For the fabrication of high-performance carbon nanotube (CNT) composites with practical applicability, the development of new methods for the controlled growth of high-aspect-ratio CNTs still constitutes a challenge. With the aim of gaining a deeper understanding of the catalytic CNT growth, in this study, the effect of the catalyst composition is investigated using different mixtures of Fe(SO) and FeCl as catalysts. The relationship between the catalyst chemical state and the growth behavior of CNT forests is demonstrated by evaluating the alignment, diameter, length, and areal density of the CNT forests. When the Fe(SO) content is increased, the area density, the I/I ratio, and the crystallite size of the CNTs increase. Additionally, the obtained CNT forests exhibit good spinnability with increasing the sulfur content.
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http://dx.doi.org/10.3390/nano9060889 | DOI Listing |
Small
December 2024
Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing, 210096, China.
The electrochemical reduction of oxygen is pivotal for advancing emerging energy technologies. Precise control over morphology and electronic structure is essential for enhancing catalytic activity and stability in the oxygen reduction reaction (ORR). In this study, a freestanding carbon electrode is developed by in-situ growth of carbon nanotube (CNT)-encapsulated bimetallic CoM (M = Ni, Fe, Mn, Cu) nanoparticles (NPs) within a hierarchical carbonized wood matrix (CoM@NWCC).
View Article and Find Full Text PDFZootaxa
April 2024
Citizen Scientist; Honnepal; Bare Post-581 337; Karnataka; India.
A new species of gecarcinucid freshwater crab, Ghatiana dvirupa sp. nov., is described herein from the Kali Tiger Reserve of the Uttara Kannada district, Karnataka state, India.
View Article and Find Full Text PDFNanomaterials (Basel)
October 2024
Research Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Tsukuba 305-0044, Japan.
The synthesis, characterization, and application of carbon nanotubes (CNTs) have long posed significant challenges due to the inherent multiple complexity nature involved in their production, processing, and analysis. Recent advancements in machine learning (ML) have provided researchers with novel and powerful tools to address these challenges. This review explores the role of ML in the field of CNT research, focusing on how ML has enhanced CNT research by (1) revolutionizing CNT synthesis through the optimization of complex multivariable systems, enabling autonomous synthesis systems, and reducing reliance on conventional trial-and-error approaches; (2) improving the accuracy and efficiency of CNT characterizations; and (3) accelerating the development of CNT applications across several fields such as electronics, composites, and biomedical fields.
View Article and Find Full Text PDFNanomaterials (Basel)
October 2024
Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, International Innovation Center for Forest Chemicals and Materials, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China.
Transition metal sulfide compounds with high theoretical specific capacity and excellent electronic conductivity that can be used as cathode materials for secondary batteries attract great research interest in the field of electrochemical energy storage. Among these materials, MnSe garners significant interest from researchers due to its unique three-dimensional cubic structure and inherent stability. However, according to the relevant literature, the performance and cycle life of MnSe are not yet satisfactory.
View Article and Find Full Text PDFMicromachines (Basel)
June 2024
School of Electronic and Information Engineering, Anhui Jianzhu University, Hefei 230601, China.
Morse code recognition plays a very important role in the application of human-machine interaction. In this paper, based on the carbon nanotube (CNT) and polyurethane sponge (PUS) composite material, a flexible tactile CNT/PUS sensor with great piezoresistive characteristic is developed for detecting Morse code precisely. Thirty-six types of Morse code, including 26 letters (A-Z) and 10 numbers (0-9), are applied to the sensor.
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