Applied physicists at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have created a photon router that could plug into quantum networks to create robust optical interfaces for noise-sensitive microwave quantum computers.

A novel study has unveiled a transformative advancement in perovskite solar cells through bilayer interface engineering. This innovative method integrates 2D/3D perovskites with a dipole layer, achieving a remarkable leap in power conversion efficiency and overcoming critical challenges of scalability and stability in large-area solar modules.

Scientists have achieved a significant leap in aqueous Mg-ion battery technology by engineering a breakthrough cathode material (nickel oxide hydroxide (NiOOH)), and systematacially reveal the stable Mg-storage mechanism in NiOOH nanosheets. This innovative design significantly enhances aqueous Mg-ion battery performance, resolving long-standing challenges of balancing high voltage and high capacity. The achievement paves the way for a safer, more versatile energy storage solution, poised to meet the growing demands of next-generation devices.

Scientists have developed ultralight and ultrathin copper current collectors that could redefine lithium battery technology. These collectors, far lighter than traditional copper foils, significantly enhance cell-level energy density. This leap forward in efficiency and weight reduction is poised to transform the performance of portable electronics and electric vehicles, where lightweight, high-capacity batteries are crucial for progress.

An AI model trained on large amounts of genetic data can predict whether bacteria will become antibiotic-resistant. The new study shows that antibiotic resistance is more easily transmitted between genetically similar bacteria and mainly occurs in wastewater treatment plants and inside the human body.

"By understanding how resistance in bacteria arises, we can better combat its spread. This is crucial to protect public health and the healthcare system's ability to treat infections," says Erik Kristiansson, Professor at the Department of Mathematical Sciences at Chalmers University of Technology and the University of Gothenburg in Sweden.

Travel demand prediction is a crucial component in the formulation of transportation planning, urban planning, regional development planning, and serves as a key basis for the investment and construction of transportation infrastructure. Current prediction technologies generally lack systemic consideration, neglecting the interactions between transportation and elements such as population, land use, and housing, making it difficult to meet the increasingly complex analytical needs of urban planning and decision-making. To address this challenge, a research team from College of Urban and Environmental Sciences, Peking University and School of Urban Planning and Design, Peking University Shenzhen Graduate School has proposed an integrated land-population-housing-transportation simulation technology framework, developing an urban system-based travel demand simulation and prediction technology. Journal of Geo-Information Science has published the study's achievement.