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The equilibrium crystal structure of LnMnO3 (Ln: lanthanide) is known to be orthorhombic when larger ions from La3+ to Dy3+ are used as Ln3+, and hexagonal when smaller ions from Ho3+ to Lu3+ are used. Research indicates that the hexagonal phase forms when the tolerance factor, expressed as functions of radii of the constituent ions, is less than 0.840. In this study, we attempted to induce oxygen deficiency in DyMnO3 through solidification at low oxygen partial pressure using an aerodynamic levitator. The objective was to decrease the tolerance factor by reducing the valence of manganese ions and thereby increasing their ionic radius. The results showed an increase in oxygen deficiency as the oxygen partial pressure decreased. Based on the assumption that the manganese ions' valence decreased due to an increase in oxygen deficiency, the corresponding tolerance factor evaluated from the average ionic radii of manganese and oxygen also decreased. This decrease promoted the formation of the hexagonal phase, similar to the effect observed when the ionic radius of Ln3+ is reduced. [ABSTRACT FROM AUTHOR]

The phases of high-entropy alloys (HEAs) are closely related to their properties. However, phase prediction bears a significant challenge due to the extensive search space and complex formation mechanisms of HEAs. This study demonstrates a precise and timely methodology for predicting alloy phases. It first developed a machine learning classifier using 145 features and a dataset with 1009 samples to differentiate the four types of alloy phases. Feature selection was performed on the feature set using an Embedded algorithm and a genetic algorithm, resulting in the selection of nine features. The Light GBM algorithm was chosen to train the machine learning model. Finally, the implementation of oversampling and cost-sensitive methods enables LightGBM to tackle the problem of insufficient accuracy in BCC+FCC phase classification. The resulting accuracy of the alloy phase prediction model, evaluated through ten-fold cross-validation, stands at 0.9544. [ABSTRACT FROM AUTHOR]

In the process of hot-dip Zn-Al-Mg alloy coating, the plating solution dissipates heat in the direction perpendicular to the steel plate, which is considered to be a process of directional solidification. To understand the relationship between microstructure and cooling rate of Zn-Al-Mg alloys, both the phase constitution and microstructure characteristic length scales of Zn-9.5Al-3Mg-0.01Ce (wt.%) alloy were investigated by the directional solidification experiments at different growth velocities (V=40, 80, 160, 250 µm·s−1). The experimental results show that the microstructure of directionally solidified Zn-9.5Al-3Mg-0.01Ce alloy is composed of primary Al dendrites and (Zn-Al-Mg2Zn11) ternary eutectics at the growth velocities ranging from 40 to 250 µm·s−1. The primary Al dendrites are aligned regularly along the growth direction, accompanied with obvious secondary dendrites. The relationship between the microstructure length scale and the thermal parameters of solidification is obtained: λ1=374.66V−0.383, and λ2=167.5V−0.563 (λ1 is the primary dendrite arm spacing, and λ2 is the secondary dendrit arm spacing). In addition, through the interface response function (IRF) and the nucleation and constitutional undercooling (NCU), the phase selection of Zn-9.5Al-3Mg-0.01Ce is obtained: (Zn+Al+Mg2Zn11) ternary eutectics in the Zn-9.5Al-3Mg-0.01Ce alloy will be replaced by ternary eutectics (Zn+Al+MgZn2) when the growth rate is lower than 7.53 µm·s−1. [ABSTRACT FROM AUTHOR]

The equilibrium crystal structure of LnMnO3 (Ln: lanthanide) has been reported to be orthorhombic when relatively large ions from La3+ to Dy3+ are used as Ln3+ and hexagonal when relatively small ions from Ho3+ to Lu3+ are used. It has been reported that the hexagonal phase is formed when the tolerance factor, expressed as functions of radii of the constituent ions, is less than 0.840. In the present study, we attempted to induce oxygen deficiency in DyMnO3 under the solidification at low oxygen partial pressure using aerodynamic levitator to reduce the tolerance factor through a decrease in the valence of manganese ions and the accompanying increase in the ionic radius. The results showed that the oxygen deficiency increases with decreasing oxygen partial pressure. Assuming that valence of manganese ions decreased due to the increase in oxygen deficiency, the corresponding tolerance factor evaluated from the average ionic radii of manganese and oxygen decreased, which promoted the formation of the hexagonal phase as is the case with the reduction of the ionic radius of Ln3+. [ABSTRACT FROM AUTHOR]

In this work, we reviewed the available phase selection rules comprising atomic size and topological aspects, entropies, enthalpies, melting points, valence and itinerant electron concentrations, as well as electronegativity, and validated them using a carefully prepared database of CuTiZr alloys, to assess their strengths and weaknesses. Substantially increasing interest over the last two decades in high-entropy alloys and metallic glasses motivated the search for phase selection rules that could support the designing of new alloys. These rules are most often based on phenomenological correlation between structure and topological-, thermodynamic- and/or electronic structure-related properties of alloy systems. The available phase selection criteria are, therefore, not scientifically derived, but rather statistically constructed from available experimental data. Thus, they contain potential pitfalls, hindering the rational interpretation of obtained results. With this in mind, this work discusses the importance of defining the influence of phase transformation kinetics and synthesis method on an alloy’s final structure, while highlighting the challenges of using phenomenological alloying guidelines. Furthermore, we show that the interpretation of available phase selection criteria without caution may lead to the designing and fabrication of alloys with undesired phases.

