Chemical Short-range Order Research Articles

Unravelling the components of diffuse scattering using deep learning.

Many technologically important material properties are underpinned by disorder and short-range structural correlations; therefore, elucidating structure-property relationships in functional materials requires understanding both the average and the local structures. The latter information is contained within diffuse scattering but is challenging to exploit, particularly in single-crystal systems. Separation of the diffuse scattering into its constituent components can greatly simplify analysis and allows for quantitative parameters describing the disorder to be extracted directly. Here, a deep-learning method, DSFU-Net, is presented based on the Pix2Pix generative adversarial network, which takes a plane of diffuse scattering as input and factorizes it into the contributions from the molecular form factor and the chemical short-range order. DSFU-Net was trained on 198 421 samples of simulated diffuse scattering data and performed extremely well on the unseen simulated validation dataset in this work. On a real experimental example, DSFU-Net successfully reproduced the two components with a quality sufficient to distinguish between similar structural models based on the form factor and to refine short-range-order parameters, achieving values comparable to other established methods. This new approach could streamline the analysis of diffuse scattering as it requires minimal prior knowledge of the system, allows access to both components in seconds and is able to compensate for small regions with missing data. DSFU-Net is freely available for use and represents a first step towards an automated workflow for the analysis of single-crystal diffuse scattering.

Influence of long- and short-range chemical order on spontaneous magnetization in single-crystalline Fe0.6Al0.4 compound thin films

We systematically investigate the long- and short-range chemical order, lattice volume, and spontaneous magnetization in single-crystalline Fe0.6Al0.4 compound thin films. The vapor-quenching method based on a molecular beam epitaxy technique is utilized to fabricate the single-crystalline Fe0.6Al0.4 compound with the different B2 long-range order parameter S. S was varied by the deposition temperature T d, and it increases with increasing T d. The lattice volume V decreased with increasing T d, while the tetragonal distortion, ∼4%, due to epitaxial strain were observed. The changes in S and V were accompanied with the change in the magnetic moment per Fe, μ Fe. μ Fe showed the monotonic decrease as a function of S whereas μ Fe monotonically increases with V. With considering tetragonal distortion, μ Fe–V relationship has a good agreement with the previous reports. The μ Fe–S relationship showed the steep decrease of μ Fe around S∼ 0.6. In contrast to μ Fe–V relationship, μ Fe–S relationship does not match only from ours to previous studies but also among other reports. It implies the statistical number of the nearest-neighbor Fe–Fe bonds, i.e. S, cannot be an enough explanatory parameter. To clarify the structural origin of change in μ Fe, the short-range order (SRO) parameter inferred from the analysis of superlattice diffractions were introduced. They showed the clear difference for the films with high and low μ Fe. The results suggest that the transition from the long- to the SRO state plays the significant role on μ Fe.

Element-configuration dependent first-principles machine learning studies of multiple alloying effects on the structure stability of Co3(Al, W)

Multiple alloying is desired to improve the stability of metastable Co3(Al, W) of Co-based superalloys. However, computational studies of alloying effects are costly due to the enormous combinations of compositions and configurations. Most current element-based machine learning methods that rely solely on composition lack the ability to distinguish between polymorph materials and various local alloying configurations. In this work, we developed efficient machine learning (ML) models using element-configuration dependent Center-Environment (CE) and element-based Chemical Composition (CC) features to describe alloying element type and substitution configuration, crucial for data-driven study of correlated alloying effects and local short-range chemical ordering. We employed first-principles computation and ML methods to investigate the structure stabilities of the Al-W substitution site models with 3d and 4d transition metal (TM) elements, then the optimized ML models were validated using the untrained dual-Al or dual-W site configurations with 3d, 4d, and 5d TM elements. The ML-CE models were generally more accurate than the ML-CC models. The most stable substitution pairs are Sc-Fe 3d TM elements at the Al-W and dual-W sites with lattice constant ∼4 Å. Therefore, we propose a “Co-left” design rule to stabilize Co3(Al, W) by multiple alloying with early 3d TM elements (IIIB-VIII group). The stabilizing 3d “Co-left” elements also can improve the mechanical properties. The ML-CE approach can be generally applied to study local correlated alloying effects and chemical ordering in medium/high-entropy or amorphous alloys.

Three-dimensional atomic structure and local chemical order of medium- and high-entropy nanoalloys.

