Revealing the free energy landscape of halide perovskites: Metastability and transition characters in CsPbBr3_3 and MAPbI3_3

Halide perovskites have emerged as a promising class of materials for photovoltaic applications. A challenge in these applications is how to prevent the crystal structure from degradation to photovoltaically inactive phases, which requires an understanding of the free energy landscape of these materials. Here, we uncover the free energy landscape of two prototypical halide perovskites, CsPbBr$_3$ and MAPbI$_3$ via atomic scale simulations using umbrella sampling and machine-learned potentials. For CsPbBr$_3$ we find very small free energy differences and barriers close to the transition temperatures for both the tetragonal-to-cubic and the orthorhombic-to-tetragonal transition. For MAPbI$_3$, however, the situation is more intricate. In particular the orthorhombic-to-tetragonal transition exhibits a large free energy barrier and there are several competing tetragonal phases. Using large-scale molecular dynamics simulations we explore the character of these transition and observe latent heat and a discrete change in structural parameters for the tetragonal-to-cubic phase transition in both CsPbBr$_3$ and MAPbI$_3$ indicating first-order transitions. We find that in MAPbI$_3$ the orthorhombic phase has an extended metastability range and furthermore identify a second metastable tetragonal phase. Finally, we compile a phase diagram for MAPbI$_3$ that includes potential metastable phases.Comment: 9 pages, 5 figure

icet - A Python library for constructing and sampling alloy cluster expansions

Alloy cluster expansions (CEs) provide an accurate and computationally efficient mapping of the potential energy surface of multi-component systems that enables comprehensive sampling of the many-dimensional configuration space. Here, we introduce \textsc{icet}, a flexible, extensible, and computationally efficient software package for the construction and sampling of CEs. \textsc{icet} is largely written in Python for easy integration in comprehensive workflows, including first-principles calculations for the generation of reference data and machine learning libraries for training and validation. The package enables training using a variety of linear regression algorithms with and without regularization, Bayesian regression, feature selection, and cross-validation. It also provides complementary functionality for structure enumeration and mapping as well as data management and analysis. Potential applications are illustrated by two examples, including the computation of the phase diagram of a prototypical metallic alloy and the analysis of chemical ordering in an inorganic semiconductor.Comment: 10 page

Computational Design of Alloy Nanostructures for Optical Sensing of Hydrogen

Pd nanoalloys show great potential as hysteresis-free, reliable hydrogen sensors. Here, a multiscale modeling approach is employed to determine optimal conditions for optical hydrogen sensing using the Pd-Au-H system. Changes in hydrogen pressure translate to changes in hydrogen content and eventually the optical spectrum. At the single particle level, the shift of the plasmon peak position with hydrogen concentration (i.e., the "optical" sensitivity) is approximately constant at 180 nm/c(H) for nanodisk diameters of greater than or similar to 100 nm. For smaller particles, the optical sensitivity is negative and increases with decreasing diameter, due to the emergence of a second peak originating from coupling between a localized surface plasmon and interband transitions. In addition to tracking peak position, the onset of extinction as well as extinction at fixed wavelengths is considered. We carefully compare the simulation results with experimental data and assess the potential sources for discrepancies. Invariably, the results suggest that there is an upper bound for the optical sensitivity that cannot be overcome by engineering composition and/or geometry. While the alloy composition has a limited impact on optical sensitivity, it can strongly affect H uptake and consequently the "thermodynamic" sensitivity and the detection limit. Here, it is shown how the latter can be improved by compositional engineering and even substantially enhanced via the formation of an ordered phase that can be synthesized at higher hydrogen partial pressures

