4.6 Article

Nanostructural evolution during emission of CsI-coated carbon fiber cathodes

期刊

JOURNAL OF APPLIED PHYSICS
卷 107, 期 11, 页码 -

出版社

AMER INST PHYSICS
DOI: 10.1063/1.3428463

关键词

caesium compounds; carbon fibres; cathodes; electron field emission; fast Fourier transforms; low energy electron diffraction; nanofibres; Raman spectra; scanning-transmission electron microscopy; transmission electron microscopy; work function; X-ray chemical analysis

资金

  1. AFOSR
  2. AFRL/RX
  3. AFRL/RD

向作者/读者索取更多资源

Carbon-based nanofiber and microfiber cathodes exhibit very low voltages for the onset of electron emission, and thus provide exciting opportunities for applications ranging from high power microwave sources to field emission displays. CsI coatings have been experimentally shown to lower the work function for emission from the fiber tips, although little is known about the microstructure of the fibers themselves in their as-received state, after coating with CsI, or after being subjected to high voltage cycling. Longitudinal cross sections of the original, unused CsI-coated fibers produced by focused ion beam lift-out revealed a nanostructured graphitic core surrounded by an amorphous carbon shell with submicron sized islands of crystalline CsI on the outer surface. Aberration-corrected high resolution electron microscopy (HREM) of the fiber core achieved 0.10 nm resolution, with the graphite (200) clearly visible in digital fast Fourier transformations of the 2-4 nm highly ordered graphitic domains. As the cathode fibers are cycled at high voltage, HREM demonstrates that the graphitic ordering of the core increases with the number of cycles, however the structure and thickness of the amorphous carbon layer remains unchanged. These results are consistent with micro-Raman measurements of the fiber disordered/graphitic (D/G) band ratios. After high voltage cycling, a uniform similar to 100 nm film at the fiber tip was evident in both bright field transmission electron microscopy (TEM) and high angle annular dark field scanning TEM (STEM). Low-dose electron diffraction techniques confirmed the amorphous nature of this film, and STEM with elemental mapping via x-ray energy dispersive spectroscopy indicates this layer is composed of CsIO. The oxidative evolution of tip composition and morphology due to impurities in the chamber, along with increased graphitization of the fiber core, contributes to changes in emission behavior with cycling. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3428463]

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Multidisciplinary Sciences

Synthesis and properties of free-standing monolayer amorphous carbon

Chee-Tat Toh, Hongji Zhang, Junhao Lin, Alexander S. Mayorov, Yun-Peng Wang, Carlo M. Orofeo, Darim Badur Ferry, Henrik Andersen, Nurbek Kakenov, Zenglong Guo, Irfan Haider Abidi, Hunter Sims, Kazu Suenaga, Sokrates T. Pantelides, Barbaros Ozyilmaz

NATURE (2020)

Article Engineering, Chemical

Efficient Growth of Carbon Nanotube Carpets Enabled by In Situ Generation of Water

Brian M. Everhart, Haider Almkhelfe, Xu Li, Michael Wales, Pavel Nikolaev, Rahul Rao, Benji Maruyama, Placidus B. Amama

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2020)

Article Multidisciplinary Sciences

Efficient Closed-loop Maximization of Carbon Nanotube Growth Rate using Bayesian Optimization

Jorge Chang, Pavel Nikolaev, Jennifer Carpena-Nunez, Rahul Rao, Kevin Decker, Ahmad E. Islam, Jiseob Kim, Mark A. Pitt, Jay I. Myung, Benji Maruyama

SCIENTIFIC REPORTS (2020)

Article Materials Science, Multidisciplinary

Toward autonomous additive manufacturing: Bayesian optimization on a 3D printer

James R. Deneault, Jorge Chang, Jay Myung, Daylond Hooper, Andrew Armstrong, Mark Pitt, Benji Maruyama

Summary: The research developed a low-cost and accessible research robot, AM ARES, that utilized online machine learning planners and their soon-to-be open-sourced ARES OS software to rapidly and effectively optimize the complex high-dimensional parameter sets associated with 3D printing.

MRS BULLETIN (2021)

Editorial Material Materials Science, Multidisciplinary

One-pot chemistry: Alkyne-assisted CNT growth enables in situ functionalization

Jennifer Carpena-Nunez, Rahul Rao, Benji Maruyama

MRS BULLETIN (2021)

Article Engineering, Manufacturing

Gaussian Process Surrogate Modeling Under Control Uncertainties for Yield Prediction of Carbon Nanotube Production Processes

Chiwoo Park, Rahul Rao, Pavel Nikolaev, Benji Maruyama

Summary: This study proposes a two-tier Gaussian process model to address the prediction challenge in carbon nanotube production process. The bottom tier connects the manipulating factors and the process conditions, while the top tier connects the process conditions and the outcome, resulting in improved predictive power.

JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME (2022)

Review Chemistry, Multidisciplinary

Biomarkers and Detection Platforms for Human Health and Performance Monitoring: A Review

Daniel Sim, Michael C. Brothers, Joseph M. Slocik, Ahmad E. Islam, Benji Maruyama, Claude C. Grigsby, Rajesh R. Naik, Steve S. Kim

Summary: Human health and performance monitoring is crucial for various occupational sectors. Although commercially wearable sensors can assess human health and states, their precision in HHPM is limited. However, detecting minimally or noninvasive biomarkers has become critical for human monitoring.

