High-performance Alloys Research Articles

Additive Manufacturing of High-Performance Ti-Mo Alloys Used on a Puncture Needle: The Role of Linear Energy Density in Microstructure Evolution and Mechanical Properties

Additive Manufacturing of High-Performance Ti-Mo Alloys Used on a Puncture Needle: The Role of Linear Energy Density in Microstructure Evolution and Mechanical Properties

Revolutionary Steel Structures: A Comprehensive Review of Current Trends and Future Directions

Steel construction has always been a key element of contemporary buildings with new properties of strength, stability and versatility. This work aims to review the profound developments in the steel structures area with special emphasis on new tendencies, drawbacks and prospects for the future. Innovation areas covered are developments with high-performance steel alloys, prefabrication and modular construction techniques to improve efficiency in the use of global natural resources such as carbonized waste products like slag from coal-fired power plants), and Digital Twin technologies which include AI monitoring systems. These innovations are changing the way steel structures can be designed, constructed and maintained in ways that allow for more efficient and sustainable construction practices we have yet to see. There is a strong focus on sustainable and eco-friendly steel production, such as hydrogen-based steelmaking and the increased use of recycled materials which help reduce carbon emissions helping this transition towards a global circular economy. The paper discusses some of the big challenges facing implementation in infrastructure, as well as the critical need for material performance under these extreme conditions (corrosion & fire resistance), discussing strategies to meet or re-direct them. In terms of the future, it identifies positive steps that are good news for steel structures in growth sectors such as renewable infrastructure, aerospace and smart cities. Recently, self-healing materials14–19 (and the related quantum-inspired approaches20) were developed and tested for integration into adaptive steel designs21 using active fluids... but there are many other opportunities in construction where the robotic workload can grow further. This paper presents an in-depth examination of these trends and innovations from which the current state-of-the-art regarding innovative steel structures can be extracted, offering pertinent insights on how this is set to or could continue into its role within a burgeoning concept for resilient, sustainable and intelligent built environments.

Research Trends in Isothermal Near-Net-Shape Forming Process of High-Performance Titanium Alloys

Titanium alloys find extensive applications in aviation, maritime, and chemical engineering applications. Nonetheless, these alloys encounter significant challenges during the conventional forging process, which include high deformation resistance, limited processing temperature ranges, and inhomogeneous microstructure. Isothermal forging, as a near-net-shape forming technique, can alleviate the microstructural inhomogeneity caused by deformation dead zones in conventional forging, thus enabling the direct production of complex shapes. This process enhances the overall performance and utilization of materials while reducing manufacturing costs. This paper comprehensively reviews how isothermal near-net-shape forging process parameters influence the intricate microstructure and essential properties of titanium alloys. The unique properties of isothermal forging applied to high-performance titanium alloys are also discussed in depth, and the intricate interplay between process parameters and the microstructure and properties of recoloration is clarified. That is to say, temperature is a vital element influencing the phases and microstructure of titanium alloys during the forming process. Grain size, microstructural homogeneity, and phase transformation are influenced by the strain rate, thereby affecting the plasticity, fracture toughness, and strength of titanium alloys. The extent of deformation significantly governs the grain size, the thickness of secondary α phase, dynamic recrystallization, and primary α phase. Cooling rate affects the grain size and precipitates, contributing to grain refinement. The frequency of isothermal forging affects the grain refinement and microstructural uniformity of titanium alloys. Finally, this paper summarizes the scientific questions that remain unresolved in this field and outlines future research directions to promote the further development of isothermal near-net-shape forging processes and facilitate the broader industrial applications of high-performance titanium alloys and other difficult-to-form alloys.

Microstructure Evolution of Extruded TiAl Alloy During Vacuum Isothermal Superplastic Forging Process

Vacuum isothermal forging is an ideal method for preparing high-performance TiAl alloy forgings, as it is carried out under the conditions of a uniform temperature field and oxygen isolation. The mechanical properties of TiAl alloys strongly depend on their microstructure, so it is important to study their microstructure evolution during the forging process to improve their properties. In this study, TiAl alloy forgings with different deformations were produced from the extruded billets by vacuum isothermal superplastic forging under lower temperatures and extremely low strain rate conditions. The results indicate that the streamlined structure in the extruded alloy was destroyed during the forging process. As the deformation increased, the dynamic recrystallization was more fully carried out, leading to a substantial decrease in remnant lamellar colonies and a significant increase in the γ phase, and the microstructure was transformed from nearly lamellar (NL) to near gamma (NG) structure. The proportion of high-angle grain boundaries (HAGB) increased with increasing deformation, while the grain size reduced from 20 μm to 4.6 μm. In addition, the streamlined features and textures exhibited a weakening trend with increasing deformation, leading to a decrease in the ultimate strength from 891 MPa to 722 MPa. To maintain the streamlined characteristics and retain strengthening effects, the forging deformation should not exceed 56.7%.