[Display omitted] Discovering new high-entropy alloys (HEAs) in the vast compositional space requires a growing power of classical computers for training machine learning models. The exponential increase of HEA data will pose a challenge in making the machine learning process prohibitively time consuming in the foreseeable future. Quantum computers, which use quantum superposition and interference to perform computations, hold great potential in handling big data and accelerating the optimization algorithms ubiquitous in machine learning models. Here we adopt a quantum computer simulator and quantum processors to prepare for the future challenge in new HEA discovery. We first train a classical artificial neural network (ANN), which uses HEAs' compositions as inputs and the corresponding phases as outputs, to predict phase selection. We then apply a quantum computer simulator that implements a hybrid quantum–classical machine learning algorithm to accomplish the same supervised machine learning task. We find that the resulting testing accuracy is comparable to that from classical ANN calculations. We finally apply quantum processors to perform the hybrid quantum–classical machine learning calculations and obtain slightly lower accuracy ascribed to the fragile nature of quantum bits in quantum processors. Our work initiates the adoption of fledgling quantum computers in the noisy intermediate-scale quantum (NISQ) era for discovering new HEAs. [ABSTRACT FROM AUTHOR]

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 (λ1) and cooling rate (τ) can be described. [ABSTRACT FROM AUTHOR]

[Display omitted] • Efficient and phase-selective synthesis of (NH 4) x (Sc,Cr)F (3+ x) (x = 0, 1, 3) was achieved via methanol-based solvothermal reaction up to 140 °C. • Phase composition was found to critically depend on NH 4 F/(Sc,Cr) molar ratio and reaction temperature. • The vibrational and thermal behaviors of the ammonium fluoroscandates (x = 1, 3) were unveiled. • ScF 3 :Cr3+ showed ∼700–1300 nm NIR luminescence under 470 nm blue light excitation, with a large FWHM of ∼156 nm. 5 at% Cr3+ doped ScF 3 , NH 4 ScF 4 and (NH 4) 3 ScF 6 were selectively synthesized via solvothermal reaction of metal nitrate and NH 4 F in methanol for 24 h, with the effects of NH 4 F/M molar ratio (M=Sc 0.95 Cr 0.05), methanol content and reaction temperature (up to 140 °C) being systematically investigated. The compounds were characterized in detail for crystal structure, microstructure, thermal behavior and vibrational properties, and broadband NIR luminescence (∼700–1300 nm) with an FWHM (full width at half maximum) as large as ∼156 nm was obtained from the as synthesized ScF 3 :Cr3+ phosphor powder under 470 nm blue light excitation. The technique is advantageous over aqueous processing since it allows high yield production of the water-soluble ammonium fluoroscandates and was expected to be well applicable to analogous materials such as those of the Al, Ga and In elements. [ABSTRACT FROM AUTHOR]

[Display omitted] • An OSDA-free anion tuning approach to control zeolite polymorphism is reported. • Phenoxide media allow favorable kinetic control to facilitate CHA nucleation. • Stabilized dimeric aluminate intermediate is the key for CHA phase selection. Synthesis of small-pore chabazite (CHA) zeolites in the absence of organic structure-directing agents (OSDA) has been proven difficult. A judicious mixed cation approach recently reported could expand the design space of CHA formation. In a seemingly opposite direction, we herein report an anion tuning approach for controlling the zeolite polymorphism in an OSDA-free system that effectively promotes hierarchical CHA formation in a competitive growth with MER. Phenoxide media, utilizing mild in-situ nucleophilic etching in cooperation with zeolite framework growth, allow beneficial kinetic control to facilitate CHA nucleation. Operando analyses reveal the crucial role of stabilized dimeric aluminate species as a key intermediate for CHA phase selection. The phenol-mediated CHA zeolites exhibit almost perfect 9 molecules per unit cell CO 2 uptake capacity and no CH 4 adsorption. This work offers an anion tuning strategy for controlling zeolite polymorphism as a supplement to the current phase-selection toolbox that utilizes mixed inorganic cations. [ABSTRACT FROM AUTHOR]

The phases of high-entropy alloys (HEAs) are closely related to their properties. However, phase prediction bears a significant challenge due to the extensive search space and complex formation mechanisms of HEAs. This study demonstrates a precise and timely methodology for predicting alloy phases. It first developed a machine learning classifier using 145 features and a dataset with 1009 samples to differentiate the four types of alloy phases. Feature selection was performed on the feature set using an Embedded algorithm and a genetic algorithm, resulting in the selection of nine features. The Light GBM algorithm was chosen to train the machine learning model. Finally, the implementation of oversampling and cost-sensitive methods enables LightGBM to tackle the problem of insufficient accuracy in BCC+FCC phase classification. The resulting accuracy of the alloy phase prediction model, evaluated through ten-fold cross-validation, stands at 0.9544.

