Enhancing catalytic activity of TiO2 nanoparticles through acid treatment in Eosin-Y sensitized photohydrogen evolution reaction system.

Light-driven water splitting has gained increasing attention as an eco-friendly method for hydrogen production. There is a pressing need to enhance the performance of catalysts for the commercial viability of this reaction. Many methods have been proposed to improve catalyst performance; however, an economical and straightforward approach remains a priority. This paper presents an uncomplicated technique called acid treatment, which augments the catalytic performance of nanoparticles. The method promotes a change in the catalytic reactivity by causing a deficit in electron density of Ti and O on the surface of TiO2 nanoparticles without altering their size, morphology, or crystal structure. In the Eosin Y sensitized photocatalytic hydrogen production system, nitric acid treated TiO2 (16.95 µmol/g) exhibited 1.5 times the hydrogen production compared to bare TiO2 (11.15 µmol/g).

Design of surface nanostructures for chirality sensing based on quartz crystal microbalance.

Quartz crystal microbalance (QCM) has been widely used for various sensing applications, including chirality detection due to the high sensitivity to nanogram or picogram mass changes, fast response, real-time detection, easy operation, suitability in different media, and low experimental cost. The sensing performance of QCM is dependent on the surface design of the recognition layers. Various strategies have been employed for studying the relationship between the structural features and the specific detection of chiral isomers. This review provides an overview of the construction of chiral sensing layers by various nanostructures and materials in the QCM system, which include organic molecules, supermolecular assemblies, inorganic nanostructures, and metal surfaces. The sensing mechanisms based on these surface nanostructures and the related potentials for chiral detection by the QCM system are also summarized.

Rapid one-pot synthesis of magnetically separable Fe3O4-Pd nanocatalysts: a highly reusable catalyst for the Suzuki-Miyaura coupling reaction.

Heterogeneous catalysts comprising noble metals and magnetic materials allow a straightforward separation from a reaction using an external magnet and are recovered easily. In this study, we synthesized magnetic Fe3O4-Pdn hybrid heterogeneous catalysts via a rapid one-pot aqueous-phase method. The synthesized Fe3O4-Pd NPs dispersed well with small size (∼50 nm), maintaining high magnetic responsiveness, and showed high reactivity and reusability for the Suzuki-Miyaura coupling reaction between aryl halides and phenylboronic acid. The synthesized Fe3O4-Pd50 catalyst could be recycled at least ten times with no significant loss of catalytic activity by external magnet separation.

Chiral Recognition on Bare Gold Surfaces by Quartz Crystal Microbalance.

Quartz crystal microbalance (QCM) is one of the powerful tools for the studies of molecular recognition and chiral discrimination. Its efficiency mainly relies on the design of the functional sensitive layer on the electrode surface. However, the organic sensitive layer may easily cause dissipation of oscillation or detachment and weaken the signal transfer during the molecular recognition processes. In this work, we reveal for the first time that the bare metal surface without the organic selector layer has the capability for chiral recognition in the QCM system. During the adsorption of various chiral amino acids, relatively higher selectivity of D-enantiomers on gold (Au) surface was shown by the QCM detection. Based on analyses of the surface crystalline structure and density functional theory calculations, we demonstrate that the chiral nature of Au surface plays an important role in the selective binding of specific D-amino acids. These results may open new insights on chiral detection by QCM system. It will also promote the construction of novel chiral sensing systems with both efficient detection and separation capability.

Sensitive colorimetric glucose sensor by iron-based nanozymes with controllable Fe valence.

The proportion of Fe2+ and Fe3+ in Fe-based nanozymes is a key point in determining their catalytic activity. However, it is hard to adjust the Fe2+/Fe3+ ratio in nanozyme systems to achieve the best catalytic performance. In this work, we successfully regulate Fe2+/Fe3+ ratios in a wide range of 0.81-1.45 based on a novel porous platform of Fe doped silica hollow spheres. The homogeneous distribution and stable fixation of Fe components in Fe doped silica hollow spheres facilitate the valence regulation of Fe in the reduction heating in H2/Ar. When the Fe doped spheres (FeOx@SHSs) were used as nanozymes, different Fe2+/Fe3+ ratios have shown to influence the peroxidase-like catalytic activity greatly. The highest activity at the ratio of 1.41 should be due to the combined effects of the accelerated reaction rate by Fe2+ and the enhanced catalytic cycle efficiency by Fe3+. The FeOx@SHSs-based nanozyme is further applied to construct a facile colorimetric biosensing system, which exhibited extremely sensitive determination of glucose. This work presents an effective platform for controlling Fe valences and optimizing the peroxidase-like activity for catalytic processes or sensing systems.

Tailored Palladium-Platinum Nanoconcave Cubes as High Performance Catalysts for the Direct Synthesis of Hydrogen Peroxide.

