71 research outputs found
Visualization 1: Differential-interference-contrast digital in-line holography microscopy based on a single-optical-element
Video 1 Originally published in Optics Letters on 01 November 2015 (ol-40-21-5015
The performance of the BLAST/PSI-BLAST method under various E-values.
<p>The performance of the BLAST/PSI-BLAST method under various E-values.</p
Pivotal Role and Regulation of Proton Transfer in Water Oxidation on Hematite Photoanodes
Hematite is a promising material
for solar water splitting; however,
high efficiency remains elusive because of the kinetic limitations
of interfacial charge transfer. Here, we demonstrate the pivotal role
of proton transfer in water oxidation on hematite photoanodes using
photoelectrochemical (PEC) characterization, the H/D kinetic isotope
effect (KIE), and electrochemical impedance spectroscopy (EIS). We
observed a concerted proton–electron transfer (CPET) characteristic
for the rate-determining interfacial hole transfer, where electron
transfer (ET) from molecular water to a surface-trapped hole was accompanied
by proton transfer (PT) to a solvent water molecule, demonstrating
a substantial KIE (∼3.5). The temperature dependency of KIE
revealed a highly flexible proton transfer channel along the hydrogen
bond at the hematite/electrolyte interface. A mechanistic transition
in the rate-determining step from CPET to ET occurred after OH<sup>–</sup> became the dominant hole acceptor. We further modified
the proton–electron transfer sequence with appropriate proton
acceptors (buffer bases) and achieved a greater than 4-fold increase
in the PEC water oxidation efficiency on a hematite photoanode
Rate-Limiting O–O Bond Formation Pathways for Water Oxidation on Hematite Photoanode
Photoelectrochemical
(PEC) water oxidation has attracted heightened
interest in solar fuel production. It is well accepted that water
oxidation on hematite is mediated by surface trapped holes, characterized
to be the high valent −FeO species. However, the mechanism
of the subsequent rate-limiting O–O bond formation step is
still a missing piece. Herein we investigate the reaction order of
interfacial hole transfer by rate law analysis based on electrochemical
impedance spectroscopy (EIS) measurement and probe the reaction intermediates
by operando Fourier-transform infrared (FT-IR) spectroscopy. Distinct
reaction orders of ∼1 and ∼2 were observed in near-neutral
and highly alkaline environments, respectively. The unity rate law
in near-neutral pH regions suggests a mechanism of water nucleophilic
attack (WNA) to −FeO to form the O–O bond. Operando
observation of a surface superoxide species that hydrogen bonded to
the adjacent hydroxyl group by FT-IR further confirmed this pathway.
In highly alkaline regions, coupling of adjacent surface trapped holes
(I2M) becomes the dominant mechanism. While both are operable at intermediate
pHs, mechanism switch from I2M to WNA induced by local pH decrease
was observed at high photocurrent level. Our results highlight the
significant impact of surface protonation on O–O bond formation
pathways and oxygen evolution kinetics on hematite surfaces
Prediction of Multi-Type Membrane Proteins in Human by an Integrated Approach
<div><p>Membrane proteins were found to be involved in various cellular processes performing various important functions, which are mainly associated to their types. However, it is very time-consuming and expensive for traditional biophysical methods to identify membrane protein types. Although some computational tools predicting membrane protein types have been developed, most of them can only recognize one kind of type. Therefore, they are not as effective as one membrane protein can have several types at the same time. To our knowledge, few methods handling multiple types of membrane proteins were reported. In this study, we proposed an integrated approach to predict multiple types of membrane proteins by employing sequence homology and protein-protein interaction network. As a result, the prediction accuracies reached 87.65%, 81.39% and 70.79%, respectively, by the leave-one-out test on three datasets. It outperformed the nearest neighbor algorithm adopting pseudo amino acid composition. The method is anticipated to be an alternative tool for identifying membrane protein types. New metrics for evaluating performances of methods dealing with multi-label problems were also presented. The program of the method is available upon request.</p></div
Original feature values of physicochemical and biochemical properties of the 20 amino acids.
<p>Original feature values of physicochemical and biochemical properties of the 20 amino acids.</p
Distributions of correct and incorrect predictions for different multi-type proteins.
<p>The subfigures A, B and C were the predicted results on the dataset S1, while D, E and F were for those on the dataset S2, and G, H and I for S3. c denotes the number of completely correct predictions of membrane proteins, e is the number of incorrect predicted membrane proteins, and p represents the number of partly correct type predictions.</p
Comparison of the integrated method with NNA based on PseACC and RWC on the three datasets.
<p>Comparison of the integrated method with NNA based on PseACC and RWC on the three datasets.</p
The homologous proteins of the membrane protein Q9UMF0 (A) and the interactive proteins of the membrane protein O00623 (B) in the dataset S3.
<p>The numbers represent the membrane protein types: 1 GPI-anchor, 2 lipid-anchor, 3 multi-pass, 4 peripheral, 5 single-pass type I and 6 single-pass type II.</p
Performances of the three single methods tested on the three datasets.
<p>*NU represents the number of unannotated membrane proteins.</p
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