Open Access

Chemically complex materials (CCMats) 􀀀 including high-entropy alloys, oxides, and related multi-principal element systems 􀀀 offer a paradigm shift in materials design by leveraging chemical diversity to simultaneously optimize functional, structural, and sustainability criteria. The vastness of the compositional and structural space in CCMats propels the field into an expanding exploratory state. To reconcile functional and structural performance across this immense parameter space remains an open challenge. This Perspective evaluates the opportunities and challenges associated with harnessing chemical complexity across a broad spectrum of applications, such as hydrogen storage, ionic conductors, catalysis, magnetics, dielectrics, semiconductors, optical materials, and multifunctional structural systems. It is delineated how three central design strategies: targeted substitution (SUB), defect engineering (DEF), and diversity management (DIV) enable the reconciliation of high functional performance with long-term structural stability and environmental responsibility. Advances in computational thermodynamics, microstructure simulations, machine learning, and multimodal characterization are accelerating the exploration and optimization of CCMats, while robust data infrastructures and automated synthesis workflows are emerging as essential tools for navigating their complex compositional space. By fostering cross-disciplinary knowledge transfer and embracing data-driven design, CCMats are poised to deliver next-generation materials solutions that address urgent technological, energy, and environmental demands.

The segregation of solute atoms at grain boundaries (GBs) plays a critical role in defining the mechanical properties of materials, including corrosion resistance and fracture toughness. This study investigates the structural transformations induced by minimal boron concentrations at Σ13 GBs in ferrite thin films synthesized. Two sample protocols were examined: one with carbon as the sole solute and the other with carbon and boron co-segregation. To understand the thermodynamics of such phases, we employed ab initio calculations to meticulously examine the competing Σ13 GB phases that coexist in the presence of defects and stacking faults. Building on our findings regarding these competing GB phases, we analyzed the energetic aspects of solute segregation at the GB interface. Furthermore, we constructed a defect phase diagram to gain insights into the influence of Boron concentration on the evolution of GB structure. We reveal that boron segregation transforms the GB structure from flat to zigzag trigonal prisms by forming new chemical bonds, ultimately enhancing bonding strength between boron and iron atoms by 5%. This transformation doubles steel's resistance to fracture and provides valuable insights into the thermodynamic and energetic aspects of solute-driven GB phase evolution. These findings contribute to developing innovative strategies for designing high-performance steel with enhanced mechanical integrity and durability.

Ni-Mn-Ga shape-memory alloys are promising candidates for large strain actuation and magnetocaloric cooling devices. In view of potential small-scale applications, we probe here nanomechanically the stress-induced austenite–martensite transition in single crystalline austenitic thin films as a function of temperature. In 0.5 μm thin films, a marked incipient phase transformation to martensite is observed during nanoindentation, leaving behind pockets of residual martensite after unloading. These nanomechanical instabilities occur irrespective of deformation rate and temperature, are Weibull distributed, and reveal large spatial variations in transformation stress. In contrast, at a larger film thickness of 2 μm fully reversible transformations occur, and mechanical loading remains entirely smooth. Ab-initio simulations demonstrate how an in-plane constraint can considerably increase the martensitic transformation stress, explaining the thickness-dependent nanomechanical behavior. These findings for a shape-memory Heusler alloy give insights into how reduced dimensions and constraints can lead to unexpectedly large transformation stresses that need to be considered in small-scale actuation design.

The signal intensities of linear and star‐shaped poly(L‐lactides) (PLA) and poly (ethylene oxides) (PEO) were compared to determine the influence of the number of arms on the ionization in matrix‐assisted laser desorption/ionization time‐of‐flight (MALDI‐TOF) mass spectrometry. In this study, a variety of blends were prepared and investigated, including binary and ternary combinations of linear and star‐shaped polymers with similar molecular masses. The focus was on examining their intensity ratios. In equimolar binary PLA blends, polymer stars were observed to exhibit higher intensities than their linear counterparts. This result was supported by experiments with equimolar ternary PLA blends, which clearly demonstrated an intensity dependence on the number of polymer arms. It was observed that four‐arm PLA exhibited higher intensities than three‐arm PLA. A similar trend was observed in investigations involving acetylated polymer end groups, suggesting that differences in ionization are primarily influenced by polymer architecture rather than end groups. In order to validate this assumption, the binding energies for [polymer‐K] + adduct ions utilizing the most stable geometry obtained from GOAT (Global Optimizer Algorithm) were calculated, revealing that star‐shaped lower mass oligomers have slightly higher binding energies.