J Nanopart Res (2010) 12:551–562 DOI 10.1007/s11051-009-9673-3
RESEARCH PAPER
Economic assessment of single-walled carbon nanotube processes J. A. Isaacs Æ A. Tanwani Æ M. L. Healy Æ L. J. Dahlben
Received: 11 September 2008 / Accepted: 29 May 2009 / Published online: 30 June 2009 Ó Springer Science+Business Media B.V. 2009
Abstract The carbon nanotube market is steadily growing and projected to reach $1.9 billion by 2010. This study examines the economics of manufacturing single-walled carbon nanotubes (SWNT) using process-based cost models developed for arc, CVD, and HiPco processes. Using assumed input parameters, manufacturing costs are calculated for 1 g SWNT for arc, CVD, and HiPco, totaling $1,906, $1,706, and $485, respectively. For each SWNT process, the synthesis and filtration steps showed the highest costs, with direct labor as a primary cost driver. Reductions in production costs are calculated for increased working hours per day and for increased synthesis reaction yield (SRY) in each process. The process-based cost models offer a means for J. A. Isaacs (&) A. Tanwani M. L. Healy L. J. Dahlben NSF Center for High-rate Nanomanufacturing, Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA e-mail:
[email protected] J. A. Isaacs Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA Present Address: A. Tanwani Infojini Solutions Inc., Maryland, USA Present Address: M. L. Healy Babcock Power Inc., Worcester, MA, USA
exploring opportunities for cost reductions, and provide a structured system for comparisons among alternative SWNT manufacturing processes. Further, the models can be used to comprehensively evaluate additional scenarios on the economics of environmental, health, and safety best manufacturing practices. Keywords Single-walled nanotube (SWNT) Nanotubes Manufacturing Economics Production cost
Introduction Since the inception of the National Nanotechnology Initiative (NNI) in 2001, tremendous investment has been afforded to research involving various aspects of nanotechnology. The United States federal funding of nanotechnology research and development (R&D) went from $464 million in 2001 to $1,425 million in 2007 (NNI 2008). In addition, governments, corporations, and venture capitalists worldwide spent $9.6 billion on nanotechnology R&D in 2005, up 10% from 2004 (Lux Research 2006). The global carbon nanotube (CNT) market is projected to exceed $1.9 billion by 2010, and the single-walled carbon nanotube (SWNT) market is projected to exceed $5 billion by 2012 (Lux Research 2006). Furthermore, advances in nanoscience have led to steady increases in
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Other 3%
Electron emission 25%
Synthesis and processing 41%
Sensors and probes 3% Electronics Composites 6% Hydrogen storage 9% 6%
Fig. 1 Carbon nanotube patent organization by industry (Baughman et al. 2002)
publications and patents involving practical application development. From 1985 to 2001, a total of 3,966 U.S. nanotechnology patents were issued, the majority of which lie in synthesis and processing of carbon nanotubes, as shown in Fig. 1. Table 1 provides information on companies producing SWNTs. The information was gathered from literature, company web sites, and other internet sources. Most of these companies produce CNTs in small batch quantities. The variations in price are attributed to differences in production locations, impurities, and products. A more complete, detailed list of all carbon nanotube companies and research institutes can be found in market research reports such as Global Industry Analysts (2007). Carbon nanotubes have distinct electrical and mechanical properties which make them desirable in industrial applications. Such properties include superconductivity (Kociak et al. 2002), sustainable high current densities (Hamada et al. 1992), high thermal conductivity (Berber et al. 2000), and high tensile strength (Treacy et al. 1996). Hence, CNTs have great potential to be used in a variety of applications such as structural polymers, super capacitors, energy conversion, batteries, nanoprobes, sensors, and shielding. With this wide range of CNT applications it is important to understand the production cost drivers for development of commercially viable nanomanufacturing. By evaluating the economic drivers of CNT production, researchers and system developers can work toward optimizing production conditions and processes. The economic models developed through this research serve as a
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foundation for development of environmental footprints and assessment of cost trade-offs in process design for subsequent fabrication involving CNTs. This study compares the economics of three SWNT production processes: arc ablation (arc), chemical vapor deposition (CVD), and high pressure carbon monoxide (HiPco). The synthesis processes are briefly described, as well as development of the process-based cost models, input parameters, and assumptions. The models are used to calculate the total manufacturing cost of SWNT production and allow investigation of changes to base case assumptions to determine cost drivers. The sensitivity of select process parameters is also reported.
