Engineering topics

Li, Zhongwu

Publications and source records attributed to Li, Zhongwu.

3 records

DOE OSTI2024

Ion transport and ultra-efficient osmotic power generation in boron nitride nanotube porins

Nanotube porins form transmembrane nanomaterial-derived scaffolds that mimic the geometry and functionality of biological membrane channels. We report synthesis, transport properties, and osmotic energy harvesting performance of another member of the nanotube porin family: boron nitride nanotube porins (BNNTPs). Cryo–transmission electron microscopy imaging, liposome transport assays, and DNA translocation experiments show that BNNTPs reconstitute into lipid membranes to form functional channels of ~2-nm diameter. Ion transport studies reveal ion conductance characteristics of individual BNNTPs, which show an unusual C 1/4 scaling with ion concentration and pronounced pH sensitivity. Reversal potential measurements indicate that BNNTPs have strong cation selectivity at neutral pH, attributable to the high negative charge on the channel. BNNTPs also deliver very large power density up to 12 kW/m 2 in the osmotic gradient transport experiments at neutral pH, surpassing that of other BNNT-based devices by two orders of magnitude under similar conditions. Our results suggest that BNNTPs are a promising platform for mass transport and osmotic power generation.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Molecular transport enhancement in pure metallic carbon nanotube porins

Nanofluidic channels impose extreme confinement on water and ions, giving rise to unusual transport phenomena strongly dependent on the interactions at the channel–wall interface. Yet how the electronic properties of the nanofluidic channels influence transport efficiency remains largely unexplored. Here we measure transport through the inner pores of sub-1 nm metallic and semiconducting carbon nanotube porins. We find that water and proton transport are enhanced in metallic nanotubes over semiconducting nanotubes, whereas ion transport is largely insensitive to the nanotube bandgap value. Molecular simulations using polarizable force fields highlight the contributions of the anisotropic polarizability tensor of the carbon nanotubes to the ion–nanotube interactions and the water friction coefficient. We also describe the origin of the proton transport enhancement in metallic nanotubes using deep neural network molecular dynamics simulations. Finally, these results emphasize the complex role of the electronic properties of nanofluidic channels in modulating transport under extreme nanoscale confinement.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2023

Fluid learning: Mimicking brain computing with neuromorphic nanofluidic devices

Relentlessly rising energy demands in computing call for rethinking hardware paradigms with energy efficiency in mind. Nature’s example—the brain—raises the question: How can these natural computers achieve remarkable feats with minimal energy compared to supercomputers? Neuromorphic computing mimics the brain’s principles, but current neuromorphic concepts using electronic components face scalability and their own power consumption challenges. A potentially revolutionary approach is emerging: computing with ion transport in water through nanochannels. This field offers energy-efficient possibilities by imitating brain-like information processing with different types of ions as carriers. Finally, the goal is to converge advanced nanoscale architectures with brain-inspired efficiency, heralding a new era of computing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