4.6 Article

Thermochemical hole burning performance of TCNQ-based charge transfer complexes with different electrical conductivities

Journal

NANOTECHNOLOGY
Volume 19, Issue 23, Pages -

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/0957-4484/19/23/235303

Keywords

-

Ask authors/readers for more resources

Thermochemical hole burning (THB) memory is an ultrahigh density data storage technique based on the scanning tunneling microscope (STM). It utilizes the STM current to induce localized thermochemical decomposition of TCNQ-based charge transfer (CT) complexes and sequentially create nanometer-sized holes as information bits. The writing reliability and hole size depend on many factors, including the properties of the storage materials and the STM tip, and the tip-sample distance and interaction. We have found here that for the high electrical conductivity CT complexes, the hole size (represented by volume) monotonically decreases with the tip displacement increasing in the direction of leaving the sample; but for low electrical conductivity samples, the hole size first increases and then decreases with the tip displacement increasing in the same direction. Subsequent experiments and analyses indicate that the surface deformation induced by the tip-sample interaction and the heat conduction of the metal tip account for such a unique phenomenon.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Chemistry, Multidisciplinary

Direct Synthesis of Graphdiyne Nanowalls on Arbitrary Substrates and Its Application for Photoelectrochemical Water Splitting Cell

Xin Gao, Jian Li, Ran Du, Jingyuan Zhou, Mao-Yong Huang, Rong Liu, Jie Li, Ziqian Xie, Li-Zhu Wu, Zhongfan Liu, Jin Zhang

ADVANCED MATERIALS (2017)

Article Acoustics

Sensitivity Analysis and Experimental Verification of Bolt Support Parameters Based on Orthogonal Experiment

Kun Zhang, Jinpeng Su, Zengkai Liu, Hongyue Chen, Qiang Zhang, Shaoan Sun

SHOCK AND VIBRATION (2020)

Review Acoustics

Research on Adaptive Friction Compensation of Digital Hydraulic Cylinder Based on LuGre Friction Model

Shouling Jiang, Kun Zhang, Hui Wang, Donghu Zhong, Jinpeng Su, Zengkai Liu

Summary: This paper presents a method to eliminate the influence of nonlinear friction on the performance of digital hydraulic cylinders. By establishing a mathematical model and employing adaptive friction compensation control, the system performance can be effectively improved.

SHOCK AND VIBRATION (2021)

Article Education, Scientific Disciplines

Compressor fault diagnosis system based on PCA-PSO-LSSVM algorithm

Kun Zhang, Jinpeng Su, Shaoan Sun, Zhixiang Liu, Jinrui Wang, Mingchao Du, Zengkai Liu, Qiang Zhang

Summary: The article introduces a fault diagnosis system for compressor systems based on the PCA-PSO-LSSVM algorithm, which is determined to have high recognition rate and accuracy through comparative analysis.

SCIENCE PROGRESS (2021)

Article Chemistry, Analytical

High-Performance 3D Vertically Oriented Graphene Photodetector Using a Floating Indium Tin Oxide Channel

Jiawei Yang, Yudong Liu, Haina Ci, Feng Zhang, Jianbo Yin, Baolu Guan, Hailin Peng, Zhongfan Liu

Summary: The study presents a high-performance photodetector based on a VG/ITO composite structure, where the VG layer is responsible for light absorption and ITO layer serves as the carrier conduction channel, achieving broadband and high response nature of a photodetector.

SENSORS (2022)

Article Automation & Control Systems

Artificial Intelligence Enhanced Two-Stage Hybrid Fault Prognosis Methodology of PMSM

Baoping Cai, Zhengda Wang, Hongmin Zhu, Yonghong Liu, Keke Hao, Ziqi Yang, Yi Ren, Qiang Feng, Zengkai Liu

Summary: This paper proposes a multistage fault prognosis methodology that combines stage identification, Bayesian networks, and time series approach to address the issue of inaccurate fault prognosis based on a single model. The method achieves better results by accurately identifying and matching outliers, and using the ARMA model for prognosis.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2022)

Article Engineering, Marine

Remaining useful life prediction considering degradation interactions of subsea Christmas tree: A multi-stage modeling approach

Xiaoyan Shao, Yingying Wang, Baoping Cai, Yonghong Liu, Weifeng Ge, Yiliu Liu, Xiangdi Kong, Qiang Feng, Yiqi Liu, Zengkai Liu, Renjie Ji

Summary: The uneven distribution of working pressures in components leads to interactions in system performance degradation. Even the same two components have different degradation processes due to natural degradation or external impact. This paper proposes a multi-stage model-based RUL estimation approach using Bayesian networks, which can effectively evaluate system performance and RUL considering interactions.

