James W. Taylor

A porous treasure: Porous aromatic framework PAF-1 (see picture, blue structure) has been lithiated, giving a reduced framework with an increased gas storage capacity compared to native PAF-1 (by 22, 71, and 320 % for H2, CH4, and CO2, respectively). The reduced framework was examined spectroscopically, and the potential hydrogen storage capacity was calculated.

Evolution, once the preserve of biology, has been widely emulated in software, while physically embodied systems that can evolve have been limited to electronic and robotic devices and have never been artificially implemented in populations of physically interacting chemical entities. Herein we present a liquid-handling robot built with the aim of investigating the properties of oil droplets as a function of composition via an automated evolutionary process. The robot makes the droplets by mixing four different compounds in different ratios and placing them in a Petri dish after which they are recorded using a camera and the behaviour of the droplets analysed using image recognition software to give a fitness value. In separate experiments, the fitness function discriminates based on movement, division and vibration over 21 cycles, giving successive fitness increases. Analysis and theoretical modelling of the data yields fitness landscapes analogous to the genotype–phenotype correlations found in biological evolution. Chemical models of evolving systems are of interest to a range of researchers. Here, the authors use a liquid handling robot and an evolutionary process to explore oil droplets as a function of composition, which they claim may pave the way to explore bottom-up evolution in chemical systems.