Multicomponent Systems Research Articles

The Aramis Data Challenge to prognostics and health management methods for application in evolving environments

A recurrent difficulty for the effective application of Prognostics and Health Management (PHM) methods is related to the “evolving environments” in which industrial components typically operate. Several factors render the operational environments evolving, including deterioration of components, effects of maintenance activities and changes in working conditions. The issue of evolving environments is even more complicated for multi-component systems, where the degradation of one component can affect the degradation processes of other components, thus modifying their lifetime distributions and the statistical properties of the monitored signals. In an effort to convey research toward practical PHM solutions capable of dealing with evolving environments, the “Aramis challenge on degradation state assessment in evolving environments,” has been launched for the ESREL2020-PSAM15 conference. This work describes the Aramis Data Challenge and associated public dataset, illustrates the methods proposed for its solution and the related results obtained. For the evaluation of the goodness of the fault detection methods, an original metric is introduced, which is a variant of the timeliness metric that has been used in the PHM08 data challenge.

High-throughput evaluation of stress–strain relationships in Ni–Co–Cr ternary systems via indentation testing of diffusion couples

The experimental investigations of multi-component alloy systems require considerable time and effort in terms of sample preparation; in particular, when studying numerous material compositions, the melting, processing, and machining of each specimen at each composition are significantly time- and effort-intensive. To overcome this challenge, the high-throughput evaluation of the stress–strain curves associated with the chemical compositions and microstructures of a Ni–Co–Cr ternary system was performed by estimating the yield stress and tangent modulus via indentation testing. Four diffusion couples (involving the diffusion of Ni and Co) with different nominal Cr contents were prepared, and more than 570 stress-strain curves at the points with different chemical compositions and microstructures were measured. The addition of Cr solute increased the elastic modulus and hardness and decreased the normalized pile-up height, indicating a low strain hardening behavior. The estimated yield stress was strongly dependent on the Cr content, whereas the Co content did not sufficiently affect the strength. Moreover, the effects of crystal orientation on the indentation testing of the face-centered cubic and hexagonal close-packed phases are discussed. The proposed technique can facilitate the evaluation of elastoplastic behavior in multi-component systems in single phase (fcc), which can help achieve the statistical data-driven material development of Ni-based superalloys. • A novel approach for high-throughput evaluation of the stress–strain curves of various multicomponent alloys was proposed. • Stress-strain curves for various chemical compositions can be evaluated>168 times faster than conventional methods. • The optimal design of composition-gradient sample allows to evaluate data sets regarding to solid-solution strengthening. • Huge data of stress-strain curves linked to compositions and microstructure is valuable information for alloy designs.

Machine learning-based model of surface tension of liquid metals: a step in designing multicomponent alloys for additive manufacturing

The surface tension (ST) of metallic alloys is a key property in many processing techniques. Notably, the ST value of liquid metals is crucial in additive manufacturing processes as it has a direct effect on the stability of the melt pool. Although several theoretical models have been proposed to describe the ST, mainly in binary systems, both experimental studies and existing theoretical models focus on simple systems. This study presents a machine learning model based on Gaussian process regression to predict the surface tension of multi-component metallic systems. The model is built and tested on available experimental data from the literature. It is shown that the model accurately predicts the ST value of binaries and ternaries with high precision, and that identifying certain trends in the ST values as a function of alloy composition is possible. The ability of the model to extrapolate to higher-order systems, especially novel concentrated alloys (high entropy alloys, HEA), is discussed.

