Bi Alloying into Rare Earth Double Perovskites Enhances Synthesizability and Visible Light Absorption.

A high throughput combinatorial synthesis utilizing inkjet printing of precursor inks was used to rapidly evaluate Bi-alloying into double perovskite oxides for enhanced visible light absorption. The fast visual screening of photo image scans of the library plates identifies 4-metal oxide compositions displaying an increase in light absorption, which subsequent UV-vis spectroscopy indicates is due to bandgap reduction. Structural characterization by X-ray diffraction (XRD) and Raman spectroscopy demonstrates that the visually darker composition range contains Bi-alloyed Sm2MnNiO6 (double perovskite structure), of the form (Bi,Sm)2MnNiO6. Bi alloying not only increases the visible absorption but also facilitates crystallization of this structure at the relatively low annealing temperature of 615 °C. Investigation of additional seven combinations of a rare earth (RE) and a transition metal (TM) with Bi and Mn indicates that Bi-alloying on the RE site occurs with similar effect in the family of rare earth oxide double perovskites.

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.

Synthesis, optical imaging, and absorption spectroscopy data for 179072 metal oxides.

Optical absorption spectroscopy is an important materials characterization for applications such as solar energy generation. This data descriptor describes the to date (Dec 2018) largest publicly available curated materials science dataset for near infrared to near UV (UV-Vis) light absorbance, composition and processing properties of metal oxides. By supplying the complete synthesis and processing history of each of the 179072 samples from 99965 unique compositions we believe the dataset will enable the community to develop predictive models for materials, such as prediction of optical properties based on composition and processing, and ultimately serve as a benchmark dataset for continued integration of machine learning in materials science. The dataset is also a resource for identifying materials composition and synthesis to attain specific optical properties.

Machine learning of optical properties of materials - predicting spectra from images and images from spectra.

As the materials science community seeks to capitalize on recent advancements in computer science, the sparsity of well-labelled experimental data and limited throughput by which it can be generated have inhibited deployment of machine learning algorithms to date. Several successful examples in computational chemistry have inspired further adoption of machine learning algorithms, and in the present work we present autoencoding algorithms for measured optical properties of metal oxides, which can serve as an exemplar for the breadth and depth of data required for modern algorithms to learn the underlying structure of experimental materials science data. Our set of 178 994 distinct materials samples spans 78 distinct composition spaces, includes 45 elements, and contains more than 80 000 unique quinary oxide and 67 000 unique quaternary oxide compositions, making it the largest and most diverse experimental materials set utilized in machine learning studies. The extensive dataset enabled training and validation of 3 distinct models for mapping between sample images and absorption spectra, including a conditional variational autoencoder that generates images of hypothetical materials with tailored absorption properties. The absorption patterns auto-generated from sample images capture the salient features of ground truth spectra, and band gap energies extracted from these auto-generated patterns are quite accurate with a mean absolute error of 180 meV, which is the approximate uncertainty from traditional extraction of the band gap energy from measurements of the full transmission and reflection spectra. Optical properties of materials are not only ubiquitous in materials applications but also emblematic of the confluence of underlying physical phenomena yielding the type of complex data relationships that merit and benefit from neural network-type modelling.

Solar fuels photoanode materials discovery by integrating high-throughput theory and experiment.

The limited number of known low-band-gap photoelectrocatalytic materials poses a significant challenge for the generation of chemical fuels from sunlight. Using high-throughput ab initio theory with experiments in an integrated workflow, we find eight ternary vanadate oxide photoanodes in the target band-gap range (1.2-2.8 eV). Detailed analysis of these vanadate compounds reveals the key role of VO4 structural motifs and electronic band-edge character in efficient photoanodes, initiating a genome for such materials and paving the way for a broadly applicable high-throughput-discovery and materials-by-design feedback loop. Considerably expanding the number of known photoelectrocatalysts for water oxidation, our study establishes ternary metal vanadates as a prolific class of photoanode materials for generation of chemical fuels from sunlight and demonstrates our high-throughput theory-experiment pipeline as a prolific approach to materials discovery.

High Throughput Light Absorber Discovery, Part 1: An Algorithm for Automated Tauc Analysis.

High-throughput experimentation provides efficient mapping of composition-property relationships, and its implementation for the discovery of optical materials enables advancements in solar energy and other technologies. In a high throughput pipeline, automated data processing algorithms are often required to match experimental throughput, and we present an automated Tauc analysis algorithm for estimating band gap energies from optical spectroscopy data. The algorithm mimics the judgment of an expert scientist, which is demonstrated through its application to a variety of high throughput spectroscopy data, including the identification of indirect or direct band gaps in Fe2O3, Cu2V2O7, and BiVO4. The applicability of the algorithm to estimate a range of band gap energies for various materials is demonstrated by a comparison of direct-allowed band gaps estimated by expert scientists and by automated algorithm for 60 optical spectra.

High Throughput Light Absorber Discovery, Part 2: Establishing Structure-Band Gap Energy Relationships.

Combinatorial materials science strategies have accelerated materials development in a variety of fields, and we extend these strategies to enable structure-property mapping for light absorber materials, particularly in high order composition spaces. High throughput optical spectroscopy and synchrotron X-ray diffraction are combined to identify the optical properties of Bi-V-Fe oxides, leading to the identification of Bi4V1.5Fe0.5O10.5 as a light absorber with direct band gap near 2.7 eV. The strategic combination of experimental and data analysis techniques includes automated Tauc analysis to estimate band gap energies from the high throughput spectroscopy data, providing an automated platform for identifying new optical materials.

High-throughput on-the-fly scanning ultraviolet-visible dual-sphere spectrometer.

We have developed an on-the-fly scanning spectrometer operating in the UV-visible and near-infrared that can simultaneously perform transmission and total reflectance measurements at the rate better than 1 sample per second. High throughput optical characterization is important for screening functional materials for a variety of new applications. We demonstrate the utility of the instrument for screening new light absorber materials by measuring the spectral absorbance, which is subsequently used for deriving band gap information through Tauc plot analysis.

Colorimetric screening for high-throughput discovery of light absorbers.

High-throughput screening is a powerful approach for identifying new functional materials in unexplored material spaces. With library synthesis capable of producing 10(5) to 10(6) samples per day, methods for material screening at rates greater than 1 Hz must be developed. For the discovery of new solar light absorbers, this throughput cannot be attained using standard instrumentation. Screening certain properties, such as the bandgap, are of interest only for phase pure materials, which comprise a small fraction of the samples in a typical solid-state material library. We demonstrate the utility of colorimetric screening based on processing photoscanned images of combinatorial libraries to quickly identify distinct phase regions, isolate samples with desired bandgap, and qualitatively identify samples that are suitable for complementary measurements. Using multiple quaternary oxide libraries containing thousands of materials, we compare colorimetric screening and UV-vis spectroscopy results, demonstrating successful identification of compounds with bandgap suitable for solar applications.