E/Z photo-isomerization of a new surfactant causes substantial changes in interfacial properties, which are a prerequisite for responsive and adaptive material control on a molecular level.

Arylazopyrazoles (AAPs) as substitutes for azo derivatives have gained considerable attention due to their superior properties offering E/Z photo-isomerization with high yield. In order to compare and quantify their performance, azobenzene tetraethylammonium (Azo-TB) and arylazopyrazole tetraethylammonium (AAP-TB) bromides were synthesized and characterized in the bulk (water) using NMR spectroscopy. At the air-water interface complementary information from vibrational sum-frequency generation (SFG) spectroscopy and neutron reflectometry (NR) has revealed the effects of E/Z isomerization in great detail. In bulk water the photostationary states of >89 % for E/Z switching in both directions were very similar for the surfactants, while their interfacial behavior was substantially different. In particular, the surface excess Γ of the surfactants changed drastically between E/Z isomers for AAP-TB (maximum change of Γ: 2.15 µmol/m²); for Azo-TB the change was only moderate (maximum change of Γ: 1.02 µmol/m²). Analysis of SFG spectra revealed that strong non-resonant contributions that heterodyned the resonant vibrational bands were proportional to Γ, enabling the aromatic C-H band to be interpreted as an indicator for changes in interfacial molecular order. Close comparison of Γ from NR with the SFG amplitude from the aromatic C-H stretch as a function of concentrations and E/Z conformation revealed substantial molecular order changes for AAP-TB. In contrast, only Γ and not the molecular order varied for Azo-TB. These differences in interfacial properties are attributed to the molecular structure of the AAP center that enables favorable lateral interactions at the air-water interface, causing closed-packed interfacial layers and substantial changes during E/Z photo-isomerization.

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To realise molecular scale electrical operations beyond the von Neumann bottleneck, new types of multi-functional switches are needed that mimic selflearning or neuromorphic computing by dynamically toggling between multiple operations that depend on their past. Here we report a molecule that switches from high to low conductance states with massive negative memristive behaviour that depends on the drive speed and number of past switching events, with all measurements fully modelled using atomistic and analytical models. This dynamic molecular switch (DMS) emulates synaptic behaviour and Pavlovian learning, all within a 2.4 nm thick layer that is three orders of magnitude thinner than a neuronal synapse. The DMS provides all fundamental logic gates necessary for deep learning because of its time-domain and voltage-dependent plasticity. The synapse-mimicking multi-functional DMS represents adaptable molecular scale hardware operable in solid-state devices opening a pathway to simplify dynamic complex electrical operations encoded within a single ultra-compact component.