A field-programmable gate array (FPGA) high-resolution time-to-digital converter (TDC) based on phase-wrapping, sorting, and selection to achieve an extremely fine bin size of 1 ps is proposed in this paper. Based on Nutt interpolation method, a wide measurement range with a high resolution can be realized at the same time. The input signal is fed into tapped delay lines (TDL) with regularized and automated cell placements to generate a multitude of delayed signals with plenty of regularized phase shifts. Due to periodicity, those phase shifts will be equivalently wrapped within a reference clock period and then phase sorting, ROM-based selection are applied to construct a merged TDL with uniform phase division across the reference clock period. The FPGA TDC was implemented successfully on both Altera Stratix IV to achieve a resolution as fine as 1ps with a measurement range of 1s. The short-range integral non-linearity errors (INL) are measured as −1.470– 1.676 LSB for Stratix IV to demonstrate its excellent linearity.

Electromagnetic levitation (EML) was employed for studying the velocity and morphology of the solidification front as a function of undercooling of metallic materials. The limitation of the EML technique with respect to low melting alloys that emit outside the visible light spectrum was overcome by employing state-of-the-art high-speed mid-wavelength infrared cameras (MWIR cameras) with a photon detector. Due to the additional thermography contrast provided by the emission contrast of the solid and liquid phases, conductor, and semi-conductor, the pattern formation of Al-based alloys was studied in detail, revealing information on the nucleation, phase selection during solidification, and the influence of convection. [ABSTRACT FROM AUTHOR]

Inverter-interfaced renewable energy sources (IIRESs) are typically controlled during fault conditions to meet fault ride-through (FRT) requirements, e.g., reactive current generation (RCG) requirements specified by grid codes (GCs). However, fault currents generated by inverters are different from the traditional sources, i.e., synchronous generators. Consequently, phase selection methods (PSMs) used by protection relays could suffer from erroneous fault type classification. This paper develops a dual current controller (DCC) that regulates the inverter's negative- and positive-sequence currents to simultaneously meet phase selection and RCG requirements. First, the negative-sequence-current angle is obtained based on the angles of both zero- and positive-sequence currents to enable a correct operation for phase selection. Then, the positive-sequence current angle is adjusted to reach a trade-off between RCG requirements and phase selection achieved by the negative-sequence current. Lastly, the reference currents of the IIRES are generated in the stationary frame without violating the inverter's current limits. The proposed DCC supports the grid voltage by meeting the RCG requirements and enhancing the grid reliability and resilience by enabling correct phase selection. Comprehensive time-domain and real-time simulation verify the precise operation of the proposed DCC under various fault conditions and GCs. [ABSTRACT FROM AUTHOR]

The tasks of phase selection (recognition of damaged phases) and location (determination of the fault location) are solved by a universal algorithm for monitoring an arbitrary site of the presumed fault location. The currents and voltages observed on one side are converted into estimates of the electrical quantities at that location, which are determined on the assumption that the line is not damaged before that position. The converter is an algorithmic model of the initial section of the line with variable length. The algorithmic model is created based on a priori information about the line parameters. Information about the structure and parameters of the rest of the network is required to determine a priori coordinate functions that express the currents in the damage branches through the components of the output voltages or currents of the algorithmic model. The type of components is determined by the completeness of the observer's information base. The most valuable emergency components in terms of information are available, when a short circuit (SC) occurs against the background of the previous mode. However, in the situation when voltage is applied to an already damaged line, then one must be satisfied with the components of the zero and negative sequences. The null value of the reactive power of all damaged phases serve as the criterion for determination of the fault location (DFL), and the boundary conditions for single- and two-phase short circuits as the criterion for phase selection. The tasks of selection and location are closely intertwined. Generally speaking, a complete information base provides an opportunity to perform the detection and ranging without regard to the type of short circuit. But this will be a preliminary estimate of the location of the short circuit. Recognition of damaged phases will result in its refinement. But with an incomplete information base, phase selection certainly precedes location. [ABSTRACT FROM AUTHOR]

