Thermodynamics-guided alloy and process design for additive manufacturing

High-sensitivity differential scanning calorimetry using a MEMS thermopile chip for analyzing polymer crystallization

This paper introduces a high-sensitivity differential scanning calorimetry (DSC) technique based on a MEMS single-crystalline silicon thermopile chip and its application for analyzing the crystallization process of polyamide 6 (PA6) under various thermal processing conditions. The chip integrates 54 pairs of single-crystalline silicon thermocouples beneath a SiNx-suspended film, achieving a temperature responsivity of 31.5 mV per °C and a power responsivity of 147 V W-1. Additionally, the chip's cooling time constant is only 2.4 ms. The non-isothermal experimental results of PA6 suggest that melt-crystallization is suppressed at cooling rates exceeding the critical rate of 50 °C s-1, and cold-crystallization is suppressed at heating rates above the critical rate of 300 °C s-1. Thanks to its high sensitivity, this chip can detect subtle exothermic signals associated with the γ-α phase transition in PA6. The critical heating rate for this phase transition is determined to be 25 °C s-1. Isothermal experimental results show that PA6 undergoes crystallization within 70 °C to 170 °C, with the shortest half-crystallization time of ∼1.1 s at 120 °C. The high-sensitivity DSC technique proposed in this work holds great promise for studying the thermal behaviour of various materials at high heating and cooling rates.

Laser Powder Bed Fusion of a Novel Crack-Free γ' Phase-Strengthened Ni-Based Alloy

Laser powder bed fusion (LPBF)-fabricated Ni-based alloys with high γ' phase fractions generally suffer from cracking that limits their applications. This study presents SD247, a novel alloy that overcomes the challenge of cracking issues and exhibits superior mechanical properties after heat treatment. Compared to CM247LC, SD247 exhibited a lower cracking tendency due to alloying element modification. After heat treatment, SD247 features primary γ' phases with an average diameter of 306 nm and secondary γ' phases averaging 25 nm, with few Ta- and Ti-rich MC-type carbides. The columnar grain structure in as-built specimens largely disappeared, and the fraction of grains in soft orientations decreased by 12.8%. The microhardness and ultimate tensile strength increased by 30% and 20%, respectively. These findings demonstrate that the superior LPBF fabrication of Ni-based alloys with a high γ' fraction can be achieved. Because of the excellent mechanical properties and acceptable cost, LPBF-fabricated SD247 shows great potential in aerospace hot-end components.

Monitoring, Modeling, and Statistical Analysis in Metal Additive Manufacturing: A Review

Despite the significant advances made involving the additive manufacturing (AM) of metals, including those related to both materials and processes, challenges remain in regard to the rapid qualification and insertion of such materials into applications. In general, understanding the process-microstructure-property interrelationships is essential. To successfully understand these interrelationships on a process-by-process basis and exploit such knowledge in practice, leveraging monitoring, modeling, and statistical analysis is necessary. Monitoring allows for the identification and measurement of parameters and features associated with important physical processes that may vary spatially and temporally during the AM processes that will influence part properties, including spatial variations within a single part and part-to-part variability, and, ultimately, quality. Modeling allows for the prediction of physical processes, material states, and properties of future builds by creating material state abstractions that can then be tested or evolved virtually. Statistical analysis permits the data from monitoring to inform modeling, and vice versa, under the added consideration that physical measurements and mathematical abstractions contain uncertainties. Throughout this review, the feedstock, energy source, melt pool, defects, compositional distribution, microstructure, texture, residual stresses, and mechanical properties are examined from the points of view of monitoring, modeling, and statistical analysis. As with most active research subjects, there remain both possibilities and limitations, and these will be considered and discussed as appropriate.

