Enhancing the Thermal Conductivity of CNT/AlN/Silicone Rubber Composites by Using CNTs Directly Grown on AlN to Achieve a Reduced Filler Filling Ratio.

Achieving the thermal conductivity required for efficient heat management in semiconductors and other devices requires the integration of thermally conductive ceramic fillers at concentrations of 60 vol% or higher. However, an increased filler content often negatively affects the mechanical properties of the composite matrix, limiting its practical applicability. To address this issue, in this paper, we present a new strategy to reduce the required ceramic filler content: the use of a thermally conductive ceramic composite filler with carbon nanotubes (CNTs) grown on aluminum nitride (AlN). We combined catalyst coating technology with vacuum filtration to ensure that the catalyst was uniformly applied to micrometer-sized AlN particles, followed by the efficient and uniform synthesis of CNTs using a water-assisted process in a vertical furnace. By carefully controlling the number of vacuum filtration cycles and the growth time of the CNTs, we achieved precise control over the number and length of the CNT layers, thereby adjusting the properties of the composite to the intended specifications. When AlN/CNT hybrid fillers are incorporated into silicone rubber, while maintaining the mechanical properties of rubber, the thermal diffusivity achieved at reduced filler levels exceeds that of composites using AlN-only or simultaneous AlN and CNTs formulations. This demonstrates the critical influence of CNTs on AlN surfaces. Our study represents a significant advancement in the design of thermally conductive materials, with potential implications for a wide range of applications.

Machine Learning-Assisted Exploration and Identification of Aqueous Dispersants in the Vast Diversity of Organic Chemicals.

Dispersion represents a central processing method in the organization of nanomaterials; however, the strong interparticle interaction represents a significant obstacle to fabricating homogeneous and stable dispersions. While dispersants can greatly assist in overcoming this obstacle, the appropriate type is dependent on such factors as nanomaterial, solvent, experimental conditions, etc., and there is no general guide to assist in the selection from the vast number of possibilities. We report a strategy and successful demonstration of the machine-learning-based "Dispersant Explorer", which surveys and identifies suitable dispersants from open databases. Through the combined use of experimental and molecular descriptors derived from SMILES databases, the model showed exceptional predictive accuracy in surveying about ∼1000 chemical compounds and identifying those that could be applied as dispersants. Furthermore, fabrication of transparent conducting films using the predicted and previously unknown dispersant exhibited the highest sheet resistance and transmittance compared with those of other reported undoped films. This result highlights that, in addition to opening new avenues for novel dispersant discovery, machine learning has a potential to elucidate the chemical structures essential for optimal dispersion performance to assist in the advancement of the complex topic of nanomaterial processing.

Addressing the Trade-Off between Crystallinity and Yield in Single-Walled Carbon Nanotube Forest Synthesis Using Machine Learning.

Synthetic trade-offs exist in the synthesis of single-walled carbon nanotube (SWCNT) forests, as growing certain desired properties can often come at the expense of other desirable characteristics such as the case of crystallinity and growth efficiency. Simultaneously achieving mutually exclusive properties in the growth of SWCNT forests is a significant accomplishment, as it requires overcoming these trade-offs and balancing competing mechanisms. To address this, we trained a machine-learning regression model with a set of 585 "real" experimental synthesis data, which were taken using an automatic synthesis reactor. Subsequently, 16000 exploratory "virtual" experiments were performed by our trained model to examine potential routes toward addressing the current crystallinity-height trade-off limitation, and suggestions on growth conditions were predicted. Importantly, additional validation using "real" experimental syntheses showed good agreement with the predictions as well as a 48% increase in growth efficiency while maintaining the high crystallinity (G/D-ratio). This highlighted the effectiveness and accuracy of the predictive capability of our machine-learning model, which achieved improved results in less than 50 validation tests. Furthermore, the trained model revealed the surprising importance of the nature of the carbon feedstock, particularly the reactivity and concentration, as a route for overcoming the trade-off between the SWCNT crystallinity and growth efficiency. These results of the high-efficiency synthesis of highly crystalline SWCNT forests represent a significant advance in overcoming synthetic trade-off barriers for complex multivariable systems.

