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Quantitatively estimating defects in graphene devices using discharge current analysis method.

ABSTRACT: Defects of graphene are the most important concern for the successful applications of graphene since they affect device performance significantly. However, once the graphene is integrated in the device structures, the quality of graphene and surrounding environment could only be assessed using indirect information such as hysteresis, mobility and drive current. Here we develop a discharge current analysis method to measure the quality of graphene integrated in a field effect transistor structure by analyzing the discharge current and examine its validity using various device structures. The density of charging sites affecting the performance of graphene field effect transistor obtained using the discharge current analysis method was on the order of 10(14)/cm(2), which closely correlates with the intensity ratio of the D to G bands in Raman spectroscopy. The graphene FETs fabricated on poly(ethylene naphthalate) (PEN) are found to have a lower density of charging sites than those on SiO2/Si substrate, mainly due to reduced interfacial interaction between the graphene and the PEN. This method can be an indispensable means to improve the stability of devices using a graphene as it provides an accurate and quantitative way to define the quality of graphene after the device fabrication.

SUBMITTER: Jung U

PROVIDER: S-EPMC4013935 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Quantitatively estimating defects in graphene devices using discharge current analysis method.

Jung Ukjin U Lee Young Gon YG Kang Chang Goo CG Lee Sangchul S Kim Jin Ju JJ Hwang Hyeon June HJ Lim Sung Kwan SK Ham Moon-Ho MH Lee Byoung Hun BH

Scientific reports 20140508

Defects of graphene are the most important concern for the successful applications of graphene since they affect device performance significantly. However, once the graphene is integrated in the device structures, the quality of graphene and surrounding environment could only be assessed using indirect information such as hysteresis, mobility and drive current. Here we develop a discharge current analysis method to measure the quality of graphene integrated in a field effect transistor structure ...[more]

PMID: 24811431

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Project description:BackgroundDrug safety in children is a major concern; however, there is still a lack of methods for quantitatively measuring, let alone to improving, drug safety in children under different clinical conditions. To assess pediatric drug safety under different clinical conditions, a computational method based on Electronic Medical Record (EMR) datasets was proposed.MethodsIn this study, a computational method was designed to extract the significant drug-diagnosis associations (based on a Bonferroni-adjusted hypergeometric P-value < 0.05) among drug and diagnosis co-occurrence in EMR datasets. This allows for differences between pediatric and adult drug use to be compared based on different EMR datasets. The drug-diagnosis associations were further used to generate drug clusters under specific clinical conditions using unsupervised clustering. A 5-layer quantitative pediatric drug safety level was proposed based on the drug safety statement of the pediatric labeling of each drug. Therefore, the drug safety levels under different pediatric clinical conditions were calculated. Two EMR datasets from a 1900-bed children's hospital and a 2000-bed general hospital were used to test this method.ResultsThe comparison between the children's hospital and the general hospital showed unique features of pediatric drug use and identified the drug treatment gap between children and adults. In total, 591 drugs were used in the children's hospital; 18 drug clusters that were associated with certain clinical conditions were generated based on our method; and the quantitative drug safety levels of each drug cluster (under different clinical conditions) were calculated, analyzed, and visualized.ConclusionWith this method, quantitative drug safety levels under certain clinical conditions in pediatric patients can be evaluated and compared. If there are longitudinal data, improvements can also be measured. This method has the potential to be used in many population-level, health data-based drug safety studies.

Dataset Information

Quantitatively estimating defects in graphene devices using discharge current analysis method.

Publications

Quantitatively estimating defects in graphene devices using discharge current analysis method.

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