How to Accelerate R&D and Optimize Experiment Planning with Machine Learning and Data Science

Accelerating R&D is essential to address some of the challenges humanity is currently facing, such as achieving the global sustainability goals. Today’s Edisonian approach of trial-and-error still prevalent in R&D labs takes up to two decades of fundamental and applied research for new materials to reach the market. Turning around this situation calls for strategies to upgrade R&D and expedite innovation. By conducting smart experiment planning that is data-driven and guided by AI/ML, researchers can more efficiently search through the complex - often constrained - space of possible experiments and find or hit the global optima much faster than with the current approaches. Moreover, with digitized data management, researchers will be able to maximize the utility of their data in the short and long terms with the aid of statistics, ML and visualization tools. In what follows, we describe a framework and lay out the key technologies to accelerate R&D and optimize experiment plannin

The influence of sorbitol doping on aggregation and electronic properties of PEDOT:PSS: a theoretical study

Many organic electronics applications such as organic solar cells or thermoelectric generators rely on PEDOT:PSS as a conductive polymer that is printable and transparent. It was found that doping PEDOT:PSS with sorbitol enhances the conductivity through morphological changes. However, the microscopic mechanism is not well understood. In this work, we combine computational tools with machine learning to investigate changes in morphological and electronic properties of PEDOT:PSS when doped with sorbitol. We find that sorbitol improves the alignment of PEDOT oligomers, leading to a reduction of energy disorder and an increase in electronic couplings between PEDOT chains. The high accuracy (r2 > 0.9) and speed up of energy level predictions of neural networks compared to density functional theory enables us to analyze HOMO energies of PEDOT oligomers as a function of time. We find a surprisingly low degree of static energy disorder compared to other organic semiconductors. This finding might help to better understand the microscopic origin of the high charge carrier mobility of PEDOT:PSS in general and potentially help to design new conductive polymers

Kinetics of the Regeneration by Iodide of Dye Sensitizers Adsorbed on Mesoporous Titania

Regeneration of dye sensitizer molecules by reducing species contained in the electrolyte is a key mechanism in liquid dye-sensitized solar cells because it competes kinetically with a detrimental charge recombination process. Kinetics of the reduction by iodide ions of the oxidized states (S+) of two RuII complex dyes and four organic π-conjugated bridged donor−acceptor sensitizers were examined as a function of the electrolyte concentration. Results show that two different cases can be distinguished. A sublinear behavior of the regeneration rate and a plateau value reached at high bulk iodide concentrations were found for N820 ruthenium dye and interpreted as being due to an associative interaction involving the formation of (S+, I−)···I− surface complexes prior to the reaction. On the other hand, feeble reaction rates at low electrolyte concentrations and a superlinear behavior are observed predominantly for the organic dyes, pointing to a repulsive interaction between the dyed surface and iodide anions. At higher iodide bulk concentration, a linear behavior is reached, providing an estimate of a second-order rate constant. A correlation of these two opposite behaviors with the structure of the dye is observed, emphasizing the role of sulfur atoms in the association of I− anions in the dye-sensitized layer. These findings allow for a better understanding of the dye−electrolyte interaction and of the effect of the iodide concentration on the photovoltaic performances of dye-sensitized solar cells

Interface Molecular engineering for laminated monolithic perovskite/silicon tandem solar cells with 80.4% fill factor

A multipurpose interconnection layer based on poly(3,4‐ethylenedioxythiophene) doped with poly(styrene sulfonate) (PEDOT:PSS), and d‐sorbitol for monolithic perovskite/silicon tandem solar cells is introduced. The interconnection of independently processed silicon and perovskite subcells is a simple add‐on lamination step, alleviating common fabrication complexities of tandem devices. It is demonstrated experimentally and theoretically that PEDOT:PSS is an ideal building block for manipulating the mechanical and electrical functionality of the charge recombination layer by controlling the microstructure on the nano‐ and mesoscale. It is elucidated that the optimal functionality of the recombination layer relies on a gradient in the d‐sorbitol dopant distribution that modulates the orientation of PEDOT across the PEDOT:PSS film. Using this modified PEDOT:PSS composite, a monolithic two‐terminal perovskite/silicon tandem solar cell with a steady‐state efficiency of 21.0%, a fill factor of 80.4%, and negligible open circuit voltage losses compared to single‐junction devices is shown. The versatility of this approach is further validated by presenting a laminated two‐terminal monolithic perovskite/organic tandem solar cell with 11.7% power conversion efficiency. It is envisioned that this lamination concept can be applied for the pairing of multiple photovoltaic and other thin film technologies, creating a universal platform that facilitates mass production of tandem devices with high efficiency