Composition-spread Samples Research Articles

Automated Phase Segmentation for Large-Scale X-ray Diffraction Data Using a Graph-Based Phase Segmentation (GPhase) Algorithm.

The creation of composition-processing-structure relationships currently represents a key bottleneck for data analysis for high-throughput experimental (HTE) material studies. Here we propose an automated phase diagram attribution algorithm for HTE data analysis that uses a graph-based segmentation algorithm and Delaunay tessellation to create a crystal phase diagram from high throughput libraries of X-ray diffraction (XRD) patterns. We also propose the sample-pair based objective evaluation measures for the phase diagram prediction problem. Our approach was validated using 278 diffraction patterns from a Fe-Ga-Pd composition spread sample with a prediction precision of 0.934 and a Matthews Correlation Coefficient score of 0.823. The algorithm was then applied to the open Ni-Mn-Al thin-film composition spread sample to obtain the first predicted phase diagram mapping for that sample.

The Different Roles of Entropy and Solubility in High Entropy Alloy Stability

Multiprincipal element high entropy alloys stabilized as a single alloy phase represent a new material system with promising properties, such as high corrosion and creep resistance, sluggish diffusion, and high temperature tensile strength. However, the mechanism of stabilization to form single phase alloys is controversial. Early studies hypothesized that a large entropy of mixing was responsible for stabilizing the single phase; more recent work has proposed that the single-phase solid solution is the result of mutual solubility of the principal elements. Here, we demonstrate the first self-consistent study of the relative importance of these two proposed mechanisms. In situ high-throughput synchrotron diffraction studies were used to monitor the stability of the single phase alloy in thin-film (Al1-x-yCuxMoy)FeNiTiVZr composition spread samples. Our results indicate that a metastable solid solution can be captured via the rapid quenching typical of physical vapor deposition processes, but upon annealing the solid-solution phase stability is primarily governed by mutual miscibility.

Semi-Supervised Approach to Phase Identification from Combinatorial Sample Diffraction Patterns

Manual attribution of crystallographic phases from high-throughput x-ray diffraction studies is an arduous task, and represents a rate-limiting step in high-throughput exploration of new materials. Here, we demonstrate a semi-supervised machine learning technique, SS-AutoPhase, which uses a two-step approach to identify automatically phases from diffraction data. First, clustering analysis is used to select a representative subset of samples automatically for human analysis. Second, an AdaBoost classifier uses the labeled samples to identify the presence of the different phases in diffraction data. SS-AutoPhase was used to identify the metallographic phases in 278 diffraction patterns from a FeGaPd composition spread sample. The accuracy of SS-AutoPhase was >82.6% for all phases when 15% of the diffraction patterns were used for training. The SS-AutoPhase predicted phase diagram showed excellent agreement with human expert analysis. Furthermore it was able to determine and identify correctly a previously unreported phase.

Screening of material libraries for electrochemical CO2 reduction catalysts – Improving selectivity of Cu by mixing with Co

The efficiency of the direct electrochemical CO2 reduction can be improved by the development of new alloy catalysts, but to do so a highly resolved composition screening remains to be connected to complex sample preparation and time consuming analysis. We have developed a technique that allows a fast and easy initial catalyst composition screening by analyzing thin film composition spread samples, utilizing a scanning flow cell coupled to an online electrochemical mass spectrometer (SFC-OLEMS). As a first case example, the investigation of a Cu–Co thin film material library demonstrates the benefits and high potential of this approach. In particular, a shift in selectivity toward C2 species for low Co content (5–15at.%) has been found and is discussed as being related to changed adsorption energies of intermediate products and the consequent modification of reaction pathways.

Electrochemical CO2 Reduction: Screening of Material Libraries and Improving Selectivity of Cu By Mixing It with Co

