A programmable chemical computer with memory and pattern recognition.

Current computers are limited by the von Neumann bottleneck, which constrains the throughput between the processing unit and the memory. Chemical processes have the potential to scale beyond current computing architectures as the processing unit and memory reside in the same space, performing computations through chemical reactions, yet their lack of programmability limits them. Herein, we present a programmable chemical processor comprising of a 5 by 5 array of cells filled with a switchable oscillating chemical (Belousov-Zhabotinsky) reaction.

Implications of the variation in biological O natural abundance in body water to inform use of Bayesian methods for modelling total energy expenditure when using doubly labelled water.

Rationale: Variation in O natural abundance can lead to errors in the calculation of total energy expenditure (TEE) when using the doubly labelled water (DLW) method. The use of Bayesian statistics allows a distribution to be assigned to O natural abundance, thus allowing a best-fit value to be used in the calculation. The aim of this study was to calculate within-subject variation in O natural abundance and apply this to our original working model for TEE calculation.

Artificial intelligence exploration of unstable protocells leads to predictable properties and discovery of collective behavior.

Protocell models are used to investigate how cells might have first assembled on Earth. Some, like oil-in-water droplets, can be seemingly simple models, while able to exhibit complex and unpredictable behaviors. How such simple oil-in-water systems can come together to yield complex and life-like behaviors remains a key question.

Graphene Near-Degenerate Four-Wave Mixing for Phase Characterization of Broadband Pulses in Ultrafast Microscopy.

We investigate near-degenerate four-wave mixing in graphene using femtosecond laser pulse shaping microscopy. Intense near-degenerate four-wave mixing signals on either side of the exciting laser spectrum are controlled by amplitude and phase shaping. Quantitative signal modeling for the input pulse parameters shows a spectrally flat phase response of the near-degenerate four-wave mixing due to the linear dispersion of the massless Dirac Fermions in graphene.