Quinary System Research Articles

Solid–Liquid Phase Diagram of the Quinary Water–Salt System Li+, Na+, Rb+, Mg2+//SO42––H2O at T = 298.2 K

Lithium, rubidium, and magnesium are the elements with high development value found in the salt lake in the Qaidam Basin. The isothermal dissolution method was used to study the solid–liquid phase diagram of the quinary system Li+, Na+, Rb+, Mg2+//SO42––H2O at T = 298.2 K to develop and utilize valuable components in salt lakes and enrich thermodynamic data. Based on the experimental data, a series of diagrams were created. The results indicate that its space diagram consists of 9 crystalline regions, 21 isothermal dissolution curves, and 7 four-salt cosaturation invariant points at T = 298.2 K. The quinary system (Li+, Na+, Rb+, Mg2+//SO42––H2O at T = 298.2 K) produced five different double salts (3Na2SO4·Li2SO4·12H2O, Li2SO4·Rb2SO4, 3Li2SO4·Rb2SO4·2H2O, Rb2SO4·MgSO4·6H2O, and Na2SO4·MgSO4·4H2O); however, no double salt is created when lithium and magnesium or sodium and rubidium interact. The crystal area of the double salt Rb2SO4·MgSO4·6H2O is the greatest in the phase diagram of sodium sulfate saturation, while the crystal area of Li2SO4·H2O is the smallest in the phase diagram of magnesium sulfate saturation. The article concentrates on lithium loss during recovery. The experimental data and research can guide the efficient separation and utilization of lithium and rubidium in the bittern industry.

Accelerated design of high entropy alloys by integrating high throughput calculation and machine learning

Designing high entropy alloys (HEAs) from a large compositional space is challenging. The design process is accelerated by integrating computational techniques. The current study developed a framework for the accelerated identification of phases in HEAs by integrating high throughput calculations and machine learning (ML). The 19968 composition information was generated using high throughput CALculation of PHAse Diagrams (CALPHAD) calculations and used as a dataset for the machine learning algorithms. The Synthetic Minority Over-sampling Technique (SMOTE) makes unbiased data, and multiple machine learning algorithms are trained and compared. The Support Vector Machine (SVM) and Artificial Neural Network (NN) show test accuracy of ∼99%. The trained algorithm was used to predict phases in ternary, quaternary and quinary systems. The experimental comparison confirms that the algorithms successfully predicted the phase transitions in HEAs with respect to varying compositions. The developed framework can be adopted for designing new materials.

Empirical models to determine ions concentrations in lithium brines with high ionic strength

Argentina Puna brines are complex systems in which ions such as Na+, K+, Li+, Mg2+, Ca2+, SO42−, and B4O72− are presents. To obtain lithium carbonate from brines, they must be treated in order to increase its lithium concentrations and to eliminate the others ions that are presents in the brines. During concentration some salts can reach their solubility products (kps) and crystallize, producing different solid-liquid equilibriums. In order to design and select the process to purify the brine before lithium salts precipitation, it is necessary to know the other ions concentrations.Ion concentrations in solutions can be calculated based on the salts coefficient activities using Pitzer's model and its modifications. These methods have the restriction that can only be applied to solutions with ionic strength values up to 6 molal. The state of the art shows that the approach to study the equilibrium in complex system is to consider it as binary, ternary, quaternary and quinary systems. When ionic strength values are higher than 6 m the systems studied are binaries or have symmetrical ions.Brines of the Argentina Puna have, in general, initial ionic strength values around 6 molal and it increases when the brine is concentrated by evaporation, so the available thermodynamical models cannot be used to determine, beforehand, the final composition of a certain brine. In this work four different brines from four different Puna plateau in Argentina were evaporated to several degrees and ionic strength was calculated from the chemical brine's composition after each evaporation test. Ionic strength was found to correlate with the percentage of eliminated water following two different simple mathematical models, depending on the initial sulphate concentration of the brine and the possibility of its precipitation. Models to estimate the concentration of diluted ions of commercial value such as Li+, K+, and Mg2+ as function of ionic strength were also proposed. Ion concentrations could be modeled as function of the amount of eliminated water, once the correct relationship between this parameter and the ionic strength of the brine is established. These models correlate accurately ionic strength and ion concentrations for an ionic strength range from 4.8 to 15.4 molal; corresponding to percentages of water evaporated from 0% up to 60%.With these models it is possible to calculate beforehand the final ions concentrations after a given percentage of evaporated water. It allows to design brines processing and select the purification techniques without exhausting and time-consuming tests. Nowadays there are no tools that allows to do that, in consequence, each company must perform rigorous and numerous tests with its brines. Results of these work show that ionic strength is the parameter that unified brines behavior even if initial composition could be different. In consequence, it could be used as a parameter to describe brine behavior during evaporations.

