA, are important from the viewpoint of exposure assessment of engineered NMs. Noteworthy is the fact that no single parameter (SSA, TMe or OC) was a sufficient global metric of BOD on its own. The SWCNHs-ox, nano anatase and CNTs represent three good illustrations of the interplay of such factors. Given the current lack of instrumentation for realtime determination of the BOD potential of airborne particulate matter or NMs, this study provides additional evidence that off-line measurements of the BOD potential of NMs should complement existing approaches to NMs exposure assessment and calls for the need to systematically measure and report SSA and metals content during NMs exposure monitoring in addition to size distribution and other specific exposure data. Conclusion This work provides evidence in support of the FRAS assay as a possible test for rapid toxicity screening of NMs based on their biological oxidative damage potential and the use of BOD as an exposure metric for characterization of airborne engineered nanoparticles exposures. The FRAS results may guide an initial prioritization of NMs for subsequent in-depth (long and expensive) animal studies, complementary screening assays, or more stringent exposure controls. It is important to realize than any screening tool has its own limits and additional mechanistic and comparative work with other test systems and testing of additional materials is warranted. Exchanging of test materials between research groups and sharing of databases will greatly facilitate such evaluative work 260 D. Bello et al. and enable development of more robust screening approaches. Acknowledgements This study was supported through the Nanoscale Science and Engineering Centers Program of the National Science Foundation # 0425826. We would like to thank the following individuals who helped with the chemical analysis: Prof. Nelson Eby (UML, INAA), Drs Maura Weathers (Cornell University, XRD), Russell Dills (UW, ICP-MS for transition metals and GC-MS for PAHs), Dr. Earl Ada and Chris Santeufemio (UML, Campus Materials Characterisation Laboratory, TEM/FE-SEM). 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629. Supplementary Material Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Table S1. Results of transition metals analysis in tested NMs by Instrumental Neutron Activation Analysis (INAA) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Legend: Me INAA; Me_d Total metal after microwave-assisted acid digestion by ICP-MS; Me_e Water-extractable metal by ICP-MS. (A) Carbon-based NMs Metal (ppm mg/g) NM Fe Fe_d Fe_e Cr Cr_d Cr_e Co Co_d Co_e Ni Ni_d Ni_e Zn Zn_d Zn_e Mo N110 22 2.41 0.30 1.04 0.15 0.05 0.05 0.33 0.05 3.8 0.40 0.19 9.59 0.35 3.06 nd 1.05 0.30 0.38 0.05 N550 42 13.1 0.30 1.11 0.44 0.05 0.28 0.22 0.19 2.1 1.22 0.39 10.7 0.29 3.38 nd 0.40 0.30 0.92 1.80 N990 26 2.81 0.20 0.3 0.10 0.05 0.02 0.10 0.05 0.3 0.10 0.05 8.26 0.20 1.81 nd 0.65 0.20 0.10 0.05 F_soot 72 5.73 0.55 0.63 0.30 0.10 0.04 0.30 0.10 1.4 0.30 0.10 20.6 7.57 0.20 nd 2.35 0.60 0.30 0.10 F_refined 24 0.90 0.15 0.29 0.15 0.05 0.02 0.15 0.05 0.4 0.15 0.05 19.2 4.63 3.00 nd 1.00 0.20 0.15 0.05 F_purified 11 nd 0.15 0.1 0.15 0.00 0.02 0.15 0.00 0.4 0.15 0.00 4.15 3.54 1.60 nd 1.20 0.15 0.15 0.00 SWCNT_S 2450 353 0.30 536 230 0.05 19582 4217 0.38 317 52.6 0.05 1202 1.12 0.79 415 1472 103 12.7 0.05 SWCNT_L 1591 741 0.30 1591 476 0.05 3519 1798 1.13 92 67.3 0.05 218 4.12 1.31 295 1672 30.8 25.3 0.11 a Mo_d Mo_e Mn_d Mn_e MWCNT_S 174 172 0.25 19.2 10.0 0.05 100 68.9 14.5 6139 4738 233 14.9 11.8 5.93 14.4 113 0.77 5.32 1.96 MWCNT_L 946 306 0.50 48.6 4.15 0.10 58.9 9.02 0.43 7518 5890 73.8 12.6 2.89 5.37 nd 155 0.55 4.69 1.33 MWCNT_I 497 0.40 49.7 