Process-based cost modeling Economic assessment is carried out using processbased cost modeling, whereby costs are categorized into a comprehensive set of cost elements (Busch 1994; Clark et al. 1997; Chiango et al. 2000; Kirchain 2001) to indicate the economic competitiveness of operational factors in a particular process and to compare alternative manufacturing processes for the same product. These models capture relationships among various process variables to determine the fixed and variable costs of manufacturing operations. Unlike other cost systems prevalent in industry where the manufacturing overhead is allocated on the basis of direct labor or machine rent, process-based cost models break down manufacturing overhead into individual process steps, providing a more detailed cost assessment and an ability to explore how costs change as input parameters change. Typical cost elements include materials, labor, energy, capital equipment, tooling, building space, and maintenance. Cost model development consists of four steps: definition of the process steps, construction of the model logic and framework, collection of information, and validation of the model. Definition of the process steps establishes the major sequential steps in the process and identifies associated activities that need to be included. Construction of the model logic and framework consists of a series of equations that relate input factors to intermediate computed values and finalized cost elements. Collection of information is performed through person-to-person contact, literature, and derived data. Validation of the model
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Table 1 Information on current SWNT manufacturers Company name (Location)
Founded Process
% Purity CNT
Price per gram
Websitea
Materials and Electrochemical Research Corporation, MER (Tucson, AZ)
1985
12%
$60
www.mercorp.com
Arc
BuckyUsa (Houston, TX)
1992
Unknown
Not purified
$250
www.buckyusa.com
HeJi, Inc. (Hong Kong)
1996
CVD
[60%
$190
www.nanotubeseu.com
[90%
$275
Carbolex (Lexington, KY)
1998
Carbon Solutions Inc. (Riverside, CA)
1998
Unidym Inc. (Menlo Park, CA)
2000
Arc
50–70%
$100
www.carbolex.com
Arc
70–90% 40–60%
$800 $50
www.carbonsolution.com
70–90%
$400
[65%
$375
[85%
$500
[95%
$2,000
HiPco
www.cnanotech.com
Hanwha Nanotech (Seoul, Korea)
2000
Arc
60–70%
Unknown
http://hnt.hanwha.co.kr/en/ home.html
NanoLab, Inc. (Newton, MA)
2000
Arc
[50%
$900
www.nano-lab.com
[90%
$1,750
[50%
$210
[90%
$395
Nanoamor (Los Alamos, NM) Nanocarblab (Moscow, Russia)
2001
www.nanoamor.com
Arc
40–50%
$60
www.nanocarblab.com
CVD, Arc
80% Unknown
$380 $160
www.nanocs.com
Shenzhen Nanotech Port Co., Ltd. 2001 (Shenzhen, China)
CVD
50–80%
Unknown
www.nanotubes.com.cn
SouthWest NanoTechnologies, Inc. (Norman, OK)
Catalytic method (CoMoCATÒ)
[90%
$500
www.swnano.com
Nanocs Inc. (New York, NY)
2001
CVD
2001
2001
MicrotechNano (Indianapolis, IN)
2002
Unknown
[92%
$132
www.microtechnano.com
Nanocyl (Sambreville, Belgium)
2002
CVD
[80%
$510
www.nanocyl.com
Apex Nanomaterials (San Diego, CA)
2003
Arc
[50–80%
$28
www.apexnanomaterials.com
Helix Material Solutions (Richardson, TX)
2003
CVD
www.helixmaterial.com
NanoCraft, Inc. (Renton, WA)
2003
Raymor Industries Inc. (Montreal, Canada)
50–70%
$83
[90%
$210
CVD
[60%
$35
www.nanocraftinc.com
2004
Hybrid of CVD, arc processes
Unknown
Unknown
www.raymor.com
Cheap Tubes, Inc. (Brattleboro, VT)
2005
CVD
[50%
$40
www.cheaptubesinc.com
[90%
$150
Sun Nano (Freemont, CA)
2006
CVD
[95%
$250
www.nanomaterialstore.com
Nano Integris, Inc. (Evanston, IL) Carbon Nanotube & Fiber 21. (Austria)
2007
Unknown Unknown
[99% [90%
$7,000 $105
www.nanointegris.com www.carbon-nanofiber.com
a
All websites last accessed September 2008
compares the outputs with known or expected values. Results from process-based cost models can allow informed decision making before investing in a
prototype or pilot production process. For emerging or developmental technologies, cost models can indicate the cost drivers and process parameters that may
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Synthesis Purification Dispersion, Acid Reflux, Filtration
Inspection Packaging Fig. 2 SWNT production process steps
require additional development before the process would become economically viable. This methodology was used to develop process-based cost models for arc, CVD, and HiPco SWNT production processes.
