The concept of tolerance factors is applied quantitatively to hybrid inorganic–organic materials that adopt perovskite-like architectures.

Tolerance Factors of possible hybrid perovskites are calculated for over 2500 amine-metal-anion permutations of the periodic table.

X-ray diffraction (XRD) data acquisition and analysis is among the most time-consuming steps in the development cycle of novel thin-film materials. We propose a machine learning-enabled approach to predict crystallographic dimensionality and space group from a limited number of thin-film XRD patterns. We overcome the scarce data problem intrinsic to novel materials development by coupling a supervised machine learning approach with a model-agnostic, physics-informed data augmentation strategy using simulated data from the Inorganic Crystal Structure Database (ICSD) and experimental data. As a test case, 115 thin-film metal-halides spanning three dimensionalities and seven space groups are synthesized and classified. After testing various algorithms, we develop and implement an all convolutional neural network, with cross-validated accuracies for dimensionality and space group classification of 93 and 89%, respectively. We propose average class activation maps, computed from a global average pooling layer, to allow high model interpretability by human experimentalists, elucidating the root causes of misclassification. Finally, we systematically evaluate the maximum XRD pattern step size (data acquisition rate) before loss of predictive accuracy occurs, and determine it to be 0.16° 2θ, which enables an XRD pattern to be obtained and classified in 5.5 min or less.

Porous organic cage molecules are fabricated into thin films and molecular‐sieving membranes. Cage molecules are solution cast on various substrates to form amorphous thin films, with the structures tuned by tailoring the cage chemistry and processing conditions. For the first time, uniform and pinhole‐free microporous cage thin films are formed and demonstrated as molecular‐sieving membranes for selective gas separation.

Advantages of adding just enough alkalis: For organic-inorganic hybrid solar cells, addition of cesium or rubidium cations can improve power conversion efficiency. Correa-Baena et al. used nanoscale x-ray fluorescence imaging to show that the addition of metal cations at low concentrations homogenized the distribution of bromide and iodide anions and also increased charge-carrier lifetimes. However, at high concentrations, aggregation and cluster formation led to increased charge recombination. Science , this issue p. 627