33.0 0.05 74.2 120 2.79 66869 51867 43.7 15.2 8.55 3.37 11.9 192 3.41 25.9 1.67 4.74 0.20 1.15 1.03 0.05 0.03 0.10 0.05 1.3 0.53 0.05 nd 0.70 0.20 0.10 0.05 Zn_d Zn_e La La_d La_e Zr Zr_d 300 SWCNHs-ox 27 0.52 0.05 2.96 (B) TiO2 series Metal (ppm mg/g) Fe Fe_d Fe_e Cr Cr_d Cr_e Co Co_d Co_e Ni Ni_d Ni_e Zn Zr_e Mo Mo_d Mo_e Mn_d Mn_e TiO2_nA 24 8.19 0.20 1.023 0.81 0.05 0.43 0.15 0.05 nd 0.59 0.05 nd 11.9 0.47 0.99 0.49 0.05 13846 8.53 0.05 1.60 1.05 0.25 0.75 0.05 TiO2_nR 22 59.1 0.60 0.324 2.35 0.10 Nd 0.20 0.10 nd 1.13 0.10 nd 7.26 0.20 0.14 0.20 0.10 240 0.10 nd 0.65 1.03 0.10 TiO2_mA 32 2.15 0.10 0.957 0.10 0.00 0.05 0.10 0.00 4.21 0.10 0.00 4.218 0.62 0.05 0.21 0.10 0.00 141 5.63 0.00 nd 0.90 0.15 0.10 0.00 TiO2_mR 184 4.20 0.10 2.203 0.44 0.00 0.43 0.05 0.00 6.92 0.38 0.11 6.92 1.18 0.43 0.05 0.00 227 0.10 0.00 nd 0.50 0.10 0.05 0.00 Mo_d Mo_e Mn_d Mn_e 0.62 0.25 1.55 (C) nAg, crystallines silica and nAl2O3 Metal (ppm mg/g) Fe Fe_d Fe_e Cr Cr_d Cr_e Co Co_d Co_e Ni Ni_d Ni_e Zn Zn_d Zn_e La La_d La_e Zr Zr_d Zr_e Mo nAg nd 3.06 0.10 nd 0.05 0.00 nd 0.05 0.00 nd 0.05 0.00 nd 0.05 0.78 nd 0.05 0.00 nd 0.05 0.00 nd 0.20 0.10 0.66 0.00 Silica 452 0.40 0.15 1.78 1.36 0.00 0.30 0.18 0.00 70.6 1.26 0.04 6.43 5.94 1.22 2.98 1.54 0.00 29.8 3.60 0.00 nd 0.40 0.15 3.85 0.57 nAl2O3 19 8.24 0.25 0.64 0.59 0.05 0.03 0.10 0.05 0.28 0.42 0.05 37.3 47.1 37.3 0.22 0.10 0.05 112.5 80.9 0.05 nd 0.75 0.25 1.40 0.67 a nd, non-detectable. a Table S2. Summary description of XRD spectra. Material N110 carbon black N550 carbon black N990 carbon black F_soot Notes
Broad peaks present are consistent with amorphous carbon
Broad peaks present are consistent with amorphous carbon
Broad peaks present are consistent with amorphous carbon F_purified SWCNT_L SWCNT_S C60 [44
0558], Graphite [41
1487] C60 [44
0558], C70 [48
1206] C60 [44
0558]
Co [15
0806] MWCNT_L Ni [04
0850] MWCNT_S Ni [04
0850] MWCNT_I Ni [04
0850] SWCNHs-ox TiO2_nA
TiO2/anatase [21
1272], TiO2/rutile [21
1276] TiO2/rutile [21
1276] TiO2/anatase [21
1272], TiO2/rutile [21
1276] TiO2/rutile [21
1276], TiO2/anatase [21
1272] Ag [04
0783] SiO2/quartz [46
1045] h-Al2O3 [21
0010], g-Al2O3 [29
0063] and [47
1308] C60 and graphite peaks are equally weak; broad peaks also present are consistent with amorphous carbon C60 peaks are strong and sharp, C70 peaks are much weaker, weak unindexed peaks present at 2.58, 88, 98 and 168 2u C60 peaks are very strong and sharp, no other phases evident Broad peaks present are consistent with amorphous carbon Cobalt peaks are broadended and weak; other broad peaks also present are consistent with amorphous carbon Nickel peaks are broadened and very weak; other broad peaks also present are consistent with amorphous carbon Nickel peaks are broadened and very weak; other broad peaks also present are consistent with amorphous carbon Nickel peaks are broadened and similar in intensity to broad peaks also present and consistent with amorphous carbon; weak unindexed peaks present at 378 and 638 2u Broad peaks present are consistent with amorphous carbon Anatase peaks are broadened and weak, rutile peaks are much weaker and equally broad Rutile peaks are broadened and weak Anatase peaks are very strong and sharp, rutile peaks are much weaker but still sharp Rutile peaks are very strong and sharp, anatase peaks are much weaker but still sharp Silver peaks are broadened and weak Quartz peaks are very strong and sharp, no other phases evident All Al2O3 peaks are broadened, weak, and heavily overlapping; several weak unindexed peaks likely represent other phases of Al2O3 F_refined Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Crystalline phases present TiO2_nR TiO2_mA TiO2_mR nAg Silica