Description of processes and model assumptions Production of SWNTs consists of the following steps: synthesis, purification, inspection, and packaging, as shown in Fig. 2. The synthesis methods analyzed in this study include arc, CVD, and HiPco. Although the carbon nanotube products that result from each process are likely to have different attributes, these processes were selected for comparison because they are the most widely used CNT fabrication processes. Most input parameters for purification, inspection, and packaging steps remain consistent among the three synthesis processes, however, the purification yield varies for each process. Purification includes Table 2 Key assumptions for arc, CVD, and HiPco processes
dispersion, acid reflux, and filtration. Some of the key assumptions used to calculate the total cost of production for each production process are shown in Table 2. These parameters represent assumptions based on discussions with experts for the scale-up of lab-scale processes. The synthesis reaction yield (SRY) represents the amount of carbon product divided by the total amount of carbon entering the system. The synthesis product yield (SPY) represents the relative amount of carbon nanotubes expected in the converted carbon. The purification yield indicates the percent of SWNTs removed from the carbon product out of the total SWNTs created from the synthesis step. Purification yields are 70%, 90%, and 90% for the arc, CVD, and HiPco processes, respectively. The difference in yields is due to the varying quality of input material and catalyst compositions for each synthesis method. Along with the key process assumptions, exogenous assumptions were used in the process-based cost models, shown in Table 3. Industrial U.S. electricity is assumed to cost $0.10 kWh. The U.S. electric power mix assumed is dominated by coal (49.0%), natural gas (20.0%), nuclear (19.4%), and hydroelectric (7.0%) fuel sources (EIA 2007).
SWNT process descriptions Arc synthesis The arc method generates an assortment of carbonaceous products through arc vaporization and requires Arc
Production volume
CVD
HiPco
10,000 g/year
Working days per year
365 days/year
Working hrs per day
8 hrs/day
Synthesis reaction yield (SRY)
4.50%
2.95%
0.08%
Synthesis product yield (SPY)
60%
70%
97%
Purification steps
(1) Dispersion: Triton detergent & sonication (2) Acid reflux
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Purification yield
(3) Filtration 70%
% Batches inspected
10%
Packaging bottle size
10 g
90%
90%
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Table 3 Exogenous assumptions for arc, CVD, and HiPco processes Electricity cost
$0.10/kWh
Direct labor cost
$20/h
Building space rent
$13/sqft/ year
Inspection equipment rent
$33/h
Opportunity cost of capital
20%
Auxiliary equipment (% of main equipment cost) 10% Installation (% of main equipment cost) Overhead burden (% of direct labor cost)
2% 40%
Tools (% of main equipment cost)
25%
Maintenance (% of total investment on equipment)
5%
Table 4 Arc synthesis assumptions and input parameters Synthesis reaction yield
4.5%
Synthesis product yield
60%
Purification yield
70%
SWNT material production rate
0.081 g/h
Total processing time per batch
1.15 h
Helium gas pressure
77.3 kPa
Helium gas per batch
6.80 g
Furnace temperature
300 K
Electrode distance
1.00 mm
Catalyst composition
66.09% Fe, 16.67% Y, 8.91% S, 8.33% C
Catalyst per batch Anode rod mass
0.80 g 6.62 g
Cathode rod mass
27.0 g
additional purification to remove byproducts from the SWNTs (Daenen et al. 2003). During the process, two graphite rods act as electrodes during vaporization. The anode gradually moves toward the cathode until an arc appears, and after stabilized, the anode– cathode distance is maintained at 1 mm. The catalyst increases the yield of SWNTs and consists of a mixture of Fe, Y, S, and C (Tanaka et al. 1999). The process takes approximately one minute, after which the chamber is depressurized and opened to reveal nanotubes deposited throughout the chamber. A powdery black material covers the wall and window in the form of a web of SWNTs and a hard gray collar surrounds the cathode. These products contain the highest quantities of SWNTs, and this material proceeds to purification. Further details are presented
in other literature (Harris 1999; Tanaka et al. 1999; Flahaut et al. 2000; Daenen et al. 2003). Table 4 presents the key arc synthesis assumptions, with additional information in Healy et al. (2006) and Tanwani (2005). Using values from Table 4, approximately 28% of the carbon anode evaporates in the synthesis process. The synthesis reaction yield (SRY) is 4.5% and represents the amount of web-like product created on the cathode over the total amount of carbon placed in the reaction chamber. The synthesis product yield (60%) corresponds to the amount of SWNTs in that ‘‘usable’’ web product, which includes multi-walled carbon nanotubes (MWNT) and other products. The SWNT material production rate represents the amount of SWNTs produced over the total synthesis process time. The total duration of the synthesis process is 1.15 h/batch, which includes time for catalyst preparation, setup, processing, product removal, and furnace cleaning. The cathode rod is reused for each batch, however the anode must be replaced each time. CVD synthesis The CVD synthesis process uses hydrogen and argon as carrier gases, methane as the carbon source, and a catalyst powder made of ammonium molybdenum tetrahydrate, magnesium nitrate hexahydrate, cobalt nitrate hexahydrate, and citric acid. The annealed catalyst is placed in a furnace and methane gas is pumped through a quartz tube for 30 min. This growth process yields SWNTs, MWNTs, and other carbon products, which must be purified to obtain the SWNTs. Additional information regarding the CVD process is gathered from other literature sources (Tanaka et al. 1999; Flahaut et al. 2000; Tang et al. 2001; Zheng et al. 2002; Seo et al. 2003; Liu et al. 2004). Table 5 lists the key CVD synthesis assumptions (Tanwani 2005; Healy 2006). The synthesis reaction yield corresponds to the amount of carbon product created during CVD synthesis divided by the amount of methane pumped into the furnace. The helium and argon carrier gases are assumed to flow at 200 sccm for 1 h, resulting in 0.98 g of helium and 19.47 g of argon per batch. The assumed methane flow rate is 50 sccm for 30 min, which results in 0.98 g of methane used per batch. The synthesis product yield represents the mass of
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Table 5 CVD synthesis assumptions and input parameters
Table 6 HiPco synthesis assumptions and input parameters
Synthesis reaction yield
2.95%
Synthesis reaction yield
0.08%
Synthesis product yield
90%
Synthesis product yield
97%
Purification yield
90%
Purification yield
90%
SWNT material production rate
0.0098 g/h
SWNT material production rate
0.45 g/h
Total processing time per batch
2.95 h
Argon gas per batch
45.87 g
Helium gas pressure
101.3 Pa
Internal furnace temperature
1323 K
Hydrogen gas per batch
0.98 g
Fe(CO)5 catalyst flow rate
0.034 g/h
Argon gas per batch
19.47 g
CO catalyst flow rate
3.763 g/h
Furnace temperature
300 K
CO initial flow rate
162.5 g/h
Catalyst composition
95.54% Mg, 0.57% Co, 3.82% Citric acid, 0.07% NH4?
