Lithium-ion batteries (LIBs) still need continuous safety monitoring based on their intrinsic properties, as well as due to the increase in their sizes and device requirements. The main causes of fires and explosions in LIBs are heat leakage and the presence of highly inflammable components. Therefore, it is necessary to improve the safety of the batteries by preventing the generation of these gases and/or their early detection with sensors. The improvement of such safety sensors requires new approaches in their manufacturing. There is a growing role for research of nanostructured sensor’s durability in the field of ionizing radiation that also can induce structural changes in the LIB’s component materials, thus contributing to the elucidation of fundamental physicochemical processes; catalytic reactions or inhibitions of the chemical reactions on which the work of the sensors is based. A current method widely used in various fields, Direct Ink Writing (DIW), has been used to manufacture heterostructures of Al₂O₃/CuO and CuO:Fe₂O₃, followed by an additional ALD and thermal annealing step. The detection properties of these 3D-DIW printed heterostructures showed responses to 1,3-dioxolan (DOL), 1,2-dimethoxyethane (DME) vapors, as well as to typically used LIB electrolytes containing LiTFSI and LiNO₃ salts in a mixture of DOL:DME, as well also to LiPF₆ salts in a mixture of ethylene carbonate (EC) and dimethyl carbonate (DMC) at operating temperatures of 200 °C–350 °C with relatively high responses. The combination of the possibility to detect electrolyte vapors used in LIBs and size control by the 3D-DIW printing method makes these heterostructures extremely attractive in controlling the safety of batteries.

With this work we introduce a novel memristor in a lateral geometry whose resistive switching behaviour unifies the capabilities of bipolar switching with decelerated diffusive switching showing a biologically plausible short-term memory. A new fabrication route is presented for achieving lateral nano-scaled distances by depositing a sparse network of carbon nanotubes (CNTs) via spin-coating of a custom-made CNT dispersion. Electrochemical metallization-type (ECM) resistive switching is obtained by implanting AgAu nanoparticles with a Haberland-type gas aggregation cluster source into the nanogaps between the CNTs and shows a hybrid behaviour of both diffusive and bipolar switching. The resistance state resets to a high resistive state (HRS) either if the voltage is removed with a retention time in the second- to sub-minute scale (diffusive) or by applying a reverse voltage (bipolar). Furthermore, the retention time is positively correlated to the duration of the Set voltage pulse. The potential for low-voltage operation makes this approach a promising candidate for short-term memory applications in neuromorphic circuits. In addition, the lateral fabrication approach opens the pathway towards integrating sensor-functionality and offers a general starting point for the scalable fabrication of nanoscaled devices.

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Self‐organized neuromorphic nanogranular networks that mimic the switching dynamics of biological neural networks are promising for next‐generation brain‐inspired computing architectures. Despite recent advances, strategies to lower their switching threshold, and understanding of the influence of light on their switching dynamics, which are key aspects for energy‐efficient and multifunctional device operation, remains limited. Here, a strategy is introduced to lower the switching threshold, and the optical sensitivity of the nanoparticle networks (NPNs) is explored. Silver (Ag) NPNs are fabricated via surfactant‐free deposition from a gas aggregation cluster source. One network is coated with poly(1,3,5‐trivinyl‐1,3,5‐trimethyl‐cyclosiloxane) (pV3D3) using initiated chemical vapor deposition (iCVD), producing Ag/pV3D3 NPN with enhanced morphological stability and a significantly reduced switching threshold of 0.5 V compared to uncoated Ag NPNs (3 V). Time‐series measurements showed indications that the switching activity of Ag/pV3D3 NPNs can be modulated by visible light, with blue light irradiation showing the largest enhancement in switching events compared to the dark, unilluminated state. These findings establish a pathway toward low‐power, light‐tunable, self‐organized nanogranular networks for neuromorphic computing applications.