Zr-based quaternary half-Heusler alloy systems ZrNimX0.5Sb1.5−m (X Fe/In): Studies on phase evolution, crystal structures and electronic properties

Half Heusler(hH) compounds have demonstrated exceptional capability in a wide range of functional applications as semiconductors. Although there are theoretical predictions about newer compounds and their thermodynamic stability, experimental validation is often missing. In this study, we report two quaternary multicomponent Zr-based hH alloy systems, namely ZrNi0.5Fe0.5Sb and ZrNiIn0.5Sb0.5, designed by combining 19 and 17 VEC (valence electron count) alloy systems. The structural features, including the crystal structures and compositions, were established using multiple techniques like X-ray diffraction, scanning and transmission electron microscopy. Both these systems crystallized in signature hH cubic structure (F43̅m) having lattice parameters 0.6091 nm and 0.6104 nm, respectively. The measurement of Seebeck coefficients over a wide temperature range showed p-to n-type semiconductor transition in ZrNi0.5Fe0.5Sb at around 888 K due to bipolar conduction. Subsequently, the partial substitution of Co for Fe sites (ZnNi0.5Fe0.3Co0.2Sb) completely suppressed the bipolar conductivity, making it a n-type semiconductor and increased the absolute value of Seebeck coefficient, by an order of magnitude, to − 133μV/K. The alloy ZrNiIn0.5Sb0.5 showed n-type semiconductor behavior throughout the measurement temperature range. This study conducts an in-depth examination of the microstructural phase evolution, chemical environment of the elements forming the novel hH phase and demonstrates the tunability of electronic properties through aliovalent substitutions at various lattice sites.

Maintenance policy optimization for multi-component systems considering dynamic importance of components

A novel maintenance policy for a multi-component system consisting of an auxiliary and a critical component is presented. The deterioration process of the components is described by the Markov process. Multiple dependence between components and the dynamic importance of components are considered. When the auxiliary component degrades to a certain state, it plays a decisive role in system reliability, and then the maintenance decision is made based on the reliability of the auxiliary component. At this time, if the critical component arrives at the state when preventive maintenance (PM) is demanded, it is repaired opportunistically as well as the auxiliary component. The long-run average cost of the system is derived by the technique of the semi-regenerative process. By minimizing the long-run average cost of the system, the optimal inspection period, the PM threshold of the critical component, and the threshold of the auxiliary component are determined. Finally, the effectiveness of the proposed strategy is illustrated by numerical cases.

Strategic sourcing of multicomponent software systems: The case of electronic medical records

AbstractThe significance of information technology (IT) to organizational performance is increasingly acknowledged by senior executives and scholars alike. However, an important aspect that is underdeveloped in the extant literature is whether and how an organization's IT sourcing strategy affects performance. We examine this dimension in the context of hospitals’ sourcing strategy for electronic medical record (EMR) systems. Leveraging the organization‐IT alignment principle grounded in contingency theory, we argue that the sourcing strategy chosen by hospitals impacts the quality of patient care rendered and that the nature of this relationship has changed over time. Using data on US hospitals that operated continuously from 2006 to 2013 and employing a multilevel longitudinal modeling framework to analyze change over time, we examine how a key dimension of the sourcing strategy for EMR systems—change in closeness to single‐sourcing—impacts conformance quality, a critical measure of hospital performance that assesses how frequently hospitals comply with evidence‐based practices. We find that a change closer to single‐sourcing is positively associated with conformance quality, but this positive effect is reduced over time, meaning that the benefits realized by hospitals using a single‐sourcing approach diminish toward the end of our observation period. As explicated in our discussion of results, findings from our research reveal critical insights about how sourcing decisions impact performance, and how these effects evolve over time due to changes in regulations, technology, and competition.

Nanocrystalline cellulose based on chitosan hydrogel structure as a biological adsorbent for effluent of fish culture farms.