Development of Robust Steel Alloys for Laser-Directed Energy Deposition via Analysis of Mechanical Property Sensitivities

To ensure consistent performance of additively manufactured metal parts, it is advantageous to identify alloys that are robust to process variations. This paper investigates the effect of steel alloy composition on mechanical property robustness in laser-directed energy deposition (L-DED). In situ blending of ultra-high-strength low-alloy steel (UHSLA) and pure iron powders produced 10 compositions containing 10-100 wt% UHSLA. Samples were deposited using a novel configuration that enabled rapid collection of hardness data. The Vickers hardness sensitivity of each alloy was evaluated with respect to laser power and interlayer delay time. Yield strength (YS) and ultimate tensile strength (UTS) sensitivities of five select alloys were investigated in a subsequent experiment. Microstructure analysis revealed that cooling rate-driven phase fluctuations between lath martensite and upper bainite were a key factor leading to high hardness sensitivity. By keeping the UHSLA content ≤20% or ≥70%, the microstructure transformed primarily to ferrite or martensite, respectively, which generally corresponded to improved robustness. Above 70% UHSLA, the YS sensitivity remained low while the UTS sensitivity increased. This finding, coupled with the observation of auto-tempered martensite at lower cooling rates, may suggest a strong response of the work hardening capability to auto-tempering at higher alloy contents. This work demonstrates a methodology for incorporating robust design into the development of alloys for additive manufacturing.

Multicomponent alloys designed to sinter

Powder sintering is a low-energy, net-shape processing route for many new products in the additive manufacturing space. We advance the viewpoint that for future manufacturing, alloys should be designed from materials science principles to sinter quickly at lower temperatures and with controlled final microstructures. Specifically, we illustrate the computational design of multinary Ni-base alloys, whose chemistries permit a low-temperature solid-state sintering scheme without any pressure- or field-assistance, as well as heat-treatability after sintering. The strategy is based on sequential phase evolutions designed to occur during sintering. The reactions involve rapid reorganization of matter to full density in cycles up to just 1200 °C, while conventional Ni alloys sintered in the solid-state require about ten times longer, or more than 250 °C degrees higher temperature. Our approach yields an alloy that benefits from precipitation hardening, has an increased strength ~ 50% higher than solid-state processed commercial Ni alloys, and yet exhibits extensive plasticity beyond 35% uniaxial strain. The results point to a generalizable design scheme for many other alloys designed for solid-state powder processing that can enable greater value from additive manufacturing.

The Role of Dislocation Type in the Thermal Stability of Cellular Structures in Additively Manufactured Austenitic Stainless Steel

The ultrafine cellular structure promotes the extraordinary mechanical performance of metals manufactured by laser powder-bed-fusion (L-PBF). An in-depth understanding of the mechanisms governing the thermal stability of such structures is crucial for designing reliable L-PBF components for high-temperature applications. Here, characterizations and 3D discrete dislocation dynamics simulations are performed to comprehensively understand the evolution of cellular structures in 316L stainless steel during annealing. The dominance of screw-type dislocation dipoles in the dislocation cells is reported. However, the majority of dislocations in sub-grain boundaries (SGBs) are geometrically necessary dislocations (GNDs) with varying types. The disparity in dislocation types can be attributed to the variation in local stacking fault energy (SFE) arising from chemical heterogeneity. The presence of screw-type dislocations facilitates the unpinning of dislocations from dislocation cells/SGBs, resulting in a high dislocation mobility. In contrast, the migration of SGBs with dominating edge-type GNDs requires collaborative motion of dislocations, leading to a sluggish migration rate and an enhanced thermal stability. This work emphasizes the significant role of dislocation type in the thermal stability of cellular structures. Furthermore, it sheds light on how to locally tune dislocation structures with desired dislocation types by adjusting local chemistry-dependent SFE and heat treatment.

Fracture behavior of additively manufactured corrax maraging stainless steel

Additively manufactured a low carbon Fe-Cr-Ni-Al Corrax stainless steel has ultra-high strength, but the mechanism at work when the steel cracks is still unclear. In this study, Corrax stainless steel was tensile tested to fracture and cracks in the vicinity of the fracture surface were analyzed by scanning electron microscope and electron-backscattered diffraction. The results show that the cracks propagated at angles of 45-60° to the tensile axis. Some cracks were transgranular, and high-angle grain boundaries had little effect on crack propagation. Crack propagation was inhibited in regions with lower Taylor factors. Kernel average misorientation value analysis established that the crack propagation process is accompanied by significant plastic deformation. The influence of particles and unfused pores on crack propagation is also discussed.

