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Synchronverters are inverters that imitate the behavior of synchronous generators to enhance the dynamics of renewable energy sources (RESs) powering microgrids. However, the synchronverter's inrush currents during faults could reach intolerable levels. Limiting the synchronvertery's fault currents could obstruct protection relays from identifying faulted phase(s) during unbalanced faults, and hence, jeopardizing selective phase tripping (SPT). This paper unveils the root causes behind the deviation in phase selection that hinder SPT in microgrids powered by synchronverters. Virtual-impedance fault current limiters (VI-FCLs) are proposed for synchronverters to ensure accurate SPT by commercial relays and limit their sequence and DC inrush currents. Based on a short-circuit analysis, the positive- and negative-sequence VI-FCLs, as well as the active-to-reactive power ratio of synchronverters, are regulated to enable SPT and protect synchronverters from inrush currents. Simulation results using PSCAD/EMTDC ensure the effectiveness of the proposed control scheme in enabling reliable SPT in microgrids with synchronverters. The efficacy of the proposed scheme is assured by examining various fault types, a wide range of fault resistances, and the grid-connected and islanded modes.

Alloying is one of the most effective means to confer superior properties to metal materials. For far too long, conventional W-based alloys were generally improved by the addition of minor elements. The exploitation of conventional W-based alloy is restricted to the corner of multielement phase diagrams with tiny compositional space. High-entropy alloys (HEAs) are a novel kind of alloys consisting of multi-principal alloying elements (usually more than 4) and have attracted increasing attention, since they were first reported in 2004. The emergence of HEAs filled the gap of the unexplored central region of multielement phase diagrams. Among them, tungsten-containing HEAs (TCHEAs) exhibit excellent mechanical properties, especially at extraordinarily elevated temperatures. Moreover, recent studies showed that TCHEAs had outstanding irradiation resistance properties. TCHEAs might serve as a promising candidate for plasma-facing materials in the fusion reactor. Many characteristics of TCHEAs are different from other HEAs due to the addition of tungsten with ultrahigh-melting temperature. Here, this paper aimed to introduce the manufacturing routes of TCHEAs; review the phase selection, mechanical properties, and irradiation resistance properties of TCHEAs; and propose the future prospects of TCHEAs.

Aims: The main purpose of this paper is to achieve good convergence and distribution in different Pareto fronts. Background: Research in recent decades has shown that evolutionary multi-objective optimization can effectively solve multi-objective optimization problems with no more than 3 targets. However, when solving MaOPs, the traditional evolutionary multi-objective optimization algorithm is difficult to effectively balance convergence and diversity. In order to solve these problems, many algorithms have emerged, which can be roughly divided into the following three types: decomposition-based, indexbased, and dominance relationship-based. In addition, there are many algorithms that introduce the idea of clustering into the environment. However, there are some disadvantages to solving different types of MaOPs. In order to take advantage of the above algorithms, this paper proposes a manyobjective optimization algorithm based on two-phase evolutionary selection. Objective: In order to verify the comprehensive performance of the algorithm on the testing problem of different Pareto front, 18 examples of regular PF problems and irregular PF problems are used to test the performance of the algorithm proposed in this paper. Method: This paper proposes a two-phase evolutionary selection strategy. The evolution process is divided into two phases to select individuals with good quality. In the first phase, the convergence area is constructed by indicators to accelerate the convergence of the algorithm. In the second phase, the parallel distance is used to map the individuals to the hyperplane, and the individuals are clustered according to the distance on the hyperplane, and then the smallest fitness in each category is selected. Result: For regular Pareto front testing problems, MaOEA/TPS performed better than RVEA, PREA, CAMOEA and One by one EA in 19, 21, 30, 26 cases, respectively, while it was only outperformed by RVEA, PREA, CAMOEA and One by one EA in 8, 5, 1, and 6 cases. For the irregular front testing problem, MaOEA/TPS performed better than RVEA, PREA, CAMOEA and One by one EA in 20, 17, 25, and 21 cases, respectively, while it was only outperformed by RVEA, PREA, CAMOEA and One by one EA in 6, 8, 1, and 6 cases. Conclusion: The paper proposes a many-objective evolutionary algorithm based on two phase selection, termed MaOEA/TPS, for solving MaOPs with different shapes of Pareto fronts. The results show that MaOEA/TPS has quite a competitive performance compared with the several algorithms on most test problems. Other: Although the algorithm in this paper has achieved good results, the optimization problem in the real environment is more difficult, therefore, applying the algorithm proposed in this paper to real problems will be the next research direction.