Microstructural verification of the theoretically designed novel eutectic multi-principal element alloy

This letter proposes the theoretical design methodology based on the proportional mixing of binary eutectics for predicting novel eutectic multi-principal element alloys (EMPEAs). It was then experimentally verified by manufacturing a dual-phase eutectic Zr61.9AlTiVCr alloy having a density of 6.04 g/cc. Zirconium was identified as the eutectic forming element in this system, notably having only 3 binary eutectics in a quinary system. The alloy developed by vacuum arc melting revealed the formation of an irregular lamellar eutectic microstructure consisting of cubic and hexagonal Laves phases. The as-cast alloy had a superior hardness of HV527, with 780 MPa compressive strength. This study paves the way for designing new EMPEAs without depending on any simulation software.

Data-driven optimization of hardness and toughness of high-entropy nitride coatings

High coating hardness and toughness are mutually contradicting properties and are challenging to be achieved simultaneously. Combining the vast component space of high entropy systems and the powerful high-dimensional data processing tools is expected to be the best solution to this problem. In this paper, high-entropy nitride coatings data for quinary and hexagonal systems were collected and machine learning prediction models were trained. Using a new material system combined with multi-objective optimization, high-entropy nitride coatings with the optimal hardness and elastic modulus combination were successfully obtained and verified by experiments. In addition, the partial dependence heatmaps were used to visualize how elemental content affects mechanical properties prediction in this system. This approach helped to better interpret the optimization results and discover the unknown mapping relationships between elemental content and the mechanical properties of high-entropy nitrides in machine learning models.

Thermodynamic evaluation of the phase stability in mechanically alloyed AlCuxNiCoTi high-entropy alloys

This study investigates the phase stability of AlCuxNiCoTi high-entropy alloys with varying amounts of copper. The regular solution and Kohler’s models are used to thermodynamically evaluate the alloys and determine a symmetrical enthalpy across their compositions. The study calculates the Gibbs energy of mixing for a quinary alloy system using the extended Miedema theory and considering the change in enthalpy of mixing of the solid-solution and amorphous phases of 10 binary alloys. By comparing the experimental and predicted results, this study suggests that thermodynamic properties can help predict stable phases in multicomponent alloys comprising equiatomic and near-equiatomic elements. Furthermore, the structural instability of the solid-solution state resulting from differences in valence electron concentrations of the constituent elements in binary mixtures is discussed, highlighting the influence of alloying elements on the phase stability of multicomponent alloys.

