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![Classical binary phase diagram of Fe-Co alloy system [19].](profile/Xiaokun-Zhang/publication/283240339/figure/fig3/AS:613916820394006@1523380584695/Classical-binary-phase-diagram-of-Fe-Co-alloy-system-19.png)
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![Figure 2. Classical binary phase diagram of Fe-Co alloy system [19].](profile/Xiaokun-Zhang/publication/283240339/figure/fig3/AS:613916820394006@1523380584695/Classical-binary-phase-diagram-of-Fe-Co-alloy-system-19_Q320.jpg)
Conventionally, an experimentally determined phase diagram requires studies of phase formation at a range of temperatures for each composition, which takes years of effort from multiple research groups. Combinatorial materials chip technology, featuring high-throughput synthesis and characterization, is able to determine the phase diagram of an ent...
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... example, Figure 1 shows the 600 °C isothermal section of the Fe-Co-Ni phase diagram. High-temperature phases such as d-Fe, which is only formed at 1394 °C and is stable up to 1538 °C in the Fe-Co alloy system shown in Figure 2 [19], can- not be studied using the same chip. To map the temperature range of this Fe-Co alloy system at a 10 °C interval, 120 mate- rials libraries are still required. ...
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... the experimental process is mostly in equilibrium, the amorphous and crystal phase boundary cannot be identified as the temperature decreases (see the blue line in Figure 6). This explains why the two amorphous regions were marked in Figure 1 [22], but not in the conventional phase diagrams. ...
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... materials (PCMs) hold great promise in in- formation storage applications [29][30][31], and have attracted great interest in both the academic and the industrial communities [32][33][34][35] line-to-amorphous phase transitions are critical parameters of PCMs, especially for the purpose of lowering the power consumption of phase-change memories. The thermal his- tory of a heated pixel is depicted in Figure 12(a). When the precursor is initially prepared, it is in an amorphous phase that has low reflectivity. ...
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... on this data, the crystallization temperature and the glass-transition temperature phase diagram can be mapped. Under the approximation that the temperature vs. laser pulse-width relation at different posi- tions follows the same general trend shown in Figure 12(b), the pulse-width-dependent thermal mass of the radiated pixel is simulated by commercial software, and the ΔT(τ) curve is calibrated using known data of the Ge 2 Sb 2 Te 5 region. The calibrated curve is used to calculate the T c map shown in Figure 13, which is consistent with the data published in the previous literature [36][37][38][39][40]. ...
Citations
... It can be seen that element distributions along the depth direction are almost flat after some changes on the surface, indicating the film composition is uniform in the thickness direction. More information about CMC preparation and characterization methods can be found in ref. [ 1,3,10,13 ] Hierarchical clustering and metric multidimensional data scaling transforming were performed by using the scikitlearn package. [14] AUTHOR CONTRIBUTION Yuanxun Zhou: Investigation; formal analysis; writingoriginal draft; methodology; data curation; validation; visualization; writing-review & editing. ...
Hierarchical clustering algorithm has been applied to identify the X‐ray diffraction (XRD) patterns from a high‐throughput characterization of the combinatorial materials chips. As data quality is usually correlated with acquisition time, it is important to study the hierarchical clustering performance as a function of data quality in order to optimize the efficiency of high‐throughput experiments. This work investigated the effects of signal‐to‐noise ratio on the performance of hierarchical clustering using 29 distance metrics for the XRD patterns from Fe−Co−Ni ternary combinatorial materials chip. It is found that the clustering accuracies evaluated by the F1 score only fluctuate slightly with signal‐to‐noise ratio varying from 15.5 to 22.3 (dB) under the experimental condition. This suggests that although it may take 40–50 s to collect a visually high‐quality diffraction pattern, the measurement time could be significantly reduced to as low as 4 s without substantial loss in phase identification accuracy by hierarchical clustering. Among the 29 distance metrics, Pearson χ² shows the highest mean F1 score of 0.77 and lowest standard deviation of 0.008. It shows that the distance matrixes calculated by Pearson χ² are mainly controlled by the XRD peak shifting characteristics and visualized by the metric multidimensional data scaling.
