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 Fe_2O_3, Cu_2V_2O_7, and BiVO_4. 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

Growth and characterization of wide–gap semiconducting oxide and chalcogenide thin films by pulsed laser deposition

The preparation and characterization of thin film oxides and chalcogenides by pulsed laser deposition (PLD) is presented. An overview of fundamental PLD concepts are presented and are followed by a description implementation and development of the PLD systems at OSU. We present the results of thin film growth of high electron mobility In₂O₃:W in which we have prepared films exhibiting µ > 100 cm²/Vs on vitreous SiO₂ substrates. The growth of Cu₃TaCh₄ (Ch = S, Se) films is outlined as a two step process consisting of PLD of ceramic targets followed by ex-situ annealing in chalcogenide vapor. Also, BiCuOSe thin films have been prepared in-situ and exhibit a high hole mobility up to 4 cm²/Vs. A discussion of their electronic structure is presented which explains the nature of the low band gap energy on the basis of deep Bi 6p level at the conduction band minimum. Finally, the results of BaBiO₃ thin film preparation are presented in which both polycrystalline and highly (00l) oriented samples were grown

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

Combinatorial screening yields discovery of 29 metal oxide photoanodes for solar fuel generation

Combinatorial synthesis combined with high throughput electrochemistry enabled discovery of 29 ternary oxide photoanodes, 15 with visible light response for oxygen evolution. Y₃Fe₅O₁₂ and trigonal V₂CoO₆ emerge as particularly promising candidates due to their photorepsonse at sub-2.4 eV illumination

Analyzing machine learning models to accelerate generation of fundamental materials insights

Machine learning for materials science envisions the acceleration of basic science research through automated identification of key data relationships to augment human interpretation and gain scientific understanding. A primary role of scientists is extraction of fundamental knowledge from data, and we demonstrate that this extraction can be accelerated using neural networks via analysis of the trained data model itself rather than its application as a prediction tool. Convolutional neural networks excel at modeling complex data relationships in multi-dimensional parameter spaces, such as that mapped by a combinatorial materials science experiment. Measuring a performance metric in a given materials space provides direct information about (locally) optimal materials but not the underlying materials science that gives rise to the variation in performance. By building a model that predicts performance (in this case photoelectrochemical power generation of a solar fuels photoanode) from materials parameters (in this case composition and Raman signal), subsequent analysis of gradients in the trained model reveals key data relationships that are not readily identified by human inspection or traditional statistical analyses. Human interpretation of these key relationships produces the desired fundamental understanding, demonstrating a framework in which machine learning accelerates data interpretation by leveraging the expertize of the human scientist. We also demonstrate the use of neural network gradient analysis to automate prediction of the directions in parameter space, such as the addition of specific alloying elements, that may increase performance by moving beyond the confines of existing data

Society for Research on Nicotine and Tobacco

The proceedings of the inaugural scientific meeting of the Society for Research on Nicotine and Tobacco (SRNT) are summarized. The primary objective of the meeting was to foster the exchange of information on the effects of nicotine and tobacco use, as well as factors which influence their use, drawing from biological, behavioral and social sciences. Much of this research can be viewed as a tale of two drugs nicotine as a key to an important public health problem, and nicotine as a classical tool of physiological and pharmacological research. A historical overview of research on both drugs is provided first. Public policy alternatives for reducing the prevalence of tobacco use have been derived in part from basic and clinical research results and are briefly outlined. Evidence for genetic determinants on nicotine use and effects is presented using data from twin studies and from molecular genetic research with humans and animals. Consistent with this research, there is evidence of individual differences in pharmacokinetics and effects of nicotine, which could account for differences in smoking behavior and nicotine dependence. Finally, recent developments in the therapeutic uses of nicotine and novel nicotinic agonists with schizophrenia, Alzheimer's disease, Parkinson's disease, Tourette's syndrome and ulcerative colitis are presented. Overall, the research presented at the meeting demonstrated the vast diversity of areas of study involving nicotine and tobacco, as well as the rich opportunities for cross-communication among researchers from different disciplines.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72963/1/j.1360-0443.1996.91112915.x.pd

Mn_2V_2O_7: An Earth Abundant Light Absorber for Solar Water Splitting

Complex oxide β-Mn_2V_2O_7 is identified as exhibiting near-optimal band energetics for solar fuel applications among known metal oxides. Experiments, corroborated by theory, indicate a bandgap near 1.8 eV. The calculations predict that β-Mn_2V_2O_7 has well-aligned band edge energies for the hydrogen evolution reaction and oxygen evolution reaction. Photoelectrochemical measurements indicate appreciable photocurrent, corroborating the predictions

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

Enhanced Bulk Transport in Copper Vanadate Photoanodes Identified by Combinatorial Alloying

The impact of alloying on the performance of β-Cu₂V₂O₇ photoanodes was investigated using inkjet printing of composition libraries containing 1,809 Cu₂V₂O₇-based photoanodes. Six elements (Zr, Ca, Hf, Gd, La, and Lu) were alloyed and pairwise co-alloyed at concentrations up to 7 at % into Cu-rich, stoichiometric, and Cu-deficient host Cu₂V₂O₇. A 1.7-fold increase in oxygen evolution photocurrent in pH 9.2 electrolyte was obtained by alloying Ca into β-Cu₂V₂O₇. Experiments employing a hole scavenger to better characterize bulk charge separation and transport revealed a 2.2-fold increase in photoactivity via alloying with Hf, Zr, and La, which increased to 2.7-fold upon co-alloying these elements with Ca. Concurrent with increased photoactivity is substantially decreased photon absorption between 1.5 and 2 eV, a range reported to coincide with high exciton absorption in β-Cu₂V₂O₇, motivating further exploration of whether these co-alloy compositions may destabilize the excitonic state that appears to have limited performance to date