A Wild Idea: Quantum Magnetic Molecular Microscopy
A graphene nanotech compartment containing small samples of atoms or molecules is inserted into a graphene tube. Graphene is harder than diamond, nearly nonmagnetic, and only one carbon atom thick.
A fast triplet reaction sensor array resembling magnetoreception mechanisms is aligned to the outer walls of the chamber, sensitive enough to register magnetic fields of the molecules inside through the chamber walls, with perhaps a sealing apparatus at the insertion end to which further sensors are attached for 360 degrees of pattern recognition.
The magnetic field pattern is then translated and amplified into a digital signal sent to a computer, iteratively analyzed using machine learning algorithms for maximal resolution as well as improvement of the device’s design. This could be capable of imaging the fluctuations within electron orbitals in real time, the equivalent of an fMRI for atoms.
The device would probably have to be placed within a specially designed larger chamber that blocks the Earth’s magnetic field, or rather involve canceling Earth’s magnetic field with a computer in similarity to zeroing out a beaker’s mass when measuring with your standard laboratory scale.
Graphene has a lattice shape, with the area of each space between any four carbon atoms being approximately .06 square nm (nanometers). The diameter of a hydrogen atom is estimated at 10 nm, so this device may be capable of handling all atoms and molecules. By any standard for measuring a chemical’s surface area, the lower limit to what the chamber can contain is quite small.
The magnetic moments of elementary particles within an atom are measured by applying an external magnetic field and averaging deviations. This gives a single energy value for particles and their atomic ensembles, but does not correlate charge fluctuations with actual rather than theoretical shape of the molecule. Angular momentum and orbital momentum are concepts that describe energy distribution, but do not model the current of particles themselves in an embodied state, as if viewing dimensional motion, fluctuation, flow.
A sensor array comprised of many relatively small fast triplet reactions, if it can be assembled somehow, might be able to register not merely the energy but the changing position of atomic constituents as time elapses, whatever that position turns out to consist in. The fast triplet arrays could be like many tiny springs with rates of oscillation that slightly compress or expand as wavicles such as electrons flow by within the atom or molecule and evince a magnetic contour. The rates would be extremely rapid, which is where machine learning comes into play, looking for the slightest of consistent variations in the data over trillions of cycles.
Perhaps this could delineate the holistic structure of wavicles in their natural state of flux rather than as a cobbling together of macroscopic motion concepts for the purpose of reifying energy. The most likely target for this magnetic contour imaging would probably be the electron shell. Could we see something like a spinor complex in action with this device?
Elementary particles such as electrons and protons have single values for their magnetic moments, with researchers measuring relativities of average energy, not structure itself as position and momentum in nature. Subatomic motion in dimensional space has been modeled as relative energy, but can we image it as physical, tangible shape?