Both clinical observations and in vitro studies have confirmed that hyperoxaluria or hypercalciuria is one of the main factors that determine the phase formation of pathological calcium oxalate (Ca...

Predicting the phase precipitation of multicomponent alloys, especially the Ni-base superalloys, is a difficult task. In this work, we introduced a dependable and efficient way to establish the relationship between composition and detrimental phases in Ni-base superalloys, by integrating high throughput experiments and machine learning algorithms. 8371 sets of data about composition and phase information were obtained rapidly, and analyzed by machine learning to establish a high-confidence phase prediction model. Compared with the traditional methods, the proposed approach has remarkable advantage in acquiring and analyzing the experimental data, which can also be applied to other multicomponent alloys. IMPACT STATEMENT By integrating the high throughput experiments and machine learning algorithms, it is hopeful to facilitate the design of new Ni-base superalloys, and even other multicomponent alloys.

This paper introduces a fault detection and faulty phase selection technique for a double-circuit transmission line with thyristor-controlled series capacitor (TCSC). In a transmission system, the ...

Summary A fundamental understanding of phase transition mechanisms for polymorphic materials is the prerequisite for developing rational synthesis strategies toward phase homogeneity. Here, we target polymorphic MnO2 as the prototype system and reveal the atomic mechanisms governing the phase selection among various MnO2 tunnel structures that are hydrothermally synthesized from a layered MnO2 precursor. A topotactic layer-to-tunnel (L-T) transition mechanism featuring solid-state Mn migration and structure rearrangement is discovered. The transition exhibits multi-step kinetics with the formation of intermediate large tunnels, which introduces structural complexity into the end product with significant phase and compositional heterogeneity within single MnO2 particles. Localized valence analysis further reveals the significant effect of Jahn-Teller Mn3+ ordering on the L-T transition kinetics. We expect these findings to assist the understanding of polymorphism evolution and be further applied to rationalize material synthesis strategies toward phase homogeneity and to establish an accurate synthesis-structure relationship.

High Entropy Alloys are inherently complex and span a vast composition space, making their research and discovery challenging. Developing quantitative predictions of their phase selection requires a large quantity of consistently determined experimental data. Here, we use combinatorial methods to fabricate and characterize 2478 quinary alloys based on Al and transition metals. All data are publicly available at http://materialsatlasproject.org/ . Phase selection can be predicted for considered alloys when combining the content of FCC/BCC elements and the constituents’ atomic size difference. Mining our data reveals that High Entropy Alloys with increasing atomic size difference prefer BCC structure over FCC. This preference is typically overshadowed by other selection motifs, which dominate during close-to-equilibrium processing. Not suggested by the Hume-Rothery rules, this preference originates from the ability of the BCC structure to accommodate a large atomic size difference with lower strain energy penalty which can be practically only realized in High Entropy Alloys.

Laves phase plays a positive role in improving the strength of high-entropy alloys (HEAs); Nb and Ti elements have potential to promote Laves phase formation in some HEAs. For improving the strength of the face-centered cubic (FCC) CoCrFeMnNi HEA, a series of (CoCrFeMnNi)100−xNbx (atomic ratio: x = 0, 4, 8, 12, 16) and (CoCrFeMnNi)100−xTix (atomic ratio: x = 0, 2, 4, 6, 8, 12) HEAs were prepared by melting. The effects of Nb and Ti on the microstructure evolution and compressive properties of the CoCrFeMnNi HEAs were investigated. For (CoCrFeMnNi)100−xNbx HEAs, the second-phase (Laves and σ phase) volume fraction increased from 0 to 42%. The yield strength also increased gradually from 202 to 1010 MPa. However, the fracture strain decreased from 60% (no fracture) to 12% with increasing Nb content. For (CoCrFeMnNi)100−xTix HEAs, the yield strength increased from 202 to 1322 MPa. The Laves phase volume fraction also increased from 0 to 27%. However, the fracture strain decreased from 60% (no fracture) to 7.5% with increasing Ti content. Addition of Nb and Ti has a good effect on improving the strength of FCC CoCrFeMnNi HEA.

