2. Data Source AND visual tool
2.1. Data Source
2.2. Visual tool
Citation analysis visualization is an important branch of information visualization, which deals with a flood of citation data at first, and then makes it easier to observe, explore and understand the information to find the hidden data patterns and models by using information visualization technology. Citation analysis visualization tools as used herein are based on CiteSpace 3.7.R5 of JAVA platform. The CiteSpace 3.7.R5 is developed by By Chen Chaomei, a doctor in the College of Information Science and Technology, Drexel University in Philadelphia, USA. He is the international authority in the field of information visualization and devoted to study the information visualization research methods and related algorithms for many years.
CiteSpace is used to detect and analyze the emerging trends in the research fronts of subjects, and the relationship of their research fronts, intellectual bases and other research fronts. It can be more intuitive to recognize the evolving paths of subject fronts and classic basal literatures in subject areas by employing the visualized literature information. It mainly is equipped with the following visual features: co-cited articles analysis, co-occurring terms analysis, institution cooperation analysis, author co-citation analysis, authors cooperation analysis and so on. In addition, one of important features of CiteSpace is detection of burst term which relies on the level of frequency and trend of the words, owning high frequency change rates detected from a lot of phrases by examining the time distribution of frequency, to determine the fronts of the evolution of a field -.
3. Result analysis
3.1. The Analysis for the distribution and cooperation of research Institutions
As shown in Figure 1, every node represents a country. The size of node reflects the amount of articles, and the width of the color of “Ring” means the article amount in the corresponding time period. The connections indicate the cooperation between countries, and the colors of them mark the first cooperation time. Select of 100, which issued countries, there are a total of eight countries issuing more than 100 articles by selecting 100 as the display threshold value. Specific statistic data can be seen in Table 1.
3.2. The Analysis for the Distribution and cooperation of researchinstitutions
Use a zero before decimal points: “0.25”, not “.25”. Use “cm3”, not “cc”. As can be seen from Figure 2, the main cooperation of these institutions is divided into three relatively concentrated areas. There are 4040 articles which generate 663 nodes and 1436 connection, so most institutions cooperated with each other for the first time during 1990-2000 year. The quite important nodes are MIT, Meiji University, University of Glasgow, University of Pittsburgh and The Hong Kong Polytechnic University. In table 2, these institutions’ rankings are determined by the influence of issued statistics (issued number more than 60).
3.3. The Analysis for Author co-Citation
White, the doctor of Drake University in USA, believes that the higher frequency of author’s co-citation, the higher relevance in the academic of authors  . In the interface setting of CiteSpace software, we still
Figure 1. The distribution and cooperation of research institutions.
Figure 2. The distribution and cooperation of research institutions.
Table 1. Research institutions and the number of issued articles.
Figure 3. The analysis for author co-citation.
Table 2. The data statistics of articles and citations of the authors ranking top 10.
Firstly, we discern that the most influent author is CHOU SY in this field due to his articles higher than the threshold value are 277, and centrality is 0.35. Therefore, he should be regarded as the most authoritative expert in this field, and his researches have profound influences. The spatial distribution in Table 2 reflects the authors’ active time, which is earlier in the bottom. CHOU SY, BINNIG G and MATSUI S are prior researchers because of their earlier active time. Then it can be seen from the color of cited annual rings, the time of the citation of BINNIG G’s and MATSUI S’s researches is mainly before and after 2000, respectively. The time of the main publications and citations of VEPREK S, OLIVER WC, SPINDT CA, IIJIMA S, DEHEER WA, SAITO Y and BONARD JM’s researches are gradually rearward, so we can acquire the research frontal intellectual to some extent through analyzing them. Moreover, as the relevance of their researches is rather great, we are capable of speculating the latest study hotspots by analyzing their research overlaps.
3.4. The Analysis for Intellectual base
Figure 4. Co-citation network.
Figure 5. The map of reference co-citations depending on the time zone.
3.5. The Analysis forhotspots
3.6. The Analysis for Research fronts and trend
There are 143 nodes, 186 links and 19 clusters. Every cluster has a different area. The larger area cluster contains, the more bibliography entry it has, and this cluster is the more main research directions. In Figure 8 and Table 5, it shows that the research fronts and trends major in scanning tunneling microscopy, bidirectional atomic force microscope, carbon nanotube, ion-beam lithography, new polymer material, electron beam and so on. The records of the biggest cluster 8, carbon nanotube, and 13, scanning tunneling microscopy, are 23 and 22, respectively.
Figure 6. The analysis for hotspots.
Figure 7. Clusters of the research hotspots.
Figure 8. Research fronts clusters.
Figure 9. A time-zone view of mass-extinction research.
Table 5. Clusters of the research hotspots.
It demonstrates the evolutive gradient path of subject knowledge portal by clicking on the button, “Link Walkthrough”, and the color changes of circular node clusters in the map, we get Figure 9. The main referred research before 1990 are ion-beam lithography, ion-beam nanometer lithography, electron beam, carbon nanotube and piezo, and bidirectional atomic force microscope, scanning tunneling microscopy, phonon transport study, porous silicon, mechanical property, microgap X-ray mask, teox film, electron beam and piezo during 1990-2000, and array, new polymer material, carbon nanotube, grapheme, atomic layer between 2000-2010.
 Chen, C.M. (2006) CiteSpace II: Detecting and Visualizing Emerging Trends and Transient Patterns in Scientific Literature. Journal of the American Society for Information Science and Technology, 57, 359-377. http://dx.doi.org/10.1002/asi.20317