The poor crystalline quality of tin-based perovskite films with unfavorable trap states is the biggest challenge to achieve highly efficient tin-based perovskite solar cells. Here, we reveal the surface-controlled growth of FASnI 3 perovskites and further precisely control the crystallization process by reducing the surface energy of the solution-air surface with a tailor-made pentafluorophen-oxyethylammonium iodide (FOEI). A highly oriented and smooth FASnI 3 -FOEI perovskite film with longer carrier lifetime is achieved with a certificated efficiency of 10.16% from an accredited institute.

Tin‐based perovskites with narrow bandgaps and high charge‐carrier mobilities are promising candidates for the preparation of efficient lead‐free perovskite solar cells (PSCs). However, the crystalline rate of tin‐based perovskites is much faster, leading to abundant trap states and much lower open‐circuit voltage (Voc). Here, hydrogen bonding is introduced to retard the crystalline rate of the FASnI3 perovskite. By adding poly(vinyl alcohol) (PVA), the OH…I− hydrogen bonding interactions between PVA and FASnI3 have the effects of introducing nucleation sites, slowing down the crystal growth, directing the crystal orientation, reducing the trap states, and suppressing the migration of the iodide ions. In the presence of the PVA additive, the FASnI3–PVA PSCs attain higher power conversion efficiency of 8.9% under a reverse scan with significantly improved Voc from 0.55 to 0.63 V, which is one of the highest Voc values for FASnI3‐based PSCs. More importantly, the FASnI3–PVA PSCs exhibit striking long‐term stability, with no decay in efficiency after 400 h of operation at the maximum power point. This approach, which makes use of the OH…I− hydrogen bonding interactions between PVA and FASnI3, is generally applicable for improving the efficiency and stability of the FASnI3‐based PSCs.

We survey the underlying theory behind the large-scale and linear scaling DFT code, Conquest, which shows excellent parallel scaling and can be applied to thousands of atoms with diagonalisation, and millions of atoms with linear scaling. We give details of the representation of the density matrix and the approach to finding the electronic ground state, and discuss the implementation of molecular dynamics with linear scaling. We give an overview of the performance of the code, focussing in particular on the parallel scaling, and provide examples of recent developments and applications.

Given the widespread use of density functional theory (DFT), there is an increasing need for the ability to model large systems (beyond 1,000 atoms). We present a brief overview of the large-scale DFT code Conquest, which is capable of modelling such large systems, and discuss approaches to the generation of consistent, well-converged pseudo-atomic basis sets which will allow such large scale calculations. We present tests of these basis sets for a variety of materials, comparing to fully converged plane wave results using the same pseudopotentials and grids.

Owing to the advances in computational techniques and the increase in computational power, atomistic simulations of materials can simulate large systems with higher accuracy. Complex phenomena can be observed in such state-of-the-art atomistic simulations. However, it has become increasingly difficult to understand what is actually happening and mechanisms, for example, in molecular dynamics (MD) simulations. We propose an unsupervised machine learning method to analyze the local structure around a target atom. The proposed method, which uses the two-step locality preserving projections (TS-LPP), can find a low-dimensional space wherein the distributions of datapoints for each atom or groups of atoms can be properly captured. We demonstrate that the method is effective for analyzing the MD simulations of crystalline, liquid, and amorphous states and the melt-quench process from the perspective of local structures. The proposed method is demonstrated on a silicon single-component system, a silicon-germanium binary system, and a copper single-component system.