The phase formation of high entropy alloys (HEAs) is diversity due to the breadth of the composition space. Most of the studies about phase formation are based on features of solid solution. However, the establishment of the link between compositions and phase formation plays an important role in accelerating novel HEAs development. To achieve this aim, we employed the support vector machine (SVM) to build phase selection models with both the composition dataset and the thermodynamic parameters dataset. The accuracies of both models are above 85%. A dataset with more than a thousand data has been established, which covers 18 elements and most of the HEAs families. The feature dataset was transferred by calculation of thermodynamic parameters. The similar accuracies of the models with compositions dataset and with thermodynamic parameters proved that the prediction of phase formation in HEAs can be carried out directly from compositions. Our models provide a universal approach of phase formation prediction in HEAs.

As the ultrahigh-voltage (UHV) projects are rapidly developing, it is necessary to investigate the problems involved in overvoltage and insulation, thereby providing a technical basis for future UHV projects. The switching overvoltage of closing no-load lines was simulated and analyzed here using two kinds of typical UHV network structures: the power plant to the grid system and the grid-to-grid system. Different factors, such as line length, mode of operation on the power plant side, and short-circuit capacity, are considered. It is possible for lines shorter than 60 km to eliminate the closing resistor, determined by calculating the probability of flashover. We analyzed the phase selection closing in depth to inhibit the switching overvoltage and considered the factors such as phase deviation and the length of the line. Finally, the applicability of phase selection closing is put forward for lines of different lengths.

Modern SAT solvers are based on a paradigm named conflict driven clause learning (CDCL), while local search is an important alternative. Although there have been attempts combining these two methods, this work proposes deeper cooperation techniques. First, we relax the CDCL framework by extending promising branches to complete assignments and calling a local search solver to search for a model nearby. More importantly, the local search assignments and the conflict frequency of variables in local search are exploited in the phase selection and branching heuristics of CDCL. We use our techniques to improve three typical CDCL solvers (glucose, MapleLCMDistChronoBT and Kissat). Experiments on benchmarks from the Main tracks of SAT Competitions 2017–2020 and a real world benchmark of spectrum allocation show that the techniques bring significant improvements, particularly on satisfiable instances. For example, the integration of our techniques allow the three CDCL solvers to solve 62, 67 and 10 more instances in the benchmark of SAT Competition 2020. A resulting solver won the Main Track SAT category in SAT Competition 2020 and also performs very well on the spectrum allocation benchmark. As far as we know, this is the first work that meets the standard of the challenge “Demonstrate the successful combination of stochastic search and systematic search techniques, by the creation of a new algorithm that outperforms the best previous examples of both approaches.” [35] on standard application benchmarks.

Objectives To demonstrate the feasibility of a deep learning-based vascular segmentation tool for UWFA and evaluate its ability to automatically identify quality-optimized phase-specific images. Methods Cumulative retinal vessel areas (RVA) were extracted from all available UWFA frames. Cubic splines were fitted for serial vascular assessment throughout the angiographic phases of eyes with diabetic retinopathy (DR), sickle cell retinopathy (SCR), or normal retinal vasculature. The image with maximum RVA was selected as the optimum early phase. A late phase frame was selected at a minimum of 4 min that most closely mirrored the RVA from the selected early image. Trained image analysts evaluated the selected pairs. Results A total of 13,980 UWFA sequences from 462 sessions were used to evaluate the performance and 1578 UWFA sequences from 66 sessions were used to create cubic splines. Maximum RVA was detected at a mean of 41 ± 15, 47 ± 27, 38 ± 8 s for DR, SCR, and normals respectively. In 85.2% of the sessions, appropriate images for both phases were successfully identified. The individual success rate was 90.7% for early and 94.6% for late frames. Conclusions Retinal vascular characteristics are highly phased and field-of-view sensitive. Vascular parameters extracted by deep learning algorithms can be used for quality assessment of angiographic images and quality optimized phase selection. Clinical applications of a deep learning-based vascular segmentation and phase selection system might significantly improve the speed, consistency, and objectivity of UWFA evaluation.

The cesium lead triiodide (CsPbI3) perovskite is a promising candidate for stable light absorbers and red-light-emitting sources due to its outstanding stability. Phase engineering is the most impo...