Study on Stable Phase Equilibria of Quinary System LiBr–NaBr–KBr–MgBr2–H2O at 298.15 K

According to the composition characteristics of mineral elements in underground brine in the Sichuan basin of China, the complete phase equilibria and phase diagram of the quinary system LiBr–NaBr–KBr–MgBr2–H2O were studied at 298.15 K. Using the experimentally determined solubilities and equilibrium solids, the spatial stereo phase diagram of the quinary system, the dry base projection phase diagrams of the saturated surfaces of the four salts MgBr2·6H2O, KBr, LiBr·2H2O, and NaBr·2H2O, and the corresponding water content diagrams were plotted, respectively. The experimental results show that at 298.15 K, in addition to the four original components, the anhydrous salt NaBr and the double salt KBr·MgBr2·6H2O are formed. The phase diagram of the quinary system at 298.15 K contains 10 univariate curves, three invariant points, and six equilibrium solid-phase crystallization regions (KBr crystallization region, NaBr crystallization region, NaBr·2H2O crystallization region, MgBr2·6H2O crystallization region, LiBr·2H2O crystallization region, KBr·MgBr2·6H2O crystallization region). When MgBr2·6H2O or KBr is saturated, LiBr has a strong salting-out effect on KBr, NaBr, or MgBr2 and NaBr, while when LiBr·2H2O is saturated, MgBr2 has a salting-out effect on KBr and NaBr. All four saturated projection surfaces have MgBr2·6H2O, and NaBr is generated. These phase equilibrium data can provide a theoretical basis to guide underground brine mining and extract useful components.

From high-entropy alloys to high-entropy ceramics: The radiation-resistant highly concentrated refractory carbide (CrNbTaTiW)C

High-entropy materials represent the state-of-the-art on the alloy design strategy for future applications in extreme environments. Recent data indicates that high-entropy alloys (HEAs) exhibit outstanding radiation resistance in face of existing diluted alloy counterparts due to suppressed damage formation and evolution. An extension of the HEA concept is presented in this paper towards the synthesis and characterization of novel high-entropy ceramics as emergent materials for application in environments where energetic particle irradiation is a major concern. A novel carbide within the quinary refractory system CrNbTaTiW has been synthesized using magnetron-sputtering. The material exhibited nanocrystalline grains, single-phase crystal structure and C content around 50 at.%. Heavy-ion irradiation with in-situ Transmission Electron Microscopy was used to assess the irradiation response of the new high-entropy carbide (HEC) at 573 K and a comparison with the HEA within the system is made. No displacement damage effects appear within the microstructures of both HEA and HEC up to a dose of 10 displacements-per-atom. Surprisingly, the HEC has not amorphized under the investigated conditions. Xe was implanted in both materials and bubbles nucleated, but smaller sizes compared with conventional nuclear materials shedding light they are potential candidates for use in nuclear energy.

Solid-liquid equilibria in relevant subsystems of LiBr-NaBr-KBr-MgBr2-CaBr2-H2O system at 298.15K.

In view of the composition characteristics of lithium, calcium and bromine rich in Nanyishan oil and gas field brine of western Qaidam Basin, Qinghai Province, as well as based on the results reported in relevant literature, the phase equilibrium relationship of ternary system LiBr-CaBr2-H2O at 298.15K was studied by isothermal dissolution equilibrium method. The equilibrium solid phase crystallization regions, as well as the compositions of invariant point, in phase diagram of this ternary system were clarified. On basis of the above ternary system research, the stable phase equilibria of quaternary systems (LiBr-NaBr-CaBr2-H2O, LiBr-KBr-CaBr2-H2O and LiBr-MgBr2-CaBr2-H2O), as well as quinary systems (LiBr-NaBr-KBr-CaBr2-H2O, LiBr-NaBr-MgBr2-CaBr2-H2O and LiBr-KBr-MgBr2-CaBr2-H2O) were further carried out at 298.15K. According to the above experimental results, the corresponding phase diagrams at 298.15K were drawn, which revealed the phase relationship of each component in solution and the law of crystallization and dissolution, and meanwhile summarized changing trends. The research results of this paper lay a foundation for further research on the multitemperature phase equilibria and thermodynamic properties of lithium and bromine containing high-component brine system in later stage, and also provide basic thermodynamic data for guiding the comprehensive development and utilization of this oil and gas field brine resource.