CO use rate
0.45 g/h
CO recycling
Yes
Catalyst per batch
0.08 g
Methane per batch
0.98 g
SWNTs within the carbon product, which was assumed to be 90%. The SWNT material production rate represents the amount of SWNTs produced over the total CVD processing time, which is 2.95 h/batch and includes time for catalyst preparation, initial temperature heating, final temperature heating, growth, cooling, and removal. If only the growth time were considered, the SWNT rate of production would be 0.058 g/h, which is growth production rate reflected in the literature. HiPco synthesis In the HiPco process, developed by Smalley at Rice University, a combination of Fe(CO)5 and CO catalyst is injected into a reactor at approximately 1.4 l/min, traveling through a stainless steel watercooled injector tip. Carbon monoxide (CO) at high temperature is injected into the system through a set of orifices positioned in a circular pattern around the injector tip (Bronikowski et al. 2001). This showerhead consists of a thick graphite tube, through which six channels have been longitudinally bored in the wall. The CO and Fe(CO)5 mixture rapidly heats and mixes as it passes through the shower of CO. Iron atoms condense into clusters and serve as a catalyst upon which the SWNTs nucleate and grow. The SWNTs and iron particles propagate through the reactor by the hot, dense gas flow into the product collection apparatus. The CO gas recirculates back through the gas flow system and reactor using a compressor. The product contains Fe particles and
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other byproducts and requires subsequent purification. Table 6 provides the key HiPco synthesis assumptions (Tanwani 2005; Healy 2006). The gaseous material usages are calculated using ideal temperature and pressure values. The catalyst, comprised of Fe(CO)5 and CO gases, flows at rates of 0.034 and 3.763 g/h, respectively. The inert gas (argon) acts as a barrier between the quartz tube and aluminum outer shell. Unlike arc and CVD, the HiPco process runs continuously, allowing the reuse of CO gas and longer runtimes. Without recycling CO, the synthesis reaction yield is 0.01%. With recirculation, the amount of CO required is reduced from 162.5 g/h to 0.45 g/h, improving the synthesis reaction yield to 0.08%. The purity of the product created, the synthesis product yield, has a value of 97%. The HiPco process continuously produces SWNTs at a rate of 0.45 g/h (Nikolaev et al. 1999). Purification, inspection, and packaging The purification process consists of three steps: dispersion of synthesis product, acid reflux of synthesis product, and filtration. Since each carbon nanotube synthesis process has different synthesis reaction yields, purification yields, and chemical impurities, the number of batches and setups vary for each process’ purification step. The overall purification yields for each synthesis process are noted in Table 2. A combination method of Triton X100 detergent and pre-sonication with probe was assumed for dispersion. A mixture of 0.01 ml of Triton X100
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solution and 0.08 l of deionized water (DI H2O) was assumed for processing 1 g of carbon product, with a total processing time of 1.167 h. In the acid reflux step, 0.4 l of nitric acid is added to 0.8 l DI H2O and 1 g of dispersion product, refluxing for 10 h. Since the amount of carbon product per batch from dispersion to acid reflux is constant, so too are the number of batches. However, due to the increase in processing time, acid reflux requires more processing lines than dispersion to maintain throughput. Filtration was performed through a direct filtration method, which uses 0.8 l DI H2O and 1 polytetrafluoroethylene (PTFE) membrane over 20 min of processing time. Because the amount of carbon per filtration batch is 0.2 g (20% of the dispersion or acid reflux carbon product), filtration requires more batches and lines than other steps in the purification process and requires five runs to achieve the desired production volume. The throughput rate of one synthesis production line for any of the three processes (arc, CVD, or HiPco) is calculated as follows: Throughput ¼ Synthesis product yield Purification yield SWNT material production rate ð1Þ where the synthesis product yield and purification yield are percentages and SWNT material production rate is in [g/h]. The resulting throughput of one synthesis line for arc, CVD, and HiPco is approximately 0.034, 0.008, and 0.38 g/h of purified SWNTs, respectively. In order to determine the number of lines of equipment required for each process, the annual production volume (10,000 g SWNT, running 8 h/day) is divided by the throughput for a single line. Since each production method has different throughput rates, the number of lines required to be calculated would also differ: arc requires 101 lines, CVD requires 433 lines, while HiPco requires 9 lines of equipment. These numbers (assumed here for the subsequent calculations) are likely less efficient than for existing larger scale producers, because these equipment line assumptions reflect scaled-up lab bench processes and were based on relatively small batches. Comparison of these base case assumptions with 24/7 operation is mentioned in the discussion section.
After purification, inspection is performed using SEM and TEM equipment, where it is assumed that 10% of the production volume is assessed for its quality. Low volume, high quality application packaging follows, assuming 10 g bottles that cost $1 each.
Results: comparison of manufacturing costs for SWNT production The results from the cost models represent a high volume, industrial scenario. Figure 3 illustrates the results by breaking the cost down both by process step (a–c), and by fixed and variable costs (d–f) for arc, CVD, and HiPco processes. Arc cost analysis The manufacture of SWNT by the arc process results in a cost of $1,906/g SWNT. The complete synthesis time is 1.15 h/batch and approximately 250,000 batches are required for a production volume of 10,000 g. With a rate of $20/h, the total cost of labor is just under $6 million, or $600/g for the synthesis step. The time intensity assumed for synthesis batch processing results in very high direct labor costs, as indicated in Fig. 3d. Figure 4 shows the relationship between production volume [g/year] and production cost [$/g], with the assumed production volume of 10,000 g shown by the vertical dashed line. The graph illustrates that the production cost plateaus after a production volume of approximately 15,000 g/year. In Fig. 5, the sensitivity of the input parameters anode rod mass, purification yield, SRY, filtration batch time, synthesis batch time, and direct labor cost are explored. The x-axis varies the input quantity by ±50% of its base case assumed value. The y-axis represents the original base case cost divided by the new manufacturing cost generated by changing the input parameter, with the base case represented at (0,0) on the graph. The parameters with greater slopes show a greater impact on the overall cost. Filtration batch time, synthesis batch time, and direct labor cost are all positively sloped and relate linearly with the cost. The trend lines for direct labor cost and synthesis batch time almost coincide, where a 50% decrease in parameter value results in a 30% decrease
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in cost. Filtration is not as sensitive because a 50% decrease in filtration batch time results in only a 10% reduction in cost. The variables with negative slopes show a more polynomial relationship with the cost. A 10% decrease in the anode mass results in approximately a 30% increase in the total cost, whereas a 10% increase in mass results in an approximate 15% cost decrease. CVD cost analysis The results for CVD production indicate manufacturing costs at $1,706/g SWNT. The synthesis process step dominates at 79.6% of the total CVD process cost, as indicated in Fig. 3b. The filtration step comes in at a distant second at 14.3%, again Fig. 3 Cost contributions from each process step (a–c) and fixed and variable cost contributions (d–f) for arc, CVD, and HiPco processes
Packaging 0.1% Inspection 2.4% Filtration 24.6%
mostly due to direct labor costs. Figure 3e shows that the direct labor cost dominates at 38.4%. Fixed equipment and fixed overhead closely follow at 23.3% and 15.4%, respectively. The high direct labor costs are due to the numerous batches required in the synthesis step. Each batch takes approximately 35 min to process and 430,000 batches are required, so with the cost of labor at $20/h the direct labor cost is $5 million, or $500/g for the synthesis step. Figure 6 shows the sensitivity of purification yield, SRY, filtration batch time, direct labor cost, and synthesis batch time. The positively sloped variables, filtration batch time, direct labor cost, and synthesis batch time, exhibit a linear behavior with increasing slopes with respect to cost. The filtration batch time only slightly affects the cost: when varying it by 50%,
Installation Cost 0.3%
Acid Reflux 4.4% Dispersion 1.2%
Synthesis 67.2%
Installation Cost 0.6%
(b) Packaging 0.2%
Filtration 49.6%
Direct Labor 38.4%
Auxiliary Equipment 2.9%
Synthesis 79.6%
Inspection 8.9%
Energy 0.5%
Maintenance Cost Fixed Overhead 1.4% Raw Material 15.4% 4.2% Building Cost 0.1% Tools 7.1%
Dispersion 0.7%
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Variable Equipment 1.3%
Direct Labor 45.6%
CVD $1,706/g SWNT
Acid Reflux 2.6%
(c)
Auxiliary Equipment 1.6% Fixed Equipment 14.6%
(d)
(a) Packaging 0.1% Inspection 2.7% Filtration 14.3%
Fixed Overhead 18.2% Maintenance Cost Building Cost 0.8% 1.0% Raw Material Tools 12.0% 4.0%
Arc $1,906/g SWNT
(e)
Energy Fixed Equipment 1.4% 27.0% Variable Equipment 1.5%
Fixed Overhead Maintenance Cost 1.4% 12.4% Building Cost Raw Material 0.2% 15.2% Tools 7.1% Installation Cost Direct Labor 0.6% 30.9%
HiPco $485/g SWNT Synthesis 30.2%
Dispersion 2.4% Acid Reflux 8.7%
Auxiliary Equipment 2.9% Energy 0.8%
Fixed Equipment 23.3%
(f)
Variable Equipment 5.2%
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cost decreases of approximately 22%, whereas a 30% decrease in yield results in a 40% cost increase. An increase in the SRY by 30% allows a cost reduction of almost 20%, while a 30% reduction in synthesis reaction yield causes a 35% cost increase.