Medium- and high-entropy alloys (M/HEAs) mix several principal elements with near-equiatomic composition and represent a model-shift strategy for designing previously unknown materials in metallurgy1-8, catalysis9-14 and other fields15-18. One of the core hypotheses of M/HEAs is lattice distortion5,19,20, which has been investigated by different numerical and experimental techniques21-26. However, determining the three-dimensional (3D) lattice distortion in M/HEAs remains a challenge. Moreover, the presumed random elemental mixing in M/HEAs has been questioned by X-ray and neutron studies27, atomistic simulations28-30, energy dispersive spectroscopy31,32 and electron diffraction33,34, which suggest the existence of local chemical order in M/HEAs. However, direct experimental observation of the 3D local chemical order has been difficult because energy dispersive spectroscopy integrates the composition of atomic columns along the zone axes7,32,34 and diffuse electron reflections may originate from planar defects instead of local chemical order35. Here we determine the 3D atomic positions of M/HEA nanoparticles using atomic electron tomography36 and quantitatively characterize the local lattice distortion, strain tensor, twin boundaries, dislocation cores and chemical short-range order (CSRO). We find that the high-entropy alloys have larger local lattice distortion and more heterogeneous strain than the medium-entropy alloys and that strain is correlated to CSRO. We also observe CSRO-mediated twinning in the medium-entropy alloys, that is, twinning occurs in energetically unfavoured CSRO regions but not in energetically favoured CSRO ones, which represents,to our knowledge, the first experimental observation of correlating local chemical order with structural defects in any material. We expect that this work will not only expand our fundamental understanding of this important class of materials but also provide the foundation for tailoring M/HEA properties through engineering lattice distortion and local chemical order.

Effect of chemical short-range ordering on thermodynamics, structure, and dynamics of ZrCu-based metallic glass-forming liquids

Chemical-ordering in metallic liquid alloys affects important structural, thermodynamic, and dynamical factors governing the kinetics of the glass formation process and the glass-forming ability. The present study on Zr50Cu50, Zr50Cu45Al5, and Zr50Cu45Ag5 metallic glass-forming liquids reveal that minor addition of Al/Ag in Zr50Cu50 leads to different chemical short-range orders due to the hetero-coordination tendency of Al in Zr50Cu45Al5 and homo-coordination tendency of Ag in Zr50Cu45Ag5. Different chemical short-range ordering causes qualitatively different topological short-range orders in the two ternary alloys. Results of inherent structure energy and excess entropy indicate modification of the potential energy landscape such that the local minima (metabasins) on the landscape of Zr50Cu45Al5 become deeper and less rugged, whereas the metabasins become shallower and more rugged in Zr50Cu45Ag5. Single-particle dynamics investigations clearly demonstrate the effect of difference in the chemical-ordering, topological short-range order, and the potential energy landscape on the atomic diffusion, structural relaxation, and dynamic heterogeneities in the ternary alloys. It signifies that the dynamics of the studied glass-forming alloys is closely linked with the structure and thermodynamics. The study also provides a very useful insight of the correlation between the chemical-ordering and the short-time dynamical features in the studied metallic glass-forming liquids.

The influence of chemical short-range order on the nanoindentation properties of high-entropy alloys prepared via laser powder bed fusion

Chemical short-range order (CSRO) plays an instrumental role in determining the mechanical properties of high-entropy alloys (HEAs). Current methods for controlling CSRO mainly focus on cast HEAs, which can not solve the problem of grain coarsening caused by homogenization treatments. Laser Powder Bed Fusion (LPBF), which has extremely high cooling rates, can suppress compositional segregation, refine grain structures, and achieve low CSRO. This offers a promising avenue for quantitatively controlling CSRO without the need for homogenization treatments. In this study, we investigate the CSRO of HEAs fabricated via LPBF and elucidate their influence on nanoindentation behavior. The results show that, at the low cooling rate, the average size of CSRO is 0.66 nm and they occupy 2.8% of the cross-sectional area, while at high cooling rate, the corresponding values are 0.92 nm and 9.9%, respectively, both of which are significantly smaller than those of cast HEAs. By analyzing samples with different CSROs, we observe that the hardness increases and then decreases with the increase of CSRO, primarily due to the preferential formation of dislocations in regions enriched with Cr-Mn-Ni. With the improvement of CSRO, both the size and quantity of Cr-Mn-Ni rich region gradually increased; subsequently, as multiple Cr-Mn-Ni rich regions tend to merge into one during the CSRO improvement, the size of the Cr-Mn-Ni rich region continued to increase while the quantity gradually decreased; when the size of the Cr-Mn-Ni rich region is moderate and widely dispersed, the dislocation density is higher with much more uniform distributions, which favorably improves nanoindentation hardness.