Temperature-dependent yield stress of single crystals of non-equiatomic Cr-Mn-Fe-Co-Ni high-entropy alloys in the temperature range 10-1173 K

The temperature-dependent yield strengths of [1¯23]-oriented single crystals of four quinary non-equiatomic Cr-Mn-Fe-Co-Ni high-entropy alloys (HEAs) were investigated at temperatures of 10-1173 K. They exhibit similar trends with a rapid decrease of the critical resolved shear stress (CRSS) from 10 K to 300 K, followed by a much slower rate of decrease with increasing temperature and a plateau above 873 K. The HEAs with the highest and lowest Cr contents exhibit the highest and lowest yield strengths respectively at 10 K, but almost identical yield strengths at 300 K. Thus, at cryogenic temperatures, the magnitude of the temperature dependence of yield strength is positively correlated with Cr content. All the non-equiatomic HEAs also exhibit similar dislocation structures with planar arrays of smoothly-curved dislocations without any preferred orientations. Their stacking fault energy (SFE) decreases with increasing Cr content. An empirical expression is proposed to describe the composition dependence of SFE in the Cr-Mn-Fe-Co-Ni quinary system. A new route for optimizing the alloy design of non-equiatomic Cr-Mn-Fe-Co-Ni alloys in terms of strength and ductility through the combination of mean-square atomic displacement (MSAD) and SFE is discussed based on the results obtained.

Phases with the structure type Fe2P in quinary systems

Phases with the structure type Fe2P in quinary systems

Analyzing the effect of Li/Ni intermixing on Ni-rich layered cathode structures using atomistic simulation of the Li–Ni–Mn–Co–O quinary system

LiNixMnyCozO2 (x + y + z = 1, x > 0.6) Ni-rich layered structures are the most investigated and used cathode materials these days due to their high energy density. However, it is hard to avoid Li/Ni intermixing during synthesis and the charge/discharge cycle. This intermixing is known to degrade the cathode by inducing anisotropic stresses and phase transformations. On the other hand, some studies report that a certain amount of intermixing enhances electrochemical properties. Studying the detailed effect of the intermixing using an atomistic simulation may help in designing the cathode structure. In this paper, an interatomic potential for the Li–Ni–Mn–Co–O quinary system is developed by newly developing or modifying interatomic potentials for sub-unary, binary and ternary systems based on a second-nearest-neighbor modified embedded-atom method (2NNMEAM) formalism combined with a charge equilibration (Qeq) concept. This potential is used to analyze the effect of Li/Ni intermixing on Ni-rich cathode properties from three perspectives: lithium diffusion for rate properties, change in lattice parameter and internal stress for structural stability. The results show how the intermixing affects individual cathode properties and that controlling the intermixing will be particularly decisive in Ni-rich cathode materials. The Li–Ni–Mn–Co–O quinary potential also will be useful for analyzing and designing cathode materials.

Element-wise representations with ECNet for material property prediction and applications in high-entropy alloys

When developing deep learning models for accurate property prediction, it is sometimes overlooked that some material physical properties are insensitive to the local atomic environment. Here, we propose the elemental convolution neural networks (ECNet) to obtain more general and global element-wise representations to accurately model material properties. It shows better prediction in properties like band gaps, refractive index, and elastic moduli of crystals. To explore its application on high-entropy alloys (HEAs), we focus on the FeNiCoCrMn/Pd systems based on the data of DFT calculation. The knowledge from less-principal element alloys can enhance performance in HEAs by transfer learning technique. Besides, the element-wise features from the parent model as universal descriptors retain good accuracy at small data limits. Using this framework, we obtain the concentration-dependent formation energy, magnetic moment and local displacement in some sub-ternary and quinary systems. The results enriched the physics of those high-entropy alloys.

