BBC Inside Science
X-Rays on Mercury, Monkey Tools, Music of Molecules, AI Drivers
The 2019 Royal Society Summer Science exhibition in London is free to enter and continues until Sunday 7th July. BBC Inside Science this week comes from the Society’s HQ in central London.
BepiColombo and the X-rays from Mercury
Prof Emma Bunce, has been part of the team that last year launched an x-ray telescope on a space probe to Mercury. It will be a long journey, not arriving until 2025. As Emma describes, the MIXS instrument, designed and built in the UK, will analyze the x-rays emitted by the different chemicals on the planet’s surface, and so build a map of the abundancies of different atoms across the terrifyingly hostile world. This is only possible because of the strength of the x-rays coming from the sun that strike the atoms on the surface, eliciting a distinctive signature re-emitted back into space.
Capuchin Monkeys and their Tools
Tomos Proffitt and colleagues announced in a recent paper in the journal Nature Ecology and Evolution their study of archaeological evidence of Brazil’s capuchin monkeys using stones and anvils to smash cashew nuts for at least the last 3000 years. It is not the oldest evidence of non-human primate tool use but it is the oldest for monkeys, and suggests tantalisingly that tool use may have emerged in hominin species independently and on numerous occasions.
Chemistry and music pupils at Ilkley Grammar School in the UK have been working together with The University of Bradford to create music specific to different molecules. As A-Level students Amelia Milner and Matthew Hodson describe to Adam, they took the distinctive frequencies of the bonds in certain molecules found in nature and transposed them onto the chromatic musical scale. Then the musicians composed pieces using only that set of notes that evoked some of the properties of the molecules.
AI Drivers and Machine Learning
Genovefa Kefalidou shows Adam a self-driving car circling a track at the exhibition. The technology to identify and track different objects is getting better, and machine learning algorithms can map human actions onto different scenarios to find appropriate responses, but is society ready to trust and accept the benefits they might bring?
Presenter: Adam Rutherford
Composers: Amelia Milner, Matthew Hodson (water, aspirin) and Daniel Burgess (cinnamic acid)
Producer: Alex Mansfield