Synthetic hydrogels have been replaced by natural hydrogels due to their properties such as being long-lasting, more capacity for water absorption, high strength, and resistance. Recently, hydrogels have been defined as two- or multi-component systems consisting of three-dimensional networks of polymer chains that fill the space between macromolecules. Their water absorption efficiency depends on both polymeric nature and the capacity of the polymer network connections. Because of climate change and frequent droughts, fresh water supply has become a limiting factor for sustainable aquaculture development in Iran. Therefore, wastewater treatment and reuse can be a reasonable solution to meet the required water for expanding the aquaculture industry. The present study assessed the efficiency of a new hydrogel prepared from sugarcane waste (bagasse) to remove nitrogen and phosphate compounds from the effluent of fish farms. First, the hydrogel was prepared during the polymerization process, and then, in order to determine the optimal absorption, it was tested in a discontinuous system by performing absorption isotherm calculations. In cellulose/chitosan nanocrystalline hydrogel nanosorbent, the removal rates for nitrate, nitrite, and phosphate were 84.3%, 86%, and 90.9%, respectively. Optimal adsorption was determined at acidity of 6, time of 30min, temperature of 40 ℃, concentration of 100mg/L, and adsorbent dose of 0.5g. A comparison of adsorption isotherm models showed more conformity with Freundlich and Tamkin absorption models with correlation coefficients of 0.99 and 0.97 for nitrate, 0.98 and 0.91 for nitrite, and 0.99 and 0.93 for phosphate, respectively.

Manipulation of the spinodal decomposition behavior in a multicomponent system

Spinodal decomposition has been widely studied in binary or ternary material systems but rarely in multicomponent systems. Here we propose a strategy to manipulate the spinodal decomposition behavior in a typical Ti-Zr-C-N-Ni cermet system based on the Gibbs free energy and its second derivative of Fcc-(Ti, Zr)(C, N) phase. The impact of constituents and temperature on miscibility gap and spinodal decomposition was visualized. Interestingly, Ni impeded the spinodal decomposition of this system, while N had a complex effect. Furthermore, a subtle increase in Ni content (by 0.5 at.%) counteracted the effect of 20 at.% N addition at 1500 °C. The calculated results are further supported by the microstructure analysis of (Ti, Zr)(C, N)-Ni samples. The adopted strategy presented herein enables the optimization of cermet constituents and heat-treated temperature to manipulate the spinodal decomposition behavior for designing high-performance multicomponent materials.

Weighted-QMIX-based Optimization for Maintenance Decision-making of Multi-component Systems

It is well-known that maintenance decision optimization for multi-component systems faces the curse of dimensionality. Specifically, the number of decision variables needed to be optimized grows exponentially in the number of components causing computational expensive for optimization algorithms. To address this issue, we customize a multi-agent deep reinforcement learning algorithm, namely Weighted QMIX, in the case where system states can be fully observed to obtain cost-effective policies. A case study is conducted on a 13- component system to examine the effectiveness of the customized algorithm. The obtained results confirmed its performance.

Artificial-Intelligence-Based Maintenance Scheduling for Complex Systems with Multiple Dependencies

Maintenance planning for complex systems has still been a challenging problem. Firstly, integrating multiple dependency types into maintenance models makes them more realistic, however, more complicated to solve and analyze. Secondly, the number of maintenance decision variables needed to be optimized increases rapidly in the number of components, causing computational expensive for optimization algorithms. To face these issues, this thesis aims to incorporate multiple kinds of dependencies into maintenance models as well as to take advantage of recent advances in artificial intelligence field to effectively optimize maintenance polices for large-scale multi-component systems.

Transport Behavior of Cu2+ Under Binary and Multi-Component Systems in the Columns of Polyaluminium Chloride and Anionic Polyacrylamide Water Treatment Residuals: Implication for Reuse in Stormwater Bioretention Systems

Transport Behavior of Cu2+ Under Binary and Multi-Component Systems in the Columns of Polyaluminium Chloride and Anionic Polyacrylamide Water Treatment Residuals: Implication for Reuse in Stormwater Bioretention Systems

Approaches for handling high-dimensional cluster expansions of ionic systems

Disordered multicomponent systems attract great interest due to their engineering design flexibility and subsequent rich space of properties. However, detailed characterization of the structure and atomic correlations remains challenging and hinders full navigation of these complex spaces. A lattice cluster expansion is one tool to obtain configurational and energetic resolution. While in theory a cluster expansion can be applied to any system of any dimensionality, the method has primarily been used in binary systems or ternary alloys. Here we apply cluster expansions in high-component ionic systems, setting up the largest cluster expansion ever attempted to our knowledge. In doing so, we address and discuss challenges specific to high-component ionic systems, namely charge state assignments, structural relaxations, and rank-deficient systems. We introduce practical procedures to make the fitting and analysis of complex systems tractable, providing guidance for future computational studies of disordered ionic systems.

