Metal oxide gas sensors are predominant solid-state gas detecting devices for domestic, commercial and industrial applications, which have many advantages such as low cost, easy production, and ...compact size. However, the performance of such sensors is significantly influenced by the morphology and structure of sensing materials, resulting in a great obstacle for gas sensors based on bulk materials or dense films to achieve highly-sensitive properties. Lots of metal oxide nanostructures have been developed to improve the gas sensing properties such as sensitivity, selectivity, response speed, and so on. Here, we provide a brief overview of metal oxide nanostructures and their gas sensing properties from the aspects of particle size, morphology and doping. When the particle size of metal oxide is close to or less than double thickness of the space-charge layer, the sensitivity of the sensor will increase remarkably, which would be called "small size effect", yet small size of metal oxide nanoparticles will be compactly sintered together during the film coating process which is disadvantage for gas diffusion in them. In view of those reasons, nanostructures with many kinds of shapes such as porous nanotubes, porous nanospheres and so on have been investigated, that not only possessed large surface area and relatively mass reactive sites, but also formed relatively loose film structures which is an advantage for gas diffusion. Besides, doping is also an effective method to decrease particle size and improve gas sensing properties. Therefore, the gas sensing properties of metal oxide nanostructures assembled by nanoparticles are reviewed in this article. The effect of doping is also summarized and finally the perspectives of metal oxide gas sensor are given.
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Intrinsically low conductivity and poor reactivity restrict many semiconductors from electrochemical detection. Usually, metal- and carbon-based modifications of semiconductors are necessary, making ...them complex, expensive, and unstable. Here, for the first time, we present a surface-electronic-state-modulation-based concept applied to semiconductors. This concept enables pure semiconductors to be directly available for ultrasensitive electrochemical detection of heavy-metal ions without any modifications. As an example, a defective single-crystalline (001) TiO2 nanosheet exhibits high electrochemical performance toward Hg(II), including a sensitivity of 270.83 μA μM–1 cm–2 and a detection limit of 0.017 μM, which is lower than the safety standard (0.03 μM) of drinking water established by the World Health Organization (WHO). It has been confirmed that the surface oxygen vacancy adsorbs an O2 molecule while the Ti3+ donates an electron, forming the O2 •– species that facilitate adsorption of Hg(II) and serve as active sites for electron transfer. These findings not only extend the electrochemical sensing applications of pure semiconductors but also stimulate new opportunities for investigating atom-level electrochemical behaviors of semiconductors by surface electronic-state modulation.
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Strong metal–support interactions (SMSI) is an important concept in heterogeneous catalysis. Herein, we demonstrate that the Au‐TiO2 SMSI of Au/TiO2 catalysts sensitively depends on both Au ...nanoparticle (NP) sizes and TiO2 facets. Au NPs of ca. 5 nm are more facile undergo Au‐TiO2 SMSI than those of ca. 2 nm, while TiO2 {001} and {100} facets are more facile than TiO2{101} facets. The resulting capsulating TiO2−x overlayers on Au NPs exhibit an average oxidation state between +3 and +4 and a Au‐to‐TiO2−x charge transfer, which, combined with calculations, determines the Ti:O ratio as ca. 6:11. Both TiO2−x overlayers and TiO2−x‐Au interface exhibit easier lattice oxygen activation and higher intrinsic activity in catalyzing low‐temperature CO oxidation than the starting Au‐TiO2 interface. These results advance fundamental understanding of SMSI and demonstrate engineering of metal NP size and oxide facet as an effective strategy to tune the SMSI for efficient catalysis.
Au‐TiO2 SMSI of Au/TiO2 catalysts sensitively depends on the Au NP size and the TiO2 facet. Supported Au NPs with a size of ca. 5 nm are more facile to undergo the Au‐TiO2 SMSI than those of ca. 2 nm, and the TiO2 {001} and {100} facets are more facile than the TiO2{101} facets.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Inferences of population genetic structure are of great importance to the fields of ecology and evolutionary biology. The program structure has been widely used to infer population genetic structure. ...However, previous studies demonstrated that uneven sampling often leads to wrong inferences on hierarchical structure. The most widely used ΔK method tends to identify the uppermost hierarchy of population structure. Recently, four alternative statistics (medmedk, medmeak, maxmedk and maxmeak) were proposed, which appear to be more accurate than the previously used methods for both even and uneven sampling data. However, the lack of easy‐to‐use software limits the use of these appealing new estimators. Here, we developed a web‐based user‐friendly software structureselector to calculate the four appealing alternative statistics together with the commonly used Ln Pr(X|K) and ΔK statistics. structureselector accepts the result files of structure, admixture or faststructure as input files. It reports the “best” K for each estimator, and the results are available as HTML or tab separated tables. The program can also generate graphical representations for specific K, which can be easily downloaded from the server. The software is freely available at http://lmme.qdio.ac.cn/StructureSelector/.
