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Anderson localization in phonon heat conduction is observed in GaAs/AlAs superlattices with ErAs nanodots.

The previous experimental study illustrated that a direct laser scribing on polyimide (PI) induced the layered graphene, which opened a new door of producing graphene associated materials. However, underlain conversion mechanism is unknown, especially from theoretical perspectives. In this paper, we performed the molecular dynamics (MD) simulation of this mechanism under extreme conditions of the high pressure and temperature which mimic the ones generated by the laser induction. We investigated this process using the ReaxFF potential in a nanosecond time scale. We found out that at a pressure of ~ 3 GPa and temperature of > 2400 K generated from the NVT processes, the layered graphene clusters were crystallized from PI without metal catalysts, which is consistent with the previous experiment. However, if simulated using the NPT processes with a pressure of 27 MPa, the PI were decomposed into small molecules, and no graphene layers were observed. Furthermore, by analyzing the number of the carbon rings and the pair distribution function of them we quantified the crystallinity of the graphene clusters. Through tracing the emission of the small molecules such as H 2 O, N 2 , H 2 , CO we propose the possible reaction paths for both of the NVT and NPT processes.

It is well-known that the atomic-scale and nano-scale configuration of dopants can play a crucial role in determining the electronic properties of materials. However, predicting such effects is challenging due to the large range of atomic configurations that are possible. Here, we present a case study of how deep learning algorithms can enable bandgap prediction in hybridized boron-nitrogen graphene with arbitrary supercell configurations. A material descriptor that enables correlation of structure and bandgap was developed for convolutional neural networks. Bandgaps calculated by ab initio calculations, and corresponding structures, were used as training datasets. The trained networks were then used to predict bandgaps of systems with various configurations. For 4 × 4 and 5 × 5 supercells they accurately predict bandgaps, with a R 2 of >90% and root-mean-square error of 0.1 eV. The transfer learning was performed by leveraging data generated from small supercells to improve the prediction accuracy for 6 × 6 supercells. This work will pave a route to future investigation of configurationally hybridized graphene and other 2D materials. Moreover, given the ubiquitous existence of configurations in materials, this work may stimulate interest in applying deep learning algorithms for the configurational design of materials across different length scales.npj Computational Materials (2019) 5:26 ; https://doi.

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An unprecedented responsive mechanism in a single-layered PVDF film is reported, in which a responsive shape change is driven by the anisotropy of crystal phases.

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Responsive materials with functions of forming three-dimensional (3D) origami and/or kirigami structures have a broad range of applications in bioelectronics, metamaterials, microrobotics, and microelectromechanical (MEMS) systems. To realize such functions, building blocks of actuating components usually possess localized inhomogeneity so that they respond differently to external stimuli. Previous fabrication strategies lie in localizing nonswellable or less-swellable guest components in their swellable host polymers to reduce swelling ability. Herein, inspired by ice plant seed capsules, we report an opposite strategy of implanting swellable guest medium inside nonswellable host polymers to locally enhance the swelling inhomogeneity. Specifically, we adopted a skinning effect induced surface polymerization combined with direct laser writing to control gradient of swellable cyclopentanone (CP) in both vertical and lateral directions of the nonswellable SU-8. For the first time, the laser direct writing was used as a novel strategy for patterning programmable polymer gel films. Upon stimulation of organic solvents, the dual-gradient gel films designed by origami or kirigami principles exhibit reversible 3D shape transformation. Molecular dynamics (MD) simulation illustrates that CP greatly enhances diffusion rates of stimulus solvent molecules in the SU-8 matrix, which offers the driving force for the programmable response. Furthermore, this bioinspired strategy offers unique capabilities in fabricating responsive devices such as a soft gripper and a locomotive robot, paving new routes to many other responsive polymers.