Combinatorial Discovery of Lanthanum-Tantalum Oxynitride Solar Light Absorbers with Dilute Nitrogen for Solar Fuel Applications

The Materials Provenance Store

We present a database resulting from high throughput experimentation, primarily on metal oxide solid state materials. The central relational database, the Materials Provenance Store (MPS), manages the metadata and experimental provenance from acquisition of raw materials, through synthesis, to a broad range of materials characterization techniques. Given the primary research goal of materials discovery of solar fuels materials, many of the characterization experiments involve electrochemistry, along with optical, structural, and compositional characterizations. The MPS is populated with all information required for executing common data queries, which typically do not involve direct query of raw data. The result is a database file that can be distributed to users so that they can independently execute queries and subsequently download the data of interest. We propose this strategy as an approach to manage the highly heterogeneous and distributed data that arises from materials science experiments, as demonstrated by the management of over 30 million experiments run on over 12 million samples in the present MPS release.

The Hubbard-U correction and optical properties of d0 metal oxide photocatalysts

We report a systematic investigation of individual and multisite Hubbard-U corrections for the electronic, structural, and optical properties of the metal titanate oxide d⁰ photocatalysts SrTiO₃ and rutile/anatase TiO₂. Accurate bandgaps for these materials can be reproduced with local density approximation and generalized gradient approximation exchange-correlation density functionals via a continuous series of empirically derived U^d and U^p combinations, which are relatively insensitive to the choice of functional. On the other hand, lattice parameters are much more sensitive to the choice of U^d and U^p, but in a systematic way that enables the U^d and U^p corrections to be used to qualitatively gauge the extent of self-interaction error in the electron density. Modest U^d corrections (e.g., 4 eV-5 eV) yield the most reliable dielectric response functions for SrTiO₃ and are comparable to the range of U^d values derived via linear response approaches. For r-TiO₂ and a-TiO₂, however, the U^d,p corrections that yield accurate bandgaps fail to accurately describe both the parallel and perpendicular components of the dielectric response function. Analysis of individual U^d and U^p corrections on the optical properties of SrTiO₃ suggests that the most consequential of the two individual corrections is U^d, as it predominately determines the accuracy of the dominant excitation from O-2p to the Ti-3d t_2g/e_g orbitals. U^p, on the other hand, can be used to shift the entire optical response uniformly to higher frequencies. These results will assist high-throughput and machine learning approaches to screening photoactive materials based on d⁰ photocatalysts.

Combinatorial Synthesis of Oxysulfides in the Lanthanum-Bismuth-Copper System

Establishing synthesis methods for a target material constitutes a grand challenge in materials research, which is compounded with use-inspired specifications on the format of the material. Solar photochemistry using thin film materials is a promising technology for which many complex materials are being proposed, and the present work describes application of combinatorial methods to explore the synthesis of predicted La-Bi-Cu oxysulfide photocathodes, in particular alloys of LaCuOS and BiCuOS. The variation in concentration of three cations and two anions in thin film materials, and crystallization thereof, is achieved by a combination of reactive sputtering and thermal processes including reactive annealing and rapid thermal processing. Composition and structural characterization establish composition-processing-structure relationships that highlight the breadth of processing conditions required for synthesis of LaCuOS and BiCuOS. The relative irreducibility of La oxides and limited diffusion indicate the need for high temperature processing, which conflicts with the temperature limits for mitigating evaporation of Bi and S. Collectively the results indicate that alloys of these phases will require reactive annealing protocols that are uniquely tailored to each composition, motivating advancement of dynamic processing capabilities to further automate discovery of synthesis routes.

Rapid Characterization and Parameter Space Exploration of Perovskites Using an Automated Routine

Hybrid, e.g., organic inorganic, perovskites from the type methylammonium lead iodide CH₃NH₃PbI₃ are promising solar cell materials. However, due to the large parameter space spanned by the manifold combinations of divalent metals with organic cations and anions, an efficient approach is needed to rapidly test and categorize new promising materials. Herein, we developed a high throughput approach for the automated synthesis of perovskite layers with different precursor ratios at varying annealing temperatures. The layers were analyzed by optical absorption and photoluminescence (PL) spectroscopy as well as X-ray diffraction (XRD) and evaluated using two different procedures. The first one is a stepwise exclusion of nonperforming reactant ratios and synthesis conditions by using both spectroscopic techniques, followed by a final validation of the procedure by XRD. In the second procedure, only PL results were consulted in combination with high throughput screening using design of experiments (DoE) to reduce the total number of experiments needed and compared to the manual cascade approach. Noteworthy, by simple PL screening, it was possible to identify the best ratio of perovskite to byproducts and annealing temperature. Thus, only with PL, more detailed results as with the manual protocol were reached, while at the same time the effort for characterization was significantly reduced (by 60% of the experimental time). In conclusion, our approach opens a way toward fast and efficient identification of new promising materials under different reaction and process conditions.