Evaporation or freezing of water-rich fluids with dilute concentrations of dissolved salts can produce brines, as observed in closed basins on Earth ¹ and detected by remote sensing on icy bodies in the outer Solar System ^2,3 . The mineralogical evolution of these brines is well understood in regard to terrestrial environments ⁴ , but poorly constrained for extraterrestrial systems owing to a lack of direct sampling. Here we report the occurrence of salt minerals in samples of the asteroid (101955) Bennu returned by the OSIRIS-REx mission ⁵ . These include sodium-bearing phosphates and sodium-rich carbonates, sulfates, chlorides and fluorides formed during evaporation of a late-stage brine that existed early in the history of Bennu’s parent body. Discovery of diverse salts would not be possible without mission sample return and careful curation and storage, because these decompose with prolonged exposure to Earth’s atmosphere. Similar brines probably still occur in the interior of icy bodies Ceres and Enceladus, as indicated by spectra or measurement of sodium carbonate on the surface or in plumes ^2,3 .

The application of hardware‐based neural networks can be enhanced by integrating sensory neurons and synapses that enable direct input from external stimuli. This work reports direct optical control of an oscillatory neuron based on volatile threshold switching in V₃O₅. The devices exhibit electroforming‐free operation with switching parameters that can be tuned by optical illumination. Using temperature‐dependent electrical measurements, conductive atomic force microscopy (C‐AFM), in situ thermal imaging, and lumped element modelling, it is shown that the changes in switching parameters, including threshold and hold voltages, arise from overall conductivity increase of the oxide film due to the contribution of both photoconductive and bolometric characteristics of V₃O₅, which eventually affects the oscillation dynamics. Furthermore, V₃O₅ is identified as a new bolometric material with a temperature coefficient of resistance (TCR) as high as −4.6% K⁻¹ at 423 K. The utility of these devices is illustrated by demonstrating in‐sensor reservoir computing with reduced computational effort and an optical encoding layer for spiking neural network (SNN), respectively, using a simulated array of devices.

Devices with volatile memristive switching and self‐sustained relaxation oscillations have received significant attention for their use in neuromorphic computing and solving optimization problems. However, obtaining devices with stable response and reliable oscillation remains challenging. This work describes the utility of metal/oxide interlayers in achieving reliable device performance with tuneable characteristics using Nb‐Nb₂O₅‐Pt structures. Detailed physical characterization of the Nb/Nb₂O₅ interlayer region shows that it consists of a thin, near‐stoichiometric Nb₂O₅ and an NbO_x layer with a graded oxygen content. The impact of these interlayers on device performance is assessed by investigating their switching characteristics and oscillation dynamics. It is shown that the presence of the interlayer has a direct impact on the memristive switching mode and parameters threshold switching characteristics parameters. These dependencies are explained with reference to a lumped‐element circuit model of the device and shown to be dominated by changes in device resistance caused by interlayer formation. Significantly, stable oscillation with tuneable frequency is obtained by increasing the thickness of the reactive Nb electrode. Then, by simulating an array of coupled oscillators, a unique Hamiltonian solver is demonstrated. These results provide pathways for optimizing volatile memristive switching characteristics and guidance on how such devices can be employed to solve combinatorial optimization problems.