A Microwave-Assisted, Solvent-Free Approach for the Versatile Functionalization of Carbon Nanotubes.

While the functionalization of carbon nanotubes (CNTs) has attracted extensive interest for a wide range of applications, a facial and versatile strategy remains in demand. Here, we report a microwave-assisted, solvent-free approach to directly functionalize CNTs both in raw form and in arbitrary macroscopic assemblies. Rapid microwave irradiation was applied to generate active sites on the CNTs while not inducing excessive damage to the graphitic network, and a gas-phase deposition afforded controllable grafting for thorough or regioselective functionalization. Using methyl methacrylate (MMA) as a model functional group and a CNT sponge as a model assembly, homogeneous grafting was exhibited by the increased robust hydrophobicity (contact angle increase from 30 to 140°) and improved structural stability (compressive modulus increased by 135%). Therefore, when our MMA-functionalized CNTs served as a solar absorber for saline distillation, high operating stability with a superior water evaporation rate of ∼2.6 kg m-2 h-1 was observed. Finally, to highlight the efficacy and versatility of this functionalization approach, we fabricated asymmetrically hydrophobic CNT sponges by regioselective functionalization to serve as a moisture-driven generator, which demonstrated a stable open-circuit voltage of 0.6 mV. This versatile, solvent-free approach can complement conventional solution-based techniques in the design and fabrication of multifunctional nanocarbon-based materials.

Structural Design and Fabrication of Multifunctional Nanocarbon Materials for Extreme Environmental Applications.

Extreme environments represent numerous harsh environmental conditions, such as temperature, pressure, corrosion, and radiation. The tolerance of applications in extreme environments exemplifies significant challenges to both materials and their structures. Given the superior mechanical strength, electrical conductivity, thermal stability, and chemical stability of nanocarbon materials, such as carbon nanotubes (CNTs) and graphene, they are widely investigated as base materials for extreme environmental applications and have shown numerous breakthroughs in the fields of wide-temperature structural-material construction, low-temperature energy storage, underwater sensing, and electronics operated at high temperatures. Here, the critical aspects of structural design and fabrication of nanocarbon materials for extreme environments are reviewed, including a description of the underlying mechanism supporting the performance of nanocarbon materials against extreme environments, the principles of structural design of nanocarbon materials for the optimization of extreme environmental performances, and the fabrication processes developed for the realization of specific extreme environmental applications. Finally, perspectives on how CNTs and graphene can further contribute to the development of extreme environmental applications are presented.

A Hydrogen-Free Approach for Activating an Fe Catalyst Using Trace Amounts of Noble Metals and Confinement into Nanoparticles.

Metallic iron (Fe) represents an exceptionally active catalyst, as shown in its use in the Haber-Bosch process to dissociate nitrogen molecules; however, the ease of corrosion by oxidation limits its usage. Hence, in most applications using metallic Fe catalysts, hydrogen is a necessary reactant. We report a novel hydrogen-free approach to fabricating reduced, highly active, and corrosion-resistive Fe-based catalysts using trace levels of noble metals (NMs) such as Ir, Rh, and Pt confined in the nanoparticle (NP). X-ray photoelectron spectroscopy (XPS) revealed that as little as ∼0.3 atom % was sufficient to induce the reduction of Fe. Extensive XPS analysis showed that the reduced NM atoms segregated to the NP surface and reduced the surrounding Fe atoms. We demonstrated the catalytic activity of the nanoparticles by the efficient synthesis of submillimeter tall, vertically aligned, and mainly double-walled carbon nanotube arrays using a completely hydrogen-free chemical vapor deposition process.