nAl2O3 Crystalinity. X-ray powder diffraction serves as a method of positively identifying the presence of specific crystalline phases in these nanomaterials, and gives additional information regarding the relative amounts of various crystalline phases (in a mixed-phase system) and the size of the crystallites. As the former neglects the presence of amorphous materials and the latter may or may not reflect the true particle size (some particles may be monocrystalline, others not), we treat phase content and crystallite size only qualitatively. A summary of the XRD patterns observations appears in Table S2 in the supplemental information, with the appropriate JCPDF numbers given for the crystalline phases observed in the XRD patterns (Figure S1, supplemental information). The three carbon black samples give diffraction patterns consistent with amorphous carbon and not indicative of any other phases present, as would be expected. The three fullerene samples show distinct peaks associated with specific fullerenes in the crystalline form, with evidence of the presence of amorphous carbon and graphite impurities disappearing when moving from crude to refined to purified fullerene soot. The carbon nanotube samples vary in nature, with only the long SWCNT (SWCNT_L) showing a diffraction pattern devoid of any obvious crystalline metal impurities and quite similar to the carbon black diffraction patterns. The short SWCNTs (SWCNT_S) show a weak but observable cobalt peak, probably indicative of fine cobalt catalyst particles, given its broadness. Likewise, all three MWCNTs samples (MWCNT_S, _L, and _I) show peaks consistent with the presence of crystalline nickel, very weak in the case of the long and the short MWCNTs (MWCNT_S and -L) but substantially more evident in the case of the industrial MWCNTs (MWCNT_I). The SWCNHS-ox gives a diffraction pattern consistent with the carbon black samples, the Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 SWCNTs and amorphous carbon, and with no evidence of crystalline phases present. These results are consistent with metal analyses as well, with Ni and Co peaks being prominent in the samples with the highest Ni and Co contents detected via elemental analysis. For example, Ni is present in higher concentrations in the MWCNT_I (5.2%) whereas Co in SWCNT_S (0.4%, Table S1). All of the TiO2 particles show the expected phases, however only the rutile nanoparticles (TiO2_nR) are phase-pure by X-ray diffraction. All of the other titanium TiO2 particles contain some amount of both anatase and rutile. Consistent with what is known of their particle sizes, the titanium dioxide nanoparticles show much broader diffraction peaks than their microscopic particles counterparts. As expected, Min-U-Sil 5 gives a very clean diffraction pattern consistent with large particles of crystalline silica (quartz). The alumina nanoparticles, on the other hand, give rise to a very complex diffraction pattern, and appear to consist of a mixture of at least two phases of alumina, potentially more, though the broadening of the peaks, expected in a nanoparticulate material, makes it difficult to effectively deconvolute contributions from all of the various alumina phases that may be present. The diffraction pattern of nAg was completely consistent with their size and composition
broadened, weak peaks associated with crystalline silver
with no evidence of the presence of any other crystalline phases. Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Downloaded By: [Weltin, Heather] At: 21:20 6 September 2009 Figure S1. XRD spectra of tested materials with the appropriate JCPDF numbers given for the crystalline phases observed in the XRD patterns.