$1,970
Production Cost [$/g]
$1,960 $1,950 $1,940 Base Case
$1,930 $1,920
HiPco cost analysis
$1,910 $1,900 0
5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000
Production Volume [g/yr]
Fig. 4 Arc production volume vs. cost
50%
Purification Yield SRY
% Change of Cost
30% 10% 0% -10%
Filtration Batch Time Synthesis Batch Time Direct Labor Cost
-30% Anode Rod Mass
-50% -50%
-10% 0%
-30%
10%
30%
50%
% Change of Parameter
Fig. 5 Sensitivity analysis of assumptions in arc SWNT cost
50% Purification Yield SRY
% Change of Cost
30% 10%
The HiPco process results in the most economical SWNT at $485/g. The results for the process step cost investigation (Fig. 3c) indicate that the filtration step contributes the largest cost at 49.6%, followed by the synthesis step at 30.2%. Within HiPco, the greatest cost contributor is direct labor at 30.9%, as shown in Fig. 3f. Because the HiPco synthesis process runs continuously, its percentage of direct labor cost remains lower than that of arc or CVD. A sensitivity analysis of the HiPco process assumptions is shown in Fig. 7. The positively sloped lines that behave linearly with the production cost are filtration batch time and direct labor cost. They correspond closely to each other, where an increase of 30% results in an approximate cost decrease of 12%. The negatively sloped purification yield and synthesis production rate have more of a polynomial shape. The purification yield, when increased by 30%, creates a decrease in cost by 21%, whereas a decrease of 30% results in an increase of 40%. A 30% decrease in the synthesis production rate coincides with a cost increase of approximately 15%; however a 30% increase corresponds to an 8% decrease in cost.
0% -10%
Filtration Batch Time Direct Labor Cost
50%
-30%
Purification Yield Synthesis Batch Time
-30%
-10% 0%
10%
30%
50%
% Change of Parameter
Fig. 6 Sensitivity analysis of assumptions in CVD SWNT cost
the cost increases by about 5%. When the direct labor cost increases by 50%, the cost rises by 30%. When the synthesis batch time decreases by 30%, the cost reduces by 25%. The negatively sloped input parameters behave in a more polynomial fashion. The purification yield, when increased by 30%, results in
% Change of Cost
-50% -50%
30% 10% Synthesis Production Rate 0%
Filtration Batch Rate
-10% -30%
Direct Labor Cost
-50% -50%
-30%
-10% 0%
10%
30%
50%
% Change of Parameter
Fig. 7 Sensitivity analysis of assumptions in HiPco SWNT cost
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Discussion Calculated manufacturing costs from cost models with base case assumptions indicate total manufacturing costs for arc, CVD, and HiPco at $1,906/g, $1,706/g, and $485/g, respectively. Comparison of these processes indicates that HiPco is the most economically viable for bulk production of high purity SWNTs. This result is not unexpected, given that HiPco is a continuous process that results in a higher synthesis yield due to recirculation of CO. In the base case for each process, a production rate of 8 h/day for 365 days is assumed. These assumptions are modified to assume a ‘‘best case’’ scenario, with the production rate increased to 24 h/day for 365 days. The effect of increasing the production hours per day from 8 to 24 h for each process is shown in Fig. 8, which compares cost reductions for the arc, CVD, and HiPco processes. The x-axis reflects the production volume range from 0 to 50,000 g/year and the y-axis shows the corresponding cost per gram for each process. For the production of 10,000 g SWNTs per year, arc production costs decreased from $1,906 to $1,631/g SWNT. The production costs for the CVD process also decreased from $1,706 to $1,271/g. The increase in working hours per day slightly reduced HiPco production costs, from $485 to $377/g. The SRY represents the quantity of SWNTs produced per batch for arc and CVD and per hour for HiPco. The higher the yield, the less time required to reach the desired production volume. The best imaginable SRY assumed by experts for modifications to existing arc and CVD processes is 20%. The $2,000
Arc Base Case
Production Cost [$/g]
$1,800
CVD Base Case Arc 24 hr/day
$1,600 $1,400
CVD 24 hr/day
$1,200 Base Case Production Volume
$1,000
Arc 20% SRY
$800 $600
CVD 20% SRY HiPco Base Case
$400
HiPco 24 hr/day, 46.4% SRY
$200 0
5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000
Production Volume [g/yr]
Fig. 8 Arc, CVD, and HiPco synthesis cost effect of base versus best working hours per day and SRY
