Various Nanostructure for Electrodes
-Coating
-Core-shell
-Encapsulation

Nano science is now investigated by a large amount of researchers in Chemistry, Physics, Materials Science and Mechanical Engineering. etc. Lithium ion battery is one of field catches most nano scientists's attention. Nano electrode is the core of innovation. According to Web of Science, there are 624 research papers focus on "nano+electrode+lithium-ion" topic. 

I respect material scientist in the aspect that they have invented a large amount of electrode with different materials, geometries, and combination methods. Then these electrodes are labeled with different features. From my observation, most material scientists' work on electrode include material fabrication, characterization and performance test.  The focus lies on the fabrication and characterization of nano electrode. The mechanism study is limited and only based on certain set of electrodes. What's more there is no systematic research on the functionality of different features. Which feature is more important? How could we locate the optimal? When I was doing literature review, those questions bother me a lot. 

A natural thinking is could we use statistical method (like regression) and literature data to locate the powerful features, to find out which of  nanowire and nano particle is more useful? Review papers offered a half-processed data pool, and a larger data pool would be the 624 papers emerging last year. To test the statistical model, we may use limited sets of data with limited features. For example, I am studying the silicon-carbon anodes for LIB.  Then gradually, we move to the multi-dimensional design, with varying materials, geometries, combinations and even fabrication process. To enhance the robustness with most simple model, we need to have a pre-selection of the sensitive features, which might be done machine learning and data mining methods (like rough set) for larger data pool. The functionality model will offer the weight of different functionality to the performance, which may shed light on the explanation of the mechanism. 

After we had the basic understanding of the functionality, we would also get interested in how could we generate new electrode with the data pool. The design of electrode is actually a discrete multi-variable optimal problem. If the variables are limited, it can be reached by a searching method. But without  that, we could only try different combinations. I think we could introduce a framework of using idea matrix and innovation operator to genetically generate the new electrodes. This part is still not well-thought especially when I am doing dual projects already. 

Four-month Summary
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 In the past four month, I have been absorbing and integrating knowledge and methods in the microscale transport especially in thermal transport and lithium-ion battery.
Recently, I have been getting the fundamental understanding of the design science and social network. This will probably help me to understand the complex social-technical world. 



Lectures and Seminars​
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Jan, 2014
Lecture:      Nanowire Devices for High-Performance Energy Storage
Lecturer:     Liqiang Mai, Professor, WUT-Harvard Joint Nano Key Lab


Dec, 2013
Lecture 1:    Multiscale Simulations and Ultrafast Characterization for Nanoscale Heat Conduction
Lecture 2:    Phase-Change Heat Transfer at Micro/Nanoscale: from Fundamentals to Manufacturable Devices
Lecturer:     Ronggui Yang, Associate Professor, Mechnical Engineering, University of Colorado, Boulder


Nov, 2013
Seminar:     Interfacial Science and Technology in Energy Industry
Lecturer:    Qingxia (Chad) Liu, Professor, Chemical and Materials Engineering, University of Alberta

Oct, 2013
Lecture:      Simulation of thermal and thermoelectric properties of carbon nanomaterials
Lecturer:     S.Watanabe, Department of Material Engineering, The University of Tokyo​




 

No.5 Updates

1. I discussed the transport modeling of Lithium-ion Battery with Dr. Yonghuang Ye in NUS, Singapore. He answered my questions concerning the macro mathematical model of transport in Lithium-ion battery. He thinks there are limited research linking microscale structure and transport.
2. I am doing intern on Innovative Metrics Development in SUTD with the supervision of Prof. Katja Otto. It will deepen my understanding of  how innovative a technology is, thus facilitate my ability to innovate.  My idea to develop an innovation matrix for the nano scale electrode design gained the interest and support from Prof. Jianxi Luo. We will discuss it later.
3. Our team has completed Network Analysis  towards 2014 ICM. It is a challenging problem since none of us had knowledge on network analysis and we need to solve the problem in 4 days in a report. But I found learning new knowledge is not that challenging and understanding the challenge is much more important. It's exciting that Prof. Jianxi Luo working on network analysis are impressed by our solutions and interested in our finding. You can find our more on my site: http://www.letianwang.me/network-analysis.html

Our team paper is updated on the projects page and see the project detail there.

1)      Firstly, the link between paper influence and authors influence is biased.
      a)   Innovative researcher may get shadowed by limited productivity originated from their large efforts on individual paper. A typical scenario would be a founding scientist who had three thousand-citing paper but only obtained an H-index of 3. The quantity of his work will offsets the profundity. Only the authors with a large number of papers with high citation will be recognized.
      b)  Innovative researcher will be shadowed by the limited number of journals in his field. The typical scenario is a scientist in biology and information science could easily obtain a H-index over 10, which is hard for a mathematician and theoretical physicist. Networking effect should be normalized.
      c)  Though paper published on prestigious journals usually gain more citations, the varied significance of publicationfrom different journals still remain not well accounted for. Especially for those innovative authors who usually publish on high rated journals gain same citation.
      d)  The author’s active contribution is not indicated in the H-index. Innovative author placed as the first author gain the same citation number as the second author.
      e)On the connectivity side, the index say nothing about the cooperation of scholars. Such cooperation indicates the potential of innovation and the spread of academic findings

2) Secondly, the influence of paper measured by the citation number is biased. 
      a)  Citations do not account for confounding factors such as "gratuitous authorship", the so-called Matthew effect, and the favorable citation bias associated with review articles. Again, this is a problem for all other metrics using publications or citations.
      
Looks like using network influence is better!

Our final model of analyzing the paper-paper citation network and paper-academic entity network (entities include the author, departments, universities and journals). 

For computing concern, we split the network and analyze it step-by-step. 

We utilized PageRank, HITS algorithm to calculate the network centrality, authority and connectivity. 

To be updated...

Update No.4

1. MCM/ICM contest preparation
2. Thermal Transport Review Paper
3. Nanostructured Electrode Transport

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•  I have been working on the MCM/ ICM (The Mathematical Contest in Modeling and Interdisciplinary Contest in Modeling) held by COMAP in US. Taking part in this contest, I am trying to review and further improve my mathematics at the end of my college life. In another aspect, I am challenging a new topic.
  

•  I noticed the newly released paper Nanoscale thermal transport. II. 2003–2012 by several renowned researchers in thermal transport field.It is a great guidepoint for me to further walk into this field. It had reviewed the interfacial transport, the phonon transport and nano material effects on it, and lastly the experimental advancement. The authors focused on the interfacial transport and offered me a better understanding of how this topic evolved. But unfortunately, I could not master the detailed information, so there is much more to prepare.
  

•  I have  been keep searching detailed research topics for my senior design. I found the paper Combined Microstructure and Heat Conduction Modeling of Heterogeneous Interfaces and Materials by Prof. Fisher gives a good modeling connecting the microstructure and continum theories of transport, which could help me on reserching transport in electrodes. Also, I found what I have learnt in Purdue , the Effective Medium Theories has been used again in this work. Everything is so wonderful!