Using CO2 and converting it into useful products or even fuels is considered as a “dream reaction”. However even after over 30 years of research in the field of electrochemical CO2 reduction the “dream” didn’t come true and still remains a scientific and technical challenge. Two main applications can be considered for the electrochemical CO2 reduction: (1) The operation as storage technology to compensate the unavoidable energy fluctuations produced by renewable energy source like wind or sun and (2) the syntheses of valuable products like ethylene. Whilst in gas-phase heterogeneous catalysis the conceptual understanding about converting CO2 into fuels and the applied processes are well developed, electrochemical CO2 reduction is still in a stage where fundamental research is inevitably necessary to prove feasibility before large-scale implementation. On the contrary distinct advantages are the direct use of electrical energy, a potential dependent and therefore customizable product distribution and operation at ambient pressure and temperature. Main reasons for a so far not realized commercial application are (1) the low selectivity for valuable products on hydrocarbon producing electrodes and thereby a costly product separation, (2) the low energy efficiency as a cause of high overpotential on the working electrode and (3) the oxygen evolution as counter reaction, that also shows high overpotential and in addition to that catalyst degradation by dissolution. In order to address the fundamental understanding of the reduction processes on various types of material combinations, we have developed an electrochemical technique that enables (1) screening of thin-film material libraries with different experimental parameters, (2) investigating catalyst activity and stability of electrodes in parallel by inductively coupled plasma mass spectrometry (ICP-MS) and (3) analyzing the selectivity of catalysts for certain products via online electrochemical mass spectrometry (OLEMS). First results utilizing this approach will be presented; the focus will be in particular on the shift in selectivity towards C2 products of the electrochemical CO2 reduction on Cu-Co thin film composition spread samples at ambient temperature and pressure. Due to a high resolution composition analysis we were able to find a composition where production of C1 species is suppressed, while in return C2 production is enhanced. Utilization of this technique deepens understanding of fundamental processes and shows its high potential for improving performance of electrochemical CO2 reduction.

A high-throughput investigation of Fe–Cr–Al as a novel high-temperature coating for nuclear cladding materials

High-temperature alloy coatings that can resist oxidation are urgently needed as nuclear cladding materials to mitigate the danger of hydrogen explosions during meltdown. Here we apply a combination of computationally guided materials synthesis, high-throughput structural characterization and data analysis tools to investigate the feasibility of coatings from the Fe–Cr–Al alloy system. Composition-spread samples were synthesized to cover the region of the phase diagram previous bulk studies have identified as forming protective oxides. The metallurgical and oxide phase evolution were studied via in situ synchrotron glancing incidence x-ray diffraction at temperatures up to 690 K. A composition region with an Al concentration greater than 3.08 at%, and between 20.0 at% and 32.9 at% Cr showed the least overall oxide growth. Subsequently, a series of samples were deposited on stubs and their oxidation behavior at 1373 K was observed. The continued presence of a passivating oxide was confirmed in this region over a period of 6 h.

Combinatorial Approach to Turbine Bond Coat Discovery

A nondestructive method for the high-throughput screening of novel bond coat materials has been developed. By using a suite of characterization techniques, including Raman spectroscopy, fluorescence spectroscopy, and X-ray diffraction, a rapid determination of thermally grown oxide phases and their protective capability over a continuous composition spread sample can be obtained. The methodology is validated with the Ni-Al system. The procedure developed in this work results in the rapid identification of bond coat composition regions in which the preferred thermally grown oxide, α-Al2O3, is nucleated thus significantly reducing the amount of phase space that needs to be explored in subsequent studies.

A combinatorial passivation study of Ta–Ti alloys

A combinatorial study of the kinetics of anodic oxide formation was performed on a co-deposited Ta–Ti composition spread sample (from 2 to 76 at.% Ti). The samples were characterized by High Resolution Scanning Electron Microscopy (HRSEM) and Grazing Angle X-Ray Diffraction (GIXRD). High-throughput-screening was performed with an automated scanning-droplet-cell to anodise incrementally by cyclic voltammetry and perform electrochemical impedance spectroscopy. A comprehensive set of oxide parameters, including film formation factor, dielectric constant, specific oxide resistance, flat band potential and donor density was obtained. The observed changes could be directly correlated to the microstructure of the parent metal.

Combinatorial Approach for Thermoelectric Materials through Bulk Composition-Spreads and Diffusion Multiples

AbstractIn this paper we describe a new attempt of high-throughput screening of thermoelectric materials by combining the use of the “bulk composition-spread (CS)” or “bulk diffusion multiples (DM)” and the “scanning thermal probe microanalyzer (STPM).” The (Bi2Te3)1-x(Sb2Te3)x (0<x<1) and Ni1-xCux (0<x<1) bulk CS samples were prepared by conventional powder metallurgy method by using mechanical alloying and spark plasma sintering process. The Ni-Cu-X (X=Sn, In, Bi.) DM sample was prepared by post-heating of the CS samples in a molten metal. The two dimensional distributions of Seebeck coefficient and the thermal conductivity of the cross section of the CS and DM samples which composed of graded composition were visualized by using STPM at room temperature. The composition variation was checked by EDX. The relationship between composition and the thermoelectric properties was successfully determined by using the mapping results. The time required for mapping out the 100x100 pixel image was 8 to 11 hours. The total time required for this set of the screening experiment, from sample preparation to the final conclusion, was within 24 hours. For samples Ni-Cu-X DM the diffusion length of the elements at the interface can be large as 1mm and it was found that STPM is applicable to visualize the thermoelectric properties at the region of interest.