Effect of TiO2 content on structure of BaO-CaO-Al2O3-TiO2-Li2O slags by molecular dynamics simulation

During the continuous casting of high-titanium steel, traditional CaO-SiO2-based mold slag undergoes severe slag-metal reactions. Therefore, BaO-CaO-Al2O3-TiO2-Li2O slag system, which has low reactivity, has become a potential new slag system for the continuous casting of high-titanium steel. In this study, a melt of BaO-CaO-Al2O3-TiO2-Li2O is used as the research object. The effects of component changes on the microstructure of the quinary slag system and the evolution of amphoteric oxides are examined by molecular dynamics (MD). The results reveal that the amphoteric behavior of TiO2 is affected by Al2O3 when the content of TiO2 is less than 3 wt%. Whereas the amphoteric behavior of Al2O3 is affected by TiO2 when TiO2 content is more than 3 wt%. NBO/T increases continuously in the low TiO2 system ranging from 1 to 6 wt%. However, in the high TiO2 system ranging from 7 to 12 wt%, NBO/T first increases and then decreases.

Solid–Liquid Phase Equilibria in the Quinary System NaCl-KCl-MgCl2-SrCl2-H2O at 273 K

To realize the comprehensive utilization of underground brines, this work focuses on the research of phase equilibria in salt–water systems containing potassium, sodium, magnesium, strontium, and chlorine. The solid–liquid phase equilibria in the quinary system NaCl-KCl-MgCl2-SrCl2-H2O at 273 K were determined by the isothermal dissolution equilibrium method. X-ray powder diffraction was used to identify the equilibrium solids in invariant points, and the XRD diffraction patterns of equilibrium solids in invariant points were obtained. Based on the experimental data, the three-dimensional equilibrium phase diagram was constructed. The results show that no solid solution is formed in the quinary system, while the double salt KCl·MgCl2·6H2O and corresponding hydrates SrCl2·6H2O and MgCl2·6H2O are formed. The three-dimensional equilibrium phase diagram of this quinary system at 273 K contains two invariant points, seven isothermal solubility curves, and five single salt crystallization regions corresponding to NaCl, KCl, MgCl2·6H2O, SrCl2·6H2O, and KCl·MgCl2·6H2O. In addition, two-dimensional projection phase diagrams with the saturated surfaces of NaCl, KCl, and SrCl2·6H2O were also analyzed, and the dry-salt phase diagrams were also obtained. When NaCl is saturated, there are two invariant points, five univariant curves, and four crystallization regions (KCl, MgCl2·6H2O, SrCl2·6H2O, and KCl·MgCl2·6H2O) in the dry-salt phase diagram. When KCl is saturated, the dry-salt phase diagram consists of only one invariant point, three univariant curves, and three crystallization regions (NaCl, SrCl2·6H2O, and KCl·MgCl2·6H2O). When SrCl2·6H2O is saturated, the dry-salt phase diagram contains two invariant points, five univariant curves, and four crystallization regions corresponding to NaCl, KCl, MgCl2·6H2O, and KCl·MgCl2·6H2O.

Desana numerical symbols

Abstract In 2006, a narrative of the Desana people included a system of graphic symbols reported as a historical Indigenous invention used during intertribal warfare to count the number of enemies and pass warning information. This paper outlines and evaluates the Desana graphic system. The Desana people are described, and their timeline of mythical events is compared to historical accounts of the region. Contemporary Desana spoken numbers are then characterized as a quinary system with a restricted extent that differs significantly from the graphic writing system as presented in the cultural narrative. Implications for the development of writing systems generally and numerical notations specifically are explored. We conclude that the numerical symbols represent cultural diffusion of both European decimal numerals and the idea of writing. However, these were influenced by, synthesized with, and ultimately transformed through their contact with Indigenous cultural practices and concepts, making them an authentic Desana invention.

