Porous organic cage templates for Pd nanoparticle catalysts – a new porous, solution processable and fully soluble, recrystallisable support for heterogeneous catalysts.
There has been significant recent interest in exploiting the large dimension changes that can occur in molecular materials as a function of temperature, stress, or under optical illumination. Here, we report the remarkable thermal expansion properties of chloranilic acid pyrazine co-crystals. We show that the compound shows uniaxial negative thermal expansion over a wide temperature range with a linear contraction coefficient as low as (−)1500 × 10 −6 K −1 at 250 K. The corresponding 10% contraction between 200 and 300 K is an order of magnitude larger than in the so-called colossal contraction materials. We adopt a symmetry-inspired approach to describe both the structural changes that occur (using rotational symmetry modes) and the thermal expansion (using strain modes). This allows an extremely compact description of the phase transition responsible for this unusual behavior and gives detailed understanding of its atomic origins. We show how the coupling of primary and secondary strain modes in materials showing extreme expansion and contraction can lead to unusual reversals in the temperature dependence of cell parameters.
The development of new organic ferroelectrics has encountered some challenges and opportunities. In this perspective, we have summarised synthetic and computational design principles for high-performance organic ferroelectrics.
Metal-organic frameworks (MOFs) are promising nanoporous materials with diverse applications. Traditional material discovery based on intensive manual experiments has certain limitations on efficiency and effectiveness when faced with nearly infinite material space. The current situation offers an opportunity for high-throughput (HT) and machine learning (ML) approaches, including computational and experimental methods, as they have greatly improved the efficiency of MOF screening and discovery and have the capacity to deal with the enormous growth of data. In this review, we discuss the research progress in HT computation and experiments and their effect on MOF screening and discovery. We also highlight how ML-based approaches and the integration of HT methods with ML algorithms accelerate MOF design. In addition, we provide our insights on the future capability of data-driven techniques for MOF discovery, despite facing some knowledge gaps as an obstacle.
Controllable self-assembly of the DNA-linked gold nanoparticle
(AuNP) architecture for in vivo biomedical applications
remains a key challenge. Here, we describe the use of the programmed
DNA tetrahedral structure to control the assembly of three different
types of AuNPs (∼20, 10, and 5 nm) by organizing them into
defined positioning and arrangement. A DNA-assembled “core–satellite”
architecture is built by DNA sequencing where satellite AuNPs (10
and 5 nm) surround a central core AuNP (20 nm). The density and arrangement
of the AuNP satellites around the core AuNP were controlled by tuning
the size and amount of the DNA tetrahedron functionalized on the core
AuNPs, resulting in strong electromagnetic field enhancement derived
from hybridized plasmonic coupling effects. By conjugating with the
Raman molecule, strong surface-enhanced Raman scattering photoacoustic
imaging signals could be generated, which were able to image microRNA-21
and tumor tissues in vivo. These results provided
an efficient strategy to build precision plasmonic superstructures
in plasmonic-based bioanalysis and imaging.
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