... High-throughput characterization techniques have been used to investigate the physicochemical properties of materials, [47] ranging from basic physical properties [48] (e.g., composition and microstructure) to mechanical [44] Reproduced with permission. Copyright 2023, Elsevier. ...
High‐throughput experimental techniques can accelerate and economize corrosion evaluation, and thus, have great potential in the development of new materials for corrosion protection such as corrosion‐resistant metals, corrosion inhibitors, and anticorrosion coatings. This concise review highlights high‐throughput experimental techniques that have been recently applied for corrosion research, including (i) the high‐throughput preparation of metal samples in the form of thin films or bulk materials, (ii) high‐throughput experiments based on corrosive solutions with independent or gradient parameters, (iii) high‐throughput evaluation of changes in physicochemical properties, and (iv) high‐throughput corrosion evaluation by electrochemical methods. To advance automated and intelligent corrosion research, future directions for the development of the high‐throughput corrosion experimental and characterization techniques are also discussed.
... For the diffusion couple, it is easy to prepare, while its electrical property measuring equipment requires high spatial resolution because of the continuous composition distribution in a small space [21][22][23]. Developing material library with discrete compositions is beneficial to reduce the difficulty in the subsequent characterization process [24,25]. Compared to the thin-film material library, the quantum confinement effect can be effectively avoided and the measured Seebeck coefficient can represent the property of bulk for the thin-layer (also known as thick film) material library [26,27]. ...
Compared to the diffusion couple and thin film material library, the thin-layer (also known as thick film) material library with discrete compositions is more suitable for the screening of high performance thermoelectric (TE) materials. However, there are few apparatuses for high throughput characterizing TE properties of thin-layer material library. In this work, a tool with high reliability for effectively and quickly measuring electrical resistivity and Seebeck coefficient has been successfully devel-oped via using a combination of Van der Pauw and dynamic method. The repeatability test error is less than 10%, comparable to commercial ZEM-3 equipment. The time to measure the electrical resistivity and Seebeck coefficient at a single temperature point is 4 minutes, saving up to 61.8% of the time compared to ZEM-3. This will contribute to the screening of novel TE materials from the thin-layer TE material libraries in the future.
... One of the key techniques in these attempts is using a piece of thin film with a composition spread instead of a uniformly fixed composition. Such a piece of thin film is called a combinatorial materials chip or a materials library [5][6][7][8][9][10][11][12]. Combinatorial materials-chip method, which simply classifies phase region in the composition (X) space by one chip, has shown great potential in the experimental deter-* Corresponding author: lantingzh@sjtu.edu.cn ...
Phase boundary indicates the conditions of transition between phase regions, which is a key constituent of a phase diagram. We propose an approach to determine the phase boundary and its uncertainty in a phase-composition map based on the data from high-throughput experimentation. Bayesian logistics regression combined with the domain knowledge of phase diagrams was applied in the approach. For a typical ternary isothermal section, both the linear and nonlinear phase boundaries as well as the vertices of a ternary tie triangle were modeled to quantify the uncertainty with consideration of a couple of affecting factors such as data-point density, noise in the data, data coverage, etc. The effectiveness of the present approach was demonstrated by the Fe-Cr-Ni isothermal section data from database and the Fe-Co-Ni composition-phase map data by experiment. Moreover, the uncertainty of the phase boundary in the ternary system can be further reduced by incorporating the available data from the subbinary systems. The data-driven nature of the developed approach can further guide the efficient implementation of high-throughput experiments and provide confidence measures for decision-making in materials design and further Computer Coupling of Phase Diagrams and Thermochemistry (CALPHAD) method modeling.
... Also, the calculated ratio of Fe/Co is about 1.56. These figures are well agreed with the Co-Fe diagram [31][32] indicating that the α'-CoFe phase can be transformed when the amount of Fe is in the range of about 30-75 at. %, as shown in Fig. 12. ...
... Phase diagram of Fe-Co binary system[31][32]. ...