Exercising fine control over the synthesis of metal–organic frameworks (MOFs) is key to ensuring reproducibility of physical properties such as crystallinity, particle size, morphology, porosity, defectivity, and surface chemistry. The principle of modulated self-assembly – incorporation of modulator molecules into synthetic mixtures – has emerged as the primary means to this end. This perspective article will detail the development of modulated synthesis, focusing primarily on coordination modulation, from a technique initially intended to cap the growth of MOF crystals to one that is now used regularly to enhance crystallinity, control particle size, induce defectivity and select specific phases. The various mechanistic driving forces will be discussed, as well as the influence of modulation on physical properties and how this can facilitate potential applications. Modulation is also increasingly being used to exert kinetic control over self-assembly; examples of phase selection and the development of new protocols to induce this will be provided. Finally, the application of modulated self-assembly to alternative materials will be discussed, and future perspectives on the area given., This Perspective gives an overview of the modulated self-assembly of MOFs – incorporating additives and alternative precursors into syntheses – focusing on its varying influences on crystallization mechanisms, physical properties, and applications.

In this letter, the impact of two phase shifting designs, namely random phase shifting and coherent phase shifting, on the performance of intelligent reflecting surface (IRS) assisted non-orthogonal multiple access (NOMA) is studied. Analytical results are developed to show that the two designs achieve different tradeoffs between reliability and complexity. Simulation results are provided to compare IRS-NOMA to conventional relaying and IRS assisted orthogonal multiple access, and also to verify the accuracy of the obtained analytical results.

The undercooling (∆T) dependencies of the solidification pathways, microstructural evolution, and recalescence behaviors of undercooled Co-18.5at.%B eutectic alloys were systematically explored. Up to four possible solidification pathways were identified: (1) A lamellar eutectic structure consisting of the FCC–Co and Co3B phase forms, with extremely low ΔT; (2) The FCC–Co phase primarily forms, followed by the eutectic growth of the FCC–Co and Co2B phases when ΔT < 100 K; (3) As the ΔT increases further, the FCC–Co phase primarily forms, followed by the metastable Co23B6 phase with the trace of an FCC–Co and Co23B6 eutectic; (4) When the ΔT increases to 277 K, the FCC–Co phase primarily forms, followed by an FCC–Co and Co3B eutectic, which is similar in composition to the microstructure formed with low ΔT. The mechanisms of the microstructural evolution and the phase selection are interpreted on the basis of the composition segregation, the skewed coupled zone, the strain-induced transformation, and the solute trapping. Moreover, the prenucleation of the primary FCC–Co phase was also detected from an analysis of the different recalescence behaviors. The present work not only enriches our knowledge about the phase selection behavior in the undercooled Co–B system, but also provides us with guidance for controlling the microstructures and properties practically.

Multi-principal element alloys (MPEAs) especially high entropy alloys have attracted significant attention and resulted in a novel concept of designing metal alloys via exploring the wide composition space. Abundant experimental data of MPEAs are available to show connections between elemental properties and the resulting phases such as single-phase solid solution, amorphous, intermetallic compounds. To gain insights of designing MPEAs, here we employ neural network (NN) in the machine learning framework to recognize the underlying data pattern using an experimental dataset to classify the corresponding phase selection in MPEAs. For the full dataset, our trained NN model reaches an accuracy of over 99%, meaning that more than 99% of the phases in the MPEAs are correctly labeled. Furthermore, the trained NN parameters suggest that the valence electron concentration plays the most dominant role in determining the ensuing phases. For the cross-validation training and testing datasets, we obtain an average generalization accuracy of higher than 80%. Our trained NN model can be extended to classify different phases in numerous other MPEAs.

Here we reported a tunable full-color-emitting Ba3P4O13:Eu2+ phosphor and the phase selection depending on Eu2+ doping concentration in two different polymorphic forms of Ba3P4O13. With increasing Eu2+ doping concentration, the crystal-phase of Ba3P4O13:Eu2+ phosphor transformed from low-temperature form (low-Ba3P4O13 phase) to high-temperature form (high-Ba3P4O13 phase) when other synthesis conditions remained constant. The emission from Ba3P4O13:Eu2+ was strongly related to the specific crystal-phase structure of Ba3P4O13 host, and the luminescent colors of Ba3(1-x)P4O13:3xEu2+ were tuned successfully from blue to white and eventually to yellow following the crystal-phase transformation triggered by the Eu2+ doping. The temperature-dependent photoluminescence properties for the selected Ba3(1-x)P4O13:3xEu2+ phosphors were also investigated. The results suggest low-Ba3P4O13: Eu2+ phosphor has better thermal stability than high-Ba3P4O13: Eu2+ phosphor.

