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Quantum computing’s potential impact on chemicals

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Quantum computing, built on a new approach to computing, uses the laws of quantum mechanics to increase the speed of certain calculations far beyond the capabilities of classical computers (see sidebar, “What are the basics of quantum computing?”). For the chemical industry, the new quantum-computing capabilities open up the possibility of modeling quantum-mechanical systems, such as molecules, polymers, and solids, at a totally different level of precision. It would thus be possible to identify the most effective molecular designs or structures to accomplish specific tasks and achieve required effects—before synthesizing a single molecule in the lab.

...The design of new small molecules or polymers relies on accurate predictions of molecular properties. While chemical researchers have made a lot of headway with computational-chemistry tools to tackle issues that are ultimately governed by quantum mechanics, today’s tools can provide only rough approximations. For example, tools such as density functional theory (DFT) provide approximations of molecular systems and are somewhat effective for research on small molecules but severely limited for areas such as solids, molecules with heavy atoms, or large molecules (such as proteins).
The improved predictive power of quantum computing applied to molecular design work could have important applications in the development of crop-protection chemicals and many other segments of the specialty-chemicals industry, where accurate foresight into the properties of new molecules will speed development. Take the example of new solid-state materials: the design potential opened up by quantum computing could help new-materials development for a number of leading-edge segments, such as battery materials, semiconductors, magnets, and superconductors.
Similarly, with luminescent molecules for OLED1 displays, it could be possible to model, with a high degree of precision, new molecules that could provide the brightness and hue of the color sought before making them, instead of what is today still largely a trial-and-error process.
...Experts from industry and academia estimate that the first quantum-computing applications that promise to be useful for the chemical industry will require between roughly 1,000 and 10,000 qubits and may be here by the early-to-mid 2020s. This means that the chemical industry is likely to be able to do useful quantum computations much sooner than the other industries where quantum computing is expected to play an important role.



Hand-in-hand with the impending commercialization of carbon-based materials like graphene (see my other thread), and the shrinking of sensors and computers that can be embedded in objects, we're headed for a future where ordinary manmade objects will seem to have magical properties. 


By midcentury, I predict we'll have things like invisibility outfits and sheets of paper that display moving pictures and have impossibly long battery lives. 




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This is the kind of analysis theoreticians hope is true, but probably will not pan out.

I suspect that machine learning based methods will produce approximations that are at least 95% accurate or within 95% of the optimal solution, though can't be proved to be that accurate or near optimal.  For applications, it won't matter if there is proof or not.  
Thus, quantum computing may have a more limited impact than expected.

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