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Traditional metallic alloys are mixtures of elements in which the atoms of minority species tend to be distributed randomly if they are below their solubility limit, or to form secondary phases if they are above it. The concept of multiple-principal-element alloys has recently expanded this view, as these materials are single-phase solid solutions of generally equiatomic mixtures of metallic elements. This group of materials has received much interest owing to their enhanced mechanical properties 1 – 5 . They are usually called medium-entropy alloys in ternary systems and high-entropy alloys in quaternary or quinary systems, alluding to their high degree of configurational entropy. However, the question has remained as to how random these solid solutions actually are, with the influence of short-range order being suggested in computational simulations but not seen experimentally 6 , 7 . Here we report the observation, using energy-filtered transmission electron microscopy, of structural features attributable to short-range order in the CrCoNi medium-entropy alloy. Increasing amounts of such order give rise to both higher stacking-fault energy and hardness. These findings suggest that the degree of local ordering at the nanometre scale can be tailored through thermomechanical processing, providing a new avenue for tuning the mechanical properties of medium- and high-entropy alloys. Metal alloys consisting of three or more major elemental components show enhanced mechanical properties, which are now shown to be correlated with short-range order observed with electron microscopy.

High-entropy alloys have exhibited unusual materials properties. The stability of equimolar single-phase solid solution of five or more elements is supposedly rare and identifying the existence of such alloys has been challenging because of the vast chemical space of possible combinations. Herein, based on high-throughput density-functional theory calculations, we construct a chemical map of single-phase equimolar high-entropy alloys by investigating over 658,000 equimolar quinary alloys through a binary regular solid-solution model. We identify 30,201 potential single-phase equimolar alloys (5% of the possible combinations) forming mainly in body-centered cubic structures. We unveil the chemistries that are likely to form high-entropy alloys, and identify the complex interplay among mixing enthalpy, intermetallics formation, and melting point that drives the formation of these solid solutions. We demonstrate the power of our method by predicting the existence of two new high-entropy alloys, i.e. the body-centered cubic AlCoMnNiV and the face-centered cubic CoFeMnNiZn, which are successfully synthesized. The compositional space of potential high-entropy alloys is gigantic and difficult to explore efficiently. Here, the authors use high-throughput first-principles computations to predict what elements can mix to form high-entropy alloys, understanding of the factors favoring their formation.

For the first time in the literature, experimental determination of entire sets of exact interdiffusion coefficients in quaternary and quinary alloy systems is reported. Using the method of body-diagonal diffusion couple, a set of nine quaternary interdiffusion coefficients were evaluated in Fe–Ni–Co–Cr and a set of sixteen quinary interdiffusion coefficients were determined in a Fe–Ni–Co–Cr–Mn system, both at approximately equimolar compositions. Regions of uphill interdiffusion and zero flux planes were observed for nickel and cobalt in quinary couples, indicating the existence of strong diffusional interactions in Fe–Ni–Co–Cr–Mn alloys. The strong diffusional interactions were also manifested in the large magnitudes of cross coefficients in both the systems. The existence of strong diffusional interactions in high-entropy alloys (HEAs) as observed through experimentally determined interdiffusion coefficients in this study establishes beyond doubt the fact that cross interdiffusion coefficients cannot be ignored in HEAs.

In this study, the Ti-Zr-Hf-Nb-Ta refractory high-entropy alloy (HEA) was refined and remelted by the electron beam melting (EBM) method, and the volatilisation behaviour of the alloying elements during the melting process was investigated. The results of EBM show that Ti elements are completely volatilised, Hf and Zr elements are volatilised by about 1% to 2%, and Nb and Ta elements are not volatilised. Based on the Miedema model, the activity values of three ternary alloys, Ti-Hf-Ta, Ti-Zr-Nb, and Zr-Hf-Nb, were first calculated. Then the mean values were taken to establish a prediction model for the volatility behaviour of the Ti-Zr-Hf-Nb-Ta quinary alloy. A comparison of the experimental and model calculation results shows that the actual volatilisation rates of Hf and Zr elements after smelting are in good agreement with the calculation results, and the difference is less than 1×10 –3 kg·m –2 ·s –1 . The applicability of the present model is verified, and it provides guidance for the EBM of multi-component alloys.

The present work details experimental phase stabilization studies for the disordered, multi-cation A 6 B 2 O 17 ( A  = Zr, Hf; B  = Nb, Ta) system. We leverage both high-temperature in situ and ex situ X-ray diffraction to assess phase equilibrium and metastability in A 6 B 2 O 17 ceramics produced via reactive sintering of stoichiometric as-received powders. We observe that the A 6 B 2 O 17 phase can be stabilized for any stoichiometric combination of Group 4B and 5B transition metal cations (Zr, Nb, Hf, Ta), including ternary and quinary systems. The observed minimum stabilization temperatures for these phases are generally in agreement with prior calculations for each disordered A 6 B 2 O 17 ternary permutation, offering further support for the inferred cation-disordered structure and suggesting that chemical disorder in this system is thermodynamically preferable. We also note that the quinary (Zr 3 Hf 3 )(NbTa)O 17 phase exhibits enhanced solubility of refractory cations which is characteristic of other high-entropy oxides. Furthermore, A 6 B 2 O 17 phases experience kinetic metastability, with the orthorhombic structure remaining stable following anneals at intermediate temperatures.

