High-Throughput Selection and Experimental Realization of Two New Ce-Based Nitride Perovskites: CeMoN3 and CeWN3.

Nitride perovskites have only been experimentally realized in very few cases despite the widespread existence and commercial importance of perovskite materials. From oxide perovskites used in ultrasonics to halide perovskites that have revolutionized the photovoltaics industry, the discovery of new perovskite materials has historically impacted a wide number of fields. Here, we add two new perovskites, CeWN3 and CeMoN3, to the list of experimentally realized perovskite nitrides using high-throughput computational screening and subsequent high-throughput thin film growth techniques. Candidate compositions are first down-selected using a tolerance factor and then thermochemical stability. A novel competing fluorite-family phase is identified for both material systems, which we hypothesize is a transient intermediate phase that crystallizes during the evolution from an amorphous material to a stable perovskite. Different processing routes to overcome the competing fluorite phase and obtain phase-pure nitride perovskites are demonstrated for the CeMoN3-x and CeWN3-x material systems, which provide a starting point for the development of future nitride perovskites. Additionally, we find that these new perovskite phases have interesting low-temperature magnetic behavior: CeMoN3-x orders antiferromagnetically below T N ≈ 8 K with indications of strong magnetic frustration, while CeWN3-x exhibits no long-range order down to T = 2 K but has strong antiferromagnetic correlations. This work demonstrates the importance and effectiveness of using high-throughput techniques, both computational and experimental: they are integral to optimize the process of realizing two entirely novel nitride perovskites.

Zinc Titanium Nitride Semiconductor toward Durable Photoelectrochemical Applications.

Photoelectrochemical fuel generation is a promising route to sustainable liquid fuels produced from water and captured carbon dioxide with sunlight as the energy input. Development of these technologies requires photoelectrode materials that are both photocatalytically active and operationally stable in harsh oxidative and/or reductive electrochemical environments. Such photocatalysts can be discovered based on co-design principles, wherein design for stability is based on the propensity for the photocatalyst to self-passivate under operating conditions and design for photoactivity is based on the ability to integrate the photocatalyst with established semiconductor substrates. Here, we report on the synthesis and characterization of zinc titanium nitride (ZnTiN2) that follows these design rules by having a wurtzite-derived crystal structure and showing self-passivating surface oxides created by electrochemical polarization. The sputtered ZnTiN2 thin films have optical absorption onsets below 2 eV and n-type electrical conduction of 3 S/cm. The band gap of this material is reduced from the 3.36 eV theoretical value by cation-site disorder, and the impact of cation antisites on the band structure of ZnTiN2 is explored using density functional theory. Under electrochemical polarization, the ZnTiN2 surfaces have TiO2- or ZnO-like character, consistent with Materials Project Pourbaix calculations predicting the formation of stable solid phases under near-neutral pH. These results show that ZnTiN2 is a promising candidate for photoelectrochemical liquid fuel generation and demonstrate a new materials design approach to other photoelectrodes with self-passivating native operational surface chemistry.

Synthesis of LaWN3 nitride perovskite with polar symmetry.

Oxide materials with the perovskite structure have been used in sensors and actuators for half a century, and halide perovskites transformed photovoltaics research in the past decade. Nitride perovskites have been computationally predicted to be stable, but few have been synthesized, and their properties remain largely unknown. We synthesized and characterized a nitride perovskite lanthanum tungsten nitride (LaWN3) in the form of oxygen-free sputtered thin films, according to spectroscopy, scattering, and microscopy techniques. We report a large piezoelectric response measured with scanning probe microscopy that together with synchrotron diffraction confirm polar symmetry of the perovskite LaWN3. Our LaWN3 synthesis should inspire growth of other predicted nitride perovskites, and measurements of their properties could lead to functional integration with nitride semiconductors for microelectromechanical devices.

Research data infrastructure for high-throughput experimental materials science.