In order to increase the rated power of the DC/DC converter, the interleaved parallel connection is widely used. Although the interleaved and parallel Boost converters can increase the operating power of the system, at the same time, it has the advantages of smaller system output current ripple and can reduce the stress of switching devices, but when the system is running in low power mode, due to the use of multi-phase Boost, the increase in loss makes the conversion efficiency of the system lower. A phase selection control algorithm is proposed in this paper, by which the conversion efficiency of multi-phase interleaved parallel Boost converters can be effectively improved. Finally, the feasibility of the phase selection control algorithm designed is verified through simulation in this paper.

With the increasing titanium, the volume fraction of face-centred cubic-structured dendrites decreased, and ordered B2 phase, σ, and Laves phase appeared in CoCrCu0.5FeNiTix alloy when x > 0.5. Wit...

The effect of initial powder blend composition on the synthesis and formation mechanism of nickel silicide phases was investigated by mechanical alloying in Ni-60 and Ni-66.7 at.% Si powder blends. It was noted that the equilibrium NiSi phase started to form in the early stages of milling and that the amount of the NiSi phase in the milled powder increased with increasing milling time. Even though, under equilibrium conditions, a mixture of both the NiSi and NiSi2 phases was expected to be present in the Ni-60 at.% Si composition and the stoichiometric NiSi2 phase in the Ni-66.7 at.% Si composition, the NiSi phase was present in both the compositions investigated. However, while only the NiSi phase was present homogeneously in the Ni-60 at.% Si powder blend, both the NiSi phase and a very small amount of unreacted Si were present in the powder blend of Ni-66.7 at.% Si composition. This unexpected phase constitution in the milled powders was attributed to a partial loss of Si during mechanical allo...

The glass formation and microstructure evolution of Mg61Cu28Gd11 and alloys laying on the line linking this composition to pure magnesium, i.e. alloys with fixed Cu:Gd ratio but increasing Mg content were systematically studied. A schematic phase diagram with three ternary phase regions was built based on the related competitive crystalline phases. Moreover, the results indicate that the alloys located in the Mg 2 Cu-Mg 2 CuGd-Mg 6 CuGd ternary phase region have higher glass forming ability than alloys with increased magnesium content.

Ti–48Al–xNb alloys were solidified by containerless electromagnetic levitation with quenching system of the conical copper mold. The influence of cooling rates on phase selection of Ti–48Al–xNb alloys was investigated. In near-equilibrium solidification condition, the dendrite β phase is observed as the leading phase. No other metastable phase (e.g., α phase) is observed. In contrast, in rapid solidification condition, the metastable α phase is observed in as-quenched Ti–48Al–2Nb alloy. Furthermore, the metastable α phase is replaced by the primary β phase with Nb addition increasing. For Ti–48Al–(x = 4, 6, 8)Nb alloys, increasing cooling rate results in a solidification path transition. The peritectic reaction (L + β → α) is therefore significantly suppressed. The relationships between primary dendrite arm spacing (λ 1) and cooling rate (τ) can be described.

A series Co-(18.5–20.7) at.% B melts encompassing the eutectic composition (Co81.5B18.5) were solidified at different degrees of undercooling. It is found that the metastable Co23B6 phase solidifies as a substitute for the stable Co3B phase in the alloy melts undercooled above a critical undercooling value of ~60 K. The Co23B6 and α-Co phases make up a metastable eutectic. The corresponding eutectic composition and temperature are Co80.4B19.6 and 1343 K, respectively. On exposure of the metastable Co23B6 phase at a given temperature above 1208 K, it does not decompose even after several hours. But it transforms by a eutectoid reaction to α-Co + Co3B at lower temperature.

During the no-load closing process, transformer will produce a magnetizing inrush current which will make the transformer relay malfunction and make adversely affect to the transformer equipment and power grid. Relative to a variety of external measures limiting the inrush current, the phase selection switch technology is more effective to reduce inrush current. The author analyzed inrush current by theory and dynamic simulation experiment. By controlling the closing angle to be less than 0° to 72° of the opening angle, inrush current is well suppressed.

Beating of the heart is a type of motion which is the most difficult to control during the cardiac CT scan and causes significant artifacts. Hearts have the least motion at systole and diastole phase which for an average heart happens at 45% and 75% phase respectively. However, in practice this is not guaranteed, so doctors sometimes reconstruct several phases, review all those images and then make diagnosis from the phase that has the least artifacts. The new method for automatic dynamic optimal phase reconstruction has image quality comparable to the manual phase selection but it also significantly reduces the exam time by omitting the review of unnecessary phases.