Amorphous complexions have recently been demonstrated to simultaneously enhance the ductility and stability of certain nanocrystalline alloys. In this study, three quinary alloys (Cu–Zr–Hf–Mo–Nb, Cu–Zr–Hf–Nb–Ti, and Cu–Zr–Hf–Mo–W) are studied to test the hypothesis that increasing the chemical complexity of the grain boundaries will result in thicker amorphous complexions and further stabilize a nanocrystalline microstructure. Significant boundary segregation of Zr, Nb, and Ti is observed in the Cu–Zr–Hf–Nb–Ti alloy, which creates a quaternary interfacial composition that limits average grain size to 63 nm even after 1 week at ~ 97% of the melting temperature. This high level of thermal stability is attributed to the complex grain boundary chemistry and amorphous structure resulting from multi-component segregation. High-resolution transmission electron microscopy reveals that the increased chemical complexity of the grain boundary region in the Cu–Zr–Hf–Nb–Ti alloy results in an average amorphous complexion thickness of 2.44 nm, approximately 44% and 32% thicker than amorphous complexions previously observed in Cu–Zr and Cu–Zr–Hf alloys. Graphical abstract

The proceedings provide a selection of thirty-eight peer-reviewed papers presented at the 11th Global Conference on Materials Science and Engineering (CMSE 2022), held as a virtual conference on September 16-19, 2022. By the tradition annually followed in the full decade of its history, CMSE 2022 was dedicated to various aspects of Materials Science and Engineering. Given the aggravated Covid situation, the conference format was fully converted to the online mode to ensure the safety of participants, abandoning the previously scheduled on-site preparation plans in Shenzhen, China. CMSE 2022 was conducted via Microsoft Teams. The full three days of the conference comprised namely keynote speeches, oral presentations, and poster presentations, each part followed by a Q&A discussion. Firstly, the conference audience containing over a hundred participants from 23 countries enjoyed the keynote speeches of three distinguished professors: Prof. Qixin Guo from Saga University, Japan, Prof. Yarub Al-Douri from the American University of Iraq, Iraq, and Prof. Rodrigo Martins from Universidade Nova de Lisboa, Portugal, who shared their deep insights on rare earth doped semiconductors, quinternary alloys’ multi-application, and green and low-cost printed electronics, respectively. Next, over eighty oral and poster presentations were delivered successfully with informative results from related materials science and engineering fields. More detail can be found in the online version of the conference program. The online format of the conference somewhat limited the informal discussion opportunities for its participants. However, despite Covid-induced restrictions, this conference fulfilled its ultimate goal of bringing together experts from universities, academic institutions, industrial companies, and so on, updating the state-of-the-art developments and challenges. The selected thirty-eight contributions cover the latest advances in innovative materials, materials technology and materials properties, microstructure, testing & characterization, processing, etc. They focus on theoretical and analytical methods, numerical simulations, and experimental techniques with regard to industrial applications. All papers passed a rigorous reviewing process by the International Committee experts, whose reviews and comments were crucial for enhancing the scientific merit and quality of the proceedings. List of Committee Members is available in this Pdf.

The application fields of high-temperature titanium alloys are mainly concentrated in the aerospace, defense and military industries, such as the high-temperature parts of rocket and aircraft engines, missile cases, tail rudders, etc., which can greatly reduce the weight of aircraft while resisting high temperatures. However, traditional high-temperature titanium alloys containing multiple types of elements (more than six) have a complex impact on the solidification, deformation, and phase transformation processes of the alloys, which greatly increases the difficulty of casting and deformation manufacturing of aerospace and military components. Therefore, developing low-component high-temperature titanium alloys suitable for hot processing and forming is urgent. This study used data augmentation (Gaussian noise) to expedite the development of a novel quinary high-temperature titanium alloy. Utilizing data augmentation, the generalization abilities of four machine learning models (XGBoost, RF, AdaBoost, Lasso) were effectively improved, with the XGBoost model demonstrating superior prediction accuracy (with an R2 value of 0.94, an RMSE of 53.31, and an MAE of 42.93 in the test set). Based on this model, a novel Ti-7.2Al-1.8Mo-2.0Nb-0.4Si (wt.%) alloy was designed and experimentally validated. The UTS of the alloy at 600 °C was 629 MPa, closely aligning with the value (649 MPa) predicted by the model, with an error of 3.2%. Compared to as-cast Ti1100 and Ti6242S alloy (both containing six elements), the novel quinary alloy has considerable high-temperature (600 °C) mechanical properties and fewer components. The microstructure analysis revealed that the designed alloy was an α+β type alloy, featuring a typical Widmanstätten structure. The fracture form of the alloy was a mixture of brittle and ductile fracture at both room and high temperatures.

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

This study presents a calculation and comparison of Fe, Co, Ni and Cu deposition rates in the tungsten codeposition process based on the electrodeposition of numerous tungsten alloys. Eight different tungsten alloys containing from two to five metals were electrodeposited in constant conditions in order to compare the exact reduction rates. The calculated rates enabled control of the alloy composition precise enough to obtain a high-entropy WFeCoNiCu alloy with a well-balanced composition. The introduction of copper to form the quinternary alloy was found to catalyze the whole process, increasing the deposition rates of all the components of the high-entropy alloy.