If you think a galaxy is big, compare it to the size of the Universe: it’s just a tiny dot which, together with a huge number of other tiny dots, forms clusters that aggregate into superclusters, which in turn weave into filaments threaded with voids—an immense 3D skeleton of our Universe.

If that gives you vertigo and you’re wondering how one can understand or even “see” something so vast, the answer is: it isn’t easy. Scientists combine the physics of the Universe with data from astronomical instruments and build theoretical models, such as EFTofLSS (Effective Field Theory of Large-Scale Structure). Fed with observations, these models describe the “cosmic web” statistically and allow its key parameters to be estimated.

Models like EFTofLSS, however, demand a lot of time and computing resources. Since the astronomical datasets at our disposal are growing exponentially, we need ways to lighten the analysis without losing precision. This is why emulators exist: they “imitate” how the models respond, but operate much faster.

Since this is a kind of “shortcut,” what’s the risk of losing accuracy? An international team including, among others, INAF (Italy), The University of Parma (Italy) and the University of Waterloo (Canada) has published in the Journal of Cosmology and Astroparticle Physics (JCAP) a study testing the emulator Effort.jl, which they designed. It shows that Effort.jl delivers essentially the same correctness as the model it imitates—sometimes even finer detail—while running in minutes on a standard laptop instead of a supercomputer.

In International Journal of Extreme Manufacturing, a research team has developed all-flexible, self-cleaning smart window that not only fine-tunes solar gain in real time but also protects itself against environmental contaminants—even on curved or 3D surfaces.  Their findings could accelerate the development of green buildings and water-resistant vehicles, addressing two of the world's most pressing challenges: rising energy demand and global carbon emissions.

In August 2017, the National Natural Science Foundation of China (NSFC) launched the Major Research Plan “Dynamic Modifications and Chemical Interventions of Biomacromolecules” (implementation period 2017–2025). Through interdisciplinary research that integrates chemistry, life sciences, medicine, mathematics, materials science, and information science, its aim is to develop specific labeling methods and detection techniques for dynamic chemical modifications of biomacromolecules, elucidate the recognition mechanisms and biological functions of dynamic modifications in the regulation of cellular traits, and discover potential drug targets and corresponding lead compounds related to dynamic biomacromolecular modifications. Since its establishment, this Major Research Plan has achieved significant progress and original results in many aspects such as the dynamic properties of biomacromolecular chemical modifications, regulatory mechanisms, and chemical interventions. Recently, members of the expert group, management group, and secretariat of the program collaborated to systematically review representative research achievements obtained since the program’s implementation, and jointly published a review article in CCS Chemistry. This review provides important references for promoting development in related frontier fields, as well as for the future trend of integration between chemistry, life sciences, and medicine.

ORNL has been selected to lead three research collaborations with fusion industry partners as part of the 2025 cohort of the Innovation Network for Fusion Energy program. The awarded projects will tap ORNL’s deep expertise in fusion materials, plasma diagnostics and advanced modeling and simulation to solve practical challenges and develop new technologies to accelerate the development of fusion energy.

A new study has found land and ocean weathering processes are linked and together they influence the amount of carbon stored or released into the atmosphere.