Researchers from the Tata Institute of Fundamental Research Hyderabad (TIFRH), Roni Chatterjee and Monoj Adhikari from the group of Prof. Smarajit Karmakar, have uncovered how the intrinsic fragility of glassy materials determines whether they fail in a brittle or ductile manner. Their findings, published in Nature Communications, provide new insight into the mechanical behavior of glasses.

Glassy materials, including window glass, metallic glasses, polymers, foams, and gels, can either deform smoothly under stress (ductility) or fracture suddenly (brittleness). While fragility has traditionally been used to describe how rapidly a liquid slows down as it approaches the glassy state during cooling, this study demonstrates that it also governs how the resulting glass responds to mechanical loading.

Using large-scale computer simulations, the researchers prepared different glassy materials over a wide range of temperatures and subjected them to repeated cyclic deformation. By analyzing stress-strain curves, they measured the yield strain—the maximum deformation a material can withstand before failure—and the associated stress drop, which indicates the degree of brittleness.

The study reveals that in fragile glasses, energy barriers grow rapidly during cooling. Consequently, larger strain is required to initiate yielding, leading to higher yield strain, larger stress accumulation, and a sharp stress drop characteristic of brittle failure. In contrast, strong glasses exhibit a gradual increase in energy barriers with cooling, resulting in only a slight change in yield strain and a much smaller stress drop, indicative of ductile behavior.

By linking mechanical yielding directly to the evolution of energy barriers, the work establishes fragility as a fundamental factor controlling whether a glass breaks abruptly or deforms gradually. These findings provide a deeper understanding of the mechanical properties of amorphous materials and could guide the design of safer and more reliable glasses for structural, industrial, and technological applications.

A research team at The Hong Kong Polytechnic University (PolyU) has successfully developed Hong Kong’s first “AI Agent for Precision Diabetes Management – PIPE-AI” (AI Agent), designed specifically for Asian populations, together with a related disease risk prediction model. Leveraging artificial intelligence (AI) and large-scale local electronic health data, the system can more accurately predict the risk of deterioration of complications such as chronic kidney disease in patients with type 2 diabetes over the next 10 years, enabling healthcare professionals and patients to intervene early and improve disease management. The research findings have been published in the leading international journal npj Digital Medicine.

A study conducted by the INCLIVA Health Research Institute, the Clinical University Hospital of València, the University of Valencia (UV), the Universitat Politècnica de València (UPV), the Cardiac Imaging Unit of Ascires Biomédico Group, and the Ascires-UPV Joint Research Unit provides significant evidence in the field of advanced cardiac imaging and clinical cardiology. It shows that the damage resulting from a myocardial infarction is not confined solely to the affected area, but may also functionally extend to remote regions of the ventricle. Identifying this dysfunction could have important implications, including improved prognostic assessment of patients, earlier detection of cardiac deterioration before symptoms or more evident changes appear, and the implementation of earlier and more personalised therapeutic strategies.