Successful materials innovations can transform society. However, materials research often involves long timelines and low success probabilities, dissuading investors who have expectations of shorter times from bench to business. A combination of emergent technologies could accelerate the pace of novel materials development by 10x or more, aligning the timelines of stakeholders (investors and researchers), markets, and the environment, while increasing return-on-investment. First, tool automation enables rapid experimental testing of candidate materials. Second, high-throughput computing (HPC) concentrates experimental bandwidth on promising compounds by predicting and inferring bulk, interface, and defect-related properties. Third, machine learning connects the former two, where experimental outputs automatically refine theory and help define next experiments. We describe state-of-the-art attempts to realize this vision and identify resource gaps. We posit that over the coming decade, this combination of tools will transform the way we perform materials research. There are considerable first-mover advantages at stake, especially for grand challenges in energy and related fields, including computing, healthcare, urbanization, water, food, and the environment. The development of novel materials has long been stymied by a mismatch of time constants (Figure 1). Materials development typically occurs over a 15-25-year time horizon, sometimes requiring synthesis and characterization of millions of samples. However, corporate and government funders desire tangible results within the residency time of their leadership, typically 2-5 years. The residency time for postdocs and students in a research laboratory is usually 2-5 years; when a project outlasts the residency of a single individual, seamless continuity of motivation and intellectual property is often the exception, not the rule. Market drivers of novel materials development, informed by business competition and environmental considerations, often demand solutions within a shorter time horizon. This mismatch in time constants results in a historically poor return-on-investment of energy-materials (cleantech) research relative to comparable investments in medical or software development. 1

Perovskite solar cells (PSCs) use perovskites with an APbX structure, where A is a monovalent cation and X is a halide such as Cl, Br, and/or I. Currently, the cations for high-efficiency PSCs are Rb, Cs, methylammonium (MA), and/or formamidinium (FA). Molecules larger than FA, such as ethylammonium (EA), guanidinium (GA), and imidazolium (IA), are usually incompatible with photoactive "black"-phase perovskites. Here, novel molecular descriptors for larger molecular cations are introduced using a "globularity factor", i.e., the discrepancy of the molecular shape and an ideal sphere. These cationic radii differ significantly from previous reports, showing that especially ethylammonium (EA) is only slightly larger than FA. This makes EA a suitable candidate for multication 3D perovskites that have potential for unexpected and beneficial properties (suppressing halide segregation, stability). This approach is tested experimentally showing that surprisingly large quantities of EA get incorporated, in contrast to most previous reports where only small quantities of larger molecular cations can be tolerated as "additives". MA/EA perovskites are characterized experimentally with a band gap ranging from 1.59 to 2.78 eV, demonstrating some of the most blue-shifted PSCs reported to date. Furthermore, one of the compositions, MA EA PbBr , shows an open circuit voltage of 1.58 V, which is the highest to date with a conventional PSC architecture.

Despite the fact that perovskite solar cells (PSCs) have a strong potential as a next-generation photovoltaic technology due to continuous efficiency improvements and the tunable properties, some important obstacles remain before industrialization is feasible. For example, the selection of low-cost or easy-to-prepare materials is essential for back-contacts and hole-transporting layers. Likewise, the choice of conductive substrates, the identification of large-scale manufacturing techniques as well as the development of appropriate aging protocols are key objectives currently under investigation by the international scientific community. This Review analyses the above aspects and highlights the critical points that currently limit the industrial production of PSCs and what strategies are emerging to make these solar cells the leaders in the photovoltaic field.

L subcells integrated into a monolithic tandem solar cell is challenging though crucial in order to identify performance limiting loss mechanisms. This method can be used to improve the study of the mutual influence of adjacent subcells in the fully fabricated device, which has been an unfeasible task up to now.

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