Harvard researchers have created an electro-optic digital-to-analog converter that bridges electronic and photonic signals for efficient photonic computing and signal processing.

Indoles, which form the backbone of many bioactive compounds, are valuable in drug development but are difficult to modify at certain positions. Researchers at Chiba University have developed a cost-effective method using a copper-based catalyst to selectively attach alkyl groups to the C5 position, which has been especially challenging to target. This approach simplifies the synthesis of indole-based precursors and is expected to lead to the development of novel drug candidates in the future.  

A research team from the University of Basel, Switzerland, has developed a new molecule modeled on plant photosynthesis: under the influence of light, it stores two positive and two negative charges at the same time. The aim is to convert sunlight into carbon-neutral fuels.

Inverse lithography technology (ILT) is driving transformative innovations in semiconductor patterning processes. This paper reviews the evolution of ILT, providing an analysis of the applications in semiconductor manufacturing. In recent years, artificial intelligence (AI) has introduced breakthroughs for ILT, such as convolutional neural networks, generative adversarial networks, and model-driven deep learning, demonstrating potential in large-scale integrated circuit design and fabrication. This paper discusses future directions for ILT, which is expected to provide insights into semiconductor industry development.

The research team directed by H. Shimomoto and E. Ihara in Ehime University succeeded in preparing a new type of carbon-carbon main chain polymers, in which cyclic repeating units are densely incorporated around the carbon-based main chain. In addition, the team demonstrated the unique thermal behavior of the obtained polymers, compared to the corresponding polymers without cyclic structures. This achievement will contribute to the development of new functional polymer materials.

Researchers at UCLA and UC Riverside have demonstrated a new approach that overcomes these hurdles to solve some of the most difficult optimization problems. The team designed a system that processes information using a network of oscillators, components that move back and forth at certain frequencies, rather than representing all data digitally. This type of computer architecture, called an Ising machine, has special power for parallel computing, which makes numerous, complex calculations simultaneously. When the oscillators are in synch, the optimization problem is solved.