I noted a while back that it looks like the proteins found in cells make use of lock-and-key systems based upon local electrostatic charge. Specifically, two proteins will or won’t bond depending upon the local charges at their ends, and will or won’t permeate a medium based upon their local charges generally (versus their net overall charge). While watching DW News, specifically a report on filtering emissions from concrete production, it dawned on me the same principles could be used to filter chemicals during any process, because all sufficiently large molecules will have local charges that could differ from the net charge of the molecule as a whole. For example, water is partially, locally charged at points, because it has two hydrogen atoms and an oxygen atom, though the proteins produced by DNA of course have much more complex local charges.
The idea is, you have a mesh that is capable of changing its charge locally at a very small scale, and that mesh is controlled by a machine learning system that tunes itself to the chemicals at hand. You can run an optimizer to find the charge configuration that best filters those chemicals. This would cause the mesh to behave like the mediums you find in cells that are permeable by some molecules and not others, by simply generating an electrostatic structure that does exactly that.
Is this a trivial matter of engineering? No, of course not, because you need charges at the size of a few molecules, but the idea makes perfect sense, and can probably be implemented, because we already produce semiconductors that have components at the same scale. This would presumably require both positive and negative charges, so it’s not the same as a typical semiconductor, but it’s not an impossible ask on its surface. If it works, it would produce a generalized method for capturing hazardous substances. It might not be too expensive, because, e.g., semiconductors are cheap, but whatever the price, it’s cheaper than annihilation, which is now in the cards, because you’re all losers.
Information Overload 