As a potential material for surface coating and repair applications, Tribaloy T-800 was deposited on AISI 4140 alloy steel substrate through laser engineered net shaping (LENS) to investigate its compatibility with the substrate material with a focus on interface bonding behavior and failure mechanism. It was hypothesized that the interface bonding failure between these two dissimilar materials occurs under a high degree of lattice mismatch across the interface. The mismatch relates with the misfit dislocation caused by different crystal lattice parameters and crystalline structures. The hypothesis is proved experimentally and theoretically in this study and the following findings are obtained: Fe element diffuses from the substrate due to an increased diffusivity, resulting in a brittle intermetallic Wairauite α’-(CoFe) at the planar transition layer. A large lattice misfit (more than 20%) exists between the FCC α’-Co solid solution matrix and the BCC α’-(CoFe) Wairauite phase, indicating an incoherent interface with a large amount of dislocations at the interface. It implies that there is severe local stress occurs in this area where cracks could easily arise and then propagate along the interface.
... The latter region appears dark gray in the Fe-Ni EBSD map. Proper indexing of this region was demanding due to possible martensitic transformations in Ni-Fe alloys 30 , chemical inhomogeneity, and material deformation near the interface 31 . The , was scanned across the sample in small discrete steps (~ 5 μm). ...
Transition metal alloys are essential for magnetic recording, memory, and new materials-by-design applications. Saturation magnetization in these alloys have previously been measured by conventional techniques, for a limited number of samples with discrete compositions, a laborious and time-consuming effort. Here, we propose a method to construct complete saturation magnetization diagrams for Co–Fe–Ni alloys using scanning Hall probe microscopy (SHPM). A composition gradient was created by the diffusion multiple technique, generating a full combinatorial materials library with an identical thermal history. The composition and crystallographic phases of the alloys were identified by integrated energy dispersive X-ray spectroscopy and electron backscatter diffraction. “Pixel-by-pixel” perpendicular components of the magnetic field were converted into maps of saturation magnetization using the inversion matrix technique. The saturation magnetization dependence for the binary alloys was consistent with the Slater-Pauling behavior. By using a significantly denser data point distribution than previously available, the maximum of the Slater-Pauling curve for the Co–Fe alloys was identified at ~ 32 at% of Co. By mapping the entire ternary diagram of Co–Fe–Ni alloys recorded in a single experiment, we have demonstrated that SHPM—in concert with the combinatorial approach—is a powerful high-throughput characterization tool, providing an effective metrology platform to advance the search for new magnetic materials.
... In the interlayer diffusion method, a stack of multiple layers of different compositions is deposited. The solid-state reaction occurs in two steps 11,12 , interdiffusion of the reactants and nucleation/crystallization of end products, and it normally results in crystalline materials. However, if one component of the alloy diffuses much faster than the other components, the crystallization of the new structure is hindered 13 , and thus a crystal-to-glass transition occurs. ...
... Combinatorial multilayered thin film synthesis technique provides advantage in studying the interlayer diffusion, with which a vast number of multi-layer stacks are fabricated in parallel on one substrate by varying the thicknesses of each component deposited at different positions 12,[21][22][23][24][25][26][27][28][29] . Combined with high-throughput characterization, the screening and optimization processes of MGs can be dramatically accelerated. ...
A high-throughput investigation of metallic glass formation via solid-state reaction was reported in this paper. Combinatorial multilayered thin-film chips covering the entire Ti–Ni–Cu ternary system were prepared using ion beam sputtering technique. Microbeam synchrotron X-ray diffraction (XRD) and X-ray fluorescence (XRF) measurements were conducted, with 1,325 data points collected from each chip, to map out the composition and the phase constitution before and after annealing at 373 K for 110 hours. The composition dependence of the crystal-to-glass transition by solid-state reaction was surveyed using this approach. The resulting composition–phase map is consistent with previously reported results. Time-of-flight secondary ion mass spectroscopy (ToF-SIMS) was performed on the representative compositions to determine the inter-diffusion between layers, the result shows that the diffusion of Ti is the key factor for the crystal-to-glass transition. In addition, both layer thickness and layer sequence play important roles as well. This work demonstrates that combinatorial chip technique is an efficient way for systematic and rapid study of crystal-to-glass transition for multi-component alloy systems.