Inverter-interfaced distributed generators (IIDGs) have fault current signatures that could jeopardize protective relaying. This paper unveils the failure of phase selection methods (PSMs) utilized by commercial relays in the presence of four-wire IIDGs, which adversely impacts the grid resiliency and reliability. A triple current controller (TCC) is proposed to regulate the inverter’s sequence currents during unbalanced faults to ensure accurate fault type identification. The negative- and positive-sequence components are extracted using a decoupled double synchronous reference frame (DDSRF)-based phase-locked loop (PLL). Further, a second-order generalized integrator (SOGI)-based PLL is employed for zero-sequence component synchronization. The negative- and zero-sequence reference currents are generated to force the angles of IIDG sequence currents to behave like those from synchronous generators (SGs) and abide by the inverter’s current limits. Consequently, commercial PSMs can correctly identify the fault type. The proposed TCC scheme pertains to four-wire as well as transformer-less IIDGs. A performance evaluation using time-domain simulations is conducted on a CIGRE benchmark system to confirm the success of the proposed control scheme under different fault conditions. [ABSTRACT FROM AUTHOR]

Measurements of the thermal diffusivity of thin and bulk indium-doped lead telluride have been taken using a modified method of dynamic gratings. Thermal gratings were recorded by a 20 ns pulsed laser radiation at a wave length of 532 nm. Dynamic gratings were recorded by a 635 nm continuous laser radiation. The analysis of the diffraction signal kinetics made it possible to determine the life-time of thermal gratings recorded in the investigated samples. It is shown that the use of an additional homodyne field coherent with respect to the diffraction signal field makes it possible to enhance and filter off the selected information component. Based on registered kinetic dependences of the diffracted signal intensity, the thermal diffusivity of bulk and thin film indium-doped lead telluride samples was determined. It has been established that for a micron-thick film, the thermal diffusivity is ten percent lower than for a bulk sample. An investigation has been made into the dependence of the heat transfer in the said samples on their temperature and it has been shown that the rise in the samples′ temperature in the range from 40 to 95°C results in a 20-percent decrease of their thermal diffusivity. [ABSTRACT FROM AUTHOR]

Phase selection and microstructure evolution of the undercooled eutectic Ti-Si alloy were systematically investigated by the electromagnetic levitation method, and the maximum undercooling achieved was 318 K (0.2TE). The migration of the liquid-solid interface was in-situ detected by a high-speed camera system. When the undercooling is smaller than 140 K, the liquid-solid interface is smooth. Once the undercooling arrives at 230 K, the liquid-solid interface is irregular, which reflects the growth transition from the solute control to the combined controls of solute and thermal. The eutectic growth velocity increases as an exponential function of undercooling. The electromagnetic stirring effect makes it difficult to increase undercooling, but plays an important role in accelerating the eutectic reaction velocity at low and moderate undercoolings. Primary dendritic β-Ti phase appears in the solidified alloy from 63 to 176 K undercoolings, and the microstructure is completely composed of eutectic once the undercoolings increase up to 230 K. When the undercoolings exceed 273 K, the microstructure consists of uniformly distributed irregular eutectic. For the drop tube experiments, the microstructures composed of a large amount of dendritic α-Ti phase and eutectic phase are found in a wide range of diameters from 69 to 725 µm. As the decrease of diameter, the solubility of Si in the dendritic α-Ti phase dramatically increases from 6.80% to 10.73%, and the ratio of the area occupied by the dendritic α-Ti on a cross-section of solidified alloy obviously increases from 23.52% to 41.02%, which result from the combined effects of high undercooling and large cooling rate. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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.

Molybdenum carbides are promising low-cost electrocatalysts for electrolyzers, fuel cells, and batteries. However, synthesis of ultrafine, phase-pure carbide nanoparticles (diameter < 5 nm) with large surface areas remains challenging due to uncontrollable agglomeration that occurs during traditional high temperature syntheses. This work presents a scalable, physical approach to synthesize molybdenum carbide nanoparticles at room temperature by ion implantation. By tuning the implantation conditions, various molybdenum carbide phases, stoichiometries, and nanoparticle sizes can be accessed. For instance, molybdenum ion implantation into glassy carbon at 30 keV energy and to a fluence of 9 × 10 16 at cm -2 yields a surface η-Mo 3 C 2 with a particle diameter of (10 ± 1) nm. Molybdenum implantation into glassy carbon at 60 keV to a fluence of 6 × 10 16 at cm -2 yields a buried layer of ultrafine γ'-MoC/η-MoC nanoparticles. Carbon ion implantation at 20 keV into a molybdenum thin film produces a 40 nm thick layer primarily composed of β-Mo 2 C. The formation of nanoparticles in each molybdenum carbide phase is explained based on the Mo-C phase diagram and Monte-Carlo simulations of ion-solid interactions invoking the thermal spike model. The approaches presented are widely applicable for synthesis of other transition metal carbide nanoparticles as well., (© 2023 Wiley‐VCH GmbH.)

