Specific molecular interactions underlie unexpected and useful phenomena in nanofluidic systems, but these require descriptions that go beyond traditional macroscopic hydrodynamics. In this letter, we demonstrate how equilibrium molecular dynamics simulations and linear response theory can be synthesized with hydrodynamics to provide a comprehensive characterization of nanofluidic transport. Specifically, we study the pressure driven flows of ionic solutions in nanochannels comprised of two-dimensional crystalline substrates made from graphite and hexagonal boron nitride. While simple hydrodynamic descriptions do not predict a streaming electrical current or salt selectivity in such simple systems, we observe that both arise due to the intrinsic molecular interactions that act to selectively adsorb ions to the interface in the absence of a net surface charge. Notably, this emergent selectivity indicates that these nanochannels can serve as desalination membranes.

Due to intense interest in the potential applications of quantum computing, it is critical to understand the basis for potential exponential quantum advantage in quantum chemistry. Here we gather the evidence for this case in the most common task in quantum chemistry, namely, ground-state energy estimation, for generic chemical problems where heuristic quantum state preparation might be assumed to be efficient. The availability of exponential quantum advantage then centers on whether features of the physical problem that enable efficient heuristic quantum state preparation also enable efficient solution by classical heuristics. Through numerical studies of quantum state preparation and empirical complexity analysis (including the error scaling) of classical heuristics, in both ab initio and model Hamiltonian settings, we conclude that evidence for such an exponential advantage across chemical space has yet to be found. While quantum computers may still prove useful for ground-state quantum chemistry through polynomial speedups, it may be prudent to assume exponential speedups are not generically available for this problem.