Machine learning-based inverse design for single-phase high entropy alloys

In this work, we develop an inverse design framework to search for single-phase high entropy alloys (HEAs) subjected to specified phase targets and constraints. This framework is based on the fast grid search in the composition–temperature space, enabled by a highly accurate and efficient machine learning model trained by a huge amount of data. Using the framework, we search through the entire quaternary, quinary, and senary alloy systems, formed by Al, Co, Cr, Cu, Fe, Mn, Ni, and Ti, to identify three types of HEAs: (1) the single-phase FCC HEA with the highest Al content; (2) the single-phase FCC HEA with lower equilibrium temperatures; and (3) single-phase BCC HEAs with Al as the principal element. For the first time, we reveal that the highest Al content in single-phase FCC HEAs is 0.15 in mole fraction, which is higher than the Al contents in all reported single-phase FCC HEAs. The identified HEAs for the quaternary, quinary, and senary groups are Al0.15Co0.34Cr0.16Ni0.35, Al0.15Co0.35Cr0.1Fe0.05Ni0.35, and Al0.15Co0.36Cr0.06Fe0.06Mn0.01Ni0.36, respectively. All the designed HEAs are verified by the equilibrium calculations with Thermo-Calc software and the TCHEA3 database. We further conduct Scheil–Gulliver calculations and experimental fabrications and characterizations for the designed HEAs, to verify the formation of the targeted phases at non-equilibrium conditions. This work demonstrates a viable approach to design HEAs with specified phase targets and constraints.

Composition Engineering on the Local Structure and Viscosity of the CaO-SiO2-Al2O3-P2O5-FeO Slag by Machine Learning Methods

Due to the high cost and low accuracy of high-temperature tests, the viscosity data for multicomponent slag systems is difficult to be obtained precisely. Therefore, it is important to fulfill the viscosity database of the multicomponent slag systems via reasonable methods with lower costs. In this study, a viscosity prediction method based on the machine learning method was proposed for the CaO-SiO2-FeO-Al2O3-P2O5 quinary slag system. To provide valid data for the machine learning model, the viscosity predicted by the molecular dynamic method and multiple semi-empirical models were compared to verify the applicability of these methods to the slag system. Different machine learning models were also developed. The results showed that the prediction results from the gradient boosting decision tree method were the most accurate for the CaO-SiO2-FeO-Al2O3-P2O5 quinary slag system. Based on this method, a color-map concerning the numerical effect of Al2O3 and P2O5 contents and slag viscosity is provided, which also provides assistance for the composition engineering to fulfill a certain demand on the viscosity design.

Selective electrodialysis process for the separation of potassium: Transmembrane transport of ions in multicomponent solution systems

With the development of global agriculture, the demand for potash is growing rapidly. The concentration of K+ in bittern can reach 10 g/L, but the economic benefit of existing extraction methods is still a key concern, and a new extraction method is urgently needed. The monovalent selective electrodialysis was proposed in this study to purify K+. The effects of coexisting ion concentration, voltage, temperature, and ionic strength of dilute solution on the separation of K+ from brine were investigated in ternary system, quaternary system, and quinary system, respectively. Monovalent selective electrodialysis was preliminarily applied to separate K+ from actual bittern. The results showed that monovalent selective electrodialysis can effectively extract K+ and reduce the ratio of Mg2+/K+ from 7.11 to 0.92 with a K+ recovery rate of 74.83%.

Design of super-hard high-entropy ceramics coatings via machine learning

High-entropy ceramic coatings have some unique physical and mechanical properties, such as high hardness, good corrosion resistance and excellent thermal stability. However, since they can contain five or more metal elements, their composition is quite complex. Combined with machine learning and high-throughput experimental methods, ultra-hard high-entropy ceramic coatings were screened in a short period of time. The hardness of coatings is predicted using a random forest algorithm based on its composition and processing parameters. The uncertainty of machine learning prediction is further reduced by active learning. After three iterations, a new high-entropy ceramic coating (AlCrNbTaTi)N with a hardness of 40.1 GPa has been successfully prepared, which is 9% higher than the optimal hardness of the original quinary system. This paper demonstrates that machine learning combined with high-throughput experimental methods can effectively accelerate design and composition optimization of multicomponent materials.