Liquid–liquid phase separation morphologies in ultra-white beetle scales and a synthetic equivalent

Cyphochilus beetle scales are amongst the brightest structural whites in nature, being highly opacifying whilst extremely thin. However, the formation mechanism for the voided intra-scale structure is unknown. Here we report 3D x-ray nanotomography data for the voided chitin networks of intact white scales of Cyphochilus and Lepidiota stigma. Chitin-filling fractions are found to be 31 ± 2% for Cyphochilus and 34 ± 1% for Lepidiota stigma, indicating previous measurements overestimated their density. Optical simulations using finite-difference time domain for the chitin morphologies and simulated Cahn-Hilliard spinodal structures show excellent agreement. Reflectance curves spanning filling fraction of 5-95% for simulated spinodal structures, pinpoint optimal whiteness for 25% chitin filling. We make a simulacrum from a polymer undergoing a strong solvent quench, resulting in highly reflective (~94%) white films. In-situ X-ray scattering confirms the nanostructure is formed through spinodal decomposition phase separation. We conclude that the ultra-white beetle scale nanostructure is made via liquid–liquid phase separation

Enhanced performance in fusion plasmas through turbulence suppression by megaelectronvolt ions

© 2022, The Author(s), under exclusive licence to Springer Nature Limited.Alpha particles with energies on the order of megaelectronvolts will be the main source of plasma heating in future magnetic confinement fusion reactors. Instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons in the plasma. Furthermore, alpha particles can also excite Alfvénic instabilities, which were previously considered to be detrimental to the performance of the fusion device. Here we report improved thermal ion confinement in the presence of megaelectronvolts ions and strong fast ion-driven Alfvénic instabilities in recent experiments on the Joint European Torus. Detailed transport analysis of these experiments reveals turbulence suppression through a complex multi-scale mechanism that generates large-scale zonal flows. This holds promise for more economical operation of fusion reactors with dominant alpha particle heating and ultimately cheaper fusion electricity.N

Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

The RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of Te, Tiand nehave been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks