Combinatorial Samples Research Articles

Mapping the microstructure and the mechanical performance of a combinatorial Co–Cr–Cu–Fe–Ni–Zn high-entropy alloy thin film processed by magnetron sputtering technique

The Co–Cr–Cu–Fe–Ni–Zn compositional library was studied on a combinatorial high-entropy alloy thin film processed on a silicon substrate by magnetron sputtering technique. The thickness of the coating was between 2 and 3 μm while the lateral dimension was 10 cm. The chemical composition in the layer depended on the location and for each constituent element the concentration varied between 5 and 42 at.%. The phase composition and the microstructure were mapped using synchrotron X-ray diffraction, and the crystallite size as well as the density of lattice defects (dislocations and twin faults) were determined by diffraction line profile profile analysis. In addition, selected locations were studied by transmission electron microscopy. The influence of the chemical composition on the microstructure and the mechanical behavior was revealed. The mechanical performance was characterized by nanoindentation mapping which determined the hardness and the elastic modulus versus the element concentrations. It was found that the coating contains single phase face-centered cubic (FCC) and body-centered cubic (BCC) regions as well as an intermediate two-phase area. In the whole combinatorial sample, the microstructure consisted of nanocrystalline columns growing perpendicular to the coating surface and having pores between them. Due to the porosity, the hardness and the elastic modulus were relatively low despite the nanostructure and the very high defect density. The highest hardness (3.4 GPa) and elastic modulus (119 GPa) were measured in the BCC region with the chemical composition of 10%Co–38%Cr–13%Cu–27%Fe–5%Ni–7%Zn (at.%).

Combinatorial sample preparation platform for droplet-based applications in microbiology

Droplet microfluidics has demonstrated immense potential in microbiological studies due to its unique features, such as miniaturization, compartmentalization, and parallelization. Multiplexing droplet content allows the investigation of various experimental conditions in a highly parallelized manner. Yet, droplet library generation and tracking remain challenging in high-throughput screening. The introduction of distinct reagents into droplets necessitates precise control over droplet flow in a microfluidic chip, limiting the throughput to a few reagents. Additionally, tracking individual droplets is complex due to their fast dynamics. To address these challenges, we have developed a multiplexing platform for automated sample preparation, enabling on-demand merging and mixing of reagents for fine-tuning the sample compositions for droplet generation. A coding space with 169 optical barcodes can be realized by the pairwise combination of four fluorescence dyes at six concentration levels to encode droplet populations as required by the experimental design. A machine-learning algorithm has been employed to identify distinct droplet populations. As proof of concept, we conducted an antibiotic susceptibility assay on an E. coli strain to screen for susceptibility of four antibiotics and determine minimum inhibitory concentrations in one experiment. Utilizing the on-demand sample preparation, optical barcodes, and machine-learning analysis, our setup provides a rapid, straightforward, and reliable multiplexing capability for numerous microbial and biochemical applications.

Additive manufacturing-based combinatorial approach to improve bonding strength and heat transfer performance in wrought-cast Al compound casting

We improved the interfacial bonding strength and heat transfer performance between wrought and cast Al alloy parts by implementing an interfacial Al-Si-Zn-based alloy coating layer. An additive manufacturing (AM)-based combinatorial experiment was employed to determine the optimal composition of coating layers. Various compositional combinations of Al-Si-Zn layers were deposited onto an Al plate using a multi-nozzle direct energy deposition system, and the wetting behavior of the cast materials onto the combinatorial samples was examined to select the best composition of the coating layer. The selected coating layer was sprayed on the cooling pipes, and an actual-scale motor housing integrated by the pipe was produced by a compound die casting. The Al-Si-Zn coating layer caused the surface of the coating layers on pipes to partially melt when in contact with the molten alloy during the casting. Consequently, a reactive layer was rapidly formed between the coating and cast materials before solidification. As a result, the interfacial bonding strength increased to 13 MPa and heat transferability between the wrought and cast materials was improved. Therefore, we described the AM-based combinatorial exploring method for the interfacial coating layer to overcome the interfacial issues between the wrought and cast materials of compound casting.

Deciphering phase evolution in complex metal oxide thin films via high-throughput materials synthesis and characterization

Discovery of structure-property relationships in thin film alloys of complex metal oxides enabled by high-throughput materials synthesis and characterization facilities is demonstrated here with a case-study. Thin films of binary transition metal oxides (Ti–Zn) are prepared by pulsed laser deposition with continuously varying Ti:Zn ratio, creating combinatorial samples for exploration of the properties of this material family. The atomic structure and electronic properties are probed by spatially resolved techniques including x-ray absorption near edge structures (XANES) and x-ray fluorescence (XRF) at the Ti and Zn K-edge, x-ray diffraction, and spectroscopic ellipsometry. The observed properties as a function of Ti:Zn ratio are resolved into mixtures of five distinguishable phases by deploying multivariate curve resolution analysis on the XANES spectral series, under constraints set by results from the other characterization techniques. First-principles computations based on density function theory connect the observed properties of each distinct phase with structural and spectral characteristics of crystalline polymorphs of Ti–Zn oxide. Continuous tuning of the optical absorption edge as a function of Ti:Zn ratio, including the unusual observation of negative optical bowing, exemplifies a functional property of the film correlated to the phase evolution.

Machine Learning-Based Characterization of the Nanostructure in a Combinatorial Co-Cr-Fe-Ni Compositionally Complex Alloy Film.

A novel artificial intelligence-assisted evaluation of the X-ray diffraction (XRD) peak profiles was elaborated for the characterization of the nanocrystallite microstructure in a combinatorial Co-Cr-Fe-Ni compositionally complex alloy (CCA) film. The layer was produced by a multiple beam sputtering physical vapor deposition (PVD) technique on a Si single crystal substrate with the diameter of about 10 cm. This new processing technique is able to produce combinatorial CCA films where the elemental concentrations vary in a wide range on the disk surface. The most important benefit of the combinatorial sample is that it can be used for the study of the correlation between the chemical composition and the microstructure on a single specimen. The microstructure can be characterized quickly in many points on the disk surface using synchrotron XRD. However, the evaluation of the diffraction patterns for the crystallite size and the density of lattice defects (e.g., dislocations and twin faults) using X-ray line profile analysis (XLPA) is not possible in a reasonable amount of time due to the large number (hundreds) of XRD patterns. In the present study, a machine learning-based X-ray line profile analysis (ML-XLPA) was developed and tested on the combinatorial Co-Cr-Fe-Ni film. The new method is able to produce maps of the characteristic parameters of the nanostructure (crystallite size, defect densities) on the disk surface very quickly. Since the novel technique was developed and tested only for face-centered cubic (FCC) structures, additional work is required for the extension of its applicability to other materials. Nevertheless, to the knowledge of the authors, this is the first ML-XLPA evaluation method in the literature, which can pave the way for further development of this methodology.

An innovative strategy of anti-erosion: Combining bionic morphology and bionic arrangement

Erosion is a common and unavoidable form of wear, which seriously hinders the green and safe development of modern industrial production. Bionics has already excelled in the study of erosion resistance. This paper combines bionic units with bionic arrangements to get a new combinatorial bionic sample for anti-erosion. The bionic unit is convex morphology extracted from the body surface of desert organisms. The bionic arrangement is a phyllotaxis arrangement formed by plant leaves through long-term evolution. The removal quality and after erosion morphology of each target sample were mainly analyzed to reveal the influence of the arrangement of the bionic morphology and the arrangement density on the erosion wear. The results show that the combinatorial bionic sample (convex units + phyllotaxis arrangement) has the best erosion wear resistance. This study extends the bionic theory of anti-erosion and provides a new research idea for the solution of wear problems in engineering.

Demonstration of a laser powder bed fusion combinatorial sample for high-throughput microstructure and indentation characterization

High-throughput experiments that use combinatorial samples with rapid measurements can be used to provide process-structure-property information at reduced time, cost, and effort. Developing these tools and methods is essential in additive manufacturing where new process-structure-property information is required on a frequent basis as advances are made in feedstock materials, additive machines, and post-processing. Here we demonstrate the design and use of combinatorial samples produced on a commercial laser powder bed fusion system to study 60 distinct process conditions of nickel superalloy 625: five laser powers and four laser scan speeds in three different conditions. Combinatorial samples were characterized using optical and electron microscopy, x-ray diffraction, and indentation to estimate the porosity, grain size, crystallographic texture, secondary phase precipitation, and hardness. Indentation and porosity results were compared against a regular sample. The smaller-sized regions (3 mm × 4 mm) in the combinatorial sample have a lower hardness compared to a larger regular sample (20 mm × 20 mm) with similar porosity (<0.03%). Despite this difference, meaningful trends were identified with the combinatorial sample for grain size, crystallographic texture, and porosity versus laser power and scan speed as well as trends with hardness versus stress-relief condition.

An Economical and Flexible Dual Barcoding, Two-Step PCR Approach for Highly Multiplexed Amplicon Sequencing.

In microbiome research, phylogenetic and functional marker gene amplicon sequencing is the most commonly-used community profiling approach. Consequently, a plethora of protocols for the preparation and multiplexing of samples for amplicon sequencing have been developed. Here, we present two economical high-throughput gene amplification and sequencing workflows that are implemented as standard operating procedures at the Joint Microbiome Facility of the Medical University of Vienna and the University of Vienna. These workflows are based on a previously-published two-step PCR approach, but have been updated to either increase the accuracy of results, or alternatively to achieve orders of magnitude higher numbers of samples to be multiplexed in a single sequencing run. The high-accuracy workflow relies on unique dual sample barcoding. It allows the same level of sample multiplexing as the previously-published two-step PCR approach, but effectively eliminates residual read missasignments between samples (crosstalk) which are inherent to single barcoding approaches. The high-multiplexing workflow is based on combinatorial dual sample barcoding, which theoretically allows for multiplexing up to 299,756 amplicon libraries of the same target gene in a single massively-parallelized amplicon sequencing run. Both workflows presented here are highly economical, easy to implement, and can, without significant modifications or cost, be applied to any target gene of interest.

Combinatorial Screening of Cuprate Superconductors by Drop-On-Demand Inkjet Printing.

Combinatorial and high-throughput experimentation (HTE) is achieving more relevance in material design, representing a turning point in the process of accelerated discovery, development, and optimization of materials based on data-driven approaches. The versatility of drop-on-demand inkjet printing (IJP) allows performing combinatorial studies through fabrication of compositionally graded materials with high spatial precision, here by mixing superconducting REBCO precursor solutions with different rare earth (RE) elements. The homogeneity of combinatorial Y1–xGdxBa2Cu3O7 samples was designed with computational methods and confirmed by energy-dispersive X-ray spectroscopy (EDX) and high-resolution X-ray diffraction (XRD). We reveal the advantages of this strategy in the optimization of the epitaxial growth of high-temperature REBCO superconducting films using the novel transient liquid-assisted growth method (TLAG). Advanced characterization methods, such as in situ synchrotron growth experiments, are tailored to suit the combinatorial approach and demonstrated to be essential for HTE schemes. The experimental strategy presented is key for the attainment of large datasets for the implementation of machine learning backed material design frameworks.

High-throughput synthesis and corrosion behavior of sputter-deposited nanocrystalline Alx(CoCrFeNi)100-x combinatorial high-entropy alloys

High-entropy alloys (HEAs) are inherently complex and potentially span a vast composition space, making their research and discovery challenging. In the present study, high-throughput synthesis of an Alx(CoCrFeNi)100-x combinatorial material library covering x = 4.5–40 atomic percent Al is achieved, using magnetron co-sputtering. The effects of Al on the microstructure and corrosion behavior are investigated. With the increased amount of Al, crystal-structures of thin films transform from face-centered cubic (FCC) to body-centered cubic (BCC). Both the FCC and BCC thin films demonstrate a uniform elemental distribution. Corrosion characteristics of combinatorial samples immersed in the 3.5 wt% (wt%) NaCl solution are evaluated via electrochemical tests. Complementary X-ray photoelectron spectroscopy analysis reveals the compositional variation of passivated films formed on the sample surface after immersion. The results show that the Alx(CoCrFeNi)100-x HEA thin films possess outstanding corrosion-resistant properties, but the resistance diminishes with the increasing Al content. The decreased corrosion resistance is revealed to be directly related to the constituents of passivated films.

Development of High-Throughput Methods for Sodium-Ion Battery Cathodes.

Combinatorial synthesis of Li-ion batteries has proven extremely powerful in screening complex compositional spaces for next-generation materials. To date, no Na-ion counterpart exists wherein Na-ion cathodes can be synthesized in such a way to be comparable to that obtained in bulk synthesis. Herein, we develop a synthesis route wherein hundreds of milligram-scale powder samples can be made in a total time of 3 days. We focus on materials in the Na-Fe-Mn-O pseudoternary system of high immediate interest. Using a sol-gel method, developed herein, yields both phase-pure combinatorial samples of Na2/3Fe1/2Mn1/2O2 and NaFe1/2Mn1/2O2, consistent with previous reports on bulk samples of interest commercially. By contrast, the synthesis route used for Li-ion cathodes (namely coprecipitations) does not yield phase pure materials, suggesting that the sol-gel method is more effective in mixing the Na, Fe, and Mn than coprecipitation. This has important consequences for all attempts to make these materials, even in bulk. Finally, we demonstrate that these milligram-scale powder samples can be tested electrochemically in a combinatorial cell. The resulting cyclic voltammograms are in excellent agreement with those found on bulk samples in the literature. This demonstrates that the methodology developed here will be effective in characterizing the hundreds of samples needed to understand the complex ternary systems of interest and that such results will scale-up well to the gram and kilogram scale.

Use of a segmented cell for the combinatorial development of platinum group metal-free electrodes for polymer electrolyte fuel cells

The development of novel platinum group metal (PGM)-free catalysts is a challenging task, particularly when coupled with the integration into a cathode catalyst layer (CCL). The optimization of such PGM-free electrode structures is often non-linear and iterative, making it a demanding task due to the high number of parameters that affect performance. To accelerate both materials discovery and electrode development, this work demonstrates the application of a high-resolution segmented cell (SC) with 121 segments of 0.413 cm2 size for combinatorial high-throughput PGM-free catalyst screening and CCL optimization. The approach utilizes three flow-field strips with active areas of 4.45 cm2 each, distributed over 11 segments. Electrodes with identical catalyst material and fabrication method result in reproducible data with typically less than 10% variation between each segment and match in performance with differential single cell data. High throughput testing of combinatorial sample sets, with varied PGM-free electrocatalyst materials or electrode composition, demonstrated the ability to rapidly discern high performing outliers, and establish or confirm trends in electrode optimization. The results indicated significant performance benefits of electrodes with ionomer content of 45 wt% over lower values, and of water rich inks with 82% water content over those with 50%.

Novel Ge-Sb-Te thermoelectric materials: A demonstration for an efficient diffusion couple technique in expediently exploiting new thermoelectric materials

Abstract An efficient diffusion couple technique is proposed for rapid screening of potential thermoelectric materials and it has been explored in a (GeTe)m (Sb2Te3)n pseudobinary system. In this study, a combinatorial sample library of GeTe-Sb2Te3 diffusion couple with rich compositions and structures was prepared by plasma activation sintering (PAS). The relationship among composition, structure and performance of the materials was revealed by analyzing the chemical composition, crystal structure and thermoelectric properties of the microdomains in the combinatorial sample library, so as to achieve the purpose for rapid identification of Ge-Sb-Te compounds with excellent thermoelectric properties. The scanning results of the Seebeck coefficient of the samples library show that the sample with potential high thermoelectric performance has a chemical composition near Ge33.1Sb13.7Te53.2. The bulk materials with compositions in the vicinity of Ge33.1Sb13.7Te53.2 were prepared by a conventional melting and PAS process. Among these bulk samples, the one with a nominal composition of Ge38Sb10.3Te51.7 achieves a maximum ZT value of 0.55 at 673 K, indicating that the constituent phases Ge0.77Sb0.154Te1 and Ge3.37Sb1.63Te6 observed in this sample could be potential candidates with excellent thermoelectric properties. These two ternary compounds should be investigated for further optimization. The results of this study provide a reference for the application of combinatorial metrology for screening and optimizing new thermoelectric materials.

Effect of Novel Pretreatment of Steam Explosion Associated with Ammonium Sulfite Process on Enzymatic Hydrolysis of Corn Straw.

Effective pretreatment process to improve enzymatic saccharification and decrease inhibitors generation is a key operation involved in the lignocellulosic bioconversion. The pretreatment of steam explosion associated with ammonium sulfite (SEAS) process was carried out to investigate the effect on enzymatic hydrolysis and fermentation production as a combinatorial pretreatment. Results showed that after pretreatment (1.0MPa, 30min, 20%w/w ammonium sulfite added), the phenolic inhibitors derived from lignin significantly removed (37.8%), which transformed to chemical humic acid (humic acid and fulvic acid) mostly. Sugar conversion (glucan (77.8%) and xylan (73.3%)) and ethanol concentration (40.8g/L) of combinatorial pretreated samples were increased by 24.7% and 33.8%, respectively, compared with steam explosion (SE) pretreated samples. FT-IR and elemental analysis results indicated that the lignin structure changed and aromatization degree increased after SEAS pretreatment. In addition, the ratio of C/N decreased and compost maturity degree increased with the holding time. The effect on the growth of wheat seedlings of soluble fulvic acid solution from combinatorial pretreatment was investigated, where below 1% (w/w) concentration did contribute to growth. Therefore, one-step chemical pretreatment process could be provided for inhibitors removal, enzymatic saccharification increase, and chemical humic acid formation as well.

High-Throughput Electrochemical Testing of Positive Electrode for Li-Ion Batteries

In the search for high-energy Li-ion positive electrodes, the layered lithium NMC oxides have been extensively studied. Despite wide interest in this system, the phase diagram remained poorly understood until recently, which resulted in many conflicting reports in the literature. Combinatorial synthesis, coupled with X-ray diffraction was used to determine the phase diagrams under various synthetic conditions [1-2]. The unexpected complexity seen in this system included multiple 3-phase regions that transform during cooling along with boundaries to single phase regions which also shift during cooling. Even with a deepened understanding of the structural phase diagram, there is still minimal knowledge of how the electrochemical properties evolve across these complex phase spaces. Herein, we adapt a high-throughput electrochemical testing system wherein 64 samples are cycled simultaneously in order to measure the cycling of mg-scale powder combinatorial samples. The methodology involves using a solution-dispensing robot to make the samples by co-precipitation synthesis, followed by high temperature annealing. The samples are subsequently mounted in the combinatorial electrochemical cell and cycled simultaneously. Figure 1 shows cyclic voltammograms obtained for identical LiCoO2 samples (weighing at most 2.5 mg) in the combinatorial cell. A remarkable level of consistency is achieved in comparison to published cyclic voltammograms for LiCoO2 [3]. The described methodology allows for the determination of specific capacity, with an RSD approaching 10%. Given that these combinatorial samples are powders, synthesized using methods comparable to those used commercially, the results scale-up very well. The proof-of-concept of this novel high-throughput electrochemical technique will be presented, exploring the level of precision that can be achieved for important electrochemical metrics (redox potential, specific capacity, irreversible capacity, voltage during storage experiments, etc.). Preliminary results from this combinatorial electrochemistry methodology using the Li-Mn-Ni-O system will be displayed, and the ramifications of electrochemically probing this critical composition space will be examined. [1] McCalla, E., Rowe, A. W., Shunmugasundaram, R., & Dahn, J. R. (2013). Structural study of the Li–Mn–Ni oxide Pseudoternary system of interest for positive electrodes of Li-ion batteries. Chemistry of Materials, 25(6), 989-999. [2] Brown, C. R., McCalla, E., Watson, C., & Dahn, J. R. (2015). Combinatorial study of the Li–Ni–Mn–Co oxide pseudoquaternary system for use in Li–Ion battery materials research. ACS combinatorial science, 17(6), 381-391. [3] Cho, J., Kim, Y.J., Park, P. (2001). LiCoO2 cathode material that does not show a phase transition from hexagonal to monoclinic phase. Journal of the Electrochemical Society, 148(10), A1110-A1115 Figure 1: Cyclic voltammetry of LiCoO2 performed in the high-throughput electrochemical testing system Figure 1

High-Throughput Electrochemistry of Li-Mn-Co-Ni-O Positive Electrodes

In the search for high-energy Li-ion positive electrodes, the layered lithium NMC oxides have been studied extensively. Despite wide interest in this system, until recently, the phase diagram remained poorly understood resulting in many conflicting reports in the literature. Combinatorial synthesis, coupled with X-ray diffraction, was used to determine the phase diagrams under various synthesis conditions [1-2]. The unexpected complexity seen in this system included multiple 3-phase regions that transform during cooling along with boundaries to single phase regions which shift during cooling. Despite the deepended understanding of the structural phase diagram, there now remains a very limited exploration of how the electrochemical properties evolve across these complex phase spaces. Herein, we adapt a high-throughput electrochemical testing system wherein 64 samples are cycled simultaneously in order to measure the cycling of the mg-scale powder combinatorial samples. The methodology involves using a solution-dispensing robot is used to make the samples by co-precipitation synthesis followed by high temperature annealing. The samples are subsequently mounted in the combinatorial electrochemical cell and cycled simultaneously. Given that the combinatorial samples here are powders, made using synthesis methods comparable to those used commercially, the results scale-up very well. Beyond the proof-of-concept of the novel high-throughput measurements, results on hundreds of samples in the Li-Mn-Ni-Co-O system of extreme interest as next-generation positive electrodes will be presented. Consequences for further studies in this popular composition space will be discussed.

The Single Phase Region in Cu2ZnSnS4 Thin Films from Theory and Combinatorial Experiments

Cu2ZnSnS4 (CZTS) is hoped to be a future, earth-abundant absorber material for thin film solar cells, but performance remains below the level needed for commercialization. In this work, the size of the single phase region of CZTS obtained from thin film synthesis methods is explored, to determine the scope available for defect engineering and thereby future improvements in solar cell performance. A chemical model for the single phase region is presented, based on equilibria between defect complexes in the CZTS phase and the other solid- and gas-phase components present during synthesis. The model predicts a variable single phase region size, depending on the partial pressures of SnS and S2. The model is verified by analysis of combinatorial thin-film CZTS samples prepared with different synthetic conditions and characterized by Raman and compositional mapping. We conclude that typical synthesis strategies for CZTS are not capable of accessing the full range of the CZTS single phase region since the required partial pressure of S2 is very large. The important implication is that our understanding of CZTS defect chemistry from experimental studies is incomplete and that scope exists for tuning the defect properties toward better solar cell performance.

Sample tracking in microbiome community profiling assays using synthetic 16S rRNA gene spike-in controls

Workflows for microbiome community profiling by high-throughput sequencing are prone to sample mix-ups and cross-contamination due to the complexity of the procedures and large number of samples typically analyzed in parallel. We employed synthetic 16S rRNA gene spike-in controls to establish a method for tracking of sample identity and detection of cross-contamination in microbiome community profiling assays based on 16S rRNA gene amplicon sequencing (16S-seq). Results demonstrated that combinatorial sample tracking mixes (STMs) can be reliably resolved by Illumina sequencing and faithfully represent their sample of origin. In a single-blinded experiment, addition of STMs at low levels was shown to be sufficient to unambiguously identify and resolve swapped samples. Using artificial admixtures of individually SMT-tagged samples, we further established the ability to detect and quantify cross-contamination down to a level of approximately 1%. The utility of our technique was underscored through detection of an unplanned case of cross-contamination that occurred during this study. By enabling detection of sample mix-ups and cross-contamination throughout 16S-seq workflows, the present technique thus assures provenance of sequence data on a per-sample basis. The method can be readily implemented in standard 16S-seq workflows and its routine application is expected to enhance the reliability of 16S-seq data.

“One-sample concept” micro-combinatory for high throughput TEM of binary films

Phases of thin films may remarkably differ from that of bulk. Unlike to the comprehensive data files of Binary Phase Diagrams [1] available for bulk, complete phase maps for thin binary layers do not exist. This is due to both the diverse metastable, non-equilibrium or instable phases feasible in thin films and the required volume of characterization work with analytical techniques like TEM, SAED and EDS. The aim of the present work was to develop a method that remarkably facilitates the TEM study of the diverse binary phases of thin films, or the creation of phase maps. A micro-combinatorial method was worked out that enables both preparation and study of a gradient two-component film within a single TEM specimen. For a demonstration of the technique thin MnxAl1−x binary samples with evolving concentration from x = 0 to x = 1 have been prepared so that the transition from pure Mn to pure Al covers a 1.5 mm long track within the 3 mm diameter TEM grid.The proposed method enables the preparation and study of thin combinatorial samples including all feasible phases as a function of composition or other deposition parameters. Contrary to known “combinatorial chemistry”, in which a series of different samples are deposited in one run, and investigated, one at a time, the present micro-combinatorial method produces a single specimen condensing a complete library of a binary system that can be studied, efficiently, within a single TEM session. That provides extremely high throughput for TEM characterization of composition-dependent phases, exploration of new materials, or the construction of phase diagrams of binary films.

Phase boundaries in the ternary (Bi0.5Na0.5TiO3)x(BaTiO3)y(SrTiO3)1−x−y system

The phase boundaries within (Bi0.5Na0.5TiO3)x(BaTiO3)y(SrTiO3)1−x−y with x ≥ 0.68 have been outlined. This was achieved using a combinatorial sample fabrication method and scanning synchrotron X-ray diffraction to rapidly characterise crystallographic structures over a large region of phase space. A parametric refinement method was used to clearly outline the phase boundaries as a function of the composition. The pseudo-cubic structure from the high strain non-ergodic Bi0.5Na0.5TiO3-BaTiO3 composition extends into the phase diagram with doping of SrTiO3, with regions of tetragonal and rhombohedral in the BaTiO3 and Bi0.5Na0.5TiO3 ends, respectively. This information can be used in conjunction with further compositional modifications to develop high strain piezoceramics that make use of electric-field-induced phase transformations and further understand the mechanisms in ergodic vs non-ergodic relaxors.