Mattia Utzeri

The assessment of ductile damage at high strain rates poses challenges both at an experimental and numerical modelling levels. Indeed, testing requires special facilities, such as the split‐Hopkinson bar (SHB), through which it is not trivial to reproduce the multiaxial stress states that are mandatory for a robust material characterisation and tuning of numerical damage models. The paper proposes the use of a minimal but effective set of cylindrical, notched and shear‐tension specimens which can be tested using a conventional SHB only to investigate material strains to fracture at different (low) triaxialities and Lode angles. The materials investigated are a 17‐4PH steel and a Ti6Al4V titanium alloy. Experimental ultimate fracture strains corresponding to the different stress states are shown, along with the results of damage model calibration. It is proved that the approach can lead to an accurate dynamic characterisation, and that two widely used damage models can provide effective predictions even when high strain rates are involved. Finally, a comparison between dynamic and quasi‐static ductile fracture behaviour for the two materials is presented and discussed.

Next‐generation protective systems require adaptive materials capable of reconfiguring their response to impact type and severity, thereby offering multiple force–displacement pathways. Here, the study introduces twisting metamaterials, a subclass of architected lattices whose mechanics are captured by micropolar elasticity. Derived from twisting operations on primitive lattices, these structures exhibit geometry‐induced torsional actuation and nonlinear responses, enabling adaptive crashworthiness. A multiscale predictive framework—combining Cosserat continuum mechanics, finite element modeling, and experiments—demonstrates its viability. Twisting sheet‐based gyroid structures (10% relative density) are additively manufactured in FE7131 steel and tested under quasi‐static and dynamic compression with varied torsional constraints, revealing adaptive energy absorption. When rotation is constrained, the structures achieve high axial stiffness (4.8 GPa), collapse stress (21 MPa), and specific energy absorption (15.36 J g ⁻¹ ), while free‐to‐twist and over‐rotation conditions reduce these values by up to 25%, 24%, and 33%, respectively. A macroscale model captures both axial and torsional responses, while SEM and µCT analyses of process‐induced defects inform a parametric finite element study extended to 5% and 15% relative densities. Mapping their performance onto an Ashby chart highlights twisting metamaterials as a promising class of mechanically adaptive, crashworthy materials for advanced protection systems in automotive, rail, aerospace, and defence applications.

The CuCrZr alloy has garnered significant interest as a promising material for additive manufacturing, particularly in applications requiring high strain rate performance. Such applications include vertical targets like heat sinks in the ITER divertor and actively cooled plasma‐facing components, where these alloys serve as structural materials. Although the dynamic behaviour of additively manufactured materials is an expanding area of study, the high strain rate properties of CuCrZr remain not exhaustive and require further investigation. This study presents the results of quasi‐static and dynamic tension–compression tests conducted at various strain rates on CuCrZr alloy specimens in their as‐built condition. The alloy was fabricated using laser powder bed fusion (L‐PBF) with selective laser melting (SLM) technology. Compression samples were designed with standard cylindrical shapes, whereas tensile sample geometry was tailored to meet dynamic testing requirements. The study involves the calibration of an improved Johnson–Cook constitutive model through inverse analytical and numerical procedures. Dynamic increase factors (DIFs) were also evaluated using phenomenological and physical model parameters. The findings indicate that CuCrZr alloy exhibits strain rate sensitivity, which activates above a certain threshold. This was confirmed by a reconstructed dynamic fracture locus, which was consistently higher than the quasi‐static locus across all stress triaxiality values.

Topology-engineered PEEK/MWCNT lattices show programmable piezoresistivity, auxeticity and failure modes. An experimentally informed model predicts performance across the design space for smart structural applications.

Integrating autonomous sensing materials into future applications necessitates developing advanced multiscale multiphysics predictive models. This study introduces an experimentally informed predictive framework for autonomous sensing architected materials, combining theoretical and computational methodologies. By incorporating stress‐dependent electrical resistivity through anisotropic piezoresistive constitutive effects, alongside considering material, geometric, and contact nonlinearities, the proposed multiscale model captures the architecture‐dependent piezoresistive responses of lattice composites produced via additive manufacturing of polyetherimide (PEI)/carbon nanotube (CNT) nanoengineered feedstock. The PEI/CNT composite exhibits exceptional strength (105 MPa), stiffness (3368 MPa), and strain sensitivity (gauge factor ≈13), translating into remarkable piezoresistive characteristics for the PEI/CNT lattice composites, surpassing existing works (gauge factor ≈3 to 11). This multiscale finite element model accurately predicts both macroscopic piezoresistive responses and the influence of architectural and topological variations on electric current paths, validated via infrared thermography analysis. Additionally, an Ashby chart for the gauge factor of PEI/CNT lattice composites suggests their prediction through a scaling law similar to mechanical properties, underscoring the tunable strain and damage sensitivity of these materials. The combined experimental, theoretical, and numerical findings offer critical insights into optimizing piezoresistive composites through architected design, with profound implications for smart orthopedics, structural health monitoring, sensors, batteries, and other multifunctional applications.

Additive Manufacturing (AM) empowers the creation of high‐performance cellular materials, underscoring the increasing need for programmable and predictable energy absorption capabilities. This study evaluates the impact of a precisely tuned fused filament fabrication (FFF) process on the energy absorption and failure characteristics of 2D‐thermoplastic lattice materials through multiscale experiments and predictive modeling. Macroscale in‐plane compression testing of both thick‐ and thin‐walled lattices, along with their µ‐CT imaging, reveal relative density‐dependent damage mechanisms and failure modes, prompting the development of a robust predictive modeling framework to capture process‐induced performance variation and damage. For lower relative density lattices, an FE model based on the extended Drucker–Prager material model, incorporating Bridgman's correction with crazing failure criteria, accurately captures the crushing response. As lattice density increases, interfacial damage along bead‐bead interfaces becomes predominant, necessitating the enrichment of the model with a microscale cohesive zone model to capture interfacial debonding. The predictive modeling introduces an enhancement factor, offering a straightforward method to assess the impact of the AM process on energy absorption performance, thereby facilitating the inverse design of FFF‐printed lattices. This approach provides a critical evaluation of how FFF processes can be optimized to achieve the highest attainable performance and mitigate failures in architected materials.