Quantitative Evidence for the Dependence of Highly Crystalline Single Wall Carbon Nanotube Synthesis on the Growth Method.

We present a study quantitatively demonstrating that the method of synthesis (gas phase, fixed bed, non-fixed bed) represents a determining factor in the level of crystallinity in growing single wall carbon nanotubes (SWCNTs). Using far infrared spectroscopy, the "effective length" (associated with the level of crystallinity) was estimated for CNTs grown using various synthetic methods (lab-produced and supplemented by commercially purchased SWCNTs) as a metric for crystallinity (i.e., defect density). Analysis of the observed "effective lengths" showed that the SWCNTs fell into two general groups: long and short (high and low crystallinity) synthesized by gas-phase methods and all other supported catalyst methods, respectively. Importantly, the "long" group exhibited effective lengths in the range of 700-2200 nm, which was greater than double that of the typical values representing the "short" group (110-490 nm). These results highlight the significant difference in crystallinity. We interpret that the difference in the crystallinity stemmed from stress concentration at the nanotube-catalyst interface during the growth process, which originated from various sources of mismatch in growth rates (e.g., vertically aligned array) as well as impact stress from contact with other substrates during fluidization or rotation. These results are consistent with well-accepted belief, but now are demonstrated quantitatively.

Semiconductor nanochannels in metallic carbon nanotubes by thermomechanical chirality alteration.

Carbon nanotubes have a helical structure wherein the chirality determines whether they are metallic or semiconducting. Using in situ transmission electron microscopy, we applied heating and mechanical strain to alter the local chirality and thereby control the electronic properties of individual single-wall carbon nanotubes. A transition trend toward a larger chiral angle region was observed and explained in terms of orientation-dependent dislocation formation energy. A controlled metal-to-semiconductor transition was realized to create nanotube transistors with a semiconducting nanotube channel covalently bonded between a metallic nanotube source and drain. Additionally, quantum transport at room temperature was demonstrated for the fabricated nanotube transistors with a channel length as short as 2.8 nanometers.

Enhanced activity for reduction of 4-nitrophenol of Ni/single-walled carbon nanotube prepared by super-growth method.

In this study, we synthesised the Ni/single-walled carbon nanotube prepared by the super-growth method (SG-SWCNTs). In this approach, the Ni nanoparticles were immobilised by an impregnation method using the SG-SWCNTs with high specific surface areas (1144 m2g-1). The scanning electron microscopy images confirmed that the SG-SWCNTs exhibit the fibriform morphology corresponding to the carbon nanotubes. In addition, component analysis of the obtained samples clarified that the Ni nanoparticles were immobilised on the surface of the SG-SWCNTs. Next, we evaluated the activity for the reduction of 4-nitoropenol in the presence of the Ni/SG-SWCNTs. Additionally, the Ni/graphene, which was obtained by the same synthetic method, was utilised in this reaction. The rate of reaction activity of the Ni/SG-SWCNTs finished faster than that of the Ni/GPs. From this result, the pseudo-first-order kinetic rate constantkfor the Ni/SG-SWCNTs and the Ni/GPs was calculated respectively at 0.083 and 0.070 min-1, indicating that the Ni/SG-SWCNTs exhibits higher activity.

Role of Hydrogen in Catalyst Activation for Plasma-Based Synthesis of Carbon Nanotubes.

The importance of hydrogen in carbon nanotube (CNT) synthesis has been known as it supports the critical processes necessary for CNT growth, such as catalyst reduction. However, within the scope of our mini microplasma CNT synthesis reactor, we found that hydrogen was critical for unexpected reasons. Without hydrogen, CNT growth was inhibited and characterized by amorphous carbon particles. Optical emission spectroscopy of the microplasma revealed that without hydrogen, the high-energy electrons induced the immediate decomposition of carbon feedstock simultaneously with the catalyst feedstock, thus suppressing the formation of catalyst nanoparticles and inducing catalyst deactivation. In contrast, the inclusion of hydrogen induced less-immediate decomposition of reactant gases, through the conversion of electron energy of the plasma to thermal energy, which provided the appropriate conditions for catalyst nanoparticle formation and subsequent CNT nucleation. A simple reaction pathway model was proposed to explain these observed results and underlying mechanisms.