Highly printable, strong, and ductile ordered intermetallic alloy

Ordered intermetallic alloys are renowned for their impressive mechanical, chemical, and physical properties, making them appealing for various fields. However, practical applications of them have long been severely hindered due to their severe brittleness and poor fabricability. It is difficult to fabricate such materials into components with complex geometries through traditional subtractive manufacturing methods. Here, we proposed a strategy to solve these long-standing issues through the additive manufacturing of chemically complex intermetallic alloy (CCIMA) based on laser powder bed fusion (LPBF). The developed CCIMA exhibits good printability, enabling a crack-free microstructure with a low porosity of 0.005%. More importantly, a good combination of high tensile strength (~1.6 GPa) and large uniform elongation (~35%) can be achieved, which has not been reported in the existing additive-manufactured alloys. Such properties are attributed to the structural and chemical features of highly ordered superlattice grain decorated with disordered interfacial nanolayer, as well as dynamic evolutions and interactions of multiple dislocation substructures. These findings could provide references for developing high-performance intermetallic alloys and accelerating their practical applications.

Active learning framework to optimize process parameters for additive-manufactured Ti-6Al-4V with high strength and ductility

Optimizing process and heat-treatment parameters of laser powder bed fusion for producing Ti-6Al-4V alloys with high strength and ductility is crucial to meet performance demands in various applications. Nevertheless, inherent trade-offs between strength and ductility render traditional trial-and-error methods inefficient. Herein, we present Pareto active learning framework with targeted experimental validation to efficiently explore vast parameter space of 296 candidates, pinpointing optimal parameters to augment both strength and ductility. All Ti-6Al-4V alloys produced with the pinpointed parameters exhibit higher ductility at similar strength levels and greater strength at similar ductility levels compared to those in previous studies. By improving one property without significantly compromising the other, the framework demonstrates efficiency in overcoming the inherent trade-offs. Ultimately, Ti-6Al-4V alloys with ultimate tensile strength and total elongation of 1190 MPa and 16.5%, respectively, are produced. The proposed framework streamlines discovery of optimal processing parameters and promises accelerated development of high-performance alloys.

Robustness of machine learning predictions for Fe-Co-Ni alloys prepared by various synthesis methods.

Developing high-performance alloys is essential for applications in advanced electromagnetic energy conversion devices. In this study, we assess Fe-Co-Ni alloy compositions identified in our previous work through a machine learning (ML) framework, which used both multi-property ML models and multi-objective Bayesian optimization to design compositions with predicted high values of saturation magnetization, Curie temperature, and Vickers hardness. Experimental validation was conducted on two promising compositions synthesized using three different methods: arc melting, ball milling followed by spark plasma sintering (SPS), and chemical synthesis followed by SPS. The results show that the experimental property values of arc melted samples deviated less than 14% from predicted values. This work further explains how structural variations across synthesis methods impact property behavior, validating the robustness of ML-predicted compositions and highlighting a pathway for integrating processing conditions into alloy development.

Comparative study of gravity effects in directional solidification of Al-3.5 wt.% Si and Al-10 wt.% Cu alloys

Directional solidification experiments of Al-3.5 wt.% Si and Al-10 wt.% Cu alloys were conducted under gravity and microgravity conditions using a 50-m-high drop tube. The solidification morphology of the two alloys is mainly columnar dendrites and equiaxed dendrites, respectively. The dendrite arm spacing (DAS), eutectic content, grain size, and compositional distribution of both alloys exhibit distinct characteristics under gravity and microgravity conditions. The study introduces an innovative perspective by taking solute density and its redistribution behavior into account when discussing the gravity effects during the directional solidification of alloys. The results indicate that the way gravity works on the solidification behavior of alloys depends strongly on the redistribution behavior and density of solute as well as crystallization modes, such as columnar grain or equiaxed grain. These findings are helpful in clarifying the coupling mechanism of gravity and relevant factors on the solidification of alloys, not only contributing to understanding the effect of gravity on solidification better but also offering valuable guidance for eliminating solidification segregation and producing high-performance alloys.

MGT: Machine Learning Accelerates Performance Prediction of Alloy Catalytic Materials.