... A 200 nm thick combinatorial materials chip in an equilateral triangular shape with a perimeter of 60 mm was deposited in the layer-by-layer order of Fe-Ni-Cr-Fe-Ni-Cr and sheltered by a continuously moving shutter during the deposition. 25 The chip, whose cross-section before annealing was shown in Figure 1a, was synthesized on the surface of a quartz substrate by employing a personalized high-throughput combinatorial ion beam deposition system (HTC-IBD), 26 and basically covered the entire composition range of Fe-Cr-Ni ternary alloy system. ...
The combinatorial materials chip approach is vastly superior to the conventional that characterizes one sample at a time in the efficiency of composition-phase map construction. However, the resolution of its high-throughput characterization and the correct rate of automated composition-phase mapping are often affected by inherent experimental limitations and imperfect automated analyses, respectively. Therefore, effective data preprocessing and refined automated analysis methods are required to automatically process huge amounts of experiment data to score a higher correct rate. In this work, the pixel-by-pixel structural and compositional characterization of the Fe-Cr-Ni combinatorial materials chip annealed at 750 ℃ were performed by microbeam X-ray at synchrotron light source and electron probe microanalysis, respectively. The severe baseline drift and system noise in X-ray diffraction patterns were successfully eliminated by the three-step automated preprocessing (baseline drift removal, noise elimination, and baseline correction) proposed, which was beneficial to the subsequent quantitative analysis of the patterns. Through the injection of human experience, hierarchy clustering analyses, based on three dissimilarity measures (the cosine, Pearson correlation coefficient, and Jenson-Shannon divergence) respectively, were further accelerated by the simplified vectorization of the preprocessed X-ray diffraction patterns. As the result, a correct rate of 91.15% was reached for the whole map built automatically in comparison with the one constructed manually, which confirmed that the present data processing could assist human to improve and expedite the processing of X-ray diffraction patterns, and was feasible for composition-phase mapping. The constructed maps were generally consistent with the corresponding isothermal section of Fe-Cr-Ni ternary alloy system in the ASM Alloy Phase Diagram Database except the inexistence of the σ phase under the insufficient annealing.
... Combinatorial material chip technique, featuring highthroughput synthesis characterization, can determine an entire composition spread of a binary and ternary system at a single temperature on one materials library [7]. This technique can also map an isothermal section of phase diagram in one experiment, benefiting from the 2D concentration distribution of samples that can cover essentially all compositions of a ternary system in one sample. ...
... In addition, they also applied this method to investigate the properties of the area of interest in Ni-Al [64] and Ti-Ta [65] binary libraries. Xiang et al. [66] proposed a multilayered thin-film deposition, and a complete Fe-Co-Ni ternary system as a demonstration purpose was fabricated only after the shutter had moved and rotated three times, which extremely accelerated the construction of multi-alloy composition-phase map [67]. It had been widely utilized for the preparation of multi-alloy gradient material library and combination properties to optimize known material system [68]. ...
... Xiang et al. [66] recently developed a novel highthroughput setup, which was combined high-throughput polymerization and HTC, based on synchrotron radiation White microbeam XRD, as shown in Figure 18. Using a synchrotron beamline, the incident energy could reach up to 30 keV, which was much higher than a custom XRD device. ...
... Color online) Schematic illustration of novel high-throughput apparatus for the "one-chip method" (Xiang et al.[66]). ...
Since the Material Genome Initiative (MGI) was proposed, high-throughput based technology has been widely employed in various fields of materials science. As a theoretical guide, material informatics has been introduced based on machine learning and data mining and high-throughput computation has been employed for large scale search, narrowing down the scope of the experiment trials. High-throughput materials experiments including synthesis, processing, and characterization technologies have become valuable research tools to pin down the prediction experimentally, enabling the discovery-to-deployment of advances materials more efficiently at a fraction of cost. This review aims to summarize the recent advances of high-throughput materials experiments and introduce briefly the development of materials design based on material genome concept. By selecting representative and classic works in the past years, various high-throughput preparation methods are introduced for different types of material gradient libraries, including metallic, inorganic materials, and polymers. Furthermore, high-throughput characterization approaches are comprehensively discussed, including both their advantages and limitations. Specifically, we focus on high-throughput mass spectrometry to analyze its current status and challenges in the application of catalysts screening.