Environmental application of Saccharum munja biomass-derived hybrid composite for the simultaneous removal of cationic and anionic dyes and remediation of dye polluted water: A step towards pilot-scale studies

Herein, a novel formulation comprising of two composites: Saccharum munja biomass-functionalized carbon nanotubes (SM/CNT) and cetyltrimethylammonium bromide modified SM/CNT (SM/CNT/CTAB), was prepared and its physicochemical properties were analysed. The two composites were mixed in different ratios and investigated for the simultaneous removal of two cationic and two anionic dyes at neutral pH and the maximum removal of both types of dye were obtained with a ratio of 1:2. Further, the optimization of experimental parameters (pH, dosage and concentration) was carried out with response surface methodology (RSM). An in-depth evaluation of adsorptive interactions occurring between Malachite green (MG), Crystal Violet (CV), Congo Red (CR) and Acid Blue 93 (AB) dyes under the single, binary, ternary and quaternary systems were investigated for the first time. The maximum monolayer adsorption capacity evaluated from the Langmuir adsorption isotherm was found to be 177.62, 180.51, 193.42 and 235.29 mg/g for MG, CV, CR and AB dyes respectively. The adsorption process followed pseudo-second-order kinetics, while the thermodynamic studies revealed the spontaneous nature of adsorption for all the four dyes. However, the process was found to be exothermic in the case of CR and AB dyes while endothermic for MG and CV dyes. Interestingly, a significant increase in the adsorption capacity of the hybrid biosorbent was observed for the elimination of dyes from multi-component systems owing to the synergistic effect occurring between dyes through adsorbate-adsorbate and adsorbent-adsorbate interactions. Moreover, the hybrid composite was explored for the treatment of two dyeing effluents comprising multiple dyes and removed 95.56% and 97.34% of dyes with a dosage of 0.03 g/10 mL within 10 min. Overall, the results indicated the excellent potential of the novel formulation for treating dye-contaminated effluents in an expeditious, efficient and economical manner.

Modifikasi Kitosan sebagai Komposit Biopolimer untuk Pemisahan Pb(II) dan Cd(II) secara Simultan pada Sistem Multikomponen

Biopolymers are known to be abundant and have low toxicity. The use of biopolymers as adsorbent materials in line with the current needs for cheap, environmentally friendly, and high-efficiency adsorbents. The physicochemical properties of biopolymers based on polysaccharide like chitosan as adsorbents can still be explored. This article was written using a systemmatic review conducted by collecting scientific journals from the last ten years related to the use of chitosan for simultaneous analyte separation. According to the systemmatic review, nanoparticles, magnetic particles, inorganic natural materials, and other materials are used to strengthen the robustness and adsorption of chitosan. The chitosan composite used to separate Pb(II) and Cd(II) simultaneously in a multicomponent system showed that other ions in the binary, tertiary, and quaternary systems decreased the adsorption capacity. Adsorption in multicomponent systems is more antagonistic than non-interactional and synergistic. In a multicomponent system, the selectivity of modified chitosan for Pb(II) and Cd(II) ions is determined by the material used for chitosan modification and metal ion properties such as radius and electronegativity. Due to the abundance of chitosan and the increasing amount of industrial wastewater containing heavy metals, modified chitosan for multi-metal adsorption has the potential to be developed in Indonesia.