A method for fault type discrimination and faulted phase identification using instantaneous local current measurements is proposed. Seven current components are obtained from the measured three-phase instantaneous currents through a transformation and band passed filtered to remove the fundamental components and high frequency content. Upon detecting a fault, nine fault discrimination indices are computed taking different ratios of the maximum rates of change of these filtered current components. The indices are used to (i) separate ground faults from the phase-to-phase and three-phase faults, (ii) discriminate phase-to-ground from phase-to-phase-to-ground faults, (iii) differentiate phase-to-phase faults from the three-phase faults, and (iv) identify the faulted phases. As the indices are ratios, decisions are less affected by the fault resistance. The algorithm was validated using a power system simulated in PSCAD/EMTDC. Extensive testing involving more than 10,000 fault scenarios showed that fault type and faulted phases can be successfully identified. The algorithm found some difficulty in identifying the phases involved in phase-to-phase-to-ground faults at certain fault inception angles, and one of the thresholds can be affected by the transposition scheme. [ABSTRACT FROM AUTHOR]

Directional, phase-selection, and distance elements of a relay are prone to misoperation in the presence of inverter-based resources (IBRs). To address these problems, modifications of relay elements as well as new control schemes for IBRs have been proposed in the literature. These methods focus mainly on addressing the misoperation of only one of the above relay elements. The available solutions that are based on a new control system focus only on the negative-sequence current loop. Thus, they work only for unbalanced faults. This paper proposes a comprehensive dual current control scheme for IBRs during all types of faults such that all of these relay elements operate correctly. The proposed method controls the IBR to operate as a voltage source behind a virtual impedance in the positive-sequence circuit, and a single impedance in the negative-sequence circuit, thereby emulating the phase angles of a synchronous generator's (SG's) fault current. The proposed method also maximizes the active, and reactive current generation of the IBR during faults, and emulates the incremental sequence current magnitudes of an SG. The proposed method does not require altering the relay elements. Moreover, correct operation of the relay elements is achieved regardless of the fault type, resistance, and location. The effectiveness of the proposed method is verified through not only simulation studies, but also hardware-in-the-loop testing of commercial relays. [ABSTRACT FROM AUTHOR]

Electromagnetic levitation (EML) was employed for studying the velocity and morphology of the solidification front as a function of undercooling of metallic materials. The limitation of the EML technique with respect to low melting alloys that emit outside the visible light spectrum was overcome by employing state-of-the-art high-speed mid-wavelength infrared cameras (MWIR cameras) with a photon detector. Due to the additional thermography contrast provided by the emission contrast of the solid and liquid phases, conductor, and semi-conductor, the pattern formation of Al-based alloys was studied in detail, revealing information on the nucleation, phase selection during solidification, and the influence of convection.

Inverter-based resources respond differently than synchronous generation sources during power system faults, challenging line protection reliability. Part I of this paper presented cases that challenge line protection schemes. In this paper (Part II), we provide solutions that can be applied to gain a substantial improvement in reliability. [ABSTRACT FROM AUTHOR]

The equilibrium crystal structure of LnMnO3 (Ln: lanthanide) has been reported to be orthorhombic when La3+ to Dy3+ are used as Ln3+, and hexagonal when Ho3+ to Lu3+ are used. Whereas Kumar et al. reported a two-phase structure of orthorhombic and hexagonal phases is formed in DyMnO3 when it was solidified from the undercooled melt under containerless state. The reason for the formation of the two-phase structure was not thoroughly addressed and discussed. We investigated the formation mechanism for the two-phase structure from the undercooled melt of DyMnO3 in detail. As a result, the surface morphology, microstructure, and crystal structure of the samples, in which the nucleation was forced at a predetermined temperature with a Mo needle, indicated that the hexagonal and orthorhombic phases are dominant at high and low temperatures, respectively. When the sample was quenched from below 1670K in a water bath, as-solidified sample consisted of h-DyMnO3 and o-DyMnO3. Whereas a single phase of h-DyMnO3 was obtained in the sample quenched from above 1670 K. This phenomenon can be quantified in terms of nucleation-rate determined phase selection. That is, the activation energy for forming a critical nucleus calculated based on the model of the crystal-melt interface proposed by Turnbull and Speapen suggests that the o-DyMnO3 phase can be heterogeneously nucleated on the interface of the initially formed h-DyMnO3 phase. [ABSTRACT FROM AUTHOR]

The single crystal form and uncontrollable topography of CaCO3 in nature severely restrict its product grade and application. Meanwhile, lignin is still not utilized efficiently. In order to improve this, three types of lignin monomer model compounds as p‐coumaric acid (PCA), ferulic acid (FA), and sinapic acid (SA) are employed to induce the growth of CaCO3 to investigate the relationship between lignin structure and CaCO3 crystallization. The synthesized PCA and CaCO3 composite crystals (PC‐ACCs), FA and CaCO3 composite crystals (F‐ACCs), and SA and CaCO3 composite crystals (S‐ACCs) are characterized by field emission scanning electron microscope (FESEM), X‐ray diffraction (XRD), and Fourier transmission infrared spectroscopy (FTIR) to ascertain their molecular structures and crystal information. The growth rule of the acid and CaCO3 composite crystals (ACCs) induced by the three units is also explored. The results show that the vaterite and calcite of ACCs can be formed selectively. In the presence of PCA, FA, and SA, pH is the key factor on the phase selection of ACCs. The temperature and organic acid type also play important roles on the formation of CaCO3. The ACCs present distinguishing surface topographies at different temperatures. The number of methoxyl in the PCA, FA, and SA decides the phase ratio of vaterite and calcite in the ACCs. [ABSTRACT FROM AUTHOR]