The application of deep learning technology in the field of materials science provides a new method for predicting the adsorption energy of high-performance alloy catalysts in hydrogen evolution reactions and material discovery. The activity and selectivity of catalytic materials are mainly influenced by the properties and positions of active sites and adsorption sites. However, current deep learning models have not sufficiently focused on the importance of active atoms and adsorbates, instead placing more emphasis on the overall structure of the catalytic materials. In this paper, the overall molecular graph and a masked graph, which ignores fixed atoms, are separately input into the Masked Graph Transformer (MGT) network to enhance the model's ability to recognize key sites in catalytic reactions. Second, we introduce a nonlinear message-passing mechanism to improve the dot-product attention in the Transformer and capture the directional information on the relative positions of nodes by integrating molecular geometric information through deep tensor products. Subsequently, we constructed the NLMP-TransNet framework, which combines MPNN and Transformer and optimizes the model's learning and prediction capabilities through weight sharing and residual connections. The MGT achieves an error rate of 0.5447 eV on the small data set OC20-Ni, surpassing existing technologies. Ablation studies confirm the necessity of focusing on site features for accurate adsorption energy prediction. Code is available at https://github.com/KristinSun/OCP-MGT.git.

Vacuum-Featured High-Performance SiC-Blended Hybrid AZ91E Alloy Composite by Liquid Stir Solidification: Characteristics Measured

Vacuum-Featured High-Performance SiC-Blended Hybrid AZ91E Alloy Composite by Liquid Stir Solidification: Characteristics Measured

Tensile Properties, Strain Rate Sensitivity and Microstructural Analysis of SN100C Solder Alloys

Sn-Cu-Ni-Ge (SN100C®) is a high-performance Pb-free solder alloy widely used in the electronics manufacturing industry due to its excellent soldering performance and lower cost. SN100C has a huge potential to replace the commonly used Sn-Ag-Cu solders. This work investigates the effect of different strain rates (10-3 to 8×10-1s-1) on tensile performance for bulk SN100C samples at room temperature. The tensile properties, e.g., elastic modulus (E), yield strength (σy) and tensile strength (σT) are determined from the stress-stress curves. The value of σy and σT increases with increasing strain rates and this increase becomes less prominent at higher strain rates. Necking and ductile fracture are observed for all samples with a significant number of dimples, voids and tongues formed. The level of ductility of the samples decreases with increasing strain rates, which is further confirmed by the stress-strain behaviour. The microstructural evolution of the samples is evaluated by optical microscope (OM), scanning electron microscope (SEM) and energy dispersive X-ray (EDX) to reveal the generation of recrystallisation and fracture of the intermetallic compounds (IMCs) at the fracture tips and identify the embedded of IMCs within the sample matrix.

Upcycled high-strength aluminum alloys from scrap through solid-phase alloying

Although recycling secondary aluminum can lead to energy consumption reduction compared to primary aluminum manufacturing, products produced by traditional melt-based recycling processes are inherently limited in terms of alloy composition and microstructure, and thus final properties. To overcome the constraints associated with melting, we have developed a solid-phase recycling and simultaneous alloying method. This innovative process enables the alloying of 6063 aluminum scrap with copper, zinc, and magnesium to form a nanocluster-strengthened high-performance aluminum alloy with a composition and properties akin to 7075 aluminum alloy. The unique nanostructure with a high density of Guinier-Preston zones and uniformly precipitated nanoscale η‘/Mg(CuZn)2 strengthening phases enhances both yield and ultimate tensile strength by >200%. By delivering high-performance products from scrap that are not just recycled but upcycled, this scalable manufacturing approach provides a model for metal reuse, with the option for on-demand upcycling of a variety of metallic materials from scrap sources.

Axial Zero Thermal Expansion with Good Mechanical Strength in the Ni-Doped Kagome Ho2Fe17 Magnets.

Zero thermal expansion (ZTE) metals have drawn considerable scientific and practical interest due to their excellent dimensional stability. However, the narrow temperature window and inherent brittleness of the ZTE compounds severely limit their processing and application. Herein, an axial ZTE alloy (Ho2Fe13.8Ni3.2, αl = -0.3 × 10-6 K-1 and 110-545 K) is realized in the Ni-doped Ho2Fe17 magnets, which effectively broadens the ZTE temperature window. Combining the variable-temperature neutron diffraction and magnetization measurements, we reveal that the content of Ni tailors the ferromagnetic ordering of the Fe sublattice and regulates lattice negative thermal expansion. Good compressive strength is subsequently achieved by introducing excess Fe in the axial ZTE composition, namely, the dual-phase alloy of Ho2Fe13.8Ni3.2-Fe5 (αl = +0.3 × 10-6 K-1, 110-535 K, and 1.19 ± 0.2 GPa). Neutron diffraction and scanning electron microscopy reveal that the α phase (Fe-Ni) precipitates in the hexagonal phase matrix play a critical role in maintaining ZTE characteristics and enhancing compressive strength. The present chemical design approach may be applicable for obtaining high-performance axial ZTE alloys.