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Abstract
Despite the maximized metal dispersion offered by single-atom catalysts, further improvement of intrinsic activity can be hindered by the lack of neighboring metal atoms in these systems. ...Here we report the use of isolated Pt
1
atoms on ceria as “seeds” to develop a Pt-O-Pt ensemble, which is well-represented by a Pt
8
O
14
model cluster that retains 100% metal dispersion. The Pt atom in the ensemble is 100–1000 times more active than their single-atom Pt
1
/CeO
2
parent in catalyzing the low-temperature CO oxidation under oxygen-rich conditions. Rather than the Pt-O-Ce interfacial catalysis, the stable catalytic unit is the Pt-O-Pt site itself without participation of oxygen from the 10–30 nm-size ceria support. Similar Pt-O-Pt sites can be built on various ceria and even alumina, distinguishable by facile activation of oxygen through the paired Pt-O-Pt atoms. Extending this design to other reaction systems is a likely outcome of the findings reported here.
Single-atom catalysts (SACs) and single-cluster catalysts (SCCs) are the new frontier of heterogeneous catalysis, which exhibit high activity, selectivity, stability, and atomic efficiency as well as ...precise tunability. However, the lack of efficient methods for producing high-loading and high-purity SACs and SCCs hinders their industrial applications. In this work, we propose a general and efficient strategy for the production of high-loading and high-purity SACs and SCCs anchored on suitable substrates. Our strategy relies on the existence of an electrochemical potential window (EcPW) we predict within which any aggregate forms of the target metal on the substrate are leached away by electrochemical oxidation, while the strongly bound single atoms or single clusters remain at the substrate. We demonstrate the applicability of this strategy with modeling the production of Pt, Pd, and Ni SACs anchored on N-doped graphene and Fe2O3 as well as Pt3 and Ni3 SCCs anchored on graphdiyne.
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It is highly profitable to transform glycerol - the main by-product from biodiesel production to high value-added chemicals. In this work, we develop a photoelectrochemical system based on nanoporous ...BiVO
for selective oxidation of glycerol to 1,3-dihydroxyacetone - one of the most valuable derivatives of glycerol. Under AM 1.5G front illumination (100 mW cm
) in an acidic medium (pH = 2) without adscititious oxidant, the nanoporous BiVO
photoanode achieves a glycerol oxidation photocurrent density of 3.7 mA cm
at a potential of 1.2 V versus RHE with 51% 1,3-dihydroxyacetone selectivity, equivalent to a production rate of 200 mmol of 1,3-dihydroxyacetone per m
of illumination area in one hour.
We present the VASPKIT, a command-line program that aims at providing a robust and user-friendly interface to perform high-throughput analysis of a variety of material properties from the raw data ...produced by the VASP code. It consists of mainly the pre- and post-processing modules. The former module is designed to prepare and manipulate input files such as the necessary input files generation, symmetry analysis, supercell transformation, k-path generation for a given crystal structure. The latter module is designed to extract and analyze the raw data about elastic mechanics, electronic structure, charge density, electrostatic potential, linear optical coefficients, wave function plots in real space, etc. This program can run conveniently in either interactive user interface or command line mode. The command-line options allow the user to perform high-throughput calculations together with bash scripts. This article gives an overview of the program structure and presents illustrative examples for some of its usages. The program can run on Linux, macOS, and Windows platforms. The executable versions of VASPKIT and the related examples and tutorials are available on its official website vaspkit.com.
Program title: VASPKIT
CPC Library link to program files:https://doi.org/10.17632/v3bvcypg9v.1
Licensing provisions: GPLv3
Programming language: Fortran, Python
Nature of problem: This program has the purpose of providing a powerful and user-friendly interface to perform high-throughput calculations together with the widely-used VASP code.
Solution method: VASPKIT can extract, calculate and even plot the mechanical, electronic, optical and magnetic properties from density functional calculations together with bash and python scripts. It can run in either interactive user interface or command line mode.
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Recently developed quantum algorithms address computational challenges in numerical analysis by performing linear algebra in Hilbert space. Such algorithms can produce a quantum state proportional to ...the solution of a
d
-dimensional system of linear equations or linear differential equations with complexity
poly
(
log
d
)
. While several of these algorithms approximate the solution to within
ϵ
with complexity
poly
(
log
(
1
/
ϵ
)
)
, no such algorithm was previously known for differential equations with time-dependent coefficients. Here we develop a quantum algorithm for linear ordinary differential equations based on so-called spectral methods, an alternative to finite difference methods that approximates the solution globally. Using this approach, we give a quantum algorithm for time-dependent initial and boundary value problems with complexity
poly
(
log
d
,
log
(
1
/
ϵ
)
)
.
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