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HiPco process SRY depends upon the number of days of continuous operation, and with the base case assumption of 8 h/day production, the resulting SRY is 0.08%. The best case SRY for HiPco assumes continuous 24 h/day production, which creates a continuous run time of 8,760 h and thus a SRY of 46.4%. The effect of the improved SRY on the process economics is also shown in Fig. 8. Although the arc process model with base case assumptions of 4.5% SRY resulted in manufacturing costs of $1,906/g, if it were technically feasible to increase the yield to 20%, then the cost could decrease to $910/g. For changes in the CVD SRY assumptions from base (2.95%) to best expected yield (20%), a significant decrease would result in the production cost from $1,706/g to $548/g. For the HiPco process model, the SRY is calculated using the number of working hours. Increases in working hours each day from 8 h to 24 h results in an increase in SRY to 46.4%, and would reduce the calculated HiPco SWNT product cost from $485/g to $377/g. Results from the three cost models were compared with publically available prices for commercially available SWNTs in Table 1. The purification percentage for SWNTs directly correlates to cost increases, although in most cases, the commercial SWNT purification rates barely reach 80%. For arc processes, the trends in Table 1 indicate higher prices for higher purity, with a price of $1,750 for greater than 90% purity. Given that the exact arc manufacturing practices are unknown for this manufacturer, this price compares reasonably well with costs calculated for the base case and the three shifts per day scenarios. For SWNTs produced by CVD processes, prices in Table 1 range from $150 to $395 for purities of at least 90%, (with higher prices for higher purity expected). These prices are significantly lower than the costs predicted for all scenarios by the CVD cost model; however with the exact manufacturing practices unknown and only prices for lower product purity provided, it is unclear which manufacturing scenarios these prices reflect. HiPco processes are touted as delivering the greatest purity for the lowest costs, and offer the highest purity SWNTs available on the market. With SWNT purity ranging from 85% to greater than 95%, prices can range from $500/g to $2,000/g. The manufacturing costs resulting from the HiPco cost model reflect a reasonable correlation, with the difference attributable to costs associated
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with increased inspection processes to ensure higher purities. Although results from the cost models are not intended to predict exact manufacturing costs and do not include estimates of profit margins, the results provide insight to the cost drivers for arc, CVD, and HiPco SWNT synthesis processes.
Conclusions The economic feasibility of manufacturing is essential for scale-up of nanomanufacturing technologies. Separate process-based technical cost models were developed for three of the more established SWNT manufacturing processes. For arc, CVD, and HiPco processes, manufacturing cost per 1 g SWNT were estimated for sets of base case assumptions, and calculated at $1,906/g, $1,706/g, and $485/g, respectively. Though costs and process assumptions are not divulged by existing producers, the modeled manufacturing costs appear to remain within the range of the list prices shown in Table 1. As it is a continuous process with recirculation of CO, the HiPco process shows the lowest costs. The cost of each SWNT production process was dominated by the direct labor costs associated with the synthesis and filtration steps. Increased working hours per day and increased synthesis reaction yields could significantly reduce the production costs, assuming yield improvements are possible. The process-based cost modeling methodology proved useful for assessing the most sensitive areas for cost reduction and production increase of competing processes. Process-based technical cost models typically track the materials, energy, equipment, and labor costs, but the models can also include tangible process costs for various industrial hygiene and waste disposal practices to explore the ramifications of process changes. Incorporation of environmental costs in this way offers powerful tools for evaluating alternative materials, processes, and manufacturing technologies, especially in light of the uncertainties of the potential environmental health and safety (EHS) risks associated with exposure to engineered nanoparticles. Although the cost models cannot provide definitive answers to addressing economic and environmental health and safety tradeoffs, meaningful information is generated by the cost models that can provide insight on available alternatives.
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Information on improving the environmental attributes of SWNT production processes has been reported (Healy et al. 2008), and subsequent utilization of decisions analysis/risk assessment techniques has also provided insights (Ok et al. 2008). Implementation of these assessment tools can furnish process designers with an accessible means for comparing alternative nanomanufacturing scenarios. Given the EHS uncertainties associated with engineered nanoparticles, modeling tools can be developed to address the responsible commercialization of nanomanufacturing processes. Acknowledgments This study was supported in part by National Science Foundation awards SES-0404114 and EEC0425826 through the Nanoscale Science and Engineering Center for High-rate Nanomanufacturing at Northeastern University. The authors thank Zeynep Ok for discussions and her contributions to Table 1.