The High-Throughput Experimental Materials Database (HTEM-DB, htem.nrel.gov) is a repository of inorganic thin-film materials data collected during combinatorial experiments at the National Renewable Energy Laboratory (NREL). This data asset is enabled by NREL's Research Data Infrastructure (RDI), a set of custom data tools that collect, process, and store experimental data and metadata. Here, we describe the experimental data flow from the RDI to the HTEM-DB to illustrate the strategies and best practices currently used for materials data at NREL. Integration of the data tools with experimental instruments establishes a data communication pipeline between experimental researchers and data scientists. This work motivates the creation of similar workflows at other institutions to aggregate valuable data and increase their usefulness for future machine learning studies. In turn, such data-driven studies can greatly accelerate the pace of discovery and design in the materials science domain.

Instrument for spatially resolved, temperature-dependent electrochemical impedance spectroscopy of thin films under locally controlled atmosphere.

We demonstrate an instrument for spatially resolved measurements (mapping) of electrochemical impedance under various temperatures and gas environments. Automated measurements are controlled by a custom LabVIEW program, which manages probe motion, sample motion, temperature ramps, and potentiostat functions. Sample and probe positioning is provided by stepper motors. Dry or hydrated atmospheres (air or nitrogen) are available. The configurable heater reaches temperatures up to 500 °C, although the temperature at the sample surface is moderated by the gas flow rate. The local gas environment is controlled by directing flow toward the sample via a glass enclosure that surrounds the gold wire probe. Software and hardware selection and design are discussed. Reproducibility and accuracy are quantified on a Ba(Zr,Y)O3-δ proton-conducting electrolyte thin film synthesized by pulsed laser deposition. The mapping feature of the instrument is demonstrated on a compositionally graded array of electrocatalytically active Ba(Co,Fe,Zr,Y)O3-δ thin film microelectrodes. The resulting data indicate that this method proficiently maps property trends in these materials, thus demonstrating the reliability and usefulness of this method for investigating electrochemically active thin films.

A randomized pilot program to reduce opioid use following dental surgery and increase safe medication return.

Research indicates that increased cumulative exposure (duration of administration and strength of dose) is associated with long-term opioid use. Because dentists represent some of the highest opioid prescribing medical professionals in the US, dental practices offer a critical site for intervention. The current study used a randomized clinical trial design to examine the efficacy of an opioid misuse prevention program (OMPP), presented as a brief intervention immediately prior to dental extraction surgery. The OMPP provided educational counseling about risks and appropriate use of opioid medication, as well as 28 tablets of ibuprofen (200 mg) and 28 tablets of acetaminophen (500 mg) for weaning off opioid medication. This was compared with a Treatment as Usual (TAU) control condition. Participants were individuals presenting for surgery who were eligible for opioid medication (N = 76). Follow up assessment was conducted at 1 week following surgery, with 4 individuals refusing follow up or not prescribed opioid. Intent to treat analysis indicated a non-significant treatment group effect (N = 72, Beta = 0.16, p = .0835), such that the OMPP group self-reported less opioid use (in morphine milligram equivalents, MMEs) than the TAU group (37.94 vs. 47.79, effect size d = 0.42). Sensitivity analysis, excluding individuals with complications following surgery (n = 6) indicated a significant treatment group effect (N = 66, Beta = 0.24, p = .0259), such that the OMPP group self-reported significantly less MMEs than the TAU group (29.74 vs. 43.59, effect size d = 0.56). Results indicate that a 10-minute intervention and provision of non-narcotic pain medications may reduce the amount of self-administered opioid medication following dental surgery.

COMBIgor: Data-Analysis Package for Combinatorial Materials Science.