The crystal stmctuie of LnMnO3 (Ln: lanthanide) has been reported to be orthorhombic from La to Dy aie used as Ln, and hexagonal from Ho to Lu. Whereas Kumai et al. reported that orthorhombic and hexagonal phases aie co-exist in samples of DyMnO3 solidified from the undercooled melt under containerless state. We investigated whether this two-phases structuie was the result that the hexagonal phase formed as a metastable phase is frozen to room temperature or the result that the solid state phase transfonnation of the hexagonal # orthorhombic occurred at the cooling stage. The surface morphology of the samples, the nucleation of which were triggered by contacting with the Mo wire at given temperatures, indicates that hexagonal and orthorhombic phases are stable at high and low temperatures, respectively. Furthermore, in the experiment where the melt was dropped into water, it was found that if the temperatuie of the melt was below 1666 K, the XRD pattern of the as-solidified sample showed two phases, A-DyMnO3 and o-DyMnC3, whereas above 1666 K, it showed a single phase of A--DyMnC3. This phenomenon can be quantified in terms of nucleation rate-determined phase selection. That is, the activation energy for nucleation calculated based on the model of the crystal-melt interface proposed by Turnbull and Spaepen suggests that the o-DyMnO3 phase can be heterogeneously nucleated on the interface of the initially formed A-DyMnC3 phase. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Computational prediction of phase stability of multi-principal element alloys (MPEAs) holds a lot of promise for rapid exploration of the enormous design space and autonomous discovery of superior structural and functional properties. Regardless of many plausible works that rely on phenomenological theory and machine learning, precise prediction is still limited by insufficient data and the lack of interpretability of some machine learning algorithms, e.g., convolutional neural network. In this work, a comprehensive approach is presented, encompassing the development of a complete dataset that contains 72 387 density functional theory calculations, as well as a predictive global phenomenological descriptor. The phase selection descriptor, based on atomic electronegativity and valence electron concentration, significantly outperforms the widely used valence electron concentration, excelling in both accuracy (with an f1 score of 63% compared to 47%) and its ability to predict the HCP phase (0.48 recall compared to 0). The comprehensive data mining on the global design space of 61 425 quaternary MPEAs made from 28 possible metals, together with the phenomenological theory and physical interpretation, will set up a solid computational science foundation for data-driven exploration of MPEAs., (© 2024 Wiley‐VCH GmbH.)

Vanadium oxides exhibit a broad spectrum of physical properties due to their ability to form various compounds and polymorphs. To utilise a particular property, it is essential to selectively synthesise a desired phase. Herein, we demonstrate a method to selectively and reproducibly grow (00 l)-textured VO 2 (B) thin films using an amorphous SrTiO 3 buffer layer by sputtering at <350 °C, which enables their direct integration with read-out-integrated-circuits (ROICs), glass, and polymer substrates. The VO 2 (B) films exhibit high temperature-coefficient-of-resistances (TCRs) (>−3.5%/K at 25 °C and >−1.5%/K at 95 °C) and low electrical resistivities (∼5 × 10−1 Ω cm at 25 °C and <1 × 10−1 Ω cm at 95 °C), which are favourable for realising highly-sensitive, low-noise, and high-temperature microbolometers. A robust thermal stability of these VO 2 (B) thin films at ambient pressure will provide new opportunities to incorporate thermal sensing functions to various electronics. [ABSTRACT FROM AUTHOR]

Os silicide thin films were grown on (001) Si substrate using MBE method. The structural characterizations of the grown films were investigated using x-ray diffraction (XRD) measurements, Raman spectroscopy and x-ray photoelectron spectroscopy (XPS). In addition, the surface morphology was depicted by AFM micrographs, and the nature of the grown epilayers was recognized using Transmission electronic microscope (TEM). All the samples had rough surface with various size of hillocks and intermediate valley like regions with a remarkable decrease in surface roughness after annealing. The measurements revealed a significant difference in the formed phases and crystalline quality with the growth parameters. The influence of Si buffer layer with thickness of 20 nm which deposited at relatively low temperature of 650 °C, and high temperature annealing (at 1050 °C) of the grown Os silicide epilayer was investigated. It was confirmed that isolating a metastable phase OsSi2 was established by selecting the required growth parameters. [ABSTRACT FROM AUTHOR]

