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Ti 1−x O 3(1−x)-xBaTiO 3 ceramics with an excess in Bi 3+ and/or a deficiency in Na + were prepared and investigated. It is found that an antiferroelectric phase can be induced through a modulation of the mole ratio of Na + and Bi 3+. A phase boundary between ferroelectric and antiferroelectric phases can be observed at ambient temperature. A modulated phase, which is the origin of relaxor antiferroelectric behavior, should be attributed to a compositional modulation. The antiferroelectric phase can be induced to the ferroelectric phase by an applied electric field. The stability of the induced ferroelectric phase strongly depends on the mole ratio of Na + and Bi 3+. A recoverable giant strain of 0.48% comparable to PbZrO 3-based antiferroelectrics as well as electrostrictive coefficients (0.026 C 4 m −2) much higher than lead-based relaxor ferroelectrics with low-temperature dependence was achieved in (Na y ,Bi z)Ti 1−x O 3(1−x)-xBaTiO 3 antiferroelectrics. Our results show there is a high possibility that the novel lead-free antiferroelectrics will replace the PbZrO 3-based ones.

Optical machine learning has emerged as an important research area that, by leveraging the advantages inherent to optical signals, such as parallelism and high speed, paves the way for a future where optical hardware can process data at the speed of light. In this work, we present such optical devices for data processing in the form of single-layer nanoscale holographic perceptrons trained to perform optical inference tasks. We experimentally show the functionality of these passive optical devices in the example of decryptors trained to perform optical inference of single or whole classes of keys through symmetric and asymmetric decryption. The decryptors, designed for operation in the near-infrared region, are nanoprinted on complementary metal-oxide–semiconductor chips by galvo-dithered two-photon nanolithography with axial nanostepping of 10 nm1,2, achieving a neuron density of >500 million neurons per square centimetre. This power-efficient commixture of machine learning and on-chip integration may have a transformative impact on optical decryption3, sensing4, medical diagnostics5 and computing6,7.

As-received multiwalled carbon nanotubes (MWCNTs) were first treated by a 3 : 1 (v/v) mixture of concentrated H 2 SO 4 /HNO 3 and further functionalized by ethylenediamine/dicyclohexylcarbodiimide/tetrahydrofuran solution. MWCNT/epoxy nanocomposites were prepared. Their cure behaviors were investigated by dynamic differential scanning calorimetry. Quantitative analysis of the activation energy as a function of the degree of curing was carried out by the Flynn-Wall-Ozawa method. The fitted multiple regression equations for values of the activation energy of different systems were obtained. MWCNTs have the retardation effect on the cure reaction of epoxy resin, while the functional groups on the surface of amine-modified MWCNTs could accelerate the cure reactions. Thermal stability was studied by thermogravimetric analysis. The filling of amine-modified MWCNTs is beneficial to lower the cure activation energy and improve thermal stability of the nanocomposite.

Mesoporous hollow colloidal particles with well-defined characteristics have potential use in many applications. In liquid-phase catalysis, in particular, they can provide a large active surface area, reduced diffusion resistance, improved accessibility to reactants, and excellent dispersity in reaction media. Herein, we report the tailored synthesis of sulfated ZrO2 hollow nanostructures and their catalytic applications in the dehydration of fructose. ZrO2 hollow nanoshells with controllable thickness were first synthesized through a robust sol-gel process. Acidic functional groups were further introduced to the surface of hollow ZrO2 shells by sulfuric acid treatment followed by calcination. The resulting sulfated ZrO2 hollow particles showed advantageous properties for liquid-phase catalysis, such as well-maintained structural integrity, good dispersity, favorable mesoporosity, and a strongly acidic surface. By controlling the synthesis and calcination conditions and optimizing the properties of sulfated ZrO2 hollow shells, we have been able to design superacid catalysts with superior performance in the dehydration of fructose to 5-hydroxymethyfurfural than the solid sulfated ZrO2 nanocatalyst.

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NiCu bimetallic nanoparticles (NPs) with different Ni/Cu compositions are controllably synthesized by tuning the ratio of Ni and Cu acetylacetonate precursors in the presence of oleylamine and trioctylphosphine. The similar particle size, monodispersity, and homogeneous alloying of the obtained NPs are confirmed by spectroscopic and microscopic analyses. When the bimetallic NPs together with the monometallic counterparts are used as catalysts for the hydrolysis of ammonia borane (AB), their catalytic activities are found to be composition-dependent. The best-performing Ni 0.75 Cu 0.25 NPs show an activation energy of 34.2 kJ mol −1 , which is among the lowest in reported non-noble-metal catalysts. This volcano-type activity trend is attributed to the alloying effect of NiCu that endows a favorable electronic structure toward the hydrolysis of AB. To investigate the catalytic effect of support particle size, a critical yet largely unexplored factor, we further deposit the Ni 0.75 Cu 0.25 NPs onto six differently sized silica spheres in the size range 47−485 nm. It is found that the activity of NiCu/SiO 2 catalysts increases progressively with decreasing SiO 2 particle size, which is attributed to the less agglomeration and better stabilization of NiCu NPs enabled by SiO 2 spheres with higher curvature and longer interparticle distance. Notably, the NiCu NPs supported on the smallest SiO 2 exhibit a much higher turnover frequency of 1516 mol H2 mol metal −1 h −1 compared to the unsupported NPs as well as an excellent reusability in the consecutive hydrolysis of AB, signifying the strong metal−support interactions. The results underline the importance of engineering alloy composition and support particle size for efficient catalytic hydrolysis of AB.