Mechanism adsorption analysis during the removal of Cd2+ and Cu2+ onto cedar sawdust via experiment coupled with theoretical calculation: Mono- and multicomponent systems

In this work, a deeper comprehension of the adsorption phenomena for Cd2+ and Cu2+ occurring in mono- and multicomponent systems on an adsorbent material obtained from cedar sawdust was accomplished by using spectroscopic characterization, and computational tools. The adsorbents were prepared by a simple calcination process at 300, 400, and 500 °C or pyrolysis at 300 °C. The experimental results showed that the adsorption capacity of the CS-C-400 adsorbent is higher for Cd2+ (36 mg g−1) than Cu2+ (15 mg g−1) ions in monocomponent systems (50 mg of adsorbent, 50 mL of solution, pH = 5, 25 °C, 200 rpm, and 72 h). In contrast, the trend for the adsorption capacity was Cu2+ > Cd2+ in most of the concentrations for multicomponent systems, due to that Cu2+ showed greater antagonism to Cd2+ during the competitive adsorption (qCd2+ was 96 % reduced). Computational results correlated well with the experimental ones and evidenced the occurrence of complexation interactions between metal ions and the surface oxygenated functional groups (hydroxyl, carboxyl, ester, and ether) onto the adsorbent surface, as was also proposed through spectroscopy results. Computational and experimental results indicate that Cd2+ and Cu2+ adsorption on the adsorbent surface is governed by the occurrence of complexation, and π-cation interaction for both ions, while ionic exchange plays a significant role in Cd2+ adsorption.

Microfluidics approach for determination of the equilibrium phase composition in multicomponent biphasic liquid systems

Based on the fundamentals of microfluidics, a novel approach for the determination of liquid-liquid equilibria (LLE) of ternary systems was proposed. The system studied here consists of the compounds water, acetone, and toluene. This method was realized in a microfluidic set-up that consists of a microchannel, a camera for the determination of the position of the phase interface, and a micro density meter for measuring the densities of the conjugated phases at the outlet of the microchip. To determine the equilibrium phase compositions, an optimization problem was defined that minimized the difference between the experimentally determined and calculated ratio of the volumetric flow rates of the conjugated phases. The developed procedure uses information on the position of the phase interface in the microchannel and the phase densities, and requires previous knowledge of the binodal curve, which as shown in our previous work (Hübner and Minceva, 2019) can be also determined using the same set-up. The obtained equilibrium phase compositions were in good agreement with literature data. Eventually, once the procedure is automatized to reduce the required measuring time and achieve full user independency, the proposed approach poses a cheap and fast alternative to conventional methods for measuring LLE.

Phase equilibrium in binary La2O3-Dy2O3 and ternary CeO2-La2O3-Dy2O3 systems

Cerium oxide doped with oxides of rare earth elements is a multifunctional material, a wide range of uses which is associated with its unique physicochemical properties. Phase diagrams of multicomponent systems are the physicochemical basis for the creation of new materials with improved characteristics.In this work, phase equilibria in ternary CeO2–La2O3–Dy2O3 and binary La2O3–Dy2O3 systems in the whole concentration range were studied. No new phases have been identified in these systems. An isothermal section of the phase diagram of the CeO2–La2O3–Dy2O3 system at a temperature of 1500 °С is constructed. No new phases have been detected in the system. It was found that in the studied ternary system solid solutions are formed on the basis of (F) modification of CeO2 with structure of fluorite type, monoclinic (B), cubic (C) and hexagonal (A) modifications of Ln2O3.In the La2O3–Dy2O3 binary system (1500–1100 °С) three types of solid solutions are formed: based on hexagonal modification A-La2O3, monoclinic modification B-Dy2O3 and cubic modification C-Dy2O3 separated by two-phase fields (A+B) and (B+C), respectively. The boundaries of the regions of homogeneity of solid solutions based on A-La2O3 are determined by compositions containing 35–40, 20–25, 15–20 mol% Dy2O3 at 1500, 1250, 1100 °C, respectively. From the obtained data it follows that the solubility of Dy2O3 in the hexagonal modification of lanthanum oxide is 39 mol% at 1500 °C, 23 mol. % at 1250 °C and 16 mol% at 1100 °C. The limits of existence of solid solutions based on monoclinic B-modification are determined by compositions containing 30–35, 65–60 (1250 °С), 35–40, 55–60 (1100 °С) 40–45, 70–75 (1500 °C) mol% Dy2O3.In the studied system, with a decrease in temperature from 1500° to 1100°C, there is a decrease in the solubility of La2O3 in the crystal lattice of cubic solid solutions of C-type from 16 to 10 mol%.