Thermally Treated Fe-C-N Oxygen Reduction Catalysts Prepared by Vacuum Deposition

Vacuum deposition techniques were used to prepare composition spread samples of thin film Fe-C-N catalysts. After deposition, catalyst films were thermally treated to induce structural and composition changes. Catalytic activity was found to be at its largest when the films were annealed at ca. 800{degree sign}C. At this temperature, partial graphitization of the film occurred but it still contained a significant amount of nitrogen, which is required to have an active site. Above 800{degree sign}C, a significant quantity of Fe3C, which is inactive and not stable in acid, was formed. Single composition thin films were also prepared, thermally treated, and tested in a 50-cm2 fuel cell. After thermal treatment of the catalyst, the fuel cell performance was significantly improved.

High-Throughput Measurement of Magnetostriction Using MEMS and Composition Spreads

AbstractWhile measurement of magnetostriction in bulk materials is readily accomplished using a strain gauge, measurement of this quantity for thin films presents a greater challenge, and typically involves measurement of the overall wafer curvature (for a film of uniform composition) as a function of field. In order to evaluate magnetostriction locally in composition-spread samples, we have developed a method using a dense array of pre-fabricated cantilever beams on a silicon substrate prepared using MEMS techniques. Differential strain in the thin film/cantilever system results in curvature which is detected using an optical (laser/position-sensitive-detector) system. A magnetic field is applied using two orthogonal Helmholtz coils, and the resulting deflection-field curves are used to determine the saturation magnetostriction λs as well as dλ/dH. Our composition-spread films are prepared using a three gun on-axis magnetron cosputtering system. The position-dependent composition is inferred using rate calibrations and verified with electron microprobe and Rutherford Backscattering Spectroscopy. Preliminary experiments have validated the technique and the system has been used to measure magnetostriction in the Ni-Fe system. Our approach can also be used to measure properties of giant magnetostrictive materials (e.g. TbFe/Fe multilayers) as a function of layer thicknesses, or thin film shape-memory alloys, including magnetic shape-memory alloys.

Quantitative control and detection of heterovalent impurities in ZnO thin films grown by pulsed laser deposition

Impurities in ZnO specimens, including targets for pulsed laser deposition and thin films resulting from their use, were analyzed by secondary ion mass spectroscopy (SIMS). Negatively charged complex ions bound with oxygen (71Ga16O− and N14O-16) were found to be the most reliable species with which to evaluate the Ga and N content of ZnO films by clarifying possible mass interference effects in SIMS analysis. Calibrations were carried out to determine the Ga concentration (CGa) and the nitrogen concentration (CN) by normalizing the signal intensities for G71O-16 and N14O-16, respectively, to that for Z70O-16. Alternative ablation of pure single crystal and Ga-doped ceramic ZnO targets was found to be effective not only for achieving systematic control of the Ga concentration in ZnO:(Ga,N) films, but also for minimizing the contamination of undesired impurities from the sintered targets. The substrate temperature plays a decisive role in control of CN due to a thermally activated desorption process of N-related species during deposition. Systematic control of the CN/CGa ratio in a ZnO:(Ga,N) film was carried out on a ScAlMgO4 substrate by introducing a controlled temperature gradient on the substrate during deposition. A region with the correct concentration ratio of CN/CGa=2, where p-type conduction of the ZnO film was theoretically predicted, was included in the composition spread sample in which the CN/CGa ratio was continuously varied over a wide range.

Design of compact pulsed laser deposition chambers for the growth of combinatorial oxide thin film libraries

We have designed a series of combinatorial pulsed laser deposition (PLD) systems. The deposition chambers are similar to traditional PLD chambers except for the addition of movable masks close to the sample surface. We describe three different masking geometries, involving a carousel design and linear masks. The masking accuracy has been determined by measuring the film thickness variation at the edge of a cell in a combinatorial thin film library. Compositional variation has been observed at the cell edge using a scanning microwave microscope. It was found that a transition region, up to 200 μm in width, is unavoidable at cell edges using the present masking system. This puts a limit of 256 cells in a library chip fabricated on a typical 15 mm×15 mm single crystal substrate. The problem can be avoided when composition spread samples are used instead of isolated cells. In that case the effective library density is determined by the spatial resolution of the analysis equipment.