General Rules for Selective Growth of Enriched Semiconducting Single Walled Carbon Nanotubes with Water Vapor as in Situ Etchant

The presence of metallic nanotubes in as-grown single walled carbon nanotubes (SWNTs) is the major bottleneck for their applications in field-effect transistors. Herein, we present a method to synthesize enriched, semiconducting nanotube arrays on quartz substrate. It was discovered that introducing appropriate amounts of water could effectively remove the metallic nanotubes and significantly enhance the density of SWNT arrays. More importantly, we proposed and confirmed that the high growth selectivity originates from the etching effect of water and the difference in the chemical reactivities of metallic and semiconducting nanotubes. Three important rules were summarized for achieving a high selectivity in growing semiconducting nanotubes by systematically investigating the relationship among water concentration, carbon feeding rate, and the percentage of semiconducting nanotubes in the produced SWNT arrays. Furthermore, these three rules can be applied to the growth of random SWNT networks on silicon wafers

Comparison of decoding accuracies using different numbers of EEG channels.

<p>Data were from the optimal principal component set and averaged over all subjects. (a) Layout of three channel sets: 22 channels (circle), 39 channels (cross), and 71 channels (square). A black dot indicates one electrode on the scalp. (b) Decoding accuracy of four channels sets at ten pairs of finger movements.</p

Decoding accuracies using single and multiple principal component(s) in all subjects.

<p>Classifications were done using 50 EEG channels (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085192#pone-0085192-g001" target="_blank">figure 1(c)</a>).</p

Numbers of EEG experimental trials, detected finger movements, and detected individual finger movements in all subjects.

<p>Numbers of EEG experimental trials, detected finger movements, and detected individual finger movements in all subjects.</p

Significance tests of decoding accuracy for ten pairs of fingers from one hand using EEG data in all subjects (averaged decoding accuracy/upper bound of (1-<i>α</i>) confidence level, <i>α</i> = 0.05).

<p>The last two rows of the table show the means and standard deviations of decoding accuracies of each pair of fingers across all subjects. Classification results were obtained from using the 50-channel set. Values underlined are not significantly higher than the guessing level.</p

First and second principal components obtained in both EEG and ECoG data from ten pairs of finger movements in all subjects.

<p>Each curve is the averaged 1^st or 2^nd principal component across 50 electrodes (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085192#pone-0085192-g001" target="_blank">figure 1(c)</a>) from one pair of fingers in one subject. (a) EEG data (1–125 Hz). (b) ECoG data (1–200 Hz).</p

Topographies of project weights on the 1^st PC averaged over all subjects in two representative pairs of fingers: (a) thumb vs. little (b) index vs. middle.

<p>Left column: projection weights from movement data; Middle column: weights from corresponding resting conditions data prior to movements; Right column: r² value between projection weights from movement and resting data.</p

Decoding accuracies using the resting condition EEG data prior to movements in all subjects.

<p>Classifications were done using the first three PCs and 50 EEG channels (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085192#pone-0085192-g001" target="_blank">figure 1(c)</a>). Ten pairs are displayed in the same sequence as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085192#pone-0085192-g004" target="_blank">figure 4</a>. The red dashed line shows the empirical guessing level of 51.26%.</p

Aminative Umpolung Synthesis of Aryl Vicinal Diamines from Aromatic Aldehydes

In this paper an aminative umpolung synthesis of aryl vicinal diamines from aldehydes and <i>N</i>-Ts imines is described. Electrophilic aromatic aldehydes were smoothly converted into delocalized 2-azaallylanions via condensation with 2,2-diphenylglycine in methanol and subsequent decarboxylation in THF and underwent further reaction with <i>N</i>-Ts imines to give a variety of 1,2-diamine derivatives in good yields with high <i>syn</i>/<i>anti</i> diastereoselectivity

Porosity-Enhanced Polymers from Hyper-Cross-Linked Polymer Precursors

Hyper-cross-linked polymers (HCPs) have aroused great interest because of their potential applications in adsorbing greenhouse gases and volatile organic compounds. However, the selection of raw materials and the postcontrol of the porosity of HCPs remain a challenge. Here, we developed new porosity-enhanced materials by chemically creating additional pores in polymer-based HCPs. The as-prepared material presents a high surface area (1201 m² g^–1), large microporous volume, and high chemical stability even in concentrated acid, thus demonstrating potential in gas capture and storage (CO₂: 15.31 wt % at 273 K/1.0 bar; selectivity for CO₂ against N₂: 36.6; and large adsorption capacity for six organic vapors). This method of creating additional pores in polymer-based HCPs may open doors to the creation of novel porosity-enhanced materials suitable for high-performance adsorbents