High temperature rise dominated cracking mechanisms in ultra-ductile and tough titanium alloy

Trifunctional nanoprecipitates ductilize and toughen a strong laminated metastable titanium alloy

Metastability-engineering, e.g., transformation-induced plasticity (TRIP), can enhance the ductility of alloys, however it often comes at the expense of relatively low yield strength. Here, using a metastable Ti-1Al-8.5Mo-2.8Cr-2.7Zr (wt.%) alloy as a model material, we fabricate a heterogeneous laminated structure decorated by multiple-morphological α-nanoprecipitates. The hard α nanoprecipitate in our alloy acts not only as a strengthener to the material, but also as a local stress raiser to activate TRIP in the soft matrix for great uniform elongation and as a promoter to trigger interfacial delamination toughening for superior fracture resistance. By elaborately manipulating the activation sequence of lamellar-thickness-dependent deformation mechanisms in Ti-1Al-8.5Mo-2.8Cr-2.7Zr alloys, the yield strength of the present submicron-laminated alloy is twice that of equiaxed-coarse grained alloys with the same composition, yet without sacrificing the large uniform elongation. The desired mechanical properties enabled by this strategy combining the laminated metastable structure and trifunctional nanoprecipitates provide new insights into designing ultra-strong and ductile materials with great toughness.

Hierarchical nano-martensite-engineered a low-cost ultra-strong and ductile titanium alloy

Due to the low thermal stability of crystallographic boundaries, the grain boundary engineering (GBE) manifests some limits to the fineness and types of microstructures achievable, while unique chemical boundary engineering (CBE) enables us to create a metallic material with an ultrafine hierarchically heterogeneous microstructure for enhancing the mechanical properties of materials. Here, using a low cost metastable Ti-2.8Cr-4.5Zr-5.2Al (wt.%) alloy as a model material, we create a high density of chemical boundaries (CBs) through the significant diffusion mismatch between Cr and Al alloying elements to architecture hierarchical nano-martensites with an average thickness of ~20 nm. For this metastable titanium alloy, the significantly enhanced yield strength originates from dense nano-martensitic interface strengthening, meanwhile the large ductility is attributed to the multi-stage strain hardening of hierarchical 3D α'/β lamellae assisted by equiaxed primary α (α_p) nodules. The hierarchical nano-martensite engineering strategy confers our alloy a desired combination of strength and ductility, which can potentially be applied to many transformable alloys, and reveal a new target in microstructural design for ultrastrong-yet-ductile structural materials.

It is challenging to obtain Ti alloys with ultrafine microstructure owing to the low thermal stability of crystallographic boundaries. Here the authors demonstrate a chemical boundary-based strategy to produce a hierarchical Ti alloy with nano-martensites that has excellent strength and ductility.

Generative machine learning algorithm for lattice structures with superior mechanical properties

Lattice structures are typically made up of a crisscross pattern of beam elements, allowing engineers to distribute material in a more structurally effective way. However, a main challenge in the design of lattice structures is a trade-off between the density and mechanical properties. Current studies have often assumed the cross-sectional area of the beam elements to be uniform for reducing the design complexity. This simplified approach limits the possibility of finding superior designs with optimized weight-to-performance ratios. Here, the optimized shape of the beam elements is investigated using a deep learning approach with high-order Bézier curves to explore the augmented design space. This is then combined with a hybrid neural network and genetic optimization (NN-GO) adaptive method for the generation of superior lattice structures. In our optimized design, the distribution of material is smartly shifted more towards the joint region, the weakest location of lattice structures, to achieve the highest modulus and strength. This design strikes to balance between two modes of deformation: axial and bending. Thus, the optimized design is efficient for load bearing and energy absorption. To validate our simulations, the optimized design is then fabricated by additive manufacturing and its mechanical properties are evaluated through compression testing. A good correlation between experiments and simulations is observed and the optimized design has outperformed benchmark ones in terms of modulus and strength. We show that the extra design flexibility from high-order Bézier curves allows for a smoother transition between the beam elements which reduces the overall stress concentration profile.