Size-selective Pt siderophores based on redox active azo-aromatic ligands

Selective anchoring of Pt NPs on covalent triazine-based frameworks via in situ derived bridging ligands for boosting photocatalytic hydrogen evolution

The efficient and stable production of hydrogen (H2) through Pt-containing photocatalysts remains a great challenge. Herein, we develop an effective strategy to selectively and uniformly anchor Pt NPs (∼1.2 nm) on a covalent triazine-based framework photocatalyst via in situ derived bridging ligands. Compared to Pt/CTF-1, the obtained Pt/AT-CTF-1 exhibits a considerable photocatalytic H2 evolution rate of 562.9 μmol g-1 h-1 under visible light irradiation. Additionally, the strong interaction between the Pt NPs and in situ derived bridging ligands provides remarkable stability to Pt/AT-CTF-1. Experimental investigations and photo/chemical characterization reveal the synergy of the in situ derived bridging ligands in Pt/AT-CTF-1, which can selectively anchor the Pt NPs with homogeneous sizes and efficiently improve the transmission of charge carriers. This work provides a new perspective toward stabilizing ultrasmall nanoclusters and facilitating electron transfer in photocatalytic H2 evolution materials.

A review on the chemistry of novel platinum chelates based on azo-azomethine ligands

Numerous platinum group metals (PGMs) complexes contain azo-azomethine-based ligands. Azo-azomethine ligands are N-donor ligands that have extended conjugated π-bonded systems and both azo (–N=N–) and aldimine (–C=N–) functions in their structure. Plenty of platinum (Pt) complexes with azo-imine ligands have been prepared and characterized. Various multidentate azo-imine ligands coordinated with different platinum metal substrates afforded structurally diverse platinum chelates. Nonetheless, many azo-imine-based platinum complexes demonstrated a wide range of biological activities, photo-switchable properties, and redox activities. The review encompasses a general overview of platinum complexes with versatile azo-azomethine ligands, their synthetic protocol, spectroscopic and structural features, chemical reactivity, and multipurpose applications in different areas.

Decision trees within a molecular memristor

Profuse dendritic-synaptic interconnections among neurons in the neocortex embed intricate logic structures enabling sophisticated decision-making that vastly outperforms any artificial electronic analogues^1-3. The physical complexity is far beyond existing circuit fabrication technologies: moreover, the network in a brain is dynamically reconfigurable, which provides flexibility and adaptability to changing environments^4-6. In contrast, state-of-the-art semiconductor logic circuits are based on threshold switches that are hard-wired to perform predefined logic functions. To advance the performance of logic circuits, we are re-imagining fundamental electronic circuit elements by expressing complex logic in nanometre-scale material properties. Here we use voltage-driven conditional logic interconnectivity among five distinct molecular redox states of a metal-organic complex to embed a 'thicket' of decision trees (composed of multiple if-then-else conditional statements) having 71 nodes within a single memristor. The resultant current-voltage characteristic of this molecular memristor (a 'memory resistor', a globally passive resistive-switch circuit element that axiomatically complements the set of capacitor, inductor and resistor) exhibits eight recurrent and history-dependent non-volatile switching transitions between two conductance levels in a single sweep cycle. The identity of each molecular redox state was determined with in situ Raman spectroscopy and confirmed by quantum chemical calculations, revealing the electron transport mechanism. Using simple circuits of only these elements, we experimentally demonstrate dynamically reconfigurable, commutative and non-commutative stateful logic in multivariable decision trees that execute in a single time step and can, for example, be applied as local intelligence in edge computing^7-9.