The most recognizable staple of chemical engineering since the inception of the profession is the continuous stirred tank reactor. It has done a good job by and large and has been improved plenty. Alas its process is continuous. Material flows into the tank and emerges out of the tank at a variable rate.t On average any element of matter spends a time Tr in the reactor. “On average” -- that means that some matter spends much less time than Tr and some much more. It means that the mixer often mixes material with itself and undermixes other parts. It means that the uniformity of the emerging product is wanting. The larger the reactor, and the more equals are its dimensions the more serious the problem. It can be alleviated by change of size, and geometry. Alas the process variance is inherent in the continuous operation.
Come to think about it, any continues operation with a material flow at a rate of Ft may be matched by a quantum approach where a quantum of fluid Q is taken up by a quantum processing module, QPM -- treated batch-wise to move Q from some given conditions Qi to a subsequent condition Qi+1. Let Tin be the time it takes for the quantum processing module to draw in the quantum of fluid, and let Tp be the time it takes the QPM to carry out what we will call the “payload operation” -- effecting the change Qi to Qi+1. And let Tout be the time it takes for the QPM to discharge Q from within the module.
Since all the four parameters in the right side of the equation are degrees of freedom, then there is no difficulty to exchange the continuous operation with quantum operation.
The Question Is Then -- What Is the Benefit of the Quantum Approach?
We start with uniformity. The captured quantum can be treated until done. Every part of the quantum is subjected to whatever the Quantum Processing does for as long as it does it. This modus operandi gets rid of the time-spent variance experienced in the stirred tank reactor.
The entire sequence of continuous operation can then be replaced with a series of QPM modules, each advancing the state of the raw materials towards the final outcome.
What is left is to find such a module. And with a bit sense of ambition and hutzpah we may even seek a standard structure QFM which will be adjustable to the task at hand.
In chemical engineering we pump, we mix, we react and we separate -- can a single structure module take care of all the above?
The essence of what we do in chemical engineering, when it comes to fluid is that we move the fluid with maximum degrees of freedom. Hence the standard module we are seeking will have to be equipped to move fluid full range. Assuming the QPM will have a container, call it a capsule, where to capture the quantum of fluid, we may think of internal parts that can move fluid in all three dimensions and furthermore change the flow regimen on the spectrum between laminar flow to turbulent flow.
What is the simplest way to move fluid in a given direction? A piston fitted in the container, the capsule, with. a degree of freedom to move back and forth along a given direction, say the longest dimension. Now we need to take care of movement in the other two directions. It takes a small spark to suggest drilling holes in the piston and allowing each hole to be either covered (closed) or uncovered (open). Moving a holes-drilled piston in a closed container will impress momentum on the fluid in the direction of the drilled holes. If a hole is built in an inclined direction towards the direction of movement of the piston then when the piston moves while the hole is open, then it forces fluid to flow through the hole in the inclined direction, which is off the main direction handled by the piston. Now if we add to this piston with holes the freedom to rotate around the main direction of piston movement then we achieve the ability to generate planned flow in all three directions. If the piston does not rotate and large holes are open then the movement of the piston will generate a laminar flow. If on the other hand the piston will rotate and fast, and some holes are open, while the rest are closed, then a movement back and forth of the rotating piston will generate a turbulent flow.
The figure below depicts how two streams emerging from cross inclined holes in the piston are getting thoroughly mixed:

The table below describes the open/closed states (“O”-open, “X” - closed) of the holes in Pin, and Pout the two stationary pistons (edges) of the capsule and the slider piston for the multi-mode piston (MMP) unit basic version:

The quantum fluid dynamics is shown relative to four successive quanta of fluids:

In summary, a rotating piston drilled with fluid pass way holes, while moving from one edge of the capsule to the other, will create any desired flow pattern in the captured quantum of fluid.
The figure below shows (right) a piston that moves inside its capsule with a cogwheel fitting, operated with a built-in rechargeable battery. It has an internal rotating disc with holes that may be open or closed. The figure on the left shows an MMP designed for high viscosity fluids, requiring hydraulic operation.

Let’s see what we have so far. This capsule with the holes-drilled rotating piston inside can readily accomplish pumping. First, it sucks in fluid as its holes are closed. The the piston moves back to the edge of the cylinder where the fluid was pumped in from. It does so with all its holes open and the inlet closed. The liquid then has no choice but to flow past the returning piston to the other side of the capsule. Once at the edge, the piston holes are being closed and the piston moves away from the entry edge, pushing the captured quantum of fluid outside the capsule, all the while sucking in the next quantum, and so quantum after quantum the QPM is pumping the fluid forward. Let the capsule be fitted in a pipeline and this creates an in-pipe pump, which may be run on an internal chargeable battery, or on electrical grid, or on steam, or on a combustion engine, or on hydraulics. This in-pipe or in tube-pump works is applicable over a wide range of sizes.
The rotation of the moving piston with some holes open achieves a desired degree of mixing and unlike the situation with the stirred tank, all the parts of the quantum of fluid undergo the same processing and end up in the same degree of mixing. A fluid-to-fluid reaction depends on the degree of mixing, so the QPM is good for pumping, mixing and fluid-to-fluid reaction.
The figure below shows a piston comprising eight independently moving discs that can be arranged to project a closed piston, a fully open piston, and anything in between.

Let’s move to separation. Let the quantum of fluid be comprised of two mutually immiscible liquids one H heavier than the other, L. Let some ingredient X be present in L and not present much in H, while the process operator wishes X to change residence to H. The QPM will get L and H to mix and develop a large contact surface between L and H (that what mixing means), X will then migrate from L to H. (If some heat exchange is needed, so be it). Once X migrated to the planned degree from L to H, the capsule can be positioned vertically, allowing gravity to push H down and L up. The piston will move holes-open to the border line between L and H then close the holes and move L and H apart. Mission accomplished. The same trick may be applied to distillation -- the pump is placed on the border area between the liquid phase and the gaseous phase and separation is carried out.
A host of separation processes is based on “flow impact media” -- a certain solid media that creates a discriminating force like in chromatography. The Flow Impact Media, FIM, is also appreciated in a catalytic environment. One can then place the FIM in the inner linings of the holes in the piston, or as a membrane in some holes, through which the fluid is forced to pass and rub against the FIM.
So now we list pumping, mixing, reacting and separating -- all carried out via a QPM comprising a capsule and holes-drilled rotating and straight moving piston: a multi mode piston. (MMP).
Other more efficient QFM will be found down the road. But for now we regard the multi mode piston unit MMP unit (MMPU) as an effective quantum processor module.
We can see several advantages
The vision so far is a series of MMP units hooked together such that the output from one is the input of the other. If needed, a capsule feeds to two or more capsules (MMP units), and if needed two or more capsules feed into a single MMP unit and all together we see the MMP unit as a building block for a full-fledged chemical process.
Here below (left) is a depiction of two MMP units hooked together. They are of different diameter but of the same internal volume so that a quantum of fluid from either unit fits into the other. On the right, a division and compound MMP configuration is shown.

The MMP units are assembled together “Lego like” to represent any a complex fluid processing sequence:

Every MMP unit is fully defined by specifying the position of the piston along its direction of motion, by specifying its rotational state and by specifying the open/close state of all the holes in the piston. This is a time dependent tuple that describes the state of the MMP unit over time. This dynamic tuple defines the applied control strategy. It is perfect raw material for inferential AI neural networks.
The hooked-up MMPs can fit in a tight place and lead to compact production units that are fully automated and hence can be operated by unskilled operators. See figure below:

We learn from AI techniques that the greater the relational similarities between remote elements the greater the inferential output thereto. Thus, the universal structure of the multi mode piston unit that is kept through changes in tasks from pumping, mixing, reacting and separating, the more AI wisdom is expected.
In particular, a chemical process with a required output of Z (barrels/day) can be accomplished by constricting n production lines, each put together from hooked-up MMP units, and each with a production capacity of Z/(n-2) barrels/day. This will allow one to run (n-2) production lines in parallel so that together they satisfy the Z production rate requirement. Two production lines are left idle. One line is taken up for routine maintenance, and the other production line is taken up for upgrading options. The n production lines rotate.
The planners of the production line come up with a strategy S to meet the processing challenge. This strategy is expressed through a table that lists all the values of the operational parameters of the all the MMP units, namely the piston shift position, the piston rotational position, and the states of the holes of the piston.
This digital expression of the production strategy may then be subject to small enough randomized modifications, which in turn create a distinction in production efficiency among the (n-2) production lines. These distinctions are exactly what a standard supervised AI algorithm will need to apply a neural network or equivalent methodology to seek a better and more optimized production strategy.
Unlike customary optimization which is done once and then applied again and again. The strategy described here is dynamic, it keeps changing the recommended optimum, following any de facto changes in the attributes of the raw materials or in the exact requirements of the product, or any new regulations for disposing off the refuse.
The MMP unit can be further optimized per its dimensions. The smaller the diameter of the capsule and the longer the cylinder, the greater the ratio between outside surface to volume, and that implies easier possibilities to apply heat exchange contraptions, or to inject additives, or to fit all sorts of analytics onto the surface. On the counter side, the smaller the diameter the more difficult it is to achieve the desired mixing state. The latter can be compensated by increasing the per capsule processing time, allowing the piston to move back and forth more times to achieve the desired mixing. All these related parameters are subject to optimization.