Enhancing the sensitivity of magnetic sensors by 3D metamaterial shells

Magnetic sensors are key elements in our interconnected smart society. Their sensitivity becomes essential for many applications in fields such as biomedicine, computer memories, geophysics, or space exploration. Here we present a universal way of increasing the sensitivity of magnetic sensors by surrounding them with a spherical metamaterial shell with specially designed anisotropic magnetic properties. We analytically demonstrate that the magnetic field in the sensing area is enhanced by our metamaterial shell by a known factor that depends on the shell radii ratio. When the applied field is non-uniform, as for dipolar magnetic field sources, field gradient is increased as well. A proof-of-concept experimental realization confirms the theoretical predictions. The metamaterial shell is also shown to concentrate time-dependent magnetic fields upto frequencies of 100 kHz

High-throughput characterization of transition metal dichalcogenide alloys: Thermodynamic stability and electronic band alignment

Alloying offers a way to tune many of the properties of the transition metal dichalcogenide (TMD) monolayers. While these systems in many cases have been thoroughly investigated previously, the fundamental understanding of critical temperatures, phase diagrams and band edge alignment is still incomplete. Based on first principles calculations and alloy cluster expansions we compute the phase diagrams 72 TMD monolayer alloys and classify the mixing behavior. We show that ordered phases in general are absent at room temperature but that there exists some alloys, which have a stable Janus phase at room temperature. Furthermore, for a subset of these alloys, we quantify the band edge bowing and show that the band edge positions for the mixing alloys can be continuously tuned in the range set by the boundary phases.Comment: 10 pages, 6 figure

Revealing the Free Energy Landscape of Halide Perovskites: Metastability and Transition Characters in CsPbBr₃ and MAPbI₃

Halide perovskites have emerged as a promising class of materials for photovoltaic applications. A challenge of these applications is preventing the crystal structure from degrading to photovoltaically inactive phases, which requires an understanding of the free energy landscape of these materials. Here, we uncover the free energy landscape of two prototypical halide perovskites, CsPbBr3 and MAPbI3, via atomic-scale simulations using umbrella sampling and machine-learned potentials. For CsPbBr3, we find very small free energy differences and barriers close to the transition temperatures for both the tetragonal-to-cubic and orthorhombic-to-tetragonal transitions. For MAPbI3, however, the situation is more intricate. In particular, the orthorhombic-to-tetragonal transition exhibits a large free energy barrier, and there are several competing tetragonal phases. Using large-scale molecular dynamics simulations, we explore the character of these transitions and observe the latent heat and a discrete change in the structural parameters for the tetragonal-to-cubic phase transitions in both CsPbBr3 and MAPbI3, indicating first-order transitions. We find that in MAPbI3, the orthorhombic phase has an extended metastability range, and we identify a second metastable tetragonal phase. Finally, we compile a phase diagram for MAPbI3 that includes potential metastable phases

Computational Design of Alloy Nanostructures for Optical Sensing of Hydrogen

Pd nanoalloys show great potential as hysteresis-free, reliable hydrogen sensors. Here, a multi-scale modeling approach is employed to determine optimal conditions for optical hydrogen sensing using the Pd-Au-H system. Changes in hydrogen pressure translate to changes in hydrogen content and eventually the optical spectrum. At the single particle level, the shift of the plasmon peak position with hydrogen concentration (i.e., the "optical" sensitivity) is approximately constant at 180 nm/c_H for nanodisk diameters >~ 100 nm. For smaller particles, the optical sensitivity is negative and increases with decreasing diameter, due to the emergence of a second peak originating from coupling between a localized surface plasmon and interband transitions. In addition to tracking peak position, the onset of extinction as well as extinction at fixed wavelengths is considered. We carefully compare the simulation results with experimental data and assess the potential sources for discrepancies. Invariably, the results suggest that there is an upper bound for the optical sensitivity that cannot be overcome by engineering composition and/or geometry. While the alloy composition has a limited impact on optical sensitivity, it can strongly affect H uptake and consequently the "thermodynamic" sensitivity and the detection limit. Here, it is shown how the latter can be improved by compositional engineering and even substantially enhanced via the formation of an ordered phase that can be synthesized at higher hydrogen partial pressures.Comment: 14 pages, 8 figure