Text written in Basque and translated automatically by Elia without any subsequent editing. SEE ORIGINAL

The change in computational chemistry in the last 50 years

More than a change in computational chemistry, it has been explained, and the fact that it has been explained is undoubtedly the most significant “change”. If we had asked any chemist 50 years ago to name the parts of chemistry, he would have enumerated organic, inorganic, analytical, even biochemical, perhaps physical, but computational chemistry would have been mentioned by few.

But ironically, in about 50 years, computational chemistry has grown above all other parts of chemistry. In other words, computational chemistry is now an essential complement to biochemistry, pharmacology, catalysis, materials science, nanosciences, environmental chemistry (including climate change) and geosciences (including early earthquake detection techniques)... Expressed in this way, it seems to be an essential complement to all existing and non-existing sciences. No, it is not everyone’s, but it is the one that will bring the most significant changes in the short term (Take this prediction with the corresponding account; if it is difficult to “predict” the past, what will it be like to “guess” the future).

Computational chemists have formulated realistic computational models, consistent with physical theories and based on the "fundamental" atomic nature of matter, to describe the structures that produce them and predict their static and dynamic properties with "sufficient" precision. In fact, they have found suitable computational algorithms that can be calculated with the computers of the moment in “rational” time intervals.

They have also created the appropriate languages and discourses to interpret the results obtained. Without going into detail, to explain to experimentalists the chemical meaning of the results obtained, not only to confirm what they have “seen” in their laboratories, but also to inspire new experiments or to be able to give continuity to those already carried out. Breaking new paths in the chemical space, new fields have been explored. This collective initiative has produced a multitude of computational codes, some of which are open to code, others commercial, but which have permeated all modern scientific disciplines with new ideas and cognitive structures that have led to the ability to predict the behaviour of matter on the atomic scale.

Challenges for the next 50 years

The challenge posed by quantum computing is obvious because it is a completely different paradigm from classical computing. Quantum computing takes us to two new workspaces. The first is the construction of material support for the coding of qubits (or qudites) used by quantum computers. Among others, (2,3)-dibromothiophene has been proposed. He doesn't seem to have traveled much, but he can find computational chemistry

you'll probably find better molecules. Second.- Quantum and classical algorithms are barely similar. Therefore, to adapt the classics to the quantum, they must be completely rewritten. In fact, if the diversity of the software ecosystem mentioned above is a fundamental advantage, that is, the fact that algorithms programmed in different ways produce the same results is a strong validation, it is also a weak point, because diversity makes adaptation difficult. But it is a knot that really has to be unraveled before we start doing these quantum calculations.