Nano structured coating system demonstrates outstanding performance stemming from unique structure evolution. Zr/Si coating was proposed as an ideal candidate for the protection of Zr alloy cladding. However, the phase selection remains a challenge to coordinate the complex requirement under the service and accident conditions of reactor core. In this work, a phase selection mechanism for amorphous Zr-Si-O (abbr. ZSO) was elucidated by the competitive consumption of Zr layer by silicidation and oxidation, which was also scale-dependent. The energy-loss near-edge fine structure and nanoindentation were also employed to characterize the unique scale effect in the two processes. Both the oxides kinetics and elastic modulus gain indicated an immediate passivation process under the subcritical condition after the in situ phase selection of the amorphous ZSO. Ab initio molecular dynamics (AIMD) was performed to disclose the origination of depressed O migration in ZSO. The multilayer structure also shows accident tolerance potential. The interfacial phase selection provided a strategy to regulate mesoscale structure originating from nanomter interface and meets the diversified requirement for "structure-performance relationship" under the service and accident conditions. • Nano Zr-Si-O (ZSO) layer was in situ formed on the interface of Zr/Si. • The phase selection of ZSO was ascribed to the competition between silicidation and oxidation. • The superior oxidation resistance of multilayer was attributed to the formation of ZSO. • The strong bonding and compact atomic structure in ZSO was revealed by experiment and modeling. [ABSTRACT FROM AUTHOR]

The effect of high pressure on the microstructure of hypo-peritectic Al–38wt.%Ni alloy was studied. The results show that Al3Ni and Al3Ni2 phases coexist at ambient pressure. However, it becomes a typical hyper-eutectic microstructure when synthesized at 2 GPa and 4 GPa. Meanwhile, the interface temperature of Al3Ni and Al3Ni2 phases was calculated with the combination of the BCT dendrite growth model, which is suitable for the Al3Ni2 phase. According to the highest interface temperature principle, the result shows that the Al3Ni phase dominates over 1–5 GPa. Finally, the Debye temperature and potential energy of the hypo-peritectic Al–38wt.%Ni alloy under different pressures were researched. Based on the low temperature specific heat-capacity curve. The Debye temperatures at ambient pressure, 2 GPa, and 4 GPa are 504.4 K, 508.71 K and 515.36 K, respectively, and the potential energy in the lowest point decreases with the increase of pressure.

The unique fault current signatures of inverter-interfaced renewable energy sources (IIRES) hinders the correct operation of the existing phase selection methods (PSMs) that operate based on the sequence currents. As a result, the system resilience during unbalanced faults is imperiled. In this paper, a new dual current controller is developed to regulate the relative angles of the IIRES sequence currents during unbalanced faults to enable accurate identification of the fault type by the existing PSMs. The proposed method consists of three design stages. In Stage I, the IIRES control system identifies the fault type using the sequence voltages at its terminal. Stage II aims at generating the appropriate reference angle for the IIRES negative-sequence current. In Stage III, the IIRES sequence currents are controlled in the double synchronous reference frame to track the reference angle. The proposed controller makes the existing PSMs immune against fault conditions and reactive current generation requirements imposed by grid codes. Consequently, the protection system can select and trip only the faulted phase(s), and thus, the system reliability is considerably enhanced. Time-domain simulations are used to confirm the successful operation of the proposed controller under different fault conditions and grid codes. [ABSTRACT FROM AUTHOR]

Abstract High-entropy alloys (HEAs) have been receiving intensive attention due to their unusual properties that largely depend on the selection among three phases: solid solution (SS), intermetallic compound (IM), and mixed SS and IM (SS + IM). Accurate phase prediction is therefore crucial for guiding the selection of a combination of elements to form a HEA with desirable properties. It is widely accepted that the phase selection is correlated with elemental features such as valence electron concentration and the formation enthalpy, leading to a set of parametric phase-selection rules [ 1 ]. Previous studies on predicting the phase selection employed density functional theory (DFT) calculations to obtain some correlated parameters. But DFT calculations are time consuming and exhibit uncertainties in terms of treating the d orbitals of transition-metal atoms that are often components of HEAs. Here we employ machine learning (ML) algorithms to efficiently explore phase selection rules using a comprehensive experimental dataset consisting of 401 different HEAs including 174 SS, 54 IM, and 173 SS + IM phases. We adopt three different ML algorithms: K-nearest neighbours (KNN), support vector machine (SVM), and artificial neural network (ANN). To avoid overfitting, we divide the whole dataset into four nearly equal portions to perform a cross validation. For the classification of the three phases at the same time, the testing accuracy values from the KNN, SVM and ANN calculations achieve 68.6%, 64.3% and 74.3%, respectively. We then focus on the classification of two of the three phases using SVM and ANN. We find that the testing accuracy values using ANN in classifying the SS and IM phases, the SS + IM and IM phases, and the SS and SS + IM phases, are 86.7%, 94.3%, and 78.9%, respectively, which are higher than the corresponding testing accuracy values using SVM. As such, the trained ANN model performs the best among the three ML algorithms and is useful for predicting the phases of new HEAs. Our work provides an alternative route of computational design of HEAs, which is also applicable to accelerate the discovery of other metal alloys for modern engineering applications. Graphical abstract Image 1 [ABSTRACT FROM AUTHOR]