Review on Fatigue of Additive Manufactured Metallic Alloys: Microstructure, Performance, Enhancement, and Assessment Methods

Additive manufacturing (AM), which is a process of building objects in a layer-upon-layer fashion from designed models, has received unprecedented attention from research and industry because it offers outstanding merits of flexibility, customization, reduced buy-to-fly ratio, and cost-effectiveness. However, the fatigue performance of safety-critical industrial components fabricated by AM is still far below that obtained from conventional methods. This review discusses the microstructural heterogeneities, randomly dispersed defects, poor surface quality, and complex residual stress generated during the AM process that can negatively impact the fatigue performance of as-printed parts. The difference in microstructural origin of fatigue failure between conventionally manufactured and printed metals is reviewed with particular attention to the effects of the trans-scale microstructures on AM fatigue failure mechanisms. Various methods for mitigating the fatigue issue, including pre-process, inter-process, and post-process treatments, are illustrated. Empirical, semi-empirical, and microstructure-sensitive models are presented to predict fatigue strength and lifetime. Summary and outlooks for future development of the fatigue performance of AM materials are provided.

Solute trapping and non-equilibrium microstructure during rapid solidification of additive manufacturing

Solute transport during rapid and repeated thermal cycle in additive manufacturing (AM) leading to non-equilibrium, non-uniform microstructure remains to be studied. Here, a fully-coupled fluid dynamics and microstructure modelling is developed to rationalise the dynamic solute transport process and elemental segregation in AM, and to gain better understanding of non-equilibrium nature of intercellular solute segregation and cellular structures at sub-grain scale during the melting-solidification of the laser powder bed fusion process. It reveals the solute transport induced by melt convection dilutes the partitioned solute at the solidification front and promotes solute trapping, and elucidates the mechanisms of the subsequent microstructural morphology transitions to ultra-fine cells and then to coarse cells. These suggest solute trapping effect could be made used for reducing crack susceptibility by accelerating the solidification process. The rapid solidification characteristics exhibit promising potential of additive manufacturing for hard-to-print superalloys and aid in alloy design for better printability.

Understanding the influence of alloying elements on the print quality of powder bed fusion-based metal additive manufacturing: Ta and Cu addition to Ti alloy

Alloy design coupled with metal additive manufacturing (AM) opens many opportunities for materials innovation. Investigating the effect of printing parameters for alloy design is essential to achieve good part quality. Among different factors, laser absorptivity, heat diffusivity, and in situ intermetallic phase formations are critical. In this study, the first step employed was a reduction in Al and V contents in Ti6Al4V to design Ti3Al2V alloy, and further 10 wt.% tantalum (Ta) and 3 wt.% copper (Cu) were added to Ti3Al2V. A synergistic effect of Ta and Cu addition in Ti3Al2V negated their effect with higher porosities in Ti3Al2V-Ta-Cu. Ti3Al2V-Ta composition was more sensitive to the laser power, whereas Ti3Al2V-Ta-Cu to the overall energy density. Understanding the effect of energy density on these alloys' microstructural evolution and mechanical properties highlights the need for process-property optimization during alloy design using AM.

Benchmarking First-Principles Reaction Equilibrium Composition Prediction

The availability of thermochemical properties allows for the prediction of the equilibrium compositions of chemical reactions. The accurate prediction of these can be crucial for the design of new chemical synthesis routes. However, for new processes, these data are generally not completely available. A solution is the use of thermochemistry calculated from first-principles methods such as Density Functional Theory (DFT). Before this can be used reliably, it needs to be systematically benchmarked. Although various studies have examined the accuracy of DFT from an energetic point of view, few studies have considered its accuracy in predicting the temperature-dependent equilibrium composition. In this work, we collected 117 molecules for which experimental thermochemical data were available. From these, we constructed 2648 reactions. These experimentally constructed reactions were then benchmarked against DFT for 6 exchange-correlation functionals and 3 quality of basis sets. We show that, in reactions that do not show temperature dependence in the equilibrium composition below 1000 K, over 90% are predicted correctly. Temperature-dependent equilibrium compositions typically demonstrate correct qualitative behavior. Lastly, we show that the errors are equally caused by errors in the vibrational spectrum and the DFT electronic ground state energy.