Statistical Analysis of Variation in Laboratory Growth of Carbon Nanotube Forests and Recommendations for Improved Consistency

Abstract

While many promising applications have been demonstrated for vertically aligned carbon nanotube (CNT) forests, lack of consistency in results (e.g., CNT quality, height, and density) continues to hinder knowledge transfer and commercialization. For example, it is well known that CNT growth can be influenced by small concentrations of water vapor, carbon deposits on the reactor wall, and experiment-to-experiment variations in pressure within the reaction chamber. However, even when these parameters are controlled during synthesis, we found that variations in ambient lab conditions can overwhelm attempts to perform parametric optimization studies. We established a standard growth procedure, including the chemical vapor deposition (CVD) recipe, while we varied other variables related to the furnace configuration and experimental procedure. Statistical analysis of 280 samples showed that ambient humidity, barometric pressure, and sample position in the CVD furnace contribute significantly to experiment-to-experiment variation. We investigated how these factors lead to CNT growth variation and recommend practices to improve process repeatability. Initial results using this approach reduced run-to-run variation in CNT forest height and density by more than 50%.

Robofurnace: A semi-automated laboratory chemical vapor deposition system for high-throughput nanomaterial synthesis and process discovery

“…Finally, the ability to reduce moisture levels to a minimum (5 ppm) improves robustness and controls contamination of moisture sensitive samples. 10,12 This target was chosen based on experience with CNT reactions, which are sensitive to reactor moisture levels of 100 ppm.…”

“…Based on previous studies of the sample position influence on CNT growth, this performance is sufficient to achieve consistent exposure to active gas species along the length of the tube furnace. 11,12 The rotational placement (Figure 8(b)) averages −0.11…”

“…To demonstrate the first intended use of Robofurnace, we present an exemplary growth of CNT forests based on a procedure outlined by Oliver and Polsen et al 12 The CNT forest growth recipe, including states of the machine at each stage of growth, is shown in Table V. After insertion of the boat (with sample) into the reactor tube, the reactor is purged with He and then He/H 2 .…”

“…Specifically, fluctuations in ambient humidity affect the density and diameter of the catalyst nanoparticles formed during annealing and influence the gas phase reactions in the furnace, 12 resulting in CNT density and growth rate variation.…”

Investigation of carbon nanotube growth termination mechanism by in-situ transmission electron microscopy approaches

“…For example, SWCNT are 100 times stronger than steel at only one sixth of the weight, and conduct electrical current three orders of magnitude greater than conventional metals [1,2]. In order to utilize these exceptional properties in many promising applications, much effort has been made not only to control and improve the growth of CNTs [3][4][5][6][7], but also to assemble nano-scale CNTs into micro-scale fibers or yarns by direct spinning from chemical vapor deposition (CVD) chambers [8,9] or spinning from CNT forests or carpets [10]. However, once CNTs are assembled into fibers or yarns, their exceptional properties diminish to levels at which CNT fibers or yarns lose their advantages over conventional materials already used in various industries.…”