Abstract In order to further understand the dependence between phase composition and alloying component. (Al 21.7 Cr 15.8 Fe 28.6 Ni 33.9) x (Al 9.4 Cr 19.7 Fe 41.4 Ni 29.5) 100-x high entropy alloys (HEAs) are designed based on the AlCrFe 2 Ni 2 eutectic high entropy alloy (EHEA). The phase composition, microstructure and mechanical properties of this HEA are investigated systematically. The result shows that the volume fraction of body-centered cubic (BCC) phase increases from 5.32% to 98.81% as the x value increasing. Compressive testing shows that the yield strength of (Al 21.7 Cr 15.8 Fe 28.6 Ni 33.9) x (Al 9.4 Cr 19.7 Fe 41.4 Ni 29.5) 100-x HEAs boosts from 310 MPa to 1268 MPa, while the fracture strain gradually decreases from 55% (no fracture) to 33.85% with the development of x value. The accretion of BCC phase volume fraction is the main factor for increasing strength and decreasing fracture strain of alloy system. The valence electron concentration (VEC) is the fundamental parameter having affection on the phase selection of the alloy system, which was further verified by the calculation results of the physical parameters. [ABSTRACT FROM AUTHOR]

Abstract 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. Graphical abstract Image 1 [ABSTRACT FROM AUTHOR]

The as-cast CoCrFeNi high-entropy alloys show simple FCC structure and outstanding deformation ability at room temperature. Respectively, after 50% of deforming at room temperature and annealing at intermediate temperature range of 600 °C–800 °C for 2 h, CoCrFeNi alloys still show simple-phase FCC structure. It is noteworthy that CoCrFeNi high-entropy alloys can’t be strengthened by means of annealing, while deformation is an effective way to strengthen the alloys. It is investigated that the formation of sigma ( σ ) phase in high-entropy alloys is closely related to the difference of atomic radius ( δ ), the concentration of valence electron ( VEC ) and paired sigma-forming element ( PSFE ) content, and PSFE plays an crucial role. When PSFE > 40 at.%, 6.75 ≤ VEC ≤ 7.86, 4.0 ≤ δ ≤ 7.2, σ phase is prone to form in high-entropy alloys. In addition, alloying and processing route are two important factors that affect the sigma-formation in CoCrFeNi high-entropy alloys.

The microstructure, phase structure, mechanical properties and damping capacity of Al _x Fe _2 CrNiCu ( 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 Fe _2 CrNiCu HEAs. Among them, a novel dual phase microstructure consisting of 51 vol.% FCC and 49 vol.% BCC with large interface area was obtained in Al _0.5 FeCrNiCu 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 Al _0.5 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.

The phase selection of hyper-peritectic Al-47wt.%Ni alloy solidified under different pressures was investigated. The results show that Al3Ni2 and Al3Ni phases coexist at ambient pressure, while another new phase α-Al exists simultaneously when solidified at high pressure. Based on the competitive growth theory of dendrite, a kinetic stabilization of metastable peritectic phases with respect to stable ones is predicted for different solidification pressures. It demonstrates that Al3Ni2 phase nucleates and grows directly from the undercooled liquid. Meanwhile, the Debye temperatures of Al-47wt.%Ni alloy that fabricated at different pressures were also calculated using the low temperature heat capacity curve.

Compared with 2D Magnetic Resonance Imaging (MRI), 3D MRI is more powerful for generating high resolution images and visualizing small anatomical structures. However, 3D MRI acquisition is much more time-consuming due to the significantly larger number of phase encoding steps, which is directly proportional to the acquisition time. This paper proposes to select a volume-adaptive small subset of phases to accelerate 3D MRI scans and accurately reconstruct 3D images from the corresponding undersampled 3D k-space data. To avoid the delays caused by computationally expensive yet high-performance volume-adaptive phase selection, we propose a strategy of selecting multiple phases based on sampled slices from the volume during idle time within the repetition time (TR). To enhance the performance of phase selection, we propose a novel three-directional cross-attention phase selection network. Additionally, to improve the reconstruction performance, we introduce a three-directional slice-wise volume reconstruction. To the best of our knowledge, the proposed method, which we called EVOLVE (l e arning vol ume-adapti ve phases), is the first work that learns volume-adaptive phases for fast 3D MRI. The extensive experimental results on a large-scale 3D MRI dataset at various acceleration factors demonstrate the substantial performance improvement in terms of image reconstruction achieved by using the EVOLVE method for phase selection compared to traditional learning free 3D MRI phase selection methods. [ABSTRACT FROM AUTHOR]