References Baughman RH, Zakhidov AA et al (2002) Carbon nanotubes–– the route toward applications. Science 297(5582):787– 792. doi:10.1126/science.1060928 Berber S, Kwon Y-K et al (2000) Unusually high thermal conductivity of carbon nanotubes. Phys Rev Lett 84:4613. doi:10.1103/PhysRevLett.84.4613 Bronikowski MJ, Willis PA et al (2001) Gas-phase production of carbon single-walled nanotubes from carbon monoxide via the HiPco process: a parametric study, AVS. J Vac Sci Technol A 19(4):1800–1805. doi: 10.1116/1.1380721 Busch J (1994) Cost modeling as a technical management tool. Res Technol Manag 37(6):50–56 Chiango DA, Isaacs JA et al (2000) Production of steel powder by rotating electrode processes: economic analyses. Int J Powder Metall 36(4):49–56 Clark JP, Field FR et al (1997) Techno-economic issues in materials selection. ASM Handb Mater Sel Des 20:255– 265 Daenen M, de Fouw RD et al (2003) The wondrous world of carbon nanotubes. Eindhoven University of Technology, Eindhoven EIA (2007) Energy Information Administration: Electricity InfoCard 2006. http://www.eia.doe.gov/bookshelf/ brochures/electricityinfocard/elecinfocard2006/elecinfocard. html Flahaut E, Peigney A et al (2000) Synthesis of single-walled carbon nanotube–Co–MgO composite powders and extraction of the nanotubes. J Mater Chem 10(2):249–252. doi:10.1039/a908593i Global Industry Analysts I (2007). Carbon nanotubes: a Global strategic business report IV-1-IV-199
123
562 Hamada N, Sawada S-i et al (1992) New one-dimensional conductor: graphite microtubules. Phys Rev Lett 68(10):1579–1581. doi:10.1103/PhysRevLett.68.1579 Harris PJF (1999) Carbon nanotubes and related structures. Cambridge University Press, Cambridge Healy M (2006) Environmental and economic comparison of single-wall carbon nanotube production alternatives. MS thesis, Mechanical and Industrial Engineering, Northeastern University, Boston, MA Healy ML, Isaacs JA et al (2006) Economic and environmental tradeoffs of SWNT production. NSTI-Nanotech 2006, Boston, MA Healy ML, Dahlben LJ et al (2008) Environmental assessment of single-walled carbon nanotube processes. J Ind Ecol 12(3):376–393. doi:10.1111/j.1530-9290.2008.00058.x Kirchain R (2001) Cost modeling of materials and manufacturing processes. Encyclopedia of material science and engineering. E. S. Ltd, pp 1718–1727 Kociak M, Kasumov A et al (2002) Intrinsic superconductivity in ropes of carbon nanotubes. American Institute of Physics, New York, pp 237–241 Liu BC, Lyu SC et al (2004) Single-walled carbon nanotubes produced by catalytic chemical vapor deposition of acetylene over Fe–Mo/MgO catalyst. Chem Phys Lett 383(1–2): 104–108. doi:10.1016/j.cplett.2003.10.134 Lux Research (2006) The nanotech report, 4th edn. Lux Research Inc., New York, NY Nikolaev P, Bronikowski MJ et al (1999) Gas-phase catalytic growth of single-walled carbon nanotubes from carbon
123
J Nanopart Res (2010) 12:551–562 monoxide. Chem Phys Lett 313(1–2):91–97. doi: 10.1016/S0009-2614(99)01029-5 NNI (2008) FY 2009 Budget and Highlights. National Nanotechnology Initiative Ok ZD, Benneyan JC et al (2008) Risk analysis modeling of production costs and occupational health exposure of single-wall carbon nanotube manufacturing. J Ind Ecol 12(3):411–434. doi:10.1111/j.1530-9290.2008.00030.x Seo JW, Couteau E et al (2003) Synthesis and manipulation of carbon nanotubes. N J Phys 5(120):1–22 Tanaka K, Yamabe T et al (1999) The science and technology of carbon nanotubes. Elsevier, Tokyo Tang S, Zhong Z et al (2001) Controlled growth of singlewalled carbon nanotubes by catalytic decomposition of CH4 over Mo/Co/MgO catalysts. Chem Phys Lett 350(1– 2):19–26. doi:10.1016/S0009-2614(01)01183-6 Tanwani A (2005) Carbon nanotube production: an economic and environmental assessment of alternative technologies. MS Thesis, Mechanical and Industrial Engineering, Northeastern University, Boston, MA Treacy MMJ, Ebbesen TW et al (1996) Exceptionally high Young’s modulus observed for individual carbon nanotubes. Nature 381(6584):678–680. doi:10.1038/381678a0 Zheng B, Li Y et al (2002) CVD synthesis and purification of single-walled carbon nanotubes on aerogel-supported catalyst. Appl Phys, A Mater Sci Process 74:345–348. doi: 10.1007/s003390201275