Combinatorial experiments involve synthesis of sample libraries with lateral composition gradients requiring spatially resolved characterization of structure and properties. Because of the maturation of combinatorial methods and their successful application in many fields, the modern combinatorial laboratory produces diverse and complex data sets requiring advanced analysis and visualization techniques. In order to utilize these large data sets to uncover new knowledge, the combinatorial scientist must engage in data science. For data science tasks, most laboratories adopt common-purpose data management and visualization software. However, processing and cross-correlating data from various measurement tools is no small task for such generic programs. Here we describe COMBIgor, a purpose-built open-source software package written in the commercial Igor Pro environment and designed to offer a systematic approach to loading, storing, processing, and visualizing combinatorial data. It includes (1) methods for loading and storing data sets from combinatorial libraries, (2) routines for streamlined data processing, and (3) data-analysis and -visualization features to construct figures. Most importantly, COMBIgor is designed to be easily customized by a laboratory, group, or individual in order to integrate additional instruments and data-processing algorithms. Utilizing the capabilities of COMBIgor can significantly reduce the burden of data management on the combinatorial scientist.

Adverse childhood experiences predict opioid relapse during treatment among rural adults.

Adverse childhood experiences (ACE) are a public health concern and strong predictor of substance abuse, but no studies to date have explored the association between ACE and opioid relapse during medication-assisted treatment. Using an observational design, we examined this relationship using archived medical records of 87 patients who attended opioid use disorder treatment (buprenorphine-naloxone and group counseling) at a rural medical clinic. All variables were collected from medical files. ACE scores were derived from a 10-item screening questionnaire administered at intake, a regular procedure for this clinic. The primary outcome was opioid relapse observed at each visit, as indicated by self-reported opioid use, positive urine drug screen for opioids, or prescription drug database results for opioid acquisition. The sample was 100% Caucasian and 75% male. A total of 2052 visit observations from the 87 patients were extracted from the medical records. Patients had an average of 23.6 (SD = 22) treatment visits. Opioid relapse occurred in 54% of patients. Results indicated that for every unit increase in ACE score, there was an increase of 17% in the odds of relapse (95% CI: 1.05-1.30, p = .005). Additionally, each treatment visit was associated with a 2% reduction in the odds of opioid relapse (95% CI: 0.97-0.99, p = .008). We conclude that ACE may increase the risk for poor response to buprenorphine-naloxone treatment due to high rates of opioid relapse during the first treatment visits. However, consistent adherence to treatment is likely to reduce the odds of opioid relapse.

Characterization of Elastic Modulus Across the (Al1-xScx)N System Using DFT and Substrate-Effect-Corrected Nanoindentation.

Knowledge of accurate values of elastic modulus of (Al1-xScx)N is required for design of piezoelectric resonators and related devices. Thin films of (Al1-xScx)N across the entire composition space are deposited and characterized. Accuracy of modulus measurements is improved and quantified by removing the influence of substrate effects and by direct comparison of experimental results with density functional theory calculations. The 5%-30% Sc compositional range is of particular interest for piezoelectric applications and is covered at higher compositional resolution here than in previous work. The reduced elastic modulus is found to decrease by as much as 40% with increasing Sc concentration in the wurtzite phase according to both experimental and computational techniques, whereas Sc-rich rocksalt-structured films exhibit little variation in modulus with composition.

Combinatorial Nitrogen Gradients in Sputtered Thin Films.

High-throughput synthesis and characterization methods can significantly accelerate the rate of experimental research. For physical vapor deposition (PVD), these methods include combinatorial sputtering with intentional gradients of metal/metalloid composition, temperature, and thickness across the substrate. However, many other synthesis parameters still remain out of reach for combinatorial methods. Here, we extend combinatorial sputtering parameters to include gradients of gaseous elements in thin films. Specifically, a nitrogen gradient was generated in a thin film sample library by placing two MnTe sputtering sources with different gas flows (Ar and Ar/N2) opposite of one another during the synthesis. The nitrogen content gradient was measured along the sample surface, correlating with the distance from the nitrogen source. The phase, composition, and optoelectronic properties of the resulting thin films change as a function of the nitrogen content. This work shows that gradients of gaseous elements can be generated in thin films synthesized by sputtering, expanding the boundaries of combinatorial science.