Crystalline and Electrical Property Improvement of Filtrated, Exfoliated Graphite Sheets by an In-Plane Current and Heating Treatment.

We report an approach to fabricate high conductivity graphite sheets based on a heat-and-current treatment of filtrated, exfoliated graphite flakes. This treatment combines heating (~ 900 °C) and in-plane electrical current flow (550 A·cm-2) to improve electrical conductivity through the reduction of crystalline defects. This process was shown to require only a 1-min treatment time, which resulted in a 2.1-fold increase in electrical conductivity (from 1088 ± 72 to 2275 ± 50 S·cm-1). Structural characterization by Raman spectroscopy and X-ray diffraction indicated that the improvement electrical conductivity originated from a 30-fold improvement in the crystallinity (Raman G/D ratio increase from 2.8 to 85.3) with no other observable structural transformations. Significantly, this treatment was found to act uniformly across a macroscopic (10 mm) sheet surface indicating it is on the development of applications, such as electrodes for energy generation and storage and electromagnetic shielding, as well as on the potential for the development of large-scale treatment technologies.

Additional obstacles in carbon nanotube growth by gas-flow directed chemical vapour deposition unveiled through improving growth density.

Here, we demonstrate an approach of increasing the density of ultralong carbon nanotube (CNT) growth by combining a fast-heating method developed by Huang et al. (J. Am. Chem. Soc., 2003, 125, 5636-5637) with catalyst support engineering. Specifically, using graphene oxide as a catalyst support for iron oxide (Fe3O4) catalyst nanoparticles, we achieved high density growth of CNTs grown by the "kite-mechanism". Our analysis revealed that the fast-heating method reduced undesired aggregation of the catalyst nanoparticles, which has been reported to be a primary limitation mechanism, by shortening the time between substrate heating and CNT growth. In addition, the use of the graphene oxide support led to controllable and uniform dispersion of catalyst nanoparticles in relatively high density which provided increased process control by extending the time before the onset of catalyst aggregation. Together, these approaches suppressed the aggregation of the catalyst nanoparticles, which facilitated the "tip-growth" mode instead of the "root-growth" mode, and led to the high density growth of ultralong CNTs. Our results also indicate additional limitations and complexities on the high density CNT growth by the kite-growth approach, which limit high density synthesis.

Carbon Nanotubes and Related Nanomaterials: Critical Advances and Challenges for Synthesis toward Mainstream Commercial Applications.

Advances in the synthesis and scalable manufacturing of single-walled carbon nanotubes (SWCNTs) remain critical to realizing many important commercial applications. Here we review recent breakthroughs in the synthesis of SWCNTs and highlight key ongoing research areas and challenges. A few key applications that capitalize on the properties of SWCNTs are also reviewed with respect to the recent synthesis breakthroughs and ways in which synthesis science can enable advances in these applications. While the primary focus of this review is on the science framework of SWCNT growth, we draw connections to mechanisms underlying the synthesis of other 1D and 2D materials such as boron nitride nanotubes and graphene.

One millimeter per minute growth rates for single wall carbon nanotube forests enabled by porous metal substrates.

