Composition-Dependent Catalytic Activity of Bimetallic Nanocrystals: AgPd-Catalyzed Hydrodechlorination of 4‑Chlorophenol

Ag–Pd bimetallic nanocrystals (NCs) with tunable compositions and narrow size distributions were produced by a one-pot synthesis. The NC growth process was investigated by time-dependent TEM, XRD, and UV–vis studies. In the hydrodechlorination of 4-chlorophenol, the AgPd_<i>x</i> (<i>x</i> = 2, 4, 6, 9, 19) showed pronounced composition-dependent catalytic activities, leading to the AgPd₉ catalyst with excellent activity

Flexible and Free-Standing Organic/Carbon Nanotubes Hybrid Films as Cathode for Rechargeable Lithium-Ion Batteries

Organic carbonyl compounds are promising electrode materials for high-performance lithium-ion batteries (LIBs), but generally suffer from poor cycling stability, low utilization, inferior rate performance, and relatively low reduction potential. In order to solve these problems, we report a dissolution-recrystallization method to prepare flexible, binder-free, and free-standing hybrid films of sodium 1,4-dioxonaphthalene-2-sulfonate and multiwalled carbon nanotubes (NQS/MWNTs) as high-performance cathode for rechargeable LIBs. The hybrid films demonstrate high utilization of NQS, stable cycling, and high-rate capability. The superior electrochemical performance is attributed to decreased size and high polarity of NQS, three-dimensional intertwined conductive network formed by MWNTs. Moreover, NQS/MWNTs show high initial reduction potential at 2.97 V, which is well explained via density functional theory (DFT) calculations. Meanwhile, the reversible redox mechanism of NQS/MWNTs during discharge/charge process is revealed by in situ infrared spectroscopy (IR) test and the stability of fully discharged product is further confirmed by DFT calculations. This study illustrates a facile method to build high-performance flexible rechargeable batteries with sustainable organic materials

Effects of Catalyst Processing on the Activity and Stability of Pt–Ni Nanoframe Electrocatalysts

Pt-based alloys have shown great promise as cathodic catalysts for cost-effective proton-exchange membrane fuel cells. Post-synthesis treatment has been recognized as a critical step to improve the catalytic performance of Pt-based alloys. Here, we present the effects of catalyst processing on the catalytic behavior of Pt–Ni nanoframe electrocatalysts in oxygen reduction reaction. The Pt–Ni nanoframes were made by corroding the Ni-rich phase from solid rhombic dodecahedral particles. A total of three different corrosion procedures were compared. Among them, electrochemical corrosion led to the highest initial specific activity (1.35 mA cm^–2 at 0.95 V <i>versus</i> reversible hydrogen electrode) by retaining more Ni in the nanoframes. However, the high activity gradually went down in a subsequent stability test due to continuous Ni loss and concomitant surface reconstruction. On the other hand, the best stability was achieved by a more-aggressive corrosion using oxidative nitric acid. Although the initial activity was compromised, this procedure imparted a less-defective surface, and thus, the specific activity dropped by only 7% over 30 000 potential cycles. These results indicate a delicate trade-off between the activity and stability of Pt–Ni nanoframe electrocatalysts. The obtained understanding of how to balance the activity–stability trade-off <i>via</i> catalyst processing can be generalized to other Pt-based alloys

Towards the digitalisation of porous energy materials: evolution of digital approaches for microstructural design

Porous energy materials are essential components of many energy devices and systems, the development of which have been long plagued by two main challenges. The first is the ‘curse of dimensionality’, i.e. the complex structure–property relationships of energy materials are largely determined by a highdimensional parameter space. The second challenge is the low efficiency of optimisation/discovery techniques for new energy materials. Digitalisation of porous energy materials is currently being considered as one of the most promising solutions to tackle these issues by transforming all material information into the digital space using reconstruction and imaging data and fusing this with various computational methods. With the help of material digitalisation, the rapid characterisation, the prediction of properties, and the autonomous optimisation of new energy materials can be achieved by using advanced mathematical algorithms. In this paper, we review the evolution of these computational and digital approaches and their typical applications in studying various porous energy materials and devices. Particularly, we address the recent progress of artificial intelligence (AI) in porous energy materials and highlight the successful application of several deep learning methods in microstructural reconstruction and generation, property prediction, and the performance optimisation of energy materials in service. We also provide a perspective on the potential of deep learning methods in achieving autonomous optimisation and discovery of new porous energy materials based on advanced computational modelling and AI techniques.</p

Age-specific mean central corneal thickness among the three ethnic groups.

<p>Age-specific mean central corneal thickness among the three ethnic groups.</p

Distribution of central corneal thickness among the three ethnic groups.

<p>Distribution of central corneal thickness among the three ethnic groups.</p

Principle component analysis one the association between ethnicity and other significant associated factors.

<p>Principle component analysis one the association between ethnicity and other significant associated factors.</p

Demographic, systemic and ocular parameters among the three ethnic groups.

<p>Demographic, systemic and ocular parameters among the three ethnic groups.</p

Associations of central corneal thickness with systemic and ocular factors.

<p>CI = confidence interval</p><p>Associations of central corneal thickness with systemic and ocular factors.</p

A Consecutive Spray Printing Strategy to Construct and Integrate Diverse Supercapacitors on Various Substrates

The rapid development of printable electronic devices with flexible and wearable characteristics requires supercapacitor devices to be printable, light, thin, integrated macro- and micro-devices with flexibility. Herein, we developed a consecutive spray printing strategy to controllably construct and integrate diverse supercapacitors on various substrates. In such a strategy, all supercapacitor components are fully printable, and their thicknesses and shapes are well controlled. As a result, supercapacitors obtained by this strategy achieve diverse structures and shapes. In addition, different nanocarbon and pseudocapacitive materials are applicable for the fabrication of these diverse supercapacitors. Furthermore, the diverse supercapacitors can be readily constructed on various objects with planar, curved, or even rough surfaces (e.g., plastic film, glass, cloth, and paper). More importantly, the consecutive spray printing process can integrate several supercapacitors together in the perpendicular and parallel directions of one substrate by designing the structure of electrodes and separators. This enlightens the construction and integration of fully printable supercapacitors with diverse configurations to be compatible with fully printable electronics on various substrates