Open Access

Safe, durable, and efficient storage remains a central hurdle in hydrogen economy, where metal hydrides offer a promising route, particularly for stationary applications. Among these materials, FeTi stands out as a cost-effective system capable of reversible hydrogen uptake and release under near-ambient conditions. As part of BMBF-funded collaborative project GreenH2Metals, we performed atomistic simulations aimed at elucidating experimentally observed microstructural transformations such as formation of secondary phases and hydrides. We analyzed the thermodynamic stability of competing phases using ab initio calculations and examined chemical segregation as well as heterogeneous precipitation at dislocations and planar defects. Defect phase diagrams, along with the roles of vacancies and antisite defects in bulk diffusion, are explored in detail. The impact of various tramp elements on these processes is assessed through high-throughput calculations enabled by workflow frameworks such as pyiron. Together, these computational insights support a data-driven alloy design strategy for optimizing FeTi-based materials for sustainable hydrogen storage.

Mechanical and thermodynamic properties, including the influence of crystal defects, are critical for evaluating materials in engineering applications. Molecular dynamics simulations provide valuable insight into these mechanisms at the atomic scale. However, current practice often relies on fragmented scripts with inconsistent metadata and limited provenance, which hinders reproducibility, interoperability, and reuse. FAIR data principles and workflow‐based approaches offer a path to address these limitations. We present reusable atomistic workflows that incorporate metadata annotation aligned with application ontologies, enabling automatic provenance capture and FAIR‐compliant data outputs. The workflows cover key mechanical and thermodynamic quantities, including equation of state, elastic tensors, mechanical loading, thermal properties, defect formation energies, and nanoindentation. We demonstrate validation of structure–property relations such as the Hall–Petch effect and show that the workflows can be reused across different interatomic potentials and materials within a coherent semantic framework. The approach provides artificial intelligence (AI)‐ready simulation data, supports emerging agentic AI workflows, and establishes a generalizable blueprint for knowledge‐based mechanical and thermodynamic simulations.

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.

Oxide glasses have proven to be useful across a wide range of technological applications. Nevertheless, their medium-range structure has remained elusive. Previous studies focused on ring statistics as a metric of the medium-range structure, but this metric provides an incomplete picture of the glassy structure. Here, we use atomistic simulations and state-of-the-art topological analysis tools, namely persistent homology (PH), to analyze the medium-range structure of the archetypal oxide glass (Silica) at ambient temperatures and with varying pressures. PH presents an unbiased definition of loops and voids, providing an advantage over other methods for studying the structure and topology of complex materials, such as glasses, across multiple length scales. We captured subtle topological transitions in medium-range order and cavity distributions, providing new insights into glass structure. Our work provides a robust way for extracting the void distribution of oxide glasses based on PH.

Solute segregation at low-angle grain boundaries (LAGBs) critically affects the microstructure and mechanicalproperties of magnesium (Mg) alloys. In modern alloys containing multiple substitutional elements, understanding solute-solute interactions at microstructural defects becomes essential for alloy design. This study investigates the co-segregation mechanisms of calcium (Ca), zinc (Zn), and aluminum (Al) at a LAGB in a dilute Mg-0.23Al-1.00Zn-0.38Ca (AZX010) alloy by combining atomic-scale experimental and modeling techniques.Three-dimensional atom probe tomography (3D-APT) revealed significant segregation of Ca, Zn, and Al at the LAGB, with Ca forming linear segregation patterns along dislocation arrays characteristic of the LAGB. Clustering analysis showed increased Ca–Ca pairs at the boundary, indicating synergistic solute interactions. Atomistic simulations and elastic dipole calculations demonstrated that larger Ca atoms prefer tensile regions around dislocations, while smaller Zn and Al atoms favor compressive areas. These simulations also found that Ca–Ca co-segregation near dislocation cores is energetically more favorable than other solute pairings, explaining the enhanced Ca clustering observed experimentally. Thermodynamic modeling incorporating calculated segregation energies and solute-solute interactions accurately predicted solute concentrations at the LAGB, aligning with experimental data. The findings emphasize the importance of solute interactionsat dislocation cores in Mg alloys, offering insights for improving mechanical performance through targeted alloying and grain boundary engineering.