Efficient Screening of Coformers for Active Pharmaceutical Ingredient Cocrystallization.

Controlling the physical properties of solid forms for active pharmaceutical ingredients (APIs) through cocrystallization is an important part of drug product development. However, it is difficult to know a priori which coformers will form cocrystals with a given API, and the current state-of-the-art for cocrystal discovery involves an expensive, time-consuming, and, at the early stages of pharmaceutical development, API material-limited experimental screen. We propose a systematic, high-throughput computational approach primarily aimed at identifying API/coformer pairs that are unlikely to lead to experimentally observable cocrystals and can therefore be eliminated with only a brief experimental check, from any experimental investigation. On the basis of a well-established crystal structure prediction (CSP) methodology, the proposed approach derives its efficiency by not requiring any expensive quantum mechanical calculations beyond those already performed for the CSP investigation of the neat API itself. The approach and assumptions are tested through a computational investigation on 30 potential 1:1 multicomponent systems (cocrystals and solvate) involving 3 active pharmaceutical ingredients and 9 coformers and one solvent. This is complemented with a detailed experimental investigation of all 30 pairs, which led to the discovery of five new cocrystals (three API–coformer combinations, a polymorphic cocrystal example, and one with different stoichiometries) and a cis-aconitic acid polymorph. The computational approach indicates that, for some APIs, a significant proportion of all potential API/coformer pairs could be investigated with only a brief experimental check, thereby saving considerable experimental effort.

Femtosecond Laser Densification of Hydrogels to Generate Customized Volume Diffractive Gratings.

Inspired by nature’s ability to shape soft biological materials to exhibit a range of optical functionalities, we report femtosecond (fs) laser-induced densification as a new method to generate volume or subsurface diffractive gratings within ordinary hydrogel materials. We characterize the processing range in terms of fs laser power, speed, and penetration depths for achieving densification within poly(ethylene glycol) diacrylate (PEGDA) hydrogel and characterize the associated change in local refractive index (RI). The RI change facilitates the fabrication of custom volume gratings (parallel line, grid, square, and ring gratings) within PEGDA. To demonstrate this method’s broad applicability, fs laser densification was used to generate line gratings within the phenylboronic acid (PBA) hydrogel, which is known to be responsive to changes in pH. In the future, this technique can be used to convert ordinary hydrogels into multicomponent biophotonic systems.

The Multicomponent Higher-Order Chen–Lee–Liu System: The Riemann–Hilbert Problem and Its N-Soliton Solution

It is well known that multicomponent integrable systems provide a method for analyzing phenomena with numerous interactions, due to the interactions between their different components. In this paper, we derive the multicomponent higher-order Chen–Lee–Liu (mHOCLL) system through the zero-curvature equation and recursive operators. Then, we apply the trace identity to obtain the bi-Hamiltonian structure of mHOCLL system, which certifies that the constructed system is integrable. Considering the spectral problem of the Lax pair, a related Riemann–Hilbert (RH) problem of this integrable system is naturally constructed with zero background, and the symmetry of this spectral problem is given. On the one hand, the explicit expression for the mHOCLL solution is not available when the RH problem is regular. However, according to the formal solution obtained using the Plemelj formula, the long-time asymptotic state of the mHOCLL solution can be obtained. On the other hand, the N-soliton solutions can be explicitly gained when the scattering problem is reflectionless, and its long-time behavior can still be discussed. Finally, the determinant form of the N-soliton solution is given, and one-, two-, and three-soliton solutions as specific examples are shown via the figures.