Buyers are faced with selecting the optimal supplier, while suppliers are left to consider production costs. In this study, we developed a two-phase selection framework that allows buyers to evaluate the performance of suppliers while taking production costs into account for value maximisation. This scheme is a win-win solution capable of promoting long-term relationships between buyers and suppliers. Under the assumption of normality, the first phase involves constructing a new Six Sigma quality capability analysis chart (SSQCAC) which takes production costs into account. The objective is to evaluate all potential suppliers using the 100 × (1–α)% upper confidence limit (UCL) of an integrated Six Sigma quality index (SSQI) QPIh when dealing with products with smaller-the-better (STB), larger-the-better (LTB), or nominal-the-best (NTB) quality characteristics. According to interval estimation theory, this method can have a significant impact on the consumption of resources; i.e. the production costs of the supplier can be decreased by reducing the production quality to below that required by the buyer. The proposed method also filters out unsuitable suppliers in order to simplify the decision problem and reduce computational demands and operational risks/costs without compromising the quality of the final product. In the second phase, a detailed analysis is conducted using Euclidean distance measure to select the optimal supplier from among the remaining candidates. We conducted a real-world case study to evaluate the efficacy of the proposed method. We also conducted comparisons with existing methods to demonstrate the advantages of the proposed method and its managerial implications. Suggestions for future study are also provided.

The search for effective methods to fabricate bulk single-phase quasicrystalline Al-Cu-Fe alloys is currently an important task. Crucial to solving this problem is to understand mechanisms of phase formation in this system. Here we study crystallization sequence during solidification as well as the conditions of solid phase formation in slowly solidified Al-Cu-Fe alloys in a wide range of compositions. Concentration dependencies of undercoolability were also constructed by differential thermal analysis method. These experimental results are compared with data on chemical short-range order in the liquid state determined from \textit{ab initio} molecular dynamic simulations. We observe that main features of interatomic interaction in the Al-Cu-Fe alloys are similar for both liquid and solid states and they change in the vicinity of i-phase composition. In the concentration region, where the i-phase forms from the melt, both the undercoolability and the crystallization character depend on the temperature of the melts before cooling., Comment: 4 pages, 5 figures

Phase selection in Ti-Zr-Hf-Al high-entropy alloys was investigated by in-situ high-energy X$-$ray diffraction, single-crystal X$-$ray diffraction, and density-functional theory based electronic-structure methods that address disorder and vacancies, predicting formation enthalpy and chemical short-range order (SRO). Samples with varying Al content were synthesized, characterized, and computationally assessed to ascertain the composition-dependent phase selection, as increased Al content often acts as a stabilizer of a body-centered-cubic structure. Equiatomic TiZrHfAl was especially interesting due to its observed bcc superstructure - a variant of $\gamma-$brass with 4 vacancies per cell (not 2 as in $\gamma-$brass). We highlight how vacancy ordering mediates selection of this variant of $\gamma-$brass, which is driven by vacancy-atom SRO that dramatically suppress all atomic SRO. As vacancies are inherent in processing refractory systems, we expect that similar discoveries await in other high entropy alloys or in revisiting older experimental data., Comment: 19 Pages, 7 Figures, 3 Table

We reveal high-fidelity new phase selection rules for high entropy alloys (HEAs) by combining CALPHAD calculations and the machine learning (ML) method. Employing Thermo-Calc and TCHEA3 database, we first generate more than 300,000 equilibrium phase data from 20 quinary families formed by the 8 elements of Al Co, Cr, Cu, Fe, Mn, Ni, and Ti, and choose initially 15 materials/physical descriptors. The eXtreme Gradient Boosting (XGBoost) method is then used to identify 5 most important descriptors that best delineate the single and mixed phases in the complex temperature-composition space of HEAs. The ML model trained by the 5 features is validated by 155 annealing experimental data points from 15 publications and then used to predict 213 new single-phase alloys with BCC and FCC structures of the alloy families of AlCrNiFeMn and AlCrCoNiFeTi. We also highlight the importance of equilibrium temperature and offer in-depth insights into the paradigm of composition-feature-phase of HEAs. On the basis of the 5 important features, we establish new phase selection rules for single FCC and BCC phases with a success rate above 90%, significantly outperforming all existing phase selection rules and providing a powerful tool for mapping single-phase in the complex temperature-composition space of HEAs.

