24 research outputs found
Magnetic field-temperature phase diagram of multiferroic (NH4)2FeCl5??H2O
Owing to their overall low energy scales, flexible molecular architectures, and ease of chemical substitution, molecule-based multiferroics are extraordinarily responsive to external stimuli and exhibit remarkably rich phase diagrams. Even so, the stability and microscopic properties of various magnetic states in close proximity to quantum critical points are highly under-explored in these materials. Inspired by these opportunities, we combined pulsed-field magnetization, first-principles calculations, and numerical simulations to reveal the magnetic field???temperature (B???T) phase diagram of multiferroic (NH4)2FeCl5???H2O. In this system, a network of intermolecular hydrogen and halogen bonds creates a competing set of exchange interactions that generates additional structure in the phase diagram???both in the vicinity of the spin flop and near the 30 T transition to the fully saturated state. Consequently, the phase diagrams of (NH4)2FeCl5???H2O and its deuterated analog are much more complex than those of other molecule-based multiferroics. The entire series of coupled electric and magnetic transitions can be accessed with a powered magnet, opening the door to exploration and control of properties in this and related materials
Competing magnetostructural phases in a semiclassical system
The interplay between charge, structure, and magnetism gives rise to rich phase diagrams in complex materials with exotic properties emerging when phases compete. Molecule-based materials are particularly advantageous in this regard due to their low energy scales, flexible lattices, and chemical tunability. Here, we bring together high pressure Raman scattering, modeling, and first principles calculations to reveal the pressure-temperature-magnetic field phase diagram of Mn[N(CN)2]2. We uncover how hidden soft modes involving octahedral rotations drive two pressure-induced transitions triggering the low ??? high magnetic anisotropy crossover and a unique reorientation of exchange planes. These magnetostructural transitions and their mechanisms highlight the importance of spin-lattice interactions in establishing phases with novel magnetic properties in Mn(II)-containing systems
On the Relationships between Generative Encodings, Regularity, and Learning Abilities when Evolving Plastic Artificial Neural Networks
Experimental and Numerical Simulation of Biodegradable Stents with Different Strut Geometries
Towards the evolution of vertical-axis wind turbines using supershapes
© 2014, Springer-Verlag Berlin Heidelberg. We have recently presented an initial study of evolutionary algorithms used to design vertical-axis wind turbines (VAWTs) wherein candidate prototypes are evaluated under fan generated wind conditions after being physically instantiated by a 3D printer. That is, unlike other approaches such as computational fluid dynamics simulations, no mathematical formulations are used and no model assumptions are made. However, the representation used significantly restricted the range of morphologies explored. In this paper, we present initial explorations into the use of a simple generative encoding, known as Gielis superformula, that produces a highly flexible 3D shape representation to design VAWT. First, the target-based evolution of 3D artefacts is investigated and subsequently initial design experiments are performed wherein each VAWT candidate is physically instantiated and evaluated under fan generated wind conditions. It is shown possible to produce very closely matching designs of a number of 3D objects through the evolution of supershapes produced by Gielis superformula. Moreover, it is shown possible to use artificial physical evolution to identify novel and increasingly efficient supershape VAWT designs