We report an exceptionally high-efficiency synthesis of long single-wall carbon nanotube (SWCNT) forests using porous substrates (metal meshes) in place of nonporous flat substrates. This study examined the dependence of the growth efficiency on various mesh structures, including wire diameter, aperture size, and total surface area. We demonstrated that the synthesis of SWCNT forests is highly dependent on the initial porosity as well as maintaining the open pores throughout the duration of the growth. Our results show that carbon nanotubes (CNTs) can be grown on all surfaces of the mesh in high efficiency with the optimum growth efficiency observed for a mesh porosity of ∼30%. Based on these results, we demonstrated the high efficiency synthesis of SWCNT forests (height: >3.47 mm, average growth rate: 301 µm min-1, and yield: 12.7 mg cm-2 in 10 min growth time). Furthermore, we showed that the initial growth rates exceeded 1 millimeter per minute (1000 µm min-1). Our results further indicate that metal meshes represent a viable alternative to nonporous flat substrates for the efficient synthesis of tall and high yielding SWCNTs.

A New, General Strategy for Fabricating Highly Concentrated and Viscoplastic Suspensions Based on a Structural Approach To Modulate Interparticle Interaction.

We report a general strategy to fabricate highly concentrated, viscoplastic and stable suspensions by designing the particle surface structure to control the interparticle attractive forces. Unlike conventional methods, where the choice of solvent is critical in balancing interparticle interactions, suspensions showing excellent stability and viscoplastic properties were made using various solvents. We demonstrated this approach using highly sparse agglomerates of carbon nanotubes (CNTs) as the particles. Our results revealed that the essential feature of the CNT agglomerate to fabricate these suspensions was high porosity with a spacing size much smaller than the overall size, which was only possible using long single-walled carbon nanotubes (SWNTs). In this way, the agglomerate surface was characterized by fine network of CNT bundles. These suspensions exhibited solid-like behavior at rest (characterized by a high yield stress of c.a. 100 Pa) and a liquid-like behavior when subjected to a stress (characterized by a significant drop of an apparent viscosity to 1 Pa·s at a shear rate of 1000 s-1). Furthermore, in contrast to conventionally fabricated suspensions, these "CNT pastes" exhibited exceptional stability at rest, under flow, and at extremely high concentrations during the drying process, with only a weakly observable dependence on solvent type. As a result, highly uniform micrometer-thick SWNT films were successfully fabricated by dried blade-coated films of these pastes. Finally, we developed a simple, semiempirical model and clarified the importance of the CNT agglomerate microstructure (the ratio of spacing size/particle size and porosity) on tailoring the cohesive forces between particles to fabricate stable viscoplastic suspensions.

Designing Neat and Composite Carbon Nanotube Materials by Porosimetric Characterization.

We propose a porosimetry-based method to characterize pores formed by carbon nanotubes (CNTs) in the CNT agglomerates for designing neat CNT-based materials and composites. CNT agglomerates contain pores between individual CNTs and/or CNT bundles (micropore < 2 nm, mesopores 2-50 nm, and macropores > 50 nm). We investigated these pores structured by CNTs with different diameters and number of walls, clarifying the broader size distribution and the larger volume with increased diameters and number of walls. Further, we demonstrated that CNT agglomerate structures with different bulk density were distinguished depending on the pore sizes. Our method also revealed that CNT dispersibility in solvent correlated with the pore sizes of CNT agglomerates. By making use of these knowledge on tailorable pores for CNT agglomerates, we successfully found the correlation between electrical conductivity for CNT rubber composites and pore sizes of CNT agglomerates. Therefore, our method can distinguish diverse CNT agglomerate structures and guide pore sizes of CNT agglomerates to give high electrical conductivity of CNT rubber composites.

The double-edged effects of annealing MgO underlayers on the efficient synthesis of single-wall carbon nanotube forests.

Recently, the millimetre-scale, highly efficient synthesis of single-wall carbon nanotube (SWCNT) forests from Fe catalysts has been reported through the annealing of the magnesia (MgO) underlayer. Here, we report the double-edged effects of underlayer annealing on the efficiency and structure of the SWCNT forest synthesis through a temperature-dependent examination. Our results showed that the efficiency of the SWCNT forests sharply increased with increased underlayer annealing temperatures from 600 °C up to 900 °C due to a temperature-dependent structural modification, characterized by increased grain size and reduced defects, of the MgO underlayer. Beyond this temperature, the SWCNT fraction also decreased as a result of further structural modification of the MgO underlayer. This exemplifies the double-edged effects of annealing. Specifically, for underlayer annealing below 600 °C, the catalyst subsurface diffusion was found to limit the growth efficiency, and for excessively high underlayer annealing temperatures (>900 °C), catalyst coalescence/ripening led to the formation of double-wall carbon nanotubes. As a result, three distinct regions of synthesis were observed: (i) a "low yield" region below a threshold temperature (∼600 °C); (ii) an "increased yield" region from 600 to 900 °C, and (iii) a "saturation" region above 900 °C. The efficient SWCNT forest synthesis could only occur within a specific annealing temperature window as a result of this double-edged effects of underlayer annealing.

Unexpected Efficient Synthesis of Millimeter-Scale Single-Wall Carbon Nanotube Forests Using a Sputtered MgO Catalyst Underlayer Enabled by a Simple Treatment Process.

An unexpected 5000% increase in growth efficiency and high (95%) single-wall selectivity synthesis of vertically aligned carbon nanotubes (CNTs) was shown from Fe catalysts supported on a sputtered MgO underlayer from a simple underlayer treatment, i.e., annealing treatment. In this way, millimeter-scale single-wall carbon nanotube "forests" could be synthesized in a 10 min time, which has never been previously reported for MgO catalyst underlayer or any underlayer besides Al2O3. This level of efficiency and characterized SWCNT properties were similar to those grown using Al2O3 underlayers. Spectroscopic and microscopic analyses revealed that the treatment improved stability of the catalyst nanoparticle array by the suppressing catalyst subsurface diffusion and retaining the metallic state of the surface Fe atoms. Taken together, these results reveal a new route in achieving highly efficient SWCNT synthesis.

A sweet spot for highly efficient growth of vertically aligned single-walled carbon nanotube forests enabling their unique structures and properties.

We investigated the correlation between growth efficiency and structural parameters of single-walled carbon nanotube (SWCNT) forests and report the existence of a SWCNT "sweet spot" in the CNT diameter and spacing domain for highly efficient synthesis. Only within this region could SWCNTs be grown efficiently. Through the investigation of the growth rates for ∼340 CNT forests spanning diameters from 1.3 to 8.0 nm and average spacing from 5 to 80 nm, this "sweet spot" was found to exist because highly efficient growth was constrained by several mechanistic boundaries that either hindered the formation or reduced the growth rate of SWCNT forests. Specifically, with increased diameter SWCNTs transitioned to multiwalled CNTs (multiwall border), small diameter SWCNTs could only be grown at low growth rates (low efficiency border), sparse SWCNTs lacked the requirements to vertically align (lateral growth border), and high density catalysts could not be prepared (high catalyst density border). As a result, the SWCNTs synthesized within this "sweet spot" possessed a unique set of characteristics vital for the development applications, such as large diameter, long, aligned, defective, and high specific surface area.

A phenomenological model for selective growth of semiconducting single-walled carbon nanotubes based on catalyst deactivation.

A method for the selective semiconducting single-walled carbon nanotube (SWCNT) growth over a continuous range from 67% to 98%, within the diameter range of 0.8-1.2 nm, by the use of a "catalyst conditioning process" prior to growth is reported. Continuous control revealed an inverse relationship between the selectivity and the yield as evidenced by a 1000-times difference in yield between the highest selectivity and non-selectivity. Further, these results show that the selectivity is highly sensitive to the presence of a precise concentration of oxidative and reductive gases (i.e. water and hydrogen), and the highest selectivity occurred along the border between the conditions suitable for high yield and no-growth. Through these results, a phenomenological model has been constructed to explain the inverse relationship between yield and selectivity based on catalyst deactivation. We believe our model to be general, as the fundamental mechanisms limiting selective semiconducting SWCNT growth are common to the previous reports of limited yield.