Optimization of Process Parameters and Microstructure of CoCrFeNiTiAl High-Performance High-Entropy Alloy Coating

CoCrFeNiTiAl high-entropy alloy coatings have been prepared by laser cladding technology based on response surface methodology (RSM). The results show that the effects of laser power, cladding speed, and pulse width on the dilution rate and microhardness of the high-entropy alloy coatings are investigated. Among the single-factor results, the laser power has the most significant effect on the properties of high-entropy alloy coatings, followed by the cladding speed, while the pulse width has no significant effect. In the interaction term analysis, the interaction term of laser power and pulse width has a remarkable effect on both output responses, whereas the interaction term of pulse width and cladding speed only has a considerable effect on microhardness, while the interaction term of laser power and cladding speed has an insignificant effect on both output responses. The optimum parameters for the preparation of high-performance high-entropy alloy coatings are found at laser power P = 676.73 W, cladding speed V = 5 mm/s, and pulse width P0 = 9 ms. The microstructures of the high-entropy alloy coating prepared with optimal process parameters have been characterized, which show that the metallurgical bonding between the cladding layer and the substrate is strong and without obvious defects such as porosity and cracks.

Collaborative improvement of mechanical and electrical properties of Cu–Ni–Co–P alloys via regulation of nanophase precipitation behavior

Owing to their excellent strength and electrical conductivity, Cu–Ni–Co–P alloys present strong potential as next-generation materials for integrated circuits in electronic information systems. However, these outstanding properties are closely tied to the precise control of nanophase precipitation behavior within Cu-based alloy systems. Herein, the design of alloy composition was combined with aging treatment to regulate the nanoprecipitation process. Furthermore, the effects of P content and aging treatment conditions, including temperature and duration, on the microstructure and the mechanical, and electrical properties of Cu–Ni–Co–P alloys were systematically investigated. The findings reveal that Cu–0.3Ni–0.3Co–0.16P alloys, when aged at 500 °C for 4 h, primarily consist of a Cu-rich matrix interspersed with numerous nanoprecipitates. These nanoprecipitates were identified as the hexagonal CoNiP phase, precipitating in Guinier–Preston (GP) zones and maintaining a coherent relationship with the Cu matrix. The as-annealed Cu–0.3Ni–0.3Co–0.16P alloys demonstrated a tensile strength of 652.9 MPa, a yield strength of 631.2 MPa, a Vickers hardness of 203.2 HV, and an electrical conductivity of 66.4 %IACS. Aberration-corrected scanning transmission electron microscopy revealed that G.P. zones suppressed the coarsening of the CoNiP phase, thereby enhancing the mechanical strength of the Cu–Ni–Co–P alloys. The strength analysis calculations suggest that fine-grain and precipitation strengthening mechanisms are the predominant factors in improving the mechanical strength of these alloys. This study provides valuable insights into the development and manufacturing of high-performance Cu-based alloys for advanced applications in the electronics industry.

Temperature-dependent solid material properties of GRCop-42 for an additively manufactured liquid rocket engine LOx cooling channel

Recent technological developments in the field of Additive Manufacturing (AM) provide a number of opportunities for the utilisation of high-performance copper alloys for aerospace applications. The additively manufactured LOx/LNG DemoP1 aerospike engine demonstrator designed by Pangea Aerospace is a characteristic example based on the Direct Metal Laser Sintering (DMLS) technology. The aerospike engine thrust chamber and LOx cooling channels are manufactured using GRCop-42 material powder, a Cu-Cr-Nb based copper alloy developed by the National Aeronautics and Space Administration (NASA) for the regenerative cooling technology of high thermal demand thrust chambers and nozzles. In the current work temperature-dependent correlations are derived for the density, specific heat capacity at constant pressure and thermal conductivity of the GRCop-42 material. The correlations for the solid material properties are then introduced into the ANSYS Fluent 2023 R2 Computational Fluid Dynamics (CFD) package and their capabilities are investigated for the characterisation of the flow-field characteristics of the LOx flow in the cooling channel. The numerical solution of the coolant flow in the AM cooling channel is compared against experimental data of the DemoP1 engine demonstrator. The main objective of this study is to provide a realistic physical description of the temperature-dependent properties of the AM solid material in high heat flux applications where the material properties are mostly considered as constant in previous studies.