Impacts of chemical short-range orders on nanotribological properties of CrCoNi medium-entropy alloy at room and cryogenic temperatures

Presence of chemical short-range orders (SROs) had a great impact on the property-structure relationships of high/medium-entropy alloys (H/MEAs), but its influence on the tribological performance of H/MEAs has never been reported. This study provides an understanding on the chemical SRO degree dependent nanoscratching response of CrCoNi MEA by hybrid Monte-Carlo and molecular dynamic simulations. Friction coefficient, wear rate, worn surface morphology, phase stability and dislocation activities have been systematically investigated considering different load mode and temperature conditions. CrCoNi MEA exhibited superior nanotribological properties at cryogenic temperature than room temperature. Increasing chemical SRO degree is found to be effective in reducing friction and improving wear resistance and phase stability, regardless of nanoscratching conditions.

A novel criterion for predicting the glass-forming ability in Zr–Cu–Al ternary alloys: A molecular dynamics study

The molecular dynamics simulation is used to investigate the correlation between the atomic scale structure and glass-forming ability (GFA) of the ternary (Zr0.5Cu0.5)100-xAlx (x = 2, 4, 6, 8, 10, 12) bulk metallic glasses. Different techniques, like the Voronoi tessellation, are exploited to quantify this system's topological and chemical short-range ordering. It is found that the potential energy and the virial stress energy density of the icosahedra reveal the geometrical and chemical ordering in this system, respectively. Accordingly, a new GFA prediction criterion is presented, and the criterion's feasibility is demonstrated for various compositions by comparing the predicted and experimental data. It is found that Zr46Cu46Al8, Zr70Cu20Al10, and Zr40Cu10Al50 alloys are the optimal compounds with respect to GFA.

Deep machine learning, molecular dynamics and experimental studies of liquid Al-Cu-Co alloys

Understanding the correlations between liquids and solids opens the way to predict by investigating liquids, the domains of thermodynamic parameters favoring intriguing solid phases. This approach is especially urgent for the design of multicomponent systems working with a continuous array of component concentrations (most modern materials of practical interest are multicomponent). Here we address an Al-Cu-Co system experimentally and theoretically using molecular dynamics and machine learning interaction potentials on top of the first-principles training data in a composition range of 15 at.% Co and 10 to 30 at.% Cu, and 25 at.% Cu and 2.5 to 20 at.% Co. The selected concentration sections contain different high-temperature solid phases. Differential thermal analysis has uncovered the features of solid phase formation at slow cooling and normal pressure. The boundaries of different phase regions correlate with the extrema on the one hand in undercooling and on the other hand in viscosity in the concentration area. The theoretical calculations have uncovered the correlations between the extrema and the readjustment of the chemical short-range order in the liquid, with the nonmonotonicity of the concentration dependence of the glass transition temperature and the specific volume.

Abnormal strain-hardening in Co-rich CoNiV medium-entropy alloys

Two new nonequiatomic Co70Ni20V10 and Co65Ni20V15 medium entropy alloys were designed to investigate the synergistic strengthening effects of the dislocation slip, hexagonal close-packed (HCP) martensitic transformation, chemical short-range order (CSRO), and chemical medium-range order (CMRO), using X-ray diffraction, backscattered electron, electron channeling contrast imaging, electron backscattered diffraction, and transmission electron microscope. The results showed the Co65Ni20V15 alloy presented an abnormally higher strain-hardening rate than the Co70Ni20V10 alloy in the range of 5∼30 % strain, although the Co70Ni20V10 alloy possessed higher dislocation density with extra HCP martensitic transformation strengthening. This abnormality could be attributed to the profound CSRO and CMRO strengthening in the Co65Ni20V15 alloy with more large-sized V atoms, which was evidently observed by a high-resolution transmission electron microscope. It is expected that the strength of the CoNiV medium entropy alloys could be further enhanced via synthetically tuning the CSRO and CMRO effects, together with other strengthening mechanisms.

Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography

Chemical short-range order (CSRO) refers to atoms of specific elements self-organising within a disordered crystalline matrix to form particular atomic neighbourhoods. CSRO is typically characterized indirectly, using volume-averaged or through projection microscopy techniques that fail to capture the three-dimensional atomistic architectures. Here, we present a machine-learning enhanced approach to break the inherent resolution limits of atom probe tomography enabling three-dimensional imaging of multiple CSROs. We showcase our approach by addressing a long-standing question encountered in body-centred-cubic Fe-Al alloys that see anomalous property changes upon heat treatment. We use it to evidence non-statistical B2-CSRO instead of the generally-expected D03-CSRO. We introduce quantitative correlations among annealing temperature, CSRO, and nano-hardness and electrical resistivity. Our approach is further validated on modified D03-CSRO detected in Fe-Ga. The proposed strategy can be generally employed to investigate short/medium/long-range ordering phenomena in different materials and help design future high-performance materials.

Mechanism of elemental segregation around extended defects in high-entropy alloys and its effect on mechanical properties

Elemental segregation around extended defects is common in high-entropy alloys (HEAs) composed of multi-principal elements, which profoundly impacts their mechanical properties. In HEAs, the driving force for segregation usually competes with chemical short-range ordering (CSRO) formation, making it challenging to elucidate the segregation mechanisms. In this study, we systematically investigate the chemical composition changes around extended defects, including dislocations, stacking faults, and grain boundaries (GBs) in CoNiCrFe HEAs, to explore the chemical-structure-mechanical relationship utilizing hybrid Monte Carlo and molecular dynamic (MC/MD) simulations and theoretical analysis. We find a pronounced Cr enrichment and Co/Ni/Fe depletion around all defects considered in this work. A correlation between the degree of structural disorder and the chemical segregation/depletion phenomenon in the proximity of extended defects has been uncovered. Our results show that due to the extreme chemical complexity in HEAs, CSRO inevitably contributes to the elemental rearrangement and affects segregation. Consequently, the segregation behavior in HEAs is mainly controlled by interactions between different atomic pairs, and the segregation entropy also plays a dominant role. By decoupling the strengthening contribution from elemental segregation and CSRO, we demonstrate and highlight that the strengthening in HEAs can be modulated by elemental segregation. The positive impact of element segregation on interfacial properties - improved ultimate tensile strength and elongation, has been evidenced through experimental comparisons of CoNiCrFe with different Fe additions. This work elucidates the mechanism of heterogenous elemental distributions in HEAs where elemental segregation and CSRO coexist, paving the way for manipulating their mechanical properties by modulating the compositional variations.

Relationship among intrinsic magnetic parameters and structure and crucial effect of metastable Fe3B phase in Fe-metalloid amorphous alloys

The intrinsic heterogeneity of an amorphous structure originates from composition, and the structure determines the magnetic properties and crystallization models of amorphous magnets. Based on classical Fe–B binary magnetic amorphous alloys, the relationship between the structure and magnetic properties was extensively studied. The stacking structure of Fe–B binary amorphous alloys exhibit discontinuous changes within the range of 74–87 at.% Fe. The structural feature can be expressed as Amor. Fe3B matrix + Fe atoms are transforming into Amor. Fe matrix + B atoms with the increase of Fe content. The solute atoms are uniformly distributed in the amorphous matrix holes, similar to a single-phase solid solution structure. The transition point corresponds to the eutectic crystallization model composition (Fe82B18 to Fe83B17). A high Fe content will amplify magnetic moment sensitivity to temperature. Under a given service temperature, the disturbance effect of magnetic moment self-spinning will offset the beneficial effect of increasing Fe content and induce the saturation magnetization (Ms) value to decrease. Binary amorphous Fe–B alloys obtain the maximum Curie temperature near 75 at.% Fe, which is slightly smaller than that of the corresponding metastable Fe3B phase, i.e., the amorphous short-range order structure maintains the highest similarity to the Fe3B phase. The chemical short-range ordering (SRO) structure of amorphous alloys exhibits heredity to corresponding (meta)stable crystal phases. The unique spatial orientation structure of the metastable Fe3B phase is the structural origin of the amorphous nature. This study can guide the composition design of Fe-metalloid magnetic amorphous alloys. The design of materials with excellent magnetic properties originates from a deep understanding of precise composition control and temperature disturbance mechanism.

