Computer gleans chemical insight from lab notebook failures

A lab notebook can be a litany of unsuccessful, unpublished experiments. Don't bin the data just yet -- they could be useful. Chemists in the United States say that they have created a machine-learning algorithm that beats humans at predicting ways to make crystals, by training it on data both from successful experiments and from trials that didn't work. The team terms these failures'dark reactions', because they are either never written down or are recorded only privately in laboratory notebooks. "Failed reactions contain a vast amount of unreported and unextracted information," says Alex Norquist, a materials-synthesis researcher at Haverford College in Pennsylvania, who is part of the team that has reported the work in Nature1.