Search

While metal halide perovskites (MHPs) have shown great potential for various optoelectronic applications, their widespread adoption in commercial photovoltaic cells or photo-sensors is currently restricted, given that MHPs such as CsPbI3 and FAPbI(3) spontaneously transition to an optically inactive non-perovskite phase at ambient conditions. Herein, we put forward an accurate first-principles procedure to obtain fundamental insight into this phase stability conundrum. To this end, we computationally predict the Helmholtz free energy, composed of the electronic ground state energy and thermal corrections, as this is the fundamental quantity describing the phase stability in polymorphic materials. By adopting the random phase approximation method as a wave function-based method that intrinsically accounts for many-body electron correlation effects as a benchmark for the ground state energy, we validate the performance of different exchange-correlation functionals and dispersion methods. The thermal corrections, accessed through the vibrational density of states, are accessed through molecular dynamics simulations, using a phase-transferable machine learning potential to accurately account for the MHPs' anharmonicity and mitigate size effects. The here proposed procedure is critically validated on CsPbI3, which is a challenging material as its phase stability changes slowly with varying temperature. We demonstrate that our procedure is essential to reproduce the experimental transition temperature, as choosing an inadequate functional can easily miss the transition temperature by more than 100 K. These results demonstrate that the here validated methodology is ideally suited to understand how factors such as strain engineering, surface functionalization, or compositional engineering could help to phase-stabilize MHPs for targeted applications.

This chapter critically reviews the computational tools for the in silico modelling of MOF mechanics from the atomic level onwards. To this end, the macroscopic properties describing the mechanical behaviour of these materials – such as stress and strain – are formulated in terms of atomistic information that can be readily extracted from quantum mechanical or classical computer simulations. This immediately reveals the fundamental challenges that arise when attempting to computationally predict the wide array of responses which MOFs exhibit under mechanical stimuli. The different techniques to extract the mechanical behaviour of MOFs near equilibrium – especially the elastic constants – are contrasted with one another through representative literature examples. While these elastic constants capture the response of a material to small mechanical stimuli, different approaches are required to computationally predict how MOFs respond to larger stresses. A distinction is made between those techniques suitable to describe single-crystal-to-single-crystal phase transitions on the one hand, and those applicable to describe single-crystal-to-amorphous phase transitions, a field that currently remains in its infancy, on the other hand. Through various illustrations from literature, this chapter highlights the open questions arising in each of these topics and explores how ongoing research aims to tackle these challenges.

A diverse database of 268 687 covalent organic framework geometries and accompanying ab initio derived system-specific force fields is developed. This database is ready-to-use, as shown by our high-throughput study for vehicular methane storage.

The black perovskite phase of CsPbI

We present the computational design of naphthalene diimide (NDI)-containing metal pyrazolate metal–organic frameworks (MOFs) [M(NDIDP), M = Zn, Co, and Fe] judiciously bestowed with both framework flexibility and electrical conductivity. M(NDIDP) MOFs exhibit “wine rack” type flexibility, allowing them to partake in pressure-induced structural transitions at low pressures and room temperature. The MOFs are also equipped with closely packed redox-active NDI moieties, which results in dispersive conduction band minima for efficient charge transport and conductivity. Remarkably, structural transitions of the designed MOFs are found to facilitate the rearrangement of NDI moieties. As a result, charge transport properties of M(NDIDP) MOFs can be finely tuned, which is evidenced by the gradual shift from one-dimensional to two-dimensional charge transport and up to 7.5-fold reduction in carrier effective mass (2.76m0–0.37m0) when transitioning between different structural configurations. The unprecedented discovery of flexible MOFs with tunable electrical conductivity arising from configuration-dependent charge transport behavior firmly establishes MOFs as versatile candidate materials for multifunctional electronics.

The high-temperature, all-inorganic CsPbI

pH‐Sensitive dyes are increasingly applied on polymer substrates for the creation of novel sensor materials. Recently, these dye molecules were modified to form a covalent bond with the polymer host. This had a large influence on the pH‐sensitive properties, in particular on the acidity constant (pK a). Obtaining molecular control over the factors that influence the pK a value is mandatory for the future intelligent design of sensor materials. Herein, we show that advanced molecular dynamics (MD) methods have reached the level at which the pK a values of large solvated dye molecules can be predicted with high accuracy. Two MD methods were used in this work: steered or restrained MD and the insertion/deletion scheme. Both were first calibrated on a set of phenol derivatives and afterwards applied to the dye molecule bromothymol blue. Excellent agreement with experimental values was obtained, which opens perspectives for using these methods for designing dye molecules.