The microstructure, phase structure, mechanical properties and damping capacity of Al x Fe2CrNiCu (x = 0.0, 0.5, 0.75, 1.0, 1.5) (x in molar ratio) HEAs were investigated. The results show that with the increase of x value, the volume fractions of BCC phase increase from 0 for x = 0.0 to 100% x = 1.5 for the as-cast Al x Fe2CrNiCu HEAs. Among them, a novel dual phase microstructure consisting of 51 vol.% FCC and 49 vol.% BCC with large interface area was obtained in Al0.5FeCrNiCu HEA. Especially the compressive yield strength of the alloy with BCC structure is more than 5 times larger than that of the alloy with FCC structure, indicating that a typical damping alloy with a soft second phase distributed on the hard matrix was successfully fabricated. Compared with other HEAs, the damping capacity (Q−1) of Al0.5 HEA is 0.1, which is the largest one obtained up to now. The foundational contribution of this paper is to show that the damping capacity of the HEAs can be adjusted by tuning the volume fraction of BCC and FCC phases.

BiMn-α is promising permanent magnet. Due to its peritectic formation feature, there is a synthetic challenge to produce single BiMn-α phase. The objective of this study is to assess driving force for crystalline phase pathways under far-from-equilibrium conditions. First-principles calculations with Hubbard U correction are performed to provide a robust description of the thermodynamic behavior. The energetics associated with various degrees of the chemical partitioning are quantified to predict temperature, magnetic field, and time dependence of the phase selection. By assessing the phase transformation under the influence of the chemical partitioning, temperatures, and cooling rate from our calculations, we suggest that it is possible to synthesize the magnetic BiMn-α compound in a congruent manner by rapid solidification. The external magnetic field enhances the stability of the BiMn-α phase. In conclusion, the compositions of the initial compounds from these highly driven liquids can be far from equilibrium.

Eight multi-component Nb–Si based ultrahigh temperature alloys were prepared by vacuum non-consumable arc melting. The effects of Hf, B and Cr alloying on the phase selection, phase stability, both non-equilibrium and equilibrium microstructure, room-temperature fracture toughness, hardness and oxidation resistance at 1250 °C of the alloys have been investigated and estimated systematically. The results show that the addition of B or Cr promotes the formation of hypereutectic structures. The alloying with both Hf and B suppresses the formation of β(Nb,X) 5 Si 3 and promotes the formation of α(Nb,X) 5 Si 3 and γ(Nb,X) 5 Si 3 , while the alloying with Cr has no effect on the crystal structures of 5-3 silicides. The room-temperature fracture toughness of the alloys is always degraded by the addition of Cr but almost not influenced by the combined additions of Hf and B. The hardness of 5-3 silicides exhibits a tendency of γ > α > β. The macrohardness of the alloys increases with Cr addition, and it obviously reduces in the presence of Hf after 1450 °C/50 h heat-treatment. The best oxidation-resistant performance has been obtained for the alloy with both B and Cr additions. However, in the presence of B and/or Cr, the oxidation resistance of the alloys has been degraded by further addition of Hf.

A simple thermodynamic criterion is proposed to predict the presence or absence of equilibrium intermetallic phases in a high entropy alloy at a given temperature T. The criterion was verified using 45 currently available HEAs, for which equilibrium phases and respective annealing temperature are reported. The present model shows good correlation with experiment and gives an improved ability to predict formation of solid solution and intermetallic phases compared to earlier models.

In this work, Cu–Sb–S nanocrystals (NCs) with various compositions and crystal structures are realized by only tuning the amount of 1-dodecanethiol (DDT). When the DDT amount is 3.6, 5.5, 20.5, and 25.6 mmol, pure tetragonal Cu3SbS4, cubic Cu12Sb4S13, orthorhombic CuSbS2, and orthorhombic Cu3SbS3 NCs are respectively obtained. Systematic investigations demonstrate that different amounts of DDT are responsible for formation of the different compositions and crystal structures of the initial Cu2−xS seeds, which results into the formation of various Cu–Sb–S NCs. This reaction path is further verified by control experiments from successful preparation of Cu–Sb–S NCs comparable to that of the as-prepared ones directly from the reaction of Sb2S3 NCs with Cu2−xS seeds. The current study not only provides a facile and economical way to synthesize high-quality Cu–Sb–S NCs, but also opens a new route for preparation other I–V–VI multicomponent chalcogenides NCs, such as Cu–Bi–S systems.

