Jun Ye

Dr. Jun Ye

orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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31 March 2009 in Physical Review Letters
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Journal Article
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XDXiaochen Dong
Xiaochen Dong
Yumeng ShiYumeng Shi
Yumeng Shi
YZYang Zhao
Yang Zhao
DCDongmeng Chen
Dongmeng Chen
JYJun Ye
Jun Ye
LLLain-Jong Li
Lain-Jong Li
Aromatic molecules can effectively exfoliate graphite into graphene monolayers, and the resulting graphene monolayers sandwiched by the aromatic molecules exhibit a pronounced Raman G-band splitting, similar to that observed in single-walled carbon nanotubes. Raman measurements and calculations based on the force-constant model demonstrate that the absorbed aromatic molecules are responsible for the G-band splitting by removing the energy degeneracy of in-plane longitudinal and transverse optical phonons at the Γ point.

18 December 2017 in Journal of Materials Chemistry C
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HJHui Jiang
Hui Jiang
PHPeng Hu
Peng Hu
JYJun Ye
Jun Ye
KZKeke K. Zhang
Keke K. Zhang
Yi LongYi Long
Yi Long
CKChristian Kloc
Christian Kloc
7,7,8,8-Tetracyanoquinodimethane (TCNQ) and FxTCNQ (x = 1, 2, 4) as acceptors and aromatic hydrocarbons form a variety of compounds in which the degree of charge transfer is tuned by crystal engineering.

23 August 2011 in Chemistry – A European Journal
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JSJunling Song
Junling Song
Zongyou YinZongyou Yin
Zongyou Yin
ZYZijiang Yang
Zijiang Yang
PAPitchamuthu Amaladass
Pitchamuthu Amaladass
SWShixin Wu
Shixin Wu
XLXue‐Wei Liu
Xue‐Wei Liu

12 July 2019 in npj Computational Materials
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Journal Article
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JKJatin N. Kumar
Jatin N. Kumar
QLQianxiao Li
Qianxiao Li
KTKaren Y. T. Tang
Karen Y. T. Tang
TBTonio Buonassisi
Tonio Buonassisi
AGAnibal L. Gonzalez-Oyarce
Anibal L. Gonzalez-Oyarce
JYJun Ye
Jun Ye
Inverse design is an outstanding challenge in disordered systems with multiple length scales such as polymers, particularly when designing polymers with desired phase behavior. Here we demonstrate high-accuracy tuning of poly(2-oxazoline) cloud point via machine learning. With a design space of four repeating units and a range of molecular masses, we achieve an accuracy of 4 °C root mean squared error (RMSE) in a temperature range of 24–90 °C, employing gradient boosting with decision trees. The RMSE is >3x better than linear and polynomial regression. We perform inverse design via particle-swarm optimization, predicting and synthesizing 17 polymers with constrained design at 4 target cloud points from 37 to 80 °C. Our approach challenges the status quo in polymer design with a machine learning algorithm, that is capable of fast and systematic discovery of new polymers.

1 October 2010 in Solid State Communications
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Journal Article
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YSYuanyuan Sun
Yuanyuan Sun
LCLi Chen
Li Chen
FZFeiwu Zhang
Feiwu Zhang
DLDaoyong Li
Daoyong Li
HPHongzhe Pan
Hongzhe Pan
JYJun Ye
Jun Ye

17 December 2014 in Scientific Reports
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HJHui Jiang
Hui Jiang
JYJun Ye
Jun Ye
PHPeng Hu
Peng Hu
FWFengxia Wei
Fengxia Wei
KDKe-zhao Du
Ke-zhao Du
CKChristian Kloc
Christian Kloc
The fluorination of p-type metal phthalocyanines produces n-type semiconductors, allowing the design of organic electronic circuits that contain inexpensive heterojunctions made from chemically and thermally stable p- and n-type organic semiconductors. For the evaluation of close to intrinsic transport properties, high-quality centimeter-sized single crystals of F16CuPc, F16CoPc and F16ZnPc have been grown. New crystal structures of F16CuPc, F16CoPc and F16ZnPc have been determined. Organic single-crystal field-effect transistors have been fabricated to study the effects of the central metal atom on their charge transport properties. The F16ZnPc has the highest electron mobility (~1.1 cm2 V−1 s−1). Theoretical calculations indicate that the crystal structure and electronic structure of the central metal atom determine the transport properties of fluorinated metal phthalocyanines.