To obtain high catalytic properties, finely modulating the electronic structure and active sites of catalysts is important. Herein, we report the design and economical synthesis of Pd@Pt core-shell nanoparticles for high productivity in the direct synthesis of hydrogen peroxide. Pd@Pt core-shell nanoparticles with a partially covered Pt shell on a Pd cube were synthesized using a simple direct seed-mediated growth method. The synthesized Pd@Pt core-shell nanoparticles were composed of high index faceted Pt on the corners and edges, while the Pd-Pt alloy was located on the terrace area of the Pd cubes. Because of the high-indexed Pt and Pd-Pt alloy sites, the synthesized concave Pd@Pt7 nanoparticles exhibited both high H2 conversion and H2O2 selectivity compared with Pd cubes.

A Novel CNN-Based Poisson Solver for Fluid Simulation.

Solving a large-scale Poisson system is computationally expensive for most of the Eulerian fluid simulation applications. We propose a novel machine learning-based approach to accelerate this process. At the heart of our approach is a deep convolutional neural network (CNN), with the capability of predicting the solution (pressure) of a Poisson system given the discretization structure and the intermediate velocities as input. Our system consists of four main components, namely, a deep neural network to solve the large linear equations, a geometric structure to describe the spatial hierarchies of the input vector, a Principal Component Analysis (PCA) process to reduce the dimension of input in training, and a novel loss function to control the incompressibility constraint. We have demonstrated the efficacy of our approach by simulating a variety of high-resolution smoke and liquid phenomena. In particular, we have shown that our approach accelerates the projection step in a conventional Eulerian fluid simulator by two orders of magnitude. In addition, we have also demonstrated the generality of our approach by producing a diversity of animations deviating from the original datasets.

Facile synthesis of Pd@Pt core-shell nanocubes with low Pt content via direct seed-mediated growth and their enhanced activity for formic acid oxidation.

Pd@Pt core-shell nanocubes with a partially covered Pt shell on the Pd nanocubes were synthesized by a direct seed-mediated growth method without a washing process. The FAO activity of Pd@Pt 0.4 at% was 4.3 times and 2.2 times higher than that of Pd cubes and commercial Pt/C, respectively.

Heterostructured Nanorings of Fe-Fe3O4@C Hybrid with Enhanced Microwave Absorption Performance.

Microwave absorption is a critical challenge with progression in electronics, where fine structural designing of absorbent materials plays an effective role in optimizing their microwave absorption properties. Here, we have developed Fe3O4@C (FC) and Fe-Fe3O4@C (FFC) hybrid nanorings via a hydrothermal method coupled with a chemical catalytic vapor deposition technique. FC and FFC hybrid nanorings have fine carbon coating while their size can easily be tunable in a certain range from 80-130 to 90-140 nm. The optimized FC and FFC hybrid nanorings bear minimum reflection loss (RL) values of -39.1 dB at 15.9 GHz and -32.9 dB at 17.1 GHz, respectively, whereas FFC shows an effective absorption bandwidth (RL values < -10 dB) ranged from 5.2 to 18 GHz. Such an enhanced microwave absorption performance of hybrid nanorings is mainly due to the suitable impedance characteristics, multilevel interfaces, and polarization features in nanorings. This work provides an approach to design hybrid materials having a complex structure to enhance the microwave absorption properties.

A new asynchronous parallel algorithm for inferring large-scale gene regulatory networks.

The reconstruction of gene regulatory networks (GRNs) from high-throughput experimental data has been considered one of the most important issues in systems biology research. With the development of high-throughput technology and the complexity of biological problems, we need to reconstruct GRNs that contain thousands of genes. However, when many existing algorithms are used to handle these large-scale problems, they will encounter two important issues: low accuracy and high computational cost. To overcome these difficulties, the main goal of this study is to design an effective parallel algorithm to infer large-scale GRNs based on high-performance parallel computing environments. In this study, we proposed a novel asynchronous parallel framework to improve the accuracy and lower the time complexity of large-scale GRN inference by combining splitting technology and ordinary differential equation (ODE)-based optimization. The presented algorithm uses the sparsity and modularity of GRNs to split whole large-scale GRNs into many small-scale modular subnetworks. Through the ODE-based optimization of all subnetworks in parallel and their asynchronous communications, we can easily obtain the parameters of the whole network. To test the performance of the proposed approach, we used well-known benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge (DREAM), experimentally determined GRN of Escherichia coli and one published dataset that contains more than 10 thousand genes to compare the proposed approach with several popular algorithms on the same high-performance computing environments in terms of both accuracy and time complexity. The numerical results demonstrate that our parallel algorithm exhibits obvious superiority in inferring large-scale GRNs.

Applications of gold nanoparticles in optical biosensors.

Currently gold nanoparticles are widely used in optical bioassays because of their characteristics, such as good biocompatibility, excellent optical performance, special catalytic activity and the convenience of controlled fabrication. This review describes the application development of gold nanoparticles in various optical biosensors, including colorimetry, scanometry, dry-reagent strip, surface plasmon resonance (SPR), surface-enhanced Raman scattering (SERS), chemiluminescence and fluorescent biosensors. Firstly, we present the underlying principles that contribute to the enhanced detection capability of gold nanoparticles, taking advantage of their unique characteristics in these bioassay methods. We then demonstrate selected examples to illustrate the development of each method, focusing on the performance improvement of the biosensor, such as sensitivity, selectivity and so on. Finally, we conclude and discuss the future prospects of using gold nanoparticles in biosensors.