Prediction of formation energy for oxides in ODS steels by machine learning

The phase and proportion of nano-oxides in oxide dispersion strengthened (ODS) steels are determined by the formation energy and the content of oxide-forming elements, particularly minor reactive elements, which in turn influence the macroscopic properties of the ODS steels. To study the phase, morphology, and interfaces of oxides in six ODS steels, transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM), and high-resolution transmission electron microscopy (HRTEM) techniques were employed. Subsequently, machine learning (ML) methods were used to predict the formation energies of the oxides in the ODS steels. Among six ML models employed, the light gradient boosting machine (LGBM) model shows the highest accuracy in predicting the formation energy of the oxides, with root mean square error (RMSE) values of 0.18 eV/atom and 0.27 eV/atom, mean absolute error (MAE) values of 0.11 eV/atom and 0.18 eV/atom, and coefficient of determination (R2) values of 0.96 and 0.92 for the training and testing sets, respectively. For Magpie descriptors, the most essential feature is “dev_Electronegativity” with an importance score of 444. The method developed in this study can establish an accurate prediction model for the formation energy of oxides. The knowledge obtained in this work guides the future development of high-performance ODS alloys.

Closed-loop control of a directed energy deposition process for repair applications

AbstractAdditive manufacturing processes of the directed energy deposition family such as laser metal deposition or wire arc additive manufacturing offer great control and improved metallurgical properties over traditional processes such as casting. They are very promising for many industrial applications such as the fabrication of intricate parts with high-performance alloys as well as repair applications. However, these processes are generally very sensitive to process conditions, yet are most often operated in open loop. In this study, a closed-loop controller with a suitable error criteria based on 3D scanning data in-between layers is implemented. It is applied to various repair samples made of 316L stainless steel and Inconel 625 materials. The results show that the controller can compensate for suboptimal operating points and in-process deviations while maintaining satisfactory metallurgical and mechanical properties.

The Effects of Bismuth Addition on the Characteristics of Aluminum Alloys for Electric Vehicle Battery Housings

As the Electric Vehicle(EV) market has recently grown, the application of high-performance aluminum alloy, a representative lightweight material for lightening car bodies, is increasing. Among them, die casting is receiving the most attention due to its rapid productivity and excellent formability, and research on improving the properties of the mainly used Al-Si alloy is being actively conducted. In this study, the influence of additions of bismuth(Bi) on microstructure, thermal, and machinability of Al-10%Si alloy has been reported. Bismuth depressed the aluminum-silicon eutectic growth temperature and altered the silicon morphology. When the bismuth contents of the specimens were 0, 0.22, 0.5 and 1.8 wt%, results show that bismuth has a refining effect on the eutectic silicon and its refinement behavior is improved with increasing bismuth. Also bismuth is added to improve the mechanical and thermal properties of aluminium alloys for EV battery housing. Finally, we analyzed the heat emission characteristics and oxidation resistance of the battery housing using the developed aluminum alloy to study whether it could contribute to the stable operation of the battery.

Achieving superior ductility with ultrahigh strength via deformation and strain hardening in the non-recrystallized regions of the heterogeneous-structured high-entropy alloy

Developing metallic structural materials with ultrahigh strength and exceptional ductility remains a significant challenge due to the trade-off between both properties. This study presents a heterogeneous-structured high-entropy alloy achieving a superior combination of strength and ductility compared to the reported heterogeneous-structured high entropy alloys through deformation and strain hardening in the non-recrystallized regions. The cold rolling followed by annealing at 760 °C resulted in a heterogeneous microstructure consisting of a small fraction of ultrafine recrystallized grains and extensive non-recrystallized regions, with a significant amount of L12 precipitates throughout the alloy. The architected microstructure led to a significant enhancement of yield strength through mechanisms including dislocation strengthening, L12 strengthening, and grain boundary strengthening. During the deformation, the non-recrystallized regions accommodated substantial strain through the reactivation of pre-existing deformation bands and the synergistic deformation of the FCC and L12 phases, thereby markedly enhancing ductility. Moreover, the metastable FCC matrix underwent FCC→BCC phase transformation, leading to the formation of numerous short-range BCC domains, which further contributed to the pronounced strain hardening. Consequently, the alloy annealing at 760 °C achieved a yield strength of 1.73 GPa, an ultimate strength of 2.05 GPa, and an elongation of 21.0 %. This study underscores a novel strategy for the concurrent enhancement of strength and ductility and provides valuable insights for the design of high-performance alloys.