ADVANCED SCIENCE (2022)

Article Chemistry, Physical

Advanced machine learning decision policies for diameter control of carbon nanotubes

Rahul Rao, Jennifer Carpena-Nunez, Pavel Nikolaev, Michael A. Susner, Kristofer G. Reyes, Benji Maruyama

Summary: In this study, a machine learning planner was used to control the diameters of single-walled carbon nanotubes (SWCNTs), successfully optimizing synthesis conditions to maximize the SWCNT diameters within specific ranges. The optimized growth experiments showed high selectivity compared to unoptimized growth experiments. Interestingly, significantly different synthesis conditions were found for maximizing two diameter ranges, despite their relative closeness.

NPJ COMPUTATIONAL MATERIALS (2021)

Article Chemistry, Physical

Benchmarking the performance of Bayesian optimization across multiple experimental materials science domains

Qiaohao Liang, Aldair E. Gongora, Zekun Ren, Armi Tiihonen, Zhe Liu, Shijing Sun, James R. Deneault, Daniil Bash, Flore Mekki-Berrada, Saif A. Khan, Kedar Hippalgaonkar, Benji Maruyama, Keith A. Brown, John Fisher Iii, Tonio Buonassisi

Summary: Bayesian optimization (BO) has shown effectiveness in guiding autonomous and high-throughput experiments in materials science. This study evaluated the efficiency of BO across five different experimental materials systems, finding that Gaussian Process (GP) with anisotropic kernels and Random Forest (RF) performed well in BO, outperforming commonly used GP with isotropic kernels. GP with anisotropic kernels demonstrated robustness, while RF is a close alternative with advantages such as lack of distribution assumptions, lower time complexity, and easier initial hyperparameter selection. The benefits of using GP with anisotropic kernels in future materials optimization campaigns were also highlighted.

NPJ COMPUTATIONAL MATERIALS (2021)

Article Materials Science, Multidisciplinary

Artificial intelligence for materials research at extremes

B. Maruyama, J. Hattrick-Simpers, W. Musinski, L. Graham-Brady, K. Li, J. Hollenbach, A. Singh, M. L. Taheri

Summary: Materials development is a slow and expensive process, especially for extreme conditions where desired property combinations can interact in complex ways. AI and autonomous experimentation are valuable tools in understanding materials under extreme conditions and bridging the gap between materials properties and performance.

MRS BULLETIN (2022)

Article Engineering, Industrial

Sequential adaptive design for jump regression estimation

Chiwoo Park, Peihua Qiu, Jennifer Carpena-Nunez, Rahul Rao, Michael Susner, Benji Maruyama

Summary: This article introduces an adaptive design strategy for regression analysis with discontinuities and demonstrates its effectiveness through two scientific examples.

IISE TRANSACTIONS (2022)

Proceedings Paper Engineering, Electrical & Electronic

POINTWISE FABRICATION AND FLUIDIC SHAPING OF CARBON NANOTUBE FIELD EMITTERS

Crystal E. Owens, Jon Ludwick, Joy Y. Ma, Robert J. Headrick, Steven M. Williams, Megan Creichton, Tyson C. Back, Benji Maruyama, Matteo Pasquali, Gareth H. McKinley, A. John Hart

Summary: The new method involves pointwise deposition of aqueous suspensions of carbon nanotubes to fabricate fiber-like field emitters with high aspect ratios, dense packing of CNTs, and a large base for mechanical stability and enhanced thermal/electrical contact. This results in excellent field emission properties, including a high field enhancement factor and low turn-on voltage for various emitter sizes, motivating further research on emitter array manufacturing and device integration.

2021 21ST INTERNATIONAL CONFERENCE ON SOLID-STATE SENSORS, ACTUATORS AND MICROSYSTEMS (TRANSDUCERS) (2021)

Review Materials Science, Multidisciplinary

Autonomous experimentation systems for materials development: A community perspective

Eric Stach, Brian DeCost, A. Gilad Kusne, Jason Hattrick-Simpers, Keith A. Brown, Kristofer G. Reyes, Joshua Schrier, Simon Billinge, Tonio Buonassisi, Ian Foster, Carla P. Gomes, John M. Gregoire, Apurva Mehta, Joseph Montoya, Elsa Olivetti, Chiwoo Park, Eli Rotenberg, Semion K. Saikin, Sylvia Smullin, Valentin Stanev, Benji Maruyama

Summary: Materials research and development are crucial for solving world problems, and the partnership between humans and robots can accelerate technological advancements. The new paradigm brings both challenges and opportunities, requiring collaborative efforts across academia, industry, government, and funding agencies.

MATTER (2021)

Article Chemistry, Multidisciplinary

Interaction of gases with monolayer WS2: an in situ spectroscopy study

Rahul Rao, Hyunil Kim, Nestor Perea-Lopez, Mauricio Terrones, Benji Maruyama

Summary: This study investigated the dynamics of NO2 and NH3 adsorption on monolayer WS2 using spectroscopic techniques, revealing the influence of gas concentration and temperature on photoluminescence emission energies, as well as the correlation between lattice defects and gas adsorption. The results suggest that lattice defects, such as sulfur vacancies, play a key role in gas adsorption on WS2, with gases like NO2 and NH3 potentially contributing to the creation of defects with increasing temperature. This research provides valuable insights for the development of spectroscopy-based gas sensors using 2D materials.

NANOSCALE (2021)

Article Nanoscience & Nanotechnology

Magnesia and Magnesium Aluminate Catalyst Substrates for Carbon Nanotube Carpet Growth

Xu Li, Eric R. Gray, Ahmad E. Islam, Gordon A. Sargent, Benji Maruyama, Placidus B. Amama

ACS APPLIED NANO MATERIALS (2020)

暂无数据