Researchers from The University of Osaka used large-scale simulations and turbulence theory to study how dolphins swim so effectively. The team found that large vortices created by the dolphin’s tail provide most of the propulsion, while smaller vortices contribute little. This discovery improves our mechanical understanding of fast swimming and could guide the design of energy-efficient underwater robots and technologies for controlling turbulence.

POSTECH and UNIST Researchers Develop an Optimization Framework for High-Efficiency Thermoelectric Generators.

The Society for Industrial and Applied Mathematics has named Illinois Tech Professor of Applied Mathematics Fred Hickernell as a member of the 2026 class of SIAM fellows in recognition of his outstanding research and service to the community. Hickernell’s research group at Illinois Tech has been developing software libraries that gives researchers access to cutting-edge computational methods to solve their finance, engineering, and scientific problems. These efforts have conveniently consolidated software that promotes important theory that supports novel computational methods that help solve high-dimensional integration and function approximation problems, or problems with large amounts of variables and need a more even distribution of data points and estimations. 

Interpreting Fermi surface data requires specialized expertise and is vulnerable to noise, creating a bottleneck in materials research. Researchers now demonstrate a machine learning approach that can analyze simulated Fermi surface images of the alloy Co₂MnGa_xGe_1-x and automatically identify compositions where the Fermi surface morphology changes, even in blurred or noisy data. The method reduces the need for manual screening and could accelerate the discovery of advanced electronic materials.