In this work, the effects of Mg contents on the microstructure evolution, Fe–bearing phase selection, and composition microsegregation of Al–xMg–1.0Si–0.2Fe (x = 0.2, 0.7, 1.2, and 1.7 wt.%) alloys were investigated under the sub–rapid solidification (SRS, 102–103 °C/s). The as–cast microstructure transformed from fully columnar to equiaxed grains as Mg content increases, and there was a burst of equiaxed grains in the 1.2Mg sample due to the enhanced constitutional under–cooling. Besides, Mg content altered the types of Fe–bearing intermetallic compounds. β–AlFeSi was the intermetallic compound in the 0.2Mg sample. In contrast, the Fe–bearing phase changed to α–AlFeSi in the 0.7Mg, 1.2Mg, and 1.7Mg samples, because the peritectic transformation of α–AlFeSi to β–AlFeSi was greatly suppressed due to the reduced reaction temperature with increasing Mg contents. Furthermore, 0.7Mg had the weakest composition microsegregation among the studied samples, owing to its fewer number of Mg2Si phase compared to the 1.2Mg and 1.7Mg samples. Moreover, β–AlFeSi in the 0.2Mg sample can form and exist at a high–temperature range, getting coarser and denser, and initiating a more serious composition microsegregation compared to the 0.7Mg sample. The results of this study provide guidelines for reasonably developing high–performance dilute Al–Mg–Si–Fe alloys based on the SRS.

A group of high entropy alloys (HEAs) in equal valence electron concentration (VEC), AlCoCr0.5FexNi2.5 (x = 0.5, 1.5, 2.5, 3.5), were melted and prepared. The microstructures and hardnesses were analyzed after homogenizing treatment. The results indicated that all of the equal-VEC HEAs consisted of FCC phase and BCC phase, their orientations obey Kurdjumov–Sachs relationship. This work also implied that the atomic size difference (Δr), like VEC, is an important parameter influencing the phase selection and worth considering in the HEA design. Fe is an FCC phase stabilizer for AlCoCr0.5FexNi2.5 HEAs and the ordered FCC phase (L12) gradually disappear with the Fe addition increased. The increasing FCC phase and the decreasing BCC phase resulted in the decreased hardness of HEAs.

This paper introduces an accurate fault location algorithm for double-circuit transmission lines compensated by Static Var Compensator (SVC). The proposed algorithm is based on the negative-sequence circuit of the transmission system and it depends only on the current data available from one end of the line. Since only magnitudes of current signals are required, there is no need for data synchronization. The proposed technique uses the COMTRADE fault files available from digital distance relays and it can effectively locate the all types of unbalanced faults, regardless the high fault resistance, effect of mutual coupling and SVC current injection information. As one formula can be used for all types of fault, classification of fault types and phase selection are not required. The shunt capacitances of the line are considered by utilizing the distributed parameters model of the transmission lines. The proposed algorithm is rigorously investigated for various fault scenarios in SVC compensated transmission system. The simulation cases in the MATLAB environment verifies that the proposed scheme has excellent performance. Test results are compared with a conventional fault location technique to illustrate the accuracy of the proposed algorithm. 2019 Elsevier Ltd This publication was made possible by NPRP Grant no. 11S-1125-170027 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Scopus 2-s2.0-85071925020

We perform a thorough structural search with the minima hopping method (MHM) to explore low-energy structures of methylammonium lead iodide. By combining the MHM with a forcefield, we efficiently screen vast portions of the configurational space with large simulation cells containing up to 96 atoms. Our search reveals two structures of methylammonium iodide perovskite (MAPI) that are substantially lower in energy than the well-studied experimentally observed low-temperature $Pnma$ orthorhombic phase according to density functional calculations. Both structures have not yet been reported in the literature for MAPI, but our results show that they could emerge as thermodynamically stable phases via compression at low temperatures. In terms of the electronic properties, the two phases exhibit larger band gaps than the standard perovskite-type structures. Hence, the pressure-induced phase selection at technologically achievable pressures (i.e., via thin-film strain) is a viable route towards the synthesis of several MAPI polymorph with variable band gaps.