Stimulating the amorphous structure of Fe56Co24Nb4B13Si2Cu1 ferromagnetic alloy by thermal annealing, laser and electron beam irradiation: A Mӧssbauer spectroscopy investigation

This study presents a Mӧssbauer spectroscopy investigation of the Fe56Co24Nb4B13Si2Cu1 amorphous ferromagnetic alloy in the as-quenched state and after thermal annealing, laser and electron beam irradiation. Thermal treatment at temperatures of 450–750° C caused nano, partial and complete crystallization of the alloy system. Crystalline phases such as α-(FeCo), (FeCo)2(BSi) and (FeCo)3(BSi) were identified in the thermally annealed specimens. By analyzing the hyperfine magnetic field distributions, it was shown that continuous wave (cw) CO2 laser irradiation of fresh samples determined a more pronounced in-plane orientation of magnetic moment directions and caused changes in the chemical short-range order in the system with non-zero magnetostriction. For direct comparison, atomic rearrangements were not observed in the Fe68.5Co5Nb3Cu1Si15.5B7 ferromagnetic alloy having a zero magnetostriction constant. Unlike the case of laser annealing, irradiation with 11 GeV electrons of the Fe56Co24Nb4B13Si2Cu1 alloy determined a pronounced out-of-plane magnetic anisotropy and supported the formation of stress centers in the irradiated system. Both laser and electron beam irradiation were found to essentially preserve the amorphous phase of the processed alloy.

Aging elevates chemical short-range order and twinning stress in a CrCoNi medium-entropy alloy

Aging elevates chemical short-range order and twinning stress in a CrCoNi medium-entropy alloy

The design of Pd-containing high-entropy alloys and their hardening behavior under He ion irradiation

Imparting additional chemical heterogeneities of high-entropy alloys (HEAs) is considered as a novel strategy to improve their irradiation resistance on dislocation loop growth; however, there is still a lack of knowledge about the effects of this strategy on bubble evolution and irradiation-induced hardening. In this study, a series of Pd-containing FeCrNiCo HEAs with proven potential for chemical short-range order were designed and irradiated by 400 keV He ions to the fluences of 5 × 1016 cm−2, 1 × 1017 cm−2, and 5 × 1017 cm−2 at 723 K. Microscopic characterization demonstrates a remarkably inhibited growth of dislocation loops and promoted bubble coarsening in the Pd-containing HEAs compared to the HEA without Pd alloying. The underlying mechanism is that although the alloying of Pd can suppress the evolution of dislocation loops through severe local lattice distortion, it also significantly reduces the vacancy formation energy of the entire HEA system, leading to the encouraged bubble evolution. Pd-containing HEAs exhibit improved resistance to irradiation-induced hardening at low doses, but this advantage is unexpectedly absent with increasing dose. The hardening mechanism is explained by identifying the loop-dominated hardening at low dose and the bubble-induced hardening which makes an increased contribution at high dose. In addition, the Ni segregation around bubbles and loop punching mechanism are also discussed to provide essential evidence. These insights can help to shed light on the effects of Pd alloying on bubble evolution and irradiation-induced hardening behavior in HEAs, and thus contribute to the design of irradiation-resistant HEAs.

Formation of Chemical Short-Range Order in Equiatomic CoNiCrFeMn High-Entropy Alloy. Atomistic MD/MC Simulation

Abstract—The formation of short-range order in the equiatomic high-entropy alloy (HEA) CoNiCrFeMn during annealing at moderate temperatures was studied using atomistic MD/MC simulation, including the exchange of atoms in the Monte Carlo (MC) scheme and the relaxation of its positions by the molecular dynamics (MD) method. It has been found that two types of chemical short range order (CSRO) regions are formed during annealing. One of them consist mainly of Fe and Co atoms, while others are enriched by Cr with Ni and Mn atoms at their boundaries. It is shown that the formation of short-range order includes several stages, the sequence of which is determined by the value of Cr–Cr, Fe–Co and Ni–Mn interatomic interactions.