OCEAN ENGINEERING (2022)

Article Environmental Sciences

Risk assessment of marine oil spills using dynamic Bayesian network analyses

Zengkai Liu, Zhonghao Han, Qi Chen, Xuewei Shi, Qiang Ma, Baoping Cai, Yonghong Liu

Summary: Oil spills pose serious threats to the marine ecosystem, particularly when faced with extreme weather conditions. This study presents a novel method using dynamic Bayesian networks (DBNs) to quantify the risk of oil spills in extreme winds. By transforming physical models into DBNs and establishing a vulnerability model based on coastline types and socio-economic resources, the overall DBN for quantifying the dynamic risk of oil spills in extreme winds is obtained. The proposed method is demonstrated in the Laizhou Bay and validated using a three-axiom-based approach to calculate the temporal and spatial dynamics of risk caused by oil spills in potential locations. The study also examines the risk of the Laizhou Bay coast caused by oil spills in annual extreme wind speeds corresponding to different mean recurrence intervals and investigates the effects of the occurrence time of annual extreme winds.

ENVIRONMENTAL POLLUTION (2023)

Article Engineering, Marine

Condition-based maintenance method for multicomponent system considering maintenance delay based on remaining useful life prediction: Subsea tree system as a case

Yuandong Wang, Baoping Cai, Yanping Zhang, Jing Liu, Javed Akbar Khan, Yiliu Liu, Rongkang Li, Zhengde Chu, Zengkai Liu, Yonghong Liu

Summary: This paper proposes a condition-based maintenance (CBM) method based on remaining useful life (RUL) prediction, which dynamically sets inspection time and optimizes maintenance cost by considering maintenance preparation time and RUL prediction results.

OCEAN ENGINEERING (2022)

Article Computer Science, Artificial Intelligence

A hybrid multi-stage methodology for remaining useful life prediction of control system: Subsea Christmas tree as a case study

Xuelin Liu, Baoping Cai, Xiaobing Yuan, Xiaoyan Shao, Yiliu Liu, Javed Akbar Khan, Hongyan Fan, Yonghong Liu, Zengkai Liu, Guijie Liu

Summary: In this study, a hybrid multi-stage methodology for remaining useful life (RUL) prediction of control systems is proposed. The variant of unscented Kalman filter (UKF) and dynamic Bayesian networks (DBNs) are used for uncertainty analysis, and the real degradation process of control systems is simulated by optimizing the degradation process, leading to improved accuracy and robustness of RUL prediction.

EXPERT SYSTEMS WITH APPLICATIONS (2023)

Article Automation & Control Systems

Fault Diagnosis Methodology of Redundant Closed-Loop Feedback Control Systems: Subsea Blowout Preventer System as a Case Study

Xiangdi Kong, Baoping Cai, Yonghong Liu, Hongmin Zhu, Chao Yang, Chuntan Gao, Yiqi Liu, Zengkai Liu, Renjie Ji

Summary: Faults in closed-loop feedback control systems are difficult to identify. Redundancy improves system reliability but poses new challenges for fault diagnosis in multiple redundant systems. This study proposes a causality-based method using dynamic Bayesian networks for fault diagnosis, which dynamically evaluates system performance and integrates monitoring information to assist diagnosis and location.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2023)

Article Engineering, Mechanical

Influence of Texture Parameters on Lubrication Performance of Surface Textured Bearings

Li-Li Wang, Xing-Tang Zhao, Zeng-Kai Liu, Shao-Hui Guo, Min Wang

Summary: The study used simulation analysis and experiments to investigate the effects of viscosity and rotational speed on the friction coefficient of bearings, finding that higher viscosity lubricating oil and appropriate rotational speeds can improve lubrication performance.

JOURNAL OF THE CHINESE SOCIETY OF MECHANICAL ENGINEERS (2021)

Review Chemistry, Physical

Rational Design of Binary Alloys for Catalytic Growth of Graphene via Chemical Vapor Deposition

Yanglizhi Li, Luzhao Sun, Haiyang Liu, Yuechen Wang, Zhongfan Liu

CATALYSTS (2020)

Article Computer Science, Information Systems

An Unsupervised Intelligent Method for Cutting Pick State Recognition of Coal Mining Shearer

Kun Zhang, Lingyu Meng, Yuhao Qi, Hongyue Chen, Jinpeng Su, Qiang Zhang, Zengkai Liu, Zhenduo Song

IEEE ACCESS (2020)

Article Engineering, Mechanical

Combined Influence of Noncondensable Gas Mass Fraction and Mathematical Model on Cavitation Performance of Bearing

Wang Lili, Liu Zengkai, Yuan Guoteng, Wei Yuliang

INTERNATIONAL JOURNAL OF ROTATING MACHINERY (2020)

No Data Available