Performance of single nanopore and multi-pore membranes for blue energy.

The salinity gradient power extracted from the mixing of electrolyte solutions at dierent concentrations through selective nanoporous membranes is a promising route to renewable energy. However, several challenges need to be addressed to make this technology protable, one of the most relevant being the increase of the extractable power per membrane area. Here, the performance of asymmetric conical and bullet-shaped nanopores in a 50 nm thick membrane are studied via electrohydrodynamic simulations, varying the pore radius, curvature, and surface charge. The output power reaches ∼ 60 pW per pore for positively charged membranes (surface charge σw =160 mC/m2 ) and ∼ 30 pW for negatively charges ones, σw =-160 mC/m2 and it is robust to minor variations of nanopore shape and radius. A theoretical argument that takes into account the interaction among neighbour pores allows to extrapolate the single-pore performance to multi-pore membranes showing that power densities from tens to hundreds of W/m2 can be reached by proper tuning of the nanopore number density and the boundary layer thickness. Our model for scaling single-pore performance to multi-pore membrane can be applied also to experimental data providing a simple tool to effectively compare different nanopore membranes in blue energy applications.

Controlling Electroosmosis in Nanopores Without Altering the Nanopore Sensing Region.

Nanopores are powerful tools for single-molecule sensing of biomolecules and nanoparticles. The signal coming from the molecule to be analyzed strongly depends on its interaction with the narrower section of the nanopore (constriction) that may be tailored to increase sensing accuracy. Modifications of nanopore constriction have also been commonly used to induce electroosmosis, that favors the capture of molecules in the nanopore under a voltage bias and independently of their charge. However, engineering nanopores for increasing both electroosmosis and sensing accuracy is challenging. Here it is shown that large electroosmotic flows can be achieved without altering the nanopore constriction. Using continuum electrohydrodynamic simulations, it is found that an external charged ring generates strong electroosmosis in cylindrical nanopores. Similarly, for conical nanopores it is shown that moving charges away from the cone tip still results in an electroosmotic flow (EOF), whose intensity reduces increasing the diameter of the nanopore section where charges are placed. This paradigm is applied to engineered biological nanopores showing, via atomistic simulations and experiments, that mutations outside the constriction induce a relatively intense electroosmosis. This strategy provides much more flexibility in nanopore design since electroosmosis can be controlled independently from the constriction, which can be optimized to improve sensing accuracy.

Bubbles enable volumetric negative compressibility in metastable elastocapillary systems.

Although coveted in applications, few materials expand when subject to compression or contract under decompression, i.e., exhibit negative compressibility. A key step to achieve such counterintuitive behaviour is the destabilisations of (meta)stable equilibria of the constituents. Here, we propose a simple strategy to obtain negative compressibility exploiting capillary forces both to precompress the elastic material and to release such precompression by a threshold phenomenon - the reversible formation of a bubble in a hydrophobic flexible cavity. We demonstrate that the solid part of such metastable elastocapillary systems displays negative compressibility across different scales: hydrophobic microporous materials, proteins, and millimetre-sized laminae. This concept is applicable to fields such as porous materials, biomolecules, sensors and may be easily extended to create unexpected material susceptibilities.

Hydrophobically gated memristive nanopores for neuromorphic applications.

Signal transmission in the brain relies on voltage-gated ion channels, which exhibit the electrical behaviour of memristors, resistors with memory. State-of-the-art technologies currently employ semiconductor-based neuromorphic approaches, which have already demonstrated their efficacy in machine learning systems. However, these approaches still cannot match performance achieved by biological neurons in terms of energy efficiency and size. In this study, we utilise molecular dynamics simulations, continuum models, and electrophysiological experiments to propose and realise a bioinspired hydrophobically gated memristive nanopore. Our findings indicate that hydrophobic gating enables memory through an electrowetting mechanism, and we establish simple design rules accordingly. Through the engineering of a biological nanopore, we successfully replicate the characteristic hysteresis cycles of a memristor and construct a synaptic device capable of learning and forgetting. This advancement offers a promising pathway for the realization of nanoscale, cost- and energy-effective, and adaptable bioinspired memristors.