Investigation of chemical short range order strengthening in a model Fe–12Ni–18Cr (at. %) stainless steel alloy: A modeling and experimental study

Solid solution strengthening remains the basis for many industrial alloys, yet chemical short-range order (CSRO) can also play a significant role in the strengthening of alloys with appreciable alloying additions, such as in Austenitic stainless steels. In this work, we study the evolution of CSRO under various annealing temperatures and its role on the mechanical strength of a ternary Fe–12Ni–18Cr (at.%) alloy using molecular dynamics (MD) and Monte Carlo atomistic simulations and experimental measurements from mechanical microindentation and atom-probe tomography (APT). A general model that incorporates the role of CSRO into a solute–solution strengthening model is proposed, based on a family of analytical models due to Varvenne et al. (2016) which takes into account dislocation-solute misfit interaction, and a more recent extension due to Nag and Curtin (2020) which incorporates the role of solute–solute interactions during dislocation slip. Predictions of the modified model are validated against MD shearing simulations using two commonly used embedded atom model (EAM) interatomic potentials for Austenitic stainless steel alloys, and mechanical microindentation experiments on cast alloys of the same composition. Our results suggest that, while significant CSRO is predicted in the simulations, there is little experimental evidence in cast and annealed alloys analyzed by APT.

Unexpected sluggish martensitic transformation in a strong and super-ductile high-entropy alloy of ultralow stacking fault energy

Displacive martensitic transformation usually prevails in face-centered cubic (FCC) steels and high-entropy alloys (HEAs) of low stacking fault energy (SFE; e.g., <15 mJ/m2) upon deformation. Here, we present and rationalize an unexpectedly sluggish and suppressed martensitic transformation behavior in a newly developed non-equiatomic HEA (Fe30Ni20Co20Cr20Si10, at.%) with an ultralow SFE, i.e., ∼7 mJ/m2 measured by weak-beam dark-field scanning transmission electron microscopy (STEM) at room temperature. The recrystallized FCC HEA with an average grain size of ∼14.9 µm shows an ultimate tensile strength of 903 MPa and a fracture elongation of ∼83.1 %. Plastic deformation of this alloy with ultralow SFE is characterized by the intensive formation of stacking faults (SFs), whereas the volume fraction of hexagonal close-packed (HCP) martensite is very low even at cold-rolled state with an equivalent strain of 1.85, i.e., < 8.3 % according to neutron diffraction analysis. Atomic-scale TEM observation demonstrates that chemical short-range order (CSRO) domains are present in the FCC solid solution. Apart from contributing to the high strength, the CSRO domains and atomic size misfit (2.36 %) promoted by the high content of Si are regarded to enhance the local barrier for the successive accumulation of SFs, hindering the formation of HCP martensite and mechanical twin. The uniform formation of SFs in the FCC matrix upon deformation effectively alleviates strain localization, contributing to the sustained strain-hardening ability and super-ductility. These insights suggest a strategy to design low-SFE alloys with excellent mechanical properties via manipulating the rate of martensitic transformation by CSROs and atomic size misfit.

Viscosity database for ternary Cu–Cr–X (X=Ni, Si, Zr) alloys based on CALPHAD-type modeling

A viscosity model with composition and temperature dependence for the liquid alloys of the Cu–Cr–X (X = Ni, Si, Zr) systems was developed using the CALPHAD (CALculation of PHAse Diagrams) approach. Based on the critical review of the available experimental data for pure metal viscosity, the viscosities of pure liquid Cu, Cr, Zr, Ni and Si were simulated with the Arrhenius formula. The viscosities of the binary liquid alloys of the Cu–Ni, Cu–Si, Cu–Zr, Cr–Ni, Cr–Si and Ni–Zr systems at different temperatures were evaluated using the CALPHAD-type formalism. The non-linear viscosity behavior resulting from chemical short-range order was described using temperature-dependent binary interaction parameters. The viscosities of the Cu–Cr and Cr–Zr liquid alloys were predicted employing the Hirai equation. The viscosities of the Cu–Cr–Zr, Cu–Cr–Ni and Cu–Cr–Si ternary liquids were directly extrapolated using the Redlish-Kister-Muggianu equation from the parameters of the binary systems. A comprehensive understanding of the temperature-composition-solidification phase-viscosity relationship was established for ternary melts. The satisfactory agreement observed between calculations and experimental data validates the use of CALPHAD-type viscosity modeling, supporting the suitability of the constructed viscosity database for predicting the viscosity of high-performance Cu-based alloys.