The Materials Genome Initiative held a 2017 workshop, that led to this published report: de Pablo et al., "New frontiers for the materials initiative," npj Computational Materials 5, 41 (2019). In part, this report lists various successes of the initiative, due to complementary theoretical, computational, and experimental studies. Perhaps more interestingly, it also lists several challenges for future research. One particular challenge that gets listed in several contexts is related to computational modeling of synthesis:
Improving computational support for the synthesis of soft materials would be very valuable. Although significant steps have been made using machine learning to predict outcomes of simple organic reactions,36,37 extending this capability to include a larger range of chemical variety and macromolecular synthesis would democratize chemical synthesis and accelerate our validation of theories for new chemistries. Computational guidance in the iterative experimental synthesis process is also critical to future advances.38
Recent advances, particularly in x-ray diffraction at high temperatures, pressures, and inert environments could allow a more quantitative understanding of the thermodynamics of crystal synthesis. This could improve computational models of nucleation and crystal formation, help optimize the synthesis of known materials, as well as drive the discovery of new non-equilibrium compounds that are only stable under narrow conditions. Computational models of synthesis would be helpful to encourage feedback between theory and synthesis and enable calculations of optimal synthetic conditions.
Often synthesis is referred to as an art, which exudes respect for those active in the field, but may also signify that theory is lagging significantly behind the practice. Of course, synthesis typically occurs through rapid non-equilibrium processes, and sometimes at very elevated temperatures or in unusual atmospheres. This makes modeling such reactions beyond the input/output scope of simple reaction equations rather challenging, and a very different proposal to the calculation of equilibrium properties of some material post-synthesis. However, smart people have made progress on difficult problems before, and it seems clear that such modeling could potentially bring new insight and advance the art itself - and perhaps the design of novel materials.
Hence, I wonder:
- How well can we theoretically or computationally model the dynamics of synthesis today, whether of molecules or crystals? What is considered state-of-the art, and what are its limitations?
- Have there been any particularly striking successes or failures in this regard?
- Do such computations incorporate quantum physics?
Personally, I am particularly interested in the case of transition metal systems (e.g. oxides). However, I'd suspect there's been considerable advances on the side of molecular and organic chemistry, where there might be a large interest in such methods from the medical industry. In support of this hunch, I was able to find a List of computer-assisted organic synthesis software on Wikipedia, but no matching lists for the general or inorganic cases.